Search result: Catalogue data in Spring Semester 2015
Computer Science Master ![]() | ||||||
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Number | Title | Type | ECTS | Hours | Lecturers | |
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252-0312-00L | Ubiquitous Computing ![]() | W | 3 credits | 2V | F. Mattern | |
Abstract | Ubiquitous computing integrates tiny wirelessly connected computers and sensors into the environment and everyday objects. Main topics: The vision of ubiquitous computing, trends in technology, smart cards, RFID, Personal Area Networks (Bluetooth), sensor networks, location awareness, privacy and security, application areas, economic and social impact. | |||||
Objective | The vision of ubiquitous computing, trends in technology, smart cards, RFID, Personal Area Networks (Bluetooth), sensor networks, location awareness, privacy and security, application areas, economic and social impact. | |||||
Lecture notes | Copies of slides will be made available | |||||
Literature | Will be provided in the lecture. To put you in the mood: Mark Weiser: The Computer for the 21st Century. Scientific American, September 1991, pp. 94-104 | |||||
252-0807-00L | Information Systems Laboratory ![]() ![]() Number of participants limited to 16. In the Master Programme max. 10 credits can be accounted by Labs on top of the Interfocus Courses. These Labs will only count towards the Master Programme. Additional Labs will be listed on the Addendum. | W | 10 credits | 9P | M. Norrie | |
Abstract | The purpose of this laboratory course is to practically explore modern techniques to build large-scale distributed information systems. Participants will work in groups of three or more students, and develop projects in several phases. | |||||
Objective | The students will gain experience of working with technologies used in the design and development of information systems. | |||||
Content | First week: Kick-off meeting and project assignment Second week: Meeting with the project supervisor to discuss the goals and scope of the project. During the semester: Individual group work. Each team member should contribute to the project roughly about 10h/week, excluding any necessary reading or self-studying (e.g. the time spent to learn a new technology). In addition, it is expected that each team can meet with their supervisor on a regular basis. End of semester: Final presentation. | |||||
252-0817-00L | Distributed Systems Laboratory ![]() In the Master Programme max. 10 credits can be accounted by Labs on top of the Interfocus Courses. Additional Labs will be listed on the Addendum. | W | 10 credits | 9P | G. Alonso, F. Mattern, T. Roscoe, R. Wattenhofer | |
Abstract | This course involves the participation in a substantial development and/or evaluation project involving distributed systems technology. There are projects available in a wide range of areas: from web services to ubiquitous computing including as well wireless networks, ad-hoc networks, and distributed application on mobile phones. | |||||
Objective | Students acquire practical knowledge about technologies from the area of distributed systems. | |||||
Content | This course involves the participation in a substantial development and/or evaluation project involving distributed systems technology. There are projects available in a wide range of areas: from web services to ubiquitous computing including as well wireless networks, ad-hoc networks, and distributed application on mobile phones. The objecte of the project is for the students to gain hands-on-experience with real products and the latest technology in distributed systems. There is no lecture associated to the course. For information of the course or projects available, please contact Prof. Mattern, Prof. Wattenhofer, Prof. Roscoe or Prof. G. Alonso. | |||||
263-3501-00L | Advanced Computer Networks ![]() | W | 5 credits | 2V + 2U | T. Roscoe, P. M. Stüdi | |
Abstract | This course covers a set of advanced topics in computer networks. The focus is on principles, architectures, and protocols used in modern networked systems, such as the Internet itself, wireless and mobile networks, and large-scale peer-to-peer systems. | |||||
Objective | The goals of the course is to build on basic networking course material in providing an understanding of the tradeoffs and existing technology in building large, complex networked systems, and provide concrete experience of the challenges through a series of lab exercises. | |||||
Content | The focus of the course is on principles, architectures, and protocols used in modern networked systems. Topics include: wireless networks and mobility issues at the network and transport layer (Mobile IP and micromobility protocols, TCP in wireless environments). Mobile phone networks. Overlay networks, flat routing protocols (DHTs), and peer-to-peer architectures. The Border Gateway Protocol (BGP) in practice. | |||||
263-3700-00L | User Interface Engineering ![]() | W | 4 credits | 2V + 1U | O. Hilliges | |
Abstract | An in-depth introduction to the core concepts of post-desktop user interface engineering. Current topics in UI research, in particular non-desktop based interaction, mobile device interaction, augmented and mixed reality, and advanced sensor and output technologies. | |||||
Objective | Students will learn about fundamental aspects pertaining to the design and implementation of modern (non-desktop) user interfaces. Students will understand the basics of human cognition and capabilities as well as gain an overview of technologies for input and output of data. The core competency acquired through this course is a solid foundation in data-driven algorithms to process and interpret human input into computing systems. At the end of the course students should be able to understand and apply advanced hardware and software technologies to sense and interpret user input. Students will be able to develop systems that incorporate non-standard sensor and display technologies and will be able to apply data-driven algorithms in order to extract semantic meaning from raw sensor data. | |||||
Content | User Interface Engineering covers theoretical and practical aspects relating to the design and implementation of modern non-standard user interfaces. A particular area of interest are machine-learning based algorithms for input recognition in advanced non-desktop user interfaces, including UIs for mobile devices but also Augmented Reality UIs, gesture and multi-modal user interfaces. The course covers three main areas: I) Basic principles of human cognition and perception (and their application for UIs) II) (Hardware) technologies for user input sensing III) Data-driven methods for input recognition (gestures, speech, etc.) Specific topics include: * Model Human Processor (MHP) model - prediction of task completion times. * Fitts' Law - measure of information load on human motor and cognitive system during user interaction. * Touch sensor technologies (capacitive, resistive, force sensing etc). * Data-driven algorithms for user input recognition: - SVMs for classification and regression - Randomized Decision Forests for gesture recognition and pose estimation - Markov chains and HMMs for gesture and speech recognition - Optical flow and other image processing and computer vision techniques - Input filtering (Kalman) * Applications of the above in HCI research | |||||
Lecture notes | Slides and other materials will be available online. Lecture slides on a particular topic will typically not be made available prior the completion of that lecture. | |||||
Literature | A detailed reading list will be made available on the course website. | |||||
Prerequisites / Notice | Prerequisites: proficiency in a programming language such as C, programming methodology, problem analysis, program structure, etc. Normally met through an introductory course in programming in C, C++, Java. The following courses are strongly recommended as prerequisite: * "Human Computer Interaction" * "Machine Learning" * "Visual Computing" or "Computer Vision" The course will be assessed by a written Midterm and Final examination in English. No course materials or electronic devices can be used during the examination. Note that the examination will be based on the contents of the lectures, the associated reading materials and the exercises. |
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