Program description

Content

Core Qualification

Module M0523: Business & Management

Module Responsible Prof. Matthias Meyer
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students are able to find their way around selected special areas of management within the scope of business management.
  • Students are able to explain basic theories, categories, and models in selected special areas of business management.
  • Students are able to interrelate technical and management knowledge.


Skills
  • Students are able to apply basic methods in selected areas of business management.
  • Students are able to explain and give reasons for decision proposals on practical issues in areas of business management.


Personal Competence
Social Competence
  • Students are able to communicate in small interdisciplinary groups and to jointly develop solutions for complex problems

Autonomy
  • Students are capable of acquiring necessary knowledge independently by means of research and preparation of material.


Workload in Hours Depends on choice of courses
Credit points 6
Course L1486: Business Model Generation & Green Technologies
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 0
Lecturer Prof. Michael Prange
Language EN
Cycle WiSe
Content
  • Overview about Green Technologies
  • Introduction to Business Model Generation
  • Business model patterns
  • Design techniques for business ideas
  • Strategy development
  • Value proposition architecture
  • Business plan and financing
  • Component‐based foundations
  • Lean Entrepreneurship


Based on examples and case studies primarily in the field of green technologies, students learn the basics of
Business Model Generation and will be able to develop business models and to evaluate start‐up projects.

Literature

Präsentationsfolien, Beispiele und Fallstudien aus der Vorlesung

Presentation slides, examples and case studies from the lecture

Course L1487: Corporate Entrepreneurship & Green Innovation
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale
Lecturer Prof. Michael Prange
Language EN
Cycle WiSe
Content
  • Overview about Green Innovation
  • Introduction to Corporate Entrepreneurship
  • Entrepreneurial thinking in established companies
  • Entrepreneurs and managers
  • Strategic innovation processes
  • Corporate Venturing
  • Product Service Systems
  • Open Innovation
  • User Innovation


Based on examples and case studies primarily in the field of green innovation, students learn the basics of
corporate entrepreneurship and will be able to implement entrepreneurial thinking in established companies and
to describe strategic innovation processes.

Literature

Präsentationsfolien, Beispiele und Fallstudien aus der Vorlesung

Presentation slides, examples and case studies from the lecture

Course L1280: Creation of Business Opportunities
Typ Project-/problem-based Learning
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Examination Form Referat
Examination duration and scale 30 Minuten
Lecturer Prof. Christoph Ihl
Language EN
Cycle SoSe
Content

Important note: This course is part of an 6 ECTS module consisting of two courses "Entrepreneurship” & “Creation of Business Opportunities”, which have to be taken together in one semester.

Startups are temporary, team-based organizations, which can form both within and outside of established companies, to pursue one central objective: taking a new venture idea to market by designing a business model that can be scaled to a full-grown company. In this course, students will form startup teams around self-selected ideas and run through the process just like real startups would do in the first three months of intensive work. Startup Engineering takes an incremental and iterative approach, in that it favors variety and alternatives over one detailed, linear five-year business plan to reach steady state operations. From a problem solving and systems thinking perspective, student teams create different possible versions of a new venture and alternative hypotheses about value creation for customers and value capture vis-à-vis competitors. We will draw on recent scientific findings about international success factors of new venture design. To test critical hypotheses early on, student teams engage in scientific, evidence-based, experimental trial-and-error learning process that measures real progress.
Upon completion of this course, students will be able to:
· Apply a modern innovation toolkit relevant in both the corporate & startup world
· Analyze given business opportunities in terms of its constituent elements
· Design new business models by gathering and combining relevant ideas, facts and information 
· Evaluate business opportunities and derive judgment about next steps & decisions
Course language is English, but participants can decide to give their graded presentations in German. Students are invited to apply to this course module already with a startup idea and/ or team, but this is not a requirement! We will form teams and ideas in the beginning of the course. Class meetings have alternate intervals of lecture inputs, teamwork, mentoring, and peer feedback. Attendance is mandatory for at least 80% of class time due to large proportion of teamwork sessions.
Student teams give three presentations and submit them with backup analyses. Grading scheme:
· Startup discovery presentation after 5 weeks: 30%
· Startup validation presentation after 10 weeks: 30%
· Final startup pitches after 13 weeks: 40%


Literature

• Blank, S. & Dorf, B. (2012). The startup owner's manual.
• Gans, J. & Stern, S. (2016). Entrepreneurial Strategy.
• Osterwalder, A. & Yves, P. (2010). Business model generation.
• Maurya, A. (2012). Running lean: Iterate from plan A to a plan that works.
• Maurya, A. (2016). Scaling lean: Mastering the Key Metrics for Startup Growth.
• Wilcox, J. (2016). FOCUS Framework: How to Find Product-Market Fit.

Course L2348: Drivers of success for projects
Typ Project-/problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Schriftliche Ausarbeitung
Examination duration and scale 0
Lecturer Lucia Pohl
Language DE
Cycle WiSe/SoSe
Content
Literature
Course L1384: Intellectual Property
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale
Lecturer Janna Thomsen, Cathérine Elkemann
Language DE
Cycle WiSe
Content
  • Trademark law
  • Copyright
  • Patent law
  • Know-how, supplementary performance protection, et al.
  • Enforcement of intellectual property rights
  • Licensing of intellectual property rights
  • Hypothecation, security assignment and evaluation of intellectual property rights


Literature

Quellen und Materialen wird im Internet zur Verfügung gestellt

Course L2347: Human resource management for engineers
Typ Project-/problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Schriftliche Ausarbeitung
Examination duration and scale 0
Lecturer Helge Kochskämper
Language DE
Cycle WiSe
Content
Literature
Course L1711: Innovation Debates
Typ Project-/problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Fachtheoretisch-fachpraktische Arbeit
Examination duration and scale 3 Präsentationen der schriftlichen Ausarbeitung à 20 Minutes
Lecturer Prof. Daniel Heiner Ehls
Language EN
Cycle WiSe
Content

Scientific knowledge grows continuously but also experiences certain alignments over time. For example, early cultures had the believe of a flat earth while latest research has a spherical earth model. Also in social science and business management, from time to time certain concepts that have even been the predominant paradigm are challenged by new observations and models. Consequently, certain controversies emerge and build the base for advancing theory and managerial practice. With this lecture, we put ourselves in the middle of heated debates for informed academics and practitioners of the day after tomorrow.

The lecture targets several controversies in the domain of technology strategy and innovation management. By the classical academic method and the novel problem based learning format of a structured discussion, a given controversy is scrutinized. On selected topics, students will discuss a dispute and gain a thorough understanding. Specifically, based on a brief introduction of a motion, a affirmative constructive as well as a negative constructive is presented by two different student groups. Each presentation is followed by a response of the other group and questions from the class. Topics range from latest theories and concepts for value capture, to the importance of operating within a global marketplace, to cutting edge approaches for innovation stimulation and technology management. Consequently, this lecture deepens the knowledge in technology strategy and innovation management (TIM), enables a critical thinking and thought leadership.

Literature

1.       Course notes and materials provided before the lecture

2.       Leiblein/ Ziedonis (2011): Technology Strategy and innovation management. Edward Elgar Publishing Ltd (optional)

Course L0940: Innovation Management
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale
Lecturer Prof. Cornelius Herstatt
Language DE/EN
Cycle SoSe
Content Innovation is key to corporate growth and sustainibility. In this lecture Prof. Herstatt presents a systematic way from generating ideas to the successful implementation of innovations. The lecture is presented in German language only
Literature
  • Goffin, K., Herstatt, C. and Mitchell, R. (2009): Innovationsmanagement: Strategie und effektive Umsetzung von Innovationsprozessen mit dem Pentathlon-Prinzip, München: Finanzbuch Verlag

    Weiterführende Literatur
  • Innovationsmanagement
    Juergen Hauschildt
  • F + E Management
    Specht, G. / Beckmann, Chr.
  • Management der frühen Innovationsphasen
    Cornelius Herstatt, Birgit Verworn
    (im TUHH-Intranet auch als E-Book verfügbar)
  • Bringing Technology and Innovation Into the Boardroom
  • weitere Literaturempfehlungen auf Anfrage
Course L0161: Internationalization Strategies
Typ Project-/problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 20-30 Minuten Referat einschl. Diskussionsleitung plus schriftliche Ausarbeitung (ca. 10 Seiten)
Lecturer Prof. Thomas Wrona
Language EN
Cycle SoSe
Content
  • Introduction
  • Internationalization of markets
  • Measuring internationalization of firms
  • Target market strategies
  • Market entry strategies
  • Timing strategies
  • Allocation strategies
  • Working in small teams on close-to-reality problems based on presented theories
  • Paper writing on developed solution to the given problem/project e.g. market attractiveness analysis; development of market entry strategy for a hypothetical product in a given region
Literature
  • Bartlett/Ghoshal (2002): Managing Across Borders, The Transnational Solution, 2nd edition, Boston
  • Buckley, P.J./Ghauri, P.N. (1998), The Internationalization of the Firm, 2nd edition
  • Czinkota, Ronkainen, Moffett, Marinova, Marinov (2009), International Business, Hoboken
  • Dunning, J.H. (1993), The Globalization of Business: The Challenge of the 1990s, London
  • Ghoshal, S. (1987), Global Strategy: An Organizing Framework, Strategic Management Journal, p. 425-440
  • Praveen Parboteeah, K.,Cullen, J.B. (2011) , Strategic International Management, International 5th Edition
  • Rugman, A.M./Collinson, S. (2012): International Business, 6th Edition, Essex 2012
Course L2350: Leadership
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale 60 min
Lecturer Dr. Thomas Kosin
Language DE
Cycle WiSe
Content
Literature
Course L1231: Management and Leadership
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale 60 Minuten
Lecturer Prof. Christian Ringle
Language DE
Cycle SoSe
Content
  • definitions and foundations of strategic management
  • strategic planning
  • strategic analysis and forecast
  • development of strategic options
  • strategy evaluaton, implementation and strategic control
Literature

- Bea, F.X.; Haas, J.: Strategisches Management, 5. Auflage, Stuttgart 2009.
- Dess, G. G.; Lumpkin, G. T.; Eisner, A. B.: Strategic management: Creating competitive advantages, Boston 2010
- Hahn, D.; Taylor, B.: Strategische Unternehmensplanung: Strategische Unternehmensführung, 9. Auflage, Heidelberg 2006.
- Hinterhuber, H.H.: Strategische Unternehmensführung Bd. 1: Strategisches Denken, 7. Aufl., Berlin u. a. 2004
- Hinterhuber, H.H.: Strategische Unternehmensführung Bd. 2: Strategisches Handeln, 7. Aufl., Berlin u. a. 2004
- Hungenberg, H.: Strategisches Management in Unternehmen, 6. Auflage, Wiesbaden 2011
- Johnson, G.; Scholes, K.; Whittington, R.: Strategisches Management. Eine Einführung, 9. Auflage, München 2011
- Macharzina, K.: Unternehmensführung: Das internationale Managementwissen, 7. Auflage, Wiesbaden 2010.
- Porter, M.E.: Competitive strategy, New York 1980 (deutsche Ausgabe: Wettbewerbsstrategie, 10. Aufl., Frankfurt am Main 1999)
- Welge, M. K.; Al-Laham, A.: Strategisches Management, 5. Auflage, Wiesbaden 2008.

Course L1857: Entrepreneurial Management
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 20 Minuten inklusive 15 Seiten Ausarbeitung
Lecturer Prof. Christoph Ihl
Language EN
Cycle WiSe
Content

Important note: This course is part of an 6 ECTS module consisting of the three courses "Startup Engineering", "Startup Engineering Project" and "Entrepreneurship Management", which have to be taken together in one semester.

Startups are temporary, team-based organizations, which can form both within and outside of established companies, to pursue one central objective: taking a new venture idea to market by designing a business model that can be scaled to a full-grown company. In this course, students will form startup teams around self-selected ideas and run through the process just like real startups would do in the first three months of intensive work. Startup Engineering takes an incremental and iterative approach, in that it favors variety and alternatives over one detailed, linear five-year business plan to reach steady state operations. From a problem solving and systems thinking perspective, student teams create different possible versions of a new venture and alternative hypotheses about value creation for customers and value capture vis-à-vis competitors. To test critical hypotheses early on, student teams engage in an evidence-based, experimental trial-and-error learning process that measures real progress.
Upon completion of this course, students will be able to:
· Apply a modern innovation toolkit relevant in both the corporate & startup world
· Analyze given business opportunities in terms of its constituent elements
· Design new business models by gathering and combining relevant ideas, facts and information 
· Evaluate business opportunities and derive judgment about next steps & decisions
Course language is English, but participants can decide to give their graded presentations in German. Students are invited to apply to this course module already with a startup idea and/ or team, but this is not a requirement! We will form teams and ideas in the beginning of the course. Class meetings have alternate intervals of lecture inputs, teamwork, mentoring, and peer feedback. Attendance is mandatory for at least 80% of class time due to large proportion of teamwork sessions.
Student teams give three presentations and submit them with backup analyses. Grading scheme:
· Startup discovery presentation after 5 weeks: 30%
· Startup validation presentation after 10 weeks: 30%
· Final startup pitches after 13 weeks: 40%



Literature

• Blank, S. & Dorf, B. (2012). The startup owner's manual.
• Gans, J. & Stern, S. (2016). Entrepreneurial Strategy.
• Osterwalder, A. & Yves, P. (2010). Business model generation.
• Maurya, A. (2012). Running lean: Iterate from plan A to a plan that works.
• Maurya, A. (2016). Scaling lean: Mastering the Key Metrics for Startup Growth.
• Wilcox, J. (2016). FOCUS Framework: How to Find Product-Market Fit.

Course L0863: Marketing
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale
Lecturer Prof. Christian Lüthje
Language EN
Cycle WiSe
Content

Contents

Basics of Marketing

The philosophy and fundamental aims of marketing. Contrasting different marketing fields (e.g. business-to-consumer versus business-to-business marketing). The process of marketing planning, implementation and controlling

Strategic Marketing Planning

How to find profit opportunities? How to develop cooperation, internationalization, timing, differentiation and cost leadership  strategies?

Market-oriented Design of products and services

How can companies get valuable customer input on product design and development? What is a service? How can companies design innovative services supporting the products?

Pricing

What are the underlying determinants of pricing decision? Which pricing strategies should companies choose over the life cycle of products? What are special forms of pricing on business-to-business markets (e.g. competitive bidding, auctions)?

Marketing Communication

What is the role of communication and advertising in business-to-business markets? Why advertise? How can companies manage communication over advertisement, exhibitions and public relations?

Sales and Distribution

How to build customer relationship? What are the major requirements of industrial selling? What is a distribution channel? How to design and manage a channel strategy on business-to-business markets?


Knowledge

Students will gain an introduction and good overview of

  • Specific challenges in the marketing of innovative goods and services
  • Key strategic areas in strategic marketing planning (cooperation, internationalization, timing)
  • Tools for information gathering about future customer needs and requirements
  • Fundamental pricing theories and pricing methods
  • Main communication instruments
  • Marketing channels and main organizational issues in sales management
  • Basic approaches for managing customer relationship

Skills

Based on the acquired knowledge students will be able to:

  • Design market timing decisions
  • Make decisions for marketing-related cooperation and internationalization activities
  • Manage the challenges of market-oriented development of new products and services
  • Translate customer needs into concepts, prototypes and marketable offers
  • Determine the perceived quality of an existing product or service using advanced elicitation and measurement techniques that fit the given situation
  • Analyze the pricing alternatives for products and services
  • Make strategic sales decisions for products and services (i.e. selection of sales channels)
  • Analyze the value of customers and apply customer relationship management tools

Social Competence

The students will be able to

  • have fruitful discussions and exchange arguments
  • present results in a clear and concise way
  • carry out respectful team work

Self-reliance

The students will be able to

  • Acquire knowledge independently in the specific context and to map this knowledge on other new complex problem fields.
  • Consider proposed business actions in the field of marketing and reflect on them.



Literature

Homburg, C., Kuester, S., Krohmer, H. (2009). Marketing Management, McGraw-Hill Education, Berkshire, extracts p. 31-32, p. 38-53, 406-414, 427-431

Bingham, F. G., Gomes, R., Knowles, P. A. (2005). Business Marketing, McGraw-Hill Higher Education, 3rd edition, 2004,  p. 106-110

Besanke, D., Dranove, D., Shanley, M., Schaefer, S. (2007), Economics of strategy, Wiley, 3rd edition, 2007, p. 149-155

Hutt, M. D., Speh, T.W. (2010), Business Marketing Management, 10th edition, South Western, Lengage Learning, p. 112-116


Course L2440: Mergers & Acquistions (M&A)
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale 60 min
Lecturer Prof. Philipp Haberstock
Language DE
Cycle SoSe
Content
Literature
Course L0709: Project Management
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale
Lecturer Prof. Carlos Jahn
Language EN
Cycle WiSe
Content

The lecture “project management” aims at characterizing typical phases of projects. Important contents are: possible tasks, organization, techniques and tools for initiation, definition, planning, management and finalization of projects. This will also be deepened by exercises within the framework of the event.

The following topics will be covered in the lecture:

  • SMART, Work Breakdown Structure, Operationalization, Goals relation matrix
  • Metra-Potential Method (MPM), Critical-Path Method (CPM), Program evaluation and review technique (PERT)
  • Milestone Analysis, Earned Value Analyis (EVA)
  • Progress reporting, Tracing of project goals, deadlines and costs, Project Management Control Loop, Maturity Level Assurance (MLA)
  • Risk Management, Failure Mode and Effects Analysis (FMEA), Risk Matrix

Literature

Project Management Institute (2017): A Guide to the Project Management Body of Knowledge (PMBOK® Guide) 6. Aufl. Newtown Square, PA, USA: Project Management Institute.

DeMarco, Tom (1997). The Deadline: A Novel About Project Management.

DIN Deutsches Institut für Normung e.V. (2009). Projektmanagement - Projektmanagementsysteme - Teil 5: Begriffe. (DIN 69901-5)

Frigenti, Enzo and Comninos, Dennis (2002). The Practice of Project Management.

Haberfellner, Reinhard (2015). Systems Engineering: Grundlagen und Anwendung

Harrison, Frederick and Lock, Dennis (2004). Advanced Project Management: A Structured Approach.

Heyworth, Frank (2002). A Guide to Project Management.

ISO - International Organization for Standardization (2012). Guidance on Project Management. (21500:2012(E))

Kerzner, Harold (2013). Project Management: A Systems Approach to Planning, Scheduling, and Controlling.

Lock, Dennis (2018). Project Management.

Martinelli, Russ J. and Miloševic, Dragan (2016). Project Management Toolbox: Tools and Techniques for the Practicing Project Manager.

Murch, Richard (2011). Project Management: Best Practices for IT Professionals.

Patzak, Gerold and Rattay, Günter (2009). Projektmanagement: Leitfaden zum Management von Projekten, Projektportfolios, Programmen und projektorientierten Unternehmen.

Course L1385: Project Management in Industrial Practice
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale
Lecturer Dipl.-Ing. Wilhelm Radomsky
Language DE
Cycle WiSe
Content
  • Project management in a company
  • Project life cycle / Project environment
  • Project structuring / Project planning
  • Deployment of methods / Team development
  • Contract / Risk / Change management
  • Multi-project management / Quality management
  • Project controlling / Reporting
  • Project organization / Project conclusion


Literature

• Brown (1998): Erfolgreiches Projektmanagement in 7 Tagen

• Burghardt (2002): Einführung in Projektmanagement

• Cleland / King (1997): Project Management Handbook

• Hemmrich, Harrant (2002): Projektmanagement, In 7 Schritten zum Erfolg

• Kerzner (2003): Projektmanagement

• Litke (2004): Projektmanagement

• Madauss (2005): Handbuch Projektmanagement

• Patzak / Rattay (2004): Projektmanagement

• PMI (2004): A Guide to the Project Management Body of Knowledge

• RKW / GPM: Projektmanagement Fachmann

• Schelle / Ottmann / Pfeiffer (2005): ProjektManager

Course L1897: Project Management and Agile Methods
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Fachtheoretisch-fachpraktische Arbeit
Examination duration and scale Ausarbeitung eines Projektplans in Kleingruppen (ca. 5-10 Seiten)
Lecturer Christian Bussler
Language DE
Cycle SoSe
Content

The Seminar teaches the basics of project management, which constitutes the foundations for technical as well as for business projects. It also includes a sideline about process management. The participants will work on the following questions:

  • What is a project and what challenges does it imply?
  • What methods have been developed to meet those challenges?
  • How have this methods evolved over time? What is “state of the art” today?
  • What basic skills should project members have?
  • What is the difference between project and process? How can the latter be analyzed?

The approaches are not just taught theoretically, but put to use in group work. Through this approach, participants are enabled to work successfully on actual projects - and manage projects later on. As project work is increasingly important in work life, project management is a key skill for job applicants.

Main topics of the seminar include:

  • The “magic triangle” of project objectives
  • Typical project phases
  • Key instruments and methods (project structure plan, RACI, Gantt chart)
  • Project organization and steering
  • Team communication and collaboration
  • The agile approach of Scrum
  • Process levels and cascading
  • Process improvement

With the knowledge and experience from the seminar, participants should be able to acquire a basic certificate in project management with relatively little additional effort. The certification is available through institutions like GPM.

Participants already start working on their homework paper in the group work. It comprises 5 to 10 pages and a structure plan for the chosen project, which can be done in Excel for example. Ideally, the members of the work groups write their homework paper together. The expected scale of the paper would increase in this case, yet not proportionally with the number of group members (4 participants would be expected to hand in a paper of 15-20 pages).

Literature

Hans-D. Litke, Ilonka Kunow; Projektmanagement. 3. Auflage 2015

Georg Patzak, Günter Rattay; Projektmanagement: Projekte, Projektpotfolios, Programme und projektorientierte Unternehmen. 6. Auflage 2014

GPM Deutsche Gesellschaft für Projektmanagement; Kompetenzbasiertes Projektmanagement (PM3): Handbuch für die Projektarbeit, Qualifizierung und Zertifizierung auf Basis der IPMA Competence Baseline Version 3.0. 6. Auflage, 2014

Tom DeMarco; Der Termin: Ein Roman über Projektmanagement. 2007

Jeff Sutherland, Ken Schwaber; Der Scrum Guide. Der gültige Leitfaden für Scrum: Die Spielregeln. Ständig aktualisiert, kostenloser Download auf http://www.scrumguides.org/

Jurgen Appello; Management 3.0: Leading Agile Developers, Developing Agile Leaders. 2010

Course L2349: Accounting and Financial Statements
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale 60 min
Lecturer Prof. Matthias Meyer
Language DE
Cycle WiSe/SoSe
Content
Literature
Course L1293: Risk Management
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale 60 Minuten
Lecturer Dr. Meike Schröder
Language DE
Cycle WiSe
Content

Risks are inherent in every aspect of business, and the ability of managing risks is one important aspect that differentiates successful business leaders from others. There exist various categories of risk, such as credit, country, market, liquidity, operational, supply chain and reputational. Companies are vulnerable to risks. What makes such risks even more complex and challenging to manage is that the risks are often not within the direct control of the business executive. They can exist outside of the company boundary, and yet the impact to the company can be huge. The awareness and knowledge of how to manage risks in companies, will become increasingly important.

Some of the main topics covered in this lecture include:

  • Targets and legal aspects of risk management
  • Risks and their impact
  • Risk types (classification)
  • Risk management and human resource
  • Steps of the risk management process and their instruments
  • Methods of risk assessment
  • Implementation of risk management
  • Management of specific risks

This lecture is presented in German language only.


Literature

Brühwiler, B., Romeike, F. (2010), Praxisleitfaden Risikomanagement. ISO 31000 und ONR 49000 sicher anwenden, Berlin: Erich Schmidt.

Cottin, C., Döhler, S. (2013), Risikoanalyse. Modellierung, Beurteilung und Management von Risiken mit Praxisbeispielen, 2. überarbeitete und erweiterte Aufl., Wiesbaden: Springer.

Eller, R., Heinrich, M., Perrot, R., Reif, M. (2010), Kompaktwissen Risikomanagement. Nachschlagen, verstehen und erfolgreich umsetzen, Wiesbaden: Gabler.

Fiege, S. (2006), Risikomanagement- und Überwachungssystem nach KonTraG. Prozess, Instrumente, Träger, Wiesbaden: Deutscher Universitäts-Verlag.

Frame, D. (2003), Managing Risk in organizations. A guide for managers, San Francisco: Wiley.

Götze, U., Henselmann, K., Mikus, B. (2001), Risikomanagement, Heidelberg: Physica-Verlag.

Müller, K. (2010), Handbuch Unternehmenssicherheit. Umfassendes Sicherheits-, Kontinuitäts- und Risikomanagement mit System, 2., neu bearbeitete Auflage, Wiesbaden: Springer.

Rosenkranz, F., Missler-Behr, M. (2005), Unternehmensrisiken erkennen und managen. Einführung in die quantitative Planung, Berlin u.a.: Springer.

Wengert, H., Schittenhelm F. A. (2013), Coporate Risk Mangement, Berlin: Springer.


Course L1389: Key Aspects of Patent Law
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale
Lecturer Prof. Christian Rohnke
Language DE
Cycle SoSe
Content

Mayor Issues in Patent Law:

The seminar covers five mayor issues in german patent law, namely patentatbility, prosecution, ownership and employee inventions, infringement and licensing and other commercila uses.

The lecturer will give an introduction to each issue which will be followed by in-depth inquiry by the participants through group work, presentation of results and moderated discussion.


Literature wird noch bekannt gegeben
Course L1491: Startup Engineering
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Fachtheoretisch-fachpraktische Arbeit
Examination duration and scale Ausarbeitung einer Geschäftsidee auf 20-30 Seiten (Inhaltsfolien zur detailliierten Dokumentation des Herangehensweise). Bearbeitungsdauer über den ganzen Kurs hinweg 13 Wochen, Zwischen- und Abschlusspräsentation jeweils 15 min plus 15 Diskussion.
Lecturer Prof. Christoph Ihl
Language EN
Cycle WiSe
Content

Important note: This course is part of an 6 ECTS module consisting of the three courses "Startup Engineering", "Startup Engineering Project" and "Entrepreneurship Management", which have to be taken together in one semester.

Startups are temporary, team-based organizations, which can form both within and outside of established companies, to pursue one central objective: taking a new venture idea to market by designing a business model that can be scaled to a full-grown company. In this course, students will form startup teams around self-selected ideas and run through the process just like real startups would do in the first three months of intensive work. Startup Engineering takes an incremental and iterative approach, in that it favors variety and alternatives over one detailed, linear five-year business plan to reach steady state operations. From a problem solving and systems thinking perspective, student teams create different possible versions of a new venture and alternative hypotheses about value creation for customers and value capture vis-à-vis competitors. To test critical hypotheses early on, student teams engage in an evidence-based, experimental trial-and-error learning process that measures real progress.
Upon completion of this course, students will be able to:
· Apply a modern innovation toolkit relevant in both the corporate & startup world
· Analyze given business opportunities in terms of its constituent elements
· Design new business models by gathering and combining relevant ideas, facts and information 
· Evaluate business opportunities and derive judgment about next steps & decisions
Course language is English, but participants can decide to give their graded presentations in German. Students are invited to apply to this course module already with a startup idea and/ or team, but this is not a requirement! We will form teams and ideas in the beginning of the course. Class meetings have alternate intervals of lecture inputs, teamwork, mentoring, and peer feedback. Attendance is mandatory for at least 80% of class time due to large proportion of teamwork sessions.
Student teams give three presentations and submit them with backup analyses. Grading scheme:
· Startup discovery presentation after 5 weeks: 30%
· Startup validation presentation after 10 weeks: 30%
· Final startup pitches after 13 weeks: 40%




Literature

• Blank, S. & Dorf, B. (2012). The startup owner's manual.
• Gans, J. & Stern, S. (2016). Entrepreneurial Strategy.
• Osterwalder, A. & Yves, P. (2010). Business model generation.
• Maurya, A. (2012). Running lean: Iterate from plan A to a plan that works.
• Maurya, A. (2016). Scaling lean: Mastering the Key Metrics for Startup Growth.
• Wilcox, J. (2016). FOCUS Framework: How to Find Product-Market Fit.

Course L1492: Startup Engineering Project
Typ Project-/problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Mündliche Prüfung
Examination duration and scale 20 min
Lecturer Prof. Christoph Ihl
Language EN
Cycle WiSe
Content

Important note: This course is part of an 6 ECTS module consisting of the three courses "Startup Engineering", "Startup Engineering Project" and "Entrepreneurship Management", which have to be taken together in one semester.

Startups are temporary, team-based organizations, which can form both within and outside of established companies, to pursue one central objective: taking a new venture idea to market by designing a business model that can be scaled to a full-grown company. In this course, students will form startup teams around self-selected ideas and run through the process just like real startups would do in the first three months of intensive work. Startup Engineering takes an incremental and iterative approach, in that it favors variety and alternatives over one detailed, linear five-year business plan to reach steady state operations. From a problem solving and systems thinking perspective, student teams create different possible versions of a new venture and alternative hypotheses about value creation for customers and value capture vis-à-vis competitors. To test critical hypotheses early on, student teams engage in an evidence-based, experimental trial-and-error learning process that measures real progress.
Upon completion of this course, students will be able to:
· Apply a modern innovation toolkit relevant in both the corporate & startup world
· Analyze given business opportunities in terms of its constituent elements
· Design new business models by gathering and combining relevant ideas, facts and information 
· Evaluate business opportunities and derive judgment about next steps & decisions
Course language is English, but participants can decide to give their graded presentations in German. Students are invited to apply to this course module already with a startup idea and/ or team, but this is not a requirement! We will form teams and ideas in the beginning of the course. Class meetings have alternate intervals of lecture inputs, teamwork, mentoring, and peer feedback. Attendance is mandatory for at least 80% of class time due to large proportion of teamwork sessions.
Student teams give three presentations and submit them with backup analyses. Grading scheme:
· Startup discovery presentation after 5 weeks: 30%
· Startup validation presentation after 10 weeks: 30%
· Final startup pitches after 13 weeks: 40%



Literature

• Blank, S. & Dorf, B. (2012). The startup owner's manual.
• Gans, J. & Stern, S. (2016). Entrepreneurial Strategy.
• Osterwalder, A. & Yves, P. (2010). Business model generation.
• Maurya, A. (2012). Running lean: Iterate from plan A to a plan that works.
• Maurya, A. (2016). Scaling lean: Mastering the Key Metrics for Startup Growth.
• Wilcox, J. (2016). FOCUS Framework: How to Find Product-Market Fit.



Course L2409: Strategic Shared-Value Management
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 30 Minuten
Lecturer Dr. Jill Küberling-Jost
Language EN
Cycle SoSe
Content
Literature
Course L2295: Strategische Planung mit Planspielen
Typ Project-/problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale
Lecturer Dr. Jan Spitzner
Language DE
Cycle SoSe
Content
Literature
Course L2410: Technology Entrepreneurship
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 30 Minuten
Lecturer Prof. Christoph Ihl
Language EN
Cycle SoSe
Content
Literature
Course L1351: Management Consulting
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale
Lecturer Gerald Schwetje
Language DE
Cycle SoSe
Content

The Management Consulting lecture teaches students knowledge that is complementary to their technical and business administration studies. They learn the basics of consulting and agent-principal theory and are given an overview of the consulting market. They are also shown how management consulting works and which methodical building blocks (processes) are needed to deal with a client’s concerns and to undertake a consulting process. By means of practical examples students gain an insight into the extensive range of management consultancy services and of functional consulting.

Literature

Bamberger, Ingolf (Hrsg.): Strategische Unternehmensberatung: Konzeptionen - Prozesse - Methoden, Gabler Verlag, Wiesbaden 2008

Bansbach, Schübel, Brötzel & Partner (Hrsg.): Consulting: Analyse - Konzepte - Gestaltung, Stollfuß Verlag, Bonn 2008

Fink, Dietmar (Hrsg.): Strategische Unternehmensberatung, Vahlens Handbücher, München, Verlag Vahlen, 2009

Heuermann, R./Herrmann, F.: Unternehmensberatung: Anatomie und Perspektiven einer Dienstleistungselite, Fakten und Meinungen für Kunden, Berater und Beobachter der Branche, Verlag Vahlen, München 2003

Kubr, Milan: Management consulting: A guide to the profession, 3. Auflage, Geneva, International Labour Office, 1992

Küting, Karlheinz (Hrsg.): Saarbrücker Handbuch der Betriebswirtschaftlichen Beratung; 4. Aufl., NWB Verlag, Herne 2008

Nagel, Kurt: 200 Strategien, Prinzipien und Systeme für den persönlichen und unternehmerischen Erfolg, 4. Aufl., Landsberg/Lech, mi-Verlag, 1991

Niedereichholz, Christel: Unternehmensberatung: Beratungsmarketing und Auftragsakquisition, Band 1, 2. Aufl., Oldenburg Verlag, 1996

Niedereichholz; Christel: Unternehmensberatung: Auftragsdurchführung und Qualitätssicherung, Band 2, Oldenburg Verlag, 1997

Quiring, Andreas: Rechtshandbuch für Unternehmensberater: Eine praxisorientierte Darstellung der typischen Risiken und der zweckmäßigen Strategien zum Risikomanagement mit Checklisten und Musterverträgen, Vahlen Verlag, München 2005

Schwetje, Gerald: Ihr Weg zur effizienten Unternehmensberatung: Beratungserfolg durch eine qualifizierte Beratungsmethode, NWB Verlag, Herne 2013

Schwetje, Gerald: Wer seine Nachfolge nicht regelt, vermindert seinen Unternehmenswert, in: NWB, Betriebswirtschaftliche Beratung, 03/2011 und: Sparkassen Firmenberatung aktuell, 05/2011

Schwetje, Gerald: Strategie-Assessment mit Hilfe von Arbeitshilfen der NWB-Datenbank - Pragmatischer Beratungsansatz speziell für KMU: NWB, Betriebswirtschaftliche Beratung, 10/2011

Schwetje, Gerald: Strategie-Werkzeugkasten für kleine Unternehmen, Fachbeiträge, Excel-Berechnungsprogramme, Checklisten/Muster und Mandanten-Merkblatt: NWB, Downloadprodukte, 11/2011

Schwetje, Gerald: Die Unternehmensberatung als komplementäres Leistungsangebot der Steuerberatung - Zusätzliches Honorar bei bestehenden Klienten: NWB, Betriebswirtschaftliche Beratung, 02/2012

Schwetje, Gerald: Die Mandanten-Berater-Beziehung: Erfolgsfaktor Beziehungsmanagement, in: NWB Betriebswirtschaftliche Beratung, 08/2012

Schwetje, Gerald: Die Mandanten-Berater-Beziehung: Erfolgsfaktor Vertrauen, in: NWB Betriebswirtschaftliche Beratung, 09/2012

Wohlgemuth, Andre C.: Unternehmensberatung (Management Consulting): Dokumentation zur Vorlesung „Unternehmensberatung“, vdf Hochschulverlag, Zürich 2010

Course L0536: Management of Trust and Reputation
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 20-30 Minuten und Thesenpapier
Lecturer Dr. Michael Florian
Language DE
Cycle SoSe
Content

The seminar offers a comparison and analysis of relevant theoretical concepts and practical issues in the corporate management of trust and reputation. Selected case studies will be used to discuss opportunities, problems, and limitations using trust and reputation to coordinate and control economic behavior.

Literature

Allgäuer, Jörg E. (2009): Vertrauensmanagement: Kontrolle ist gut, Vertrauen ist besser. Ein Plädoyer für Vertrauensmanagement als zentrale Aufgabe integrierter Unternehmenskommunikation von Dienstleistungsunternehmen. München: brain script Behr.
Beckert, Jens; Metzner, André; Roehl, Heiko (1998): Vertrauenserosion als organisatorische Gefahr und wie ihr zu begegnen ist. In: Organisationsentwicklung 17 (4), S. 57-66.
Eberl, Peter (2003): Vertrauen und Management. Studien zu einer theoretischen Fundierung des Vertrauenskonstruktes in der Managementlehre. Stuttgart: Schäffer-Poeschel.
Eberl, Peter (2012): Vertrauen und Kontrolle in Organisationen. Das problematische Verhältnis der Betriebswirtschaftslehre zum Vertrauen. In: Möller, Heidi (Hg.): Vertrauen in Organisationen. Riskante Vorleistung oder hoffnungsvolle Erwartung? Wiesbaden: Springer VS, S. 93-110.
Eisenegger, Mark (2005): Reputation in der Mediengesellschaft. Konstitution   Issues Monitoring   Issues Management. Wiesbaden: VS Verlag für Sozialwissenschaften.
Florian, Michael (2013): Paradoxien des Vertrauensmanagements. Risiken und Chancen einer widerspenstigen immateriellen Ressource. In: Personalführung 46, Heft 2/2013, S. 40-47.
Grüninger, Stephan (2001): Vertrauensmanagement - Kooperation, Moral und Governance. Marburg: Metropolis.
Grüninger, Stephan; John, Dieter (2004): Corporate Governance und Vertrauensmanagement. In: Josef Wieland (Hg.): Handbuch Wertemanagement. Erfolgsstrategien einer modernen Corporate Governance. Hamburg: Murmann, S. 149-177.
Meifert, Matthias (2008): Ist Vertrauenskultur machbar? Vorbedingungen und Überforderungen betrieblicher Personalpolitik. In: Rainer Benthin und Ulrich Brinkmann (Hg.): Unternehmenskultur und Mitbestimmung. Betriebliche Integration zwischen Konsens und Konflikt. Frankfurt/Main, New York: Campus, S. 309-327.
Neujahr, Elke; Merten, Klaus (2012): Reputationsmanagement. Zur Kommunikation von Wertschätzung. In: PR-Magazin 06/2012, S. 60-67.
Osterloh, Margit; Weibel, Antoinette (2006): Investition Vertrauen. Prozesse der Vertrauensentwicklung in Organisationen. Wiesbaden: Gabler.
Osterloh, Margit; Weibel, Antoinette (2006): Vertrauen und Kontrolle. In: Robert J. Zaugg und Norbert Thom (Hg.): Handbuch Kompetenzmanagement. Durch Kompetenz nachhaltig Werte schaffen. Festschrift für Prof. Dr. Dr. h.c. mult. Norbert Thom zum 60. Geburtstag. Bern [u.a.]: Haupt, S. 53-63.
Osterloh, Margit; Weibel, Antoinette (2007): Vertrauensmanagement in Unternehmen: Grundlagen und Fallbeispiele. In: Manfred Piwinger und Ansgar Zerfaß (Hg.): Handbuch Unternehmenskommunikation. Wiesbaden: Gabler, S. 189-203.
Schmidt, Matthias; Beschorner, Thomas (2005): Werte- und Reputationsmanagement. München und Mering: Hampp.
Seifert, Matthias (2003): Vertrauensmanagement in Unternehmen. Eine empirische Studie über Vertrauen zwischen Angestellten und ihren Führungskräften. 2. Aufl. München und Mering: Hampp.
Sprenger, Reinhard K. (2002): Vertrauen führt. Worauf es im Unternehmen wirklich ankommt, Frankfurt/Main, New York.
Thiessen, Ansgar (2011): Organisationskommunikation in Krisen. Reputationsmanagement durch strategische, integrierte und situative Krisenkommunikation. Wiesbaden: VS Verlag für Sozialwissenschaften.
Walgenbach, Peter (2000): Das Konzept der Vertrauensorganisation. Eine theoriegeleitete Betrachtung. In: Die Betriebswirtschaft 60 (6), S. 707-720.
Walgenbach, Peter (2006): Wieso ist Vertrauen in ökonomischen Transaktionsbeziehungen so wichtig, und wie lässt es sich generieren? In: Hans H. Bauer, Marcus M. Neumann und Anja Schüle (Hg.): Konsumentenvertrauen. Konzepte und Anwendungen für ein nachhaltiges Kundenbindungsmanagement. München: Vahlen, S. 17-26.
Weibel, Antoinette (2004): Kooperation in strategischen Wissensnetzwerken. Vertrauen und Kontrolle zur Lösung des sozialen Dilemmas. Wiesbaden: Dt. Univ.-Verl.
Weinreich. Uwe (2003): Vertrauensmanagement. In: Deutscher Manager-Verband e.V. (Hg.): Die Zukunft des Managements. Perspektiven für die Unternehmensführung. Zürich: Vdf, Hochsch.-Verl. an der ETH, S. 193-201.

Course L1381: Public and Constitutional Law
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale 2 Stunden
Lecturer Klaus-Ulrich Tempke
Language DE
Cycle WiSe/SoSe
Content

Different areas of public law; proceedings, jurisdiction of administrative courts with stages of appeal,
members of the courts;
Court levels, organization and legal capacity;
lntroduction to and structure of fundamental rights;
Human dignity: the guiding principle of the constitution;
General right of privacy and freedom of action.

Literature

Module M0524: Non-technical Courses for Master

Module Responsible Dagmar Richter
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The Nontechnical Academic Programms (NTA)

imparts skills that, in view of the TUHH’s training profile, professional engineering studies require but are not able to cover fully. Self-reliance, self-management, collaboration and professional and personnel management competences. The department implements these training objectives in its teaching architecture, in its teaching and learning arrangements, in teaching areas and by means of teaching offerings in which students can qualify by opting for specific competences and a competence level at the Bachelor’s or Master’s level. The teaching offerings are pooled in two different catalogues for nontechnical complementary courses.

The Learning Architecture

consists of a cross-disciplinarily study offering. The centrally designed teaching offering ensures that courses in the nontechnical academic programms follow the specific profiling of TUHH degree courses.

The learning architecture demands and trains independent educational planning as regards the individual development of competences. It also provides orientation knowledge in the form of “profiles”.

The subjects that can be studied in parallel throughout the student’s entire study program - if need be, it can be studied in one to two semesters. In view of the adaptation problems that individuals commonly face in their first semesters after making the transition from school to university and in order to encourage individually planned semesters abroad, there is no obligation to study these subjects in one or two specific semesters during the course of studies.

Teaching and Learning Arrangements

provide for students, separated into B.Sc. and M.Sc., to learn with and from each other across semesters. The challenge of dealing with interdisciplinarity and a variety of stages of learning in courses are part of the learning architecture and are deliberately encouraged in specific courses.

Fields of Teaching

are based on research findings from the academic disciplines cultural studies, social studies, arts, historical studies, communication studies, migration studies and sustainability research, and from engineering didactics. In addition, from the winter semester 2014/15 students on all Bachelor’s courses will have the opportunity to learn about business management and start-ups in a goal-oriented way.

The fields of teaching are augmented by soft skills offers and a foreign language offer. Here, the focus is on encouraging goal-oriented communication skills, e.g. the skills required by outgoing engineers in international and intercultural situations.

The Competence Level

of the courses offered in this area is different as regards the basic training objective in the Bachelor’s and Master’s fields. These differences are reflected in the practical examples used, in content topics that refer to different professional application contexts, and in the higher scientific and theoretical level of abstraction in the B.Sc.

This is also reflected in the different quality of soft skills, which relate to the different team positions and different group leadership functions of Bachelor’s and Master’s graduates in their future working life.

Specialized Competence (Knowledge)

Students can

  • explain specialized areas in context of the relevant non-technical disciplines,
  • outline basic theories, categories, terminology, models, concepts or artistic techniques in the disciplines represented in the learning area,
  • different specialist disciplines relate to their own discipline and differentiate it as well as make connections, 
  • sketch the basic outlines of how scientific disciplines, paradigms, models, instruments, methods and forms of representation in the specialized sciences are subject to individual and socio-cultural interpretation and historicity,
  • Can communicate in a foreign language in a manner appropriate to the subject.
Skills

Professional Competence (Skills)

In selected sub-areas students can

  • apply basic and specific methods of the said scientific disciplines,
  • aquestion a specific technical phenomena, models, theories from the viewpoint of another, aforementioned specialist discipline,
  • to handle simple and advanced questions in aforementioned scientific disciplines in a sucsessful manner,
  • justify their decisions on forms of organization and application in practical questions in contexts that go beyond the technical relationship to the subject.



Personal Competence
Social Competence

Personal Competences (Social Skills)

Students will be able

  • to learn to collaborate in different manner,
  • to present and analyze problems in the abovementioned fields in a partner or group situation in a manner appropriate to the addressees,
  • to express themselves competently, in a culturally appropriate and gender-sensitive manner in the language of the country (as far as this study-focus would be chosen), 
  • to explain nontechnical items to auditorium with technical background knowledge.





Autonomy

Personal Competences (Self-reliance)

Students are able in selected areas

  • to reflect on their own profession and professionalism in the context of real-life fields of application
  • to organize themselves and their own learning processes      
  • to reflect and decide questions in front of a broad education background
  • to communicate a nontechnical item in a competent way in writen form or verbaly
  • to organize themselves as an entrepreneurial subject country (as far as this study-focus would be chosen)     



Workload in Hours Depends on choice of courses
Credit points 6
Course L1775: “What’s up, Doc?” Science and Stereotypes in Literature and Film
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dr. Jennifer Henke
Language EN
Cycle WiSe/SoSe
Content

Popular novels and films significantly contribute to the public understanding of science and its representatives. How to define “good” or “bad” science is negotiated in a variety of artistic works. Stereotypes such as the “mad scientist”, which originated in early nineteenth century England, continue to persist. Mary Shelley created the prototype of the obsessive and reckless scientist in Frankenstein - The Modern Prometheus (1818) who conducts his forbidden experiments in a secret lab and crosses ethical boundaries. This masculine stereotype has been followed by further ones such as the noble, adventurous or clumsy scientist, whereas scholars have only recently begun to consider the representation of female science.

First, this seminar is devoted to selected formations of knowledge in relation to literature from classical antiquity to the present. Second, the focus shall rest on the production of persistent stereotypes in various media formats such as novels or films while paying particular attention to the aspect of gender. The overall goal of the seminar is an understanding of science as a cultural practice.  

Requirements for participation: Shelley, Mary: Frankenstein. New York: Norton, 2012. Please pay attention to the exact publication dates.

Literature Teilnahmevoraussetzungen: Shelley, Mary: Frankenstein. New York: Norton, 2012. Bitte ausschließlich diese Edition anschaffen.


Course L2064: 120 years of film history
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale 90 min
Lecturer Prof. Margarete Jarchow
Language DE
Cycle SoSe
Content The lecture deals with the relationship between the develpoment of film technology, film aesthetics, and society. Based on the nineteenth-century film's precursors such as the laterna magica, photography and kinetoscope, crucial stages of more than 120 years of film history are studied chronologically in terms of: How does the development of new media techniques reflect certain social changes and needs? What new forms of aesthetic expression are possible through such technical innovations as the introduction of sound film, color film or handheld camera? And to what extent do these new forms of aesthetic expression in turn reflect certain social sensitivities, ultimately the respective zeitgeist? Main topics of the lecture are: the technical euphoria of the 19th century, the early film, the German Expressionist film, the classic Hollywood cinema, the European postwar cinema, exploitation and underground cinema, New Hollywood, the blockbuster cinema, independent cinema up to current phenomena like the „cinema of dissolution“. On the one hand, the participants learn in-depth, detailed knowledge of the history, meaning and analysis of the medium film and thereby acquire media literacy. On the other hand, the participants should gain a deeper understanding of the real interdependencies of technologies in culture and society and their historical transformation processes through an interdisciplinary perspective on film (history of technology, media studies and social science).
Literature
Course L1774: Applied Arts: Form and Function
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Prof. Margarete Jarchow, Dr. Christian Lechelt
Language DE
Cycle WiSe/SoSe
Content

From Arts & Crafts to modern Design - applied arts focus on the design of all kinds of products. Therefore applied arts allow to come to more thorough conclusions about social, historical, cultural issues.

In the course the impact of social developments on these particular genres are discussed.

Literature

Wird noch angegeben

Will be announced in lecture
Course L2338: Bauhaus architecture - a search for traces
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dr. Jörg Schilling
Language DE
Cycle WiSe/SoSe
Content

The „100 years of bauhaus“ centenery also involved examining the references, differences and similarities to Hamburg architecture from 1919-1933.
The seminar intends to find these traces in social (i.e. Jarrestadt) and private (i.e. Landhaus Michaelsen / Puppenmuseum) housing as well as in numerous other building projects. During the excursions to buildings by Hamburg architects like Fritz Schumacher, Gustav Oelsner, Karl Schneider and others we will discuss aspects related to architectural modernism.

Literature wird im Seminar bekanntgegeben
Course L1882: Facilitating groups in problem-oriented courses
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Fachtheoretisch-fachpraktische Arbeit
Examination duration and scale Schriftliche Ausarbeitung (in mehreren Teilen) sowie eine Präsentation, Teilnahme an Gruppendiskussionen
Lecturer Siska Simon
Language DE
Cycle WiSe/SoSe
Content

Content:
- Changing the role of the teacher in problem-oriented courses
- Structure and benefits of problem-oriented courses
- Attitude and beliefs concerning teaching and learning
- Question and discussion techniques
- Group dynamic processes
- Situation-related interventions
- dealing with heterogeneous groups
- Moderation and presentation
- Interference levels and conflict management
- Feedback processes and methods

Methods:
- impulse lectures and group work

- Planning, execution and reflection of an exemplary course unit
- Micro teaching and feedback
- peer observation and feedback


Literature

Auszüge aus Fachliteratur zu oben genannten Themen werden in der Veranstaltung ausgegeben

Course L1990: Clash of Cultures. Film and TV series as images of the own and the other
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Jacobus Bracker
Language DE
Cycle WiSe/SoSe
Content

Images are negotiating concepts of the own, other and alien. Especially tv series like “Game of Thrones”, “Vikings”, or “The Walking Dead” and films like “Alien” or “Lord of the Rings” show clashes of cultures. Irrespective of their genre - fantasy, science fiction, or history - the moving images use always similar patterns to show and tell the own and the other. During the seminar we will deal with such concepts and concepts of culture and the specifics of film and series to watch and analyse selected examples from these perspectives.


Literature

Literaturhinweise, Texte etc. werden zu gegebener Zeit online zur Verfügung gestellt.

Course L1176: The end is near - Survival in the post-apocalypse
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dr. Marlis Bussacker
Language DE
Cycle WiSe/SoSe
Content

According to the FAZ in December 2015, the end of the world is booming. At all times, people have dealt with the imminent future scenario of ultimate horror - the collapse of their own world. Where does the idea of a final disaster come from? What's so fascinating about our own demise? During the seminar we will take a look at European cultural history, which is closely linked to mythological and religious prophecies about the end of the world.

However, this question, or rather the question of survival in a post-apocalyptic world, has fortunately remained speculative to this day despite regular predictions. Since the end of the world has not yet happened in reality, we are therefore dependent on the imagination of writers, screenwriters and directors who have anticipated the event in an infinite number of texts, films and series.

Based on selected films and texts, the seminar will focus on the questions of which apocalyptic scenarios are developed, with which problems the survivors are confronted and how they deal with the situation and with each other. The focus is on the reactions of people in a state of extreme threat. Which survival strategies are presented to us, how do we assess the behaviour of the actors, can we create alternatives?

Furthermore, the effect of the genre on the recipient will be discussed. Do we dismiss films like Armaggedon and The Day After Tomorrow as entertaining thrills? Do we just enjoy the special effects? Do we feel threatened? Do we take them in the end as real instructions for action? Do they make us reflect? Or are even current social discourses reflected in the garment of the apocalypse?

Literature
Course L1441: German as a Foreign Language for International Master Programs
Typ Seminar
Hrs/wk 4
CP 4
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
Examination Form Klausur
Examination duration and scale
Lecturer Dagmar Richter
Language DE
Cycle WiSe/SoSe
Content

Master’s German course in cooperation with IBH e.V. - Master’s German courses at different levels

In the international studies program these are obligatory for non-native speakers of German and for students without a DSH certificate or equivalent TEST-DAF result. Grading after an aptitude test. All other students must sign up for a total of 4 ECTS from the catalog of non-technical supplementary courses.



Literature - Will be announced in lectures -
Course L1884: The Hamburger Speicherstadt - from achievements of engineering to world cultural heritage
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 20 minütiges Referat mit anschließender Diskussion
Lecturer Dr. Jörg Schilling
Language DE
Cycle WiSe/SoSe
Content

The seminar wants to show the problems and challenges for the engineers, who built the Hamburger Speicherstadt and their sustainable architectural solutions, which are still of vital importance and the basis for becoming a world cultural heritage.

Literature u.a.: Hamburg und seine Bauten unter Berücksichtigung seiner Nachbarstädte Altona und Wandsbek, hg. vom Architekten- und Ingenieur-Verein zu Hamburg, Hamburg 1890; Karin Maak: Die Speicherstadt im Hamburger Hafen, Hamburg 1895; Hermann Hipp: Freie und Hansestadt Hamburg, Köln 1989; Matthias von Popowski: Franz Andreas Meyer (1837-1901). Oberingenieur und Leiter des Ingenieurwesens von 1872-1901, in: Wie das Kunstwerk Hamburg entstand, hg. v. Dieter Schädel, Hamburg 2006, S. 64-79; Ralf Lange: HafenCity + Speicherstadt : das maritime Quartier in Hamburg, Hamburg 2010.
Course L1996: Digital culture(s): from subculture to media mainstream
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dr. Oliver Schmidt
Language DE
Cycle WiSe/SoSe
Content

The course gives an introduction to the development of digitization in a media cultural perspective. In addition to technical aspects, we will focus on the cultural impact of digitization for current media users and the ermergence und development of media subcultures from the late 1970s to the 21st century. On the one hand, we will deal with questions such as: What is digitization? What is culture? What are digital (sub)cultures? In this context, the concept of ‚digital natives‘ and ‚digital immigrants‘, coined by Marc Prensky, will also be discussed. On the other hand, there will be a historical perspective on topics and developments such as the mediatization oft he children’s room in the early 1980s, the hacker scene, video game culture, the demo scene, digital culture in cinema, 8-bit culture, digital aesthetics , net art, post-digitality and ultimately the question of how digital subcultures have become part of the media mainstream at the beginning of the 21st century.

Literature
Course L2367: Digital art
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale Referat ca. 20 min. plus anschließende Diskussion
Lecturer Dr. Imke Hofmeister
Language DE
Cycle WiSe/SoSe
Content

Digitalization is having a major impact on many areas of our lives and the use of digital technologies in art and design has increased rapidly. After all, art is not only subject to constant change, but also constantly adapts to technical conditions. After the photographic art of the mid-19th century and the video art of the 1960s, which already brought about major changes in artistic creation, digital art is becoming increasingly important in the field of media art. The first attempts to use the computer with corresponding graphic software as an artistic medium took place in the 80/90s of the 20th century. Since then, there has been a broad development in the field of digital art, which now encompasses the most diverse digital pictorial phenomena and art genres and is thus intertwined in its objects, theories and practices with digital media in a variety of ways. The seminar gives an overview of the history of digital art and its different genres. These include, for example, photopaintings, where digital manipulation, filtering processes and painting can process the image and transform it over many stages into a completely new form. Also 3-D images, vector graphics, mathematical art and computer art in general. At the same time, the digital development in art is to be illuminated, from the first beginnings on the computer with comparatively simple "digital aids", e.g. in the form of simple image processing programs, to the present sophisticated graphic tools.

In addition, the presentation, dissemination and conservation possibilities of digital art will also be discussed, which can be disseminated very well on the Internet primarily because it can be displayed on a computer screen. The great fascination with digital creative work and the almost inexhaustible possibilities offered by the medium of computers to artists, who will continue to ensure that digital art finds a permanent place alongside traditional media, will also be discussed. Finally, in contrast to the traditional production methods in the field of fine arts and design, there are always new manifestations of digital art, which ultimately give not only the "trained" artist but also the layman far-reaching possibilities for artistic expression. And all this in the spirit of the performance artist Joseph Beuys , who postulated, every human being is capable of creativity, indeed "every human being is an artist".

The seminar will also discuss the question of how digital art can be described as "the" contemporary art, i.e. contemporary art in the age of digital technology. Furthermore, it is of great interest to what extent the perception of art per se has already changed and will continue to change in a digitalized society.

Literature folgt
Course L1725: Introduction to the Science & Technoloy Studies (STS)
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale Gruppenreferat (30 bis 45 Minuten, Eigenanteil je Person 10 bis 15 Minuten) inkl. schriftlicher Ausarbeitung, Ggf. alternativ eine längere, schriftliche Ausarbeitung.
Lecturer Dr. Simon Egbert
Language EN
Cycle WiSe/SoSe
Content

Since the end of the 1980’s or the beginning of the 1990’s, in the Sociology of Technology a line of research has emerged which initially called for a socialization of the sociology of technology (especially through the Social Construction of Technology Approach [SCOT]) and right away called for its re-materialisation (especially through Bruno Latour and the Actor-Network Theory). Technologies, thus their basic idea, are always intertwined with society and shaped by their socio-cultural context. In reverse, society is also inherently formed by the existing technologies and an adequate sociology of technology has to deal especially with the interaction of both. In the seminar at hand first of all an overview shall be given about the classical sociology of technology which routinely used argumentations inspired by technological determinism, which shall be followed by the presentation of the SCOT-approach. The later in turn was criticised by the Actor-Network Theory (which will be presented in a separate section as well) as being social deterministic which has led to a rather heated debate about the agency of technological artefacts, which shall be presented and discussed in a further part of the seminar. In the last section of the class it shall be determined what kind of relevance the sociological analysis of technological artefacts and their societal embedding can or could implicate for the own lifeworld of the students - especially of course with special focus on their engineer studies.


Literature

Bammé, Arno (2009): Science and Technology Studies: ein Überblick. Marburg: Metropolis.

Degele, Nina (2002): Einführung in die Techniksoziologie. München: Fink.

Hackett, Edward et al. (Hrsg.) (2008): The Handbook of Science and Technology Studies. 3rd Edition. Cambridge: MIT Press.

Häußling, Roger (2014): Techniksoziologie. Baden-Baden: Nomos.

MacKenzie, Donald/Judy, Wajcman (2003): The social shaping of technology. 2nd Edition. Maidenhead et al.: Open University Press.

Sismondo, Sergio (2010): An Introduction to Science and Technology Studies, 2nd Edition.

Chichester: Wiley-Blackwell.

Course L2336: Introduction to Marxian Theory of Economy
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale 90 min
Lecturer Dr. Martin Schütz
Language DE
Cycle WiSe/SoSe
Content

Capitalism - what’s the definition in Marxian economical theorie? Which are the functions of gold, money, interest?
Focusing on the Marxian basis categories Ware - Gebrauchswert - Tauschwert - Wert - Arbeit - Austauschprozess - Geld - Zirkulation - Arbeitskraft, the subjects of the lecture are the first four chapters of ‘Das Kapital’ vol. 1, accompanied by discussion of neo-classical theory, monetarism etc.

Literature

Karl Marx, Das Kapital, Band 1, Berlin 1962ff (=Marx-Engels-Werke [MEW] Bd. 23), S. 1-390
Dieser Text steht text- und seitengenau im Internet zur Verfügung: http://www.mlwerke.de/me/me23/me23_000.htm oder http://www.zeno.org/Philosophie/M/Marx,+Karl/Das+Kapital
David Harvey, Marx‘ Kapital lesen, Hamburg 2017, Seiten 1-214
Begleitend: Harvey selbst hat seine ‚Kapital‘-Seminare (auf Englisch) als Stream veröffentlicht: http://davidharvey.org/reading-capital/
Ergänzende Literatur:

Altvater, Elmar (Hg.) (1999): Kapital.doc. Das Kapital (Bd. 1) von Marx in Schaubildern mit Kommentaren. Mit CD-ROM. Münster
Artus, Ingrid u.a. (Hg.) (2014): Marx für SozialwissenschaftlerInnen. Eine Einführung. Wiesbaden
Fülberth, Georg (2008): G Strich. Kleine Geschichte des Kapitalismus. 4., verb. und erw. Aufl. Köln
Krause, Alexandra (2014): Kritik der Politischen Ökonomie - Wachstum als Imperativ kapitalistischen Wirtschaftens. In: Artus (2014) S. 135-160.
Münch, Richard (2008): Soziologische Theorie. Grundlegung durch die Klassiker. Korr. Nachdr. 2008. Frankfurt/Main (Soziologische Theorie, 1).
Nachtwey, Oliver (2014): Arbeit, Lohnarbeit und Industriearbeit. In: Artus (2014) S. 109-134
Söllner, Fritz (2015): Die Geschichte des ökonomischen Denkens. 4. Aufl. Berlin

Course L1994: Facts, Facts, Facts - Understanding and Applying Techniques of Journalism - in German
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Prof. Margarete Jarchow, Matthias Kowalski
Language DE
Cycle WiSe/SoSe
Content Regardless of whether it is via classic channels such as newspapers and magazines or radio and TV as well as via internet, social media or via communication in specialist circles: Today we encounter journalism in almost all forms of public and private communication. But what makes a story really important in this flood of content? How do we recognize relevance? How do we expose fake news? In this block seminar the principles of journalistic techniques are imparted by means of practical examples and editorial exercises. The participants also develop tools to detect and deactivate manipulation and fake news. Regular attendance and attendance at all block dates is required.
Literature
Course L2370: Facts, Facts, Facts - Understanding and Applying Techniques of Journalism - in English
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Prof. Margarete Jarchow
Language EN
Cycle WiSe/SoSe
Content

Regardless of whether it is via classic channels such as newspapers and magazines or radio and TV as well as via internet, social media or via communication in specialist circles: Today we encounter journalism in almost all forms of public and private communication. But what makes a story really important in this flood of content? How do we recognize relevance? How do we expose fake news? In this block seminar the principles of journalistic techniques are imparted by means of practical examples and editorial exercises. The participants also develop tools to detect and deactivate manipulation and fake news. Regular attendance and attendance at all block dates is required.

Literature folgt
Course L0970: Foreign Language Course
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Klausur
Examination duration and scale 60 min
Lecturer Dagmar Richter
Language
Cycle WiSe/SoSe
Content

In the Field of the Nontechnical Complementary Courses students are able to chose foreign language courses. Therefore the Hamburger Volkshochschule offers a special language programm on TUHH campus for TUHH Students. It includes courses in english, chinese, french, japanese, portuguese, russia, swedish, spanisch and german as a foreign language. All lectures impart common language knowledge, english courses although english for technical purposes.

Literature Kursspezifische Literatur / selected bibliography depending on special lecture programm.
Course L0983: Management and Communication
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 90-minütige interaktive Präsentation im Team inkl. Handout.
Lecturer Wibke Derboven
Language DE
Cycle SoSe
Content

The seminar will present basic elements of personality-promoting work organisation, motivation theories, different management concepts, communication theories and approaches to conflict and knowledge management. These subjects are applied to specific practical examples. Participants are given the opportunity to reflect on their own communicative and social behaviour.


Literature

Große Boes, Stefanie; Kaseric, Tanja (2010): Trainer-Kit. Die wichtigsten Trainings-Theorien, ihre
Anwendung im Seminar und Übungen für den Praxistransfer. 4. Aufl. Bonn: managerSeminare
Verlags GmbH
Klutmann, Beate (2004): Führung: Theorie und Praxis. Hamburg: Windmühle
Laufer, Hartmut (2011): Grundlagen erfolgreicher Mitarbeiterführung. Führungspersönlichkeit,
Führungsmethoden, Führungsinstrumente. 11. Auflage. Offenbach: GABAL
Neuberger, Oswald (2002): Führen und führen lassen. 6. überarb. und erw. Aufl. Stuttgart: Lucius und
Lucius
Schulz von Thun, Friedemann; Ruppel, Johannes; Stratmann, Roswitha (2002): Miteinander reden:
Kommunikationspsychologie für Führungskräfte. 4. Aufl. Reinbek bei Hamburg

Course L1883: Guest, barbarian or subject with equal rights? ‘The refugee’ in the history of ‘Western’ political ideas.
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 5-10 Minuten Vortrag im Rahmen eines Gruppenreferats; anschließend Diskussion
Lecturer Dr. Simone Beate Borgstede
Language DE/EN
Cycle WiSe/SoSe
Content

The seminar discusses concepts of ‘the refugee’ in the history of ‘Western’ political ideas over a period of about 2,750 years. We will try to understand these concepts as historically distinct. We will also analyze the powerful effect of related stereotypes and images.  We will read and contextualize philosophical, sociological, juridical, literary and political texts. In the second part of the seminar we will use the patterns we found to understand actual discourses on flight and migration. One aim is also to recognize alternative representations in the articulations and practices of the refugees themselves.

Literature

Agamben, Giorgio, ‚Homo Sacer: Die souveräne Macht und das nackte Leben.’

Arendt, Hannah, ‚Wir Flüchtlinge’ und ‚Das Recht, Rechte zu haben’.

Aristoteles, Politik und Platon, Politeia (Auszüge).

Derrida, Jacques, ‚Weltbürger aller Länder, noch eine Anstrengung!’

Erpenbeck, Jenny: Gehen, ging, gegangen. Roman.

Genfer Konvention und Menschenrechtserklärung.

Homer, Die Odyssee.

Simmel, Georg, ‚Exkurs über den Fremden’.

Dazu kommen Textstellen aus Bibel und Koran, aktuelle Interviews mit Migrationsforscher_innen wie Manuela Bojadzijev und Vassilis Tsianos, aber auch Erklärungen von Geflüchteten-Gruppen, Musiktexte, Fotographien und Filmspots.

Course L1844: Stay cool in conflict. Nonviolent Communication by Marshall Rosenberg
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 2-3 Seiten bzw. 10-20 Minuten plus anschließende Besprechung
Lecturer Dr. Claudia Wunram
Language EN
Cycle WiSe/SoSe
Content

„Words can build bridges or create rafts“ - this is also true for the scientific and business world. For example, how do I react if I get attacked in a professional debate by an opponent or by a colleague in my team, or if a fight arises during the planning of a project? In a challenging situation, what will help me to communicate respectfully and with appreciation? How can I express criticism or irritation honestly, directly and without reproach? 

Nonviolent Communication is a concept developped by Marshall B. Rosenberg, Ph.D., intended to help create an appreciative attitude towards oneself and others, and to live by it. Nonviolent Communication opens paths to express oneself in a mindful and responsible way, so that a bridge can be built even in challenging situations of conflict. Effective and satisfactory cooperation is only possible with well functioning communication between all parties involved, otherwise things will become difficult and inefficient.

By working with their own examples and anticipating questions that might arise in their future professional lives, the students of Engineering Sciences will be able to reflect their own communicative behavior and learn ways of cooperation and conjoint solution finding. This course will impart the essential competencies of communication necesary for that.

Literature German:
  • Rosenberg, Marshall.  (2001) Gewaltfreie Kommunikation. Eine Sprache des Lebens. Junfermann
  • Rosenberg, Marshall B. und Seils, Gabriele. (15. Auflage 2012) Konflikte lösen durch Gewaltfreie Kommunikation. Ein Gespräch mit Gabriele Seils. Herder Taschenbuch
  • Larsson, Liv. (2013) 42 Schlüsselunterscheidungen in der GFK. Für ein tieferes Verständnis der Gewaltfreien Kommunikation. Junfermann
  • De Haen, Nayoma V. und Torsten Hardieß. (2015) 30 Minuten Gewaltfreie Kommunikation. Gabal
  • Connor, Jane M. und Killian, Dian, Drs. (2014) Verbindung herstellen - Trennendes überbrücken. Mit jedermann, jederzeit und überall eine gemeinsame Ebene finden. Praktische GFK für den Alltag. Junfermann
  • Dietz, Angela. (2015) Macht ohne Machtwort. Verantwortung übernehmen, Potenziale entfalten. Business Village
  • Miyashiro, Marie R. (2013) Der Faktor Empathie. Ein Wettbewerbsvorteil für Teams und Organisationen. Junfermann
  • Brüggemeier, Beate. (2010) Wertschätzende Kommunikation im Business. Wer sich öffnet, kommt weiter. Wie Sie die GFK im Berufsalltag nutzen. Junfermann
  • Heim, Vera und Lindemann, Gabriele. (2016) Beziehungskompetenz im Beruf. Brücken bauen mit Empathie und Gewaltfreier Kommunikation. Haufe Taschen Guide

English:

  • Rosenberg, Marshall B., Ph.D. (3rd Edition 2015) Nonviolent Communication: A Language of Life. Create your Life, your Relationships, and your World in Harmony with your Values. Puddledancer Press
  • Connor, Jane, Ph.D. and Killian, Dian, Ph.D. (2nd edition 2012) Connecting Across Differences: Finding Common Ground with Anyone, Anywhere, Anytime. Puddledancer Press
  • Miyashiro, Marie R. (2011) The Empathy Factor. Your Competitive Advantage for Personal, Team and Business Success. Puddledancer Press
  • Roele, Hugo and Rich-Tolsma, Matthew, Drs. (2015) The Book of Needs. A Structural Model for Listening. Kommunikasie.nl
  • Kashtan, Miki. (2014) Reweaving our Human Fabric. Working Together to Create a Nonviolent Future. Fearless Heart Publications


Course L2345: Theory, Research and Practice of University Teaching
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Fachtheoretisch-fachpraktische Arbeit
Examination duration and scale Schriftliche Ausarbeitung (in mehreren Teilen) sowie eine Präsentation
Lecturer Prof. Christian Kautz, Jenny Alice Rohde
Language DE
Cycle WiSe/SoSe
Content

This course covers theory and practice of being a student teaching assistant in small-group instructional settings at TUHH.  As part of the seminar, the participants have the opportunity to reflect on their work, e. g. through mutual observation and discussion.

For prior knowledge / the event requirements:

This event requires basic first work / collaboration experiences in the academic work structures of a higher education institution, which Master's students have acquired as part of the qualification for the Bachelor's degree at a university.

These presumed work experiences include specific self-study experiences at a college.

These are picked up, reflected, expanded and further developed both theoretically and practically with regard to learning from and in groups and later guiding this learning process.

Furthermore, experiences with different types of learning / group types of higher education, which are part of a degree program acquired during the bachelor's program, are assumed, taken up, reflected on, expanded and further developed here in the master's program.

The course also requires basic knowledge of presenting scholarly work results obtained by Master's students with a Bachelor's degree.

In the course, this experience with and in representation in a group situation will be expanded and further developed in the direction of students' involvement with their own role as well as their design in face-to-face interaction as well as in group processes, learning and leadership situations, as masters graduates Graduate unlike bachelor graduates professionally stronger in a moderating role and with the guidance of humans because with the guidance in subject matters are demanded.

According to the later professional role, the work of the seminar promotes and enables graduate students significantly more than graduates' qualifications for independent work and learning, transferring what they have learned to new areas, contributing, involving discussion and contributing their own examples and interests.

Literature

Auszüge aus Fachliteratur zu oben genannten Themen werden in der Veranstaltung ausgegeben.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.

Bosse, E. (2016). Herausforderungen und Unterstützung für gelingendes Studieren: Studienanforderungen

und Angebote für den Studieneinstieg. In I. van den Berk, K. Petersen, K. Schultes, &

K. Stolz (Hrsg.). Studierfähigkeit - theoretische Erkenntnisse, empirische Befunde und praktische

Perspektiven (Bd. 15). (S.129-169). Hamburg: Universität Hamburg.

Collins, D. & Holton, E. (2004). The effectiveness of managerial leadership development programs: A meta-analysis of studies from 1982 to 2001. Human resource development quarterly, 15(2),

217 - 248.

Danielsiek, H., Hubwieser, P., Krugel, J., Magenheim, J., Ohrndorf, L., Ossenschmidt, D., Schaper,

N. & Vahrenhold, J. (2017). Verbundprojekt KETTI: Kompetenzerwerb von Tutorinnen und Tutoren in der Informatik. In A. Hanft, F. Bischoff, B. Prang (Hrsg.), Working Paper Lehr-/Lernformen. Perspektiven aus der Begleitforschung zum Qualitätspakt Lehre. Abgerufen von KoBF:

Freeman, S., Eddy, SL., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H. & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematic.

Proceedings of the National Academy of Sciences 11(23), 8410-8415.

Glathe, A. (2017). Effekte von Tutorentraining und die Kompetenzentwicklung von MINTFachtutor*

innen in Lernunterstützungsfunktion. (Nicht veröffentlichte Dissertation). Technische

Universität Darmstadt, Deutschland.

Kirkpatrick, D. L. (1959). Techniques for Evaluation Training Program. Journal of the American Society

of Training Directors, 13, 21-26.

Hänze, M. Fischer, E. Schreiber, Biehler, R. & Hochmuth, R- (2013). Innovationen in der Hochschullehre:

empirische Überprüfung eines Studienprogramms zur Verbesserung von vorlesungsbegleitenden

Übungsgruppen in der Mathematik. Zeitschrift für Hochschulentwicklung, 8(4), 89-

103.

Kröpke, H. (2014). Who is who? Tutoring und Mentoring - der Versuch einer begrifflichen Schärfung.

In D. Lenzen & H. Fischer (Hrsg.), Tutoring und Mentoring unter besonderer Berücksichtigung

der Orientierungseinheit (Bd. 5). (21-29). Hamburg: Universitätskolleg-Schriften.

Kühlmann, T. (2007). Fragebögen. In J. Straub, A. Weidemann & D. Weidemann (Hrsg.), Handbuch

interkulturelle Kommunikation und Kompetenz (346-352). Stuttgart: Metzler.

Mayring, P. (2010). Qualitative Inhaltsanalyse. Grundlagen und Techniken (11. aktualisierte und überarbeitete

Auflage). Weinheim/Basel: Beltz.

Mummendey, H. D. (1981). Methoden und Probleme der Kontrolle sozialer Erwünschtheit (Social

Desirability). Zeitschrift für Differentielle und Diagnostische Psychologie, 2, 199-218.

Rohde, J. & Block, M. (2018). Welche Herausforderungen und Bewältigungsstrategien berichten

Tutor/innen der Ingenieurwissenschaften? Eine explorative Analyse von Reflexionsberichten. Vortrag

auf der 47. Tagung der Deutschen Gesellschaft für Hochschuldidaktik, Karlsruhe.

Heterogenität der Studierenden und Lösungsansätze von Tutor/-innen

Jenny Alice Rohde. Posterpräsentation auf der Tagung “Tutorielle Lehre und Heterogenität”. Technische Universität Darmstadt, 16.05.2019.Hochschuldidaktische Tutorenqualifizierung - Eine Basisqualifizierung des akademischen Nachwuchses und Chance für den Wandel der Lehr-/Lernkultur?

Jenny Alice Rohde & Caroline Thon-Gairola. Posterpräsentation auf der DGHD am 07.03.2019.Welches Lehrverhalten zeigen geschulte Tutor/innen? Eine explorative Analyse selbst- und fremdwahrnehmungsbasierter Reflexionsberichte

Jenny Alice Rohde & Nadine Stahlberg. In: die hochschulehre (2019).

Schneider, M. & Preckel, F. (2017). Variables associated with achievement in higher education: A

systematic review of meta-analyse. Psychological Bulletin, 143(6), 565-600.

Skylar Powell, K. & Yalcin, S. (2010). Managerial training effectiveness: A meta-analysis 1952-2002.

Personnel Review, 39(2), 227-241.

27 Welches Lehrverhalten zeigen geschulte Tutor/innen

d ie hochs chul l ehre 2019 www.hochschullehre.org

Stes, A., Min-Leliveld, M., Gijbels, D. & Van Petegem, P. (2010). The impact of instructional development

in higher education: The state-of-the-art of the research. Educational Research Review,

5(1), 25-49.

Stroebe, W. (2016). Why Good Teaching Evaluations May Reward Bad Teaching: On Grade Inflation

and Other Unintended Consequences of Student Evaluation. Perspectives on Psychological Science,

11(6), 800-816.

Technische Universität Hamburg (2018). Kennzahlen 2017. Hamburg: Technische Universität Hamburg.

[https://www.tuhh.de/tuhh/uni/informationen/kennzahlen.html]

Thumser-Dauth, K. (2008). Und was bringt das? Evaluation hochschuldidaktischer Weiterbildung.

In B. Berendt, H.-P. Voss & J. Wildt (Hrsg.), Neues Handbuch Hochschullehre. Lehren und Lernen

effizient gestalten. Kap. L 1.11 Hochschuldidaktische Aus- und Weiterbildung. Veranstaltungskonzepte

und -modelle. Berlin: Raabe. S. 1-10.

Wibbecke, G. (2015): Evaluation einer hochschuldidaktischen Weiterbildung an der Medizinischen

Fakultät Heidelberg. Dissertation. Ruprecht-Karls-Universität Heidelberg.

Willige, J., Woisch, A., Grützmacher, J. & Naumann, H. (2015a). Randauszählung Studienqualitätsmonitor

2014, Technische Universität Hamburg-Harburg, Online-Befragung Studierender im

Sommersemester 2014, DZHW - Deutsches Zentrum für Hochschul- und Wissenschaftsforschung.

Willige, J., Woisch, A., Grützmacher, J. & Naumann, H. (2015b). Randauszählung Studienqualitätsmonitor

2015, Technische Universität Hamburg-Harburg, Online-Befragung Studierender im

Sommersemester 2015, DZHW - Deutsches Zentrum für Hochschul- und Wissenschaftsforschung.

Winkler, M. (2018). Tutorielle Lehransätze im Vergleich. Die KOMPASS Begleitforschung. Vortrag

gehalten am 12.03.2018 auf dem Netzwerktreffen Tutorienarbeit an Hochschulen in Würzburg.

Zech, F. (1977). Grundkurs Mathematikdidaktik: theoretische und praktische Anleitungen für das

Lehren und Lernen im Fach Mathematik. Weinheim: Beltz.

Course L1509: Intercultural Communication
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Prof. Margarete Jarchow, Anna Katharina Bartel
Language EN
Cycle WiSe/SoSe
Content

As young professionals with technical background you may often tend to focus on communicating numbers and statistics in your presentations. However, facts are only one aspect of convincing others. Often, your personality, personal experience, cultural background and emotions are more important. You have to convince as a person in order to get your content across.

In this workshop you will learn how to increase and express your cultural competence. You will apply cultural knowledge and images in order to positively influence communicative situations. You will learn how to add character and interest to your talks, papers and publications by referring to your own and European Cultural background. You will find out the basics of communicating professionally and convincingly by showing personality and by referring to your own cultural knowledge. You will get hands-on experience both in preparing and in conducting such communicative situations. This course is not focussing on delivering new knowledge about European culture but helps you using existing knowledge or such that you can gain e.g. in other Humanities courses.

Content

  • How to enrich the personal character of your presentations by referring to European and your own culture.
  • How to properly arrange content and structure.
  • How to use PowerPoint for visualization (you will use computers in an NIT room).
  • How to be well-prepared and convincing when delivering your thoughts to your audience.
Literature

Literaturhinweise werden zu Beginn des Seminars bekanntgegeben.

Literature will be announced at the beginning of the seminar.

Course L2015: Intercultural Management - Theory and Awareness Training
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Schriftliche Ausarbeitung
Examination duration and scale 15 Minuten Vortrag und dessen schriftliche Ausarbeitung (10 Seiten)
Lecturer Prof Jürgen Rothlauf
Language EN
Cycle WiSe/SoSe
Content

The subject of the course is the deepening of the intercultural dimension of international management in relation to fundamental challenges, the importance of culture in team work and leadership of large multinational companies. In addition, culture-awareness trainings are discussed and carried out.

Literature

Rothlauf, J (2014): A Global View on Intercultural Management - Challenges in a Globalized World, De Gruyter Oldenbourg Verlag, 360 p

Course L2346: Young, educated, (non)political - are our young engineers well prepared for the future?
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Vincent-Immanuel Herr
Language DE
Cycle WiSe/SoSe
Content

Digitalization, climate change, democracy - society is facing fundamental upheavals. The next generation of young engineers in particular must no longer remain out of debate and can provide answers to the big questions of our time. Why is social commitment important? Is studying preparing us well for the future? What needs to improve? In the interactive workshop, the participants will be accompanied in analyzing their own generation and their own actions and in developing thesis on how to improve technical studies and training. The result of the seminar will be a joint thesis paper.

Literature
Wird im Seminar bekannt gegeben.
Course L2176: Culture of Communication - Theories and Methods of Successful Communication
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Anna Katharina Bartel
Language DE
Cycle WiSe/SoSe
Content

This course is for master students. In this seminar, we will explore different theories, models and methods from the fields of communication, psychology and cultural theory.

The participants will work on theoretical content and do group presentations. They will also use examples from their own experiences to apply models and methods in practical exercises.

The way we communicate shapes the way we experience our relationships, in the business world as well as in our private lives. We spend an overwhelming amount of time in group situations. This makes it worthwhile to explore how communication works within the group context and how, within these different groups, different cultures of communication develop. This particularly applies in highly specialized fields, such as engineering.

Our ability to flexibly and successfully move from one context to another helps us along in building successful careers and allows us to feel positive about our private lives.

However, this is not always simple. For example:

            If we are part of a context in which many conflicts arise

            If we have to switch between different contexts frequently

            Or if, on the one hand, complicated facts and data are our main focus but on the other hand, we have to communicate them to people who are not familiar with the subject. Maybe we even have to win their attention in order to help along our causes.

Oftentimes, this leads to misunderstandings. There also might be a lack of openness or willingness to embrace conflict. This might make it difficult for us to reach our goals. To be able to reflect on the way we communicate, to identify patterns of communication and the ability to actively build positive relationships through communication are useful skills to help overcome those obstacles..

Literature
  • Knoblauch, H. (1995). Kommunikationskultur: Die kommunikative Konstruktion kultureller Kontexte (Materiale Soziologie, Band 5). de Gruyter.
  • Geert Hofstede, Geert Jan Hofstede, Michael Minkov. (2010). Cultures and Organizations - Software Of The Mind:Intercultural Cooperation and Its Importance for Survival. McGraw-Hill Education.
  • Bay, Rolf H. (2006) Erfolgreiche Gespräche durch aktives Zuhören. Ehningen. Expert-Verlag.
  • Cohn, Ruth (1975). Von der Psychoanalyse zur Themenzentrierten Interaktion. Stuttgart. Klett - Cotta
  • Fengler, Jörg (1998) Feedback geben. Weinheim. Beltz.
  • Lumma, Klaus (2006). Die Teamfibel oder das Einmaleins der Team- & Gruppenqualifizierung im sozialen und betrieblichen Bereich. Windmühle.
  • Spies, Stefan. (2010). Der  Gedanke lenkt den Körper: Körpersprache - Erfolgsstrathegien eines Regisseurs. Hoffmann und Campe.
Course L0535: Theory of Communication
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale 20-30 Minuten Referat und Thesenpapier
Lecturer Dr. Michael Florian
Language DE
Cycle SoSe
Content

The seminar focuses on sociological theories of communication and selected problems of practical application in the area of crisis communication. The issue of crisis communication will be analyzed on the basis of case studies.

Literature

Habermas, Jürgen (1981): Theorie des kommunikativen Handelns. 2 Bände. Frankfurt/Main: Suhrkamp.
Luhmann, Niklas (1984): Soziale Systeme. Grundriß einer allgemeinen Theorie. Frankfurt/Main: Suhrkamp.
Malsch, Thomas (2005): Kommunikationsanschlüsse. Zur soziologischen Differenz von realer und künstlicher Sozialität. Wiesbaden: VS Verlag für Sozialwissenschaften.
Malsch, Thomas; Schmitt, Marco (Hg.) (2014): Neue Impulse für die soziologische Kommunikationstheorie. Empirische Widerstände und theoretische Verknüpfungen. Springer Fachmedien: Wiesbaden.
Meckel, Miriam; Schmid, Beat F. (Hg.) (2008): Unternehmenskommunikation. Kommunikationsmanagement aus Sicht der Unternehmensführung. 2., überarbeitete und erweiterte
Auflage. Gabler GWV Fachverlage: Wiesbaden.
Merten, Klaus (1999): Einführung in die Kommunikationswissenschaft. Bd 1/1: Grundlagen der Kommunikationswissenschaft. Münster: Lit Verlag.
Nolting, Tobias; Thießen, Ansgar (Hg.) (2008): Krisenmanagement in der Mediengesellschaft. Potenziale und Perspektiven der Krisenkommunikation. Wiesbaden: VS Verlag für Sozialwissenschaften.
Schützeichel, Rainer (2004): Soziologische Kommunikationstheorien. Konstanz: UVK Verlagsgesellschaft.
Thießen, Ansgar (2011): Organisationskommunikation in Krisen. Reputationsmanagement durch situative, integrierte und strategische Krisenkommunikation. VS Verlag für Sozialwissenschaften/Springer Fachmedien: Wiesbaden.
Thießen, Ansgar (Hg.) (2013): Handbuch Krisenmanagement. Springer Fachmedien: Wiesbaden.

Course L1732: criminology and society - in German
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale Gruppenreferat (30 bis 45 Minuten, Eigenanteil je Person 10 bis 15 Minuten) inkl. schriftlicher Ausarbeitung, Ggf. alternativ eine längere, schriftliche Ausarbeitung.
Lecturer Sarah Schirmer
Language DE
Cycle WiSe/SoSe
Content

The seminar will provide an overview of Criminology and introduce different
theories of criminality. It is necessary to consider the discipline of Criminology
within its historical context in order to understand how some theories have
evolved. The students will use this knowledge of Criminology theory to discuss
and consider the advantages and disadvantages of each theory. Discussions
will include how society constructs crime as well as a more philosophical
debate about a determined view.

Literature

Wird zeitnah bekannt gegeben.

Will be announced in lecture.
Course L2369: Literature and Culture for international students of Master's degree programs in English (non-native speakers of German)
Typ Seminar
Hrs/wk 4
CP 4
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
Examination Form Referat
Examination duration and scale 45 min. Präsentation und anschließende Diskussion
Lecturer Bertrand Schütz
Language DE
Cycle WiSe/SoSe
Content

The seminar LITERATURE AND CULTURE investigates what culture is, especially what characterises epistemic cultures.

Culture is to be understood as the creative response to a given situation and the capacity to integrate inputs and influences, therefore as an ongoing process of permanent readjustment and learning, and by no means as a fixed identity in terms of an “essence”.

There is a growing awareness that Europe cannot lay claim to possess the ultimate standards of knowledge.

A topography of our contemporary world is to be sketched by highlighting its historical and cultural premises.

For more information please refer to the German description and the StudIP.

Literature

Je nach Thematik des Semesters wird eine spezifische
Literatur-Liste erstellt.

cf. StudIP

Course L1837: People in Business Organizations
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Schriftliche Ausarbeitung
Examination duration and scale Schriftliche Hausarbeit 7-10 Textseiten; verpflichtend: Präsentation der Zwischenergebnisse mit Diskussion (geht nicht in die Bewertung mit ein)
Lecturer Dr. Martin Schütz
Language DE
Cycle WiSe/SoSe
Content

The influence of technological change and social change on business organizations - how to manage the organizational change.

Literature

Becker, Karen Louise (2007): Unlearning in the workplace. A mixed methods study. PhD. Queensland University of Technology, Brisbane. Faculty of Education. Online verfügbar unter http://eprints.qut.edu.au/16574/.

Frey, Dieter; Gerkhardt, Marit; Peus, Claudia; Traut-Mattausch, Eva; Fischer, Peter (2014): Veränderungen managen. Widerstände und Erfolgsfaktoren der Umsetzung. In: Lutz von Rosenstiel, Erika Regnet und Michel E. Domsch (Hg.): Führung von Mitarbeitern. Handbuch für erfolgreiches Personalmanagement. 7. Aufl. Stuttgart: Schäffer-Poeschel, S. 547-559.

Hauser, Berndhard (2014): Konflikte in und zwischen Gruppen. In: Lutz von Rosenstiel, Erika Regnet und Michel E. Domsch (Hg.): Führung von Mitarbeitern. Handbuch für erfolgreiches Personalmanagement. 7. Aufl. Stuttgart: Schäffer-Poeschel, S. 354-367.

Kieser, Alfred; Walgenbach, Peter (2007): Organisation. 5. Aufl. Stuttgart: Schäffer-Poeschel.

Miebach, Bernhard (2012): Organisationstheorie. Problemstellung - Modelle - Entwicklung. 2. Aufl. Wiesbaden: Springer Fachmedien Wiesbaden; Imprint: Springer VS.

Müller, Ursula (Hg.) (2013): Geschlecht und Organisation. Wiesbaden: Springer VS (Geschlecht und Gesellschaft, 45).

Olfert, Klaus (2012): Organisation. 16. Aufl. Herne: NWB Verlag.

Pohlmann, Markus; Markova, Hristina (2011): Soziologie der Organisation. Eine Einführung. Konstanz, München: UVK-Verl.-Ges. (3573).

Preisendörfer, Peter (2011): Organisationssoziologie. Grundlagen, Theorien und Problemstellungen. 3. Aufl. Wiesbaden: VS Verlag für Sozialwissenschaften.

Robbins, Stephen P.; Judge, Timothy A. (2013): Organizational Behavior. 15. Aufl. Boston, Mass: Pearson.

Rosenstiel, Lutz von; Nerdinger, Friedemann W. (2011): Grundlagen der Organisationspsychologie. Basiswissen und Anwendungshinweise. 7. Aufl. Stuttgart: Schäffer-Poeschel.

Sanders, Karin; Kianty, Andrea (2006): Organisationstheorien. Eine Einführung. 1. Aufl. Wiesbaden: VS Verlag für Sozialwissenschaften.

Schreyögg, Georg (2008): Organisation. Grundlagen moderner Organisationsgestaltung, mit Fallstudien. 5. Aufl. Wiesbaden: Gabler (Lehrbuch).

Vahs, Dietmar (2012): Organisation. Ein Lehr- und Managementbuch. 8. Aufl. Stuttgart: Schäffer-Poeschel.

Weinert, Ansfried B. (2004): Organisations- und Personalpsychologie. 5. Aufl. Weinheim: BeltzPVU.


Course L1846: Classical Journalism and New Media
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale Ca. 20 min. plus anschließende Diskussion
Lecturer Dieter Bednarz
Language DE
Cycle WiSe/SoSe
Content

The world wide walkover of the internet dramatically changed the perception of classical media like newspapers, magazines and even TV. In this seminar the reasons of and the consequences for the dramatic changes regarding our information habits will be analyzed and discussed. Has the media expert Neil Postman been right, when he one said, that we all one day will be „overnewsed but underinformed“?

Keeping a close eye on the real challenges of journalism, the seminar will discuss the standards of ethics in politics and media.


Literature

Wird im Seminar genannt

Course L1023: Politics
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dr. Stephan Albrecht
Language EN
Cycle WiSe/SoSe
Content

Scientists and engineers neither just strive for truths and scientific laws, nor are they working in a space far from politics.  Science and engineering have contributed to what we now call the Anthropocene, the first time in the history of mankind when essential cycles of the earth system, e.g. carbon cycle, climate system, are heavily influenced or even shattered. Furthermore, Peak oil is indicating the end of cheap fossil energy thus triggering the search for alternatives such as biomass.

Systems of knowledge, science and technology in the OECD countries have since roughly 30 years increasingly become divided. On the one hand new technologies such as modern biotechnology, IT or nanotechnology are developing rapidly, bringing about many innovations for industry, agriculture, and consumers. On the other hand scientific studies from earth, environmental, climate change, agricultural and social sciences deliver increasingly robust evidence on more or less severe impacts on society, environment, global equity, and economy resulting from innovations during the last 50 years. Technological innovation thus is no longer an uncontested concept. And many protest movements demonstrate that the introduction of new or the enlargement of existing technologies (e.g. airports, railway stations, highways, high-voltage power lines surveillance) isn’t at all a matter of course.

It is important to bear in mind the fact that all processes of technological innovation are made by humans, individually and collectively. Industrial, social, and political organizations as actors from the local to global level of communication, deliberation, and decision making interact in diverse arenas, struggling to promote their respective corporate and/or political agenda. So innovations are as well a problem of technology as a problem of politics. Innovation and technology policies aren’t the same in all countries. We can observe conceptual and practical variations.

Since the 1992 Earth Summit in Rio de Janeiro Agenda 21 constitutes a normative umbrella, indicating Sustainable Development (SD) as core cluster of earth politics on all levels from local to global. Meanwhile other documents such as the Millennium Development Goals (MDG) have complemented the SD agenda. SD can be interpreted as operationalization of the Universal Declaration of Human Rights, adopted in 1948 by the General Assembly of the United Nations and since amended many times. 

Engineers and scientists as professionals can’t avoid to become confronted with many non-technical and non-disciplinary items, challenges, and dilemmas. So they have to choose between alternative options for action, as individuals and as members of organizations or employees. Therefore the seminar will address core elements of the complex interrelations between science, society and politics. Reflections on experiences of participants - e.g. from other countries as Germany - during the seminar are very welcome.

The goals of the seminar include:

  • Raising awareness and increasing knowledge about the political implications of scientific work and institutions;
  • Improving the understanding of different concepts and designs of innovation and technology policies;
  • Increasing knowledge about the status and perspectives of sustainable development as framework concept for technological and scientific progress;
  • Understanding core elements of recent arguments, conflicts, and crises on technological innovations, e.g. geo-engineering or bio-economy;
  • Improving the understanding of scientists’ responsibility for impacts of their professional activities;
  • Embedding individual professional responsibility in social and political contexts.

The seminar will deal with current problems from areas such as innovation policy, energy, food systems, and raw materials. Issues will include the future of energy, food security and electronics. Historical issues will also be addressed.

The seminar will start with a profound overarching introduction. Issues will be introduced by a short presentation and a Q & A session, followed by group work on selected problems. All participants will have to prepare a presentation during the weekend seminar. The seminar will use inter alia interactive tools of teaching such as focus groups, simulations and presentations by students. Regular and active participation is required at all stages.


Literature Literatur wird zu Beginn des Seminars abgesprochen.
Course L1856: Politics and Science - in German
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale Referat ca. 20 min. plus anschließende Diskussion
Lecturer Dr. Mirko Himmel, Dr. Ines Krohn-Molt
Language DE
Cycle WiSe/SoSe
Content

Scientists often like to believe that their work is non-political. Within this seminar we want to demonstrate how deeply both are interconnected and converged. Not only, scientific guidance is often needed to take a political decision but also scientific outcomes are a sub-ject to political interpretation. Also, politics are significantly influencing scientific progress by framing research agendas and by funding decisions.

Literature

Wird im Seminar genannt

Course L1779: Politics and Science - in English
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dr. Frederik Postelt, Dr. Gunnar Jeremias
Language EN
Cycle WiSe/SoSe
Content

Scientists often like to believe that their work is non-political. Within this seminar we want to demonstrate how deeply both are interconnected and converged. Not only, scientific guidance is often needed to take a political decision but also scientific outcomes are a sub-ject to political interpretation. Also, politics are significantly influencing scientific progress by framing research agendas and by funding decisions.

During this seminar we would like to show the different range of influences - scientific, economic, social, environmental, ethical/normative, security-related - affecting decision-making on science and politics. Using case studies on current debates on food security, public health, nuclear energy and terrorism to discuss the interrelation between science and politics illuminating the role of various actors in this process, such as:

• Governments,

• International organizations,

• Scientific associations,

• Industry,

• Civil society, and

• Individual scientists.

The guiding questions will be:

• How does and should science influence politics?

• How does and should politics influence science?

In order to take responsibility for the consequences of scientific work, engineers and scientists increasingly need to acknowledge the political dimension of their work and their role in the political process. We will address this political dimension of scientific work by discussing:

• Biographies and motivations of famous scientists,

• Individual responsibility of scientists for the implications of their work, and

• The role of codes of conduct as guidelines for responsible behaviour.

The goals of the seminar include:

• Raising awareness and increasing knowledge about the political dimensions of scientific work,

• Providing guidelines for evaluating political implications of scientific research,

• Improving the understanding of scientists’ and engineers’ responsibility for the results of their professional activities,

• Taking decisions at the institutional, national and international level about rules and regulations concerning scientific conduct, and

• Choosing arguments and defending positions in situations of conflicting interests.

The seminar will use current issues, such as dilemmas in the life sciences or bio fuels to demonstrate the problematic relationship between science and politics. The seminar, however, does not focus on providing in-depth knowledge of these current issues. We strongly discourage students that have participated in an “Ethics for Engineers” seminar to take this course, because the contents of the two seminars overlap.

Issues will be introduced by short presentations and a Q&A session, followed by group work on selected problems. All participants will have to prepare a presentation. Those requiring a graded certificate (“Schein”) additionally have to write a 3-4 page paper on selected issues. The seminar will use interactive tools of teaching such as role playing and simulations. Group work and active participation is expected at all stages of the seminar.

Literature

will be announced in lecture

wird im Seminar bekannt gegeben

Course L1734: Projectrealisation: TUHH goes circular - Sustainability in Research, Education and campus management
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale
Lecturer Prof. Kerstin Kuchta
Language EN
Cycle WiSe/SoSe
Content
Literature

Wird im Seminar bekanntgegeben

Will be announced in lecture.

Course L1872: Social Learning: Social Commitment in Refugee Issues / Master
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Schriftliche Ausarbeitung
Examination duration and scale 10 Seiten
Lecturer Muthana Al-Temimi
Language DE
Cycle WiSe/SoSe
Content folgt
Literature

Wird im Seminar bekannt gegeben.

Will be announced in lecture.

Course L1647: Soft skill seminar for dual study programme (dual@TUHH) / Master
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale Referat mit 2-3 Videoübungen à 20 Minuten + anschließende Diskussion
Lecturer Silke Wolckenhaar-Wagner, Dr. Henning Haschke
Language DE
Cycle WiSe/SoSe
Content
Literature
Course L1771: The Arabic Spring an its Consequences
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dieter Bednarz
Language DE
Cycle WiSe/SoSe
Content

The world wide walkover of the internet dramatically changed the perception of classical media like newspapers, magazines and even TV. In this seminar the reasons of and the consequences for the dramatic changes regarding our information habits will be analyzed and discussed:

Taking a close look at the Middle East the political impact of the new media´s triumphal procession will be assessed and evaluated. How come that Twitter and Facebook on one hand facilitated the so called Arabic  Spring and caused hope for the rise of democracy in the region, while on the other hand the revolutionaries failed so dramatically - at least for now.

Keeping a close  eye on both fields, the Media and the Middle East, the seminar will discuss the standards of ethics in politics and journalism.

Literature

Wird im Seminar angegeben und besprochen.

Will be announced in the lecture.

Course L1916: Responsible Conduct in Technology & Science
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dr. Mirko Himmel, Dr. Ines Krohn-Molt
Language DE
Cycle WiSe/SoSe
Content

Aim of the seminar is raising awareness for the responsibility of engineers and researchers for a proper and ethical conduct in technology and science. The Participants will present and discuss practical examples for good as well as bad conduct in science.


Literature folgt im Seminar
Course L1991: What can philosophy do?
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dr. Ursula Töller
Language DE
Cycle WiSe/SoSe
Content

Over the centuries, the philosophy is lined up as a discipline that provides complex and universal answers to contemporary history and circumstances. Often, she could design utopias that have led the way for political upheaval. While all scientific disciplines are subject to an increasing differentiation, the philosophy in the second half of the 20th century has lost its claim to universality. But what then are the topics of the philosophy of the 20th and 21st century and what impact have philosophical theories for processes of change?

We will provide an overview of Western philosophies of the 20th and 21st century. and take a critical look at the self-understanding of philosophy.

Literature

Gerhardt Schweppenhäuser: Kritische Theorie, Stuttgart 2010

Postmoderne und Dekonstruktion, Texte französischer Philosophen der Gegenwart, hrsg. von Peter Engelmann, Reclam UB 8668

Thomas Rentsch: Philosophie des 20. Jhdts. Von Husserl bis Derrida, München 2014

Geschichte der Philosophie in Text und Darstellung, Bd. 8=20 Jhdt.

Reclam UB 9918

Geschichte der Philosophie in Text und Darstellung, Bd. 9= Gegenwart

Reclam UB 18267

Course L2343: Academic Writing and Presentation for Master-Students
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Referat
Examination duration and scale etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion
Lecturer Dr. Ursula Töller
Language DE
Cycle WiSe/SoSe
Content

The course is aimed at Master students who are planning to write their thesis, want to pursue their PhD or intend to present their research results at conferences and in journals. The course is structured on three levels: 1. writing, 2. presenting and 3. interacting in organizational structures. The latter refers to the work environment at university as well as in research groups and enterprises. In the course of the seminar, the participants become acquainted with various methods and theories on the subject. Furthermore, the methods and theories will be put into practice, reflected upon and discussed as part of the seminar.

Literature
  • Umberto Eco, Wie man eine wiss. Abschlussarbeit schreibt (2010)
  • Helga Esselborn-Krumbiegel, Von der Idee zum Text. Eine Anleitung zum wissenschaftlichen Schreiben (2008)
  • Tony Buzan: Das Mind-Map-Buch. (2001)
  • John W. Chinneck: How to organize your Thesis (1999)
  •  Lothar Seiwert: Das neue 1x1 des Zeitmanagements (2003)
  • Steven R. Covey: Die sieben Wege der Effektivität (2000)
  • Harold Kerzner: Twenty Common Mistakes Made by New or Inexperienced Project Manager (2010)
  • Friedemann Schulz von Thun: Miteinander Reden. (1996)

Tim McClintock: Dealing with Specific Types of Difficult People.

(2008)

Course L2029: “Lying press”? Functions and current challenges of journalism
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Examination Form Mündliche Prüfung
Examination duration and scale 20 min
Lecturer Prof. Horst Pöttker
Language DE
Cycle WiSe/SoSe
Content

Lying press - there is a revival of the disparaging invective. Journalists use to shoot it down by leading it back to its supposed roots in the NS-propaganda. This is less convincing as several parties and ideologies have used it since the middle of the 19th century to discredit the media of other parties and ideologies. And it is missing the core of the problem. Critics are reasonably afraid that the choice of “lying press” to the “non-word of the year” 2014 has blocked the question, if there is a justified criticism of information media and journalism - or more precisely of the relationship between journalism and its audience. If this is the case both - journalism and audience - are involved from the perspective of inter actionism.    

Against this background interactive instructions will be given by scholarly literature and practical examples from the German and international media business.

Questions like the following will be discussed:

  • Is journalism really a profession? If so - since when?
  • What is journalism for? (task and duties, functions, self-images)
  • Do the audience and journalists themselves have a reasonable understanding of tasks, functions, practices, problems of journalism?
  • What is the current concept of journalistic professionalism? Has it ever been the same?
  • From an international perspective: Does journalism in Germany have special shortcomings - if so, how can they be removed?
  • What are the economic challenges for journalism from the digital media upheaval?
  • In which direction do journalistic professionalism and self-understanding change in the digital media world?

Objective is solid learning about professional tasks, ethics, techniques, endagerments, history and current problems of journalism including science journalism.

Literature

Zur Einführung:

Lilienthal, Volker/Neverla, Irene (Hrsg.) (2017): „Lügenpresse“. Anatomie eines politischen Kampfbegriffs. Köln: Kiepenheuer & Witsch. https://www.kiwi-verlag.de/buch/luegenpresse/978-3-462-31782-4/

Pöttker, Horst (2010): Der Beruf zur Öffentlichkeit. Über Aufgabe, Grundsätze und Perspektiven des Journalismus in der Mediengesellschaft aus der Sicht praktischer Vernunft. In: Publizistik, 55. Jg., H. 2, S. 107-128. https://www.springerprofessional.de/en/der-beruf-zur-oeffentlichkeit/5889108

Weischenberg, S. (2007): Das Jahrhundert des Journalismus ist vorbei. Rekonstruktionen und Prognosen zur Formation gesellschaftlicher Selbstbeobachtung. In: Bartelt-Kircher, G. et al.: Krise der Printmedien - eine Krise des Journalismus? Berlin und New York, de Gruyter Saur, S. 32-60.

https://medien21.wordpress.com/2011/10/17/weischenberg-das-jahrhundert-des-journalismus-ist-vorbei/

Eine ausführliche Literaturliste wird am Anfang des Seminars verteilt.

Module M0804: Research Project and Seminar

Courses
Title Typ Hrs/wk CP
Project Work (L1761) Projection Course 10 15
Seminar (L0817) Seminar 2 3
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge Basic knowledge and techniques in the chosen field of specialization.
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students are able to acquire advanced knowledge in a specific field of Computer Science or a closely related subject.
Skills Students are able to work self-dependent in a field of Computer Science or a closely related field.
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 372, Study Time in Lecture 168
Credit points 18
Course achievement None
Examination Study work
Examination duration and scale Presentation of a current research topic (25-30 min and 5 min discussion).
Assignment for the Following Curricula Computer Science: Core Qualification: Compulsory
Information and Communication Systems: Core Qualification: Compulsory
Course L1761: Project Work
Typ Projection Course
Hrs/wk 10
CP 15
Workload in Hours Independent Study Time 310, Study Time in Lecture 140
Lecturer Dozenten des SD E
Language DE/EN
Cycle WiSe
Content

Current research topics of the chosen specialization.

Literature

Aktuelle Literatur zu Forschungsthemen aus der gewählten Vertiefungsrichtung.
/
Current literature on research topics of the chosen specialization.

Course L0817: Seminar
Typ Seminar
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des SD E
Language DE/EN
Cycle WiSe
Content
  • Seminar presentations by enrolled students about the research work carried out by the students
  • Active participation in discussions
Literature Wird vom Veranstalter bekanntgegeben.

Specialization Computer and Software Engineering

Module M0753: Software Verification

Courses
Title Typ Hrs/wk CP
Software Verification (L0629) Lecture 2 3
Software Verification (L0630) Recitation Section (small) 2 3
Module Responsible Prof. Sibylle Schupp
Admission Requirements None
Recommended Previous Knowledge
  • Automata theory and formal languages
  • Computational logic
  • Object-oriented programming, algorithms, and data structures
  • Functional programming or procedural programming
  • Concurrency
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students apply the major verification techniques in model checking and deductive verification. They explain in formal terms syntax and semantics of the underlying logics, and assess the expressivity of different logics as well as their limitations. They classify formal properties of software systems. They find flaws in formal arguments, arising from modeling artifacts or underspecification. 

Skills

Students formulate provable properties of a software system in a formal language. They develop logic-based models that properly abstract from the software under verification and, where necessary, adapt model or property. They construct proofs and property checks by hand or using tools for model checking or deductive verification, and reflect on the scope of the results. Presented with a verification problem in natural language, they select the appropriate verification technique and justify their choice.   

Personal Competence
Social Competence

Students discuss relevant topics in class. They defend their solutions orally. They communicate in English. 

Autonomy

Using accompanying on-line material for self study, students can assess their level of knowledge continuously and adjust it appropriately.  Working on exercise problems, they receive additional feedback. Within limits, they can set their own learning goals. Upon successful completion, students can identify and precisely formulate new problems in academic or applied research in the field of software verification. Within this field, they can conduct independent studies to acquire the necessary competencies and compile their findings in academic reports. They can devise plans to arrive at new solutions or assess existing ones. 

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement
Compulsory Bonus Form Description
Yes 15 % Excercises
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems: Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
Course L0629: Software Verification
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle WiSe
Content
  • Syntax and semantics of logic-based systems
  • Deductive verification
    • Specification
    • Proof obligations
    • Program properties
    • Automated vs. interactive theorem proving
  • Model checking
    • Foundations
    • Property languages
    • Tool support
  • Timed automata
  • Recent developments of verification techniques and applications
Literature
  • C. Baier and J-P. Katoen, Principles of Model Checking, MIT Press 2007.
  • M. Huth and M. Bryan, Logic in Computer Science. Modelling and Reasoning about Systems, 2nd Edition, 2004.
  • Selected Research Papers
Course L0630: Software Verification
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1270: Technical Complementary Course I for CSMS (according to Subject Specific Regulations)

Courses
Title Typ Hrs/wk CP
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students acquire advanced knowledge in a technical subject available at TUHH.

Skills

The students acquire professional competence in a technical subject available at TUHH.

Personal Competence
Social Competence
Autonomy
Workload in Hours Depends on choice of courses
Credit points 6
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory

Module M0667: Algorithmic Algebra

Courses
Title Typ Hrs/wk CP
Algorithmic Algebra (L0422) Lecture 3 5
Algorithmic Algebra (L0423) Recitation Section (small) 1 1
Module Responsible Dr. Prashant Batra
Admission Requirements None
Recommended Previous Knowledge

Mathe I-III (Real analysis,computing in Vector spaces , principle of complete induction)  Diskrete Mathematik I (gropus, rings, ideals, fields; euclidean algorithm)

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can discuss logical connections between the following concepts and explain them by means of examples: Smith normal form, Chinese remainder theorem, grid point sets, integer solution of inequality systems.

Skills

Students are able to access independently further logical connections between the concepts with which they have become familiar and are able to verify them.

Students are able to develop a suitable solution approach to given problems, to pursue it and to evaluate the results critically, such as in solving multivariate equation systems and in grid point theory.

Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Course L0422: Algorithmic Algebra
Typ Lecture
Hrs/wk 3
CP 5
Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Lecturer Dr. Prashant Batra
Language DE
Cycle WiSe
Content

Extended euclidean algorithm, solution of the Bezout-equation

Division with remainder (over rings)

 fast arithmetic algorithms (conversion, fast multiplications)

discrete Fourier-transformation over rings

Computation with  modular remainders, solving of remainder systems (chinese remainder theorem), solvability of integer linear systems over the integers

linearization of polynomial equations-- matrix approach

Sylvester-matrix, elimination

elimination in rings, elimination of many variables

Buchberger algorithm, Gröbner basis

Minkowskis Lattice Point theorem and integer-valued  optimization

LLL-algorithm for construction of  'short' lattice vectors in polynomial time

Literature von zur Gathen, Joachim; Gerhard, Jürgen

Modern computer algebra. 3rd ed. (English) Zbl 1277.68002
Cambridge: Cambridge University Press (ISBN 978-1-107-03903-2/hbk; 978-1-139-85606-5/ebook).


Yap, Chee Keng
Fundamental problems of algorithmic algebra. (English) Zbl 0999.68261
Oxford: Oxford University Press. xvi, 511 p. $ 87.00 (2000).


Free download for students from author's website: http://cs.nyu.edu/yap/book/berlin/

Cox, David; Little, John; O’Shea, Donal
Ideals, varieties, and algorithms. An introduction to computational algebraic geometry and commutative algebra. 3rd ed. (English) Zbl 1118.13001
Undergraduate Texts in Mathematics. New York, NY: Springer (ISBN 978-0-387-35650-1/hbk; 978-0-387-35651-8/ebook). xv, 551 p.

eBook: http://dx.doi.org/10.1007/978-0-387-35651-8


Concrete abstract algebra : from numbers to Gröbner bases / Niels Lauritzen
Verfasser: 
Lauritzen, Niels
Ausgabe: 
Reprinted with corr.
Erschienen: 
Cambridge [u.a.] : Cambridge Univ. Press, 2006
Umfang: 
XIV, 240 S. : graph. Darst.
Anmerkung: 
Includes bibliographical references and index
ISBN: 
0-521-82679-9, 978-0-521-82679-2 (hbk.) : GBP 55.00
0-521-53410-0, 978-0-521-53410-9 (pbk.) : USD 39.99

Koepf, Wolfram
Computer algebra. An algorithmic oriented introduction. (Computeralgebra. Eine algorithmisch orientierte Einführung.) (German) Zbl 1161.68881
Berlin: Springer (ISBN 3-540-29894-0/pbk). xiii, 515 p.

springer eBook: http://dx.doi.org/10.1007/3-540-29895-9

Kaplan, Michael
Computer algebra. (Computeralgebra.) (German) Zbl 1093.68148
Berlin: Springer (ISBN 3-540-21379-1/pbk). xii, 391 p.

springer eBook:

http://dx.doi.org/10.1007/b137968



Course L0423: Algorithmic Algebra
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Prashant Batra
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0836: Communication Networks

Courses
Title Typ Hrs/wk CP
Analysis and Structure of Communication Networks (L0897) Lecture 2 2
Selected Topics of Communication Networks (L0899) Project-/problem-based Learning 2 2
Communication Networks Excercise (L0898) Project-/problem-based Learning 1 2
Module Responsible Prof. Andreas Timm-Giel
Admission Requirements None
Recommended Previous Knowledge
  • Fundamental stochastics
  • Basic understanding of computer networks and/or communication technologies is beneficial
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to describe the principles and structures of communication networks in detail. They can explain the formal description methods of communication networks and their protocols. They are able to explain how current and complex communication networks work and describe the current research in these examples.

Skills

Students are able to evaluate the performance of communication networks using the learned methods. They are able to work out problems themselves and apply the learned methods. They can apply what they have learned autonomously on further and new communication networks.

Personal Competence
Social Competence

Students are able to define tasks themselves in small teams and solve these problems together using the learned methods. They can present the obtained results. They are able to discuss and critically analyse the solutions.

Autonomy

Students are able to obtain the necessary expert knowledge for understanding the functionality and performance capabilities of new communication networks independently.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Course achievement None
Examination Presentation
Examination duration and scale 1.5 hours colloquium with three students, therefore about 30 min per student. Topics of the colloquium are the posters from the previous poster session and the topics of the module.
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory
Aircraft Systems Engineering: Specialisation Avionic and Embedded Systems: Elective Compulsory
Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Course L0897: Analysis and Structure of Communication Networks
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle WiSe
Content
Literature
  • Skript des Instituts für Kommunikationsnetze
  • Tannenbaum, Computernetzwerke, Pearson-Studium


Further literature is announced at the beginning of the lecture.

Course L0899: Selected Topics of Communication Networks
Typ Project-/problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle WiSe
Content Example networks selected by the students will be researched on in a PBL course by the students in groups and will be presented in a poster session at the end of the term.
Literature
  • see lecture
Course L0898: Communication Networks Excercise
Typ Project-/problem-based Learning
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle WiSe
Content Part of the content of the lecture Communication Networks are reflected in computing tasks in groups, others are motivated and addressed in the form of a PBL exercise.
Literature
  • announced during lecture

Module M0926: Distributed Algorithms

Courses
Title Typ Hrs/wk CP
Distributed Algorithms (L1071) Lecture 2 3
Distributed Algorithms (L1072) Recitation Section (large) 2 3
Module Responsible Prof. Volker Turau
Admission Requirements None
Recommended Previous Knowledge
  • Algorithms and data structures
  • Distributed systems
  • Discrete mathematics
  • Graph theory
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students know the main abstractions of distributed algorithms (synchronous/asynchronous model, message passing and shared memory model). They are able to describe complexity measures for distributed algorithms (round , message and memory complexity). They explain well known distributed algorithms for important problems such as leader election, mutual exclusion, graph coloring, spanning trees. They know the fundamental techniques used for randomized algorithms.
Skills Students design their own distributed algorithms and analyze their complexity. They make use of known standard algorithms. They compute the complexity of randomized algorithms.
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 45 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory
Course L1071: Distributed Algorithms
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Volker Turau
Language DE/EN
Cycle WiSe
Content
  • Leader Election
  • Colorings & Independent Sets
  • Tree Algorithms
  • Minimal Spanning Trees
  • Randomized Distributed Algorithms
  • Mutual Exclusion
Literature
  1. David Peleg: Distributed Computing - A Locality-Sensitive Approach. SIAM Monograph, 2000

  2. Gerard Tel: Introduction to Distributed Algorithms, Cambridge University Press, 2nd edition, 2000
  3. Nancy Lynch: Distributed Algorithms. Morgan Kaufmann, 1996
  4. Volker Turau: Algorithmische Graphentheorie. Oldenbourg Wissenschaftsverlag, 3. Auflage, 2004.


Course L1072: Distributed Algorithms
Typ Recitation Section (large)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Volker Turau
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0586: Efficient Algorithms

Courses
Title Typ Hrs/wk CP
Efficient Algorithms (L0120) Lecture 2 3
Efficient Algorithms (L1207) Recitation Section (small) 2 3
Module Responsible Prof. Siegfried Rump
Admission Requirements None
Recommended Previous Knowledge

Programming in Matlab and/or C

Basic knowledge in discrete mathematics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are able to explain the basic theory and methods of network algorithms and in particular their data structures. They are able to analyze the computational behavior and computing time of linear programming algorithms as well network algorithms. Moreover the students can distinguish between efficiently solvable and NP-hard problems.

Skills

The students are able to analyze complex tasks and can determine possibilities to transform them into networking algorithms. In particular they can efficiently implement basic algorithms and data structures of LP- and network algorithms and identify possible weaknesses. They are able to distinguish between different efficient data structures and are able to use them appropriately.

Personal Competence
Social Competence

The students have the skills to solve problems together in small groups and to present the achieved results in an appropriate manner.

Autonomy

The students are able to retrieve necessary informations from the given literature and to combine them with the topics of the lecture. Throughout the lecture they can check their abilities and knowledge on the basis of given exercises and test questions providing an aid to optimize their learning process.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0120: Efficient Algorithms
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content

- Linear Programming

- Data structures

- Leftist heaps

- Minimum spanning tree

- Shortest path

- Maximum flow

- NP-hard problems via max-cut

Literature

R. E. Tarjan: Data Structures and Network Algorithms. CBMS 44, Society for Industrial and Applied Mathematics, Philadelphia, PA, 1983.

Wesley, 2011 http://algs4.cs.princeton.edu/home/

V. Chvátal, ``Linear Programming'', Freeman, New York, 1983.

Course L1207: Efficient Algorithms
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1271: Technical Complementary Course II for CSMS (according to Subject Specific Regulations)

Courses
Title Typ Hrs/wk CP
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Die Studierenden können die wesentlichen Inhalte des technischen Faches im Rahmen eines Vortrages oder einer Diskussion wiedergeben.

Skills

The students acquire professional competence in a technical subject available at TUHH.

Personal Competence
Social Competence
Autonomy
Workload in Hours Depends on choice of courses
Credit points 6
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory

Module M1318: Wireless Sensor Networks

Courses
Title Typ Hrs/wk CP
Wireless Sensor Networks (L1815) Lecture 2 2
Wireless Sensor Networks (L1816) Recitation Section (small) 1 1
Wireless Sensor Networks: Project (L1819) Project-/problem-based Learning 2 3
Module Responsible Prof. Bernd-Christian Renner
Admission Requirements None
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory
Course L1815: Wireless Sensor Networks
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Bernd-Christian Renner
Language EN
Cycle SoSe
Content
Literature
Course L1816: Wireless Sensor Networks
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Bernd-Christian Renner
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L1819: Wireless Sensor Networks: Project
Typ Project-/problem-based Learning
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Bernd-Christian Renner
Language EN
Cycle SoSe
Content

The PrBL course part will be performed in small groups of students. Topics are from the field of wireless sensor networks and are loosely related to the lecture contents. Project descriptions and goals are provided but have to be solved by the students as follow:

  1. Group meeting, creation of working plan and milestones
  2. kick-off presentation (during lecture)
  3. free working
  4. poster creation and presentation

Throughout the semester, there will be meetings with the supervisor on a regular basis (weekly or biweekly). Details about the topics and course organization will be provided in the first lecture. Please note that the number of participants is limited due to the available capacity (rooms, equipment, supervisors).

Literature

Will be provided individually

Module M0556: Computer Graphics

Courses
Title Typ Hrs/wk CP
Computer Graphics (L0145) Lecture 2 3
Computer Graphics (L0768) Recitation Section (small) 2 3
Module Responsible Prof. Tobias Knopp
Admission Requirements None
Recommended Previous Knowledge

Students are expected to have a solid knowledge of object-oriented programming as well as of linear algebra and geometry.

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students have acquired a theoretical basis in computer graphics and have a clear understanding of the process of computer animation.

Skills

Students have acquired

  • solid skills in modelling and shading,
  • solid skills in computer animation techniques, and
  • a thorough command of Maya, a first-class animation system.


Personal Competence
Social Competence

Students are trained in communicating abstract ideas and are familiar with planning and conducting projects within a small team.


Autonomy

Students are able to direct complex computer animation projects.



Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
Course L0145: Computer Graphics
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language EN
Cycle SoSe
Content

Computer graphics and animation are leading to an unprecedented visual revolution. The course deals with its technological foundations:

  • Object-oriented Computer Graphics
  • Projections and Transformations
  • Polygonal and Parametric Modelling
  • Illuminating, Shading, Rendering
  • Computer Animation Techniques
  • Kinematics and Dynamics Effects

Students will be be working on a series of mini-projects which will eventually evolve into a final project. Learning computer graphics and animation resembles learning a musical instrument. Therefore, doing your projects well and in time is essential for performing well on this course.

Literature
Alan H. Watt:
3D Computer Graphics.
Harlow: Pearson (3rd ed., repr., 2009).

Dariush Derakhshani:
Introducing Autodesk Maya 2014.
New York, NY : Wiley (2013).

Course L0768: Computer Graphics
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1248: Compilers for Embedded Systems

Courses
Title Typ Hrs/wk CP
Compilers for Embedded Systems (L1692) Lecture 3 4
Compilers for Embedded Systems (L1693) Project-/problem-based Learning 1 2
Module Responsible Prof. Heiko Falk
Admission Requirements None
Recommended Previous Knowledge

Module "Embedded Systems"

C/C++ Programming skills

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The relevance of embedded systems increases from year to year. Within such systems, the amount of software to be executed on embedded processors grows continuously due to its lower costs and higher flexibility. Because of the particular application areas of embedded systems, highly optimized and application-specific processors are deployed. Such highly specialized processors impose high demands on compilers which have to generate code of highest quality. After the successful attendance of this course, the students are able

  • to illustrate the structure and organization of such compilers,
  • to distinguish and explain intermediate representations of various abstraction levels, and
  • to assess optimizations and their underlying problems in all compiler phases.

The high demands on compilers for embedded systems make effective code optimizations mandatory. The students learn in particular,

  • which kinds of optimizations are applicable at the source code level,
  • how the translation from source code to assembly code is performed,
  • which kinds of optimizations are applicable at the assembly code level,
  • how register allocation is performed, and
  • how memory hierarchies can be exploited effectively.

Since compilers for embedded systems often have to optimize for multiple objectives (e.g., average- or worst-case execution time, energy dissipation, code size), the students learn to evaluate the influence of optimizations on these different criteria.

Skills

After successful completion of the course, students shall be able to translate high-level program code into machine code. They will be enabled to assess which kind of code optimization should be applied most effectively at which abstraction level (e.g., source or assembly code) within a compiler.

While attending the labs, the students will learn to implement a fully functional compiler including optimizations.

Personal Competence
Social Competence

Students are able to solve similar problems alone or in a group and to present the results accordingly.

Autonomy

Students are able to acquire new knowledge from specific literature and to associate this knowledge with other classes.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L1692: Compilers for Embedded Systems
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Heiko Falk
Language DE/EN
Cycle SoSe
Content
  • Introduction and Motivation
  • Compilers for Embedded Systems - Requirements and Dependencies
  • Internal Structure of Compilers
  • Pre-Pass Optimizations
  • HIR Optimizations and Transformations
  • Code Generation
  • LIR Optimizations and Transformations
  • Register Allocation
  • WCET-Aware Compilation
  • Outlook
Literature
  • Peter Marwedel. Embedded System Design - Embedded Systems Foundations of Cyber-Physical Systems. 2nd Edition, Springer, 2012.
  • Steven S. Muchnick. Advanced Compiler Design and Implementation. Morgan Kaufmann, 1997.
  • Andrew W. Appel. Modern compiler implementation in C. Oxford University Press, 1998.
Course L1693: Compilers for Embedded Systems
Typ Project-/problem-based Learning
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Heiko Falk
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0837: Simulation of Communication Networks

Courses
Title Typ Hrs/wk CP
Simulation of Communication Networks (L0887) Project-/problem-based Learning 5 6
Module Responsible Prof. Andreas Timm-Giel
Admission Requirements None
Recommended Previous Knowledge
  • Knowledge of computer and communication networks
  • Basic programming skills
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain the necessary stochastics, the discrete event simulation technology and modelling of networks for performance evaluation.

Skills

Students are able to apply the method of simulation for performance evaluation to different, also not practiced, problems of communication networks. The students can analyse the obtained results and explain the effects observed in the network. They are able to question their own results.

Personal Competence
Social Competence

Students are able to acquire expert knowledge in groups, present the results, and discuss solution approaches and results. They are able to work out solutions for new problems in small teams.

Autonomy

Students are able to transfer independently and in discussion with others the acquired method and expert knowledge to new problems. They can identify missing knowledge and acquire this knowledge independently.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Aircraft Systems Engineering: Specialisation Avionic and Embedded Systems: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory
Course L0887: Simulation of Communication Networks
Typ Project-/problem-based Learning
Hrs/wk 5
CP 6
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle SoSe
Content

In the course necessary basic stochastics and the discrete event simulation are introduced. Also simulation models for communication networks, for example, traffic models, mobility models and radio channel models are presented in the lecture. Students work with a simulation tool, where they can directly try out the acquired skills, algorithms and models. At the end of the course increasingly complex networks and protocols are considered and their performance is determined by simulation.

Literature
  • Skript des Instituts für Kommunikationsnetze

Further literature is announced at the beginning of the lecture.

Module M0924: Software for Embedded Systems

Courses
Title Typ Hrs/wk CP
Software for Embdedded Systems (L1069) Lecture 2 3
Software for Embdedded Systems (L1070) Recitation Section (small) 3 3
Module Responsible Prof. Volker Turau
Admission Requirements None
Recommended Previous Knowledge
  • Good knowledge and experience in programming language C
  • Basis knowledge in software engineering
  • Basic understanding of assembly language
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students know the basic principles and procedures of software engineering for embedded systems. They are able to describe the usage and pros of event based programming using interrupts. They know the components and functions of a concrete microcontroller. The participants explain requirements of real time systems. They know at least three scheduling algorithms for real time operating systems including their pros and cons.
Skills Students build interrupt-based programs for a concrete microcontroller. They build and use a preemptive scheduler. They use peripheral components (timer, ADC, EEPROM) to realize complex tasks for embedded systems. To interface with external components they utilize serial protocols.
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Course L1069: Software for Embdedded Systems
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Volker Turau
Language DE/EN
Cycle SoSe
Content
  • General-Purpose Processors
  • Programming the Atmel AVR
  • Interrupts
  • C for Embedded Systems
  • Standard Single Purpose Processors: Peripherals
  • Finite-State Machines
  • Memory
  • Operating Systems for Embedded Systems
  • Real-Time Embedded Systems
  • Boot loader and Power Management
Literature
  1. Embedded System Design,  F. Vahid and T. Givargis,  John Wiley
  2. Programming Embedded Systems: With C and Gnu Development Tools, M. Barr and A. Massa, O'Reilly

  3. C und C++ für Embedded Systems,  F. Bollow, M. Homann, K. Köhn,  MITP
  4. The Art of Designing  Embedded Systems, J. Ganssle, Newnses

  5. Mikrocomputertechnik mit Controllern der Atmel AVR-RISC-Familie,  G. Schmitt, Oldenbourg
  6. Making Embedded Systems: Design Patterns for Great Software, E. White, O'Reilly

Course L1070: Software for Embdedded Systems
Typ Recitation Section (small)
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Volker Turau
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1301: Software Testing

Courses
Title Typ Hrs/wk CP
Software Testing (L1791) Lecture 2 3
Software Testing (L1792) Project-/problem-based Learning 2 3
Module Responsible Prof. Sibylle Schupp
Admission Requirements None
Recommended Previous Knowledge
  • Software Engineering
  • Higher Programming Languages
  • Object-Oriented Programming
  • Algorithms and Data Structures
  • Experience with (Small) Software Projects
  • Statistics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Students explain the different phases of testing, describe fundamental
techniques of different types of testing, and paraphrase the basic
principles of the corresponding test process. They give examples of
software development scenarios and the corresponding test type and
technique. They explain algorithms used for particular testing
techniques and describe possible advantages and limitations.
Skills
Students identify the appropriate testing type and technique for a given
problem. They adapt and execute respective algorithms to execute a
concrete test technique properly. They interpret testing results and
execute corresponding steps for proper re-test scenarios. They write and
analyze test specifications. They apply bug finding techniques for
non-trivial problems.
Personal Competence
Social Competence

Students discuss relevant topics in class. They defend their solutions orally.
They communicate in English.

Autonomy

Students can assess their level of knowledge continuously and adjust it appropriately, based on feedback and on self-guided studies. Within limits, they can set their own learning goals. Upon successful completion, students can identify and precisely formulate new problems in academic or applied research in the field of software testing. Within this field, they can conduct independent studies to acquire the necessary competencies and compile their findings in academic reports. They can devise plans to arrive at new solutions or assess existing ones

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Subject theoretical and practical work
Examination duration and scale Software
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
Course L1791: Software Testing
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle SoSe
Content
  • Fundamentals of software testing
  • Model-based testing
  • Test automation
  • Criteria-based testing
Literature
  • M. Pezze and M. Young, Software Testing and Analysis, John Wiley 2008.
  • P. Ammann and J. Offutt, "Introduction to Software Testing", 2nd edition 2016.
  • A. Zeller: "Why Programs Fail: A Guide to Systematic Debugging", 2nd edition 2012.
Course L1792: Software Testing
Typ Project-/problem-based Learning
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle SoSe
Content
  • Fundamentals of software testing
  • Model-based testing
  • Test automation
  • Criteria-based testing
Literature
  • M. Pezze and M. Young, Software Testing and Analysis, John Wiley 2008.
  • P. Ammann and J. Offutt, "Introduction to Software Testing", 2nd edition 2015.

Module M0711: Numerical Mathematics II

Courses
Title Typ Hrs/wk CP
Numerical Mathematics II (L0568) Lecture 2 3
Numerical Mathematics II (L0569) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Numerical Mathematics I
  • MATLAB knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • name advanced numerical methods for interpolation, integration, linear least squares problems, eigenvalue problems, nonlinear root finding problems and explain their core ideas,
  • repeat convergence statements for the numerical methods,
  • sketch convergence proofs,
  • explain practical aspects of numerical methods concerning runtime and storage needs


    explain aspects regarding the practical implementation of numerical methods with respect to computational and storage complexity.


Skills

Students are able to

  • implement, apply and compare advanced numerical methods in MATLAB,
  • justify the convergence behaviour of numerical methods with respect to the problem and solution algorithm and to transfer it to related problems,
  • for a given problem, develop a suitable solution approach, if necessary through composition of several algorithms, to execute this approach and to critically evaluate the results


Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 25 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0568: Numerical Mathematics II
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Jens-Peter Zemke
Language DE/EN
Cycle SoSe
Content
  1. Error and stability: Notions and estimates
  2. Interpolation: Rational and trigonometric interpolation
  3. Quadrature: Gaussian quadrature, orthogonal polynomials
  4. Linear systems: Perturbation theory of decompositions, structured matrices
  5. Eigenvalue problems: LR-, QD-, QR-Algorithmus
  6. Krylov space methods: Arnoldi-, Lanczos methods
Literature
  • Stoer/Bulirsch: Numerische Mathematik 1, Springer
  • Dahmen, Reusken: Numerik für Ingenieure und Naturwissenschaftler, Springer
Course L0569: Numerical Mathematics II
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Jens-Peter Zemke
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1397: Model Checking - Proof Engines and Algorithms

Courses
Title Typ Hrs/wk CP
Model Checking - Proof Engines and Algorithms (L1979) Lecture 2 3
Model Checking - Proof Engines and Algorithms (L1980) Recitation Section (small) 2 3
Module Responsible Prof. Görschwin Fey
Admission Requirements None
Recommended Previous Knowledge Basic knowledge about data structures and algorithms
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students know

  • algorithms and data structures for model checking,
  • basics of Boolean reasoning engines and
  • the impact of specification and modelling on the computational effort for model checking.
Skills

Students can

  • explain and implement algorithms and data structures for model checking,
  • decide whether a given problem can be solved using Boolean reasoning or model checking, and
  • implement the respective algorithms.
Personal Competence
Social Competence

Students

  • discuss relevant topics in class and
  • defend their solutions orally.
Autonomy Using accompanying material students independently learn in-depth relations between concepts explained in the lecture and additional solution strategies.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory
Course L1979: Model Checking - Proof Engines and Algorithms
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Görschwin Fey
Language DE/EN
Cycle SoSe
Content

Correctness is a major concern in embedded systems. Model checking can fully automatically proof formal properties about digital hardware or software. Such properties are given in temporal logic, e.g., to prove "No two orthogonal traffic lights will ever be green."

And how do the underlying reasoning algorithms work so effectively in practice despite a computational complexity of NP hardness and beyond?

But what are the limitations of model checking?
How are the models generated from a given design?
The lecture will answer these questions. Open source tools will be used to gather a practical experience.

Among other topics, the lecture will consider the following topics:

  • Modelling digital Hardware, Software, and Cyber Physical Systems

  • Data structures, decision procedures and proof engines

    • Binary Decision Diagrams

    • And-Inverter-Graphs

    • Boolean Satisfiability

    • Satisfiability Modulo Theories

  • Specification Languages

    • CTL

    • LTL

    • System Verilog Assertions

  • Algorithms for

    • Reachability Analysis

    • Symbolic CTL Checking

    • Bounded LTL-Model Checking

    • Optimizations, e.g., induction, abstraction

  • Quality assurance

Literature

Edmund M. Clarke, Jr., Orna Grumberg, and Doron A. Peled. 1999. Model Checking. MIT Press, Cambridge, MA, USA.

A. Biere, A. Biere, M. Heule, H. van Maaren, and T. Walsh. 2009. Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications. IOS Press, Amsterdam, The Netherlands, The Netherlands.

Selected research papers

Course L1980: Model Checking - Proof Engines and Algorithms
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Görschwin Fey
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1405: Randomised Algorithms and Random Graphs

Courses
Title Typ Hrs/wk CP
Randomised Algorithms and Random Graphs (L2010) Lecture 2 3
Randomised Algorithms and Random Graphs (L2011) Recitation Section (large) 2 3
Module Responsible Prof. Anusch Taraz
Admission Requirements None
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in the area of Randomized Algorithms and Random Graphs such as random walks, tail bounds, fingerprinting and algebraic techniques, first and second moment methods, and various random graph models. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can apply them.

Skills
  • Students can model problems with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to explore and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable technique, and are able to critically evaluate the results.
Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to establish a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.
Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory
Mathematical Modelling in Engineering: Theory, Numerics, Applications: Specialisation l. Numerics (TUHH): Elective Compulsory
Course L2010: Randomised Algorithms and Random Graphs
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Anusch Taraz, Prof. Volker Turau
Language DE/EN
Cycle SoSe
Content

Randomized Algorithms:

  • introduction and recalling basic tools from probability
  • randomized search
  • random walks
  • text search with fingerprinting
  • parallel and distributed algorithms
  • online algorithms


Random Graphs: 

  • typical properties 
  • first and second moment method
  • tail bounds 
  • thresholds and phase transitions 
  • probabilistic method  
  • models for complex networks 

Literature
  • Motwani, Raghavan: Randomized Algorithms
  • Worsch: Randomisierte Algorithmen
  • Dietzfelbinger: Randomisierte Algorithmen
  • Bollobas: Random Graphs
  • Alon, Spencer: The Probabilistic Method
  • Frieze, Karonski: Random Graphs
  • van der Hofstad: Random Graphs and Complex Networks


Course L2011: Randomised Algorithms and Random Graphs
Typ Recitation Section (large)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Anusch Taraz, Prof. Volker Turau
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0758: Application Security

Courses
Title Typ Hrs/wk CP
Application Security (L0726) Lecture 3 3
Application Security (L0729) Recitation Section (small) 2 3
Module Responsible Prof. Dieter Gollmann
Admission Requirements None
Recommended Previous Knowledge Familiarity with Information security, fundamentals of cryptography, Web protocols and the architecture of the Web
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students can name current approaches for securing selected applications, in particular of web applications
Skills

Students are capable of

  • performing a security analysis
  • developing security solutions for distributed applications
  • recognizing the limitations of existing standard solutions  




Personal Competence
Social Competence Students are capable of appreciating the impact of security problems on  those affected and of the potential responsibilities for their resolution. 
Autonomy Students are capable of acquiring knowledge independently from professional publications, technical  standards, and other sources, and are capable of applying newly acquired knowledge to new problems. 
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 120 minutes
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
Course L0726: Application Security
Typ Lecture
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Dieter Gollmann
Language EN
Cycle SoSe
Content
  • Email security 
  • Web Services security
  • Security in Web applications
  • Access control
  • Trust Management
  • Trusted Computing
  • Digital Rights Management
  • Security Solutions for selected applications
Literature

Webseiten der OMG, W3C, OASIS, WS-Security, OECD, TCG

D. Gollmann: Computer Security, 3rd edition, Wiley (2011)

R. Anderson: Security Engineering, 2nd edition, Wiley (2008)

U. Lang: CORBA Security, Artech House, 2002

Course L0729: Application Security
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Dieter Gollmann
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1400: Design of Dependable Systems

Courses
Title Typ Hrs/wk CP
Designing Dependable Systems (L2000) Lecture 2 3
Designing Dependable Systems (L2001) Recitation Section (small) 2 3
Module Responsible Prof. Görschwin Fey
Admission Requirements None
Recommended Previous Knowledge Basic knowledge about data structures and algorithms
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

In the following "dependable" summarizes the concepts Reliability, Availability, Maintainability, Safety and Security.

Knowledge about approaches for designing dependable systems, e.g.,

  • Structural solutions like modular redundancy
  • Algorithmic solutions like handling byzantine faults or checkpointing

Knowledge about methods for the analysis of dependable systems


Skills

Ability to implement dependable systems using the above approaches.

Ability to analyzs the dependability of systems using the above methods for analysis.

Personal Competence
Social Competence

Students

  • discuss relevant topics in class and
  • present their solutions orally.
Autonomy Using accompanying material students independently learn in-depth relations between concepts explained in the lecture and additional solution strategies.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement
Compulsory Bonus Form Description
No None Excercises Praktische Übungsaufgaben zur Anwendung der gelernten Ansätze
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory
Course L2000: Designing Dependable Systems
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Görschwin Fey
Language DE/EN
Cycle SoSe
Content

Description

The term dependability comprises various aspects of a system. These are typically:
  • Reliability
  • Availability
  • Maintainability
  • Safety
  • Security
This makes dependability a core aspect that has to be considered early in system design, no matter whether software, embedded systems or full scale cyber-physical systems are considered.

Contents

The module introduces the basic concepts for the design and the analysis of dependable systems. Design examples for getting practical hands-on-experience in dependable design techniques. The module focuses towards embedded systems. The following topics are covered:
  • Modelling
  • Fault Tolerance
  • Design Concepts
  • Analysis Techniques
Literature
Course L2001: Designing Dependable Systems
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Görschwin Fey
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1337: Curves, Cryptosystems and Quantum Computing

Courses
Title Typ Hrs/wk CP
Curves, Cryptosystems and Quantum Computing (L1870) Lecture 4 6
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge Higher algebra, linear algebra, and mathematical analysis.
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students understand the basic theory of elliptic curves, classical cryptosysteme, basic methods of cryptanalysis, cryptography of elliptic curves, quantum computing and the post-quantum computing scenario, algebraic codes over curves, and the famous theorem of Riemann-Roch.
Skills The students are in the position to apply the group law of elliptic curves, to find out if a curve is non-singular, to sketch cryptographic algorithms that make use of elliptic curves, to specify quantum algorithms, and to determine the parameters of algebraic codes defined over curves.
Personal Competence
Social Competence

Students are able to solve specific problems alone or in a group and to present the results accordingly.

Autonomy

Students are able to acquire new knowledge from specific standard books and to associate the acquired knowledge to other classes.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 25 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Course L1870: Curves, Cryptosystems and Quantum Computing
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Karl-Heinz Zimmermann
Language DE/EN
Cycle SoSe
Content
Literature

Module M0839: Traffic Engineering

Courses
Title Typ Hrs/wk CP
Seminar Traffic Engineering (L0902) Seminar 2 2
Traffic Engineering (L0900) Lecture 2 2
Traffic Engineering Exercises (L0901) Recitation Section (small) 1 2
Module Responsible Prof. Andreas Timm-Giel
Admission Requirements None
Recommended Previous Knowledge
  • Fundamentals of communication or computer networks
  • Stochastics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to describe methods for planning, optimisation and performance evaluation of communication networks.

Skills

Students are able to solve typical planning and optimisation tasks for communication networks. Furthermore they are able to evaluate the network performance using queuing theory.

Students are able to apply independently what they have learned to other and new problems. They can present their results in front of experts and discuss them.

Personal Competence
Social Competence
Autonomy

Students are able to acquire the necessary expert knowledge to understand the functionality and performance of new communication networks independently.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory
Course L0902: Seminar Traffic Engineering
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Andreas Timm-Giel, Dr. Phuong Nga Tran
Language EN
Cycle WiSe
Content Selected applications of methods for planning, optimization, and performance evaluation of communication networks, which have been introduced in the traffic engineering lecture are prepared by the students and presented in a seminar.
Literature
  • U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Vieweg + Teubner
  • further literature announced in the lecture
Course L0900: Traffic Engineering
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Andreas Timm-Giel, Dr. Phuong Nga Tran
Language EN
Cycle WiSe
Content

Network Planning and Optimization
• Linear Programming (LP)
• Network planning with LP solvers
• Planning of communication networks
Queueing Theory for Communication Networks
• Stochastic processes
• Queueing systems
• Switches (circuit- and packet switching)
• Network of queues

Literature

Literatur:
U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Springer
Weitere Literatur wird in der Lehrveranstaltung bekanntgegeben
/
 Literature:
U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Springer
further literature announced in the lecture

Course L0901: Traffic Engineering Exercises
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle WiSe
Content

Accompanying exercise for the traffic engineering course

Literature

Literatur:
U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Springer
Weitere Literatur wird in der Lehrveranstaltung bekanntgegeben / Literature:
U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Springer
further literature announced in the lecture

Module M0910: Advanced System-on-Chip Design (Lab)

Courses
Title Typ Hrs/wk CP
Advanced System-on-Chip Design (L1061) Project-/problem-based Learning 3 6
Module Responsible Prof. Heiko Falk
Admission Requirements None
Recommended Previous Knowledge

Successful completion of the practical FPGA lab of module "Computer Architecture" is a mandatory prerequisite.

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

This module provides in-depth, hands-on experience on advanced concepts of computer architecture. Using the Hardware Description Language VHDL and using reconfigurable FPGA hardware boards, students learn how to design complex computer systems (so-called systems-on-chip, SoCs), that are commonly found in the domain of embedded systems, in actual hardware.

Starting with a simple processor architecture, the students learn to how realize instruction-processing of a computer processor according to the principle of pipelining. They implement different styles of cache-based memory hierarchies, examine strategies for dynamic scheduling of machine instructions and for branch prediction, and finally construct a complex MPSoC system (multi-processor system-on-chip) that consists of multiple processor cores that are connected via a shared bus.

Skills Students will be able to analyze, how highly specific and individual computer systems can be constructed using a library of given standard components. They evaluate the interferences between the physical structure of a computer system and the software executed thereon. This way, they will be enabled to estimate the effects of design decision at the hardware level on the performance of the entire system, to evaluate the whole and complex system and to propose design options to improve a system.
Personal Competence
Social Competence

Students are able to solve similar problems alone or in a group and to present the results accordingly.

Autonomy

Students are able to acquire new knowledge from specific literature, to transform this knowledge into actual implementations of complex hardware structures, and to associate this knowledge with contents of other classes.

Workload in Hours Independent Study Time 138, Study Time in Lecture 42
Credit points 6
Course achievement None
Examination Subject theoretical and practical work
Examination duration and scale VHDL Codes and FPGA-based implementations
Assignment for the Following Curricula Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory
Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory
Course L1061: Advanced System-on-Chip Design
Typ Project-/problem-based Learning
Hrs/wk 3
CP 6
Workload in Hours Independent Study Time 138, Study Time in Lecture 42
Lecturer Prof. Heiko Falk
Language DE/EN
Cycle WiSe
Content
  • Introduction into fundamental technologies (FPGAs, MIPS single-cycle machine)
  • Pipelined instruction execution
  • Cache-based memory hierarchies
  • Busses and their arbitration
  • Multi-Processor Systems-on-Chip
  • Optional: Advanced pipelining concepts (dynamic scheduling, branch prediction)
Literature
  • D. Patterson, J. Hennessy. Rechnerorganisation und -entwurf. Elsevier, 2005.
  • A. Tanenbaum, J. Goodman. Computerarchitektur. Pearson, 2001.
  • A. Clements. The Principles of Computer Hardware. 3. Auflage, Oxford University Press, 2000.

Specialization Intelligence Engineering

Module M1270: Technical Complementary Course I for CSMS (according to Subject Specific Regulations)

Courses
Title Typ Hrs/wk CP
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students acquire advanced knowledge in a technical subject available at TUHH.

Skills

The students acquire professional competence in a technical subject available at TUHH.

Personal Competence
Social Competence
Autonomy
Workload in Hours Depends on choice of courses
Credit points 6
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory

Module M0550: Digital Image Analysis

Courses
Title Typ Hrs/wk CP
Digital Image Analysis (L0126) Lecture 4 6
Module Responsible Prof. Rolf-Rainer Grigat
Admission Requirements None
Recommended Previous Knowledge

System theory of one-dimensional signals (convolution and correlation, sampling theory, interpolation and decimation, Fourier transform, linear time-invariant systems), linear algebra (Eigenvalue decomposition, SVD), basic stochastics and statistics (expectation values, influence of sample size, correlation and covariance, normal distribution and its parameters), basics of Matlab, basics in optics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can

  • Describe imaging processes
  • Depict the physics of sensorics
  • Explain linear and non-linear filtering of signals
  • Establish interdisciplinary connections in the subject area and arrange them in their context
  • Interpret effects of the most important classes of imaging sensors and displays using mathematical methods and physical models.


Skills

Students are able to

  • Use highly sophisticated methods and procedures of the subject area
  • Identify problems and develop and implement creative solutions.

Students can solve simple arithmetical problems relating to the specification and design of image processing and image analysis systems.

Students are able to assess different solution approaches in multidimensional decision-making areas.

Students can undertake a prototypical analysis of processes in Matlab.


Personal Competence
Social Competence k.A.


Autonomy

Students can solve image analysis tasks independently using the relevant literature.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 60 Minutes, Content of Lecture and materials in StudIP
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0126: Digital Image Analysis
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Rolf-Rainer Grigat
Language EN
Cycle WiSe
Content
  • Image representation, definition of images and volume data sets, illumination, radiometry, multispectral imaging, reflectivities, shape from shading
  • Perception of luminance and color, color spaces and transforms, color matching functions, human visual system, color appearance models
  • imaging sensors (CMOS, CCD, HDR, X-ray, IR), sensor characterization(EMVA1288), lenses and optics
  • spatio-temporal sampling (interpolation, decimation, aliasing, leakage, moiré, flicker, apertures)
  • features (filters, edge detection, morphology, invariance, statistical features, texture)
  • optical flow ( variational methods, quadratic optimization, Euler-Lagrange equations)
  • segmentation (distance, region growing, cluster analysis, active contours, level sets, energy minimization and graph cuts)
  • registration (distance and similarity, variational calculus, iterative closest points)
Literature

Bredies/Lorenz, Mathematische Bildverarbeitung, Vieweg, 2011
Wedel/Cremers, Stereo Scene Flow for 3D Motion Analysis, Springer 2011
Handels, Medizinische Bildverarbeitung, Vieweg, 2000
Pratt, Digital Image Processing, Wiley, 2001
Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1989

Module M0677: Digital Signal Processing and Digital Filters

Courses
Title Typ Hrs/wk CP
Digital Signal Processing and Digital Filters (L0446) Lecture 3 4
Digital Signal Processing and Digital Filters (L0447) Recitation Section (large) 1 2
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics 1-3
  • Signals and Systems
  • Fundamentals of signal and system theory as well as random processes.
  • Fundamentals of spectral transforms (Fourier series, Fourier transform, Laplace transform)
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know and understand basic algorithms of digital signal processing. They are familiar with the spectral transforms of discrete-time signals and are able to describe and analyse signals and systems in time and image domain. They know basic structures of digital filters and can identify and assess important properties including stability. They are aware of the effects caused by quantization of filter coefficients and signals. They are familiar with the basics of adaptive filters. They can perform traditional and parametric methods of spectrum estimation, also taking a limited observation window into account.
Skills The students are able to apply methods of digital signal processing to new problems. They can choose and parameterize suitable filter striuctures. In particular, the can design adaptive filters according to the minimum mean squared error (MMSE) criterion and develop an efficient implementation, e.g. based on the LMS or RLS algorithm.  Furthermore, the students are able to apply methods of spectrum estimation and to take the effects of a limited observation window into account.
Personal Competence
Social Competence

The students can jointly solve specific problems.

Autonomy

The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation II. Engineering Science: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0446: Digital Signal Processing and Digital Filters
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Gerhard Bauch
Language EN
Cycle WiSe
Content
  • Transforms of discrete-time signals:

    • Discrete-time Fourier Transform (DTFT)

    • Discrete Fourier-Transform (DFT), Fast Fourier Transform (FFT)

    • Z-Transform

  • Correspondence of continuous-time and discrete-time signals, sampling, sampling theorem

  • Fast convolution, Overlap-Add-Method, Overlap-Save-Method

  • Fundamental structures and basic types of digital filters

  • Characterization of digital filters using pole-zero plots, important properties of digital filters

  • Quantization effects

  • Design of linear-phase filters

  • Fundamentals of stochastic signal processing and adaptive filters

    • MMSE criterion

    • Wiener Filter

    • LMS- and RLS-algorithm

  • Traditional and parametric methods of spectrum estimation

Literature

K.-D. Kammeyer, K. Kroschel: Digitale Signalverarbeitung. Vieweg Teubner.

V. Oppenheim, R. W. Schafer, J. R. Buck: Zeitdiskrete Signalverarbeitung. Pearson StudiumA. V.

W. Hess: Digitale Filter. Teubner.

Oppenheim, R. W. Schafer: Digital signal processing. Prentice Hall.

S. Haykin:  Adaptive flter theory.

L. B. Jackson: Digital filters and signal processing. Kluwer.

T.W. Parks, C.S. Burrus: Digital filter design. Wiley.

Course L0447: Digital Signal Processing and Digital Filters
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0563: Robotics

Courses
Title Typ Hrs/wk CP
Robotics: Modelling and Control (L0168) Lecture 3 3
Robotics: Modelling and Control (L1305) Recitation Section (small) 2 3
Module Responsible Prof. Uwe Weltin
Admission Requirements None
Recommended Previous Knowledge

Fundamentals of electrical engineering

Broad knowledge of mechanics

Fundamentals of control theory

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students are able to describe fundamental properties of robots and solution approaches for multiple problems in robotics.
Skills

Students are able to derive and solve equations of motion for various manipulators.

Students can generate trajectories in various coordinate systems.

Students can design linear and partially nonlinear controllers for robotic manipulators.

Personal Competence
Social Competence Students are able to work goal-oriented in small mixed groups.
Autonomy

Students are able to recognize and improve knowledge deficits independently.

With instructor assistance, students are able to evaluate their own knowledge level and define a further course of study.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
International Management and Engineering: Specialisation II. Product Development and Production: Elective Compulsory
Mechanical Engineering and Management: Core Qualification: Compulsory
Mechatronics: Core Qualification: Compulsory
Product Development, Materials and Production: Specialisation Product Development: Elective Compulsory
Product Development, Materials and Production: Specialisation Production: Elective Compulsory
Product Development, Materials and Production: Specialisation Materials: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Product Development and Production: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0168: Robotics: Modelling and Control
Typ Lecture
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Uwe Weltin
Language EN
Cycle WiSe
Content

Fundamental kinematics of rigid body systems

Newton-Euler equations for manipulators

Trajectory generation

Linear and nonlinear control of robots

Literature

Craig, John J.: Introduction to Robotics Mechanics and Control, Third Edition, Prentice Hall. ISBN 0201-54361-3

Spong, Mark W.; Hutchinson, Seth;  Vidyasagar, M. : Robot Modeling and Control. WILEY. ISBN 0-471-64990-2


Course L1305: Robotics: Modelling and Control
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Uwe Weltin
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0633: Industrial Process Automation

Courses
Title Typ Hrs/wk CP
Industrial Process Automation (L0344) Lecture 2 3
Industrial Process Automation (L0345) Recitation Section (small) 2 3
Module Responsible Prof. Alexander Schlaefer
Admission Requirements None
Recommended Previous Knowledge

mathematics and optimization methods
principles of automata 
principles of algorithms and data structures
programming skills

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students can evaluate and assess discrete event systems. They can evaluate properties of processes and explain methods for process analysis. The students can compare methods for process modelling and select an appropriate method for actual problems. They can discuss scheduling methods in the context of actual problems and give a detailed explanation of advantages and disadvantages of different programming methods. The students can relate process automation to methods from robotics and sensor systems as well as to recent topics like 'cyberphysical systems' and 'industry 4.0'.


Skills

The students are able to develop and model processes and evaluate them accordingly. This involves taking into account optimal scheduling, understanding algorithmic complexity, and implementation using PLCs.

Personal Competence
Social Competence

The students work in teams to solve problems.


Autonomy

The students can reflect their knowledge and document the results of their work. 


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement
Compulsory Bonus Form Description
No 10 % Excercises
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation General Process Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation General Process Engineering: Elective Compulsory
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory
Aircraft Systems Engineering: Specialisation Cabin Systems: Elective Compulsory
Aircraft Systems Engineering: Specialisation Cabin Systems: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Course L0344: Industrial Process Automation
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content

- foundations of problem solving and system modeling, discrete event systems
- properties of processes, modeling using automata and Petri-nets
- design considerations for processes (mutex, deadlock avoidance, liveness)
- optimal scheduling for processes
- optimal decisions when planning manufacturing systems, decisions under uncertainty
- software design and software architectures for automation, PLCs

Literature

J. Lunze: „Automatisierungstechnik“, Oldenbourg Verlag, 2012
Reisig: Petrinetze: Modellierungstechnik, Analysemethoden, Fallstudien; Vieweg+Teubner 2010
Hrúz, Zhou: Modeling and Control of Discrete-event Dynamic Systems; Springer 2007
Li, Zhou: Deadlock Resolution in Automated Manufacturing Systems, Springer 2009
Pinedo: Planning and Scheduling in Manufacturing and Services, Springer 2009

Course L0345: Industrial Process Automation
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0549: Scientific Computing and Accuracy

Courses
Title Typ Hrs/wk CP
Verification Methods (L0122) Lecture 2 3
Verification Methods (L1208) Recitation Section (small) 2 3
Module Responsible Prof. Siegfried Rump
Admission Requirements None
Recommended Previous Knowledge

Basic knowledge in numerics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students have deeper knowledge of numerical and semi-numerical methods with the goal to compute principally exact and accurate error bounds. For several fundamental problems they know algorithms with the verification of the correctness of the computed result.

Skills

The students can devise algorithms for several basic problems which compute rigorous error bounds for the solution and analyze the sensitivity with respect to variation of the input data as well.

Personal Competence
Social Competence

The students have the skills to solve problems together in small groups and to present the achieved results in an appropriate manner.

Autonomy

The students are able to retrieve necessary informations from the given literature and to combine them with the topics of the lecture. Throughout the lecture they can check their abilities and knowledge on the basis of given exercises and test questions providing an aid to optimize their learning process.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Course L0122: Verification Methods
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content
  • Fast and accurate interval arithmetic

  • Error-free transformations

  • Verification methods for linear and nonlinear systems

  • Verification methods for finite integrals

  • Treatment of multiple zeros

  • Automatic differentiation

  • Implementation in Matlab/INTLAB

  • Practical applications

Literature

Neumaier: Interval Methods for Systems of Equations. In: Encyclopedia of Mathematics and its  Applications. Cambridge University Press, 1990

S.M. Rump. Verification methods: Rigorous results using floating-point arithmetic. Acta Numerica, 19:287-449, 2010.
Course L1208: Verification Methods
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0623: Intelligent Systems in Medicine

Courses
Title Typ Hrs/wk CP
Intelligent Systems in Medicine (L0331) Lecture 2 3
Intelligent Systems in Medicine (L0334) Project Seminar 2 2
Intelligent Systems in Medicine (L0333) Recitation Section (small) 1 1
Module Responsible Prof. Alexander Schlaefer
Admission Requirements None
Recommended Previous Knowledge
  • principles of math (algebra, analysis/calculus)
  • principles of stochastics
  • principles of programming, Java/C++ and R/Matlab
  • advanced programming skills
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are able to analyze and solve clinical treatment planning and decision support problems using methods for search, optimization, and planning. They are able to explain methods for classification and their respective advantages and disadvantages in clinical contexts. The students can compare  different methods for representing medical knowledge. They can evaluate methods in the context of clinical data  and explain challenges due to the clinical nature of the data and its acquisition and due to privacy and safety requirements.

Skills

The students can give reasons for selecting and adapting methods for classification, regression, and prediction. They can assess the methods based on actual patient data and evaluate the implemented methods.

Personal Competence
Social Competence

The students discuss the results of other groups, provide helpful feedback and can incoorporate feedback into their work.

Autonomy

The students can reflect their knowledge and document the results of their work. They can present the results in an appropriate manner.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Course achievement
Compulsory Bonus Form Description
Yes 10 % Written elaboration
Yes 10 % Presentation
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory
Course L0331: Intelligent Systems in Medicine
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content

- methods for search, optimization,  planning,  classification, regression and prediction in a clinical context
- representation of medical knowledge
- understanding challenges due to clinical and patient related data and data acquisition
The students will work in groups to apply the methods introduced during the lecture using problem based learning.


Literature

Russel & Norvig: Artificial Intelligence: a Modern Approach, 2012
Berner: Clinical Decision Support Systems: Theory and Practice, 2007
Greenes: Clinical Decision Support: The Road Ahead, 2007
Further literature will be given in the lecture


Course L0334: Intelligent Systems in Medicine
Typ Project Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0333: Intelligent Systems in Medicine
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0676: Digital Communications

Courses
Title Typ Hrs/wk CP
Digital Communications (L0444) Lecture 2 3
Digital Communications (L0445) Recitation Section (large) 1 2
Laboratory Digital Communications (L0646) Practical Course 1 1
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics 1-3
  • Signals and Systems
  • Fundamentals of Communications and Random Processes
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students are able to understand, compare and design modern digital information transmission schemes. They are familiar with the properties of linear and non-linear digital modulation methods. They can describe distortions caused by transmission channels and design and evaluate detectors including channel estimation and equalization. They know the principles of single carrier transmission and multi-carrier transmission as well as the fundamentals of basic multiple access schemes.
Skills The students are able to design and analyse a digital information transmission scheme including multiple access. They are able to choose a digital modulation scheme taking into account transmission rate, required bandwidth, error probability, and further signal properties. They can design an appropriate detector including channel estimation and equalization taking into account performance and complexity properties of suboptimum solutions. They are able to set parameters of a single carrier or multi carrier transmission scheme and trade the properties of both approaches against each other.
Personal Competence
Social Competence

The students can jointly solve specific problems.

Autonomy

The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement
Compulsory Bonus Form Description
Yes None Written elaboration
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Core Qualification: Compulsory
Computational Science and Engineering: Specialisation II. Engineering Science: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems: Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Course L0444: Digital Communications
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle WiSe
Content
  • Digital modulation methods

  • Coherent and non-coherent detection

  • Channel estimation and equalization

  • Single-Carrier- and multi carrier transmission schemes, multiple access schemes (TDMA, FDMA, CDMA, OFDM)

Literature

K. Kammeyer: Nachrichtenübertragung, Teubner

P.A. Höher: Grundlagen der digitalen Informationsübertragung, Teubner.

J.G. Proakis, M. Salehi: Digital Communications. McGraw-Hill.

S. Haykin: Communication Systems. Wiley

R.G. Gallager: Principles of Digital Communication. Cambridge

A. Goldsmith: Wireless Communication. Cambridge.

D. Tse, P. Viswanath: Fundamentals of Wireless Communication. Cambridge.

Course L0445: Digital Communications
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0646: Laboratory Digital Communications
Typ Practical Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle WiSe
Content

- DSL transmission

- Random processes

- Digital data transmission

Literature

K. Kammeyer: Nachrichtenübertragung, Teubner

P.A. Höher: Grundlagen der digitalen Informationsübertragung, Teubner.

J.G. Proakis, M. Salehi: Digital Communications. McGraw-Hill.

S. Haykin: Communication Systems. Wiley

R.G. Gallager: Principles of Digital Communication. Cambridge

A. Goldsmith: Wireless Communication. Cambridge.

D. Tse, P. Viswanath: Fundamentals of Wireless Communication. Cambridge.

Module M0846: Control Systems Theory and Design

Courses
Title Typ Hrs/wk CP
Control Systems Theory and Design (L0656) Lecture 2 4
Control Systems Theory and Design (L0657) Recitation Section (small) 2 2
Module Responsible Prof. Herbert Werner
Admission Requirements None
Recommended Previous Knowledge Introduction to Control Systems
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain how linear dynamic systems are represented as state space models; they can interpret the system response to initial states or external excitation as trajectories in state space
  • They can explain the system properties controllability and observability, and their relationship to state feedback and state estimation, respectively
  • They can explain the significance of a minimal realisation
  • They can explain observer-based state feedback and how it can be used to achieve tracking and disturbance rejection
  • They can extend all of the above to multi-input multi-output systems
  • They can explain the z-transform and its relationship with the Laplace Transform
  • They can explain state space models and transfer function models of discrete-time systems
  • They can explain the experimental identification of ARX models of dynamic systems, and how the identification problem can be solved by solving a normal equation
  • They can explain how a state space model can be constructed from a discrete-time impulse response

Skills
  • Students can transform transfer function models into state space models and vice versa
  • They can assess controllability and observability and construct minimal realisations
  • They can design LQG controllers for multivariable plants
  •  They can carry out a controller design both in continuous-time and discrete-time domain, and decide which is  appropriate for a given sampling rate
  • They can identify transfer function models and state space models of dynamic systems from experimental data
  • They can carry out all these tasks using standard software tools (Matlab Control Toolbox, System Identification Toolbox, Simulink)

Personal Competence
Social Competence

Students can work in small groups on specific problems to arrive at joint solutions. 

Autonomy

Students can obtain information from provided sources (lecture notes, software documentation, experiment guides) and use it when solving given problems.

They can assess their knowledge in weekly on-line tests and thereby control their learning progress.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Core Qualification: Compulsory
Energy Systems: Core Qualification: Elective Compulsory
Aircraft Systems Engineering: Specialisation Aircraft Systems: Compulsory
Aircraft Systems Engineering: Specialisation Avionic and Embedded Systems: Elective Compulsory
Computational Science and Engineering: Specialisation II. Engineering Science: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Core Qualification: Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Product Development, Materials and Production: Core Qualification: Elective Compulsory
Theoretical Mechanical Engineering: Core Qualification: Compulsory
Course L0656: Control Systems Theory and Design
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle WiSe
Content

State space methods (single-input single-output)

• State space models and transfer functions, state feedback 
• Coordinate basis, similarity transformations 
• Solutions of state equations, matrix exponentials, Caley-Hamilton Theorem
• Controllability and pole placement 
• State estimation, observability, Kalman decomposition 
• Observer-based state feedback control, reference tracking 
• Transmission zeros
• Optimal pole placement, symmetric root locus 
Multi-input multi-output systems
• Transfer function matrices, state space models of multivariable systems, Gilbert realization 
• Poles and zeros of multivariable systems, minimal realization 
• Closed-loop stability
• Pole placement for multivariable systems, LQR design, Kalman filter 

Digital Control
• Discrete-time systems: difference equations and z-transform 
• Discrete-time state space models, sampled data systems, poles and zeros 
• Frequency response of sampled data systems, choice of sampling rate 

System identification and model order reduction 
• Least squares estimation, ARX models, persistent excitation 
• Identification of state space models, subspace identification 
• Balanced realization and model order reduction 

Case study
• Modelling and multivariable control of a process evaporator using Matlab and Simulink 
Software tools
• Matlab/Simulink

Literature
  • Werner, H., Lecture Notes „Control Systems Theory and Design“
  • T. Kailath "Linear Systems", Prentice Hall, 1980
  • K.J. Astrom, B. Wittenmark "Computer Controlled Systems" Prentice Hall, 1997
  • L. Ljung "System Identification - Theory for the User", Prentice Hall, 1999
Course L0657: Control Systems Theory and Design
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0881: Mathematical Image Processing

Courses
Title Typ Hrs/wk CP
Mathematical Image Processing (L0991) Lecture 3 4
Mathematical Image Processing (L0992) Recitation Section (small) 1 2
Module Responsible Prof. Marko Lindner
Admission Requirements None
Recommended Previous Knowledge
  • Analysis: partial derivatives, gradient, directional derivative
  • Linear Algebra: eigenvalues, least squares solution of a linear system
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to 

  • characterize and compare diffusion equations
  • explain elementary methods of image processing
  • explain methods of image segmentation and registration
  • sketch and interrelate basic concepts of functional analysis 
Skills

Students are able to 

  • implement and apply elementary methods of image processing  
  • explain and apply modern methods of image processing
Personal Competence
Social Competence

Students are able to work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge) and to explain theoretical foundations.

Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 20 min
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Course L0991: Mathematical Image Processing
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Marko Lindner, Dr. Christian Seifert
Language DE/EN
Cycle WiSe
Content
  • basic methods of image processing
  • smoothing filters
  • the diffusion / heat equation
  • variational formulations in image processing
  • edge detection
  • de-convolution
  • inpainting
  • image segmentation
  • image registration
Literature Bredies/Lorenz: Mathematische Bildverarbeitung
Course L0992: Mathematical Image Processing
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0629: Intelligent Autonomous Agents and Cognitive Robotics

Courses
Title Typ Hrs/wk CP
Intelligent Autonomous Agents and Cognitive Robotics (L0341) Lecture 2 4
Intelligent Autonomous Agents and Cognitive Robotics (L0512) Recitation Section (small) 2 2
Module Responsible Rainer Marrone
Admission Requirements None
Recommended Previous Knowledge Vectors, matrices, Calculus
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the agent abstraction, define intelligence in terms of rational behavior, and give details about agent design (goals, utilities, environments). They can describe the main features of environments. The notion of adversarial agent cooperation can be discussed in terms of decision problems and algorithms for solving these problems. For dealing with uncertainty in real-world scenarios, students can summarize how Bayesian networks can be employed as a knowledge representation and reasoning formalism in static and dynamic settings. In addition, students can define decision making procedures in simple and sequential settings, with and with complete access to the state of the environment. In this context, students can describe techniques for solving (partially observable) Markov decision problems, and they can recall techniques for measuring the value of information. Students can identify techniques for simultaneous localization and mapping, and can explain planning techniques for achieving desired states. Students can explain coordination problems and decision making in a multi-agent setting in term of different types of equilibria, social choice functions, voting protocol, and mechanism design techniques.

Skills

Students can select an appropriate agent architecture for concrete agent application scenarios. For simplified agent application students can derive decision trees and apply basic optimization techniques. For those applications they can also create Bayesian networks/dynamic Bayesian networks and apply bayesian reasoning for simple queries. Students can also name and apply different sampling techniques for simplified agent scenarios. For simple and complex decision making students can compute the best action or policies for concrete settings. In multi-agent situations students will apply techniques for finding different equilibria states,e.g., Nash equilibria. For multi-agent decision making students will apply different voting protocols and compare and explain the results.


Personal Competence
Social Competence

Students are able to discuss their solutions to problems with others. They communicate in English

Autonomy

Students are able of checking their understanding of complex concepts by solving varaints of concrete problems

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0341: Intelligent Autonomous Agents and Cognitive Robotics
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Rainer Marrone
Language EN
Cycle WiSe
Content
  • Definition of agents, rational behavior, goals, utilities, environment types
  • Adversarial agent cooperation: 
    Agents with complete access to the state(s) of the environment, games, Minimax algorithm, alpha-beta pruning, elements of chance
  • Uncertainty: 
    Motivation: agents with no direct access to the state(s) of the environment, probabilities, conditional probabilities, product rule, Bayes rule, full joint probability distribution, marginalization, summing out, answering queries, complexity, independence assumptions, naive Bayes, conditional independence assumptions
  • Bayesian networks: 
    Syntax and semantics of Bayesian networks, answering queries revised (inference by enumeration), typical-case complexity, pragmatics: reasoning from effect (that can be perceived by an agent) to cause (that cannot be directly perceived).
  • Probabilistic reasoning over time:
    Environmental state may change even without the agent performing actions, dynamic Bayesian networks, Markov assumption, transition model, sensor model, inference problems: filtering, prediction, smoothing, most-likely explanation, special cases: hidden Markov models, Kalman filters, Exact inferences and approximations
  • Decision making under uncertainty:
    Simple decisions: utility theory, multivariate utility functions, dominance, decision networks, value of informatio
    Complex decisions: sequential decision problems, value iteration, policy iteration, MDPs
    Decision-theoretic agents: POMDPs, reduction to multidimensional continuous MDPs, dynamic decision networks
  • Simultaneous Localization and Mapping
  • Planning
  • Game theory (Golden Balls: Split or Share) 
    Decisions with multiple agents, Nash equilibrium, Bayes-Nash equilibrium
  • Social Choice 
    Voting protocols, preferences, paradoxes, Arrow's Theorem,
  • Mechanism Design 
    Fundamentals, dominant strategy implementation, Revelation Principle, Gibbard-Satterthwaite Impossibility Theorem, Direct mechanisms, incentive compatibility, strategy-proofness, Vickrey-Groves-Clarke mechanisms, expected externality mechanisms, participation constraints, individual rationality, budget balancedness, bilateral trade, Myerson-Satterthwaite Theorem
Literature
  1. Artificial Intelligence: A Modern Approach (Third Edition), Stuart Russell, Peter Norvig, Prentice Hall, 2010, Chapters 2-5, 10-11, 13-17
  2. Probabilistic Robotics, Thrun, S., Burgard, W., Fox, D. MIT Press 2005

  3. Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Yoav Shoham, Kevin Leyton-Brown, Cambridge University Press, 2009

Course L0512: Intelligent Autonomous Agents and Cognitive Robotics
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Rainer Marrone
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1336: Soft Computing - Introduction to Machine Learning

Courses
Title Typ Hrs/wk CP
Soft Computing (L1869) Lecture 4 6
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge

Bachelor in Computer Science.

Basics in higher mathematics are inevitable, like calculus, linear algebra, graph theory, and optimization.

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to formalize, compute, and analyze belief networks, alignments of sequences, hidden Markov models, phylogenetic tree models, neural networks, and fuzzy controllers. In particular, inference and learning in belief networks are important topics that the students should be able to master. 

Skills Students can apply the relevant algorithms and determine their complexity, and they can make use of the statistics language R.
Personal Competence
Social Competence

Students are able to solve specific problems alone or in a group and to present the results accordingly.

Autonomy

Students are able to acquire new knowledge from newer literature and to associate the acquired knowledge to other fields.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 25 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L1869: Soft Computing
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Karl-Heinz Zimmermann, Dr. Mehwish Saleemi
Language DE/EN
Cycle WiSe
Content Students are able to formalize, compute, and analyze belief networks, alignments of sequences, hidden Markov models, phylogenetic tree models, neural networks, and fuzzy controllers. In particular, inference and learning in belief networks are important topics that the students should be able to master.

Students can apply the relevant algorithms and determine their complexity, and they can make use of the statistics language R.

Literature

1. David Barber, Bayes Reasoning and Machine Learning, Cambridge Univ. Press, Cambridge, 2012.
2. Volker Claus, Stochastische Automaten, Teubner, Stuttgart, 1971.
3. Ernst Klement, Radko Mesiar, Endre Pap, Triangular Norms, Kluwer, Dordrecht, 2000.
4. Timo Koski, John M. Noble, Bayesian Networks, Wiley, New York, 2009.
5. Dimitris Margaritis, Learning Bayesian Network Model Structure from Data, PhD thesis, Carnegie Mellon
University, Pittsburgh, 2003.
6. Hidetoshi Nishimori, Statistical Physics of Spin Glasses and Information Processing, Oxford Univ. Press,
London, 2001.
7. James R. Norris, Markov Chains, Cambridge Univ. Press, Cambridge, 1996.
8. Maria Rizzo, Statistical Computing with R, Chapman & Hall/CRC, Boca Raton, 2008.
9. Peter Sprites, Clark Glymour, Richard Scheines, Causation, Prediction, and Search, Springer, New York,
1993.
10. Raul Royas, Neural Networks, Springer, Berlin, 1996.
11. Lior Pachter, Bernd Sturmfels, Algebraic Statistics for Computational Biology, Cambridge Univ. Press,
Cambridge, 2005.
12. David A. Sprecher, From Algebra to Computational Algorithms, Docent Press, Boston, 2017.
13. Karl-Heinz Zimmermann, Algebraic Statistics, TubDok, Hamburg, 2016.

Module M1271: Technical Complementary Course II for CSMS (according to Subject Specific Regulations)

Courses
Title Typ Hrs/wk CP
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Die Studierenden können die wesentlichen Inhalte des technischen Faches im Rahmen eines Vortrages oder einer Diskussion wiedergeben.

Skills

The students acquire professional competence in a technical subject available at TUHH.

Personal Competence
Social Competence
Autonomy
Workload in Hours Depends on choice of courses
Credit points 6
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory

Module M1302: Applied Humanoid Robotics

Courses
Title Typ Hrs/wk CP
Applied Humanoid Robotics (L1794) Project-/problem-based Learning 6 6
Module Responsible Patrick Göttsch
Admission Requirements None
Recommended Previous Knowledge
  • Object oriented programming; algorithms and data structures
  • Introduction to control systems
  • Control systems theory and design
  • Mechanics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain humanoid robots.
  • Students can explain the basic concepts, relationships and methods of forward- and inverse kinematics
  • Students learn to apply basic control concepts for different tasks in humanoid robotics.
Skills
  • Students can implement models for humanoid robotic systems in Matlab and C++, and use these models for robot motion or other tasks.
  • They are capable of using models in Matlab for simulation and testing these models if necessary with C++ code on the real robot system.
  • They are capable of selecting methods for solving abstract problems, for which no standard methods are available, and apply it successfully.
Personal Competence
Social Competence
  • Students can develop joint solutions in mixed teams and present these.
  • They can provide appropriate feedback to others, and  constructively handle feedback on their own results
Autonomy
  • Students are able to obtain required information from provided literature sources, and to put in into the context of the lecture.
  • They can independently define tasks and apply the appropriate means to solve them.
Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Course achievement None
Examination Written elaboration
Examination duration and scale 5-10 pages
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L1794: Applied Humanoid Robotics
Typ Project-/problem-based Learning
Hrs/wk 6
CP 6
Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Lecturer Patrick Göttsch
Language DE/EN
Cycle WiSe/SoSe
Content
  • Fundamentals of kinematics
  • Static and dynamic stability of humanoid robotic systems
  • Combination of different software environments (Matlab, C++, etc.)
  • Introduction to the necessary  software frameworks
  • Team project
  • Presentation and Demonstration of intermediate and final results
Literature
  • B. Siciliano, O. Khatib. "Handbook of Robotics. Part A: Robotics Foundations", Springer (2008)

Module M0551: Pattern Recognition and Data Compression

Courses
Title Typ Hrs/wk CP
Pattern Recognition and Data Compression (L0128) Lecture 4 6
Module Responsible Prof. Rolf-Rainer Grigat
Admission Requirements None
Recommended Previous Knowledge

Linear algebra (including PCA, unitary transforms), stochastics and statistics, binary arithmetics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can name the basic concepts of pattern recognition and data compression.

Students are able to discuss logical connections between the concepts covered in the course and to explain them by means of examples.


Skills

Students can apply statistical methods to classification problems in pattern recognition and to prediction in data compression. On a sound theoretical and methodical basis they can analyze characteristic value assignments and classifications and describe data compression and video signal coding. They are able to use highly sophisticated methods and processes of the subject area. Students are capable of assessing different solution approaches in multidimensional decision-making areas.



Personal Competence
Social Competence

k.A.

Autonomy

Students are capable of identifying problems independently and of solving them scientifically, using the methods they have learnt.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 60 Minutes, Content of Lecture and materials in StudIP
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0128: Pattern Recognition and Data Compression
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Rolf-Rainer Grigat
Language EN
Cycle SoSe
Content

Structure of a pattern recognition system, statistical decision theory, classification based on statistical models, polynomial regression, dimension reduction, multilayer perceptron regression, radial basis functions, support vector machines, unsupervised learning and clustering, algorithm-independent machine learning, mixture models and EM, adaptive basis function models and boosting, Markov random fields

Information, entropy, redundancy, mutual information, Markov processes, basic coding schemes (code length, run length coding, prefix-free codes), entropy coding (Huffman, arithmetic coding), dictionary coding (LZ77/Deflate/LZMA2, LZ78/LZW), prediction, DPCM, CALIC, quantization (scalar and vector quantization), transform coding, prediction, decorrelation (DPCM, DCT, hybrid DCT, JPEG, JPEG-LS), motion estimation, subband coding, wavelets, HEVC (H.265,MPEG-H)

Literature

Schürmann: Pattern Classification, Wiley 1996
Murphy, Machine Learning, MIT Press, 2012
Barber, Bayesian Reasoning and Machine Learning, Cambridge, 2012
Duda, Hart, Stork: Pattern Classification, Wiley, 2001
Bishop: Pattern Recognition and Machine Learning, Springer 2006

Salomon, Data Compression, the Complete Reference, Springer, 2000
Sayood, Introduction to Data Compression, Morgan Kaufmann, 2006
Ohm, Multimedia Communication Technology, Springer, 2004
Solari, Digital video and audio compression, McGraw-Hill, 1997
Tekalp, Digital Video Processing, Prentice Hall, 1995

Module M0630: Robotics and Navigation in Medicine

Courses
Title Typ Hrs/wk CP
Robotics and Navigation in Medicine (L0335) Lecture 2 3
Robotics and Navigation in Medicine (L0338) Project Seminar 2 2
Robotics and Navigation in Medicine (L0336) Recitation Section (small) 1 1
Module Responsible Prof. Alexander Schlaefer
Admission Requirements None
Recommended Previous Knowledge
  • principles of math (algebra, analysis/calculus)
  • principles of programming, e.g., in Java or C++
  • solid R or Matlab skills
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students can explain kinematics and tracking systems in clinical contexts and illustrate systems and their components in detail. Systems can be evaluated with respect to collision detection and  safety and regulations. Students can assess typical systems regarding design and  limitations.

Skills

The students are able to design and evaluate navigation systems and robotic systems for medical applications.


Personal Competence
Social Competence

The students discuss the results of other groups, provide helpful feedback and can incoorporate feedback into their work.

Autonomy

The students can reflect their knowledge and document the results of their work. They can present the results in an appropriate manner.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Course achievement
Compulsory Bonus Form Description
Yes 10 % Written elaboration
Yes 10 % Presentation
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Product Development, Materials and Production: Specialisation Product Development: Elective Compulsory
Product Development, Materials and Production: Specialisation Production: Elective Compulsory
Product Development, Materials and Production: Specialisation Materials: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory
Course L0335: Robotics and Navigation in Medicine
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle SoSe
Content

- kinematics
- calibration
- tracking systems
- navigation and image guidance
- motion compensation
The seminar extends and complements the contents of the lecture with respect to recent research results.


Literature

Spong et al.: Robot Modeling and Control, 2005
Troccaz: Medical Robotics, 2012
Further literature will be given in the lecture.

Course L0338: Robotics and Navigation in Medicine
Typ Project Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L0336: Robotics and Navigation in Medicine
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0673: Information Theory and Coding

Courses
Title Typ Hrs/wk CP
Information Theory and Coding (L0436) Lecture 3 4
Information Theory and Coding (L0438) Recitation Section (large) 1 2
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics 1-3
  • Probability theory and random processes
  • Basic knowledge of communications engineering (e.g. from lecture "Fundamentals of Communications and Random Processes")
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know the basic definitions for quantification of information in the sense of information theory. They know Shannon's source coding theorem and channel coding theorem and are able to determine theoretical limits of data compression and error-free data transmission over noisy channels. They understand the principles of source coding as well as error-detecting and error-correcting channel coding. They are familiar with the principles of decoding, in particular with modern methods of iterative decoding. They know fundamental coding schemes, their properties and decoding algorithms. 
Skills The students are able to determine the limits of data compression as well as of data transmission through noisy channels and based on those limits to design basic parameters of a transmission scheme. They can estimate the parameters of an error-detecting or error-correcting channel coding scheme for achieving certain performance targets. They are able to compare the properties of basic channel coding and decoding schemes regarding error correction capabilities, decoding delay, decoding complexity and to decide for a suitable method. They are capable of implementing basic coding and decoding schemes in software.
Personal Competence
Social Competence

The students can jointly solve specific problems.

Autonomy

The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation II. Engineering Science: Elective Compulsory
Information and Communication Systems: Core Qualification: Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Course L0436: Information Theory and Coding
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle SoSe
Content
  • Fundamentals of information theory

    • Self information, entropy, mutual information

    • Source coding theorem, channel coding theorem

    • Channel capacity of various channels

  • Fundamental source coding algorithms:

    • Huffman Code, Lempel Ziv Algorithm

  • Fundamentals of channel coding

    • Basic parameters of channel coding and respective bounds

    • Decoding principles: Maximum-A-Posteriori Decoding, Maximum-Likelihood Decoding, Hard-Decision-Decoding and Soft-Decision-Decoding

    • Error probability

  • Block codes

  • Low Density Parity Check (LDPC) Codes and iterative Ddecoding

  • Convolutional codes and Viterbi-Decoding

  • Turbo Codes and iterative decoding

  • Coded Modulation

Literature

Bossert, M.: Kanalcodierung. Oldenbourg.

Friedrichs, B.: Kanalcodierung. Springer.

Lin, S., Costello, D.: Error Control Coding. Prentice Hall.

Roth, R.: Introduction to Coding Theory.

Johnson, S.: Iterative Error Correction. Cambridge.

Richardson, T., Urbanke, R.: Modern Coding Theory. Cambridge University Press.

Gallager, R. G.: Information theory and reliable communication. Whiley-VCH

Cover, T., Thomas, J.: Elements of information theory. Wiley.

Course L0438: Information Theory and Coding
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1310: Discrete Differential Geometry

Courses
Title Typ Hrs/wk CP
Discrete Differential Geometry (L1808) Lecture 4 6
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge Linear Algebra, Multivariate Calculus 
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

These lectures are on geometrical aspects of the solutions of differential equations and their treatment on the computer. The required basics from linear algebra and analysis are reviewed at the beginning. Applications are to curved surfaces in space, to mechanics and mechatronics, to different types of field equations, and to the tranfer of mathematical constructions to data types, compiler functions, programming languages, and special compute circuits.

- basic prerequisites from linear algebra, tensors, exterior algebra, Clifford algebras

- basic prerequisites from coordinate-free analysis, vector fields and differential forms, integration, discretization

- local differential geometry: connections, symplectic geometry and Hamiltonian systems, Riemannian geometry, discretization

- global differential geometry: manifolds, Lie groups, fiber bundles, random processes, space and time


Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 25 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1808: Discrete Differential Geometry
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Georg Friedrich Mayer-Lindenberg
Language DE/EN
Cycle SoSe
Content

These lectures deal with geometric aspects of differential equations and with their treatment on the computer. The prerequisites from linear algebra and analysis are reviewed at the beginning. Applications are to curved surfaces, to classical mechanics and mechatronics, to various field equations, to computer graphics and to transferring mathematical constructions to data types, compiler functions, programming languages, and special hardware. Keywords:

Basics from linear algebra, tensors, exterior algebra, Clifford algebras, tuple types

Basics of coordinate-free analysis, vector fields and differential forms, integration, discrete exterior calculus

Local differential geometry: connections, symplectic geometry, Riemannian geometry, discrete mechanics and connections

Global differential geometry: manifolds, Lie groups, fibre bundles, Fourier decompositions, random processes, space and time


Literature

Agricola, Friedrich,  Vektoranalysis,  Vieweg/Teubner 2010

A.C. Da Silva,  Lectures on Symplectic Geometry, Springer L.N. Math. 1764

J. Snygg, Differential Geometry using Clifford's Algebra, Birkhäuser 2010

T. Frankel, The Geometry of Physics, Cambridge U. P. 2012

M.Desbrun et al., Discrete exterior calculus, arXiv:math/0508341v2

J.Marsden  et al., Discrete Mechanics and Variational Integrators, Acta numerica. 2001

Module M0711: Numerical Mathematics II

Courses
Title Typ Hrs/wk CP
Numerical Mathematics II (L0568) Lecture 2 3
Numerical Mathematics II (L0569) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Numerical Mathematics I
  • MATLAB knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • name advanced numerical methods for interpolation, integration, linear least squares problems, eigenvalue problems, nonlinear root finding problems and explain their core ideas,
  • repeat convergence statements for the numerical methods,
  • sketch convergence proofs,
  • explain practical aspects of numerical methods concerning runtime and storage needs


    explain aspects regarding the practical implementation of numerical methods with respect to computational and storage complexity.


Skills

Students are able to

  • implement, apply and compare advanced numerical methods in MATLAB,
  • justify the convergence behaviour of numerical methods with respect to the problem and solution algorithm and to transfer it to related problems,
  • for a given problem, develop a suitable solution approach, if necessary through composition of several algorithms, to execute this approach and to critically evaluate the results


Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 25 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0568: Numerical Mathematics II
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Jens-Peter Zemke
Language DE/EN
Cycle SoSe
Content
  1. Error and stability: Notions and estimates
  2. Interpolation: Rational and trigonometric interpolation
  3. Quadrature: Gaussian quadrature, orthogonal polynomials
  4. Linear systems: Perturbation theory of decompositions, structured matrices
  5. Eigenvalue problems: LR-, QD-, QR-Algorithmus
  6. Krylov space methods: Arnoldi-, Lanczos methods
Literature
  • Stoer/Bulirsch: Numerische Mathematik 1, Springer
  • Dahmen, Reusken: Numerik für Ingenieure und Naturwissenschaftler, Springer
Course L0569: Numerical Mathematics II
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Jens-Peter Zemke
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0840: Optimal and Robust Control

Courses
Title Typ Hrs/wk CP
Optimal and Robust Control (L0658) Lecture 2 3
Optimal and Robust Control (L0659) Recitation Section (small) 2 3
Module Responsible Prof. Herbert Werner
Admission Requirements None
Recommended Previous Knowledge
  • Classical control (frequency response, root locus)
  • State space methods
  • Linear algebra, singular value decomposition
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the significance of the matrix Riccati equation for the solution of LQ problems.
  • They can explain the duality between optimal state feedback and optimal state estimation.
  • They can explain how the H2 and H-infinity norms are used to represent stability and performance constraints.
  • They can explain how an LQG design problem can be formulated as special case of an H2 design problem.
  • They  can explain how model uncertainty can be represented in a way that lends itself to robust controller design
  • They can explain how - based on the small gain theorem - a robust controller can guarantee stability and performance for an uncertain plant.
  • They understand how analysis and synthesis conditions on feedback loops can be represented as linear matrix inequalities.
Skills
  • Students are capable of designing and tuning LQG controllers for multivariable plant models.
  • They are capable of representing a H2 or H-infinity design problem in the form of a generalized plant, and of using standard software tools for solving it.
  • They are capable of translating time and frequency domain specifications for control loops into constraints on closed-loop sensitivity functions, and of carrying out a mixed-sensitivity design.
  • They are capable of constructing an LFT uncertainty model for an uncertain system, and of designing a mixed-objective robust controller.
  • They are capable of formulating analysis and synthesis conditions as linear matrix inequalities (LMI), and of using standard LMI-solvers for solving them.
  • They can carry out all of the above using standard software tools (Matlab robust control toolbox).
Personal Competence
Social Competence Students can work in small groups on specific problems to arrive at joint solutions. 
Autonomy

Students are able to find required information in sources provided (lecture notes, literature, software documentation) and use it to solve given problems. 


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory
Energy Systems: Core Qualification: Elective Compulsory
Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Product Development, Materials and Production: Specialisation Product Development: Elective Compulsory
Product Development, Materials and Production: Specialisation Production: Elective Compulsory
Product Development, Materials and Production: Specialisation Materials: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Core Qualification: Elective Compulsory
Course L0658: Optimal and Robust Control
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle SoSe
Content
  • Optimal regulator problem with finite time horizon, Riccati differential equation
  • Time-varying and steady state solutions, algebraic Riccati equation, Hamiltonian system
  • Kalman’s identity, phase margin of LQR controllers, spectral factorization
  • Optimal state estimation, Kalman filter, LQG control
  • Generalized plant, review of LQG control
  • Signal and system norms, computing H2 and H∞ norms
  • Singular value plots, input and output directions
  • Mixed sensitivity design, H∞ loop shaping, choice of weighting filters
  • Case study: design example flight control
  • Linear matrix inequalities, design specifications as LMI constraints (H2, H∞ and pole region)
  • Controller synthesis by solving LMI problems, multi-objective design
  • Robust control of uncertain systems, small gain theorem, representation of parameter uncertainty
Literature
  • Werner, H., Lecture Notes: "Optimale und Robuste Regelung"
  • Boyd, S., L. El Ghaoui, E. Feron and V. Balakrishnan "Linear Matrix Inequalities in Systems and Control", SIAM, Philadelphia, PA, 1994
  • Skogestad, S. and I. Postlewhaite "Multivariable Feedback Control", John Wiley, Chichester, England, 1996
  • Strang, G. "Linear Algebra and its Applications", Harcourt Brace Jovanovic, Orlando, FA, 1988
  • Zhou, K. and J. Doyle "Essentials of Robust Control", Prentice Hall International, Upper Saddle River, NJ, 1998
Course L0659: Optimal and Robust Control
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0627: Machine Learning and Data Mining

Courses
Title Typ Hrs/wk CP
Machine Learning and Data Mining (L0340) Lecture 2 4
Machine Learning and Data Mining (L0510) Recitation Section (small) 2 2
Module Responsible NN
Admission Requirements None
Recommended Previous Knowledge
  • Calculus
  • Stochastics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the difference between instance-based and model-based learning approaches, and they can enumerate basic machine learning technique for each of the two basic approaches, either on the basis of static data, or on the basis of incrementally incoming data . For dealing with uncertainty, students can describe suitable representation formalisms, and they explain how axioms, features, parameters, or structures used in these formalisms can be learned automatically with different algorithms. Students are also able to sketch different clustering techniques. They depict how the performance of learned classifiers can be improved by ensemble learning, and they can summarize how this influences computational learning theory. Algorithms for reinforcement learning can also be explained by students.

Skills

Student derive decision trees and, in turn, propositional rule sets from simple and static data tables and are able to name and explain basic optimization techniques. They present and apply the basic idea of first-order inductive leaning. Students apply the BME, MAP, ML, and EM algorithms for learning parameters of Bayesian networks and compare the different algorithms. They also know how to carry out Gaussian mixture learning. They can contrast kNN classifiers, neural networks, and support vector machines, and name their basic application areas and algorithmic properties. Students can describe basic clustering techniques and explain the basic components of those techniques. Students compare related machine learning techniques, e.g., k-means clustering and nearest neighbor classification. They can distinguish various ensemble learning techniques and compare the different goals of those techniques.




Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0340: Machine Learning and Data Mining
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Rainer Marrone
Language EN
Cycle SoSe
Content
  • Decision trees
  • First-order inductive learning
  • Incremental learning: Version spaces
  • Uncertainty
  • Bayesian networks
  • Learning parameters of Bayesian networks
    BME, MAP, ML, EM algorithm
  • Learning structures of Bayesian networks
  • Gaussian Mixture Models
  • kNN classifier, neural network classifier, support vector machine (SVM) classifier
  • Clustering
    Distance measures, k-means clustering, nearest neighbor clustering
  • Kernel Density Estimation
  • Ensemble Learning
  • Reinforcement Learning
  • Computational Learning Theory
Literature
  1. Artificial Intelligence: A Modern Approach (Third Edition), Stuart Russel, Peter Norvig, Prentice Hall, 2010, Chapters 13, 14, 18-21
  2. Machine Learning: A Probabilistic Perspective, Kevin Murphy, MIT Press 2012
Course L0510: Machine Learning and Data Mining
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Rainer Marrone
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0832: Advanced Topics in Control

Courses
Title Typ Hrs/wk CP
Advanced Topics in Control (L0661) Lecture 2 3
Advanced Topics in Control (L0662) Recitation Section (small) 2 3
Module Responsible Prof. Herbert Werner
Admission Requirements None
Recommended Previous Knowledge H-infinity optimal control, mixed-sensitivity design, linear matrix inequalities 
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the advantages and shortcomings of the classical gain scheduling approach
  • They can explain the representation of nonlinear systems in the form of quasi-LPV systems
  • They can explain how stability and performance conditions for LPV systems can be formulated as LMI conditions
  • They can explain how gridding techniques can be used to solve analysis and synthesis problems for LPV systems
  • They are familiar with polytopic and LFT representations of LPV systems and some of the basic synthesis techniques associated with each of these model structures


  • Students can explain how graph theoretic concepts are used to represent the communication topology of multiagent systems
  • They can explain the convergence properties of  first order consensus protocols
  • They can explain analysis and synthesis conditions for formation control loops involving either LTI or LPV agent models


  • Students can explain the state space representation of spatially invariant distributed systems that are discretized according to an actuator/sensor array
  • They can explain (in outline) the extension of the bounded real lemma to such distributed systems and the associated synthesis conditions for distributed controllers

Skills
  • Students are capable of constructing LPV models of nonlinear plants and carry out a mixed-sensitivity design of gain-scheduled controllers; they can do this using polytopic, LFT or general LPV models 
  • They are able to use standard software tools (Matlab robust control toolbox) for these tasks


  • Students are able to design distributed formation controllers for groups of agents with either LTI or LPV dynamics, using Matlab tools provided


  • Students are able to design distributed controllers for spatially interconnected systems, using the Matlab MD-toolbox
Personal Competence
Social Competence Students can work in small groups and arrive at joint results.
Autonomy

Students are able to find required information in sources provided (lecture notes, literature, software documentation) and use it to solve given problems. 


 
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory
Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory
Aircraft Systems Engineering: Specialisation Avionic Systems: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Core Qualification: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Robotics and Computer Science: Elective Compulsory
Course L0661: Advanced Topics in Control
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle WiSe
Content
  • Linear Parameter-Varying (LPV) Gain Scheduling

    - Linearizing gain scheduling, hidden coupling
    - Jacobian linearization vs. quasi-LPV models
    - Stability and induced L2 norm of LPV systems
    - Synthesis of LPV controllers based on the two-sided projection lemma
    - Simplifications: controller synthesis for polytopic and LFT models
    - Experimental identification of LPV models
    - Controller synthesis based on input/output models
    - Applications: LPV torque vectoring for electric vehicles, LPV control of a robotic manipulator
  • Control of Multi-Agent Systems

    - Communication graphs
    - Spectral properties of the graph Laplacian
    - First and second order consensus protocols
    - Formation control, stability and performance
    - LPV models for agents subject to nonholonomic constraints
    - Application: formation control for a team of quadrotor helicopters
  • Control of Spatially Interconnected Systems

    - Multidimensional signals, l2 and L2 signal norm
    - Multidimensional systems in Roesser state space form
    - Extension of real-bounded lemma to spatially interconnected systems
    - LMI-based synthesis of distributed controllers
    - Spatial LPV control of spatially varying systems
    - Applications: control of temperature profiles, vibration damping for an actuated beam
Literature
  • Werner, H., Lecture Notes "Advanced Topics in Control"
  • Selection of relevant research papers made available as pdf documents via StudIP
Course L0662: Advanced Topics in Control
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0552: 3D Computer Vision

Courses
Title Typ Hrs/wk CP
3D Computer Vision (L0129) Lecture 2 3
3D Computer Vision (L0130) Recitation Section (small) 2 3
Module Responsible Prof. Rolf-Rainer Grigat
Admission Requirements None
Recommended Previous Knowledge
  • Knowlege of the modules Digital Image Analysis and Pattern Recognition and Data Compression are used in the practical task
  • Linear Algebra (including PCA, SVD), nonlinear optimization (Levenberg-Marquardt), basics of stochastics and basics of Matlab are required and cannot be explained in detail during the lecture.
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain and describe the field of projective geometry.

Skills

Students are capable of

  • Implementing an exemplary 3D or volumetric analysis task
  • Using highly sophisticated methods and procedures of the subject area
  • Identifying problems and
  • Developing and implementing creative solution suggestions.

With assistance from the teacher students are able to link the contents of the three subject areas (modules)

  • Digital Image Analysis 
  • Pattern Recognition and Data Compression
    and 
  • 3D Computer Vision 

in practical assignments.

Personal Competence
Social Competence

Students can collaborate in a small team on the practical realization and testing of a system to reconstruct a three-dimensional scene or to evaluate volume data sets.

Autonomy

Students are able to solve simple tasks independently with reference to the contents of the lectures and the exercise sets.

Students are able to solve detailed problems independently with the aid of the tutorial’s programming task.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 60 Minutes, Content of Lecture and materials in StudIP
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation II: Intelligence Engineering: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Robotics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0129: 3D Computer Vision
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Rolf-Rainer Grigat
Language EN
Cycle WiSe
Content
  • Projective Geometry and Transformations in 2D und 3D in homogeneous coordinates
  • Projection matrix, calibration
  • Epipolar Geometry, fundamental and essential matrices, weak calibration, 5 point algorithm
  • Homographies 2D and 3D
  • Trifocal Tensor
  • Correspondence search
Literature
  • Skriptum Grigat/Wenzel
  • Hartley, Zisserman: Multiple View Geometry in Computer Vision. Cambridge 2003.
Course L0130: 3D Computer Vision
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Rolf-Rainer Grigat
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1552: Mathematics of Neural Networks

Courses
Title Typ Hrs/wk CP
Mathematics of Neural Networks (L2322) Lecture 2 3
Mathematics of Neural Networks (L2323) Recitation Section (small) 2 3
Module Responsible Dr. Jens-Peter Zemke
Admission Requirements None
Recommended Previous Knowledge
  1. Mathematics I-III
  2. Numerical Mathematics 1/ Numerics
  3. Programming skills, preferably in Python
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students are able to name, state and classify state-of-the-art neural networks and their corresponding mathematical basics. They can assess the difficulties of different neural networks.
Skills Students are able to implement, understand, and, tailored to the field of application, apply neural networks.
Personal Competence
Social Competence

Students can

  • develop and document joint solutions in small teams;
  • form groups to further develop the ideas and transfer them to other areas of applicability;
  • form a team to develop, build, and advance a software library.
Autonomy

Students are able to

  • correctly assess the time and effort of self-defined work;
  • assess whether the supporting theoretical and practical excercises are better solved individually or in a team;
  • define test problems for testing and expanding the methods;
  • assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Oral exam
Examination duration and scale 25 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation III. Mathematics: Elective Compulsory
Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Robotics and Computer Science: Elective Compulsory
Course L2322: Mathematics of Neural Networks
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Jens-Peter Zemke
Language DE/EN
Cycle WiSe
Content
  1. Basics: analogy; layout of neural nets, universal approximation, NP-completeness
  2. Feedforward nets: backpropagation, variants of Stochastistic Gradients
  3. Deep Learning: problems and solution strategies
  4. Deep Belief Networks: energy based models, Contrastive Divergence
  5. CNN: idea, layout, FFT and Winograds algorithms, implementation details
  6. RNN: idea, dynamical systems, training, LSTM
  7. ResNN: idea, relation to neural ODEs
  8. Standard libraries: Tensorflow, Keras, PyTorch
  9. Recent trends
Literature
  1. Skript
  2. Online-Werke:
    • http://neuralnetworksanddeeplearning.com/
    • https://www.deeplearningbook.org/


Course L2323: Mathematics of Neural Networks
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Jens-Peter Zemke
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0738: Digital Audio Signal Processing

Courses
Title Typ Hrs/wk CP
Digital Audio Signal Processing (L0650) Lecture 3 4
Digital Audio Signal Processing (L0651) Recitation Section (large) 1 2
Module Responsible Prof. Udo Zölzer
Admission Requirements None
Recommended Previous Knowledge

Signals and Systems

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Die Studierenden können die grundlegenden Verfahren und Methoden der digitalen Audiosignalverarbeitung erklären. Sie können die wesentlichen physikalischen Effekte bei der Sprach- und Audiosignalverarbeitung erläutern und in Kategorien einordnen. Sie können einen Überblick der numerischen Methoden und messtechnischen Charakterisierung von Algorithmen zur Audiosignalverarbeitung geben. Sie können die erarbeiteten Algorithmen auf weitere Anwendungen im Bereich der Informationstechnik und Informatik abstrahieren.

Skills

The students will be able to apply methods and techniques from audio signal processing in the fields of mobile and internet communication. They can rely on elementary algorithms of audio signal processing in form of Matlab code and interactive JAVA applets. They can study parameter modifications and evaluate the influence on human perception and technical applications in a variety of applications beyond audio signal processing. Students can perform measurements in time and frequency domain in order to give objective and subjective quality measures with respect to the methods and applications.

Personal Competence
Social Competence

The students can work in small groups to study special tasks and problems and will be enforced to present their results with adequate methods during the exercise.

Autonomy

The students will be able to retrieve information out of the relevant literature in the field and putt hem into the context of the lecture. They can relate their gathered knowledge and relate them to other lectures (signals and systems, digital communication systems, image and video processing, and pattern recognition). They will be prepared to understand and communicate problems and effects in the field audio signal processing.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 45 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Course L0650: Digital Audio Signal Processing
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Udo Zölzer
Language EN
Cycle WiSe
Content
  • Introduction (Studio Technology,  Digital Transmission Systems, Storage Media, Audio Components at Home)

  • Quantization (Signal Quantization, Dither, Noise Shaping, Number Representation)

  • AD/DA Conversion (Methods, AD Converters, DA Converters, Audio Processing Systems, Digital Signal Processors, Digital Audio Interfaces, Single-Processor Systems, Multiprocessor Systems)

  • Equalizers (Recursive Audio Filters, Nonrecursive Audio Filters, Multi-Complementary Filter Bank)

  • Room Simulation (Early Reflections, Subsequent Reverberation, Approximation of Room Impulse Responses)

  • Dynamic Range Control (Static Curve, Dynamic Behavior, Implementation, Realization Aspects)

  • Sampling Rate Conversion (Synchronous Conversion, Asynchronous Conversion, Interpolation Methods)

  • Data Compression (Lossless Data Compression, Lossy Data Compression, Psychoacoustics, ISO-MPEG1 Audio Coding)

Literature

- U. Zölzer, Digitale Audiosignalverarbeitung, 3. Aufl., B.G. Teubner, 2005.

- U. Zölzer, Digitale Audio Signal Processing, 2nd Edition, J. Wiley & Sons, 2005.


- U. Zölzer (Ed), Digital Audio Effects, 2nd Edition, J. Wiley & Sons, 2011.


 






Course L0651: Digital Audio Signal Processing
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Udo Zölzer
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1249: Medical Imaging

Courses
Title Typ Hrs/wk CP
Medical Imaging (L1694) Lecture 2 3
Medical Imaging (L1695) Recitation Section (small) 2 3
Module Responsible Prof. Tobias Knopp
Admission Requirements None
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Course achievement None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation II: Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L1694: Medical Imaging
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language DE
Cycle WiSe
Content
Literature

Bildgebende Verfahren in der Medizin; O. Dössel; Springer, Berlin, 2000

Bildgebende Systeme für die medizinische Diagnostik; H. Morneburg (Hrsg.); Publicis MCD, München, 1995

Introduction to the Mathematics of Medical Imaging; C. L.Epstein; Siam, Philadelphia, 2008

Medical Image Processing, Reconstruction and Restoration; J. Jan; Taylor and Francis, Boca Raton, 2006

Principles of Magnetic Resonance Imaging; Z.-P. Liang and P. C. Lauterbur; IEEE Press, New York, 1999

Course L1695: Medical Imaging
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Thesis

Module M-002: Master Thesis

Courses
Title Typ Hrs/wk CP
Module Responsible Professoren der TUHH
Admission Requirements
  • According to General Regulations §21 (1):

    At least 60 credit points have to be achieved in study programme. The examinations board decides on exceptions.

Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • The students can use specialized knowledge (facts, theories, and methods) of their subject competently on specialized issues.
  • The students can explain in depth the relevant approaches and terminologies in one or more areas of their subject, describing current developments and taking up a critical position on them.
  • The students can place a research task in their subject area in its context and describe and critically assess the state of research.


Skills

The students are able:

  • To select, apply and, if necessary, develop further methods that are suitable for solving the specialized problem in question.
  • To apply knowledge they have acquired and methods they have learnt in the course of their studies to complex and/or incompletely defined problems in a solution-oriented way.
  • To develop new scientific findings in their subject area and subject them to a critical assessment.
Personal Competence
Social Competence

Students can

  • Both in writing and orally outline a scientific issue for an expert audience accurately, understandably and in a structured way.
  • Deal with issues competently in an expert discussion and answer them in a manner that is appropriate to the addressees while upholding their own assessments and viewpoints convincingly.


Autonomy

Students are able:

  • To structure a project of their own in work packages and to work them off accordingly.
  • To work their way in depth into a largely unknown subject and to access the information required for them to do so.
  • To apply the techniques of scientific work comprehensively in research of their own.
Workload in Hours Independent Study Time 900, Study Time in Lecture 0
Credit points 30
Course achievement None
Examination Thesis
Examination duration and scale According to General Regulations
Assignment for the Following Curricula Civil Engineering: Thesis: Compulsory
Bioprocess Engineering: Thesis: Compulsory
Chemical and Bioprocess Engineering: Thesis: Compulsory
Computer Science: Thesis: Compulsory
Electrical Engineering: Thesis: Compulsory
Energy and Environmental Engineering: Thesis: Compulsory
Energy Systems: Thesis: Compulsory
Environmental Engineering: Thesis: Compulsory
Aircraft Systems Engineering: Thesis: Compulsory
Global Innovation Management: Thesis: Compulsory
Computational Science and Engineering: Thesis: Compulsory
Information and Communication Systems: Thesis: Compulsory
International Management and Engineering: Thesis: Compulsory
Joint European Master in Environmental Studies - Cities and Sustainability: Thesis: Compulsory
Logistics, Infrastructure and Mobility: Thesis: Compulsory
Materials Science: Thesis: Compulsory
Mathematical Modelling in Engineering: Theory, Numerics, Applications: Thesis: Compulsory
Mechanical Engineering and Management: Thesis: Compulsory
Mechatronics: Thesis: Compulsory
Biomedical Engineering: Thesis: Compulsory
Microelectronics and Microsystems: Thesis: Compulsory
Product Development, Materials and Production: Thesis: Compulsory
Renewable Energies: Thesis: Compulsory
Naval Architecture and Ocean Engineering: Thesis: Compulsory
Ship and Offshore Technology: Thesis: Compulsory
Teilstudiengang Lehramt Metalltechnik: Thesis: Compulsory
Theoretical Mechanical Engineering: Thesis: Compulsory
Process Engineering: Thesis: Compulsory
Water and Environmental Engineering: Thesis: Compulsory
Certification in Engineering & Advisory in Aviation: Thesis: Compulsory