Suchergebnis: Katalogdaten im Herbstsemester 2017

Agrarwissenschaften Bachelor Information
Bachelor-Studium (Studienreglement 2016)
1. Semester
Basisprüfung
NummerTitelTypECTSUmfangDozierende
401-0251-00LMathematik I: Analysis I und Lineare AlgebraO6 KP4V + 2UL. Halbeisen
KurzbeschreibungDiese Vorlesung behandelt mathematische Konzepte und Methoden, die zum Modellieren, Lösen und Diskutieren wissenschaftlicher Probleme nötig sind - speziell durch gewöhnliche Differentialgleichungen.
LernzielMathematik ist von immer grösserer Bedeutung in den Natur- und Ingenieurwissenschaften. Grund dafür ist das folgende Konzept zur Lösung konkreter Probleme: Der entsprechende Ausschnitt der Wirklichkeit wird in der Sprache der Mathematik modelliert; im mathematischen Modell wird das Problem - oft unter Anwendung von äusserst effizienter Software - gelöst und das Resultat in die Realität zurück übersetzt.

Ziel der Vorlesungen Mathematik I und II ist es, die einschlägigen mathematischen Grundlagen bereit zu stellen. Differentialgleichungen sind das weitaus wichtigste Hilfsmittel im Prozess des Modellierens und stehen deshalb im Zentrum beider Vorlesungen.
Inhalt1. Differential- und Integralrechnung:
Wiederholung der Ableitung, Linearisierung, Taylor-Polynome, Extremwerte, Stammfunktion, Hauptsatz der Differential- und Integralrechnung, Integrationsmethoden, uneigentliche Integrale.

2. Lineare Algebra und Komplexe Zahlen:
lineare Gleichungssysteme, Gauss-Verfahren, Matrizen, Determinanten, Eigenwerte und Eigenvektoren, Darstellungsformen der komplexe Zahlen, Potenzieren, Radizieren, Fundamentalsatz der Algebra.

3. Gewöhnliche Differentialgleichungen:
Separierbare Differentialgleichungen (DGL), Integration durch Substitution, Lineare DGL erster und zweiter Ordnung, homogene Systeme linearer DGL mit konstanten Koeffizienten, Einführung in die dynamischen Systeme in der Ebene.
Literatur- Thomas, G. B., Weir, M. D. und Hass, J.: Analysis 1, Lehr- und Übungsbuch (Pearson).
- Gramlich, G.: Lineare Algebra, eine Einführung (Hanser).
- Papula, L.: Mathematik für Ingenieure und Naturwissenschaftler, Bd. 1 und 2 (Vieweg+Teubner).
Voraussetzungen / BesonderesVoraussetzungen: Vertrautheit mit den Grundlagen der Analysis, insbesondere mit dem Funktions- und Ableitungsbegriff.

Mathe-Lab (Präsenzstunden):
Mo 12-14, Di 17-19, Mi 17-19, stets im Raum HG E 41.
Grundlagenfächer (zweiter Studienjahr)
Prüfungsblock
NummerTitelTypECTSUmfangDozierende
701-0071-00LMathematik III: SystemanalyseO4 KP2V + 1UN. Gruber, M. Vogt
KurzbeschreibungIn der Systemanalyse geht es darum, durch ausgesuchte praxisnahe Beispiele die in der Mathematik bereit gestellte Theorie zu vertiefen und zu veranschaulichen. Konkret behandelt werden: Dynamische lineare Boxmodelle mit einer und mehreren Variablen; Nichtlineare Boxmodelle mit einer oder mehreren Variablen; zeitdiskrete Modelle, und kontinuierliche Modelle in Raum und Zeit.
LernzielErlernen und Anwendung von Konzepten (Modellen) und quantitativen Methoden zur Lösung von umweltrelevanten Problemen. Verstehen und Umsetzen des systemanalytischen Ansatzes, d.h. Erkennen des Kernes eines Problemes - Abstraktion - Quantitatives Erfassen - Vorhersage.
Inhalthttp://www.up.ethz.ch/education/systems-analysis.html
SkriptFolien werden über Ilias zur Verfügung gestellt.
LiteraturImboden, D. and S. Koch (2003) Systemanalyse - Einführung in die mathematische Modellierung natürlicher Systeme. Berlin Heidelberg: Springer Verlag.
Bachelor-Studium (Studienreglement 2010)
5. Semester
Methodenfächer
NummerTitelTypECTSUmfangDozierende
751-0441-00LWissenschaftliche Datenauswertung und -präsentationO2 KP2GW. Eugster
KurzbeschreibungDiese Veranstaltung macht die Studierenden mit den Schritten von der Dateneingabe über statistischen Analyseverfahren bis zu grafischen Darstellungsformen vertraut. In Übungen mit der Daten-Analyse-Software R (via RStudio) wird das methodische Werkzeug zur Daten-Auswertung und -Präsentation erklärt. Daten aus einem Versuch mit Prof. E. Frossard aus dem Vorsemester werden verwendet und diskutiert.
LernzielDiese Veranstaltung soll die Studierenden mit den statistischen Analyseverfahren, die im Rahmen einer Bachelorarbeit benötigt werden (deskriptive Statistik, linear Regression usw.) vertraut machen und ihnen Gelegenheit bieten, im Rahmen geleiteter praktischer Übungen mit der Daten-Analyse-Software R anhand ausgewählter Beispiele das methodische Werkzeug zur Daten-Auswertung und -Präsentation kennen zu lernen. Ein wichtiger Schwerpunkt wird die Vermittlung geeigneter grafischer Darstellungsarten sein (wie präsentiert man Daten anschaulich und wissenschaftlich korrekt?).
InhaltVoraussichtliche Kursschwerpunkte:
1. Einführung
2. Datenerfassung, -organisation, -pflege, Arbeit mit Daten
3. Grafische Darstellungen I - Tabellenkalkulation
4. Vorbereitung Daten aus Kurs mit Prof. E. Frossard / 4. Sem.
5. Korrekte und problematische grafische Darstellungen
6. Einführung in 'R'
7. Daten einlesen und darstellen
8. Verteilungen und Konfidenzintervalle
9. Statistische Tests - Repetition und Anwendung
10. Lineare Regression
11./12. Analysis of Variance
13. ANOVA - Diskussion der Resultate mit Prof. E. Frossard

In der letzten Doppelstunde: Leistungskontrolle
SkriptHauptsächlich Deutsch (mit englischen Abschnitten aus Lehrbüchern)
Voraussetzungen / BesonderesTheoretisches Wissen in Statistik aus der Vorlesung mit Übungen des 4. Semesters; erfüllte Leistungskontrolle dieser Veranstaltung
Agrarwissenschaften Master Information
Master-Studium (Studienreglement 2016)
Vertiefung Agrarökonomie
Methodische Kompetenzbereiche
Methods in Agricultural Economics
NummerTitelTypECTSUmfangDozierende
751-0423-00LRisk Analysis and Risk Management in AgricultureW+3 KP2GR. Finger
KurzbeschreibungAgricultural production is exposed to various risks which are important for decisions taken by farmers and other actors in the agri-food sector. Moreover, risk management is indispensable for all actors. This course introduces modern concepts on decision making under risk and recent developments in risk management. The focus of this course in on agriculture applications.
Lernziel-to develop a better understanding of decision making under uncertainty and risk;
-to gain experience in different approaches to analyze risky decisions;
-to develop an understanding for different sources of risk in agricultural production;
-to understand the crucial role of subjective perceptions and preferences for risk management decisions;
-to get an overview on risk management in the agricultural sector, with a particular focus on insurance solutions
Inhalt- Quantification and measurement of risk
- Risk preferences, expected utility theory and alternative models of risk behavior
- Concepts on the decision making under risk
- Production, investment and diversification decisions under risk
- Risk management in agriculture
SkriptHandouts will be distributed in the lecture and available on the moodle.
Voraussetzungen / Besonderesknowledge of basic concepts of probability theory and microeconomics
Ergänzungen
Agricultural Economics and Policy
NummerTitelTypECTSUmfangDozierende
751-0423-00LRisk Analysis and Risk Management in AgricultureW3 KP2GR. Finger
KurzbeschreibungAgricultural production is exposed to various risks which are important for decisions taken by farmers and other actors in the agri-food sector. Moreover, risk management is indispensable for all actors. This course introduces modern concepts on decision making under risk and recent developments in risk management. The focus of this course in on agriculture applications.
Lernziel-to develop a better understanding of decision making under uncertainty and risk;
-to gain experience in different approaches to analyze risky decisions;
-to develop an understanding for different sources of risk in agricultural production;
-to understand the crucial role of subjective perceptions and preferences for risk management decisions;
-to get an overview on risk management in the agricultural sector, with a particular focus on insurance solutions
Inhalt- Quantification and measurement of risk
- Risk preferences, expected utility theory and alternative models of risk behavior
- Concepts on the decision making under risk
- Production, investment and diversification decisions under risk
- Risk management in agriculture
SkriptHandouts will be distributed in the lecture and available on the moodle.
Voraussetzungen / Besonderesknowledge of basic concepts of probability theory and microeconomics
Master-Studium (Studienreglement 2011)
Vertiefungen
Vertiefung in Food and Resource Use Economics
Methodische Kompetenzbereiche
Methods in Food and Resource Use Economics
NummerTitelTypECTSUmfangDozierende
751-0423-00LRisk Analysis and Risk Management in AgricultureW+3 KP2GR. Finger
KurzbeschreibungAgricultural production is exposed to various risks which are important for decisions taken by farmers and other actors in the agri-food sector. Moreover, risk management is indispensable for all actors. This course introduces modern concepts on decision making under risk and recent developments in risk management. The focus of this course in on agriculture applications.
Lernziel-to develop a better understanding of decision making under uncertainty and risk;
-to gain experience in different approaches to analyze risky decisions;
-to develop an understanding for different sources of risk in agricultural production;
-to understand the crucial role of subjective perceptions and preferences for risk management decisions;
-to get an overview on risk management in the agricultural sector, with a particular focus on insurance solutions
Inhalt- Quantification and measurement of risk
- Risk preferences, expected utility theory and alternative models of risk behavior
- Concepts on the decision making under risk
- Production, investment and diversification decisions under risk
- Risk management in agriculture
SkriptHandouts will be distributed in the lecture and available on the moodle.
Voraussetzungen / Besonderesknowledge of basic concepts of probability theory and microeconomics
Atmospheric and Climate Science Master Information
Module
Hydrologie und Wasserkreislauf
NummerTitelTypECTSUmfangDozierende
701-1253-00LAnalysis of Climate and Weather Data Information W3 KP2GC. Frei
KurzbeschreibungObservation networks and numerical climate and forcasting models deliver large primary datasets. The use of this data in practice and in research requires specific techniques of statistical data analysis. This lecture introduces a range of frequently used techniques, and enables students to apply them and to properly interpret their results.
LernzielObservation networks and numerical climate and forcasting models deliver large primary datasets. The use of this data in practice and in research requires specific techniques of statistical data analysis. This lecture introduces a range of frequently used techniques, and enables students to apply them and to properly interpret their results.
InhaltIntroduction into the theoretical background and the practical application of methods of data analysis in meteorology and climatology.

Topics: exploratory methods, hypothesis testing, analysis of climate trends, measuring the skill of climate and forecasting models, analysis of extremes, principal component analysis and maximum covariance analysis.

The lecture also provides an introduction into R, a programming language and graphics tool frequently used for data analysis in meteorology and climatology. During hands-on computer exercises the student will become familiar with the practical application of the methods.
SkriptDocumentation and supporting material include:
- documented view graphs used during the lecture
- excercise sets and solutions
- R-packages with software and example datasets for exercise sessions

All material is made available via the lecture web-page.
LiteraturSuggested literature:
- Wilks D.S., 2005: Statistical Methods in the Atmospheric Science. (2nd edition). International Geophysical Series, Academic Press Inc. (London)
- Coles S., 2001: An introduction to statistical modeling of extreme values. Springer, London. 208 pp.
Voraussetzungen / BesonderesPrerequisites: Atmosphäre, Mathematik IV: Statistik, Anwendungsnahes Programmieren.
Ergänzungen
Ergänzung in nachhaltiger Energienutzung
NummerTitelTypECTSUmfangDozierende
227-1631-00LEnergy System Analysis Information W4 KP3GG. Hug, S. Hellweg, F. Noembrini, A. Schlüter
KurzbeschreibungThe course provides an introduction to the methods and tools for analysis of energy consumption, energy production and energy flows. Environmental aspects are included as well as economical considerations. Different sectors of the society are discussed, such as electric power, buildings, and transportation. Models for energy system analysis planning are introduced.
LernzielThe purpose of the course is to give the participants an overview of the methods and tools used for energy systems analysis and how to use these in simple practical examples.
InhaltThe course gives an introduction to methods and tools for analysis of energy consumption, energy production and energy flows. Both larger systems, e.g. countries, and smaller systems, e.g. industries, homes, vehicles, are studied. The tools and methods are applied to various problems during the exercises. Different conventions of energy statistics used are introduced.

The course provides also an introduction to energy systems models for developing scenarios of future energy consumption and production. Bottom-up and Top-Down approaches are addressed and their features and applications discussed.

The course contains the following parts:
Part I: Energy flows and energy statistics
Part II: Environmental impacts
Part III: Electric power systems
Part IV: Energy in buildings
Part V: Energy in transportation
Part VI: Energy systems models
SkriptHandouts
LiteraturExcerpts from various books, e.g. K. Blok: Introduction to Energy Analysis, Techne Press, Amsterdam 2006, ISBN 90-8594-016-8
Auflagen-Lerneinheiten
Das untenstehende Lehrangebot gilt nur für MSc Studierende mit Zulassungsauflagen.
NummerTitelTypECTSUmfangDozierende
701-0071-AALMathematics III: Systems Analysis
Belegung ist NUR erlaubt für MSc Studierende, die diese Lerneinheit als Auflagenfach verfügt haben.

Alle anderen Studierenden (u.a. auch Mobilitätsstudierende, Doktorierende) können diese Lerneinheit NICHT belegen.
E-4 KP9RN. Gruber
KurzbeschreibungIn der Systemanalyse geht es darum, durch ausgesuchte praxisnahe Beispiele die in der Mathematik bereit gestellte Theorie zu vertiefen und zu veranschaulichen. Konkret behandelt werden: Dynamische lineare Boxmodelle mit einer und mehreren Variablen; Nichtlineare Boxmodelle mit einer oder mehreren Variablen; zeitdiskrete Modelle, und kontinuierliche Modelle in Raum und Zeit.
LernzielErlernen und Anwendung von Konzepten (Modellen) und quantitativen Methoden zur Lösung von umweltrelevanten Problemen. Verstehen und Umsetzen des systemanalytischen Ansatzes, d.h. Erkennen des Kernes eines Problemes - Abstraktion - Quantitatives Erfassen - Vorhersage.
Inhalthttp://www.up.ethz.ch/education/systems-analysis.html
SkriptFolien werden über Ilias zur Verfügung gestellt.
LiteraturImboden, D. and S. Koch (2003) Systemanalyse - Einführung in die mathematische Modellierung natürlicher Systeme. Berlin Heidelberg: Springer Verlag.
701-1901-AALSystems Analysis
Belegung ist NUR erlaubt für MSc Studierende, die diese Lerneinheit als Auflagenfach verfügt haben.

Alle anderen Studierenden (u.a. auch Mobilitätsstudierende, Doktorierende) können diese Lerneinheit NICHT belegen.
E-4 KP9RN. Gruber
KurzbeschreibungSystems analysis is about the application of mathematical concepts to solve real world problems in a quantitative manner. Areas covered include: Dynamic linear models with one and several variables, Non-linear models with one or several variables; discrete-time models; and continuous models in space and time.
LernzielThe goal of the course is to develop quantitative skills in order to understand and solve a range of typical environmental problems.
InhaltThe subject of the exam is the content of my
undergraduate lecture series Systemanalyse I and II (see http://www.up.ethz.ch/education/system_analysis/index_DE).
This course is closely aligned with the Imboden&Koch / Imboden&Pfenniger books, except that I essentially skip chapter 7.
SkriptNo script is available, but you can purchase the Imboden/Koch or Imboden/Pfenniger books (or download some of the chapters yourself) through the Springer Verlag:

English version:
http://link.springer.com/book/10.1007/978-3-642-30639-6/page/1

German version:
http://www.springer.com/environment/book/978-3-540-43935-6
Bauingenieurwissenschaften Bachelor Information
Bachelor-Studium (Studienreglement 2014)
Obligatorische Fächer des Basisjahres
Basisprüfung
Anstelle der deutschsprachigen Lehrveranstaltung 851-0703-03L Grundzüge des Rechts für Bauwissenschaften kann wahlweise auch die französischsprachige Lehrveranstaltung 851-0709-00L Droit civil belegt werden.
NummerTitelTypECTSUmfangDozierende
401-0241-00LAnalysis I Information O7 KP5V + 2UM. Akka Ginosar
KurzbeschreibungMathematische Hilfsmittel des Ingenieurs
LernzielMathematik als Hilfsmittel zur Lösung von Ingenieurproblemen:
Verständnis für mathematische Formulierung von technischen und naturwissenschaftlichen Problemen.
Erarbeitung des mathematischen Grundwissens für einen Ingenieur.
InhaltKomplexe Zahlen.
Differentialrechnung und Integralrechnung für Funktionen einer Variablen mit Anwendungen.
Einfache mathematische Modelle in den Naturwissenschaften.
SkriptDie Vorlesung folgt weitgehend

Klaus Dürrschnabel, "Mathematik für Ingenieure - Eine Einführung mit Anwendungs- und Alltagsbeispielen", Springer; online verfügbar unter:
http://link.springer.com/book/10.1007/978-3-8348-2559-9/page/1
LiteraturNeben Klaus Dürrschnabel, "Mathematik für Ingenieure - Eine Einführung mit Anwendungs- und Alltagsbeispielen", Springer sind auch die folgenden Bücher/Skripte empfehlenswert und decken den zu behandelnden Stoff ab:

Tilo Arens et al., "Mathematik", Springer; online verfügbar unter:
http://link.springer.com/book/10.1007/978-3-642-44919-2/page/1

Meike Akveld, "Analysis 1", vdf;
http://vdf.ch/index.php?route=product/product&product_id=1706

Urs Stammbach, "Analysis I/II" (erhältlich im ETH Store);
https://people.math.ethz.ch/~stammb/analysisskript.html
Obligatorische Fächer 3. Semester
Prüfungsblock 1
NummerTitelTypECTSUmfangDozierende
401-0243-00LAnalysis IIIO3 KP2V + 1UA. Sisto
KurzbeschreibungWe will model and solve scientific problems with partial differential equations. Differential equations which are important in applications will be classified and solved. Elliptic, parabolic and hyperbolic differential equations will be treated. The following mathematical tools will be introduced: Laplace and Fourier transforms, Fourier series, separation of variables, methods of characteristics.
LernzielLearning to model scientific problems using partial differential equations and developing a good command of the mathematical methods that can be applied to them. Knowing the formulation of important problems in science and engineering with a view toward civil engineering (when possible). Understanding the properties of the different types of partial differential equations arising in science and in engineering.
InhaltClassification of partial differential equations

Study of the Heat equation general diffusion/parabolic problems using the following tools:
* Separation of variables
* Fourier series
* Fourier transform
* Laplace transform

Study of the wave equation and general hyperbolic problems using similar tools and the method of characteristics.

Study of the Laplace equation and general elliptic problems using similar tools and generalizations of Fourier series.
LiteraturThe course material is taken from the following sources:

Stanley J. Farlow - Partial Differential Equations for Scientists and Engineers

G. Felder: Partielle Differenzialgleichungen.
https://people.math.ethz.ch/~felder/PDG/
Voraussetzungen / BesonderesAnalysis I and II. In particular, knowing how to solve ordinary differential equations is an important prerequisite.
Bauingenieurwissenschaften Master Information
1. Semester
Vertiefungsfächer
Vertiefung in Konstruktion
NummerTitelTypECTSUmfangDozierende
101-0187-00LStructural Reliability and Risk Analysis Information W3 KP2GS. Marelli
KurzbeschreibungStructural reliability aims at quantifying the probability of failure of systems due to uncertainties in their design, manufacturing and environmental conditions. Risk analysis combines this information with the consequences of failure in view of optimal decision making. The course presents the underlying probabilistic modelling and computational methods for reliability and risk assessment.
LernzielThe goal of this course is to provide the students with a thorough understanding of the key concepts behind structural reliability and risk analysis. After this course the students will have refreshed their knowledge of probability theory and statistics to model uncertainties in view of engineering applications. They will be able to analyze the reliability of a structure and to use risk assessment methods for decision making under uncertain conditions. They will be aware of the state-of-the-art computational methods and software in this field.
InhaltEngineers are confronted every day to decision making under limited amount of information and uncertain conditions. When designing new structures and systems, the design codes such as SIA or Euro- codes usually provide a framework that guarantees safety and reliability. However the level of safety is not quantified explicitly, which does not allow the analyst to properly choose between design variants and evaluate a total cost in case of failure. In contrast, the framework of risk analysis allows one to incorporate the uncertainty in decision making.

The first part of the course is a reminder on probability theory that is used as a main tool for reliability and risk analysis. Classical concepts such as random variables and vectors, dependence and correlation are recalled. Basic statistical inference methods used for building a probabilistic model from the available data, e.g. the maximum likelihood method, are presented.

The second part is related to structural reliability analysis, i.e. methods that allow one to compute probabilities of failure of a given system with respect to prescribed criteria. The framework of reliability analysis is first set up. Reliability indices are introduced together with the first order-second moment method (FOSM) and the first order reliability method (FORM). Methods based on Monte Carlo simulation are then reviewed and illustrated through various examples. By-products of reliability analysis such as sensitivity measures and partial safety coefficients are derived and their links to structural design codes is shown. The reliability of structural systems is also introduced as well as the methods used to reassess existing structures based on new information.

The third part of the course addresses risk assessment methods. Techniques for the identification of hazard scenarios and their representation by fault trees and event trees are described. Risk is defined with respect to the concept of expected utility in the framework of decision making. Elements of Bayesian decision making, i.e. pre-, post and pre-post risk assessment methods are presented.

The course also includes a tutorial using the UQLab software dedicated to real world structural reliability analysis.
SkriptSlides of the lectures are available online every week. A printed version of the full set of slides is proposed to the students at the beginning of the semester.
LiteraturAng, A. and Tang, W.H, Probability Concepts in Engineering - Emphasis on Applications to Civil and Environmental Engineering, 2nd Edition, John Wiley & Sons, 2007.

S. Marelli, R. Schöbi, B. Sudret, UQLab user manual - Structural reliability (rare events estimation), Report UQLab-V0.92-107.
Voraussetzungen / BesonderesBasic course on probability theory and statistics
3. Semester
Vertiefungsfächer
Vertiefung in Bau- und Erhaltungsmanagement
NummerTitelTypECTSUmfangDozierende
101-0439-00LIntroduction to Economic Analysis - A Case Study Approach with Cost Benefit Analysis in Transport
Remark:
Former Title "Introduction to Economic Policy - A Case Study Approach with Cost Benefit Analysis in Transport".
W6 KP4GK. W. Axhausen, R. Schubert
KurzbeschreibungDie Vorlesung stellt einige grundlegende ökonomische Prinzipien sowie die Verfahren der Kosten-Nutzen-Analyse vor; sie führt auch in Methoden zur Ermittlung von Bewertungsgrössen ein
LernzielSichere Kenntnis mikro- und makroökonomischer Grundlagen. Erarbeitung und Übung von Verfahren der Bewertung von Massnahmen und infrastrukturellen Ausbauten
InhaltMikro-und makroökonomische Grundlagen; Kosten - Nutzen - Analyse; Nutzwertanalyse; Europäische Richtlinien; Stated response Verfahren; Reisekostenansatz et al.; Bewertung von Reisezeitveränderungen; Bewertung der Verkehrssicherheit
Skriptmoodle Plattform für die ökonomischen Grundlagen; Umdrucke
LiteraturTaylor, M.P., Mankiw, N.G. (2014): Economics; Harvard Press

VSS (2006) SN 640 820: Kosten-Nutzen-Analysen im Strassenverkehr, VSS, Zürich.

Boardman, A.E., D.H. Greenberg, A.R. Vining und D.L. Weimer (2001) Cost – Benefit – Analysis: Concepts and Practise, Prentice-Hall, Upper Saddle River.

ecoplan and metron (2005) Kosten-Nutzen-Analysen im Strassenverkehr: Kommentar zu SN 640 820, UVEK, Bern.
Vertiefung in Konstruktion
NummerTitelTypECTSUmfangDozierende
101-0179-00LProbabilistic Seismic Risk Analysis and Management for Civil Systems
Findet dieses Semester nicht statt.
W3 KP2GB. Stojadinovic, Noch nicht bekannt
KurzbeschreibungAdvanced topics covered in this course are: 1) probabilistic seismic hazard analysis; 2) probabilistic seismic risk analysis; 3) seismic risk management using structural and financial engineering means; and, time permitting, 4) advanced topics in systemic probabilistic risk evaluation.
LernzielAfter successfully completing this course the students will be able to:

1. Gather the necessary data and conduct a probabilistic seismic hazard analysis for a site.
2. Gather the necessary data and conduct a probabilistic vulnerability analysis of a building or an element of a civil infrastructure system at a site.
3. Design structural and/or financial engineering solutions to mitigate the seismic risk at a site.
InhaltThis course extends the series of two courses on seismic design of structures at ETHZ and introduces the topic of probabilistic seismic risk analysis and seismic risk management for the build environment and civil infrastructure systems. The following advanced topics will be covered in this course: 1) probabilistic seismic hazard analysis; 2) probabilistic seismic risk analysis; 3) seismic risk management using structural and financial engineering means; and, time permitting, 4) advanced topics in systemic probabilistic risk evaluation.
SkriptThe electronic copies of the learning material will be uploaded to ILIAS and available through myStudies. This will include the lecture notes, additional reading, and exercise problems and solutions. There is no textbook for this course.
LiteraturReading material:
- Jack R Benjamin, C. Allin Cornell (2014) Probability, Statistics, and Decision for Civil Engineers
- A. H-S. Ang (Author), W. H. Tang Probability Concepts in Engineering: Emphasis on Applications to Civil and Environmental Engineering
- P.E. Pinto, R. Giannini and P. Franchin (2004) Seismic reliability analysis of structures, IUSSPress. Pavia;
- McGuire, R.K. 2004. Seismic hazard and risk analysis: EERI Monograph MNO-10, Earthquake Engineering Research Institute.
- A Mc. Neil, R. Frey and P. Embrechts, Quantitative Risk Management, Concepts, Techniques and Tools, Princeton University Press, 2015
- R. Rees, A. Wambach, The Microeconomics of Insurance, Foundations and Trends in Microeconomics, Vol. 4, Mps. 1-2 (2008), pp. 1- 163, DOI: 10.1561/0700000023
- Earthquake Engineering: From Engineering Seismology to Performance-Based Engineering, Yousef Borzorgnia and Vitelmo Bertero, Eds., CRC Press, 2004
- Dynamics of Structures: Theory and Applications to Earthquake Engineering, 4th edition, Anil Chopra, Prentice Hall, 2012
- Erdbebensicherung von Bauwerken, 2nd edition, Hugo Bachmann, Birkhäuser, Basel, 2002

References:
-Norm SIA 261: Einwirkungen auf Tragwerke (Actions on Structures). Schweizerischer Ingenieur- und Architekten-Verein, Zürich, 2003

Software:
- Bispec: software for unidirectional and bidirectional dynamic time-history and spectral seismic analysis of a simple dynamic system. http://eqsols.com/Bispec.aspx
- SAP2000 v15.1: general-purpose 3D nonlinear structural analysis software. http://www.csiberkeley.com/sap2000
- OpenSees: Open System for Earthquake Engineering Simulation, is an object-oriented, open- source software framework. http://opensees.berkeley.edu/
Voraussetzungen / BesonderesETH Seismic Design of Structures I course (101-0188-00), or equivalent. Students are expected to understand the seismological nature of earthquakes, to characterize the ground motion excitation, to analyze the response of elastic single- and multiple-degree-of-freedom systems to earthquake excitation, to use the concept of response and design spectrum, to compute the equivalent seismic loads on simple structures, and to perform code-based seismic design of simple structures.
Vertiefung in Verkehrssysteme
NummerTitelTypECTSUmfangDozierende
101-0439-00LIntroduction to Economic Analysis - A Case Study Approach with Cost Benefit Analysis in Transport
Remark:
Former Title "Introduction to Economic Policy - A Case Study Approach with Cost Benefit Analysis in Transport".
W6 KP4GK. W. Axhausen, R. Schubert
KurzbeschreibungDie Vorlesung stellt einige grundlegende ökonomische Prinzipien sowie die Verfahren der Kosten-Nutzen-Analyse vor; sie führt auch in Methoden zur Ermittlung von Bewertungsgrössen ein
LernzielSichere Kenntnis mikro- und makroökonomischer Grundlagen. Erarbeitung und Übung von Verfahren der Bewertung von Massnahmen und infrastrukturellen Ausbauten
InhaltMikro-und makroökonomische Grundlagen; Kosten - Nutzen - Analyse; Nutzwertanalyse; Europäische Richtlinien; Stated response Verfahren; Reisekostenansatz et al.; Bewertung von Reisezeitveränderungen; Bewertung der Verkehrssicherheit
Skriptmoodle Plattform für die ökonomischen Grundlagen; Umdrucke
LiteraturTaylor, M.P., Mankiw, N.G. (2014): Economics; Harvard Press

VSS (2006) SN 640 820: Kosten-Nutzen-Analysen im Strassenverkehr, VSS, Zürich.

Boardman, A.E., D.H. Greenberg, A.R. Vining und D.L. Weimer (2001) Cost – Benefit – Analysis: Concepts and Practise, Prentice-Hall, Upper Saddle River.

ecoplan and metron (2005) Kosten-Nutzen-Analysen im Strassenverkehr: Kommentar zu SN 640 820, UVEK, Bern.
Biologie Bachelor Information
2. Studienjahr, 3. Semester
Kernfächer
NummerTitelTypECTSUmfangDozierende
551-1003-00LMethoden der Biologischen Analytik Information O3 KP3GR. Aebersold, M. Badertscher, K. Weis
Kurzbeschreibung529-1042-00
Grundlagen der wichtigsten Trennmethoden und der Interpretation von Molekülspektren.

551-1003-00
Der Kurs befasst sich mit den Methoden und ausgewählten Anwendungen von Methoden der Nukleinsäuresequenzierung, der massenspektrometrischen Analyse von Proteinen und Proteomen und Licht-und Fluoreszenz gestützten Methoden der Mikroskopie.
Lernziel529-1042-00
Kenntnis der notwendigen Grundlagen und der Anwendungsmöglichkeiten für den Einsatz von relevanten spektroskopischen und Trennmethoden in der analytisch-chemischen Praxis.

551-1003-00
Kenntnis der notwendigen Grundlagen und der Anwendungsmöglichkeiten der Methoden für die Bestimmung von Nukleinsäuresequenzen, der massenspektrometrischen Analyse von Proteinen und Proteomen und Licht-und Fluoreszenz gestützten Methoden der Mikroskopie.
Inhalt529-1042-00
Anwendungsorientierte Grundlagen der organischen Instrumentalanalytik und des empirischen Einsatzes von Methoden der Strukturaufklärung (Massenspektrometrie, NMR-, IR-, UV/VIS-Spektroskopie). Grundlagen und Anwendung chromatographischer und elektrophoretischer Trennverfahren. Praxisnahe Anwendung und Vertiefung des Grundwissens anhand von Übungen.

551-1003-00
Der Kurs setzt sich zusammen aus Vorlesungen, die die theoretischen und technischen Grundlagen der betreffenden analytischen Methoden vermitteln und Übungen, die sich mit den Anwendungen der analytischen Methoden in der modernen experimentellen Biologie befassen.
Skript529-1042-00
Ein umfangreiches Skript ist im HCI-Shop erhältlich. Eine Kurzfassung des Teils "Spektroskopie" definiert die für die Prüfung dieses Teils relevanten Themen.
Literatur529-1042-00
- Pretsch E., Bühlmann P., Badertscher M. Structure Determination of Organic Compounds, 5th revised and enlarged English edition, Springer-Verlag, Berlin 2009;
- Pretsch E., Bühlmann P., Badertscher M., Spektroskopische Daten zur Strukturaufklärung organischer Verbindungen, fünfte Auflage, Springer-Verlag, Berlin 2010;
- D.A. Skoog, J.J. Leary, Instrumentelle Analytik, Grundlagen, Geräte, Anwendungen, Springer, Berlin, 1996;
- K. Cammann, Instrumentelle Analytische Chemie, Verfahren, Anwendungen, Qualitätssicherung, Spektrum Akademischer Verlag, Heidelberg, 2001;
- R. Kellner, J.-M. Mermet, M. Otto, H.M. Widmer, Analytical Chemistry, Wiley-VCH Verlag, Weinheim, 1998;
- K. Robards, P.R.Haddad, P.E. Jackson, Principles and practice of modern chromatographic methods, Academic Press, London, 1994;
Voraussetzungen / Besonderes529-1042-00
Voraussetzungen:
- 529-1001-01 V "Allgemeine Chemie I (für Biol./Pharm.Wiss.)"
- 529-1001-00 P "Allgemeine Chemie I (für Biol./Pharm.Wiss.)"
- 529-1011-00 G "Organische Chemie I (für Biol./Pharm.Wiss.)"
3. Studienjahr, 5. Semester
Blockkurse
Anmeldung zu Blockkursen muss zwingend über die website https://www.uzh.ch/zoolmed/ssl-dir/Blockkurse_UNIETH.php erfolgen. Anmeldung möglich von 24.7.2017 bis 6.8.2017.
Blockkurse im 2. Semesterviertel
Von 12.10.2017 08:00 Uhr bis 3.11.2017 17:00 Uhr
NummerTitelTypECTSUmfangDozierende
551-1201-00LComputational Methods in Genome and Sequence Analysis Belegung eingeschränkt - Details anzeigen
Number of participants limited to 5.

The enrolment is done by the D-BIOL study administration.
W6 KP7GA. Wutz
KurzbeschreibungThis course aims to provide students with a comprehensive overview of computational methods for sequence analysis and assist with developing skills for application of computational approaches by experimental scientists in the life sciences.
LernzielMethods for analyzing animal genomes are increasingly becoming important for applications in human health and biotechnology suggesting that the experience will be useful to develop relevant expertise for a broad range of functions. Students will have the opportunity to advance their knowledge in programming by focusing on algorithms for genome and gene sequence analysis. A major goal of the course will be to lead the student to an independent and empowered attitude towards computational problems. For reaching this goal the students will work on an implementation of a solution for a set real-world problem in genome and sequence analysis under guided supervision.
Inhalt•Understanding the information in biological sequences and quantifying similarity
•Introduction to algorithms for sequence comparison and searches
•Implementation of sequence comparisons and searches in Python
•Accessing data formats associated with genome sequence analysis tasks
•Understanding the anatomy of a real world sequence analysis project
•Applying tools for sequence alignment and estimating error rates
•Ability to implement a solution to a problem in sequence analysis using Python
•Accessing genome annotation and retrieving relevant information in Pandas
•Application of Genomic intervals and arrays for sequence analysis with HTSeq

The course will consist of a series of lectures, assignments for implementing elementary tasks in Python, project development and discussion workshops, and 3 and a half week of practical work implementing a Pythons script as a solution to a real world problem associated with sequence analysis. At the end of the course students will explain their solutions and demonstrate the functionality of their implementations, which will then be discussed and commented on by the group. It is expected that students will be able to apply the knowledge to improve on concrete problems.
Voraussetzungen / Besonderes- It is recommended to bring your own computer with a Python installation to the course
- simple computers can be provided
- Programming basics with Python
Blockkurse im 4. Semesterviertel
Von 30.11.2017 08:00 Uhr bis 22.12.2017 17:00 Uhr
NummerTitelTypECTSUmfangDozierende
551-1417-00LIn Vivo Cryo-EM Analysis of Dynein Motor Proteins Belegung eingeschränkt - Details anzeigen
Number of participants limited to 3.

The enrolment is done by the D-BIOL study administration.
W6 KP7GT. Ishikawa
KurzbeschreibungMotor proteins convert chemical energy into mechanical motion. In this block course, we study dynein motor proteins in cilia. Dynein causes conformational change upon ATP hydrolysis and finally generate ciliary bending motion. Participants will analyze cryo-EM data of cilia and visualize in vivo 3D structure of dynein to learn how motor proteins function in the cell.
LernzielThe goal of this course is to be familiar with structural biology techniques of cryo-electron tomography and single particle cryo-EM studies on motor proteins. The main focus is 3D image analysis of cryo-EM datasets acquired by highest-end microscopes. Participants will learn structure-function relationship at various scales: how the conformational change of motor proteins causes mechanical force and generates cellular motility.
InhaltMotor proteins, such as dynein, myosin and kinesin, hydrolyze ATP to ADP and phosphate to convert chemical energy to mechanical motion. Their function is essential for intracellular transport, muscle contraction and other cellular motility as well as cell division. Motor proteins have been major targets of biophysical studies. There exist questions from atomic to tissue levels – how ATP hydrolysis causes conformational change of motor proteins; how their motion is regulated by calcium, phosphorylation and other factors; how motions of multiple motor proteins are coordinated to generate cellular motility. Structural biology has been playing central roles to answer these questions. X-ray crystallography and single particle cryo-EM address structural analysis at atomic resolution and try to reveal molecular mechanism of conformational change. Cryo-electron tomography analyze localization and 3D structure of motor proteins in the cell to explain how motions of molecular motors happen in the context of cellular environment and are integrated into cellular motion.
In this course, we study dyneins in cilia. Cilia are force-generating organelles, made by nine microtubules and thousands of dyneins. Dynein hydrolyzes ATP and undergoes conformational change, generating linear motion with respect to the microtubule. As a whole system, cilia integrate motions of these dyneins and orchestrate beating motion. To explain ciliary motion at molecular level, we need to know dynein conformational change in the cellular context. Cryo-electron tomography is recently developed technique to study molecular structures in vivo and therefore a suitable method to study dynein in cilia. Recently spatial resolution of these cryo-EM techniques was dramatically improved, driven by development of new types of detectors and electron optics.
The participants of this course will learn a program to analyze cryo-electron tomography and single particle cryo-EM data, acquired by highest-end electron microscopes and detectors in ETH and other places, and reconstruct 3D structure (tomogram) of cilia from various organisms (from green algae to human). They will further learn a program to study molecular structures from these tomograms (called subtomogram averaging) and apply it to reconstruct high-resolution 3D structure of dyneins, microtubules and regulatory proteins. This practical course is therefore mainly computational, but we will also provide students a chance of cilia preparation from green algae, cryo-EM data collection using an electron microscope in PSI and site-visit of highest-end electron microscope facility in ETH.
SkriptScripts will be distributed during the course.
LiteraturAn overview is given in the following review articles. Further literature will be indicated during the course.
Ishikawa (2017) “Axoneme structure from motile cilia” Cold Spring Harb. Perspect Biol. 9. doi: 10.1101/cshperspect.a028076.
Ishikawa (2017) “Cryo-electron tomography of motile cilia and flagella” Cilia 4, 3. doi: 10.1186/s13630-014-0012-7.
Biologie Master Information
Wahlvertiefungen
Wahlvertiefung: Ökologie und Evolution
Wahlpflicht Masterkurse
NummerTitelTypECTSUmfangDozierende
401-0625-01LApplied Analysis of Variance and Experimental Design Information W5 KP2V + 1UL. Meier
KurzbeschreibungPrinciples of experimental design, one-way analysis of variance, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs, random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.
LernzielParticipants will be able to plan and analyze efficient experiments in the fields of natural sciences. They will gain practical experience by using the software R.
InhaltPrinciples of experimental design, one-way analysis of variance, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs, random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.
LiteraturG. Oehlert: A First Course in Design and Analysis of Experiments, W.H. Freeman and Company, New York, 2000.
Voraussetzungen / BesonderesThe exercises, but also the classes will be based on procedures from the freely available, open-source statistical software R, for which an introduction will be held.
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