Suchergebnis: Katalogdaten im Frühjahrssemester 2021

Rechnergestützte Wissenschaften Bachelor Information
Für alle Studienreglemente
Vertiefungsgebiete
Geophysik
Empfohlene Kombinationen:
Fach 1 + Fach 2
Fach 1 + Fach 3
Fach 2 + Fach 3
Fach 3 + Fach 4
Fach 5 + Fach 6 + Fach 8
Fach 4 + Fach 5
Fach 7 + Fach 8
Geophysik: Fach 8
findet im Herbstsemester statt
Biologie
NummerTitelTypECTSUmfangDozierende
636-0702-00LStatistical Models in Computational BiologyW6 KP2V + 1U + 2AN. Beerenwinkel
KurzbeschreibungThe course offers an introduction to graphical models and their application to complex biological systems. Graphical models combine a statistical methodology with efficient algorithms for inference in settings of high dimension and uncertainty. The unifying graphical model framework is developed and used to examine several classical and topical computational biology methods.
LernzielThe goal of this course is to establish the common language of graphical models for applications in computational biology and to see this methodology at work for several real-world data sets.
InhaltGraphical models are a marriage between probability theory and graph theory. They combine the notion of probabilities with efficient algorithms for inference among many random variables. Graphical models play an important role in computational biology, because they explicitly address two features that are inherent to biological systems: complexity and uncertainty. We will develop the basic theory and the common underlying formalism of graphical models and discuss several computational biology applications. Topics covered include conditional independence, Bayesian networks, Markov random fields, Gaussian graphical models, EM algorithm, junction tree algorithm, model selection, Dirichlet process mixture, causality, the pair hidden Markov model for sequence alignment, probabilistic phylogenetic models, phylo-HMMs, microarray experiments and gene regulatory networks, protein interaction networks, learning from perturbation experiments, time series data and dynamic Bayesian networks. Some of the biological applications will be explored in small data analysis problems as part of the exercises.
Skriptno
Literatur- Airoldi EM (2007) Getting started in probabilistic graphical models. PLoS Comput Biol 3(12): e252. doi:10.1371/journal.pcbi.0030252
- Bishop CM. Pattern Recognition and Machine Learning. Springer, 2007.
- Durbin R, Eddy S, Krogh A, Mitchinson G. Biological Sequence Analysis. Cambridge university Press, 2004
Wahlfächer
Von den angebotenen Wahlfächern müssen mindestens zwei Lerneinheiten erfolgreich abgeschlossen werden.
NummerTitelTypECTSUmfangDozierende
151-3202-00LProduct Development and Engineering Design Belegung eingeschränkt - Details anzeigen
Number of participants limited to 60.
W4 KP2GK. Shea, T. Stankovic
KurzbeschreibungThe course introduces students to the product development process. In a team, you will explore the early phases of conceptual development and product design, from ideation and concept generation through to hands-on prototyping. This is an opportunity to gain product development experience and improve your skills in prototyping and presenting your product ideas. The project topic changes each year.
LernzielThe course introduces you to the product development process and methods in engineering design for: product planning, user-centered design, creating product specifications, ideation including concept generation and selection methods, material selection methods and prototyping. Further topics include design for manufacture and design for additive manufacture. You will actively apply the process and methods learned throughout the semester in a team on a product development project including prototyping.
InhaltWeekly topics accompanying the product development project include:
1 Introduction to Product Development and Engineering Design
2 Product Planning and Social-Economic-Technology (SET) Factors
3 User-Centered Design and Product Specifications
4 Concept Generation and Selection Methods
5 System Design and Embodiment Design
6 Prototyping and Prototype Planning
7 Material Selection in Engineering Design
8 Design for Manufacture and Design for Additive Manufacture
Skriptavailable on Moodle
LiteraturUlrich, Eppinger, and Yang, Product Design and Development. 7th ed., McGraw-Hill Education, 2020.

Cagan and Vogel, Creating Breakthrough Products: Revealing the Secrets that Drive Global Innovation, 2nd Edition, Pearson Education, 2013.
Voraussetzungen / BesonderesAlthough the course is offered to ME (BSc and MSc) and CS (BSc and MSc) students, priority will be given to ME BSc students in the Focus Design, Mechanics, and Materials if the course is full.
151-0840-00LOptimization and Machine Learning
Note: previous course title until FS20 "Principles of FEM-Based Optimization and Robustness Analysis".
W4 KP2V + 2UB. Berisha, D. Mohr
KurzbeschreibungThe course teaches the basics of nonlinear optimization and concepts of machine learning. An introduction to the finite element method allows an extension of the application area to real engineering problems such as structural optimization and modeling of material behavior on different length scales.
LernzielStudents will learn mathematical optimization methods including gradient based and gradient free methods as well as established algorithms in the context of machine learning to solve real engineering problems, which are generally non-linear in nature. Strategies to ensure efficient training of machine learning models based on large data sets define another teaching goal of the course.

Optimization tools (MATLAB, LS-Opt, Python) and the finite element program ABAQUS are presented to solve both general and real engineering problems.
Inhalt- Introduction into Nonlinear Optimization
- Design of Experiments DoE
- Introduction into Nonlinear Finite Element Analysis
- Optimization based on Meta Modeling Techniques
- Shape and Topology Optimization
- Robustness and Sensitivity Analysis
- Fundamentals of Machine Learning
- Generalized methods for regression and classification, Neural Networks, Support Vector machines
- Supervised and unsupervised learning
SkriptLecture slides and literature
151-0206-00LEnergy Systems and Power EngineeringW4 KP2V + 2UR. S. Abhari, A. Steinfeld
KurzbeschreibungIntroductory first course for the specialization in ENERGY. The course provides an overall view of the energy field and pertinent global problems, reviews some of the thermodynamic basics in energy conversion, and presents the state-of-the-art technology for power generation and fuel processing.
LernzielIntroductory first course for the specialization in ENERGY. The course provides an overall view of the energy field and pertinent global problems, reviews some of the thermodynamic basics in energy conversion, and presents the state-of-the-art technology for power generation and fuel processing.
InhaltWorld primary energy resources and use: fossil fuels, renewable energies, nuclear energy; present situation, trends, and future developments. Sustainable energy system and environmental impact of energy conversion and use: energy, economy and society. Electric power and the electricity economy worldwide and in Switzerland; production, consumption, alternatives. The electric power distribution system. Renewable energy and power: available techniques and their potential. Cost of electricity. Conventional power plants and their cycles; state-of-the-art and advanced cycles. Combined cycles and cogeneration; environmental benefits. Solar thermal; concentrated solar power; solar photovoltaics. Fuel cells: characteristics, fuel reforming and combined cycles.
SkriptVorlesungsunterlagen werden verteilt
151-0306-00LVisualization, Simulation and Interaction - Virtual Reality I Information W4 KP4GA. Kunz
KurzbeschreibungTechnologie der virtuellen Realität. Menschliche Faktoren, Erzeugung virtueller Welten, Beleuchtungsmodelle, Display- und Beschallungssysteme, Tracking, haptische/taktile Interaktion, Motion Platforms, virtuelle Prototypen, Datenaustausch, VR-Komplettsysteme, Augmented Reality; Kollaborationssysteme; VR und Design; Umsetzung der VR in der Industrie; Human COmputer Interfaces (HCI).
LernzielDie Studierenden erhalten einen Überblick über die virtuelle Realität, sowohl aus technischer als auch aus informationstechnologischer Sicht. Sie lernen unterschiedliche Software- und Hardwareelemente kennen sowie deren Einsatzmöglichkeiten im Geschäftsprozess. Die Studierenden entwickeln eine Kenntnis darüber, wo sich heute die virtuelle Realität nutzbringend einsetzen lässt und wo noch weiterer Forschungsbedarf besteht. Anhand konkreter Programme und Systeme erfahren die Teilnehmer den Umgang mit den erlernten neuen Technologien.
Studierende sind in der Lage:
• gängige VR-Technologien zu evaluieren und die geeignetste für eine gegebene Aufgabe auszuwählen bezüglich der folgenden Gesichtspunkte:
o Visualisierungsmöglichkeiten: Monitore, Projektionssysteme, Datenbrillen
o Positionserfassungssystemen (optisch/elektromagnetisch/mechanisch)
o Interaktionstechnologien: Datenhandschuhe, Möglichkeit des echten Laufens/Erfassung der Augenbewegung/manuelle Interaktion, usw.
• eine VR-Anwendung selbstständig zu entwickeln,
• die VR-Technologie auf industrielle Anforderungen anzuwenden,
• das erlernte Wissen in einer praktischen Anwendung zu vertiefen.
• grundlegende Unterschiede in Anwendung digitaler Welten zu vergleichen (VR/AR/MR/XR)
InhaltDiese Vorlesung gibt eine Einführung in die Technologie der virtuellen Realität als neues Tool zur Bewältigung komplexer Geschäftsprozesse. Es sind die folgenden Themen vorgesehen: Einführung und Geschichte der VR; Eingliederung der VR in die Produktentwicklung; Nutzen von VR für die Industrie; menschliche Faktoren als Grundlage der virtuellen Realität; Einführung in die Erzeugung (Modellierung) virtueller Welten; Beleuchtungsmodelle; Kollisionserkennung; Displaysysteme; Projektionssysteme; Beschallungssysteme; Trackingssysteme; Interaktionsgeräte für die virtuelle Umgebung; haptische und taktile Interaktion; Motion Platforms; Datenhandschuh; physikalisch basierte Simulation; virtuelle Prototypen; Datenaustausch und Datenkommunikation; VR-Komplettsysteme; Augmented Reality; Kollaborationssysteme; VR zur Unterstützung von Designaufgaben; Umsetzung der VR in der Industrie; Ausblick in die laufende Forschung im Bereich VR.

Lehrmodule:
- Geschichte der VR und Definition der wichtigsten Begriffe
- Einordnung der VR in Geschäftsprozesse
- Die Erzeugung virtueller Welten
- Geräte und Technologien für die immersive virtuelle Realität
- Anwendungen der VR in unterschiedlichsten Gebieten
SkriptDie Durchführung der Lehrveranstaltung erfolgt gemischt mit Vorlesungs- und Übungsanteilen.
Die Vorlesung kann auf Wunsch in Englisch erfolgen. Das Skript ist ebenfalls in Englisch verfügbar.
Skript, Handout; Kosten SFr.30.-
Voraussetzungen / BesonderesVoraussetzungen:
keine
Vorlesung geeignet für D-MAVT, D-ITET, D-MTEC und D-INF

Testat/ Kredit-Bedingungen/ Prüfung:
– Teilnahme an Vorlesung und Kolloquien
– Erfolgreiche Durchführung von Übungen in Teams
– Mündliche Einzelprüfung 30 Minuten
151-0314-00LInformationstechnologien im digitalen ProduktW4 KP3GE. Zwicker, R. Montau
KurzbeschreibungZielsetzung, Konzepte und Methoden der Digitalisierung, Digitales Produkt und Product Lifecycle Management (PLM), Industrie 4.0
Digitalisierungskonzepte: Produktstrukturen, Prozessoptimierung mit digitalen Modellen in Verkauf, Produktion, Service, Digital Twin versus Digital Thread
PLM-Grundlagen: Objekte, Strukturen, Prozesse, Integrationen, Visualisierung
Praktische Anwendungen
LernzielStudierenden lernen die Grundlagen und Konzepte der Digitalisierung im Produktlebenszylus auf Basis von Produkt Lifecycle Management-Technologien (PLM), den Einsatz von Datenbanken, die Integration von CAx-Systemen und Visualisierung/AR, den Aufbau computergestützter Kollaboration auf Basis von Standards und Protokollen sowie das Varianten- und Konfigurationsmanagement zur effizienten Nutzung des Digitalen Produkt-Ansatzes für Industrie 4.0.
InhaltMöglichkeiten und Potenziale moderner IT-Applikationen mit Fokus auf PLM- und CAx--Technologien für den zielgerichteten Einsatz im Zusammenhang Produktplattform - Unternehmensprozesse - IT-Tools. Einführung in die Konzepte des Product Lifecycle Managements (PLM): Informationsmodellierung, Datenmanagement, Revisionierung, Nutzung und Verteilung von Produktdaten. Aufbau und Funktionsweise von PLM-Systemen. Integration neuer IT-Technologien in Unternehmensprozesse. Möglichkeiten der Publikation und automatischen Konfiguration von Produktvarianten im Internet. Einsatz modernster Informations- und Kommunikationstechnologien beim Entwickeln von Produkten an global verteilten Standorten. Schnittstellen der rechnerintegrierten Produktentwicklung. Auswahl, Projektierung, Anpassung und Einführung von PLM-Systemen. Beispiele und Fallstudien für den industriellen Einsatz moderner Informationstechnologien.

Lehrmodule:
- Einführung in die Digitalisierung (Digitales Produkt, PLM)
- Datenbanktechnologie (Basis der Digitalisierung)
- Objektmanagement
- Objektklassifikation
- Objektidentifikation mit Sachnummernsystem
- CAx/PLM-Integration mit Visualisierung/AR
- Workflow & Change Management
- Schnittstellen im Digitalen Produkt
- Enterprise Application Integration (EAI)
SkriptDidaktisches Konzept/Lehrmaterialien:
Die Durchführung der Lehrveranstaltung erfolgt gemischt mit Vorlesungs- und Übungsanteilen anhand von Praxisbeispielen.
Bereitstellung von Vorlesungs-Handouts und Skriptum digital in Moodle.
Voraussetzungen / BesonderesVoraussetzungen: Keine
Empfohlen: Fokus-Projekt, Interesse an Digitalisierung
Vorlesung geeignet für D-MAVT, D-MTEC, D-ITET und D-INFK

Testat/Kredit-Bedingungen / Prüfung:
- Durchführung von Übungen in Teams (empfohlen)
- Mündliche Einzelprüfung 30 Minuten, anhand konkreter Problemstellungen
151-0660-00LModel Predictive Control Information W4 KP2V + 1UM. Zeilinger, A. Carron
KurzbeschreibungModel predictive control is a flexible paradigm that defines the control law as an optimization problem, enabling the specification of time-domain objectives, high performance control of complex multivariable systems and the ability to explicitly enforce constraints on system behavior. This course provides an introduction to the theory and practice of MPC and covers advanced topics.
LernzielDesign and implement Model Predictive Controllers (MPC) for various system classes to provide high performance controllers with desired properties (stability, tracking, robustness,..) for constrained systems.
Inhalt- Review of required optimal control theory
- Basics on optimization
- Receding-horizon control (MPC) for constrained linear systems
- Theoretical properties of MPC: Constraint satisfaction and stability
- Computation: Explicit and online MPC
- Practical issues: Tracking and offset-free control of constrained systems, soft constraints
- Robust MPC: Robust constraint satisfaction
- Nonlinear MPC: Theory and computation
- Hybrid MPC: Modeling hybrid systems and logic, mixed-integer optimization
- Simulation-based project providing practical experience with MPC
SkriptScript / lecture notes will be provided.
Voraussetzungen / BesonderesOne semester course on automatic control, Matlab, linear algebra.
Courses on signals and systems and system modeling are recommended. Important concepts to start the course: State-space modeling, basic concepts of stability, linear quadratic regulation / unconstrained optimal control.

Expected student activities: Participation in lectures, exercises and course project; homework (~2hrs/week).
151-0940-00LModelling and Mathematical Methods in Process and Chemical EngineeringW4 KP3GM. Mazzotti
KurzbeschreibungEinführung in die Modellierungstechniken und mathematischen Methoden für nichtnumerische Lösungen von Gleichungen in der chemischen Verfahrenstechnik.
LernzielEinführung in die Modellierungstechniken und mathematischen Methoden für nichtnumerische Lösungen von Gleichungen in der chemischen Verfahrenstechnik.
InhaltFormulierung und Bearbeitung von mathematischen Modellen, Auswertung und Präsentation von Resultaten, Matrizen und deren Anwendung, Nichtlineare, gewöhnliche Differentialgl. erster Ordnung u. Stabilitätstheorem, Partielle Differenzialgleichungen erster Ordnung, Einführung in die Störungstheorie, Fallstudien: Mehrdeutigkeiten und Stabilität eines kontinuierlichen Rührkessels; Rückstandskurvendiagramme für einfache Destillation; Dynamik von Chromatographiekolonnen; Kinetik und Dynamik von oszillierenden Reaktionen.
Skriptkein Skript
LiteraturA. Varma, M. Morbidelli, "Mathematical methods in chemical engineering," Oxford University Press (1997)
H.K. Rhee, R. Aris, N.R. Amundson, "First-order partial differential equations. Vol. 1," Dover Publications, New York (1986)
R. Aris, "Mathematical modeling: A chemical engineer’s perspective," Academic Press, San Diego (1999)
151-0980-00LBiofluiddynamicsW4 KP2V + 1UD. Obrist, P. Jenny
KurzbeschreibungIntroduction to the fluid dynamics of the human body and the modeling of physiological flow processes (biomedical fluid dynamics).
LernzielA basic understanding of fluid dynamical processes in the human body. Knowledge of the basic concepts of fluid dynamics and the ability to apply these concepts appropriately.
InhaltThis lecture is an introduction to the fluid dynamics of the human body (biomedical fluid dynamics). For selected topics of human physiology, we introduce fundamental concepts of fluid dynamics (e.g., creeping flow, incompressible flow, flow in porous media, flow with particles, fluid-structure interaction) and use them to model physiological flow processes. The list of studied topics includes the cardiovascular system and related diseases, blood rheology, microcirculation, respiratory fluid dynamics and fluid dynamics of the inner ear.
SkriptLecture notes are provided electronically.
LiteraturA list of books on selected topics of biofluiddynamics can be found on the course web page.
227-0052-10LElektromagnetische Felder und Wellen Information W4 KP2V + 2UL. Novotny
KurzbeschreibungGegenstand dieser Vorlesung ist die Erzeugung und Ausbreitung elektromagnetischer Felder. Ausgehend von den Maxwell'schen Gleichungen werden die Wellengleichung und ihre Loesungen hergeleitet. Spezifische Themen sind: Felder im freien Raum, Brechung und Reflexion an Grenzflaechen, Dipolstrahlung und Green'sche Funktionen, Vektor- und Skalarpotentiale, sowie Eichtransformationen.
LernzielVerständnis von elektromagnetischen Feldern und Anwendungsgebiete
227-0418-00LAlgebra and Error Correcting Codes Information W6 KP4GH.‑A. Loeliger
KurzbeschreibungThe course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course includes a self-contained introduction of the pertinent basics of "abstract" algebra.
LernzielThe course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course includes a self-contained introduction of the pertinent basics of "abstract" algebra.
InhaltError correcting codes: coding and modulation, linear codes, Hamming space codes, Euclidean space codes, trellises and Viterbi decoding, convolutional codes, factor graphs and message passing algorithms, low-density parity check codes, turbo codes, polar codes, Reed-Solomon codes.

Algebra: groups, rings, homomorphisms, quotient groups, ideals, finite fields, vector spaces, polynomials.
SkriptLecture Notes (english)
227-0420-00LInformation Theory II Information W6 KP4GA. Lapidoth, S. M. Moser
KurzbeschreibungThis course builds on Information Theory I. It introduces additional topics in single-user communication, connections between Information Theory and Statistics, and Network Information Theory.
LernzielThe course's objective is to introduce the students to additional information measures and to equip them with the tools that are needed to conduct research in Information Theory as it relates to Communication Networks and to Statistics.
InhaltSanov's Theorem, Rényi entropy and guessing, differential entropy, maximum entropy, the Gaussian channel, the entropy-power inequality, the broadcast channel, the multiple-access channel, Slepian-Wolf coding, the Gelfand-Pinsker problem, and Fisher information.
Skriptn/a
LiteraturT.M. Cover and J.A. Thomas, Elements of Information Theory, second edition, Wiley 2006
Voraussetzungen / BesonderesBasic introductory course on Information Theory.
227-0104-00LCommunication and Detection Theory Information W6 KP4GA. Lapidoth
KurzbeschreibungThis course teaches the foundations of modern digital communications and detection theory. Topics include the geometry of the space of energy-limited signals; the baseband representation of passband signals, spectral efficiency and the Nyquist Criterion; the power and power spectral density of PAM and QAM; hypothesis testing; Gaussian stochastic processes; and detection in white Gaussian noise.
LernzielThis is an introductory class to the field of wired and wireless communication. It offers a glimpse at classical analog modulation (AM, FM), but mainly focuses on aspects of modern digital communication, including modulation schemes, spectral efficiency, power budget analysis, block and convolu- tional codes, receiver design, and multi- accessing schemes such as TDMA, FDMA and Spread Spectrum.
Inhalt- Baseband representation of passband signals.
- Bandwidth and inner products in baseband and passband.
- The geometry of the space of energy-limited signals.
- The Sampling Theorem as an orthonormal expansion.
- Sampling passband signals.
- Pulse Amplitude Modulation (PAM): energy, power, and power spectral density.
- Nyquist Pulses.
- Quadrature Amplitude Modulation (QAM).
- Hypothesis testing.
- The Bhattacharyya Bound.
- The multivariate Gaussian distribution
- Gaussian stochastic processes.
- Detection in white Gaussian noise.
Skriptn/a
LiteraturA. Lapidoth, A Foundation in Digital Communication, Cambridge University Press, 2nd edition (2017)
227-0120-00LCommunication Networks Information W6 KP4GL. Vanbever
KurzbeschreibungAt the end of this course, you will understand the fundamental concepts behind communication networks and the Internet. Specifically, you will be able to:

- understand how the Internet works;
- build and operate Internet-like infrastructures;
- identify the right set of metrics to evaluate the performance of a network and propose ways to improve it.
LernzielAt the end of the course, the students will understand the fundamental concepts of communication networks and Internet-based communications. Specifically, students will be able to:

- understand how the Internet works;
- build and operate Internet-like network infrastructures;
- identify the right set of metrics to evaluate the performance or the adequacy of a network and propose ways to improve it (if any).

The course will introduce the relevant mechanisms used in today's networks both from an abstract perspective but also from a practical one by presenting many real-world examples and through multiple hands-on projects.

For more information about the lecture, please visit: Link
SkriptLecture notes and material for the course will be available before each course on: Link
LiteraturMost of course follows the textbook "Computer Networking: A Top-Down Approach (6th Edition)" by Kurose and Ross.
Voraussetzungen / BesonderesNo prior networking background is needed. The course will include some programming assignments (in Python) for which the material covered in Technische Informatik 1 (227-0013-00L) will be useful.
227-0159-00LSemiconductor Devices: Quantum Transport at the Nanoscale Information W6 KP2V + 2UM. Luisier, A. Emboras
KurzbeschreibungThis class offers an introduction into quantum transport theory, a rigorous approach to electron transport at the nanoscale. It covers different topics such as bandstructure, Wave Function and Non-equilibrium Green's Function formalisms, and electron interactions with their environment. Matlab exercises accompany the lectures where students learn how to develop their own transport simulator.
LernzielThe continuous scaling of electronic devices has given rise to structures whose dimensions do not exceed a few atomic layers. At this size, electrons do not behave as particle any more, but as propagating waves and the classical representation of electron transport as the sum of drift-diffusion processes fails. The purpose of this class is to explore and understand the displacement of electrons through nanoscale device structures based on state-of-the-art quantum transport methods and to get familiar with the underlying equations by developing his own nanoelectronic device simulator.
InhaltThe following topics will be addressed:
- Introduction to quantum transport modeling
- Bandstructure representation and effective mass approximation
- Open vs closed boundary conditions to the Schrödinger equation
- Comparison of the Wave Function and Non-equilibrium Green's Function formalisms as solution to the Schrödinger equation
- Self-consistent Schödinger-Poisson simulations
- Quantum transport simulations of resonant tunneling diodes and quantum well nano-transistors
- Top-of-the-barrier simulation approach to nano-transistor
- Electron interactions with their environment (phonon, roughness, impurity,...)
- Multi-band transport models
SkriptLecture slides are distributed every week and can be found at
Link
LiteraturRecommended textbook: "Electronic Transport in Mesoscopic Systems", Supriyo Datta, Cambridge Studies in Semiconductor Physics and Microelectronic Engineering, 1997
Voraussetzungen / BesonderesBasic knowledge of semiconductor device physics and quantum mechanics
227-0558-00LPrinciples of Distributed Computing Information W7 KP2V + 2U + 2AR. Wattenhofer, M. Ghaffari
KurzbeschreibungWe study the fundamental issues underlying the design of distributed systems: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques.
LernzielDistributed computing is essential in modern computing and communications systems. Examples are on the one hand large-scale networks such as the Internet, and on the other hand multiprocessors such as your new multi-core laptop. This course introduces the principles of distributed computing, emphasizing the fundamental issues underlying the design of distributed systems and networks: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques, basically the "pearls" of distributed computing. We will cover a fresh topic every week.
InhaltDistributed computing models and paradigms, e.g. message passing, shared memory, synchronous vs. asynchronous systems, time and message complexity, peer-to-peer systems, small-world networks, social networks, sorting networks, wireless communication, and self-organizing systems.

Distributed algorithms, e.g. leader election, coloring, covering, packing, decomposition, spanning trees, mutual exclusion, store and collect, arrow, ivy, synchronizers, diameter, all-pairs-shortest-path, wake-up, and lower bounds
SkriptAvailable. Our course script is used at dozens of other universities around the world.
LiteraturLecture Notes By Roger Wattenhofer. These lecture notes are taught at about a dozen different universities through the world.

Distributed Computing: Fundamentals, Simulations and Advanced Topics
Hagit Attiya, Jennifer Welch.
McGraw-Hill Publishing, 1998, ISBN 0-07-709352 6

Introduction to Algorithms
Thomas Cormen, Charles Leiserson, Ronald Rivest.
The MIT Press, 1998, ISBN 0-262-53091-0 oder 0-262-03141-8

Disseminatin of Information in Communication Networks
Juraj Hromkovic, Ralf Klasing, Andrzej Pelc, Peter Ruzicka, Walter Unger.
Springer-Verlag, Berlin Heidelberg, 2005, ISBN 3-540-00846-2

Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes
Frank Thomson Leighton.
Morgan Kaufmann Publishers Inc., San Francisco, CA, 1991, ISBN 1-55860-117-1

Distributed Computing: A Locality-Sensitive Approach
David Peleg.
Society for Industrial and Applied Mathematics (SIAM), 2000, ISBN 0-89871-464-8
Voraussetzungen / BesonderesCourse pre-requisites: Interest in algorithmic problems. (No particular course needed.)
252-0211-00LInformation Security Information W8 KP4V + 3UD. Basin, S. Capkun
KurzbeschreibungThis course provides an introduction to Information Security. The focus
is on fundamental concepts and models, basic cryptography, protocols and system security, and privacy and data protection. While the emphasis is on foundations, case studies will be given that examine different realizations of these ideas in practice.
LernzielMaster fundamental concepts in Information Security and their
application to system building. (See objectives listed below for more details).
Inhalt1. Introduction and Motivation (OBJECTIVE: Broad conceptual overview of information security) Motivation: implications of IT on society/economy, Classical security problems, Approaches to
defining security and security goals, Abstractions, assumptions, and trust, Risk management and the human factor, Course verview. 2. Foundations of Cryptography (OBJECTIVE: Understand basic
cryptographic mechanisms and applications) Introduction, Basic concepts in cryptography: Overview, Types of Security, computational hardness, Abstraction of channel security properties, Symmetric
encryption, Hash functions, Message authentication codes, Public-key distribution, Public-key cryptosystems, Digital signatures, Application case studies, Comparison of encryption at different layers, VPN, SSL, Digital payment systems, blind signatures, e-cash, Time stamping 3. Key Management and Public-key Infrastructures (OBJECTIVE: Understand the basic mechanisms relevant in an Internet context) Key management in distributed systems, Exact characterization of requirements, the role of trust, Public-key Certificates, Public-key Infrastructures, Digital evidence and non-repudiation, Application case studies, Kerberos, X.509, PGP. 4. Security Protocols (OBJECTIVE: Understand network-oriented security, i.e.. how to employ building blocks to secure applications in (open) networks) Introduction, Requirements/properties, Establishing shared secrets, Principal and message origin authentication, Environmental assumptions, Dolev-Yao intruder model and
variants, Illustrative examples, Formal models and reasoning, Trace-based interleaving semantics, Inductive verification, or model-checking for falsification, Techniques for protocol design,
Application case study 1: from Needham-Schroeder Shared-Key to Kerberos, Application case study 2: from DH to IKE. 5. Access Control and Security Policies (OBJECTIVES: Study system-oriented security, i.e., policies, models, and mechanisms) Motivation (relationship to CIA, relationship to Crypto) and examples Concepts: policies versus models versus mechanisms, DAC and MAC, Modeling formalism, Access Control Matrix Model, Roll Based Access Control, Bell-LaPadula, Harrison-Ruzzo-Ullmann, Information flow, Chinese Wall, Biba, Clark-Wilson, System mechanisms: Operating Systems, Hardware Security Features, Reference Monitors, File-system protection, Application case studies 6. Anonymity and Privacy (OBJECTIVE: examine protection goals beyond standard CIA and corresponding mechanisms) Motivation and Definitions, Privacy, policies and policy languages, mechanisms, problems, Anonymity: simple mechanisms (pseudonyms, proxies), Application case studies: mix networks and crowds. 7. Larger application case study: GSM, mobility
263-4660-00LApplied Cryptography Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 150.
W8 KP3V + 2U + 2PK. Paterson
KurzbeschreibungThis course will introduce the basic primitives of cryptography, using rigorous syntax and game-based security definitions. The course will show how these primitives can be combined to build cryptographic protocols and systems.
LernzielThe goal of the course is to put students' understanding of cryptography on sound foundations, to enable them to start to build well-designed cryptographic systems, and to expose them to some of the pitfalls that arise when doing so.
InhaltBasic symmetric primitives (block ciphers, modes, hash functions); generic composition; AEAD; basic secure channels; basic public key primitives (encryption,signature, DH key exchange); ECC; randomness; applications.
LiteraturTextbook: Boneh and Shoup, “A Graduate Course in Applied Cryptography”, Link.
Voraussetzungen / BesonderesStudents should have taken the D-INFK Bachelor's course “Information Security" (252-0211-00) or an alternative first course covering cryptography at a similar level. / In this course, we will use Moodle for content delivery: Link.
252-0570-00LGame Programming Laboratory Information
Im Masterstudium können zusätzlich zu den Vertiefungsübergreifenden Fächern nur max. 10 Kreditpunkte über Laboratorien erarbeitet werden. Weitere Laboratorien werden auf dem Beiblatt aufgeführt.
W10 KP9PB. Sumner
KurzbeschreibungDas Ziel dieses Kurses ist ein vertieftes Verständnis der Technologie und der Programmierung von Computer-Spielen. Die Studierenden entwerfen und entwickeln in kleinen Gruppen ein Computer-Spiel und machen sich so vertraut mit der Kunst des Spiel-Programmierens.
LernzielDas Ziel dieses neuen Kurses ist es, die Studenten mit der Technologie und der Kunst des Programmierens von modernen dreidimensionalen Computerspielen vertraut zu machen.
InhaltDies ist ein Kurs, der auf die Technologie von modernen dreidimensionalen Computerspielen eingeht. Während des Kurses werden die Studenten in kleinen Gruppen ein Computerspiel entwerfen und entwickeln. Der Schwerpunkt des Kurses wird auf technischen Aspekten der Spielentwicklung wie Rendering, Kinematographie, Interaktion, Physik, Animation und KI liegen. Zusätzlich werden wir aber auch Wert auf kreative Ideen für fortgeschrittenes Gameplay und visuelle Effekte legen.

Der Kurs wird als Labor durchgeführt. Zusätzlich zu Vorträgen und Übungen wird der Kurs in einen praktischen, hands-on Ansatz durchgeführt. Wir treffen uns einmal wöchentlich um technische Aspekte zu besprechen und den Fortschritt der Entwicklung zu verfolgen. Für die Enwicklung verwenden wir MonoGames. Dies ist eine Ansammlung von Bibliotheken und Werkzeugen um die Spieleentwicklung zu erleichtern. Die Entwicklung wird zunächst auf dem PC stattfinden, das Spiel wird dann im weiteren Verlauf auf der Xbox One Konsole eingesetzt.

Am Ende des Kurses werden die Resultate öffentlich präsentiert.
SkriptGame Design Workshop: A Playcentric Approach to Creating Innovative Games by Tracy Fullerton
Voraussetzungen / BesonderesDie Anzahl der Teilnehmer ist begrenzt.

Voraussetzung für die Teilnahme sind:

- Gute Programmierkenntnisse (Java, C++, C#, o.ä.)

- Erfahrung in Computergrafik: Teilnehmer sollten mindestens die Vorlesung Visual Computing besucht haben. Wir empfehlen auch noch die weiterführenden Kurse Introduction to Computer Graphics, Surface Representations and Geometric Modeling, und Physically-based Simulation in Computer Graphics.
252-0538-00LShape Modeling and Geometry Processing Information W8 KP2V + 1U + 4AO. Sorkine Hornung
KurzbeschreibungThis course covers the fundamentals and some of the latest developments in geometric modeling and geometry processing. Topics include surface modeling based on point clouds and polygonal meshes, mesh generation, surface reconstruction, mesh fairing and parameterization, discrete differential geometry, interactive shape editing, topics in digital shape fabrication.
LernzielThe students will learn how to design, program and analyze algorithms and systems for interactive 3D shape modeling and geometry processing.
InhaltRecent advances in 3D geometry processing have created a plenitude of novel concepts for the mathematical representation and interactive manipulation of geometric models. This course covers the fundamentals and some of the latest developments in geometric modeling and geometry processing. Topics include surface modeling based on point clouds and triangle meshes, mesh generation, surface reconstruction, mesh fairing and parameterization, discrete differential geometry, interactive shape editing and digital shape fabrication.
SkriptSlides and course notes
Voraussetzungen / BesonderesPrerequisites:
Visual Computing, Computer Graphics or an equivalent class. Experience with C++ programming. Solid background in linear algebra and analysis. Some knowledge of differential geometry, computational geometry and numerical methods is helpful but not a strict requirement.
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