Search result: Catalogue data in Autumn Semester 2024
Integrated Building Systems Master  | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 401-0647-00L | Introduction to Mathematical Optimization | W | 5 credits | 2V + 1U | D. Adjiashvili | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Introduction to basic techniques and problems in mathematical optimization, and their applications to a variety of problems in engineering. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The goal of the course is to obtain a good understanding of some of the most fundamental mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. The students will also practice applying the learned models to problems in engineering. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Topics covered in this course include: - Linear programming (simplex method, duality theory, shadow prices, ...). - Basic combinatorial optimization problems (spanning trees, shortest paths, network flows, ...). - Modelling with mathematical optimization: applications of mathematical programming in engineering. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Information about relevant literature will be given in the lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course is meant for students who did not already attend the course "Linear & Combinatorial Optimization", which is a more advance lecture covering similar topics. Compared to "Linear & Combinatorial Optimization", this course has a stronger focus on modeling and applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 227-0477-00L | Acoustics I | W | 3 credits | 2G | R. Pieren | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Introduction to the fundamentals of acoustics in the field of sound field calculations, measurement of acoustical events, outdoor sound propagation and room acoustics of large and small enclosures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Understanding of the basic acoustical concepts and methods. Ability to understand the technical and scientific literature. Confidence in the use of measuring instruments. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Fundamentals of acoustics, calculation of sound fields, measurement and analysis of acoustical events, anatomy and properties of the ear, outdoor sound propagation, absorption and transmission of sound, room acoustics of large and small enclosures, noise and noise control. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 101-0577-00L | An Introduction to Sustainable Development in the Built Environment | W | 3 credits | 2G | G. Habert, A. Komkova | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | In 2015, the UN Conference in Paris shaped future world objectives to tackle climate change. This decarbonization strategy is additional to Sustainable Development goals formulated the same year by the UN general assembly. What does that mean for the built environment? This course provides an introduction to the notion of sustainable development when applied to our built environment. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | At the end of the semester, the students have an understanding of the term of sustainable development, its history, the current political and scientific discourses and its relevance for our built environment. In order to address current challenges of climate change mitigation and resource depletion, students will learn a holistic approach of sustainable development. Ecological, economical and social constraints will be presented and students will learn about methods for argumentation and tools for assessment (i.e. life cycle assessment). For this purpose an overview of sustainable development is presented with an introduction to the history of sustainability and its today definition as well as the role of cities, urbanisation and material resources (i.e. energy, construction material) in social economic and environmetal aspects. The course aims to promote an integral view and understanding of sustainability and describing different spheres (social/cultural, ecological, economical, and institutional) that influence our built environment. Students will acquire critical knowledge and understand the role of involved stakeholders, their motivations and constraints, learn how to evaluate challenges, identify deficits and define strategies to promote a more sustainable construction. Notion of environmental justice and regenerative practices will be addressed. After the course students should be able to define the relevance of specific local, regional or territorial aspects to achieve coherent and applicable solutions toward sustainable development. The course offers an environmental, socio-economic and socio-technical perspective focussing on buildings, cities and their transition to resilience with sustainable development. Students will learn on theory and application of current scientific pathways towards sustainable development. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The following topics give an overview of the themes that are to be worked on during the lecture. - Overview on the history and emergence of sustainable development - Overview on the current understanding and definition of sustainable development and beyond Methods - Method 1: Life cycle assessment (planning, construction, operation/use, deconstruction) - Method 2: Life Cycle Costing - Method 3: Labels and certification - Method 4: Material Flow Analysis Main issues: - Operation energy at building, urban and national scale - Mobility and density questions - Embodied energy for developing and developed world Values: limits efficiency environmental justice regeneration - Synthesis: Transition to sustainable development | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | All relevant information will be online available before the lectures. For each lecture slides of the lecture will be provided. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | A list of the basic literature will be offered on a specific online platform, that could be used by all students attending the lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 101-0417-00L | Transport Planning Methods | W | 6 credits | 4G | E. Heinen | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course provides the necessary knowledge to develop models to understand, to support and to evaluate the solution of given planning problems. The course is composed of a lecture part, providing the theoretical knowledge, and an applied part in which students develop their own models in order to evaluate a transport project/policy. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | - Appraise the role of theory and data in transport planning - Differentiate and appraise different transport planning methods (causality, 4 stage and agent based modeling, cost-benefit analysis) - Construct a transport model by statistical methods and algorithms commonly used in transport planning - Propose a modeling framework to analyze transport planning challenges. a decision-making supporting tool | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course provides the necessary knowledge to develop models to understand travel behaviour and travel demand, and to support the solution of given planning problems. It also introduces cost-benefit analysis as a decision-making tool. Examples of such planning problems are the estimation of traffic volumes, prediction of estimated utilization of new public transport lines, and evaluation of effects (e.g. change in emissions of a city) triggered by building new infrastructure and changes to operational regulations. To cope with that, the problem is divided into sub-problems, which are solved using various statistical models and algorithms. The course is composed of a lecture part, providing the theoretical knowledge, and an applied part in which students develop their own models in order to analyse travel behaviour, develop a traditional transport model and to evaluate a transport project/ policy by means of cost-benefit analysis. Regular lab session take place to guide and support students with the applied part of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Moodle platform (enrollment needed) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Willumsen, P. and J. de D. Ortuzar (2024) Modelling Transport, Wiley, Chichester. Van Wee, B., Annema, J.A., Banister, D. and Pudāne, B. (2023) The Transport System and Transport Policy, An Introduction. Second Edition. Cheltenham, UK • Northampton, MA, USA Pearl, J., Glymour, M., and Jewell N.P. (2016) Causal Inference in Statistics. Wiley and Sons. Cascetta, E. (2001) Transportation Systems Engineering: Theory and Methods, Kluwer Academic Publishers, Dordrecht. Sheffi, Y. (1985) Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods, Prentice Hall, Englewood Cliffs. Other: Schnabel, W. and D. Lohse (1997) Verkehrsplanung, 2. edn., vol. 2 of Grundlagen der Strassenverkehrstechnik und der Verkehrsplanung, Verlag für Bauwesen, Berlin. McCarthy, P.S. (2001) Transportation Economics: A case study approach, Blackwell, Oxford. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 363-0387-00L | Corporate Sustainability | W | 3 credits | 2G | V. Hoffmann, C. Bening-Bach, B. Girod, L. Miehé | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The lecture explores current challenges of corporate sustainability and prepares students to become champions for sustainable business practices. The module combines asynchronous videos, live sessions, with a group work phase between weeks 5-10 of semester during which students deep-dive into one of 10 sustainability challenges. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students - assess the limits and the potential of corporate sustainability for sustainable development - develop competencies that are useful in the context of corporate sustainability and beyond (analytical competency, critical thinking, problem solving) - recognize and realize opportunities through team work for corporate sustainability in a business environment - present strategic recommendations in teams | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Corporate Sustainability is the flagship course of the Group for Sustainability and Technology at D-MTEC. In this course, students learn about key concepts in corporate sustainability and develop skills to implement them in the real world. The course prepares students for making well-informed sustainability decisions in their future careers. The course uses constructive alignment to bring the various innovative teaching and learning elements (e.g., case-based experiential learning, reflective thinking and blended learning with videos and quizzes) into a coherent transformational journey. Students can now flexibly, efficiently, and effectively acquire the conceptual foundations that are essential for a substantial understanding of corporate sustainability. For part of the course, students work in groups to complete a set of graded assignments designed to guide them into a deep dive on a selected corporate sustainability challenge. Please note that full participation in this part is essential, so make sure you are available. Furthermore, these group assignments count towards the overall grade for the course. For further details on the course structure etc. visit the following link: http://www.sustec.ethz.ch/teaching/lectures/corporate-sustainability.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Presentation slides will be made available on Moodle after lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Literature recommendations will be distributed via Moodle, and are available from the start of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | TEACHING FORMAT/ ATTENDANCE: The course includes several mandatory sessions that participants must attend to successfully earn credit points. It is not possible to take the class purely online | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 402-0809-00L | Introduction to Computational Physics | W | 8 credits | 2V + 2U | A. Adelmann | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course offers an introduction to computer simulation methods for physics problems and their implementation on PCs and super computers. The covered topics include classical equations of motion, partial differential equations (wave equation, diffusion equation, Maxwell's equations), Monte Carlo simulations, percolation, phase transitions, and N-Body problems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students learn to apply the following methods: Random number generators, Determination of percolation critical exponents, numerical solution of problems from classical mechanics and electrodynamics, canonical Monte-Carlo simulations to numerically analyze magnetic systems. Students also learn how to implement their own numerical frameworks in Julia and how to use existing libraries to solve physical problems. In addition, students learn to distinguish between different numerical methods to apply them to solve a given physical problem. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Introduction to computer simulation methods for physics problems. Models from classical mechanics, electrodynamics and statistical mechanics as well as some interdisciplinary applications are used to introduce modern programming methods for numerical simulations using Julia. Furthermore, an overview of existing software libraries for numerical simulations is presented. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture notes and slides are available online and will be distributed if desired. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Literature recommendations and references are included in the lecture notes. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Lecture and exercise lessons in english, exams in German or in English | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 101-0187-00L | Structural Reliability and Risk Analysis | W | 3 credits | 2G | S. Marelli | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Structural 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Engineers 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Slides 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Ang, 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Basic course on probability theory and statistics | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 701-1346-00L | Climate Change Mitigation: Carbon Dioxide Removal  | W | 3 credits | 2G | N. Gruber, C. Brunner | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Future climate change can only kept within reasonable bounds when CO2 emissions are drastically reduced. In this course, we will discuss a portfolio of options involving the alteration of natural carbon sinks and carbon sequestration. The course includes introductory lectures, presentations from guest speakers from industry and the public sector, and final presentations by the students. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The goal of this course is to investigate, as a group, a particular set of carbon mitigation/sequestration options and to evaluate their potential, their cost, and their consequences. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | From the large number of carbon sequestration/mitigation options, a few options will be selected and then investigated in detail by the students. The results of this research will then be presented to the other students, the involved faculty, and discussed in detail by the whole group. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | None | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Will be identified based on the chosen topic. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Exam: No final exam. Pass/No-Pass is assigned based on the quality of the presentation and ensuing discussion. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 363-0537-00L | Resource and Environmental Economics | W | 3 credits | 2G | A. Miftakhova, A. Minabutdinov | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Relationship between economy and environment, market failures, external effects and public goods, contingent valuation, internalisation of externalities, economics of non-renewable resources, economics of renewable resources, environmental cost-benefit analysis, sustainability economics, and international resource and environmental problems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | A successful completion of the course will enable a thorough understanding of the basic questions and methods of resource and environmental economics and the ability to solve typical problems using appropriate tools consisting of concise verbal explanations, diagrams or mathematical expressions. Concrete goals are first of all the acquisition of knowledge about the main questions of resource and environmental economics and about the foundation of the theory with different normative concepts in terms of efficiency and fairness. Secondly, students should be able to deal with environmental externalities and internalisation through appropriate policies or private negotiations, including knowledge of the available policy instruments and their relative strengths and weaknesses. Thirdly, the course will allow for in-depth economic analysis of renewable and non-renewable resources, including the role of stock constraints, regeneration functions, market power, property rights and the impact of technology. A fourth objective is to successfully use the well-known tool of cost-benefit analysis for environmental policy problems, which requires knowledge of the benefits of an improved natural environment. The last two objectives of the course are the acquisition of sufficient knowledge about the economics of sustainability and the application of environmental economic theory and policy at international level, e.g. to the problem of climate change. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course covers all the interactions between the economy and the natural environment. It introduces and explains basic welfare concepts and market failure; external effects, public goods, and environmental policy; the measurement of externalities and contingent valuation; the economics of non-renewable resources, renewable resources, cost-benefit-analysis, sustainability concepts; international aspects of resource and environmental problems; selected examples and case studies. After a general introduction to resource and environmental economics, highlighting its importace and the main issues, the course explains the normative basis, utilitarianism, and fairness according to different principles. Pollution externalities are a deep core topic of the lecture. We explain the governmental internalisation of externalities as well as the private internalisation of externalities (Coase theorem). Furthermore, the issues of free rider problems and public goods, efficient levels of pollution, tax vs. permits, and command and control instruments add to a thorough analysis of environmental policy. Turning to resource supply, the lecture first looks at empirical data on non-renewable natural resources and then develops the optimal price development (Hotelling-rule). It deals with the effects of explorations, new technologies, and market power. When treating the renewable resources, we look at biological growth functions, optimal harvesting of renewable resources, and the overuse of open-access resources. A next topic is cost-benefit analysis with the environment, requiring measuring environmental benefits and measuring costs. In the chapter on sustainability, the course covers concepts of sustainability, conflicts with optimality, and indicators of sustainability. In a final chapter, we consider international environmental problems and in particular climate change and climate policy. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Perman, R., Ma, Y., McGilvray, J, Common, M.: "Natural Resource & Environmental Economics", 4th edition, 2011, Harlow, UK: Pearson Education | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 363-0565-00L | Principles of Macroeconomics | W | 3 credits | 2V | J.‑E. Sturm, E. Baselgia | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course examines the behaviour of macroeconomic variables, such as gross domestic product, unemployment and inflation rates. It tries to answer questions like: How can we explain fluctuations of national economic activity? What can economic policy do against unemployment and inflation? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This lecture will introduce the fundamentals of macroeconomic theory and explain their relevance to every-day economic problems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | This course helps you understand the world in which you live. There are many questions about the macroeconomy that might spark your curiosity. Why are living standards so meagre in many African countries? Why do some countries have high rates of inflation while others have stable prices? Why have some European countries adopted a common currency? These are just a few of the questions that this course will help you answer. Furthermore, this course will give you a better understanding of the potential and limits of economic policy. As a voter, you help choose the policies that guide the allocation of society's resources. When deciding which policies to support, you may find yourself asking various questions about economics. What are the burdens associated with alternative forms of taxation? What are the effects of free trade with other countries? How does the government budget deficit affect the economy? These and similar questions are always on the minds of policy makers. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The course Moodle page contains announcements, course information and lecture slides. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | The set-up of the course will closely follow the book of N. Gregory Mankiw and Mark P. Taylor (2023), Economics, Cengage Learning, 6th Edition. This book can also be used for the course '363-0503-00L Principles of Microeconomics' (Filippini). Besides this textbook, the slides, lecture notes and problem sets will cover the content of the lecture and the exam questions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 252-0839-00L | Informatics | W | 2 credits | 2G | M. Dahinden, L. E. Fässler | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Students learn to apply selected concepts and tools from computer science for working on interdisciplinary projects. The following topics are covered: modeling and simulations, managing data with lists, tables and relational databases, introduction to programming. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The students learn to... - choose and apply appropriate tools from computer science, - process and analyze real-world data from their subject of study, - handle the complexity of real-world data, - query databases and understand and evaluate the corresponding database model, - encode a problem into a program, test the program, and correct errors, - implement models from the natural sciences as a simulation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | 1. Modeling and simulations 2. Data management with lists and tables 3. Data management with a relational database 4. Introduction to programming with Python 1 (variables & data types) 5. Introduction to programming with Python 2 (control structures & logic) 6. Introduction to programming with Python 3 (sequential data structures) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | All materials for the lecture are available at www.evim.ethz.ch | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | L. Fässler, M. Dahinden, D. Komm, and D. Sichau: Einführung in die Programmierung mit Python. Begleitunterlagen zum Onlinekurs und zur Vorlesung, 2022. ISBN: 978-3-7562-1004-6. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course is based on application-oriented learning. The students spend most of their time working through projects with data from natural science and discussing their results with teaching assistants. To learn the computer science basics there are electronic tutorials available. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 101-0007-00L | Project Management for Construction Projects | W | 4 credits | 3S | B. Hofer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course is designed to lay down the foundation of the different concepts, techniques, and tools for successful project management of construction projects. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The goal is that at the end of this course students should have a good understanding of the different project management knowledge areas, the phases required for successful project management, and the role of a project manager. To demonstrate this, students will work in groups in different case studies to apply the concepts, tools and techniques presented in the class. Two 3 to 4 hours sessions towards the end of the lecture series will introduce a practical project to allow the teams to demonstrate the tools and techniques learned during the semester. The course will have a final quiz that will be graded. The course will be supported by several external lecturers from the construction industry and demonstrations of real-life case studies. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The main content of the course is summarized in the following topics: - Introduction, project and organization structures - Project scheduling - Resource management - Risk management - Project estimating and budgeting - Project financing and Public-Private Partnerships (PPP) - Construction Process management and controlling - Sustainability management - Reporting and Communication - Interpersonal skills and leadership in Construction projects - Advanced Topics in Construction Project management (BIM / 5D planning, KI) - Project Evaluation and Closure | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The slides for the class will be available for download from Moodle at least one day before each class. Copies of all necessary documents will be distributed at appropriate times. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Relevant readings will be recommended throughout the course (and made available to the students via Moodle). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The students will be randomly assigned to teams. Students will be graded as a team based on the final Project proposal with the in-class oral presentation as well as a final exam (50% exam and 50% project). Homework will not be graded but your final report and presentation will consist mostly of your homework assignments consolidated and put in a report and presentation format. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 376-1177-00L | Human Factors I | W | 3 credits | 2V | M. Menozzi Jäckli | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Strategies of human-system-interaction, individual needs, physical & mental abilities, and system properties are key factors affecting the quality and performance in interaction processes. In the lecture, factors are investigated by basic scientific approaches. Discussed topics are important for optimizing people's health, well-being, and satisfaction as well as the overall system performance. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The goal of the lecture is to empower students in better understanding the applied theories, principles, and methods in various applications. Students are expected to learn about how to enable an efficient and qualitatively high standing interaction between human and the environment, considering costs, benefits, health, and safety as well. Thus, an ergonomic design and evaluation process of products, tasks, and environments may be promoted in different disciplines. The goal is achieved in addressing a broad variety of topics and embedding the discussion in macroscopic factors such as the behavior of consumers and objectives of economy. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | - Physiological, physical, and cognitive factors in sensation, perception, and action - Body spaces and functional anthropometry, Digital Human Models - Experimental techniques in assessing human performance, well-being, and comfort - Usability engineering in system designs, product development, and innovation - Human information processing and biological cybernetics - Interaction among consumers, environments, behavior, and tasks | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | - Gavriel Salvendy, Handbook of Human Factors and Ergonomics, 4th edition (2012), is available on NEBIS as electronic version and for free to ETH students - Further textbooks are introduced in the lecture - Brouchures, checklists, key articles etc. are uploaded in ILIAS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 103-0569-00L | European Aspects of Spatial Development | W | 3 credits | 2G | A. Peric Momcilovic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Following the insight into historical perspective and contemporary models of governance and planning, the course focuses on the international dimension of spatial planning in Europe. This includes a discussion of how European spatial policy is made and by whom, how planners can participate in such process and how they can address transnational challenges of spatial development cooperatively. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Keeping the general aim of exploring the European dimension of spatial planning in mind, the specific course learning objectives are as follows: - to interpret the history of spatial planning at the transnational scale - to understand and explain the content of the European spatial policy agenda - to describe and analyse the role of territorial cooperation in making European spatial development patterns and planning procedures - to discuss the changing role of planners and evaluate the ways of their engagement in European spatial policy-making | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | - European spatial policy agenda: introduction and basic directives - governance models - planning models; collaborative planning model (main concepts & critics) - post-positivist approach to spatial planning - transnational spatial planning in Europe; questioning the European spatial planning; spatial development trends in Europe - EU as a political system: EU institutions & non-EU actors - planning families in Europe; the European spatial planning agenda - spatial planning strategies and programmes on territorial cooperation - the notion of planning culture and planning system; planning cultures in Europe - basic characteristics of planning systems in Europe - the relevance of European transnational cooperation for spatial planning - European transnational initiatives | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The documents for the lecture will be provided at the moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Obligatory literature: - Dühr, S., Colomb, C. & Nadin, V. (2010). European Spatial Planning and Territorial Cooperation. London: Routledge. Recommended literature: Governance models: - Martens, K. (2007). Actors in a Fuzzy Governance Environment. In G. de Roo & G. Porter (Eds.), Fuzzy Planning: The Role of Actors in a Fuzzy Governance Environment (pp. 43-65). Abingdon, Oxon, GBR: Ashgate Publishing Group. Planning models: - Davoudi, S. & Strange, I. (2009). Conceptions of Space and Place in Strategic Spatial Planning. Abingdon, Oxon, GBR: Routledge. - Allmendinger, P. (2002). The Post-Positivist Landscape of Planning Theory. In P. Allmendinger & M. Tewdwr-Jones (Eds.), Planning Futures: New Directions for Planning Theory (pp. 3-17). London: Routledge. - Healey, P. (1997). Collaborative Planning - Shaping places in fragmented societies. London: MacMillan Press. EU as a political context: - Williams, R. H. (1996). European Union Spatial Policy and Planning. London: Sage. Territorial cooperation in Europe: - Dühr, S., Stead, D. & Zonneveld, W. (2007). The Europeanization of spatial planning through territorial cooperation. Planning Practice & Research, 22(3), 291-307. - Dühr, S. & Nadin, V. (2007). Europeanization through transnational territorial cooperation? The case of INTERREG IIIB North-West Europe. Planning Practice and Research, 22(3), 373-394. - Faludi, A. (Ed.) (2002). European Spatial Planning. Cambridge, Mass.: Lincoln institute of land policy. - Faludi, A. (2010). Cohesion, Coherence, Cooperation: European Spatial Planning Coming of Age? London: Routledge. - Faludi, A. (2014). EUropeanisation or Europeanisation of spatial planning? Planning Theory & Practice, 15(2), 155-169. - Kunzmann, K. R. (2006). The Europeanisation of spatial planning. In N. Adams, J. Alden & N. Harris (Eds.), Regional Development and Spatial Planning in an Enlarged European Union. Aldershot: Ashgate. Planning families and cultures: - Newman, P. & Thornley, A. (1996). Urban Plannning in Europe: international competition, national systems and planning projects. London: Routledge. - Knieling, J. & Othengrafen, F. (Eds.). (2009). Planning Cultures in Europe: Decoding Cultural Phenomena in Urban and Regional Planning. Aldershot: Ashgate. - Stead, D., de Vries, J. & Tasan-Kok, T. (2015). Planning Cultures and Histories: Influences on the Evolution of Planning Systems and Spatial Development Patterns. European Planning Studies, 23(11), 2127-2132. - Scholl, B. (Eds.) (2012). Spaces and Places of National Importance. Zurich: ETH vdf Hochschulverlag. Planning systems in Europe: - Nadin, V. & Stead, D. (2008). European Spatial Planning Systems, Social Models and Learning. disP - The Planning Review, 44(172), 35-47. - Commission of the European Communities. (1997). The EU compendium of spatial planning systems and policies. Luxembourg: Office for Official Publications of the European Communities. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Only for master students, otherwise a special permission by the lecturer is required. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0252-08L | Evidence-Based Design: Methods and Tools for Evaluating Architectural Design Particularly suitable for students of D-ARCH. | W | 3 credits | 2S | C. Hölscher, L. Aguilar Melgar, M. Gath Morad, L. Narvaez Zertuche, C. Veddeler, to be announced | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Students are taught a variety of analytic techniques that can be used to evaluate architectural design. The concept of evidence-based design is introduced, and complemented with theoretical background on space syntax and spatial cognition. This is a project-oriented course, students implement a range of methods on a sample project. The course is tailored for architecture design students. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The course aims to teach students how to evaluate a design project from the perspective of the end user. The concept of evidence-based design is introduced through a series of case studies. Students are given a theoretical background in space syntax and spatial cognition, with a view to applying this knowledge during the design process. The course covers a range of methods including visibility analysis, network analysis, conducting real-world observations, and virtual reality for architectural design. Students apply these methods to a case study of their choice, which can be at building or urban scale. For students taking a B-ARCH or M-ARCH degree, this can be a completed or ongoing design studio project. The course gives students the chance to implement the methods iteratively and explore how best to address the needs of the eventual end-user during the design process. The course is tailored for students studying for B-ARCH and M-ARCH degrees. As an alternative to obtaining D-GESS credit, architecture students can obtain course credit in "Vertiefungsfach" or "Wahlfach". | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0834-00L | Information Systems for Engineers | W | 4 credits | 2V + 1U | G. Fourny | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course provides the basics of relational databases from the perspective of the user. We will discover why tables are so incredibly powerful to express relations, learn the SQL query language, and how to make the most of it. The course also covers support for data cubes (analytics). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Do you want to be able to query your own data productively and efficiently in your future semester projects, bachelor's thesis, master thesis, or PhD thesis? Are you looking for something beyond the Python+Pandas hype? This courses teaches you how to do so as well as the dos and don'ts. This lesson is complementary with Big Data for Engineers as they cover different time periods of database history and practices -- you can take them in any order, even though it might be more enjoyable to take this lecture first. After visiting this course, you will be capable to: 1. Explain, in the big picture, how a relational database works and what it can do in your own words. 2. Explain the relational data model (tables, rows, attributes, primary keys, foreign keys), formally and informally, including the relational algebra operators (select, project, rename, all kinds of joins, division, cartesian product, union, intersection, etc). 3. Perform non-trivial reading SQL queries on existing relational databases, as well as insert new data, update and delete existing data. 4. Design new schemas to store data in accordance to the real world's constraints, such as relationship cardinality 5. Explain what bad design is and why it matters. 6. Adapt and improve an existing schema to make it more robust against anomalies, thanks to a very good theoretical knowledge of what is called "normal forms". 7. Understand how indices work (hash indices, B-trees), how they are implemented, and how to use them to make queries faster. 8. Access an existing relational database from a host language such as Java, using bridges such as JDBC. 9. Explain what data independence is all about and didn't age a bit since the 1970s. 10. Explain, in the big picture, how a relational database is physically implemented. 11. Know and deal with the natural syntax for relational data, CSV. 12. Explain the data cube model including slicing and dicing. 13. Store data cubes in a relational database. 14. Map cube queries to SQL. 15. Slice and dice cubes in a UI. And of course, you will think that tables are the most wonderful object in the world. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Using a relational database ================= 1. Introduction 2. The relational model 3. Data definition with SQL 4. The relational algebra 5. Queries with SQL Taking a relational database to the next level ================= 6. Database design theory 7. Databases and host languages 8. Databases and host languages 9. Indices and optimization 10. Database architecture and storage Analytics on top of a relational database ================= 12. Data cubes Outlook ================= 13. Outlook | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | - Lecture material (slides). - Book: "Database Systems: The Complete Book", H. Garcia-Molina, J.D. Ullman, J. Widom (It is not required to buy the book, as the library has it) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The lecture is hybrid, meaning you can attend with us in the lecture hall, or on Zoom, or watch the recordings on YouTube later. Exercise sessions are in presence. For non-CS/DS students only, BSc and MSc Elementary knowledge of set theory and logics Knowledge as well as basic experience with a programming language such as Pascal, C, C++, Java, Haskell, Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 052-0707-00L | Urban Design III | W | 2 credits | 2V | H. Klumpner, F. T. Salva Rocha Franco | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Students are introduced to a narrative of 'Urban Stories' through a series of three tools driven by social, governance, and environmental transformations in today's urbanization processes. Each lecture explores one city's spatial and organizational ingenuity born out of a particular place's realities, allowing students to transfer these inventions into a catalog of conceptual tools. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | How can students of architecture become active agents of change? What does it take to go beyond a building's scale, making design-relevant decisions to the city rather than a single client? How can we design in cities with a lack of land, tax base, risk, and resilience, understanding that Zurich is the exception and these other cities are the rule? How can we discover, set rather than follow trends and understand existing urban phenomena activating them in a design process? The lecture series produces a growing catalog of operational urban tools across the globe, considering Governance, Social, and Environmental realities. Instead of limited binary comparing of cities, we are building a catalog of change, analyzing what design solutions cities have been developing informally incrementally over time, why, and how. We look at the people, institutions, culture behind the design and make concepts behind these tools visible. Students get first-hand information from cities where the chair as a Team has researched, worked, or constructed projects over the last year, allowing competent, practical insight about the people and topics that make these places unique. Students will be able to use and expand an alternative repertoire of experiences and evidence-based design tools, go to the conceptual core of them, and understand how and to what extent they can be relevant in other places. Urban Stories is the basic practice of architecture and urban design. It introduces a repertoire of urban design instruments to the students to use, test, and start their designs. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Urban form cannot be reduced to physical space. Cities result from social construction, under the influence of technologies, ecology, culture, the impact of experts, and accidents. Urban un-concluded processes respond to political interests, economic pressure, cultural inclinations, along with the imagination of architects and urbanists and the informal powers at work in complex adaptive systems. Current urban phenomena are the result of urban evolution. The facts stored in urban environments include contributions from its entire lifecycle, visible in the physical environment, and non-physical aspects. This imaginary city exists along with its potentials and problems and with the conflicts that have evolved. Knowledge and understanding, along with a critical observation of the actions and policies, are necessary to understand the diversity and instability present in the contemporary city and understand how urban form evolved to its current state. How did cities develop into the cities we live in now? Urban plans, instruments, visions, political decisions, economic reasonings, cultural inputs, and social organization have been used to operate in urban settlements in specific moments of change. We have chosen cities that exemplify how these instruments have been implemented and how they have shaped urban environments. We transcribe these instruments into urban operational tools that we have recognized and collected within existing tested cases in contemporary cities across the globe. This lecture series will introduce urban knowledge and the way it has introduced urban models and operational modes within different concrete realities, therefore shaping cities. The lecture series translates urban knowledge into operational tools, extracted from cities where they have been tested and become exemplary samples, most relevant for understanding how the urban landscape has taken shape. The tools are clustered in twelve thematic clusters and three tool scales for better comparability and cross-reflection. The Tool case studies are compiled into a global urbanization toolbox, which we use as typological models to read the city and critically reflect upon it. The presented contents are meant to serve as inspiration for positioning in future professional life and provide instruments for future design decisions. In an interview with a local designer, we measure our insights against the most pressing design topics in cities today, including inclusion, affordable housing, provision of public spaces, and infrastructure for all. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The learning material, available via https://moodle-app2.let.ethz.ch/ is comprised of the following: - Toolbox 'Reader' with an introduction to the lecture course and tool summaries - Weekly exercise tasks - Infographics with basic information about each city - Quiz question for each tool - Additional reading material - Interviews with experts - Archive of lecture recordings For one-semester students, only a Research will be required. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | - Reading material will be provided throughout the semester. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 151-3209-00L | Engineering Design Optimization | W | 4 credits | 4G | K. Shea, T. Stankovic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course covers fundamentals of computational optimization methods in the context of engineering design. It develops skills to formally state and model engineering design tasks as optimization problems and select appropriate methods to solve them. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The lecture and exercises teach the fundamentals of optimization methods in the context of engineering design. After taking the course students will be able to express engineering design problems as formal optimization problems. Students will also be able to select and apply a suitable optimization method given the nature of the optimization model. They will understand the links between optimization and engineering design in order to design more efficient and performance optimized technical products. The exercises are MATLAB based. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | 1. Optimization modeling and theory 2. Unconstrained optimization methods 2. Constrained optimization methods - linear and non-linear 4. Direct search methods 5. Stochastic and evolutionary search methods 6. Multi-objective optimization | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | available on Moodle | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 101-0139-00L | Scientific Machine and Deep Learning for Design and Construction | W | 3 credits | 4G | B. Bickel, A. Müller, M. Piovarci | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course will present methods of scientific machine and deep learning (ML / DL) for applications in design and construction. After providing proper background on ML and the scientific ML (SciML) track, several applications of SciML together with their computational implementation during the design and construction process of the built environment are examined. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This course aims to provide a graduate-level introduction to machine learning, with a particular focus on scientific machine learning for applications in the design and construction phases of projects from architecture and civil engineering. Upon completion of the course, the students will be able to: 1. Understand main ML background theory and methods. 2. Assess a problem and apply ML and DL in a computational framework accordingly. 3. Incorporate scientific domain knowledge in the SciML process. 4. Define, plan, conduct and present a SciML project. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course will include theory and algorithms for SciML, programming assignments, as well as a final project assessment. The topics to be covered are: 1. Fundamentals of Machine and Deep Learning (ML / DL). 2. Incorporation of Domain Knowledge into ML and DL. 3. Generative AI and its applications. 4. ML training, validation and testing pipelines for academic and research projects. A comprehensive series of computer/lab exercises and in-class demonstrations will take place, providing a "hands-on" feel for the course topics. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The course script is composed by lecture slides, which are available online and will be continuously updated throughout the duration of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Suggested Reading: Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong Mathematics for Machine Learning K. Murphy. Machine Learning: a Probabilistic Perspective. MIT Press 2012 C. Bishop. Pattern Recognition and Machine Learning. Springer, 2007 S. Guido, A. Müller: Introduction to machine learning with python. O'Reilly Media, 2016 O. Martin: Bayesian analysis with python. Packt Publishing Ltd, 2016 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Familiarity with Python is advised. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 102-0327-01L | Implementation of Environmental and Other Sustainability Goals Master students in Environmental Engineering choosing module Ecological Systems Design are not allowed to enrol 102-0327-01 Advanced Environmental Assessments (2KP) as already included in 102-0307-01 Advanced Environmental, Social and Economic Assessments (5KP). | W | 2 credits | 2G | A. E. Braunschweig | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course teaches approaches and methods to identify, assess and manage environmental (mainly) and societal (to some extent) aspects in organisations. The course contains an introduction to the global ISO 14001 standard on environmental management, into the concept of ecobalance of organisations, and supply chain management, and a general view on how such approaches fit into a management system. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students will learn to - describe key sustainability problems of the current economic system and measuring units. - describe the management system of an organisation and how to develop a sustainability orientation - discuss approaches to measure environmental performance of an organisation, including 'organisational LCA' (Ecobalance) - explain the pros and cons of single score environmental assessment methods - apply life cycle costing - interpret stakeholder relations of an organisation - (if time allows) describe sustainable supply chain management and stakeholder management | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | - Sustainability problems of the current economic system and its measuring units; - The structure of a management system, and elements to integrate environmental management (ISO 14001) and social management (SA8000), especially into strategy development, planning, controlling and communication; - Sustainability Opportunities and Innovation for companies - The concept of 'continuous Improvement', and its application to environmental management - Life Cycle Costing, as part of Life Cycle Management - environmental performance measurement of an organisation, including 'organisational LCA' (Ecobalance), incl. practical examples of companies - single score environmental assessment methods, with a focus on the 'ecopoints' method - stakeholder management and sustainability oriented communication - an intro into sustainability issues of supply chain management Students will get small homework excercises to apply the course topics and methods issues. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Documents will be available on Ilias | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Will be made available. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course is meant for any interested student. (Students of ESD Ecological Systems Design should choose the combined "AESEA" course (102-0307-01), which is specifically offered and mandatory for their module and includes this course. Basic knowledge of environmental assessment tools is a prerequisite for this class. Students who have not yet had classwork in this topic will profit more from this course after reading an appropriate textbook before or at the beginning of this course, e.g. Jolliet, O et al. (2016). Environmental Life Cycle Assessment. CRC Press, Boca Raton - London - New York. ISBN 978-1-4398-8766-0 (Chapters 2-5.2). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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