Study plan
Compulsory elective modules 1. Semester
Compulsory elective modules 2. Semester
Compulsory elective modules 3. Semester
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 6ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 5ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 6ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 4SWS
- 6ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
- WP
- 2SWS
- 3ECTS
Compulsory elective modules 4. Semester
Neurophysiologie 1
Systembiologie 2: Systemtheorie
Angewandte Biosignalverarbeitung - Einf. In maschinelle Lernverfahren
Angewandte Biosignalverarbeitung - Schlagdetektion
Ausgewählte Kapitel der Digitalen Technologien 1
Ausgewählte Kapitel der Digitalen Technologien 2
Ausgewählte Softwaresysteme - Programmierung IV
Automotive Systems
Bewegungsanalyse
Bildgebende Verfahren der Medizintechnik 1
Bildgebende Verfahren der Medizintechnik 2
Cyber Security 1
Cyber Security 2
Digitale Signalverarbeitung 2
Digitale Signalverarbeitung für (Mobil-)Kommunikationssysteme
EM Design
Einführung in Maschinelles Lernen und Künstliche Intelligenz
Einführung in die Radartechnik
Embedded Systems Hardware Design and Rapid Prototyping
Extended Reality
Extended Reality 2
Grundlagen der Mensch-Computer-Interaktion
IoT-Protokolle
Mathematik Ergänzungen 1
Mathematik Ergänzungen 2
Medizinische Signalverarbeitung
Neurophysiologie 2
RMS anerk.
RMS anerk.
Regulatorische Grundlagen für Medizinprodukte - Teil I
Regulatorische Grundlagen für Medizinprodukte - Teil II
Robotik 1
Robotik 2
Sensorik
Softwareentwicklung robotischer Systeme mit ROS
Systembiologie 1: biologische Netzwerke
Compulsory elective modules 5. Semester
Compulsory elective modules 6. Semester
Module overview
1. Semester of study
Grundlagen der Informationstechnik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10020
Duration (semester)
1
Learning outcomes/competences
Students have a basic understanding of digital technology and
are familiar with some of the methods and mathematical fundamentals required in the advanced
courses. They are able to describe certain problems in the field of
digital technology and the fundamentals of information technology both verbally and mathematically
and to solve problems in these areas using systematic methods. They have gained an understanding of the discrete
nature that characterizes information technology systems on many levels.
are familiar with some of the methods and mathematical fundamentals required in the advanced
courses. They are able to describe certain problems in the field of
digital technology and the fundamentals of information technology both verbally and mathematically
and to solve problems in these areas using systematic methods. They have gained an understanding of the discrete
nature that characterizes information technology systems on many levels.
Contents
The course highlights perspectives inherent in digital and information technology systems that may initially
seem somewhat abstract. The discrete nature of the
subject matter is the primary focus. First, a clear and understandable
foundation is established using digital circuits—starting with
simple logic circuits and progressing to arithmetic circuits and automata. The discussion is then broadened to include algebraic structures, arithmetic
with residue classes and polynomial rings, thereby shedding new light
on what has already been learned. Practical applications—computations over number fields, CRT for reducing the computational effort in
the implementation of cryptographic methods, polynomial multiplication and division using
shift registers for error-correcting coding schemes, among other things, maximum sequence generation for, among other things,
communications engineering purposes—are introduced (although some topics have not yet been fully
covered), thereby preparing the groundwork for and building upon the material of subsequent courses.
• Distinction between analog and digital signals and systems, representation of digital signals,
number systems and representations
• logical gates, switching algebra, combinational circuits, disjunctive and
conjunctive normal form
• Circuit minimization (Karnaugh map, Quine–McCluskey)
• Arithmetic circuits: adders, multipliers, convolution
• Sequential circuits: flip-flops, automata
• Shift register circuits: linear (and nonlinear) feedback, m-sequences, structures
(Fibonacci, Galois)
• Algebraic structures, Boolean algebra, residue classes, polynomial rings
seem somewhat abstract. The discrete nature of the
subject matter is the primary focus. First, a clear and understandable
foundation is established using digital circuits—starting with
simple logic circuits and progressing to arithmetic circuits and automata. The discussion is then broadened to include algebraic structures, arithmetic
with residue classes and polynomial rings, thereby shedding new light
on what has already been learned. Practical applications—computations over number fields, CRT for reducing the computational effort in
the implementation of cryptographic methods, polynomial multiplication and division using
shift registers for error-correcting coding schemes, among other things, maximum sequence generation for, among other things,
communications engineering purposes—are introduced (although some topics have not yet been fully
covered), thereby preparing the groundwork for and building upon the material of subsequent courses.
• Distinction between analog and digital signals and systems, representation of digital signals,
number systems and representations
• logical gates, switching algebra, combinational circuits, disjunctive and
conjunctive normal form
• Circuit minimization (Karnaugh map, Quine–McCluskey)
• Arithmetic circuits: adders, multipliers, convolution
• Sequential circuits: flip-flops, automata
• Shift register circuits: linear (and nonlinear) feedback, m-sequences, structures
(Fibonacci, Galois)
• Algebraic structures, Boolean algebra, residue classes, polynomial rings
Teaching methods
The lecture is designed to convey theoretical content. At times, supplementary references are made to the
reading list to help students practice working with it and introduce them to the process of seeking out
additional perspectives. In the exercises, the methods taught
are applied and the theoretical content is explored in greater depth.
The exercises take place in small groups, where students can present and discuss their own solutions
.
reading list to help students practice working with it and introduce them to the process of seeking out
additional perspectives. In the exercises, the methods taught
are applied and the theoretical content is explored in greater depth.
The exercises take place in small groups, where students can present and discuss their own solutions
.
Participation requirements
Formatting: none
Content: none
Content: none
Forms of examination
Module Exam: Fundamentals of Information Technology:
Written Exam (120 min.)
Written Exam (120 min.)
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
wird in der Veranstaltung angegeben
Informatik 1- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10160
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Students can explain the key principles of imperative, structured, and basic
object-oriented programming on a small scale and apply them to develop simple programs.
They can explain, analyze, and evaluate basic algorithms and data structures as well as their
relationships, and apply them to implement programs for
targeted problem-solving.
Subject-Specific and Methodological Competence:
Students acquire the formal competence to explain the principles, methods, concepts, and notations of programming on a small scale, place them in various contexts, and apply them in imperative (structured and elementary object-oriented) programs. This includes identifying the algorithmic core of a simple problem and designing an design an algorithm, as well as to apply means of data and program structuring in a targeted manner. Students can describe the recursive core of a problem and implement a recursive problem-solving strategy.
They acquire fundamental analytical competence to analyze algorithms and data structures as well as their properties. This competency also includes the ability to independently familiarize themselves with applications and tools, such as programming libraries and development environments, and to use them effectively.
Subject-Specific and Methodological Competence:
Students acquire the formal competence to explain the principles, methods, concepts, and notations of programming on a small scale, place them in various contexts, and apply them in imperative (structured and elementary object-oriented) programs. This includes identifying the algorithmic core of a simple problem and designing an design an algorithm, as well as to apply means of data and program structuring in a targeted manner. Students can describe the recursive core of a problem and implement a recursive problem-solving strategy.
They acquire fundamental analytical competence to analyze algorithms and data structures as well as their properties. This competency also includes the ability to independently familiarize themselves with applications and tools, such as programming libraries and development environments, and to use them effectively.
Contents
Fundamental Concepts and Methods in Computer Science: Algorithms, Programs,
Object-Oriented Programming
• Algorithmic problem-solving skills using Java-Kara (imperative, object-oriented programming model)
• Imperative language elements (in Java and C)
• Elementary object-oriented programming (in Java)
• Approaches for the step-by-step structured development of programs
• Algorithmic description methods, such as UML activity diagrams
• Recursion
• Selected algorithms and data structures
• Parameters, variables, arrays (specific features in C and Java)
• Algorithmic problem-solving skills using Java-Kara (imperative, object-oriented programming model)
• Imperative language elements (in Java and C)
• Elementary object-oriented programming (in Java)
• Approaches for the step-by-step structured development of programs
• Algorithmic description methods, such as UML activity diagrams
• Recursion
• Selected algorithms and data structures
• Parameters, variables, arrays (specific features in C and Java)
Teaching methods
Lecture involving student participation
Completion of programming assignments on computers, either individually or in teams, during the
lab session
Language: German
Participation requirements
Formal: none
Content: none
Content: none
Forms of examination
Computer Science 1 Module Exam:
Written Exam (90 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Applicability of the module (in other degree programs)
- Bachelor's degree in Business Informatics
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] München [u.a.]: Pearson Studium.
[2] Gumm, Heinz Peter, Sommer, Manfred (2011). Einführung in die Informatik. 9. Auflage. München: Oldenbourg.
[3] Gumm, Heinz-Peter, Sommer, Manfred (2016). Informatik, Band 1: Programmierung, Algorithmen und Datenstrukturen. De Gruyter Studium.
[4] Sedgewick, Robert (2005). Algorithmen in C. München [u.a.]: Pearson Studium.
[5] SwissEduc. Kara: Lernumgebungen rund ums Programmieren. https://www.swisseduc.ch/informatik/karatojava/
[6] Ullenboom. Java ist auch eine Insel: Einführung, Ausbildung, Praxis. Openbook. Rheinwerk. https://openbook.rheinwerk-verlag.de/javainsel/
Weitere Literaturhinweise und Hinweise auf Quellen werden in der Lehrveranstaltung bekanntgegeben.
[2] Gumm, Heinz Peter, Sommer, Manfred (2011). Einführung in die Informatik. 9. Auflage. München: Oldenbourg.
[3] Gumm, Heinz-Peter, Sommer, Manfred (2016). Informatik, Band 1: Programmierung, Algorithmen und Datenstrukturen. De Gruyter Studium.
[4] Sedgewick, Robert (2005). Algorithmen in C. München [u.a.]: Pearson Studium.
[5] SwissEduc. Kara: Lernumgebungen rund ums Programmieren. https://www.swisseduc.ch/informatik/karatojava/
[6] Ullenboom. Java ist auch eine Insel: Einführung, Ausbildung, Praxis. Openbook. Rheinwerk. https://openbook.rheinwerk-verlag.de/javainsel/
Weitere Literaturhinweise und Hinweise auf Quellen werden in der Lehrveranstaltung bekanntgegeben.
Mathematik 1- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10010
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Upon completion of this module, students will be able to
• Apply basic techniques of one-dimensional calculus
• Apply basic techniques of linear algebra
• Describe the special role of complex numbers in technical applications
• Analyze mathematical concepts
• Evaluate the correctness of mathematical statements
• Formulate simple technical relationships using mathematical terminology
• Apply basic techniques of one-dimensional calculus
• Apply basic techniques of linear algebra
• Describe the special role of complex numbers in technical applications
• Analyze mathematical concepts
• Evaluate the correctness of mathematical statements
• Formulate simple technical relationships using mathematical terminology
Contents
• Real Numbers and Functions
• Complex Numbers
• Vector and Matrix Algebra
• Systems of Linear Equations
• Complex Numbers
• Vector and Matrix Algebra
• Systems of Linear Equations
Teaching methods
A lecture course covers the fundamentals of calculus and linear algebra. The presentation
of the theoretical foundations is supported by numerous examples and exercises.
In the exercise sessions, students work independently on solving problems.
Participation requirements
Formal requirements: none
Content: Mathematics at the level required for the university of applied sciences entrance qualification
Content: Mathematics at the level required for the university of applied sciences entrance qualification
Forms of examination
Mathematics 1 Module Exam:
Written Exam (90 min.)
Requirements for the awarding of credit points
Module examination must be passed
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree study programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Koch, Jürgen und Stämpfle, Martin: Mathematik für das Ingenieurstudium, Carl Hanser Verlag,
München, 3., aktualisierte und erweiterte Auflage, 2015
[2] Koch, Jürgen und Stämpfle, Martin: Mathematik für das Ingenieurstudium, Aufgaben und
Lösungen, Carl Hanser Verlag, München, 1. Auflage, 2025
[3] Papula, Lothar: Mathematische Formelsammlung für Ingenieure und Naturwissenschaftler,
Springer Vieweg, Wiesbaden, 13., überarbeitete und erweiterte Auflage, 2024
[4] Papula, Lothar: Mathematik für Ingenieure und Naturwissenschaftler, Band 1, Springer
Vieweg, Wiesbaden, 16., überarbeitete und erweiterte Auflage, 2024
[5] Papula, Lothar: Mathematik für Ingenieure und Naturwissenschaftler, Band 2, Springer
Vieweg, Wiesbaden, 15., überarbeitete und erweiterte Auflage, 2025
München, 3., aktualisierte und erweiterte Auflage, 2015
[2] Koch, Jürgen und Stämpfle, Martin: Mathematik für das Ingenieurstudium, Aufgaben und
Lösungen, Carl Hanser Verlag, München, 1. Auflage, 2025
[3] Papula, Lothar: Mathematische Formelsammlung für Ingenieure und Naturwissenschaftler,
Springer Vieweg, Wiesbaden, 13., überarbeitete und erweiterte Auflage, 2024
[4] Papula, Lothar: Mathematik für Ingenieure und Naturwissenschaftler, Band 1, Springer
Vieweg, Wiesbaden, 16., überarbeitete und erweiterte Auflage, 2024
[5] Papula, Lothar: Mathematik für Ingenieure und Naturwissenschaftler, Band 2, Springer
Vieweg, Wiesbaden, 15., überarbeitete und erweiterte Auflage, 2025
Mikroprozessortechnik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10040
Duration (semester)
1
Contact time
45 h
Self-study
75 h
Learning outcomes/competences
Students understand the digitization of signals. They are familiar with fixed-point and floating-point formats. In particular, they can confidently convert between binary and hexadecimal numbers and
are proficient in performing calculations in these number formats, especially in two’s complement format. They are aware
of quantization effects. In addition, they are proficient in logical operations and know how to use them efficiently when
programming microprocessors.
Students understand the basic structure and fundamental operation of
microprocessors. They can formulate performance requirements for microprocessors and
possess basic knowledge of real-time processing, application-specific
optimization, and low-level programming while adhering to the specified
arithmetic.
They understand the role of operating systems and can identify application-specific performance characteristics.
are proficient in performing calculations in these number formats, especially in two’s complement format. They are aware
of quantization effects. In addition, they are proficient in logical operations and know how to use them efficiently when
programming microprocessors.
Students understand the basic structure and fundamental operation of
microprocessors. They can formulate performance requirements for microprocessors and
possess basic knowledge of real-time processing, application-specific
optimization, and low-level programming while adhering to the specified
arithmetic.
They understand the role of operating systems and can identify application-specific performance characteristics.
Contents
General Principles: Processing Chain (Discrete-Time Processing of Analog Signals), AD
/DA Converters, History of Microprocessors, Architectures, Timers, Watchdog, Processing Time,
Real-time requirements, polling, interrupts, and interrupt control
Number formats and arithmetic: Fixed-point format in binary, two’s complement, and hexadecimal representation; floating-point format according to IEEE 754; arithmetic operations; arithmetic design
Microprocessors: Detailed information on selected microprocessors with a focus on Atmel AVR microcontrollers (Arduino platform), ARM microprocessors (Raspberry Pi and STM32F4
Discovery platform), DSPs (Texas Instruments C6xxx family), distinction from FPGAs
Interfaces and Programming: GPIO, UART, SPI, I2C, memory management, ring buffer, DMA,
programming (assembly language, high-level language), cross-compilers, parallelization, pipelining,
implementation of a digital filter, model-based approach
operating system: functionality, concepts, basic structure, and services; impact on
programming
/DA Converters, History of Microprocessors, Architectures, Timers, Watchdog, Processing Time,
Real-time requirements, polling, interrupts, and interrupt control
Number formats and arithmetic: Fixed-point format in binary, two’s complement, and hexadecimal representation; floating-point format according to IEEE 754; arithmetic operations; arithmetic design
Microprocessors: Detailed information on selected microprocessors with a focus on Atmel AVR microcontrollers (Arduino platform), ARM microprocessors (Raspberry Pi and STM32F4
Discovery platform), DSPs (Texas Instruments C6xxx family), distinction from FPGAs
Interfaces and Programming: GPIO, UART, SPI, I2C, memory management, ring buffer, DMA,
programming (assembly language, high-level language), cross-compilers, parallelization, pipelining,
implementation of a digital filter, model-based approach
operating system: functionality, concepts, basic structure, and services; impact on
programming
Teaching methods
The subject matter is taught through lectures. Procedures and methods
are explored in greater depth through examples in exercises. Practical examples illustrate the
practical relevance of what has been learned.
The exercises take place in small groups, where students can
present and discuss their own solutions.
are explored in greater depth through examples in exercises. Practical examples illustrate the
practical relevance of what has been learned.
The exercises take place in small groups, where students can
present and discuss their own solutions.
Participation requirements
Formatting: none
Content: none
Content: none
Forms of examination
Microprocessor Technology Module Exam:
Written Exam (90 min.)
Written Exam (90 min.)
Requirements for the awarding of credit points
The module examination must have been graded at least "sufficient" (4.0). This must
at least 50% of the total points possible under a (maximum total points: 240 points, minimum number of points required to
minimum number of points required to pass: 120 points), bonus points described under b. (max. 36
points) are taken into account.
at least 50% of the total points possible under a (maximum total points: 240 points, minimum number of points required to
minimum number of points required to pass: 120 points), bonus points described under b. (max. 36
points) are taken into account.
Applicability of the module (in other degree programs)
Conversion, modernization and refurbishment of existing buildings nowadays determine to a large extent
the architect's field of activity. Errors are often caused by ignorance of elementary building physics, material technology or building design principles. BI is therefore closely related to building physics, building material technology (materiality) and building construction.
the architect's field of activity. Errors are often caused by ignorance of elementary building physics, material technology or building design principles. BI is therefore closely related to building physics, building material technology (materiality) and building construction.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
- Hohmann, R.: Abdichtung bei wasserundurchlässigen Bauwerken aus Beton. Stuttgart, Fraunhofer IRB Verlag, 2009
- Hohmann, R.: Elementwände im drückenden Grundwasser richtig ausgeführt. Stuttgart, Fraunhofer IRB Verlag, 2015
- Hohmann, R.: Planung und Ausführung von Elementwänden bei drückendem Grundwasser. In: Beton und Stahlbetonbau 108 Spezial: WU-Bauwerke aus Beton. Supplement S1 Oktober 2014. S. 81 – 95
- Hohmann, R.: Fugensysteme für WU-Konstruktionen. In: Beton, Heft 12 (2014), S. 482 – 490 − Dahmen, Engel, et. al.: Innenabdichtungen. Fraunhofer IRB Verlag, Stuttgart
- Reul: Handbuch Bautenschutz und Bausanierung. Rudolf Müller Verlag, Köln
- Böhning: Altbaumodernisierung im Detail. Rudolf Müller Verlag, Köln
- Thomas: Denkmalpflege für Architekten und Ingenieure. Rudolf Müller Verlag, Köln
- Frössel: Mauerwekstrockenlegung und Kellersanierung. Fraunhofer IRB Verlag, Stuttgart
- • Arendt: Feucht und Salze in Gebäuden. Verlagsanstalt Alexander Koch, Leinefelden − Hankammer,
- • Lorenz: Schimmelpilze und Bakterien in Gebäuden. Rudolf Müller Verlag, Köln
- • Vogt: Abdichtung – Fachgerecht und Sicher. Fraunhofer IRB Verlag, Stuttgart
- • Stahr: Praxiswissen Bausanierung. Vieweg Verlag, Wiesbaden − Balak
- • Pech: Mauerwerkstrockenlegung. Springer Verlag, Wien
- • Reul: Sanierung von Tiefgaragen und Parkhäusern. Fraunhofer IRB Verlag, Stuttgart − Weber,
- • Hafkesbrink: Bauwerksabdichtung in der Altbausanierung. Teubner Verlag, Wiesbaden
- • Brundiers, Hebeisen, Hunstock, Meyer, Spirgatis: Außenabdichtungen. Fraunhofer IRB Verlag, Stutt
- gart
- • BFA BWA: BWA-Richtlinien für Bauwerksabdichtungen
- • Grundwissen zur Ausführung von Abdichtungen. Beuth Verlag, Berlin −
- • Raps, Schmidt, Rohr-Suchala: Schutz und Instandsetzung von Parkhäusern und Tiefgaragen. Fraunho
- fer IRB Verlag, Stuttgart
- • Röhling, Meichner: Rissbildungen im Stahllbetonbau – Ursachen – Auswirkungen – Maßnahmen.
- Fraunhofer IRB Verlag, Stuttgart −
- Stand: 12. März 2021 Fachhochschule Dortmund Seite 66 von 126
- Bachelor im Fach Architektur (Prüfungsordnungsversion 2014)
- Lotz, Hammacher: Schimmelschäden vermeiden. Fraunhofer IRB Verlag, Stuttgart
- Colling: Lernen aus Schäden im Holzbau. Fraunhofer IRB Verlag, Stuttgart
- Ansorge: Bauwerksabdichtung gegen von außen und innen angreifende Feuchte. Fraunhofer IRB Verlag, Stuttgart
- Scholz: Typische Baufehler. Rudolf Müller Verlag, Köln
- Nürnberger: Korrosion und Korrosionsschutz im Bauwesen. Bauverlag, Wiesbaden
- Meichsner: Bauwerksrisse kurz und bündig. Fraunhofer IRB Verlag, Stuttgart 04.07.2019
- Wallasch: Instandsetzung von Ziegelmauerwerk. DVA
- Kempe: Dokumentation Holzschädlinge. Verlag Bauwesen. Berlin
- Meier: Sanierputze. Expert-Verlag, Renningen
- Raupach: Schutz und Instandsetzung von Betontragwerken. Verlag Bau + Technik
- Frössel: Schimmelpilze und andere Innenraumbelastungen. Fraunhofer IRB Verlag, Stuttgart
WTA-Merkblätter
Physik 1- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10103
Duration (semester)
1
Contact time
60 h
Self-study
120 h
Learning outcomes/competences
Students are familiar with the fundamental principles of physics in the fields of mechanics, thermodynamics
, and oscillations. Students are able to describe the most important physical phenomena
both verbally and mathematically and to
solve simple problems in these fields
, and oscillations. Students are able to describe the most important physical phenomena
both verbally and mathematically and to
solve simple problems in these fields
Contents
Mechanics:
o Kinematics (uniform motion, accelerated motion, superposition of
motions, oblique projectile motion, translation, rotation)
o Dynamics of a point mass
o Forces (Newton’s axioms, spring force, friction, centripetal force, gravitational attraction)
o Momentum (central elastic and inelastic collisions)
o Work and energy, conservation of energy
o Dynamics of a rigid body
o Rotation (torque, angular momentum, moment of inertia, rotational energy)
o Analogy between translation and rotation
o Deformable bodies (density, pressure, states of matter)
Thermodynamics:
o Definition of temperature scales
o Thermal expansion
o Heat capacity/thermal energy
Oscillations:
o Free oscillations, damped oscillations, resonance
o Kinematics (uniform motion, accelerated motion, superposition of
motions, oblique projectile motion, translation, rotation)
o Dynamics of a point mass
o Forces (Newton’s axioms, spring force, friction, centripetal force, gravitational attraction)
o Momentum (central elastic and inelastic collisions)
o Work and energy, conservation of energy
o Dynamics of a rigid body
o Rotation (torque, angular momentum, moment of inertia, rotational energy)
o Analogy between translation and rotation
o Deformable bodies (density, pressure, states of matter)
Thermodynamics:
o Definition of temperature scales
o Thermal expansion
o Heat capacity/thermal energy
Oscillations:
o Free oscillations, damped oscillations, resonance
Teaching methods
The lecture is designed to convey the theoretical content. In the exercises,
mathematical methods are applied and the theoretical material is explored in greater depth.
The exercises take place in small groups, where students can
present and discuss their own solutions
mathematical methods are applied and the theoretical material is explored in greater depth.
The exercises take place in small groups, where students can
present and discuss their own solutions
Participation requirements
Formal: none
Content: Physics at the level required for the university of applied sciences entrance qualification
Content: Physics at the level required for the university of applied sciences entrance qualification
Forms of examination
Physics 1 Module Exam:
Written Exam (120 min.)
Written Exam (120 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Hering, Martin, Stoher: Physik für Ingenieure, VDI Verlag
[2] Lindner, H.: Physik für Ingenieure, Hanser
[3] Rybach, Physik für Bachelors, Hanser
[4] Dobrinski, Krakau, Vogel: Physik für Ingenieure, Teubner Verlag
[2] Lindner, H.: Physik für Ingenieure, Hanser
[3] Rybach, Physik für Bachelors, Hanser
[4] Dobrinski, Krakau, Vogel: Physik für Ingenieure, Teubner Verlag
Praxisnahe Grundlagen 1- PF
- 5 SWS
- 5 ECTS
- PF
- 5 SWS
- 5 ECTS
Number
10050
Duration (semester)
1
Contact time
30 h
Self-study
60 h
Learning outcomes/competences
After participating in the "Design" module, students are able to
develop a topic given to them into a creative idea
to bring this idea to an artistic creative expression in analog and digital form
to present and document their own artistic-creative process and its result
Contents
- Deepening the content learned in the "Fundamentals of Design" module
- Practice artistic and creative approaches
- experimenting with different materials, techniques and methods (analog and digital)
- Reflection and development: using the findings in your own work
- Ideas and form-finding / discovering your own visual worlds
Teaching methods
Exercises
Participation requirements
GG
Forms of examination
a) Examination in the form of term papers
b) Graded examinations during the semester
c) Semester-accompanying coursework (bonus points)
b) Graded examinations during the semester
c) Semester-accompanying coursework (bonus points)
Requirements for the awarding of credit points
Pass graded semester examinations (b) and successfully complete the examination in the form of term papers (a).
Importance of the grade for the final grade
70% of the examination in the form of assignments (a), 30% graded semester examinations (b), taking into account bonus points from semester coursework (c) if applicable.
2. Semester of study
Grundlagen der Elektrotechnik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10090
Duration (semester)
1
Contact time
60 h
Self-study
60 h
Learning outcomes/competences
Building on fundamental principles of physics, this module covers basic knowledge of electrical engineering
. In addition to imparting technical expertise, the introduction to
engineering-based ways of thinking and working plays a key role.
Students understand the electrical relationships in direct- and alternating-current circuits and can describe the function of basic circuits. They are able to
calculate voltages and currents in passive linear electrical networks. They are familiar with
network analysis methods and can apply them. Furthermore, students are
able to assess the validity and limitations of mathematical models in electrical engineering. They can select and apply appropriate methods to solve problems.
The knowledge acquired in this module is essential for further studies in the fields of biomedical engineering and information technology.
. In addition to imparting technical expertise, the introduction to
engineering-based ways of thinking and working plays a key role.
Students understand the electrical relationships in direct- and alternating-current circuits and can describe the function of basic circuits. They are able to
calculate voltages and currents in passive linear electrical networks. They are familiar with
network analysis methods and can apply them. Furthermore, students are
able to assess the validity and limitations of mathematical models in electrical engineering. They can select and apply appropriate methods to solve problems.
The knowledge acquired in this module is essential for further studies in the fields of biomedical engineering and information technology.
Contents
Based on the fundamentals of physics, this section first explains several terms and fundamental
relationships in electrical engineering. In addition to standard
mathematical notation, symbolic representation using circuit diagrams is also introduced.
In particular, the course focuses on the description of electrical processes using mathematical
models. The validity and limitations of these models are explored.
First, Ohm’s law and Kirchhoff’s laws are covered. Direct current (DC) technology is subsequently considered as a special case of alternating current (AC) technology. To this end,
general time-dependent quantities and several parameters, such as the mean value or
root mean square (RMS) value, are first introduced. Under the assumption of single-frequency sinusoidal time-dependent relationships
, voltage and current are treated as complex signals. It becomes apparent that the
time course itself is not relevant; rather, only the complex amplitudes of the signals need to be
considered.
Following the introduction of passive components and their description using network theory,
selected simple basic circuits are examined. A generalization of the topic then leads
to loop current and node potential analysis of networks. The definition and
introduction of two-port elements and their description using corresponding matrices ultimately lay the
foundation for further system-theoretical considerations.
relationships in electrical engineering. In addition to standard
mathematical notation, symbolic representation using circuit diagrams is also introduced.
In particular, the course focuses on the description of electrical processes using mathematical
models. The validity and limitations of these models are explored.
First, Ohm’s law and Kirchhoff’s laws are covered. Direct current (DC) technology is subsequently considered as a special case of alternating current (AC) technology. To this end,
general time-dependent quantities and several parameters, such as the mean value or
root mean square (RMS) value, are first introduced. Under the assumption of single-frequency sinusoidal time-dependent relationships
, voltage and current are treated as complex signals. It becomes apparent that the
time course itself is not relevant; rather, only the complex amplitudes of the signals need to be
considered.
Following the introduction of passive components and their description using network theory,
selected simple basic circuits are examined. A generalization of the topic then leads
to loop current and node potential analysis of networks. The definition and
introduction of two-port elements and their description using corresponding matrices ultimately lay the
foundation for further system-theoretical considerations.
Teaching methods
A lecture covers the theoretical content. Using typical problems as examples,
corresponding practical problems are addressed promptly in the accompanying exercises.
In this process, mathematical methods, analytical techniques, and solution strategies are applied
and practiced. In addition, special emphasis is placed on the confident application of complex
alternating current calculations. Alongside the teaching of theoretical knowledge,
practical digressions are also woven into the course.
corresponding practical problems are addressed promptly in the accompanying exercises.
In this process, mathematical methods, analytical techniques, and solution strategies are applied
and practiced. In addition, special emphasis is placed on the confident application of complex
alternating current calculations. Alongside the teaching of theoretical knowledge,
practical digressions are also woven into the course.
Participation requirements
Formal: none
Content: Basic knowledge of electrical engineering equivalent to a university of applied sciences entrance qualification,
complex calculations (Mathematics 1
Content: Basic knowledge of electrical engineering equivalent to a university of applied sciences entrance qualification,
complex calculations (Mathematics 1
Forms of examination
Module Exam: Fundamentals of Electrical Engineering:
Written Exam (120 min.)
Written Exam (120 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Reinhard Scholz: Grundlagen der Elektrotechnik, Fachbuchverlag Leipzig im Carl Hanser
Verlag, München, 2018, ISBN 978-3-44645160-5.
[2] Arnold Führer, Klaus Heidemann, Wolfgang Nerreter: Grundgebiete der Elektrotechnik 1, 9.
Auflage, Fachbuchverlag Leipzig im Carl Hanser Verlag,
München, 2012, ISBN 978-3-446-43039-6.
[3] Arnold Führer, Klaus Heidemann, Wolfgang Nerreter: Grundgebiete der Elektrotechnik 2, 9.
Auflage, Fachbuchverlag Leipzig im Carl Hanser Verlag,
München, 2011, ISBN 978-3-446-43038-9.
[4] Reinhold Pregla: Grundlagen der Elektrotechnik, 8. Auflage, Hüthig Verlag, Heidelberg, 2009,
ISBN 978-3-7785-4059-6.
[5] Rainer Ose: Elektrotechnik für Ingenieure 1, 3. Auflage, Fachbuchverlag Leipzig im Carl Hanser
Verlag, München, 2005, ISBN 3-446-40272-1.
[6] Hans Wilhelm Schüßler: Netzwerke, Signale und Systeme Band I, 3. Auflage, Springer Verlag,
Berlin, Heidelberg, 1991, ISBN 3-540-53791-0.
[7] Herbert Bernstein: Elektrotechnik in der Praxis. De Gruyter Oldenbourg, Berlin, 2016, ISBN
978-3-11-044098-0.
[8] Michael Felleisen: Elektrotechnik für Dummies, 1. Auflage, Wiley-VCH Verlag, Weinheim,
2016, ISBN 978-3-527-71037-9.
[9] Dieter Zastrow: Elektrotechnik., 17. Auflage, Vieweg + Teubner,
Wiesbaden, 2010, ISBN 978-3-8348-0562-1.
[10] Andreas Wagner: Elektrische Netzwerkanalyse, Books on Demand,
Norderstedt, 2001, ISBN 3-8311-2716-6.
[11] Dieter Metz, Uwe Naundorf, Jürgen Schlabbach: Kleine Formelsammlung Elektrotechnik, 6.
Auflage, Fachbuchverlag Leipzig im Carl Hanser Verlag,
München, 2014, ISBN: 978-3-446-43977-1.
Verlag, München, 2018, ISBN 978-3-44645160-5.
[2] Arnold Führer, Klaus Heidemann, Wolfgang Nerreter: Grundgebiete der Elektrotechnik 1, 9.
Auflage, Fachbuchverlag Leipzig im Carl Hanser Verlag,
München, 2012, ISBN 978-3-446-43039-6.
[3] Arnold Führer, Klaus Heidemann, Wolfgang Nerreter: Grundgebiete der Elektrotechnik 2, 9.
Auflage, Fachbuchverlag Leipzig im Carl Hanser Verlag,
München, 2011, ISBN 978-3-446-43038-9.
[4] Reinhold Pregla: Grundlagen der Elektrotechnik, 8. Auflage, Hüthig Verlag, Heidelberg, 2009,
ISBN 978-3-7785-4059-6.
[5] Rainer Ose: Elektrotechnik für Ingenieure 1, 3. Auflage, Fachbuchverlag Leipzig im Carl Hanser
Verlag, München, 2005, ISBN 3-446-40272-1.
[6] Hans Wilhelm Schüßler: Netzwerke, Signale und Systeme Band I, 3. Auflage, Springer Verlag,
Berlin, Heidelberg, 1991, ISBN 3-540-53791-0.
[7] Herbert Bernstein: Elektrotechnik in der Praxis. De Gruyter Oldenbourg, Berlin, 2016, ISBN
978-3-11-044098-0.
[8] Michael Felleisen: Elektrotechnik für Dummies, 1. Auflage, Wiley-VCH Verlag, Weinheim,
2016, ISBN 978-3-527-71037-9.
[9] Dieter Zastrow: Elektrotechnik., 17. Auflage, Vieweg + Teubner,
Wiesbaden, 2010, ISBN 978-3-8348-0562-1.
[10] Andreas Wagner: Elektrische Netzwerkanalyse, Books on Demand,
Norderstedt, 2001, ISBN 3-8311-2716-6.
[11] Dieter Metz, Uwe Naundorf, Jürgen Schlabbach: Kleine Formelsammlung Elektrotechnik, 6.
Auflage, Fachbuchverlag Leipzig im Carl Hanser Verlag,
München, 2014, ISBN: 978-3-446-43977-1.
Informatik 2- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10161
Duration (semester)
1
Contact time
60 h
Self-study
120 h
Learning outcomes/competences
Students can develop imperative and object-oriented application software. This
includes, in particular, the implementation of graphical user interfaces in Java and their
integration with data structures in Java. In doing so, they apply methods and principles of
software engineering.
Subject-Specific and Methodological Competence:
Students acquire the formal competence to combine principles, methods, concepts, and notations of programming from the fields of object-oriented programming and the programming of graphical and interactive user interfaces (GUI programming) with methods for structuring data (static and dynamic data structures) in order to develop application programs. They acquire the skills to implement an application using current, object-oriented programming methods and software design patterns.
Social Skills: By solving complex development tasks in small groups, for example in pairs (the principle of pair programming), students acquire the skills necessary for professional life: the ability to collaborate constructively to find targeted solutions to specified tasks. In addition, students practice presenting their progress and results within the practicum group.
Subject-Specific and Methodological Competence:
Students acquire the formal competence to combine principles, methods, concepts, and notations of programming from the fields of object-oriented programming and the programming of graphical and interactive user interfaces (GUI programming) with methods for structuring data (static and dynamic data structures) in order to develop application programs. They acquire the skills to implement an application using current, object-oriented programming methods and software design patterns.
Social Skills: By solving complex development tasks in small groups, for example in pairs (the principle of pair programming), students acquire the skills necessary for professional life: the ability to collaborate constructively to find targeted solutions to specified tasks. In addition, students practice presenting their progress and results within the practicum group.
Contents
• Object-oriented programming: classes, inheritance, interfaces, polymorphism
• Dynamic data structures: lists, Java libraries, trees, graphs • Rendering two-dimensional computer graphics
• Software design patterns
• User interfaces and application program architecture
• Dynamic data structures: lists, Java libraries, trees, graphs • Rendering two-dimensional computer graphics
• Software design patterns
• User interfaces and application program architecture
Teaching methods
Lecture involving student participation
Working on programming assignments on computers in teams during the lab
Language: German
Language: German
Participation requirements
Prerequisites: None
Content: Knowledge of the module content: Computer Science 1
Content: Knowledge of the module content: Computer Science 1
Forms of examination
Computer Science 2 Module Exam:
Written Exam (90 min)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
1] Kecher, Christoph (2021), Hoffmann-Elbern, Ralf, Will, Torsten T. UML 2.5: Das umfassende
Handbuch, 7. Auflage. Bonn: Rheinwerk Verlag.
[2] Lahres, Bernhard, Raýman, Gregor, Strich, Stefan (2021). Objektorientierte
Programmierung. Rheinwerk Verlag.
[3] Sattler, Kai-Uwe, Saake, Gunter (2020). Algorithmen und Datenstrukturen: Eine Einführung
mit Java. dpunkt.verlag.
[4] Steyer, Ralph (2022). Einführung in JavaFX/OpenJFX: Moderne GUIs für RIAs und JavaApplikationen 2. Auflage. Springer Vieweg
[5] Ullenboom. Java ist auch eine Insel: Einführung, Ausbildung, Praxis. Openbook. Rheinwerk.
https://openbook.rheinwerk-verlag.de/javainsel/
Weitere Literaturhinweise und Hinweise auf Quellen werden in der Lehrveranstaltung
bekanntgegeben
Kommunikationstechnik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10081
Duration (semester)
1
Learning outcomes/competences
Students are able to identify some basic problems and tasks in the
field of modern communication technology and to describe them using both linguistic and mathematical terms.
They have acquired basic methodological knowledge and can methodically solve corresponding problems and
tasks.
field of modern communication technology and to describe them using both linguistic and mathematical terms.
They have acquired basic methodological knowledge and can methodically solve corresponding problems and
tasks.
Contents
History and Classification
Basic Terms and Definitions, Distinction Between Analog and Digital
Communication Systems, Signal Flow Model vs. Protocol Layer Models
Network Topologies & switching techniques (in particular, circuit-switched vs. packet-switched)
Introduction to the concept of information, fundamentals of source, channel, and line coding
Media access issues and methods, error detection and correction, acknowledgment procedures,
overload and flow control
multiplexing and multiple access methods, Orthogonality principle
Introduction to traffic theory of simple loss and queuing systems, traffic shaping
Fundamental problems and design principles in wireless communication networks,
particularly in cellular networks, system examples
Basic Terms and Definitions, Distinction Between Analog and Digital
Communication Systems, Signal Flow Model vs. Protocol Layer Models
Network Topologies & switching techniques (in particular, circuit-switched vs. packet-switched)
Introduction to the concept of information, fundamentals of source, channel, and line coding
Media access issues and methods, error detection and correction, acknowledgment procedures,
overload and flow control
multiplexing and multiple access methods, Orthogonality principle
Introduction to traffic theory of simple loss and queuing systems, traffic shaping
Fundamental problems and design principles in wireless communication networks,
particularly in cellular networks, system examples
Teaching methods
The lecture is designed to convey theoretical content. In the exercises,
mathematical methods are applied and the theoretical material is explored in greater depth.
mathematical methods are applied and the theoretical material is explored in greater depth.
Participation requirements
Formatting: none
Content: none
Content: none
Forms of examination
Communication Technology Module Exam:
Written Exam (90 min.)
Written Exam (90 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
Konkrete Empfehlungen und Verweise erfolgen in der Veranstaltung.
Mathematik 2- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10060
Duration (semester)
1
Contact time
60 h
Self-study
120 h
Learning outcomes/competences
Upon completion of this module, students will be able to
• Apply basic techniques of analysis in one and multiple dimensions
• Apply basic techniques for solving ordinary differential equations
• Analyze mathematical concepts
• Evaluate the validity of mathematical statements
• Formulate technical relationships using mathematical terminology
• Apply basic techniques of analysis in one and multiple dimensions
• Apply basic techniques for solving ordinary differential equations
• Analyze mathematical concepts
• Evaluate the validity of mathematical statements
• Formulate technical relationships using mathematical terminology
Contents
• Limit Theories and Continuity
• Differential and Integral Calculus for Functions of a Single Variable
• Differential and Integral Calculus for Functions of Several Variables
• Ordinary Differential Equations of the First and Second Order
• Differential and Integral Calculus for Functions of a Single Variable
• Differential and Integral Calculus for Functions of Several Variables
• Ordinary Differential Equations of the First and Second Order
Teaching methods
A lecture provides in-depth knowledge of calculus. The teaching of
theoretical fundamentals is supported by numerous examples and exercises.
In the exercises, students work independently to solve problems.
theoretical fundamentals is supported by numerous examples and exercises.
In the exercises, students work independently to solve problems.
Participation requirements
Prerequisites: None
Content: Knowledge of the module content: Mathematics 1
Content: Knowledge of the module content: Mathematics 1
Forms of examination
Mathematics 2 Module Exam:
Written Exam (120 min.)
Written Exam (120 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Papula, Lothar
Mathematik für Ingenieure 1-3, Vieweg, Braunschweig-Wiesbaden, 2000
[2] Brauch/Dreyer/Haacke
Mathematik für Ingenieure, B.G. Teubner, 1995
[3] Stingl, Peter
Mathematik für Fachhochschulen, Carl-Hanser Verlag, 1999
[4] Papula, Lothar
Mathematische Formelsammlung, Vieweg, Braunschweig-Wiesbaden, 2000
[5] Feldmann
Repetitorium Ingenieurmathematik, Binomi-Verlag, 1994
[6] Preuß, Wenisch
Mathematik 1-3, Hanser-Verlag, 2003
[7] Fetzer, Fränkel
Mathematik 1-2, Springer-Verlag, 2004
[8] Gramlich, Werner,
Numerische Mathematik mit Matlab, Dpunkt-Verlag, Heidelberg, 2000
[9] Angermann, A., Beuschel, M., Rau, M. und Wohlfarth, U.
MATLAB – Simulink – Stateflow: Grundlagen, Toolboxen, Beispiele, Oldenbourg
[10] Hoffmann, J. und Quint, F.
Signalverarbeitung mit MATLAB und Simulink: Anwendungsorientierte Simulationen,
Oldenbourg
[11] Pietruszka, W.D.
MATLAB und Simulink in der Ingenieurpraxis: Modellbildung, Berechnung und Simulation,
Vieweg + Teubner
Mathematik für Ingenieure 1-3, Vieweg, Braunschweig-Wiesbaden, 2000
[2] Brauch/Dreyer/Haacke
Mathematik für Ingenieure, B.G. Teubner, 1995
[3] Stingl, Peter
Mathematik für Fachhochschulen, Carl-Hanser Verlag, 1999
[4] Papula, Lothar
Mathematische Formelsammlung, Vieweg, Braunschweig-Wiesbaden, 2000
[5] Feldmann
Repetitorium Ingenieurmathematik, Binomi-Verlag, 1994
[6] Preuß, Wenisch
Mathematik 1-3, Hanser-Verlag, 2003
[7] Fetzer, Fränkel
Mathematik 1-2, Springer-Verlag, 2004
[8] Gramlich, Werner,
Numerische Mathematik mit Matlab, Dpunkt-Verlag, Heidelberg, 2000
[9] Angermann, A., Beuschel, M., Rau, M. und Wohlfarth, U.
MATLAB – Simulink – Stateflow: Grundlagen, Toolboxen, Beispiele, Oldenbourg
[10] Hoffmann, J. und Quint, F.
Signalverarbeitung mit MATLAB und Simulink: Anwendungsorientierte Simulationen,
Oldenbourg
[11] Pietruszka, W.D.
MATLAB und Simulink in der Ingenieurpraxis: Modellbildung, Berechnung und Simulation,
Vieweg + Teubner
Physik 2- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10104
Duration (semester)
1
Contact time
45 h
Self-study
75 h
Learning outcomes/competences
Students are familiar with the fundamental principles of physics in the areas of electromagnetic
field theory, waves, and optics. Students are able to describe the most important physical
phenomena both verbally and mathematically and to solve simple
problems in these areas. In the field of electrodynamics, they internalize the relationships
between circuit quantities such as current, voltage, resistance, capacitance, and inductance and the
field theory quantities
field theory, waves, and optics. Students are able to describe the most important physical
phenomena both verbally and mathematically and to solve simple
problems in these areas. In the field of electrodynamics, they internalize the relationships
between circuit quantities such as current, voltage, resistance, capacitance, and inductance and the
field theory quantities
Contents
Electromagnetic Field Theory
o Electrostatics (charge, Coulomb force, electric field strength, voltage, potential field,
electric field energy, parallel-plate capacitor, capacitance)
o Electric current field (current density, current, power density, ohmic resistance)
o Magnetostatics (magnetic field strength, Biot–Savart law, magnetic field energy,
coil, inductance)
o Maxwell’s equations in integral form (application examples, wave propagation)
Waves:
o Waves (Huygens’ principle, refraction, diffraction)
o Standing waves (interference)
o Doppler effect
Optics:
o Reflection and Refraction (Mirrors, Plane Mirrors, Prisms)
o Optical Images (Lenses, Image Equation)
o Electrostatics (charge, Coulomb force, electric field strength, voltage, potential field,
electric field energy, parallel-plate capacitor, capacitance)
o Electric current field (current density, current, power density, ohmic resistance)
o Magnetostatics (magnetic field strength, Biot–Savart law, magnetic field energy,
coil, inductance)
o Maxwell’s equations in integral form (application examples, wave propagation)
Waves:
o Waves (Huygens’ principle, refraction, diffraction)
o Standing waves (interference)
o Doppler effect
Optics:
o Reflection and Refraction (Mirrors, Plane Mirrors, Prisms)
o Optical Images (Lenses, Image Equation)
Teaching methods
The lecture is designed to convey the theoretical content. In the exercises,
mathematical methods are applied and the theoretical material is explored in greater depth.
The exercises take place in small groups, where students can
present and discuss their own solutions.
mathematical methods are applied and the theoretical material is explored in greater depth.
The exercises take place in small groups, where students can
present and discuss their own solutions.
Participation requirements
Formal: none
Content: Physics at the level required for the university of applied sciences entrance qualification
Content: Physics at the level required for the university of applied sciences entrance qualification
Forms of examination
Physics 2 Module Exam:
Written Exam (120 min.)
Written Exam (120 min.)
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Hering, Martin, Stoher: Physik für Ingenieure, VDI Verlag
[2] Lindner, H.: Physik für Ingenieure, Hanser
[3] Rybach, Physik für Bachelors, Hanser
[4] Dobrinski, Krakau, Vogel: Physik für Ingenieure, Teubner Verlag
[5] Schwab: Begriffswelt der Feldtheorie, Springer Verlag
[6] Lehner, Elektromagnetische Feldtheorie: Für Ingenieure und Physiker, Springer
[2] Lindner, H.: Physik für Ingenieure, Hanser
[3] Rybach, Physik für Bachelors, Hanser
[4] Dobrinski, Krakau, Vogel: Physik für Ingenieure, Teubner Verlag
[5] Schwab: Begriffswelt der Feldtheorie, Springer Verlag
[6] Lehner, Elektromagnetische Feldtheorie: Für Ingenieure und Physiker, Springer
Praxisnahe Grundlagen 2- PF
- 5 SWS
- 5 ECTS
- PF
- 5 SWS
- 5 ECTS
Number
10110
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Development of properties taking into account cost-benefit analysis, market analysis, location analysis, risk analysis and profitability calculation with cost and income calculation
Contents
- Project development in architectural offices, authorities, banks and other organizations
- Participants in project development
- Functions and analyses of project development, carrying out project development on fictitious projects
Participation requirements
MF
Forms of examination
Examination of planning work
Requirements for the awarding of credit points
Successful final examination
Importance of the grade for the final grade
The final examination is made up of 50% presentation and 50% planning
3. Semester of study
Grundlagen der Signal- und Systemtheorie- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10130
Duration (semester)
1
Contact time
45 h
Self-study
75 h
Learning outcomes/competences
Students are proficient in describing signals and linear systems both
in the time domain (time-continuous and time-discrete) and in the frequency domain. They are familiar with
various time-to-frequency domain transformations and can apply them confidently and
appropriately. In addition, students are familiar with the fundamental properties of linear
systems and can evaluate them. Students are proficient in
distinguishing between deterministic and stochastic signals; they can determine and interpret the properties
of stochastic signals.
This basic theoretical knowledge required of an engineer in biomedical engineering or
information technology is reinforced through practical examples, enabling students to
independently apply this knowledge to other applications and draw appropriate conclusions from
the results obtained. With the methodological skills they have acquired,
students can independently and autonomously develop and evaluate potential solutions,
an important skill, particularly for development engineers.
in the time domain (time-continuous and time-discrete) and in the frequency domain. They are familiar with
various time-to-frequency domain transformations and can apply them confidently and
appropriately. In addition, students are familiar with the fundamental properties of linear
systems and can evaluate them. Students are proficient in
distinguishing between deterministic and stochastic signals; they can determine and interpret the properties
of stochastic signals.
This basic theoretical knowledge required of an engineer in biomedical engineering or
information technology is reinforced through practical examples, enabling students to
independently apply this knowledge to other applications and draw appropriate conclusions from
the results obtained. With the methodological skills they have acquired,
students can independently and autonomously develop and evaluate potential solutions,
an important skill, particularly for development engineers.
Contents
Signals: Classification, deterministic and stochastic signals, time-continuous and
time-discrete signals, special functions, Dirac impulse
Frequency transforms: continuous signals/systems: Fourier transform, Laplace transform, discrete Fourier transform, Z-transform, sampling theorem
System Description: Time-continuous and time-discrete systems, impulse and step responses,
convolution, bilinear transformation, stability
Treatment of Stochastic Signals: Random numbers, probability density function and cumulative distribution function,
Expected value, variance, autocovariance and cross-covariance, correlation, spectrum
Application examples: biomedicine, information technology, and communications technology
time-discrete signals, special functions, Dirac impulse
Frequency transforms: continuous signals/systems: Fourier transform, Laplace transform, discrete Fourier transform, Z-transform, sampling theorem
System Description: Time-continuous and time-discrete systems, impulse and step responses,
convolution, bilinear transformation, stability
Treatment of Stochastic Signals: Random numbers, probability density function and cumulative distribution function,
Expected value, variance, autocovariance and cross-covariance, correlation, spectrum
Application examples: biomedicine, information technology, and communications technology
Teaching methods
The lecture is designed to convey the theoretical content. In the exercises,
assignments are used to reinforce the theoretical material and illustrate the course content using practical examples
.
The seminars take place in small groups, where students can present and discuss their own solutions
.
assignments are used to reinforce the theoretical material and illustrate the course content using practical examples
.
The seminars take place in small groups, where students can present and discuss their own solutions
.
Participation requirements
Formal: None
Content: Knowledge of the module content: Mathematics 1 and 2
Content: Knowledge of the module content: Mathematics 1 and 2
Forms of examination
Module Exam: Fundamentals of Signal and System Theory:
Written Exam (120 min.)
Written Exam (120 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Applicability of the module (in other degree programs)
s (in other study programs)
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Böhme, J.-F.
Stochastische Signale – mit Übungen und einem MATLAB-Praktikum, Vieweg + Teubner
[2] Fettweis, A.
Elemente nachrichtentechnischer Systeme, Schlembach
[3] Föllinger, O.
Laplace-, Fourier- und z-Transformation, Hüthig
[4] Girod, B., Rabenstein, R. und Stenger, A.
Einführung in die Systemtheorie, Vieweg + Teubner
[5] Jondral, F., Wiesler, A.
Grundlagen der Wahrscheinlichkeitsrechnung und stochastische Prozesse für Ingenieure
[6] McClellan, J.H. und Schafer, R.W.
DSP First – A Multimedia Approach, Prentice Hall
[7] Mildenberger, O.
Informationstechnik kompakt, Vieweg
[8] Ohm, J.-R., Lüke, H.D.
Signalübertragung – Grundlagen digitaler und analoger Nachrichtenübertragungssysteme,
Springer
[9] Oppenheim, A.V., Schafer, R.W. und Buck, J.R.
Zeitdiskrete Signalverarbeitung, Pearson Studium
[10] Papoulis, A., Pillai, S.U.
Probability, Random Variables and Stochastic Processes, McGraw Hill
[11] Scheithauer, R.
Signale und Systeme, Vieweg + Teubner
[12] von Grünigen, D.C.
Digitale Signalverarbeitung, Hanser Fachbuchverlag
[13] Werner, M.
Digitale Signalverarbeitung mit MATLAB – Grundkurs mit 16 ausführlichen Versuchen, Vieweg
+ Teubner
Stochastische Signale – mit Übungen und einem MATLAB-Praktikum, Vieweg + Teubner
[2] Fettweis, A.
Elemente nachrichtentechnischer Systeme, Schlembach
[3] Föllinger, O.
Laplace-, Fourier- und z-Transformation, Hüthig
[4] Girod, B., Rabenstein, R. und Stenger, A.
Einführung in die Systemtheorie, Vieweg + Teubner
[5] Jondral, F., Wiesler, A.
Grundlagen der Wahrscheinlichkeitsrechnung und stochastische Prozesse für Ingenieure
[6] McClellan, J.H. und Schafer, R.W.
DSP First – A Multimedia Approach, Prentice Hall
[7] Mildenberger, O.
Informationstechnik kompakt, Vieweg
[8] Ohm, J.-R., Lüke, H.D.
Signalübertragung – Grundlagen digitaler und analoger Nachrichtenübertragungssysteme,
Springer
[9] Oppenheim, A.V., Schafer, R.W. und Buck, J.R.
Zeitdiskrete Signalverarbeitung, Pearson Studium
[10] Papoulis, A., Pillai, S.U.
Probability, Random Variables and Stochastic Processes, McGraw Hill
[11] Scheithauer, R.
Signale und Systeme, Vieweg + Teubner
[12] von Grünigen, D.C.
Digitale Signalverarbeitung, Hanser Fachbuchverlag
[13] Werner, M.
Digitale Signalverarbeitung mit MATLAB – Grundkurs mit 16 ausführlichen Versuchen, Vieweg
+ Teubner
Informatik 3- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10162
Duration (semester)
1
Learning outcomes/competences
Students acquire the necessary knowledge to develop structured imperative and
object-oriented application software in conjunction with persistent data storage. This includes the fundamental implementation of software patterns for
object-oriented programming and the use of databases (relational SQL and NoSQL).
Subject-Specific and Methodological Competence: Students acquire the formal competence to implement principles, methods, concepts, and notations of programming from the fields of structured programming and object-oriented programming, taking into account the aforementioned software patterns. They acquire a fundamental ability to represent a given description of a data model using UML or ER diagrams, to analyze it, to implement it in the form of a relational database, and to distinguish it from NoSQL databases. Students acquire a basic understanding of parallel processes and their synchronization behavior.
Subject-Specific and Methodological Competence: Students acquire the formal competence to implement principles, methods, concepts, and notations of programming from the fields of structured programming and object-oriented programming, taking into account the aforementioned software patterns. They acquire a fundamental ability to represent a given description of a data model using UML or ER diagrams, to analyze it, to implement it in the form of a relational database, and to distinguish it from NoSQL databases. Students acquire a basic understanding of parallel processes and their synchronization behavior.
Contents
• Using XML structures in application development
• Design and querying of a relational database; fundamentals of NoSQL models
• Selection of GoF software design patterns
• Synchronization and concurrency in programs
• User interfaces and application architecture
• Design and querying of a relational database; fundamentals of NoSQL models
• Selection of GoF software design patterns
• Synchronization and concurrency in programs
• User interfaces and application architecture
Teaching methods
Lecture involving student participation, with live programming, board work, and
projection. Completion of programming assignments on computers in pairs (pair programming) during the lab session.
Participation requirements
Formal: None
Substantive: Knowledge of the module content: Computer Science 1 and 2
Substantive: Knowledge of the module content: Computer Science 1 and 2
Forms of examination
Computer Science 3 Module Exam:
Written Exam (90 min)
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] „Lehrbuch der Objektmodellierung - Analyse und Entwurf mit der UML 2“;
H. Balzert; Akademischer Verlag 2011
[2] „Handbuch der Java-Programmierung“; G. Krüger; Addison Wesley, 8. aktualisierte Auflage 2014
[3] „Algorithmen und Datenstrukturen“; G. Saake, K.-U. Sattler; 3. Auflage dpunkt Verlag 2006
[4] „Algorithmen in C“ und „Algorithmen in C++“ bzw. „Algorithmen in Java“; R. Sedgewick; Addison Wesley 1992 bzw. 2003
[5] „Grundlagen der Informatik“; H. Herold et.al; Pearson-Verlag 2006, 2007
[6] „Datenbanksysteme - Eine Einführung“; A. Kemper, A. Eickler; Oldenbourg Verlag, 6. Auflage 2006
[7] „Einführung in den Sprachkern von SQL-99“; W. Panny, A. Taudes; Springer Verlag 2000
[8] „Datenbanksysteme – Theorie und Praxis mit SQL2003, Oracle und MySQL“; H. Faeskorn-Woyke et al.; Pearson Verlag 2007
[9] „Design Patterns: Elements of Reusable Object-Oriented Software“; E. Gamma, R. Helm ,R. Johson, J. Vlissides; Addison-Wesley 1995
[2] „Handbuch der Java-Programmierung“; G. Krüger; Addison Wesley, 8. aktualisierte Auflage 2014
[3] „Algorithmen und Datenstrukturen“; G. Saake, K.-U. Sattler; 3. Auflage dpunkt Verlag 2006
[4] „Algorithmen in C“ und „Algorithmen in C++“ bzw. „Algorithmen in Java“; R. Sedgewick; Addison Wesley 1992 bzw. 2003
[5] „Grundlagen der Informatik“; H. Herold et.al; Pearson-Verlag 2006, 2007
[6] „Datenbanksysteme - Eine Einführung“; A. Kemper, A. Eickler; Oldenbourg Verlag, 6. Auflage 2006
[7] „Einführung in den Sprachkern von SQL-99“; W. Panny, A. Taudes; Springer Verlag 2000
[8] „Datenbanksysteme – Theorie und Praxis mit SQL2003, Oracle und MySQL“; H. Faeskorn-Woyke et al.; Pearson Verlag 2007
[9] „Design Patterns: Elements of Reusable Object-Oriented Software“; E. Gamma, R. Helm ,R. Johson, J. Vlissides; Addison-Wesley 1995
Kommunikationsnetze und IT-Sicherheit- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10151
Duration (semester)
1
Learning outcomes/competences
Students are able to design and implement networked IT systems using recognized and standard
standards, with a particular focus on IT security.
They are familiar with the problems and tasks involved in IT networking and can
approach and solve them methodically.
standards, with a particular focus on IT security.
They are familiar with the problems and tasks involved in IT networking and can
approach and solve them methodically.
Contents
Structure and Architecture of the Internet
DoD and ISO/OSI Models
Addressing Issues and Solutions in the Lower Four Layers
Routing
Switching, Methods, Problems, and Protocols, e.g., STP, VLAN, PPP
Network protocols, especially IPv4/v6, subnetting, routing methods and protocols
(external and internal gateways)
Transport protocols, especially UDP, TCP, alternative examples: QUIC, MPTCP, etc.
TCP issues and solutions / variants (see also QoS), interaction with queuing and traffic shaping methods
Protocols and methods at higher layers, e.g., RTP and SIP, services and service protocols,
e.g., ZC, DHCP, DNS
Network elements, routers, switches, end devices, outlook on SDN
Quality of Service, Int/DiffServ, RSVP, MLPS, classful/classless queuing
Security requirements and mechanisms and their implementation in distributed systems
Introduction to threats and vulnerabilities, e.g., across the OSI layers, including Layer 8,
Kerckhoff’s Principles
Firewalls and Netfilter
Integrity / Hash Functions and Methods, MAC/HMAC, password encryption (e.g., PBKDF)
Overview of historical encryption methods, fundamentals of modern symmetric and
asymmetric encryption, algorithm examples (DES, AES, RSA, Elgamal, EC), key exchange
hierarchical PKI (e.g., X.509 certificate-based) vs. Web of Trust (e.g., OpenPGP),
Signature schemes
Securing data exchange and services at various layers, e.g., IPsec with IKEv1/v2,
e.g., SSH/OpenSSH, SSL/TLS with HTTPS, e.g., DNSsec
security management and frameworks, e.g., ISO 27000, IT-Grundschutz, institutions (NIST, BSI).
DoD and ISO/OSI Models
Addressing Issues and Solutions in the Lower Four Layers
Routing
Switching, Methods, Problems, and Protocols, e.g., STP, VLAN, PPP
Network protocols, especially IPv4/v6, subnetting, routing methods and protocols
(external and internal gateways)
Transport protocols, especially UDP, TCP, alternative examples: QUIC, MPTCP, etc.
TCP issues and solutions / variants (see also QoS), interaction with queuing and traffic shaping methods
Protocols and methods at higher layers, e.g., RTP and SIP, services and service protocols,
e.g., ZC, DHCP, DNS
Network elements, routers, switches, end devices, outlook on SDN
Quality of Service, Int/DiffServ, RSVP, MLPS, classful/classless queuing
Security requirements and mechanisms and their implementation in distributed systems
Introduction to threats and vulnerabilities, e.g., across the OSI layers, including Layer 8,
Kerckhoff’s Principles
Firewalls and Netfilter
Integrity / Hash Functions and Methods, MAC/HMAC, password encryption (e.g., PBKDF)
Overview of historical encryption methods, fundamentals of modern symmetric and
asymmetric encryption, algorithm examples (DES, AES, RSA, Elgamal, EC), key exchange
hierarchical PKI (e.g., X.509 certificate-based) vs. Web of Trust (e.g., OpenPGP),
Signature schemes
Securing data exchange and services at various layers, e.g., IPsec with IKEv1/v2,
e.g., SSH/OpenSSH, SSL/TLS with HTTPS, e.g., DNSsec
security management and frameworks, e.g., ISO 27000, IT-Grundschutz, institutions (NIST, BSI).
Teaching methods
The lecture is designed to convey theoretical content. In the exercises,
mathematical methods are applied and the theoretical material is explored in greater depth.
mathematical methods are applied and the theoretical material is explored in greater depth.
Participation requirements
Formatting: none
Content: none
Content: none
Forms of examination
Module Exam: Communication Networks and IT Security:
Written Exam (90 min.)
Written Exam (90 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
Konkrete Empfehlungen und Verweise erfolgen in der Veranstaltung.
Messtechnik und Fehlerrechnung- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10182
Duration (semester)
1
Learning outcomes/competences
Students have an overview of the various sensor principles and measurement methods used to measure physical quantities. They can describe the function of sensors as well as their
range of applications. They understand passive and active circuits for processing and evaluating
sensor signals and can calculate them. Students are
able to interpret measurement results and assess their quality by estimating the measurement uncertainty
range of applications. They understand passive and active circuits for processing and evaluating
sensor signals and can calculate them. Students are
able to interpret measurement results and assess their quality by estimating the measurement uncertainty
Contents
The theoretical foundations and application examples of various sensor principles (physical,
electrical, optical, chemical, and biochemical) and measurement methods are covered and
discussed in detail. A key aspect is the electrical connection of the sensor
and the processing of sensor signals. To this end, the most important
operational amplifier circuits as well as analog-to-digital conversion are covered. Measurement circuits
are examined and analyzed in terms of their electrical behavior, sensitivity to external influences, and the
resulting measurement uncertainty. The description and
implementation of complex measurement systems and analysis methods are also part of the module.
Furthermore, statistical methods in measurement technology and imaging measurement techniques
are explained.
electrical, optical, chemical, and biochemical) and measurement methods are covered and
discussed in detail. A key aspect is the electrical connection of the sensor
and the processing of sensor signals. To this end, the most important
operational amplifier circuits as well as analog-to-digital conversion are covered. Measurement circuits
are examined and analyzed in terms of their electrical behavior, sensitivity to external influences, and the
resulting measurement uncertainty. The description and
implementation of complex measurement systems and analysis methods are also part of the module.
Furthermore, statistical methods in measurement technology and imaging measurement techniques
are explained.
Teaching methods
The lecture covers the theoretical material. In the exercises, students build on the theoretical material using
practical examples.
practical examples.
Participation requirements
Formatting: none
Content: none
Content: none
Forms of examination
Module Exam in Measurement Technology and Error Analysis:
Written Exam (120 min.)
Written Exam (120 min.)
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
[1] Reinhard Lerch: Elektrische Messtechnik, Springer Vieweg, Berlin, Heidelberg, 7. Aufl. 2016,
ISBN 978-3-662-46980-8.
[2] Thomas Mühl: Elektrische Messtechnik, Springer Vieweg, Wiesbaden,
5. Aufl. 2016, ISBN 978-3-658-15719-7.
[3] Herbert Bernstein: Messelektronik und Sensoren, Springer Vieweg, Wiesbaden, 1. Aufl. 2014,
ISBN 978-3-658-00548-1.
[4] Rainer Felderhoff, Ulrich Freyer: Elektrische und elektronische Messtechnik, Carl Hanser
Verlag, München, Wien, 7. Aufl. 2003, ISBN 978-3-446-19227-1.
[5] Jörg Hoffmann: Messen nichtelektrischer Größen, VDI Verlag, Düsseldorf,
1. Aufl. 1996, ISBN 978-3-662-01174-4.
[6] Reinhard Scholz: Grundlagen der Elektrotechnik, Fachbuchverlag Leipzig im Carl Hanser
Verlag, München, 2018, ISBN 978-3-44645160-5.
[7] Ulrich Tietze, Christoph Schenk: Halbleiter-Schaltungstechnik, Springer-Verlag, Berlin,
Heidelberg, 15. Aufl. 2016, ISBN 978-3-662-48354-1
ISBN 978-3-662-46980-8.
[2] Thomas Mühl: Elektrische Messtechnik, Springer Vieweg, Wiesbaden,
5. Aufl. 2016, ISBN 978-3-658-15719-7.
[3] Herbert Bernstein: Messelektronik und Sensoren, Springer Vieweg, Wiesbaden, 1. Aufl. 2014,
ISBN 978-3-658-00548-1.
[4] Rainer Felderhoff, Ulrich Freyer: Elektrische und elektronische Messtechnik, Carl Hanser
Verlag, München, Wien, 7. Aufl. 2003, ISBN 978-3-446-19227-1.
[5] Jörg Hoffmann: Messen nichtelektrischer Größen, VDI Verlag, Düsseldorf,
1. Aufl. 1996, ISBN 978-3-662-01174-4.
[6] Reinhard Scholz: Grundlagen der Elektrotechnik, Fachbuchverlag Leipzig im Carl Hanser
Verlag, München, 2018, ISBN 978-3-44645160-5.
[7] Ulrich Tietze, Christoph Schenk: Halbleiter-Schaltungstechnik, Springer-Verlag, Berlin,
Heidelberg, 15. Aufl. 2016, ISBN 978-3-662-48354-1
Mobile Robotik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10323
Duration (semester)
1
Learning outcomes/competences
Students acquire knowledge of the fundamentals of mobile robotics and are able to apply this knowledge in practice through simulations and models. Subject-Specific and Methodological Competencies:
• Students can parameterize and create prototypes of algorithms for environmental perception, motion control, and path planning for mobile robots.
• Basic control algorithms can be simulated and adapted and optimized using simulation tools. • Students can apply the results using ROS.
• Use of simulation tools such as Gazebo. Interdisciplinary Methodological Competence:
• Systems thinking
• Designing and documenting target systems and services
• Specifying use cases and requirements
• Process-oriented approach Social Competence:
• Working in small teams • Results-oriented group work
• Students can parameterize and create prototypes of algorithms for environmental perception, motion control, and path planning for mobile robots.
• Basic control algorithms can be simulated and adapted and optimized using simulation tools. • Students can apply the results using ROS.
• Use of simulation tools such as Gazebo. Interdisciplinary Methodological Competence:
• Systems thinking
• Designing and documenting target systems and services
• Specifying use cases and requirements
• Process-oriented approach Social Competence:
• Working in small teams • Results-oriented group work
Contents
• Mathematical and Methodological Foundations
• Architectures
• Motion Models
• Bayesian Filters
• Localization
• Mapping
• Planning
• Control
• Architectures
• Motion Models
• Bayesian Filters
• Localization
• Mapping
• Planning
• Control
Teaching methods
The lecture (which is partly seminar-based) is designed to convey the theoretical content. In
the exercises, the theoretical material is reinforced through use cases and sample problems.
Using example applications and embedded systems in the lab (TurtleBots) and through
simulations (ROS, Gazebo, AirSim, Carla, Webots), the behavior of implementations
is illustrated.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester.
Content: none
Content: none
Forms of examination
Mobile Robotics Module Exam:
Written Exam (90 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
[1] Hertzberg, Lingemann, Nüchter, Mobile Roboter, Springer, 2012
[2] Thrun, Burgard, Fox, Probabilistic Robotics, The MIT Press, 2005
[3] Çaliş, Roboter mit ROS, Heidelberg dpunkt.verlag, 2020
[4] Fairchild, ROS robotics by example, UK Packt Publishing, 2017
[5] Koubaa, Robot Operating System (ROS): The complete Reference, Springer 2021
[2] Thrun, Burgard, Fox, Probabilistic Robotics, The MIT Press, 2005
[3] Çaliş, Roboter mit ROS, Heidelberg dpunkt.verlag, 2020
[4] Fairchild, ROS robotics by example, UK Packt Publishing, 2017
[5] Koubaa, Robot Operating System (ROS): The complete Reference, Springer 2021
Modellbildung & Simulation für die Digitalen Technologien- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10191
Duration (semester)
1
Modellbildung & Simulation für die Informationstechnik (IM, RO)- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10192
Duration (semester)
1
Learning outcomes/competences
Students are able to leverage the visual and universal nature of software tools
to their advantage and can thus independently explore new areas of application.
Students are proficient in the experimental and theoretical modeling of technical systems.
They are able to independently perform numerical simulations and analyses using software and
hardware tools in the fields of intelligent mobility and robotics.
By working with concrete real-world examples from the fields of intelligent mobility and
robotics, they can reliably assess the quality of simulation models for important practical problems
. Students are able to use modern measuring instruments and set up measurement systems independently.
to their advantage and can thus independently explore new areas of application.
Students are proficient in the experimental and theoretical modeling of technical systems.
They are able to independently perform numerical simulations and analyses using software and
hardware tools in the fields of intelligent mobility and robotics.
By working with concrete real-world examples from the fields of intelligent mobility and
robotics, they can reliably assess the quality of simulation models for important practical problems
. Students are able to use modern measuring instruments and set up measurement systems independently.
Contents
Description of simple electrical equivalent circuits by examining the fundamental
technical principles
• Theoretical modeling of system behavior through the analysis of the principles
governing system components and their interconnections (e.g., DGLs)
• Experimental modeling of system behavior by measuring system responses
to test signals in the time and/or frequency domain
• Simulation of the approximated transfer behavior of the model description and
comparison with real measurement data
• Use of software tools for modeling and simulation
(e.g., MATLAB/Simulink)
technical principles
• Theoretical modeling of system behavior through the analysis of the principles
governing system components and their interconnections (e.g., DGLs)
• Experimental modeling of system behavior by measuring system responses
to test signals in the time and/or frequency domain
• Simulation of the approximated transfer behavior of the model description and
comparison with real measurement data
• Use of software tools for modeling and simulation
(e.g., MATLAB/Simulink)
Teaching methods
Within the seminar course, the lecture components are designed to convey
theoretical content. In the exercise sessions and practical experiments, mathematical
methods are applied and the theoretical content is explored in greater depth.
theoretical content. In the exercise sessions and practical experiments, mathematical
methods are applied and the theoretical content is explored in greater depth.
Participation requirements
Formal: none
Content: Knowledge of the module content:
o Mathematics 1 and 2
Content: Knowledge of the module content:
o Mathematics 1 and 2
Forms of examination
Course Exam: Modeling & Simulation for Information Technology:
Written exam (120 min.) or oral exam (45 min.)
Written exam (120 min.) or oral exam (45 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
[1] Scherf: Modellbildung und Simulation dynamischer Systeme, Oldenbourg
[2] Nollau: Modellierung und Simulation technischer Systeme, Springer
[3] Bode: Matlab-Simulink, Teubner
[4] Angermann: MATLAB – Simulink – Stateflow, Oldenbourg…
[2] Nollau: Modellierung und Simulation technischer Systeme, Springer
[3] Bode: Matlab-Simulink, Teubner
[4] Angermann: MATLAB – Simulink – Stateflow, Oldenbourg…
Praxisnahe Grundlagen 3- PF
- 5 SWS
- 5 ECTS
- PF
- 5 SWS
- 5 ECTS
Number
10200
Duration (semester)
1
Robotik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10153
Duration (semester)
1
Learning outcomes/competences
Part 1:
Students will be able to…
• identify basic types of robots and their components, such as actuators, sensors, effectors
and control units, as well as how they interact
• identify the hazards posed by autonomous systems and the necessary safety and protective measures
• establish mathematical relationships to describe robot forward kinematics
and apply methods for calculating positions and orientations in
various coordinate systems
• Use robot software tools to
program
fixed motion sequences for a robot
• use tools such as MATLAB/Simulink or other toolboxes to solve practical
robotics tasks (e.g., “pick and place”)
Part 2:
• describe the different types and characteristics of mobile robots
• Describe the basic functioning of various sensors that mobile robots use to
perceive their environment and determine their own 3D orientation and position as well as the location
of other objects in space
• Explain the characteristics and fields of application of UAVs (Unmanned Aerial Vehicles)—
particularly drones and quadcopters—
• explain the relationship between the control of a quadcopter’s four rotors and
its altitude, orientation, and position
• use unit quaternions for the mathematical representation of 3D orientation as well as for
applying rotational transformations
• mathematically process the sensor data of a quadcopter (3D acceleration, 3D gyroscope, ultrasonic data
etc.), using MATLAB/Simulink and the Robotics Toolbox to mathematically
process this data in such a way that it can, among other things, determine the quadcopter’s pose and velocity
Students will be able to…
• identify basic types of robots and their components, such as actuators, sensors, effectors
and control units, as well as how they interact
• identify the hazards posed by autonomous systems and the necessary safety and protective measures
• establish mathematical relationships to describe robot forward kinematics
and apply methods for calculating positions and orientations in
various coordinate systems
• Use robot software tools to
program
fixed motion sequences for a robot
• use tools such as MATLAB/Simulink or other toolboxes to solve practical
robotics tasks (e.g., “pick and place”)
Part 2:
• describe the different types and characteristics of mobile robots
• Describe the basic functioning of various sensors that mobile robots use to
perceive their environment and determine their own 3D orientation and position as well as the location
of other objects in space
• Explain the characteristics and fields of application of UAVs (Unmanned Aerial Vehicles)—
particularly drones and quadcopters—
• explain the relationship between the control of a quadcopter’s four rotors and
its altitude, orientation, and position
• use unit quaternions for the mathematical representation of 3D orientation as well as for
applying rotational transformations
• mathematically process the sensor data of a quadcopter (3D acceleration, 3D gyroscope, ultrasonic data
etc.), using MATLAB/Simulink and the Robotics Toolbox to mathematically
process this data in such a way that it can, among other things, determine the quadcopter’s pose and velocity
Contents
Part 1:
• Introduction to Robotics (types of robots and typical tasks, safety considerations)
• Mathematical Fundamentals (coordinate systems, positions, and orientations in 2D and
3D space)
• Forward kinematics of articulated-arm robots
• Use of software tools (simulation and programming of robotic systems)
• Hands-on work with real-world application examples (use cases)
Part 2:
• Introduction to Mobile Robotics:
o Definition of mobile robots, classification, and application examples
o Overview of: proximity sensors (infrared, ultrasonic, LIDAR), optical sensors
(stereo vision, optical flow, depth camera), GPS, inertial sensors (accelerometer and gyroscope)
o Application areas of drones
• Controlling the pose of a drone or quadcopter (rotor control to
adjust the thrust, roll, pitch, and yaw parameters)
• 3D orientation representation using unit quaternions
• 3D orientation and position determination using 3D acceleration and gyro data
• Introduction to Robotics (types of robots and typical tasks, safety considerations)
• Mathematical Fundamentals (coordinate systems, positions, and orientations in 2D and
3D space)
• Forward kinematics of articulated-arm robots
• Use of software tools (simulation and programming of robotic systems)
• Hands-on work with real-world application examples (use cases)
Part 2:
• Introduction to Mobile Robotics:
o Definition of mobile robots, classification, and application examples
o Overview of: proximity sensors (infrared, ultrasonic, LIDAR), optical sensors
(stereo vision, optical flow, depth camera), GPS, inertial sensors (accelerometer and gyroscope)
o Application areas of drones
• Controlling the pose of a drone or quadcopter (rotor control to
adjust the thrust, roll, pitch, and yaw parameters)
• 3D orientation representation using unit quaternions
• 3D orientation and position determination using 3D acceleration and gyro data
Teaching methods
The lecture is designed to convey the theoretical content. In the exercises, students deepen their understanding of and practice the theoretical material through
a variety of assignments. In two
practical projects, students independently apply the knowledge they have acquired to solve
practical problems.
a variety of assignments. In two
practical projects, students independently apply the knowledge they have acquired to solve
practical problems.
Participation requirements
Formal: none
Content: Knowledge of the module content:
o Mathematics 1 and 2
o Practical Fundamentals 1 and 2
Content: Knowledge of the module content:
o Mathematics 1 and 2
o Practical Fundamentals 1 and 2
Forms of examination
Exams held throughout the semester in the form of projects that include a presentation and an oral exam.
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
[1] Corke: Robotics, Vision and Control, Springer
[2] Herzberg: Mobile Roboter, Springer
[3] Papula: Mathematik für Ingenieure und Naturwissenschaftler, Bd. 1+2, Vieweg
[4] Hoffman: MATLAB und SIMULINK, Addison-Wesley
[2] Herzberg: Mobile Roboter, Springer
[3] Papula: Mathematik für Ingenieure und Naturwissenschaftler, Bd. 1+2, Vieweg
[4] Hoffman: MATLAB und SIMULINK, Addison-Wesley
Smart Mobility - PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10152
Duration (semester)
1
Übertragungstechnik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10181
Duration (semester)
1
Contact time
90 h
Self-study
120 h
Learning outcomes/competences
Students have a basic understanding of line theory and high-frequency engineering. They can analyze,
design, and describe lines and passive high-frequency components using scattering parameters.
Students have knowledge of transmission engineering and can assess and analyze the influence of the
transmission link on the behavior of a communication system, as well as
make design decisions independently.
design, and describe lines and passive high-frequency components using scattering parameters.
Students have knowledge of transmission engineering and can assess and analyze the influence of the
transmission link on the behavior of a communication system, as well as
make design decisions independently.
Contents
The course content draws inspiration from the courses offered in the previous
semester:
In the Communication Technology module, when examining communication systems, it is
assumed that a
communication channel can be established between the transmitter and receiver even over long distances.
The modules “Fundamentals of Physics 1 and 2” and “Fundamentals of Electrical Engineering” cover the
physical and electrical engineering principles underlying this.
The Transmission Technology module covers the transmission techniques that utilize physics and
electrical engineering to establish the communication channel and thus has
cross-references to the modules Modeling and Simulation and Fundamentals of Signal and
System Theory.
• Introduction to line theory and the propagation of waves in space
• Description of linear passive high-frequency circuits using scattering parameters
• Overview of practically relevant waveguides and passive
standard RF components based on line structures
• Analog and digital modulation types and methods, and multiple access schemes
• Pulse shaping and pulse-shape filtering
• Transmission of stochastic signals, particularly via LTI systems
• Noise matching and matched filters
• Bit error rate behavior and link budget
semester:
In the Communication Technology module, when examining communication systems, it is
assumed that a
communication channel can be established between the transmitter and receiver even over long distances.
The modules “Fundamentals of Physics 1 and 2” and “Fundamentals of Electrical Engineering” cover the
physical and electrical engineering principles underlying this.
The Transmission Technology module covers the transmission techniques that utilize physics and
electrical engineering to establish the communication channel and thus has
cross-references to the modules Modeling and Simulation and Fundamentals of Signal and
System Theory.
• Introduction to line theory and the propagation of waves in space
• Description of linear passive high-frequency circuits using scattering parameters
• Overview of practically relevant waveguides and passive
standard RF components based on line structures
• Analog and digital modulation types and methods, and multiple access schemes
• Pulse shaping and pulse-shape filtering
• Transmission of stochastic signals, particularly via LTI systems
• Noise matching and matched filters
• Bit error rate behavior and link budget
Teaching methods
The lecture covers the theoretical material. In the exercises, students reinforce their understanding of the theoretical material using
practical examples.
practical examples.
Participation requirements
Formal: none
Forms of examination
Module Exam on Transmission Technology:
Written Exam (90 min.)
Written Exam (90 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
Aktuelle Literaturhin- und verweise werden in der Veranstaltung gegeben.
4. Semester of study
Automotive Systems Engineering- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10252
Duration (semester)
1
Autonome Systeme- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10241
Duration (semester)
1
Learning outcomes/competences
Students gain knowledge of the architecture of autonomous systems and the design
of such systems in IP networks.
Subject-Specific and Methodological Competencies:
• Defining, documenting, and evaluating architectures of autonomous systems
• Describing the architecture and design process while taking into account data protection,
data security, confidentiality, and integrity (security by design)
• Understanding the principles of software architectures as well as standard procedures and
interfaces of distributed knowledge-based systems
• Understanding the concepts of object-oriented design and the interoperability
of various software modules as well as the integration of services
• Design, implementation, testing, and documentation of exemplary applications
• Consideration of performance, runtime behavior, and service quality
Interdisciplinary methodological competence:
• Systems thinking
• Designing and documenting target systems and services
• Specifying data structures and models as well as interfaces and protocols
• Semantic description of services in autonomous systems
• Process-oriented approach
Social skills:
• Working in small teams
• Results-oriented group work
of such systems in IP networks.
Subject-Specific and Methodological Competencies:
• Defining, documenting, and evaluating architectures of autonomous systems
• Describing the architecture and design process while taking into account data protection,
data security, confidentiality, and integrity (security by design)
• Understanding the principles of software architectures as well as standard procedures and
interfaces of distributed knowledge-based systems
• Understanding the concepts of object-oriented design and the interoperability
of various software modules as well as the integration of services
• Design, implementation, testing, and documentation of exemplary applications
• Consideration of performance, runtime behavior, and service quality
Interdisciplinary methodological competence:
• Systems thinking
• Designing and documenting target systems and services
• Specifying data structures and models as well as interfaces and protocols
• Semantic description of services in autonomous systems
• Process-oriented approach
Social skills:
• Working in small teams
• Results-oriented group work
Contents
• Introduction to automated and autonomous technical systems that interact closely with
people, semi-autonomy, autonomous behavior
• Perception:
multisensor data fusion, localization, navigation and mapping, object recognition
• Planning and execution:
Task decomposition, reactive behavior, pre-planned behavior based on knowledge and skills
, behavior transfer, learning
• Architectures:
Behavior-oriented approaches, expert systems, knowledge bases, multi-level control/regulation concepts
• Exemplary Applications:
autonomous mobile service robots, humanoid walking machines, telepresence systems,
smart home, smart building, and smart city systems
• Software architectures, services, and systems
• Design of distributed autonomous software systems
• Software Design with UML
• Object-Oriented Software Design Patterns
• Communication and Interaction of Distributed Subsystems
• Communication Protocols in the Internet of Things
• Model-Based Software Development
• Application of a Systematic Development Process
with IDE, Documentation, and Test Strategies
people, semi-autonomy, autonomous behavior
• Perception:
multisensor data fusion, localization, navigation and mapping, object recognition
• Planning and execution:
Task decomposition, reactive behavior, pre-planned behavior based on knowledge and skills
, behavior transfer, learning
• Architectures:
Behavior-oriented approaches, expert systems, knowledge bases, multi-level control/regulation concepts
• Exemplary Applications:
autonomous mobile service robots, humanoid walking machines, telepresence systems,
smart home, smart building, and smart city systems
• Software architectures, services, and systems
• Design of distributed autonomous software systems
• Software Design with UML
• Object-Oriented Software Design Patterns
• Communication and Interaction of Distributed Subsystems
• Communication Protocols in the Internet of Things
• Model-Based Software Development
• Application of a Systematic Development Process
with IDE, Documentation, and Test Strategies
Teaching methods
Lecture involving student interaction, with board notes and projections
and blended learning elements.
Completing programming assignments on computers, either individually or in teams.
Building systems and testing runtime and response times under real-time conditions.
and blended learning elements.
Completing programming assignments on computers, either individually or in teams.
Building systems and testing runtime and response times under real-time conditions.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester.
Content: Programming skills, e.g., C, C++, Java,
basic knowledge of operating systems, e.g., Linux
IP protocols for IoT systems
full 30 ECTS credits from the first semester.
Content: Programming skills, e.g., C, C++, Java,
basic knowledge of operating systems, e.g., Linux
IP protocols for IoT systems
Forms of examination
Autonomous Systems Module Exam:
Written Exam (90 min.)
Written Exam (90 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
[1] R. Siegwart, I. R. Nourbakhsh, Autonomous Mobile Robots, MIT Press 2004
[2] S. Thrun, W. Burgard, D. Fox, Probabilistic Robotics, MIT Press 2005
[3] S. M. LaValle, Planning Algorithms, Cambridge University Press 2006
[4] M. Wooldridge, An Introduction to MultiAgent Systems, Wiley 2009
[5] Heide Balzert: Lehrbuch der Objektmodellierung - Analyse und Entwurf mit der UML 2,
Akademischer Verlag 2011
[6] Gernot Starke: Effektive Software-Architekturen - Ein praktischer Leitfaden,
Hanser, 7. Auflage 2015
[7] E. Gamma, R. Helm, R. Johson, J. Vlissides; Design Patterns: Elements of Reusable ObjectOriented Software; Addison-Wesley, 1995
[8] Stephan Kleuker; Grundkurs Software-Engineering mit UML,
Vieweg-Teubner Verlag, 2009
[2] S. Thrun, W. Burgard, D. Fox, Probabilistic Robotics, MIT Press 2005
[3] S. M. LaValle, Planning Algorithms, Cambridge University Press 2006
[4] M. Wooldridge, An Introduction to MultiAgent Systems, Wiley 2009
[5] Heide Balzert: Lehrbuch der Objektmodellierung - Analyse und Entwurf mit der UML 2,
Akademischer Verlag 2011
[6] Gernot Starke: Effektive Software-Architekturen - Ein praktischer Leitfaden,
Hanser, 7. Auflage 2015
[7] E. Gamma, R. Helm, R. Johson, J. Vlissides; Design Patterns: Elements of Reusable ObjectOriented Software; Addison-Wesley, 1995
[8] Stephan Kleuker; Grundkurs Software-Engineering mit UML,
Vieweg-Teubner Verlag, 2009
Connected Car und V2X- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10242
Duration (semester)
1
Learning outcomes/competences
Students acquire knowledge of the information technology fundamentals of connected and
automated mobility.
Subject-Specific and Methodological Competencies:
• Students can document and evaluate use cases for various aspects of V2X,
and define requirements for communication channels.
• Students understand the basic principles of modern cellular networks, including
modulation schemes
• Students can describe various standards and their differences with regard to, for example,
network architectures and compare them with technical requirements such as
security aspects.
• Students can evaluate various effects and requirements such as latency, Doppler shift, and
fading.
• Students analyze performance, propagation characteristics, and quality of service.
• Students understand edge solutions.
Interdisciplinary methodological competence:
• Systems thinking
• Designing and documenting target systems and services
• Specifying use cases and requirements
• Process-oriented approach
Social Competence:
• Working in small teams
• Results-oriented group work
automated mobility.
Subject-Specific and Methodological Competencies:
• Students can document and evaluate use cases for various aspects of V2X,
and define requirements for communication channels.
• Students understand the basic principles of modern cellular networks, including
modulation schemes
• Students can describe various standards and their differences with regard to, for example,
network architectures and compare them with technical requirements such as
security aspects.
• Students can evaluate various effects and requirements such as latency, Doppler shift, and
fading.
• Students analyze performance, propagation characteristics, and quality of service.
• Students understand edge solutions.
Interdisciplinary methodological competence:
• Systems thinking
• Designing and documenting target systems and services
• Specifying use cases and requirements
• Process-oriented approach
Social Competence:
• Working in small teams
• Results-oriented group work
Contents
• Vehicle-to-Vehicle, Vehicle-to-Infrastructure, and Vehicle-to-Network Communication
• Use Cases
• Requirements (including data rate, latency, security)
• 5G Mobile Networks
• 802.11p / ITS-G5
• 3GPP / 5GAA
• Edge computing
• Outlook for 6G
• Use Cases
• Requirements (including data rate, latency, security)
• 5G Mobile Networks
• 802.11p / ITS-G5
• 3GPP / 5GAA
• Edge computing
• Outlook for 6G
Teaching methods
Lecture involving student interaction, with board notes, projections, and blended
learning elements.
Completion of programming assignments on computers, either individually or in teams, to simulate
communication channels.
learning elements.
Completion of programming assignments on computers, either individually or in teams, to simulate
communication channels.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester.
Content: Programming skills, e.g., C, C++, Java,
Basic knowledge of operating systems, e.g., Linux
IP protocols for IoT systems
full 30 ECTS credits from the first semester.
Content: Programming skills, e.g., C, C++, Java,
Basic knowledge of operating systems, e.g., Linux
IP protocols for IoT systems
Forms of examination
Connected Car and V2X Module Exam:
Written exam (90 min.)
Written exam (90 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
[1] Fallgren, Dillinger, Mahmoodi, Svensson, Cellular V2X for Connected Automated Driving,
Wiley, 2021
[2] Trick, 5G: Eine Einführung in die Mobilfunknetze der 5. Generation, De Gruyter Oldenbourg,
2020
[3] Grundkurs Mobile Kommunikationssysteme: LTE-Advanced Pro, UMTS, HSPA, GSM, GPRS,
Wireless LAN und Bluetooth, Springer, 2018
[4] The Cloud-to-Thing Continuum: Opportunities and Challenges in Cloud, Fog and Edge
Computing, palgrave macmilan, 2020
[5] Mueck, Karls, Networking Vehicles to Everything, De|G Press, 2017
[6] Sommer C.; Dressler F.: Vehicular Networking. Cambridge University Press 2014
[7] 3GPP TR 22.885 Study on LTE Support for Vehicle to Everything (V2X) Services
Wiley, 2021
[2] Trick, 5G: Eine Einführung in die Mobilfunknetze der 5. Generation, De Gruyter Oldenbourg,
2020
[3] Grundkurs Mobile Kommunikationssysteme: LTE-Advanced Pro, UMTS, HSPA, GSM, GPRS,
Wireless LAN und Bluetooth, Springer, 2018
[4] The Cloud-to-Thing Continuum: Opportunities and Challenges in Cloud, Fog and Edge
Computing, palgrave macmilan, 2020
[5] Mueck, Karls, Networking Vehicles to Everything, De|G Press, 2017
[6] Sommer C.; Dressler F.: Vehicular Networking. Cambridge University Press 2014
[7] 3GPP TR 22.885 Study on LTE Support for Vehicle to Everything (V2X) Services
Fachpraktikum 1 Informationstechnik- PF
- 5 SWS
- 5 ECTS
- PF
- 5 SWS
- 5 ECTS
Number
10281
Duration (semester)
1
Informatik 4- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10163
Duration (semester)
1
Learning outcomes/competences
Students have knowledge of the applications, principles, characteristics,
areas of application, operation, and architecture of embedded systems.
Contents
• Applications and Characteristics of Embedded Systems and System-on-Chip
• Characteristics and Differences Between Hardware and System-on-Chip Architectures
• Characteristics and Principles of Digital Logic
• Communication with Sensors and Actuators, and Typical Communication Protocols
• Use of Hardware Description Languages
• Hardware-Software Interfaces
• Software Requirements for Embedded Systems
• Characteristics and Differences Between Hardware and System-on-Chip Architectures
• Characteristics and Principles of Digital Logic
• Communication with Sensors and Actuators, and Typical Communication Protocols
• Use of Hardware Description Languages
• Hardware-Software Interfaces
• Software Requirements for Embedded Systems
Teaching methods
The lecture provides an overview of the topics and serves to convey the
theoretical fundamentals. In the lab sessions, the theoretical content is reinforced through concrete
use cases and example exercises. The behavior of implementations is illustrated using IoT example applications and embedded systems
in the lab.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester.
Content: Basic knowledge of computer architecture
Content: Basic knowledge of computer architecture
Forms of examination
Computer Science 4 Module Exam:
Written Exam (90 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
[1] Jens Altenburg, „Embedded Systems Engineering: Grundlagen – Technik – Anwendungen”,
Hanser, 2021
[2] Jim Ledin, „Architecting High-Performance Embedded Systems: Design and build highperformance real-time digital systems based on FPGAs and custom circuits”, Packt Publishing, 2021
[3] Elicia White, „Making Embedded Systems: Design Patterns for Great Software”, O'Reilly 2011
[4] Daniele Lacamera, „Embedded Systems Architecture: Explore architectural concepts, pragmatic design patterns, and best practices to produce robust systems”, Packt Publishing 2018
[5] Sarah L. Harris, David Harris „Digital Design and Computer Architecture, RISC-V Edition: RISC-V Edition”, Morgan Kaufmann 2021
[6] Winfried Gehrke, Marco Winzker, Klaus Urbanski, Roland Woitowitz „Digitaltechnik: Grundlagen, VHDL, FPGAs, Mikrocontroller”, Springer Vieweg 2016
[2] Jim Ledin, „Architecting High-Performance Embedded Systems: Design and build highperformance real-time digital systems based on FPGAs and custom circuits”, Packt Publishing, 2021
[3] Elicia White, „Making Embedded Systems: Design Patterns for Great Software”, O'Reilly 2011
[4] Daniele Lacamera, „Embedded Systems Architecture: Explore architectural concepts, pragmatic design patterns, and best practices to produce robust systems”, Packt Publishing 2018
[5] Sarah L. Harris, David Harris „Digital Design and Computer Architecture, RISC-V Edition: RISC-V Edition”, Morgan Kaufmann 2021
[6] Winfried Gehrke, Marco Winzker, Klaus Urbanski, Roland Woitowitz „Digitaltechnik: Grundlagen, VHDL, FPGAs, Mikrocontroller”, Springer Vieweg 2016
Schlüsselqualifikationen- PF
- 4 SWS
- 4 ECTS
- PF
- 4 SWS
- 4 ECTS
Number
10270
Duration (semester)
1
Sensorik und Simulation- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10253
Duration (semester)
1
Learning outcomes/competences
Students gain knowledge of sensor technology and simulation.
Technical and Methodological Competence:
• Defining, documenting, and evaluating architectures of autonomous systems
• Describing the architecture and design process while taking into account data protection, data security, confidentiality, and integrity (“security by design”)
• Understanding the principles of software architectures as well as standard procedures and interfaces of distributed knowledge-based systems
• Understanding the concepts of object-oriented design and the interoperability of various software modules as well as the integration of services
• Design, implementation, testing, and documentation of exemplary applications
• Analysis of performance, runtime behavior, and quality of service
Interdisciplinary methodological competence:
• Systems thinking
• Designing and documenting target systems and services
• Specifying data structures and models, as well as interfaces and protocols
• Semantic description of services in autonomous systems
• Process-oriented approach
Social skills:
• Working in small teams
• Results-oriented group work
Technical and Methodological Competence:
• Defining, documenting, and evaluating architectures of autonomous systems
• Describing the architecture and design process while taking into account data protection, data security, confidentiality, and integrity (“security by design”)
• Understanding the principles of software architectures as well as standard procedures and interfaces of distributed knowledge-based systems
• Understanding the concepts of object-oriented design and the interoperability of various software modules as well as the integration of services
• Design, implementation, testing, and documentation of exemplary applications
• Analysis of performance, runtime behavior, and quality of service
Interdisciplinary methodological competence:
• Systems thinking
• Designing and documenting target systems and services
• Specifying data structures and models, as well as interfaces and protocols
• Semantic description of services in autonomous systems
• Process-oriented approach
Social skills:
• Working in small teams
• Results-oriented group work
Contents
Radar, camera, IMU, ...
Teaching methods
Lecture involving student interaction, with board work, projections, and blended learning
elements.
Completing programming assignments on computers, either individually or in teams.
Building systems and testing execution and response times under real-time conditions.
Completing programming assignments on computers, either individually or in teams.
Building systems and testing execution and response times under real-time conditions.
Participation requirements
Formal requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester.
Content requirements: none
Content requirements: none
Forms of examination
Sensor Technology Module Exam:
Written exam (90 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Signalverarbeitung & Regelungstechnik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10220
Duration (semester)
1
Learning outcomes/competences
Students are familiar with the essential properties of sampled signals and their
processing in sampling systems, as well as the interface challenges between analog and digital
systems, and know how to evaluate these properties as advantages or disadvantages
depending on the specific task.
They are familiar with several fundamental methods of signal analysis and processing and have
gained initial experience with practical implementation, particularly in the exercises.
The technical expertise gained throughout the module enables students to develop modern products for demanding signal processing applications in a targeted and independent manner. This applies to both analog and digital signals in the context of time- or
frequency analysis.
Students understand the description of the control-theoretic properties of typical systems as controlled systems and
the design of corresponding controllers under the assumption of stable system behavior, and can apply this knowledge in a targeted manner. Students have mastered
the fundamental principles of control engineering and the cross-system, engineering-based—i.e.,
graphical—modeling of arbitrary physical systems using the block diagram
(structure diagram methodology). They possess the ability to analyze linear, time-invariant
control-loop systems with regard to stability, transient behavior, and steady-state accuracy. The
students can independently apply the methods and procedures for the design (synthesis) and technical
implementation of controllers.
processing in sampling systems, as well as the interface challenges between analog and digital
systems, and know how to evaluate these properties as advantages or disadvantages
depending on the specific task.
They are familiar with several fundamental methods of signal analysis and processing and have
gained initial experience with practical implementation, particularly in the exercises.
The technical expertise gained throughout the module enables students to develop modern products for demanding signal processing applications in a targeted and independent manner. This applies to both analog and digital signals in the context of time- or
frequency analysis.
Students understand the description of the control-theoretic properties of typical systems as controlled systems and
the design of corresponding controllers under the assumption of stable system behavior, and can apply this knowledge in a targeted manner. Students have mastered
the fundamental principles of control engineering and the cross-system, engineering-based—i.e.,
graphical—modeling of arbitrary physical systems using the block diagram
(structure diagram methodology). They possess the ability to analyze linear, time-invariant
control-loop systems with regard to stability, transient behavior, and steady-state accuracy. The
students can independently apply the methods and procedures for the design (synthesis) and technical
implementation of controllers.
Contents
Signal Processing:
Introduction (History, Context, Motivation)
Notation, Signal Classification, Analog/Digital Elementary Signals, Periodic Signals,
Symmetries, Analog/Time-Discrete/Quantized/Digital Signals, Digital Elementary Signals,
Signal Analysis/Representation, Frequency/Transform Domain
Fourier Series, Fourier Transform, Properties of the FT Important for Communications Engineering (linearity,
shift, scaling, differentiation, convolution, symmetries)
Sampling / reconstruction, periodic spectra, ambiguity, aliasing, anti-aliasing filtering,
Spectral analysis of time-discrete signals / computational problem, DFT as an FT of a specific
class of signals, relationship between FT, FR, and the FT of discrete signals / DFT
Examples of DFTs of some signals, distinction from the FT, DFT/FFT for spectral measurements, problems
with non-integer frequency indices, time- and frequency-domain interpretation, zero-padding,
leakage effect, windowing, construction of window functions (Hann, Hamming, Blackman,
Bartlett/triangular), performance parameters
Description of continuous and discrete LTI systems, Fourier transform,
convolution integral/sum (including efficient computation/implementation in the frequency domain),
FIR filters, design using the windowing method, (non-)causality, linear phase, discrete convolution,
cyclic and acyclic convolution, overconvolution effects, Overlap-Add method
Fast Fourier transform (FFT), butterfly structure, complexity estimation/comparison, inverse
DFT/FFT, relationship with DFT/FFT, Symmetries in purely real/imaginary signals, efficient
FFT application
Discrete and recursive LTI systems, description using difference equations, (recursive)
computation, introduction of the z-transform as a “computational trick,” closed-form solution via the z-transform, Partial fraction decomposition (solution of the linear system of linear equations / residue calculation)
z-transform of some signals, properties, transfer/system function, solution of
difference equations using the z-transform, location of poles/zeros <-> Effect on
impulse response, comparison to the solution of ordinary differential equations with constant coefficients via substitution
and Laplace transform
Stability: BIBO, conditions on poles in the s-/z-domain, coefficient triangle for a complex pair of poles
Relationship between Laplace and z-transforms, mapping of the s-/psi-/z-planes
IIR filters: Design process, s-, psi-, and z-planes, approximation of the attenuation behavior (Butterworth,
Chebyshev) Bilinear transformation, spectral transformation (TP, HP, BP, BSp.), significance of
poles in the complex planes
FIR filters revisited, digital filter structures: Sensitivity, direct structure, cascade structure,
parallel structure
Introduction (History, Context, Motivation)
Notation, Signal Classification, Analog/Digital Elementary Signals, Periodic Signals,
Symmetries, Analog/Time-Discrete/Quantized/Digital Signals, Digital Elementary Signals,
Signal Analysis/Representation, Frequency/Transform Domain
Fourier Series, Fourier Transform, Properties of the FT Important for Communications Engineering (linearity,
shift, scaling, differentiation, convolution, symmetries)
Sampling / reconstruction, periodic spectra, ambiguity, aliasing, anti-aliasing filtering,
Spectral analysis of time-discrete signals / computational problem, DFT as an FT of a specific
class of signals, relationship between FT, FR, and the FT of discrete signals / DFT
Examples of DFTs of some signals, distinction from the FT, DFT/FFT for spectral measurements, problems
with non-integer frequency indices, time- and frequency-domain interpretation, zero-padding,
leakage effect, windowing, construction of window functions (Hann, Hamming, Blackman,
Bartlett/triangular), performance parameters
Description of continuous and discrete LTI systems, Fourier transform,
convolution integral/sum (including efficient computation/implementation in the frequency domain),
FIR filters, design using the windowing method, (non-)causality, linear phase, discrete convolution,
cyclic and acyclic convolution, overconvolution effects, Overlap-Add method
Fast Fourier transform (FFT), butterfly structure, complexity estimation/comparison, inverse
DFT/FFT, relationship with DFT/FFT, Symmetries in purely real/imaginary signals, efficient
FFT application
Discrete and recursive LTI systems, description using difference equations, (recursive)
computation, introduction of the z-transform as a “computational trick,” closed-form solution via the z-transform, Partial fraction decomposition (solution of the linear system of linear equations / residue calculation)
z-transform of some signals, properties, transfer/system function, solution of
difference equations using the z-transform, location of poles/zeros <-> Effect on
impulse response, comparison to the solution of ordinary differential equations with constant coefficients via substitution
and Laplace transform
Stability: BIBO, conditions on poles in the s-/z-domain, coefficient triangle for a complex pair of poles
Relationship between Laplace and z-transforms, mapping of the s-/psi-/z-planes
IIR filters: Design process, s-, psi-, and z-planes, approximation of the attenuation behavior (Butterworth,
Chebyshev) Bilinear transformation, spectral transformation (TP, HP, BP, BSp.), significance of
poles in the complex planes
FIR filters revisited, digital filter structures: Sensitivity, direct structure, cascade structure,
parallel structure
Softwaretechnik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10251
Duration (semester)
1
Learning outcomes/competences
Students acquire knowledge of the architecture of distributed systems and the design of such
systems using software engineering methods.
Technical and Methodological Competencies:
• Defining, documenting, and evaluating architectures
• Describing the architecture and design process
• Understanding the principles, patterns, and aspects of distributed software architectures
• Understanding the concepts of object-oriented design
• Design and documentation using UML Interdisciplinary methodological competence:
• Thinking in terms of systems
• Designing and documenting target systems
• Process-oriented approach Social Competence:
• Working in small teams
• Results-oriented group work
• Defining, documenting, and evaluating architectures
• Describing the architecture and design process
• Understanding the principles, patterns, and aspects of distributed software architectures
• Understanding the concepts of object-oriented design
• Design and documentation using UML Interdisciplinary methodological competence:
• Thinking in terms of systems
• Designing and documenting target systems
• Process-oriented approach Social Competence:
• Working in small teams
• Results-oriented group work
Contents
Introduction to distributed technical systems that interact closely with humans, taking
into account (partially) autonomous behavior
• Basic Concepts Time and states, distributed transactions, concurrency, synchronization
• Perception: networked data storage, multisensor data fusion
• Planning and Execution: task decomposition, reactive behavior, pre-planned behavior based on knowledge and skills, behavior transmission, learning
• Architectures: various distributed system architectures and their communication protocols (including IoT, AUTOSAR, general middleware, many-core versus multi-core concepts)
• Applications: including IoT, automotive engineering, robotics
• Software architectures, systems, and model-based software development
• Basic Concepts Time and states, distributed transactions, concurrency, synchronization
• Perception: networked data storage, multisensor data fusion
• Planning and Execution: task decomposition, reactive behavior, pre-planned behavior based on knowledge and skills, behavior transmission, learning
• Architectures: various distributed system architectures and their communication protocols (including IoT, AUTOSAR, general middleware, many-core versus multi-core concepts)
• Applications: including IoT, automotive engineering, robotics
• Software architectures, systems, and model-based software development
Teaching methods
Lecture involving student participation, with board notes and a projector.
Completion of programming assignments on computers, either individually or in teams.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester.
Substantive: Knowledge of the module content: Computer Science 1 through 3
Substantive: Knowledge of the module content: Computer Science 1 through 3
Forms of examination
Software Engineering Module Exam:
Written exam (90 min.) and/or term paper
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
[1] Coulouris et.al. : Distributed Systems – Concepts and design: Pearson 2012
[2] M. Wooldridge, An Introduction to MultiAgent Systems, Wiley 2009
[3] Heide Balzert: Lehrbuch der Objektmodellierung - Analyse und Entwurf mit der UML 2, Akademischer Verlag 2011
[4] Gernot Starke: Effektive Software-Architekturen - Ein praktischer Leitfaden, Hanser, 7. Auflage 2015
[5] E. Gamma, R. Helm, R. Johson, J. Vlissides; Design Patterns: Elements of Reusable ObjectOriented Software; Addison-Wesley, 1995
[6] Stephan Kleuker; Grundkurs Software-Engineering mit UML, Vieweg-Teubner Verlag, 2009
[2] M. Wooldridge, An Introduction to MultiAgent Systems, Wiley 2009
[3] Heide Balzert: Lehrbuch der Objektmodellierung - Analyse und Entwurf mit der UML 2, Akademischer Verlag 2011
[4] Gernot Starke: Effektive Software-Architekturen - Ein praktischer Leitfaden, Hanser, 7. Auflage 2015
[5] E. Gamma, R. Helm, R. Johson, J. Vlissides; Design Patterns: Elements of Reusable ObjectOriented Software; Addison-Wesley, 1995
[6] Stephan Kleuker; Grundkurs Software-Engineering mit UML, Vieweg-Teubner Verlag, 2009
Neurophysiologie 1- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10408
Duration (semester)
1
Systembiologie 2: Systemtheorie- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10427
Duration (semester)
1
Angewandte Biosignalverarbeitung - Einf. In maschinelle Lernverfahren- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10416
Duration (semester)
1
Learning outcomes/competences
Students understand the general principles of machine learning and know how to apply them to
specific processing tasks. They learn to read scientific publications and to develop their own algorithmic
solutions by combining technical and medical knowledge as well as elements from publications.
They are able to statistically evaluate their own algorithms, document them, and present them.
Overall, students strengthen practical skills that are highly relevant for succeeding in
project-oriented modules and for their professional careers.
specific processing tasks. They learn to read scientific publications and to develop their own algorithmic
solutions by combining technical and medical knowledge as well as elements from publications.
They are able to statistically evaluate their own algorithms, document them, and present them.
Overall, students strengthen practical skills that are highly relevant for succeeding in
project-oriented modules and for their professional careers.
Contents
- General principles of machine learning
- Applying general principles of machine learning to a specific task
- Fundamentals of feature extraction
- Selected machine learning algorithms, such as multilayer perceptrons
- Conceptual development and implementation of original algorithmic solutions
- Documentation of one’s own algorithmic solution
- Statistical evaluation
- Presentation of one’s own results
- Applying general principles of machine learning to a specific task
- Fundamentals of feature extraction
- Selected machine learning algorithms, such as multilayer perceptrons
- Conceptual development and implementation of original algorithmic solutions
- Documentation of one’s own algorithmic solution
- Statistical evaluation
- Presentation of one’s own results
Teaching methods
The course consists of lectures and seminars. Lectures cover the theoretical background of the
topics addressed. The seminars provide examples and personalized support for students’
projects, which focus on a biomedical machine learning task, such as sleep staging or the classification of
heartbeats. Students work on their projects both in the seminars and at home. The course is taught in English
(the exam may be taken in German if desired).
topics addressed. The seminars provide examples and personalized support for students’
projects, which focus on a biomedical machine learning task, such as sleep staging or the classification of
heartbeats. Students work on their projects both in the seminars and at home. The course is taught in English
(the exam may be taken in German if desired).
Participation requirements
Formal requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content requirements: Basic programming skills
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content requirements: Basic programming skills
Forms of examination
Course Exam: Applied Biosignal Processing – Introduction to Machine Learning:
Term paper with oral presentation (30 min.) (English or German)
Term paper with oral presentation (30 min.) (English or German)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Raschka, S., & Mirjalili, V. (2017). Python Machine Learning.
Weitere Literatur nach Absprache und Relevanz für die Umsetzung des studentischen Projektes.
Weitere Literatur nach Absprache und Relevanz für die Umsetzung des studentischen Projektes.
Angewandte Biosignalverarbeitung - Schlagdetektion- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10404
Duration (semester)
1
Learning outcomes/competences
Students understand the general principles of biosignal processing and know how to apply them in
specific processing tasks. They learn to read scientific publications and to develop their own algorithmic
solutions by combining technical and medical knowledge as well as elements from publications.
They are able to statistically evaluate their own algorithms, document them, and present them.
Overall, students strengthen practical skills that are highly relevant for succeeding in
project-oriented modules and for their professional careers.
specific processing tasks. They learn to read scientific publications and to develop their own algorithmic
solutions by combining technical and medical knowledge as well as elements from publications.
They are able to statistically evaluate their own algorithms, document them, and present them.
Overall, students strengthen practical skills that are highly relevant for succeeding in
project-oriented modules and for their professional careers.
Contents
General principles of biosignal processing
- Applying general principles of biosignal processing to a specific task
- Advanced processing methods such as the wavelet transform
- Conceptual development and implementation of original algorithmic solutions
- Documentation of original algorithmic solutions
- Statistical analysis
- Presentation of original results
- Applying general principles of biosignal processing to a specific task
- Advanced processing methods such as the wavelet transform
- Conceptual development and implementation of original algorithmic solutions
- Documentation of original algorithmic solutions
- Statistical analysis
- Presentation of original results
Teaching methods
The course consists of lectures and seminars. Lectures cover the theoretical background of the
topics addressed. The seminars provide examples and personalized support for the students’
project, which focuses on beat detection in electrocardiograms. The project is carried out during the
seminars and at home. The course is taught in English (the exam may be taken in German if desired).
topics addressed. The seminars provide examples and personalized support for the students’
project, which focuses on beat detection in electrocardiograms. The project is carried out during the
seminars and at home. The course is taught in English (the exam may be taken in German if desired).
Participation requirements
Formal requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content requirements: Basic programming skills
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content requirements: Basic programming skills
Forms of examination
Module Exam: Applied Biosignal Processing – Beat Detection:
Written exam (60 min.) or oral exam (30 min.) (English or German)
Written exam (60 min.) or oral exam (30 min.) (English or German)
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] I. I. Christov, “Real time electrocardiogram QRS detection using combined adaptive
threshold.,” Biomed. Eng. Online, vol. 3, no. 1, p. 28, Aug. 2004.
[2] B.-U. Köhler, C. Hennig, and R. Orglmeister, “The principles of software QRS detection.,” IEEE
Eng. Med. Biol. Mag., vol. 21, no. 1, pp. 42–57, 2002.
Weitere Literatur nach Absprache und Relevanz für die Umsetzung des studentischen Projektes.
threshold.,” Biomed. Eng. Online, vol. 3, no. 1, p. 28, Aug. 2004.
[2] B.-U. Köhler, C. Hennig, and R. Orglmeister, “The principles of software QRS detection.,” IEEE
Eng. Med. Biol. Mag., vol. 21, no. 1, pp. 42–57, 2002.
Weitere Literatur nach Absprache und Relevanz für die Umsetzung des studentischen Projektes.
Ausgewählte Kapitel der Digitalen Technologien 1- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10418
Duration (semester)
1
Learning outcomes/competences
See the module description for "Selected Chapters in Digital Technologies"
Contents
Half of the selected chapters cover topics from the module “Selected
Chapters in Digital Technologies 2” (AKDT2), which—in consultation with the students—are limited to a
suitable subset and covered over the course of one semester.
In particular, the planned practical components—scaled appropriately—are taken into account.
Chapters in Digital Technologies 2” (AKDT2), which—in consultation with the students—are limited to a
suitable subset and covered over the course of one semester.
In particular, the planned practical components—scaled appropriately—are taken into account.
Teaching methods
Seminar-style session with hands-on exercises
Participation requirements
Prerequisites for Participation
Formal: At least 45 ECTS credits must have been earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to one of the module exams for Selected Chapters in Digital
Technologies 1 or Selected Chapters in Digital Technologies 2 is
denied if the other module has already been passed. Admission to
module exams in both modules is not permitted if these module exams are scheduled to take place
within the same exam period or on the designated
exam dates no later than the start of the following semester.
Content: none
Formal: At least 45 ECTS credits must have been earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to one of the module exams for Selected Chapters in Digital
Technologies 1 or Selected Chapters in Digital Technologies 2 is
denied if the other module has already been passed. Admission to
module exams in both modules is not permitted if these module exams are scheduled to take place
within the same exam period or on the designated
exam dates no later than the start of the following semester.
Content: none
Forms of examination
Module Exam: Selected Chapters in Digital Technologies 1:
Written exam (60 min.) or oral exam (20 min.)
Written exam (60 min.) or oral exam (20 min.)
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
entsprechend der aktuellen Ausrichtung der Veranstaltung
Ausgewählte Kapitel der Digitalen Technologien 2- WP
- 2 SWS
- 6 ECTS
- WP
- 2 SWS
- 6 ECTS
Number
10419
Duration (semester)
1
Learning outcomes/competences
Students have advanced knowledge of network technology and protocols
and have gained insight into current developments.
and have gained insight into current developments.
Contents
The content of the required courses in the field of networks is supplemented by topics that
have not yet been covered or have not been addressed to the desired extent, as well as topics
with particular current relevance.
Regular topics include, among others, an in-depth examination of IPv6, DNS, DHCP, PKI, SSL/TLS
, and the tools used for their operation and experimental analysis.
have not yet been covered or have not been addressed to the desired extent, as well as topics
with particular current relevance.
Regular topics include, among others, an in-depth examination of IPv6, DNS, DHCP, PKI, SSL/TLS
, and the tools used for their operation and experimental analysis.
Teaching methods
Seminar-style session with hands-on exercises
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to one of the module exams for Selected Chapters in Digital
Technologies 1 or Selected Chapters in Digital Technologies 2 is
denied if the other module has already been passed. Admission to
module exams in both modules is not permitted if these module exams are scheduled to take place
within the same exam period or on the designated
exam dates no later than the start of the following semester.
Content: none
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to one of the module exams for Selected Chapters in Digital
Technologies 1 or Selected Chapters in Digital Technologies 2 is
denied if the other module has already been passed. Admission to
module exams in both modules is not permitted if these module exams are scheduled to take place
within the same exam period or on the designated
exam dates no later than the start of the following semester.
Content: none
Forms of examination
Module Exam: Selected Chapters in Digital Technologies 2:
Written exam (120 min.) or oral exam (30 min.)
Written exam (120 min.) or oral exam (30 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
6/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
entsprechend der aktuellen Ausrichtung der Veranstaltung
Ausgewählte Softwaresysteme - Programmierung IV- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10402
Duration (semester)
1
Learning outcomes/competences
Learning Outcomes / Competencies
Students acquire knowledge of selected topics related to current software systems and their
development.
Subject-Specific and Methodological Competencies:
• Understanding the principles, patterns, and aspects of software architectures
• Describing and explaining the software methods covered in a clear and comprehensible manner
• Documenting and evaluating the software methods covered
• Classifying the architectures and methods under consideration
• Developing a meaningful example
Interdisciplinary methodological competence:
• Expanding methodological competence based on current topics
• Independently developing new topics
• Explaining and presenting new topics
Social Competence:
• Working in small teams
• Results-oriented group work
The course content is taught in a seminar-style format.
In this format, students work on specific topics in small groups and
present their findings. This approach is designed to practice key competencies—such as communication and teamwork skills—alongside
collaborative presentation techniques, while also strengthening students’ ability to independently explore a selected
topic. In addition, there are practical exercises on the
topics covered in the seminar component to help all participants
gain a deeper understanding of these topics. (cf. flipped classroom, blended learning [7])
Students acquire knowledge of selected topics related to current software systems and their
development.
Subject-Specific and Methodological Competencies:
• Understanding the principles, patterns, and aspects of software architectures
• Describing and explaining the software methods covered in a clear and comprehensible manner
• Documenting and evaluating the software methods covered
• Classifying the architectures and methods under consideration
• Developing a meaningful example
Interdisciplinary methodological competence:
• Expanding methodological competence based on current topics
• Independently developing new topics
• Explaining and presenting new topics
Social Competence:
• Working in small teams
• Results-oriented group work
The course content is taught in a seminar-style format.
In this format, students work on specific topics in small groups and
present their findings. This approach is designed to practice key competencies—such as communication and teamwork skills—alongside
collaborative presentation techniques, while also strengthening students’ ability to independently explore a selected
topic. In addition, there are practical exercises on the
topics covered in the seminar component to help all participants
gain a deeper understanding of these topics. (cf. flipped classroom, blended learning [7])
Contents
Selected Chapters on Modern Software Architectures and Software Development
including, among others:
• Programming Languages
• Algorithms
• Handling Large Data Sets (Big Data)
• Security and Safety in Software
• Modern Software Architectures
• Software Methods in Artificial Intelligence
• Software and Systems Development
including, among others:
• Programming Languages
• Algorithms
• Handling Large Data Sets (Big Data)
• Security and Safety in Software
• Modern Software Architectures
• Software Methods in Artificial Intelligence
• Software and Systems Development
Teaching methods
Seminar course
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
The Computer Science 1 module must have been passed.
Content-wise: Knowledge of the module content:
Computer Science 2 and 3
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
The Computer Science 1 module must have been passed.
Content-wise: Knowledge of the module content:
Computer Science 2 and 3
Forms of examination
Module Exam: Selected Current Topics in Software Development:
Term paper followed by an oral presentation (45 min.)
Term paper followed by an oral presentation (45 min.)
Requirements for the awarding of credit points
Students must pass both the term paper and the oral presentation.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] W. Ertel, E. Löhmann; Angewandte Kryptographie,
Hanser Verlag 2018
[2] W. Erwig; Once upon an algorithm,
MIT Press 2017
[3] J. Frochte, Maschinelles Lernen – Grundlagen und Algorithmen in Python,
Hanser Verlag 2018
[4] S. Russel, P. Norwig, Künstliche Intelligenz, 3. Auflage
Pearson 2012
[5] S. Sedgewick, K. Wayne; Algorithms, 4th edition
Addison-Wesley 2011
[6] S. Thrun, W. Burgard, D. Fox, Probabilistic Robotics,
MIT Press 2005
[7] J. Zumbach, He. Astleitner; Effektives Lernen an der Hochschule: Ein Handbuch zur
Hochschuldidaktik, Kohlhammer Verlag 2016
[8] weitere spezifische Literatur nach Themenstellung
Hanser Verlag 2018
[2] W. Erwig; Once upon an algorithm,
MIT Press 2017
[3] J. Frochte, Maschinelles Lernen – Grundlagen und Algorithmen in Python,
Hanser Verlag 2018
[4] S. Russel, P. Norwig, Künstliche Intelligenz, 3. Auflage
Pearson 2012
[5] S. Sedgewick, K. Wayne; Algorithms, 4th edition
Addison-Wesley 2011
[6] S. Thrun, W. Burgard, D. Fox, Probabilistic Robotics,
MIT Press 2005
[7] J. Zumbach, He. Astleitner; Effektives Lernen an der Hochschule: Ein Handbuch zur
Hochschuldidaktik, Kohlhammer Verlag 2016
[8] weitere spezifische Literatur nach Themenstellung
Automotive Systems- WP
- 2 SWS
- 5 ECTS
- WP
- 2 SWS
- 5 ECTS
Number
10434
Duration (semester)
1
Contact time
60 h
Self-study
120 h
Learning outcomes/competences
Students have mastered the key techniques of systems engineering.
Subject-matter and methodological competence:
• Students can describe development methodologies and apply them to case studies .
• Students can define requirements in accordance with the SMART acronym.
• Students are familiar with key architectures such as AUTOSAR and AUTOSAR adaptive.
• Students have mastered the fundamentals of ISO 26262 and SOTIF.
Interdisciplinary methodological competence:
• Systems thinking
• Specification of use cases and requirements
• Discussion of the risks of technical systems
• Process-oriented approach
Social Competence:
• Working in small teams
• Results-oriented group work
Subject-matter and methodological competence:
• Students can describe development methodologies and apply them to case studies .
• Students can define requirements in accordance with the SMART acronym.
• Students are familiar with key architectures such as AUTOSAR and AUTOSAR adaptive.
• Students have mastered the fundamentals of ISO 26262 and SOTIF.
Interdisciplinary methodological competence:
• Systems thinking
• Specification of use cases and requirements
• Discussion of the risks of technical systems
• Process-oriented approach
Social Competence:
• Working in small teams
• Results-oriented group work
Contents
• Development Processes and Standards
• System Components
• Software Development
• Functional Safety and Cybersecurity
• System Validation and Verification
• Tools for System Development
• Automotive Supply Chain
• Application Examples: Automated Driving
• System Components
• Software Development
• Functional Safety and Cybersecurity
• System Validation and Verification
• Tools for System Development
• Automotive Supply Chain
• Application Examples: Automated Driving
Teaching methods
• Lecture
• Lab exercise using MATLAB/Simulink
• Case study based on current scientific publications
• Test drives with a prototype vehicle (subject to availability)
• Lab exercise using MATLAB/Simulink
• Case study based on current scientific publications
• Test drives with a prototype vehicle (subject to availability)
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester.
Substantive: Knowledge of: signal and system theory and MATLAB (basics)
Substantive: Knowledge of: signal and system theory and MATLAB (basics)
Forms of examination
Module Exam in Automotive Systems Engineering:
• Written exam (90 min.) or
• 50% oral exam (30 min.)
• 50% case study
• Written exam (90 min.) or
• 50% oral exam (30 min.)
• 50% case study
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Literature
[1] Maurer, Winner, Automotive Systems Engineering, Springer 2013
[2] Winner, Prokop, Maurer, Automotive Systems Engineering, Springer 2018
[2] Winner, Prokop, Maurer, Automotive Systems Engineering, Springer 2018
Bewegungsanalyse- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10432
Duration (semester)
1
Bildgebende Verfahren der Medizintechnik 1- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10405
Duration (semester)
1
Bildgebende Verfahren der Medizintechnik 2- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10415
Duration (semester)
1
Cyber Security 1- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10423
Duration (semester)
1
Learning outcomes/competences
Students who complete this course will have a basic understanding of what is known as
cybersecurity, primarily in the context of information and network security.
They can analyze application scenarios from a security perspective in a structured manner, identify
challenges, and engage in technical dialogue.
They are familiar with security principles and have a basic understanding of the
technologies and procedures to be used.
cybersecurity, primarily in the context of information and network security.
They can analyze application scenarios from a security perspective in a structured manner, identify
challenges, and engage in technical dialogue.
They are familiar with security principles and have a basic understanding of the
technologies and procedures to be used.
Contents
- Overview and Motivation
- Types of Malware and Attacks
- Protection Mechanisms, Cryptography, Obfuscation, Access Control
- Integrity, hashes, signatures, certificates
- Availability, incident response, hardening measures
- Formal frameworks, ISO 27000, BSI
- Types of Malware and Attacks
- Protection Mechanisms, Cryptography, Obfuscation, Access Control
- Integrity, hashes, signatures, certificates
- Availability, incident response, hardening measures
- Formal frameworks, ISO 27000, BSI
Teaching methods
The course content is taught through seminar-style lectures.
Online course materials are increasingly used for knowledge transfer, practice, and
assessment of learning objectives.
Procedures and methods are reinforced through examples in exercises and tested in practical applications.
Online course materials are increasingly used for knowledge transfer, practice, and
assessment of learning objectives.
Procedures and methods are reinforced through examples in exercises and tested in practical applications.
Participation requirements
Formal requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
Forms of examination
Cyber Security 1 Module Exam:
Written exam (60 min.) or oral exam (20 min.)
Written exam (60 min.) or oral exam (20 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
Literatur wird in der Veranstaltung bekannt gegeben.
Cyber Security 2- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10430
Duration (semester)
1
Learning outcomes/competences
Students who complete this course will have an in-depth understanding of
information and network security.
They will be able to analyze application scenarios from a security perspective in a structured manner.
They can address identified challenges in a practical manner and, with regard to cybersecurity, have experience in working with and deploying network protocols, development,
operating system, and application software, as well as tools.
information and network security.
They will be able to analyze application scenarios from a security perspective in a structured manner.
They can address identified challenges in a practical manner and, with regard to cybersecurity, have experience in working with and deploying network protocols, development,
operating system, and application software, as well as tools.
Contents
As examples, individual aspects of the fundamental considerations presented in CS-1
are addressed, explored in greater depth, and cross-referenced. Practical examples
are consistently developed so that, in addition to covering the theoretical background, students can also practice working with the software and tools used in the field
. The goal is to enable students to understand security as an overarching aspect of the
software development life cycle. Topics covered include, for example:
- Operating systems: Linux, (Windows)
- Network protocols and services
- Network security at various layers, attacks, defense mechanisms, and tools
- Identity & Access Management, Authentication / Authorization / Accounting
- Endpoint security, monitoring, intrusion detection/prevention, data analysis
- Handling security incidents
are covered.
The specific content of each session is also tailored to the interests of the audience and
to current events and developments.
are addressed, explored in greater depth, and cross-referenced. Practical examples
are consistently developed so that, in addition to covering the theoretical background, students can also practice working with the software and tools used in the field
. The goal is to enable students to understand security as an overarching aspect of the
software development life cycle. Topics covered include, for example:
- Operating systems: Linux, (Windows)
- Network protocols and services
- Network security at various layers, attacks, defense mechanisms, and tools
- Identity & Access Management, Authentication / Authorization / Accounting
- Endpoint security, monitoring, intrusion detection/prevention, data analysis
- Handling security incidents
are covered.
The specific content of each session is also tailored to the interests of the audience and
to current events and developments.
Teaching methods
The course content is taught through lectures with a seminar-style format.
Procedures and methods are explored in greater depth through examples in exercises.
The focus is very much on practical application.
Procedures and methods are explored in greater depth through examples in exercises.
The focus is very much on practical application.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Knowledge of the module content for Cyber Security 1. Knowledge in the area of
network protocols and software engineering is desirable.
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Knowledge of the module content for Cyber Security 1. Knowledge in the area of
network protocols and software engineering is desirable.
Forms of examination
M
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
Literatur wird in der Veranstaltung bekannt gegeben.
Digitale Signalverarbeitung 2- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10414
Duration (semester)
1
Digitale Signalverarbeitung für (Mobil-)Kommunikationssysteme- WP
- 2 SWS
- 6 ECTS
- WP
- 2 SWS
- 6 ECTS
Number
10420
Duration (semester)
1
Learning outcomes/competences
Building on the basic knowledge of digital signal processing already acquired,
students have the knowledge and skills to understand a digital transmission system in its
fundamental aspects, to design and simulate the signal processing components
and to implement such a system.
students have the knowledge and skills to understand a digital transmission system in its
fundamental aspects, to design and simulate the signal processing components
and to implement such a system.
Contents
Principles and aspects of digital transmitter and receiver architectures, including: Pulse shaping,
intersymbol interference, noise adaptation, transmission of stochastic signals, equalization methods,
adaptive filters for equalization and channel identification, nonlinear equalizers, modulation and
detection methods, sequence estimation, error protection schemes, synchronization methods,
examples of the design and operation of complete digital transmitters and receivers for
standard transmission methods, SDR
intersymbol interference, noise adaptation, transmission of stochastic signals, equalization methods,
adaptive filters for equalization and channel identification, nonlinear equalizers, modulation and
detection methods, sequence estimation, error protection schemes, synchronization methods,
examples of the design and operation of complete digital transmitters and receivers for
standard transmission methods, SDR
Teaching methods
Seminar course
Participation requirements
Formal requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
Forms of examination
Course Exam: Digital Signal Processing for (Mobile) Communication Systems:
Written exam (120 min.) or oral exam (30 min.)
Written exam (120 min.) or oral exam (30 min.)
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
6/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology and Information Technology with a Practical/Study Abroad Semester)
Information Technology and Information Technology with a Practical/Study Abroad Semester)
Literature
Literatur wird in der Veranstaltung bekannt gegeben.
EM Design- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10428
Duration (semester)
1
Learning outcomes/competences
By the end of the course, participants will have developed an understanding of the mathematical and physical fundamentals of numerical calculations of electromagnetic fields and
will have acquired practical skills in using modern 3D EM simulation tools. They will be
able to independently create simple 3D EM models in various application contexts,
perform simulations, and evaluate the quality of the results. Furthermore,
participants will be able to assess the capabilities and limitations of 3D EM field simulation
in terms of accuracy and computational effort.
will have acquired practical skills in using modern 3D EM simulation tools. They will be
able to independently create simple 3D EM models in various application contexts,
perform simulations, and evaluate the quality of the results. Furthermore,
participants will be able to assess the capabilities and limitations of 3D EM field simulation
in terms of accuracy and computational effort.
Contents
This course provides an introduction to the operation and application of 3D EM
field simulation programs. 3D EM field simulations are used in many fields
, such as medical technology (e.g., MRI coil design), communications technology (e.g.,
antenna design), as well as in occupational safety studies (the effects of electromagnetic
fields on body tissue or medical implants), and many others. This
course provides excellent preparation for students who wish to delve deeper into the topic of EM simulation in
project-oriented work.
Content:
• Fundamentals of field theory
• Numerical methods for solving Maxwell’s equations
• Structure definition/CAD, material properties
• Ports and boundary conditions
• Spatial discretization of the solution domain
• Canonical examples (e.g., plate capacitor, coil, dipole)
• Application examples (e.g., MRI birdcage coil, cellular base station antenna)
field simulation programs. 3D EM field simulations are used in many fields
, such as medical technology (e.g., MRI coil design), communications technology (e.g.,
antenna design), as well as in occupational safety studies (the effects of electromagnetic
fields on body tissue or medical implants), and many others. This
course provides excellent preparation for students who wish to delve deeper into the topic of EM simulation in
project-oriented work.
Content:
• Fundamentals of field theory
• Numerical methods for solving Maxwell’s equations
• Structure definition/CAD, material properties
• Ports and boundary conditions
• Spatial discretization of the solution domain
• Canonical examples (e.g., plate capacitor, coil, dipole)
• Application examples (e.g., MRI birdcage coil, cellular base station antenna)
Teaching methods
Computer-Assisted Seminar Course
Language
- Course: German/English
- Exam: German/English
- Reading list: German/English
Language
- Course: German/English
- Exam: German/English
- Reading list: German/English
Participation requirements
Formal requirements: See StgPO
Content requirements: Students must have successfully completed the Physics 2 submodule (Electric and Magnetic Fields) and the module
Fundamentals of Electrical Engineering.
Content requirements: Students must have successfully completed the Physics 2 submodule (Electric and Magnetic Fields) and the module
Fundamentals of Electrical Engineering.
Forms of examination
Computer-Based Exam
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Frank Gustrau
Electromagnetic Design, Theorie und Simulation elektromagnetischer Felder,
Hanser, 2023
[2] Frank Gustrau, Dirk Manteuffel
EM Modeling of Antennas and RF Components for Wireless Communication Systems
Springer, 2006
[3] Frank Gustrau
RF and Microwave Engineering, Fundamentals of Wireless Communications
Wiley, 2025
[4] Frank Gustrau
Hochfrequenztechnik, Grundlagen der mobilen Kommunikationstechnik
Hanser, 4. aktualisierte Auflage, 2023
Electromagnetic Design, Theorie und Simulation elektromagnetischer Felder,
Hanser, 2023
[2] Frank Gustrau, Dirk Manteuffel
EM Modeling of Antennas and RF Components for Wireless Communication Systems
Springer, 2006
[3] Frank Gustrau
RF and Microwave Engineering, Fundamentals of Wireless Communications
Wiley, 2025
[4] Frank Gustrau
Hochfrequenztechnik, Grundlagen der mobilen Kommunikationstechnik
Hanser, 4. aktualisierte Auflage, 2023
Einführung in Maschinelles Lernen und Künstliche Intelligenz- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10407
Duration (semester)
1
Learning outcomes/competences
Students learn about the various machine learning methods and their
areas of application.
They acquire the ability to select the appropriate methods for a given problem,
apply them, and interpret the results obtained.
Students know and understand the theoretical foundations of machine learning,
such as the bias-variance tradeoff, cross-validation, and underfitting/overfitting. They are able to apply
machine learning methods to various problems in order to arrive at new
solutions.
To apply these methods, students are proficient in a typical programming language
and related tools, as well as libraries and frameworks.
areas of application.
They acquire the ability to select the appropriate methods for a given problem,
apply them, and interpret the results obtained.
Students know and understand the theoretical foundations of machine learning,
such as the bias-variance tradeoff, cross-validation, and underfitting/overfitting. They are able to apply
machine learning methods to various problems in order to arrive at new
solutions.
To apply these methods, students are proficient in a typical programming language
and related tools, as well as libraries and frameworks.
Contents
• Fundamentals of Machine Learning
• Linear Regression
• Classification
• Cross-Validation and Model Selection
• Regularization
• Unsupervised Learning Methods
• Linear Regression
• Classification
• Cross-Validation and Model Selection
• Regularization
• Unsupervised Learning Methods
Teaching methods
The theoretical content required to acquire subject-matter and methodological competence is taught in the form of a
lecture. The lecture material is worked through—largely independently—either individually or in small groups at a computer
using assigned exercises. The results and
interpretation of the exercises are then presented to the class.
In addition to developing subject-specific and methodological competence in the field of neural networks, this is intended to foster the
key skills of teamwork and presentation techniques.
lecture. The lecture material is worked through—largely independently—either individually or in small groups at a computer
using assigned exercises. The results and
interpretation of the exercises are then presented to the class.
In addition to developing subject-specific and methodological competence in the field of neural networks, this is intended to foster the
key skills of teamwork and presentation techniques.
Participation requirements
Formal requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
Forms of examination
Module Exam: Introduction to Machine Learning and Artificial Intelligence:
Depending on the number of participating students
Exercises and oral exam (30 min.) or written exam (60 min.)
Depending on the number of participating students
Exercises and oral exam (30 min.) or written exam (60 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Handbuch der künstlichen Intelligenz
Görz et. al; de Gruyter 2013
[2] Soft Computing
Aliev, Bonfig, Aliew; Verlag Technik 2000
[3] Fuzzy Logic with Engineering Applications
Ross, R.; Wiley & Sons
[4] Aktuelle Literatur zu den Themen
machine learning, deep learning, neuronal networks, fuzzy systems
Görz et. al; de Gruyter 2013
[2] Soft Computing
Aliev, Bonfig, Aliew; Verlag Technik 2000
[3] Fuzzy Logic with Engineering Applications
Ross, R.; Wiley & Sons
[4] Aktuelle Literatur zu den Themen
machine learning, deep learning, neuronal networks, fuzzy systems
Einführung in die Radartechnik- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10445
Language(s)
de
Duration (semester)
1
Learning outcomes/competences
Radar sensors play a crucial role in the development of
automated driving functions. This module introduces students to the fundamentals.
Students gain knowledge of the fundamentals of radar technology and can apply this knowledge
in practice to configure radar systems. In doing so, they will be able to evaluate the advantages and disadvantages
of various configurations (e.g., number and type of antennas and modulation schemes)
—particularly for use in the context of intelligent mobility—for various
use cases and functions.
Subject-Specific and Methodological Competencies:
• Students are familiar with the fundamental propagation characteristics of microwaves
including multipath propagation
• They can identify and describe the basic components of radar systems
• Students are familiar with the most important modulation schemes and can create simple
simulations
• Basic signal processing algorithms such as CFAR can be prototypically implemented using
simulation tools.
Interdisciplinary methodological competence:
• Specification of use cases and requirements
• Systems thinking
• Process-oriented approach
• Modeling and implementation of simple simulation models
Social skills:
• Working in small teams
• Results-oriented group work
automated driving functions. This module introduces students to the fundamentals.
Students gain knowledge of the fundamentals of radar technology and can apply this knowledge
in practice to configure radar systems. In doing so, they will be able to evaluate the advantages and disadvantages
of various configurations (e.g., number and type of antennas and modulation schemes)
—particularly for use in the context of intelligent mobility—for various
use cases and functions.
Subject-Specific and Methodological Competencies:
• Students are familiar with the fundamental propagation characteristics of microwaves
including multipath propagation
• They can identify and describe the basic components of radar systems
• Students are familiar with the most important modulation schemes and can create simple
simulations
• Basic signal processing algorithms such as CFAR can be prototypically implemented using
simulation tools.
Interdisciplinary methodological competence:
• Specification of use cases and requirements
• Systems thinking
• Process-oriented approach
• Modeling and implementation of simple simulation models
Social skills:
• Working in small teams
• Results-oriented group work
Contents
• Wave Propagation
• Antennas
• Radar Block Diagram
• Radar Signal Processing
• Applications
• Antennas
• Radar Block Diagram
• Radar Signal Processing
• Applications
Teaching methods
The lecture (which is partly seminar-style) is designed to convey the theoretical content. In
the exercises, the theoretical material is reinforced through use cases and sample problems using
simulation tools. Individual aspects are explored in greater depth using sample applications on TI development boards
.
the exercises, the theoretical material is reinforced through use cases and sample problems using
simulation tools. Individual aspects are explored in greater depth using sample applications on TI development boards
.
Participation requirements
Formal requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
Forms of examination
Module Exam: Introduction to Radar Technology:
50% oral exam (20 minutes), 50% written assignment
50% oral exam (20 minutes), 50% written assignment
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Baur, Einführung in die Radartechnik, Teubner, 1985
[2] Detlefsen, Radartechnik: Grundlagen, Bauelemente, Verfahren, Anwendungen, Springer
Verlag
[3] Ludloff, Handbuch Radar und Radarsignalverarbeitung, Vieweg, 1993
[4] Mahafza, Radar Signal Analysis and Processing using Matlab, CRC Press, 2016
[5] Winner, Handbuch Fahrerassistenzsysteme, Springer, 2015
[2] Detlefsen, Radartechnik: Grundlagen, Bauelemente, Verfahren, Anwendungen, Springer
Verlag
[3] Ludloff, Handbuch Radar und Radarsignalverarbeitung, Vieweg, 1993
[4] Mahafza, Radar Signal Analysis and Processing using Matlab, CRC Press, 2016
[5] Winner, Handbuch Fahrerassistenzsysteme, Springer, 2015
Embedded Systems Hardware Design and Rapid Prototyping- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10421
Duration (semester)
1
Learning outcomes/competences
Knowledge
• Understands the fundamentals of circuit and PCB design
• Understands the theory of signal and power integrity
• Understands the theory of EMI pre-compliance testing
Skills
• Can create a schematic diagram for an embedded system
• Can create a PCB layout for an embedded system
• Can assemble and solder components onto a PCB
• Can perform hardware debugging using modern measurement instruments
Competences
• Can break down complex tasks into small work packages and meet deadlines
• Can communicate with experts to solve specific problems
• Can present project progress to an audience
• Understands the fundamentals of circuit and PCB design
• Understands the theory of signal and power integrity
• Understands the theory of EMI pre-compliance testing
Skills
• Can create a schematic diagram for an embedded system
• Can create a PCB layout for an embedded system
• Can assemble and solder components onto a PCB
• Can perform hardware debugging using modern measurement instruments
Competences
• Can break down complex tasks into small work packages and meet deadlines
• Can communicate with experts to solve specific problems
• Can present project progress to an audience
Contents
In this course, the course content is taught using a project-based approach. This means that
each participant will select a project at the beginning of the course, which they will then independently develop over the course of the
semester, from the design phase all the way to the finished prototype.
Course Content
Circuit Design and Printed Circuit Board Design
- Introduction to KiCad
- Fundamentals of Signal and Power Integrity
Rapid Prototyping
- Industrial Manufacturing of Printed Circuit Boards
- Soldering Techniques
- Debugging Techniques for Circuits
EMC Precompliance Testing
- CISPR Standards
- Conducted Emissions
- Electromagnetic Emissions
Practical Project
- In the first step, students develop a schematic for a simple embedded
system, e.g., an Arduino-compatible system. After completing the schematic, the
students give a 10-minute presentation on their design.
- Next, students design a PCB layout based on their schematic. The PCB layout is presented to the entire class in a 5-minute presentation
.
- PCBs are manufactured externally using the layout data created by the students, which
the students then assemble under supervision. The
soldering techniques used include conventional soldering, hot air, and, if necessary, reflow.
- Students commission the circuit they assembled themselves and run a simple
test code on the microcontroller.
Students perform a pre-compliance EMC measurement.
Teaching methods
The course material is taught through lectures. The prototype developed by the students
is built during the exercises and lab sessions.
is built during the exercises and lab sessions.
Participation requirements
Formal requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content-related requirements: none
Forms of examination
Course Exam: Embedded Systems Hardware Design and Rapid Prototyping:
Plenary presentations on the completed circuit, including a presentation of the test results, and
Q&A session
Plenary presentations on the completed circuit, including a presentation of the test results, and
Q&A session
Requirements for the awarding of credit points
Successful presentations and successful completion of the practical project.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Principles of Power Integrity for PDN Design, Smith and Bogatin, Prentice Hall (2019)
[2] KiCad Like a Pro, Dalmaris, Tech Explorations (2018)
[3] Characterization of Power Distribution Networks, Novak and Miller, Artech House (2007)
[4] High-Speed Circuit Board Signal Integrity, Thierauf, Artech house (2017)
[2] KiCad Like a Pro, Dalmaris, Tech Explorations (2018)
[3] Characterization of Power Distribution Networks, Novak and Miller, Artech House (2007)
[4] High-Speed Circuit Board Signal Integrity, Thierauf, Artech house (2017)
Extended Reality- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10429
Duration (semester)
1
Learning outcomes/competences
Students can explain the basic terms, concepts, and perceptual aspects of
Extended Reality (XR). In particular, they can classify Virtual Reality (VR) and
Augmented Reality (AR) as forms of XR. Students can explain the
basic functioning of components used to build XR systems and describe their
role in interacting with the user to create an immersive experience in a
virtual or augmented world. Furthermore, students can
apply this knowledge to their background in computer science to develop simple XR applications
.
Extended Reality (XR). In particular, they can classify Virtual Reality (VR) and
Augmented Reality (AR) as forms of XR. Students can explain the
basic functioning of components used to build XR systems and describe their
role in interacting with the user to create an immersive experience in a
virtual or augmented world. Furthermore, students can
apply this knowledge to their background in computer science to develop simple XR applications
.
Contents
• Introduction and Definition
• Applications of Extended Reality (XR)
• Tracking
• Perceptual aspects
• XR input and output devices
• Aspects of human-computer interaction
Unlike Extended Reality 2, only the basics of these topics are covered.
• Applications of Extended Reality (XR)
• Tracking
• Perceptual aspects
• XR input and output devices
• Aspects of human-computer interaction
Unlike Extended Reality 2, only the basics of these topics are covered.
Teaching methods
The lecture (SV) is conducted in a seminar-style format with the aid of slides. In the practicum
, the results of exercises are discussed, presentations are prepared and delivered, and
practicum sessions in laboratories or projects are carried out.
Field trips may be organized to supplement the course.
Language: German
, the results of exercises are discussed, presentations are prepared and delivered, and
practicum sessions in laboratories or projects are carried out.
Field trips may be organized to supplement the course.
Language: German
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to one of the module exams for Extended Reality or Extended Reality
2 must be denied if the other module has already been passed.
Admission to module exams in both modules is not permitted if these module exams are scheduled to take place within the same exam period or on the designated
exam dates no later than the start of the following semester.
Content: Computer science/programming skills, interest in Extended Reality (XR)
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to one of the module exams for Extended Reality or Extended Reality
2 must be denied if the other module has already been passed.
Admission to module exams in both modules is not permitted if these module exams are scheduled to take place within the same exam period or on the designated
exam dates no later than the start of the following semester.
Content: Computer science/programming skills, interest in Extended Reality (XR)
Forms of examination
Extended Reality Course Exam:
Term papers, presentations, and project-based assignments
Term papers, presentations, and project-based assignments
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Dörner, Ralf, Broll, Wolfgang, Grimm, Paul, Jung, Bernhard (Hg.) (2019). Virtual und
Augmented Reality (VR/AR): Grundlagen und Methoden der Virtuellen und Augmentierten
Realität. Berlin, Heidelberg: Springer. Als E-Book verfügbar.
[2] Jerald, Jason (2016). The VR Book: Human-Centered Design for Virtual Reality (Acm Books).
Morgan & Claypool Publishers-Acm.
[3] LaValle, Steven M. (2020). Virtual Reality. Als E-Book verfügbar unter http://lavalle.pl/vr/.
Abruf 13.07.2022.
[4] Schmalstieg, Dieter; Höllerer, Tobias (2016). Augmented Reality: Principles and Practice.
Boston: Addison-Wesley
Augmented Reality (VR/AR): Grundlagen und Methoden der Virtuellen und Augmentierten
Realität. Berlin, Heidelberg: Springer. Als E-Book verfügbar.
[2] Jerald, Jason (2016). The VR Book: Human-Centered Design for Virtual Reality (Acm Books).
Morgan & Claypool Publishers-Acm.
[3] LaValle, Steven M. (2020). Virtual Reality. Als E-Book verfügbar unter http://lavalle.pl/vr/.
Abruf 13.07.2022.
[4] Schmalstieg, Dieter; Höllerer, Tobias (2016). Augmented Reality: Principles and Practice.
Boston: Addison-Wesley
Extended Reality 2- WP
- 4 SWS
- 6 ECTS
- WP
- 4 SWS
- 6 ECTS
Number
10433
Duration (semester)
1
Learning outcomes/competences
Students can explain the terms, concepts, and perceptual aspects of Extended Reality (XR)
. In particular, they can classify and distinguish Virtual Reality (VR) and Augmented Reality (AR) as
forms of XR. Students can explain how
components used to build XR systems function and describe their role in interacting with the
user to create an immersive experience in a virtual or augmented
(extended) world. Furthermore, students can combine this knowledge with
their background in computer science/programming to
develop XR applications.
. In particular, they can classify and distinguish Virtual Reality (VR) and Augmented Reality (AR) as
forms of XR. Students can explain how
components used to build XR systems function and describe their role in interacting with the
user to create an immersive experience in a virtual or augmented
(extended) world. Furthermore, students can combine this knowledge with
their background in computer science/programming to
develop XR applications.
Contents
• Introduction and Definition
• Applications of Extended Reality (XR)
• Tracking
• Perceptual aspects
• XR input and output devices
• Aspects of human-computer interaction
The topics covered in Extended Reality are explored in greater depth.
• Applications of Extended Reality (XR)
• Tracking
• Perceptual aspects
• XR input and output devices
• Aspects of human-computer interaction
The topics covered in Extended Reality are explored in greater depth.
Teaching methods
The lecture (SV) is conducted in a seminar-style format with the aid of slides. In the practicum
, the results of exercises are discussed, presentations are prepared and delivered, and
practicum sessions in laboratories or projects are carried out.
Field trips may be organized to further the course material.
, the results of exercises are discussed, presentations are prepared and delivered, and
practicum sessions in laboratories or projects are carried out.
Field trips may be organized to further the course material.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to one of the module exams for Extended Reality or Extended Reality
2 must be denied if the other module has already been passed.
Admission to module exams in both modules is not permitted if these module exams are scheduled to take place within the same exam period or on the designated
exam dates no later than the start of the following semester.
Prerequisites: Computer science/programming skills, interest in Extended Reality (XR)
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to one of the module exams for Extended Reality or Extended Reality
2 must be denied if the other module has already been passed.
Admission to module exams in both modules is not permitted if these module exams are scheduled to take place within the same exam period or on the designated
exam dates no later than the start of the following semester.
Prerequisites: Computer science/programming skills, interest in Extended Reality (XR)
Forms of examination
Extended Reality 2 Course Exam:
Term papers, presentations, and project-based assignments.
Term papers, presentations, and project-based assignments.
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
6/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Dörner, Ralf, Broll, Wolfgang, Grimm, Paul, Jung, Bernhard (Hg.) (2019). Virtual und
Augmented Reality (VR/AR): Grundlagen und Methoden der Virtuellen und Augmentierten
Realität. Berlin, Heidelberg: Springer. Als E-Book verfügbar.
[2] Jerald, Jason (2016). The VR Book: Human-Centered Design for Virtual Reality (Acm Books).
Morgan & Claypool Publishers-Acm.
[3] LaValle, Steven M. (2020). Virtual Reality. Als E-Book verfügbar unter http://lavalle.pl/vr/.
Abruf 13.07.2022.
[4] Schmalstieg, Dieter; Höllerer, Tobias (2016). Augmented Reality: Principles and Practice.
Boston: Addison-Wesley.
Augmented Reality (VR/AR): Grundlagen und Methoden der Virtuellen und Augmentierten
Realität. Berlin, Heidelberg: Springer. Als E-Book verfügbar.
[2] Jerald, Jason (2016). The VR Book: Human-Centered Design for Virtual Reality (Acm Books).
Morgan & Claypool Publishers-Acm.
[3] LaValle, Steven M. (2020). Virtual Reality. Als E-Book verfügbar unter http://lavalle.pl/vr/.
Abruf 13.07.2022.
[4] Schmalstieg, Dieter; Höllerer, Tobias (2016). Augmented Reality: Principles and Practice.
Boston: Addison-Wesley.
Grundlagen der Mensch-Computer-Interaktion- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10424
Duration (semester)
1
Learning outcomes/competences
Students can present and describe aspects of the psychology and physiology of human
information processing as they relate to interaction with user interfaces.
They can identify and explain the principles of interaction with user interfaces and specifications (standards,
guidelines, recommendations) for the design of user interfaces, and apply them to
the specification and development of user interfaces. Students can
identify and explain methods of user research and user interface evaluation, and
apply selected methods.
information processing as they relate to interaction with user interfaces.
They can identify and explain the principles of interaction with user interfaces and specifications (standards,
guidelines, recommendations) for the design of user interfaces, and apply them to
the specification and development of user interfaces. Students can
identify and explain methods of user research and user interface evaluation, and
apply selected methods.
Contents
• Introduction and Background of Human-Computer Interaction
• Examples of Current User Interfaces
• Methods of Human-Centered Design (User Experience Design, Usability Engineering)
• Fundamentals of the physiology and psychology of human information processing
• Standards, guidelines, and recommendations
• Forms of interaction
• Examples of Current User Interfaces
• Methods of Human-Centered Design (User Experience Design, Usability Engineering)
• Fundamentals of the physiology and psychology of human information processing
• Standards, guidelines, and recommendations
• Forms of interaction
Teaching methods
The lecture (V/SV) is conducted in a seminar-style format with the use of slides. In the practical sessions
, students work on assignments under the lecturer’s guidance and
discuss them to deepen their understanding of the material covered in the lectures.
Field trips may be organized to supplement the course.
Language: German
, students work on assignments under the lecturer’s guidance and
discuss them to deepen their understanding of the material covered in the lectures.
Field trips may be organized to supplement the course.
Language: German
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Interest in the design of intuitive interactive systems
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Interest in the design of intuitive interactive systems
Forms of examination
Course Exam: Fundamentals of Human-Computer Interaction:
Term Papers, Presentations, and Project-Based Assignments
Term Papers, Presentations, and Project-Based Assignments
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Dahm, Markus (2006). Grundlagen der Mensch-Computer-Interaktion.
München: Pearson Studium
[2] Preim, Bernhard; Dachselt, Raimund (2010). Interaktive Systeme. Band 1: Grundlagen,
Graphical User Interfaces, Informationsvisualisierung. 2. Auflage.
Berlin [u.a.]: Springer
[3] Richter, Michael; Flückiger, Markus (2016). Usability und UX kompakt.
Heidelberg: Springer
München: Pearson Studium
[2] Preim, Bernhard; Dachselt, Raimund (2010). Interaktive Systeme. Band 1: Grundlagen,
Graphical User Interfaces, Informationsvisualisierung. 2. Auflage.
Berlin [u.a.]: Springer
[3] Richter, Michael; Flückiger, Markus (2016). Usability und UX kompakt.
Heidelberg: Springer
IoT-Protokolle- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10435
Duration (semester)
1
Contents
IoT Systems and Protocols for Smart Home Systems and IP Voice/Data/Video Communication
• ISO/OSI Layer Model
• IP Protocols, Structure, and Characteristics
• Protocol Analysis
• Fundamental Properties of IP Transmission Channels
• IP Routing and Switching
• IoT Applications
• ISO/OSI Layer Model
• IP Protocols, Structure, and Characteristics
• Protocol Analysis
• Fundamental Properties of IP Transmission Channels
• IP Routing and Switching
• IoT Applications
Teaching methods
The lecture is designed to convey the theoretical material. In the exercises, students will explore the
theoretical material in greater depth
theoretical material in greater depth
Participation requirements
Formal requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Basic Practicum II.
Content requirements: none
full 30 ECTS credits from the first semester and the
Basic Practicum II.
Content requirements: none
Forms of examination
IoT Protocols Module Exam:
Written or oral exam
Written or oral exam
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 37(2) of the Program Examination Regulations (StgPO) for the
Bachelor’s study programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Bachelor’s study programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Mathematik Ergänzungen 1- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10406
Duration (semester)
1
Learning outcomes/competences
Students have deepened and expanded upon the knowledge they gained in the introductory courses Mathematics 1 and Mathematics
2.
They can apply the techniques and solution methods taught to technical and engineering
problems.
They are prepared for complex function theory in the master’s program.
2.
They can apply the techniques and solution methods taught to technical and engineering
problems.
They are prepared for complex function theory in the master’s program.
Contents
Series and Multidimensional Calculus
Teaching methods
A lecture course provides instruction in series and multidimensional differential calculus.
The presentation of the theoretical fundamentals is supported by numerous examples and exercises/review questions.
In the exercises, students work independently to solve problems.
The presentation of the theoretical fundamentals is supported by numerous examples and exercises/review questions.
In the exercises, students work independently to solve problems.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Knowledge of the module content:
Mathematics 2
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Knowledge of the module content:
Mathematics 2
Forms of examination
Module Exam in Mathematics, Supplement 1:
Written Exam (60 min.)
Written Exam (60 min.)
Requirements for the awarding of credit points
Module examination must be passed
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Papula, Lothar
Mathematik für Ingenieure und Naturwissenschaftler
[2] Brauch/Dreyer/Haacke
Mathematik für Ingenieure
[3] Burg/Haf/Wille
Höhere Mathematik für Ingenieure
Mathematik für Ingenieure und Naturwissenschaftler
[2] Brauch/Dreyer/Haacke
Mathematik für Ingenieure
[3] Burg/Haf/Wille
Höhere Mathematik für Ingenieure
Mathematik Ergänzungen 2- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10412
Duration (semester)
1
Learning outcomes/competences
Students have deepened and expanded upon the knowledge they gained in the introductory courses Mathematics 1 and Mathematics
2.
They can apply the techniques and solution methods taught to technical and engineering
problems.
They are prepared for complex function theory in the master’s program
2.
They can apply the techniques and solution methods taught to technical and engineering
problems.
They are prepared for complex function theory in the master’s program
Contents
Multidimensional Integral Calculus
Teaching methods
A lecture course provides instruction in multidimensional integral calculus. The teaching of the
theoretical foundations is supported by numerous examples and exercises/review questions.
In the exercises, students work independently to solve problems.
theoretical foundations is supported by numerous examples and exercises/review questions.
In the exercises, students work independently to solve problems.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Knowledge of the module content:
Mathematics 2
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Knowledge of the module content:
Mathematics 2
Forms of examination
Mathematics Module Exam, Supplement 2:
Written Exam (60 min.)
Written Exam (60 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Papula, Lothar
Mathematik für Ingenieure und Naturwissenschaftler
[2] Brauch/Dreyer/Haacke
Mathematik für Ingenieure
[3] Burg/Haf/Wille
Höhere Mathematik für Ingenieure
Mathematik für Ingenieure und Naturwissenschaftler
[2] Brauch/Dreyer/Haacke
Mathematik für Ingenieure
[3] Burg/Haf/Wille
Höhere Mathematik für Ingenieure
Medizinische Signalverarbeitung- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10403
Duration (semester)
1
Neurophysiologie 2- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10409
Duration (semester)
1
RMS anerk.- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
RMS
Duration (semester)
1
RMS anerk.- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
RMS
Duration (semester)
1
Regulatorische Grundlagen für Medizinprodukte - Teil I - WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10437
Duration (semester)
1
Learning outcomes/competences
Students are familiar with the European regulatory framework for medical devices and
can relate it to non-European markets. They can identify the roles and
responsibilities of economic operators active in the medical device sector. They are familiar
with the roles of the authorities operating within the regulatory framework. They can apply international
standards—particularly for active medical devices—with regard to safety and performance
can relate it to non-European markets. They can identify the roles and
responsibilities of economic operators active in the medical device sector. They are familiar
with the roles of the authorities operating within the regulatory framework. They can apply international
standards—particularly for active medical devices—with regard to safety and performance
Contents
• Regulatory frameworks for medical devices in Europe (MDR, IVDR, national
regulations, standards) and worldwide (U.S., Asia)
• Responsibilities and obligations of manufacturers, European Authorized Representatives, importers,
distributors, and operators of medical devices
• Responsibilities of market surveillance authorities, ZLG, and BfArM in the context of safe medical devices
• Application of the DIN EN 60601 series of standards for medical electrical equipment using specific
examples
• Suitability for use and usability in the development of medical devices
regulations, standards) and worldwide (U.S., Asia)
• Responsibilities and obligations of manufacturers, European Authorized Representatives, importers,
distributors, and operators of medical devices
• Responsibilities of market surveillance authorities, ZLG, and BfArM in the context of safe medical devices
• Application of the DIN EN 60601 series of standards for medical electrical equipment using specific
examples
• Suitability for use and usability in the development of medical devices
Teaching methods
The lecture is designed to convey theoretical concepts, which are then explored in greater depth and applied in the exercises using specific
examples.
examples.
Participation requirements
Formal Requirements: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content Requirements: Knowledge of the module content:
o Physiology & Anatomy
o Biochemistry
o Cardiovascular System
o Computer Science 1–3
o Sensors & Measurement Technology
o Physics 1 + 2
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content Requirements: Knowledge of the module content:
o Physiology & Anatomy
o Biochemistry
o Cardiovascular System
o Computer Science 1–3
o Sensors & Measurement Technology
o Physics 1 + 2
Forms of examination
Module Exam: Regulatory Fundamentals 1:
Thesis
Thesis
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering and Biomedical Engineering with a practical/study abroad semester),
Information Technology and Information Technology with a practical/study abroad semester
Information Technology and Information Technology with a practical/study abroad semester
Literature
[3] Anja Rämisch, C. R. (Januar 2022). Risikomanagement und Biologische Sicherheit von
Medizinprodukten. Beuth Verlag.
[4] Dorte Kiecksee, E. S. (September 2015). Professionelles Risikomanagement von
Medizinprodukten. Beuth Verlag GmbH.
[5] Handorn, B. (Februar 2021). Die Medizinprodukte-Verordnung (EU) 2017/745. Beuth Verlag
GmbH.
[6] Kirchberg, D. (Mai 2022). Medizinprodukte sicher anwenden und betreiben. Schlütersche
Verlag.
[7] Monika Krauß-Lauth, P. R.-P. (August 2021). Klinische Prüfung von Medizinprodukten. Beuth
Verlag GmbH.
[8] Stender, R. (März 2019). Qualitätsmanagement für Hersteller von Medizinprodukten. Beuth
Verlag GmbH.
Medizinprodukten. Beuth Verlag.
[4] Dorte Kiecksee, E. S. (September 2015). Professionelles Risikomanagement von
Medizinprodukten. Beuth Verlag GmbH.
[5] Handorn, B. (Februar 2021). Die Medizinprodukte-Verordnung (EU) 2017/745. Beuth Verlag
GmbH.
[6] Kirchberg, D. (Mai 2022). Medizinprodukte sicher anwenden und betreiben. Schlütersche
Verlag.
[7] Monika Krauß-Lauth, P. R.-P. (August 2021). Klinische Prüfung von Medizinprodukten. Beuth
Verlag GmbH.
[8] Stender, R. (März 2019). Qualitätsmanagement für Hersteller von Medizinprodukten. Beuth
Verlag GmbH.
Regulatorische Grundlagen für Medizinprodukte - Teil II- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10438
Duration (semester)
1
Learning outcomes/competences
Students are familiar with the regulatory framework for digital health applications. They can outline the development process of a medical app and describe the
lifecycle of a medical app in healthcare. They have learned to use appropriate methods to overcome the
technical challenges involved in moving from a specific medical problem to
the finished product.
lifecycle of a medical app in healthcare. They have learned to use appropriate methods to overcome the
technical challenges involved in moving from a specific medical problem to
the finished product.
Contents
• Regulatory framework for digital health applications and medical apps
(MDR, MPDG, SGB V, DiGAV)
• Fundamentals of project and quality management in product development
• Frameworks for DiGA development
• Demonstrating efficacy and positive healthcare outcomes through clinical trials
• Post-market surveillance
• Independent development of a DiGA using a specific example
(MDR, MPDG, SGB V, DiGAV)
• Fundamentals of project and quality management in product development
• Frameworks for DiGA development
• Demonstrating efficacy and positive healthcare outcomes through clinical trials
• Post-market surveillance
• Independent development of a DiGA using a specific example
Teaching methods
The lecture is designed to convey theoretical concepts that will be applied during the practicum portion of the course
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Knowledge of the module content:
o Regulatory Fundamentals 1
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content: Knowledge of the module content:
o Regulatory Fundamentals 1
Forms of examination
Module Exam: Regulatory Fundamentals 2:
Thesis
Thesis
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering and Biomedical Engineering with a practical/study abroad semester),
Information Technology and Information Technology with a Practical/Study Abroad Semester
Information Technology and Information Technology with a Practical/Study Abroad Semester
Literature
[9] Davies, A., & Mueller, J. (2020). Developing Medical Apps and mHealth Interventions. Springer
International Publishing.
[10] Hagen, J., Brönneke, J. B., Matthies, H., Debatin, J. F., Kircher, P. (Oktober 2020). DiGA
VADEMECUM. MWV Medizinisch Wissenschaftliche Verlagsgesellschaft.
[11] Johner, C., Wittorf, S., Hölzer-Klüpfel, M. (Oktober 2020). Basiswissen Medizinische
Software. dpunkt.verlag.
International Publishing.
[10] Hagen, J., Brönneke, J. B., Matthies, H., Debatin, J. F., Kircher, P. (Oktober 2020). DiGA
VADEMECUM. MWV Medizinisch Wissenschaftliche Verlagsgesellschaft.
[11] Johner, C., Wittorf, S., Hölzer-Klüpfel, M. (Oktober 2020). Basiswissen Medizinische
Software. dpunkt.verlag.
Robotik 1- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10442
Duration (semester)
1
Learning outcomes/competences
Students are able to…
• identify basic types of robots and their components, such as actuators, sensors, effectors
, and control units, as well as how they interact
• identify the hazards posed by autonomous systems and the necessary safety and protective measures
• establish mathematical relationships to describe robot forward kinematics
and apply methods for calculating positions and orientations in
various coordinate systems
• Use robot software tools to
program
fixed motion sequences for a robot
• Solve practical
robotics tasks (e.g., “pick and place”) using tools such as MATLAB/Simulink or other toolboxes
• identify basic types of robots and their components, such as actuators, sensors, effectors
, and control units, as well as how they interact
• identify the hazards posed by autonomous systems and the necessary safety and protective measures
• establish mathematical relationships to describe robot forward kinematics
and apply methods for calculating positions and orientations in
various coordinate systems
• Use robot software tools to
program
fixed motion sequences for a robot
• Solve practical
robotics tasks (e.g., “pick and place”) using tools such as MATLAB/Simulink or other toolboxes
Contents
• Introduction to Robotics (types of robots and typical tasks, safety considerations)
• Mathematical Fundamentals (coordinate systems, positions, and orientations in 2D and 3D space)
• Forward kinematics of articulated-arm robots
• Use of software tools (simulation and programming of robot systems)
• Hands-on work with real-world application examples (use cases)
• Mathematical Fundamentals (coordinate systems, positions, and orientations in 2D and 3D space)
• Forward kinematics of articulated-arm robots
• Use of software tools (simulation and programming of robot systems)
• Hands-on work with real-world application examples (use cases)
Teaching methods
The seminar-style course is designed to convey theoretical content. In the exercises and practical sessions, students deepen their understanding of and practice applying the theoretical material through a variety of assignments. Practical examples help students internalize the course material.
Language
- Course: In-person: German/English; slides in English
- Exam: German
- Reading list: English
Language
- Course: In-person: German/English; slides in English
- Exam: German
- Reading list: English
Participation requirements
At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to the Robotics 1 module exam or the Introduction to Robotics module exam must be denied if the other module or submodule has already been passed.
Content:
Knowledge of the module content:
• Mathematics 1 and 2
• Practical Fundamentals 2
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Admission to the Robotics 1 module exam or the Introduction to Robotics module exam must be denied if the other module or submodule has already been passed.
Content:
Knowledge of the module content:
• Mathematics 1 and 2
• Practical Fundamentals 2
Forms of examination
Robotics 1 Module Exam:
• Practical problem-solving in teams
• Presentation on the practical problem-solving exercise, including an overview of the
underlying theoretical concepts and the results
• Oral exam
Participation in the practical component of the seminar-style course (robotics lab)
is part of the module exam.
• Practical problem-solving in teams
• Presentation on the practical problem-solving exercise, including an overview of the
underlying theoretical concepts and the results
• Oral exam
Participation in the practical component of the seminar-style course (robotics lab)
is part of the module exam.
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Corke: Robotics, Vision and Control, Springer
[2] Papula: Mathematik für Ingenieure und Naturwissenschaftler, Bd. 1+2, Vieweg
[3] Hoffman: MATLAB und SIMULINK, Addison-Wesley
[2] Papula: Mathematik für Ingenieure und Naturwissenschaftler, Bd. 1+2, Vieweg
[3] Hoffman: MATLAB und SIMULINK, Addison-Wesley
Robotik 2- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10443
Duration (semester)
1
Learning outcomes/competences
Students will be able to…
• identify the different types and characteristics of mobile robots
• describe the basic operating principles of various sensors that mobile robots use to
perceive their environment and determine their own 3D orientation and position as well as the location
of other objects in space
• explain the characteristics and fields of application of UAVs (Unmanned Aerial Vehicles)—
particularly drones and quadcopters—
• explain the relationship between the control of a quadcopter’s four rotors and
its altitude, orientation, and position
• Use unit quaternions for the mathematical representation of 3D orientation as well as for
applying rotational transformations
• mathematically process the sensor data of a quadcopter (3D acceleration, 3D gyroscope, ultrasonic data
etc.), using MATLAB/Simulink and the Robotics Toolbox to mathematically
process this data in such a way that it can, among other things, determine the quadcopter’s pose and velocity
• identify the different types and characteristics of mobile robots
• describe the basic operating principles of various sensors that mobile robots use to
perceive their environment and determine their own 3D orientation and position as well as the location
of other objects in space
• explain the characteristics and fields of application of UAVs (Unmanned Aerial Vehicles)—
particularly drones and quadcopters—
• explain the relationship between the control of a quadcopter’s four rotors and
its altitude, orientation, and position
• Use unit quaternions for the mathematical representation of 3D orientation as well as for
applying rotational transformations
• mathematically process the sensor data of a quadcopter (3D acceleration, 3D gyroscope, ultrasonic data
etc.), using MATLAB/Simulink and the Robotics Toolbox to mathematically
process this data in such a way that it can, among other things, determine the quadcopter’s pose and velocity
Contents
• Introduction to Mobile Robotics:
o Definition of mobile robots, classification, and application examples
o Overview of: proximity sensors (infrared, ultrasonic, LIDAR), optical
sensors (stereo vision, optical flow, depth camera), GPS, inertial sensors
(accelerometer and gyroscope)
o Application areas for drones
• Controlling the pose of a drone or quadcopter (rotor control to
adjust the thrust, roll, pitch, and yaw parameters)
• 3D orientation representation using unit quaternions
• 3D orientation and position determination using 3D acceleration and gyro data
• Use of software tools (simulation and programming of robotic systems)
• Practical work with real-world application examples (use cases)
o Definition of mobile robots, classification, and application examples
o Overview of: proximity sensors (infrared, ultrasonic, LIDAR), optical
sensors (stereo vision, optical flow, depth camera), GPS, inertial sensors
(accelerometer and gyroscope)
o Application areas for drones
• Controlling the pose of a drone or quadcopter (rotor control to
adjust the thrust, roll, pitch, and yaw parameters)
• 3D orientation representation using unit quaternions
• 3D orientation and position determination using 3D acceleration and gyro data
• Use of software tools (simulation and programming of robotic systems)
• Practical work with real-world application examples (use cases)
Teaching methods
The seminar course is designed to teach theoretical concepts. In the
exercises, students reinforce the theoretical material through a variety of tasks. In the
practical portion of the course, students independently collect real-world data from a drone. This gives them the opportunity to apply the sensor data processing techniques they have learned
to assess the drone’s status using real data and to evaluate the resulting
output data.
Language
— Course: In-person sessions: German, slides in English; e-learning:
English
— Exam: German
— Reading list: English and German
exercises, students reinforce the theoretical material through a variety of tasks. In the
practical portion of the course, students independently collect real-world data from a drone. This gives them the opportunity to apply the sensor data processing techniques they have learned
to assess the drone’s status using real data and to evaluate the resulting
output data.
Language
— Course: In-person sessions: German, slides in English; e-learning:
English
— Exam: German
— Reading list: English and German
Participation requirements
Formal:
At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content:
Knowledge of the module content:
• Mathematics 1 and 2
• Practical Fundamentals 2
• Robotics 1 or Introduction to Robotics
At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester and the
Practical Fundamentals 2 course.
Content:
Knowledge of the module content:
• Mathematics 1 and 2
• Practical Fundamentals 2
• Robotics 1 or Introduction to Robotics
Forms of examination
Robotics 2 Module Exam:
• Practical problem-solving in teams
• Presentation on the practical problem-solving task, including an overview of the
underlying theoretical concepts and a presentation of the results
• Oral exam
Participation in the practical component of the seminar course (robotics lab)
is a prerequisite for taking the module exam.
• Practical problem-solving in teams
• Presentation on the practical problem-solving task, including an overview of the
underlying theoretical concepts and a presentation of the results
• Oral exam
Participation in the practical component of the seminar course (robotics lab)
is a prerequisite for taking the module exam.
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
3/136 x 80% (in accordance with Subsection 36 of the Program Examination Regulations (StgPO) for the bachelor’s degree programs in Biomedical Engineering, Biomedical Engineering with a practical/study abroad semester,
Information Technology, and Information Technology with a practical or study abroad semester)
Information Technology, and Information Technology with a practical or study abroad semester)
Literature
[1] Corke: Robotics, Vision and Control, Springer
[2] Herzberg: Mobile Roboter, Springer
[3] Papula: Mathematik für Ingenieure und Naturwissenschaftler, Bd. 1+2, Vieweg
[4] Hoffman: MATLAB und SIMULINK, Addison-Wesley
[2] Herzberg: Mobile Roboter, Springer
[3] Papula: Mathematik für Ingenieure und Naturwissenschaftler, Bd. 1+2, Vieweg
[4] Hoffman: MATLAB und SIMULINK, Addison-Wesley
Sensorik- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10411
Duration (semester)
1
Softwareentwicklung robotischer Systeme mit ROS - WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10444
Duration (semester)
1
Systembiologie 1: biologische Netzwerke- WP
- 2 SWS
- 3 ECTS
- WP
- 2 SWS
- 3 ECTS
Number
10426
Duration (semester)
1
5. Semester of study
Fachpraktikum 2 Informationstechnik- PF
- 5 SWS
- 5 ECTS
- PF
- 5 SWS
- 5 ECTS
Number
10350
Duration (semester)
1
Projektorientiertes Arbeiten 1- PF
- 4 SWS
- 4 ECTS
- PF
- 4 SWS
- 4 ECTS
Number
10340
Duration (semester)
1
Seminar Informationstechnik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
10300
Duration (semester)
1
Learning outcomes/competences
Key Competencies: After receiving a general introduction to a
subject-specific topic, students can explain its most important concepts. Furthermore, they can identify the fundamentals of
scientific work. They can identify the most important findings on a topic
and summarize them in writing as part of a research paper. Students are
able to present their newly acquired knowledge in a concise and clear manner through a presentation
. They can answer questions from the audience in a targeted and accurate manner based on the knowledge they have gained.
Students can explain various presentation techniques, apply them, and
in this way present the knowledge they have acquired to an interested audience in a clear and
understandable manner.
subject-specific topic, students can explain its most important concepts. Furthermore, they can identify the fundamentals of
scientific work. They can identify the most important findings on a topic
and summarize them in writing as part of a research paper. Students are
able to present their newly acquired knowledge in a concise and clear manner through a presentation
. They can answer questions from the audience in a targeted and accurate manner based on the knowledge they have gained.
Students can explain various presentation techniques, apply them, and
in this way present the knowledge they have acquired to an interested audience in a clear and
understandable manner.
Contents
This seminar covers the fundamentals of academic work, literature and
source research and evaluation, information processing, academic
expression in both spoken and written form, as well as the design and delivery of presentations.
The seminar covers subject-specific topics in information technology, with
a focus on digital technologies, the Internet of Things, smart mobility,
and robotics. The topics represent current extensions of the specialized lectures and are
assigned to students individually. The results of the students’ work are presented, and the
understanding they have gained is critically examined. In addition, the knowledge acquired must be documented in a
written report. Through the written report and the
presentation, key skills in written and oral communication are
practiced and developed.
source research and evaluation, information processing, academic
expression in both spoken and written form, as well as the design and delivery of presentations.
The seminar covers subject-specific topics in information technology, with
a focus on digital technologies, the Internet of Things, smart mobility,
and robotics. The topics represent current extensions of the specialized lectures and are
assigned to students individually. The results of the students’ work are presented, and the
understanding they have gained is critically examined. In addition, the knowledge acquired must be documented in a
written report. Through the written report and the
presentation, key skills in written and oral communication are
practiced and developed.
Teaching methods
Seminar-style introduction to the subject areas, guidance, and support during the
writing phase.
writing phase.
Participation requirements
Formal: At least 45 ECTS credits must be earned. These must include the
full 30 ECTS credits from the first semester.
Content-related: none
full 30 ECTS credits from the first semester.
Content-related: none
Forms of examination
Module Exam for the Information Technology Seminar:
Term Paper and Presentation (45 min.)
Term Paper and Presentation (45 min.)
Requirements for the awarding of credit points
The module exam must be passed.
Importance of the grade for the final grade
5/136 x 80% (in accordance with Subsection 36 of the Degree Program Examination Regulations (StgPO) for the bachelor’s degree programs in Information Technology and Information Technology with a practical or study abroad semester)
Web Protokolle und Services- PF
- 4 SWS
- 10 ECTS
- PF
- 4 SWS
- 10 ECTS
Number
10321
Duration (semester)
1
6. Semester of study
Bachelor Arbeit und Abschluss-Kolloquium- PF
- 4 SWS
- 15 ECTS
- PF
- 4 SWS
- 15 ECTS
Number
101
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
After successfully completing the module, students will be able to:
Knowledge and understanding:
Knowledge and understanding:
- Name and understand elementary mathematical principles, in particular with regard to the calculation of limits and the derivation and integration of functions.
- Know the properties of important, elementary functions (exponential, logarithmic and trigonometric functions).
- Know how to solve mathematically indeterminate expressions.
- Understand the problems involved in differentiating and integrating products, quotients and compositions and know appropriate derivation rules and integration methods.
- Be able to approximate boundary values for mathematically indeterminate expressions.
- To apply the derivative and integration methods practically and confidently.
- Solve business management problems (e.g. extreme points of cost functions) by calculating the corresponding mathematical models (e.g. differentiating functions).
- To create Taylor polynomials as approximate solutions for functions that are difficult to calculate and to determine their error and convergence interval.
- Graphically model payment series of elementary financial mathematical problems and apply their underlying formulas for calculation.
- Use mathematical terminology correctly in a problem-solving context.
- Analyze business problems in a team, discuss their mathematical modeling and jointly determine a solution.
- Understanding the importance of mathematics for solving business problems and being able to apply it confidently.
Contents
- General basics (sets, operations, complete induction)
- Consequences and series (definition, calculation rules, limits, convergence)
- Functions (definition, composition, calculation rules, continuity, limits)
- Differential calculus (differential quotient, calculation rules, derivatives of special functions, determining local extrema, de l'Hospital's rules)
- Integral calculus (partial integration, partial fraction decomposition, substitution)
- Taylor and power series (Taylor polynomials, residual element estimation, radius of convergence)
- Elementary basics of financial mathematics (compounding and discounting, discounting sum and capital recovery factor, terminal value and residual value distribution factor)
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- exercise accompanying the lecture
- active and self-directed learning through exercises, sample solutions and internet-supported accompanying materials
- immediate feedback and success monitoring
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
The module examination consists of a written exam in which students are required to recall the content taught in the lecture and its practical application in the exercises and demonstrate this by solving analogous tasks. In addition to the exercise sheets, a comprehensive collection of older exams and sample solutions as well as (if time permits) the discussion of a mock exam serve as preparation.
Duration: 120 minutes
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
Bachelor's degree in Business Informatics (both 6 and 7 semesters with practical semester)
Literature
- Vorlesungsskript "Mathematik für Wirtschaftinformatik 1" (Hesseler, M.)
Ergänzende Literatur (optional, nicht zwingend erforderlich):
- Schwarze, J.; Mathematik für Wirtschaftswissenschaftler , Band 0, 1 + 2, 11. Auflage, Verlag Neue Wirtschafts-Briefe GmbH, Herne/Berlin, 2000
- Neunzert, H, u.a..; Analysis 1, Ein Lehr- und Arbeitsbuch für Studienanfänger , 3. Auflage, Springer-Verlag, Berlin u.a. 1996
- Hoffmann, S.; Mathematische Grundlagen für Betriebswirte, mit Fragen und Antworten, Aufgaben und Lösungen , 6. überarbeitete Auflage, Verlag Neue Wirtschafts-Briefe GmbH, Herne/Berlin, 2002
- Thomas, G. B., Weir, M. D., Hass, J.; "Basisbuch Analysis", 12., aktualisierte Auflage, Pearson Deutschland GmbH, München, 2013
Projektorientiertes Arbeiten 2- PF
- 4 SWS
- 15 ECTS
- PF
- 4 SWS
- 15 ECTS
Number
10380
Duration (semester)
1