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Erasmus Mundus Joint Doctoral Programme in Interactive and Cognitive Environments (EMJD ICE)
Syllabus and Academic Calendar 2012
Management Board
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
2
QMUL Courses 2012-2013
Code Hours Credits Title Teacher(s)
QMUL
01 22+22 5 ICE_QMUL_ELEM006: Multimedia Systems Prof. Andrea Cavallaro
02 30+4 5 ICE_QMUL_ELEM021: Music And Speech Processing
Prof. Elaine Chew
03 22+22 5 ICE_QMUL_ ELEM023: Image and Video Processing
Prof. Shaogang Gong
04 24+12 5 ICE_QMUL_ ELEM041: Machine Learning Dr. Ioannis Patras
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
3
TU/e
01 40 5 ICE_TU/e_DBD05: Complex Sensors Prof.dr. ir. J.B.O.S. Martens
02 40 5 ICE_TU/e_DB305: Persuasive Technology dr. H.A. van Essen, dr. M.M. Bekker
03 40 5 ICE_TU/e_ DB 617: Sensual Dynamics ir. E.J.L. Deckers, dr.ir. P.D. Levy
04 40 5 ICE_TU/e_DBB03: Qualitative Research
Methods for Interaction Design
Prof. Dr. ir. P. Markopoulos
05 40 5 DB214 Sense your heart Prof.dr. S. Bambang Oetomo, Prof. dr.ir. L.M.G. Feijs, dr. W.
Chen, dr. J. Hu, dr. ir. G.R. Langereis, G.J.A. van den
Boomen
TU/e Courses 2012-2013
Code Hours Credits Title Teacher(s)
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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UNIGE Courses 2012-2013
Code Hours Credits Title Teacher(s)
UNIGE
01 25 5 Data Fusion and Bayesian Interaction Modeling for Cognitive Ambient Intelligence
Prof. Carlo Regazzoni
02 20 5 Theory and Practice of Learning from Data Prof. Davide Anguita
03 20 5 Modeling, Simulation and Games Prof. Francesco Bellotti
04 20 5 Green Networking Prof. Raffaele Bolla
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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UNIKLU
01 30 5 Mobile and Wireless Communications
Prof. Christian Bettstetter
02
30 5 Pervasive Computing Prof. Bernhard Rinner
03
30
5 Mobile and Wireless Networking Prof. Christian Bettstetter
04 30 5 Sensor Networks Prof. Bernhard Rinner
05 30 5 Embedded Communications Prof. Mario Huemer
06 30 5 Interactive Systems Prof. Martin Hitz
07 30 5 Signal Processing Architectures Prof. Mario Huemer
08 30 5 Adaptive and Statistical Signal Processing Prof. Mario Huemer
09 30 5 Novel Topics in Digital Signal Processing for PhD Students
Prof. Mario Huemer
UNIKLU Courses 2012-2013
Code Hours Credits Title Teacher(s)
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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10 45 5 Special Doctorate Seminar NES Prof. Christian Bettstetter, Prof. Bernhard Rinner,
Prof. Martin Hitz, Prof. Mario Huemer
11 30 5 Research Paradigms in Computer Science Prof. Johann Eder
UNIKLU Courses 2012-2013
Code Hours Credits Title Teacher(s)
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
7
UPC
UPC Courses 2012-2013
Code Hours Credits Title Teacher(s)
01 125 5 Artificial Intelligence applied to Robotics
Prof. Andreu Català Prof.Cecilio Angulo
Prof. Francisco J. Ruiz
02 125 5 Artificial intelligence Applied to the Control and the Identification of Systems
Prof. Andreu Català Prof.Cecilio Angulo
Prof. Francisco J. Ruiz
03 30 1,2 Information Skills in Information Technologies
Prof. Conrado Martínez
04 150 5 Advanced Techniques in Machine Learning
Prof. Javier Bejar
05 150 5 Artificial Intelligence Aplications
Prof. Ulises Cortés
06 75 3 Artificial Intelligence Seminar
Prof. Miquel Sánchez Marré
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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QMUL Courses 2012-2013
ICE_QMUL_ELEM006: Multimedia Systems
Hours: 22 (lecture) + 22 (lab - optional) Credits: 5
Teacher(s): Andrea Cavallaro
Abstract:
The course aims to provide PhD Candidates with general knowledge about digital media, their integration and basic processing techniques used to generate multimedia systems. The course also aims to discuss important topics related to the creation of content description interfaces for large multimedia databases and inherent security and copyright aspects. This course will provide an understanding of multimedia, the creation, integration and processing of multimedia data and give a good overview about how state-of-the art multimedia systems are built and work. The course also gives a quick view on the most important standards for compression and coding of multimedia, as well as content description interfaces. The course begins by giving an overview of cutting-edge multimedia applications. This is followed by a detailed treatment of fundamental tasks involved in creating and processing multimedia information. Special underlying design requirements and coding aspects are then covered. In the following lectures some important areas of multimedia systems in the context of intellectual property protection and management are covered. Each student is required to complete a coursework consisting of the implementation of a specific multimedia application. To conduct this work, one supervised laboratory hour will be provided every week. The project will conclude with a demonstration of the implemented application.
Program:
Introduction to multimedia systems:
Integration of Natural Media (video and audio) into Synthetic Environments - Selected Applications. Augmented
and Virtual Reality. Immersive Telepresence. Teleshopping. 3D Videoconferencing. Medical Imaging.
Fundamentals of multimedia data:
Text, Audio, Images, Analog to Digital Conversion - Quantisation and Sampling, Noise Reduction, Filtering - low
and high pass filtering, nonlinear filtering, Feature enhancement and detection. Convulsion. Grey-scale images.
Colour spaces. Geometric transformations. Fourier Analysis
Multimedia content description:
Multimedia Content Description. Indexing and cataloguing. Video descriptors. Metrics in a descriptor space.
Population & Querying. Feature-based portals. The MPEG7 multimedia content description interface.
Coding, compression technologies and standards:
Coding fundamentals. Huffman and Arithmetic coding. The JPEG Standard. Motion compensated coding. Basic
segmentation techniques. Object based coding. Video Coding Standards - MPEG 1/2/4, H.26x.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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Intellectual property and multimedia protection:
Traditional methods of data protection - analogue and digital media. Copyright properties of digital multimedia.
Digital watermarking. Specific applications - example: distribution from a Library. Side information properties and
information theoretical aspects.
Bibliography:
Course notes
Further reading: 1. Handbook of Image and Video Processing by A. Bovik; Academic Press 2000; ISBN 0121197905
2. Computer Vision a Modern Approach by D. Forsythe and J. Ponce; Prentice Hall 2003; ISBN 0130851981
3. Video Coding: An Introduction to Standard Codecs, M. Ghanbari; IEE Publishing 1999; ISBN 0852967624
4. Digital Multimedia by N. Chapman and J. Chapman; Wiley 2000; ISBN 0471983861
5. Computer Vision by L.G. Shapiro and G.C. Stockman; Prentice Hall 2000; ISBN 0130307963
Contact: [email protected] Assessment: Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through an oral presentation.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_QMUL_ELEM021: Music And Speech Processing
Hours: 30 (lecture) + 4 (lab - optional) Credits: 5
Teacher(s): Elaine Chew
Abstract:
This course aims to introduce PhD Candidates to the application of Digital Signal Processing to Music and to Speech. By the end of the module the student will be able to:
Describe the physiology and physics involved in sound production and perception. Demonstrate how various fundamental concepts in Digital Signal Processing can be combined into systems, like a Digital Power Amplifier. Demonstrate how higher level processing components are constructed from lower level ones. Discuss how compressions of speech and of music, though similar, have different requirements. Propose specific compressors for specific applications. Identify latest innovations in this area involving delivery formats such as Internet and DVD. Position their acquired knowledge in a commercial context.
Program:
Human hearing, speech system, psychoacoustics, masking, Acoustics of musical instruments, Audio and Speech Standards, Wordlengths.
Speech technologies, Pitch estimation (voice), Source-filter model and LPC coding, Cepstrum, CELP, RELP, Waveform coders ADPCM, Delta Mod and others.
Music signal compression, MPEG1 (MP3) AAC.
Digital Audio Power Amplification, noise shaping, sigma-delta modulation, oversampled ADCs and DACs.
Digital Music in the 21st Century.
Bibliography:
Course notes Further reading:
1. Speech and Audio Signal Processing: Processing and Perception of Speech and Music by B.Gold and N.Morgan; John Wiley and Sons 1999; ISBN 0471351547
2. Speech Communications: Human and Machine by D.O'Shaughnessy; John Wiley & Sons Inc. 1999; ISBN 0780334493
3. Applications of Digital Signal Processing to Audio and Acoustics by M.Kahrs and K.Brandenburg; KAP 1998; ISBN 0792381300
Contact: elaine.chew/[email protected] Assessment: Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through an oral presentation.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_QMUL_ELEM023: Image and Video Processing
Hours: 22 (lecture) + 22 (lab - optional) Credits: 5
Teacher(s): Shaogang Gong
Abstract: This course aims to provide the PhD Candidates with knowledge of the most relevant image and video processing methods. The course also aims to discuss important topics related to the creation and manipulation of digital image and video content. Important aspects of standard transforms, compression and coding are also considered. This course provides fundamental knowledge about well established techniques for digital image and video processing. It covers mathematical models used to analyze still images, technology and standards for image and video compression and the basic methods used to design and develop a wide range of imaging solutions. Such solutions relate to the fields of machine vision, imaging graphics, pattern recognition, medical imaging, image and video coding.
Program: 1)Basic concepts Digital image representation. Sampling. Quantization. Colour spaces and colour images. Properties of digital images. Visual perception. Histograms. Image quality. Noise. 2) Global image transformations. Geometric transformations. Coordinate transformations. Histogram equalization. Sub-sampling and pixel interpolation. 3) Local image processing operators and filters. Convolution. Image smoothing and noise reduction. Low and high-pass filtering. Edge detectors. Variance based operators. Gaussian and Laplacian filters. The Canny operator. 4) Advanced filters for image processing. Median filter design. Morphological operators. Scale Space. Segmentation. Thresholding. Background detection. Chromakey techniques. Region growing. Split and merge techniques. Edge detection in scale space. Motion segmentation. 5) Video fundamentals. Video formats and standards. The optical flow. Motion estimation techniques. 6) Image and video coding, compression and standards. Coding fundamentals (FFT, DCT, Huffman and Arithmetic coding). The JPEG Standard. Wavelets and JPEG2000. Motion compensation. Object based coding
Bibliography:
Course notes Further reading:
1. Digital Image Processing by R.C. Gonzales and R.E.Woods; Prentice Hall; ISBN 0130946508
2. Handbook of Image Processing Operators by R. Klette and P. Zamperoni; Wiley 1996; ISBN 0471956422
3. Handbook of Image and Video Processing by A. Bovik; Academic Press 2000; ISBN 0121197905
4. Video Processing and Communications by Y. Wang, J. Ostermann and Y. Zhang; Prentice Hall; ISBN 0130175471
5. JPEG2000: Image Compression Fundamentals, Standards and Practice by D. Taubman and M. Marcellin; Kluwer 2002; ISBN 079237519X
Contact: [email protected] Assessment: Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through an oral presentation.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
12
ICE_QMUL_ELEM041: Machine Learning
Hours: 24 (lecture) + 12 (lab - optional) Credits: 5
Teacher(s): Dr. Ioannis Patras
Abstract: The aim of the course is to give PhD Candidates an understanding of machine learning methods, including pattern recognition, clustering and neural networks, and to allow them to apply such methods in a range of areas. This course covers methods for machine learning from signals and data, including statistical pattern recognition methods, neural networks, and clustering. By the end of the module the student will be able to: Recall a range of machine learning techniques and algorithms, including neural networks and statistical methods Use concepts from probability theory in machine learning Derive and analyse properties of machine learning methods Discuss the relative merits of different machine learning techniques and approaches Apply machine learning methods to the analysis of signals and data
Program:
Introduction to Machine Learning
Probability and Random Variables
Neural Networks
Statistical Inference
Clustering
Hidden Markov Models
Independent Component Analysis
Applications
Bibliography:
Course notes
Further reading:
1. Pattern Classification by Duda Hart and Stork; 2nd Edition; Wiley 2001; ISBN 0471056693
2. Probability Random Variables and Stochastic Processes by A. Papoulis; McGraw-Hill 2002; ISBN 0071199810
3. Neural Networks for Pattern Recognition by Bishop; OUP 1995; ISBN 0198538499
Contact: [email protected] Assessment: Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through an oral presentation.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
13
TU/e Courses 2012-2013
ICE_TU/e_DBD05: Complex Sensors
Hours: 40 Credits: 5
Teacher(s): Prof.dr. ir. J.B.O.S. Martens
Abstract: Ambient intelligence is based on the concept of context awareness, i.e., it assumes that the systems that surround us have access to information about identity, position, activity, etc. of the users that are present and of events that occur within the environment. Ambient Intelligence hence assumes complex sensing systems. Basic sensors are conceptually very easy because they are most often only required to signal the absence or presence of a single, a priori known, phenomenon (such as whether a light source is on or off). When discussing complex sensors, such as cameras with their accompanying image analysis software, or motion sensors, a more structured approach, using a mathematical framework, is needed. Complex sensors are not only general purpose, i.e., require little a priori knowledge of the phenomenon that they are monitoring, but also consist of many sub-sensors. These sub-sensors often have distinct characteristics and generate continuous (rather than on/off) responses. Making constructive use of these multiple simultaneous variations of a large set of sub-sensors requires a systematic approach. In this module we treat an approach that is based on using simple mathematical approximations to real signals to extract useful features (this approach reflects a special case of the more general mathematical theory of linear systems).
Program:
Basic insight into how mathematical models underlie complex sensing.
Insight into how the designer can influence the complexity of the sensing problem.
Experience with specific sensors and signal processing software.
Learning activities
This module is in the form of a workshop where students and lecturer together explore the basics of complex sensing, and the relevance for the design of intelligent (i.e., tangible or embodied) products. The module is run within the ConceptLab, so that theory can be practiced on real sensing data.
Bibliography:
Reader on Complex Sensors (Martens)
Contact: J.B.O.S. [email protected] Assessment: Report containing 1) description of your complex sensing problem, its relevance for design and the proposed algorithmic approach (including a discussion on feasibility, motivated by supporting material); 2) summary of your competency development within this module (target length of the report: 4-5 A4 in total).
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_TU/e_DB305: Persuasive Technology
Hours: 40 Credits: 5
Teacher(s): dr. H.A. van Essen, dr. M.M. Bekker
Abstract: Persuasion is the act of persuading someone to do or believe something. Persuasive Technology, by definition, is
technology that has the ability to persuade. Effective persuasion results in a change to a person縮 behaviour, attitudes or beliefs. This module introduces the foundations of persuasive design, i.e. the implementation of well-known persuasive principles in interactive technological products. The goal of this module is to provide the student with an understanding of existing theories and strategies for explicitly or implicitly motivating people to behave differently. The module explores how these ideas might be employed by the design of interactive products or environments to purposely effect behaviour change. Also the intention of the designer and the ethical aspects of influencing people by means of design are subject.
Program: Learning objectives in the module are to obtain an understanding of 1. Theories and frameworks of persuasion and behaviour change, in particular the functional triad from Fogg, the influence factors from Cialdini, the requirements framework from Oinas-Kukkonen, and prominent theories from social sciences. 2. Existing devices and environments that motivate behaviour change. 3. Mechanisms for identifying and exploiting persuasive influences. 4. The ethics of designing persuasive environments and technologies. 5. Methods for evaluating the effectiveness of a particular design for a persuasive environment or technology. Learning activities Analysis: Gaining insight in process of behavioral change and persuasive mechanisms by analyzing existing examples of persuasive technology in terms of the presented framework. Synthesis: Design or redesign a specific application of persuasive technology for a specific target group and a well defined behavior change, emphasizing the optimization of certain persuasive mechanisms, supported by ample analysis. Evaluation: Evaluate a persuasive design (of another team) by means of an expert evaluation, share the outcome and use the evaluation results to improve your own design
Bibliography:
Fogg, B.J. (2003). Persuasive Technology: Using Computers to Change What We Think and Do. San Francisco: Morgan Kaufmann.
Cialdini, Robert B. (2000) Influence: science and practice - 4th ed..
Oinas-Kukkonen, 2008] Oinas-Kukkonen, Harri and Harjumaa, Marja, A Systematic Framework for Designing and Evaluating Persuasive Systems, in Proceedings Persuasive 2008, LNCS 5033, pp164-176. http://www.tcw.utwente.nl/theorieenoverzicht/Theory%20clusters http://www.uri.edu/research/cprc/TTM/detailedoverview.htm
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Contact: M.M. [email protected] Assessment: Reports and presentations.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_TU/e_ DB 617: Sensual Dynamics
Hours: 40 Credits: 5
Teacher(s): ir. E.J.L. Deckers, dr.ir. P.D. Levy
Abstract:
Prior to interaction, there is perception. Perception is intrinsically rising from one縮 actions and from what one senses. These are the ways one is connected to and perceive the world. At this level, in direct contact with the world, there is no information, but energies (or forces). It is these forces that designers deal with when putting a new artefact in the world. This primacy of perception is the main focus of this module, proposing an approach to effectively taking them into consideration in the design process. For practical reasons, design should focus on qualities of senses. For example, touching is local, reciprocal, and private. Where I touch, I am touched by what I am touching, and nobody else can touch what I touch. On the other hand, smell is at a distance, possibly non-directional, and public. These are qualities of senses that can be dealt with in design. To do so, these qualities need to be explored, while taking into consideration static and dynamic situations. Finally, designers should comprehend these qualities and engage them in order to find opportunities for design how can I make something private at a distance? How can technology challenge these qualities (e.g. headphones make sound private)? What are the implications for design? and to explore them towards a concrete output.
Program: This module intends to elevate the students understanding about the senses and the use of their static and dynamic qualities in design. The main goal is to explore and to determine these qualities through experience and to transfer the understanding of them to design. Ultimately, the students will comprehend the necessity of considering their senses in design, and the richness of opportunities following this consideration. During this module, the students will also reflect on the primacy aspects of interaction design (i.e. how humans are
connected with the world in essence), on the actual place of information in interaction design. This reflection will aim the student at structuring a clear understanding of how design can sense qualities in order to influence perception and action. Learning activities - observe/explore experiences in order to determine sense qualities - map sense qualities both in static and in dynamics - translate sense qualities in movements, and explore perceptive qualities - do a design exploration of these qualities by prototyping - let guests explore final prototypes - record the results and reflect on them Planning - mapping example on senses qualities (in static and dynamics) - design exploration on a selected sense quality - prototyping on the selected sense quality
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Students will receive a feedback at the end of each step.
Bibliography: Lenay, C. (2010). Emotional value in distal contact. International Journal of Design, 4(2), 15-25. Deckers, E., Wensveen, S., Ahn, R., & Overbeeke, K. (2011) Designing for Perceptual Crossing to Improve User Involvement. In CHI 2011 - Proceedings of the29th Conference on Human Factors in Computing Systems 2011, May 7-12, Vancouver, BC, Canada, 1929.
Contact: P.D. [email protected] Assessment: - a map of sense qualities in static and in dynamics - videos of explorations - design exploration prototypes - final prototype with video of its use - final report including the entire process and the reflection
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_TU/e_DBB03: Qualitative Research Methods for Interaction Design
Hours: 40 Credits: 5
Teacher(s): Prof. Dr. ir. P. Markopoulos
Abstract:
The aim of this course is to familiarize PhD Candidates with methods and processes for performing qualitative
research to support interaction design.
Qualitative research methods have developed largely within the social sciences and recently have been applied to
the field of interaction design. This application is usually combined with a mix of creativity and elements of surprise
introduced in the research, but also often with a lack of the methodological knowledge needed to analyze the data
collected or to put the findings into perspective.
This course aims to provide interaction designers with an awareness of processes for analysing non numerical data,
but also related caveats and opportunities. It aims also to provide them with a reference framework so that the
numerous combinations and variations of known methods that they may apply in a particular project can be related
to each other. Most of all, the objective is to break mental barriers between research and design and to show how a
scientific approach to studying humans may be revealing and rewarding for interaction designers.
Program:
Lecture: Introductory overview of Qualitative Research Methods
Exercise: revisiting the data collection and data analysis of an earlier project
Study Case: 'Handling Interruptions at the Office'
Method Card assignment
Bibliography:
Brenda Laurel, Design Research, MIT Press, 2003.
Berg, B.L., Qualitative Research Methods for Social Sciences, 2nd edition, 1995.
In addition a selection of papers shall be given to PhD Candidates for use in the study case.
Contact:
Assessment:
- Report 'How would I do this study again and how would I
analyze the data'
- Presentation describing the particular qualitative method
chosen for study case and the analysis process, including
reflection on limitations and strengths of the method used.
- Presentation and report on process and result of study
case.
- Hand in an extended method card.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_TU/e_DB214: Sense your heart
Hours: 40 Credits: 5
Teacher(s): Prof.dr. S. Bambang Oetomo, Prof. dr.ir. L.M.G. Feijs, dr. W. Chen, dr. J. Hu, dr. ir. G.R. Langereis, G.J.A.
van den Boomen
Abstract: Some of you, who have followed biology classes at high school, may already know that the human body uses electricity to feel, move and think. Where this electricity originates from and what the possibilities of measuring bio-electricity are, will be discussed. Common applications are ECG (electric measurements on the heart) and EEG (measurements on the brain). These signals can be used to develop various applications, for example, health monitoring at hospital and home, sport applications, etc. This course aims to help PhD Candidates gain essential knowledge about the principles of physiological signal (e.g. ECG) measurements on the human body. PhD Candidates will learn how nerve cells interact and how the heart and the brain functions, understand the measurement principles of ECG, and gain skills to integrate the ECG frontend designed by ID.
Program:
Lecture “Monitoring heart function”
Lecture “Einthoven’s Triangle”
Lecture “ECG amplifier”
Workshop on “ECG measurement system”
Lecture “Heart rate variability”
Lecture “Filters for ECG”
Design an application involving ECG measurements
Bibliography:
Course notes Further reading:
Wilson FN, Johnston FD, Rosenbaum FF, Erlanger H, Kossmann CE, Hecht H, Cotrim N, Menezes de Olivieira R, Scarsi R, Barker PS (1944): The precordial electrocardiogram. Am. Heart J. 27: 19-85.
Lederer W.J in Medical Physiology by Boron and Boulpaep eds. 2003.
Park MK, Guntheroth WG: How to read pediatric ECGs, ed 3, St Louis, 1992, Mosby
W. Chen, S. T. Nguyen, R. Coops, S. Bambang Oetomo, L. Feijs, “Wireless Transmission Design for Health Monitoring at Neonatal Intensive Care Units”, IEEE the 2nd international symposium on applied sciences in biomedical and communication technologies (ISABEL 2009),ISBN 978-80-227-3216-1, Bratislava, Slovakia, Nov. 2009.
S. Bouwstra, W. Chen, L. Feijs, S. Bambang Oetomo, “Smart jacket design for neonatal monitoring with wearable sensors”, Proceedings of Body Sensor Networks (BSN), 2009, Berkeley, USA, pp. 162 - 167.
Contact: [email protected]
Assessment: - Development of a prototype of your own application which uses ECG. - A report on the system design, implementation (including
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
20
schematics, diagrams, photo of the ECG circuit board and coding), results (including screenshots from oscilloscope, ECG signals shown on the interface, heart rate calculation, or HRV or filtering) and possible application idea. - Short presentation / demonstration of the application.
Erasmus Mundus Joint Doctorate in
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ICE_TU/e_DB411: Intercultural Markers in the Design Process
Hours: 40 Credits: 5
Teacher(s): ir. M. Bruns, dr. O. Tomico Plasencia, dr. J.M.L. Kint
Abstract: The main goal of this course is to analyze tradition and culture as a way for differentiating and positioning design in a global market, creating value in terms of process and in terms of content. To do so it will explore the use of traditional disciplines as catalysers/platforms to bring the creative industries and technological companies together to find new design opportunities specifically tied to the country of origin. The approach to follow is research in context in order to develop a methodology that supports innovation based on cultural differentiation through value creation. The design process basically looks for cultural traces (archetypes) in traditional disciplines, like ceramics, jewellery, furniture, and cooking in order to valorize and differentiate innovation. The implementation of this process consists of different phases: identification, creation, nurturing and supporting a cultural driven value ecosystem. The expected output is an interactive product designed by means of a culturally inspired process.
Program:
Learning objectives: PhD Candidates will learn how to analyze cultural activities and how to use them as a source of inspiration to generate ideas and concepts. Furthermore they will learn how to attentively observe a process and abstract it to a level, which they can apply in the development of their designs. Finally, the main objective is to understand how culture can steer the design process in such a way that it can be used for the benefit for local industries.
Learning activities: The current module will focus on developing culturally inspired designs by analyzing the ways of cooking and eating of two distinct cultures. The preparation and consumption of food is a process that is very much influenced by culture and tradition. The goal of this module is to analyze the cooking process to determine markers that identify the specific culture and to apply those markers in the design of an interactive product, unrelated to cooking. It will include the following steps:
Observation: PhD Candidates will be divided into two equally mixed groups and assigned a specific culture. Each group will prepare a designated traditional meal and while preparing the dinner they will describe their process by speaking aloud, while the other PhD Candidates observe and analyze (video tape and note) the process. PhD Candidates may ask questions that will clarify the process. However, they are not allowed to make suggestive comments that could interfere with the process.
Analysis: Both groups will make a detailed description of the preparation process separately. This starts by studying the recipe, acquiring the materials, preparing, cooking, serving, eating the food and finally cleaning the table and washing the dishes. Continuously the PhD Candidates will discuss the separate process descriptions together and culturally different reflections will be pointed out. These culturally different markers should be discussed in the broader context of tradition.
Presentation: Each group will present the cultural markers while reflecting on their cooking process and describe how they differ from their assigned culture by observing the differences in cooking.
Implementation: The culturally different markers will continuously be used to inspire the design of an interactive product. PhD Candidates will only be allowed to adapt form and interaction of their designs
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based on the cultural markers, while using pre-defined materials.
Evaluation: The products developed inspired by the two different cultures will be evaluated at the end of the module as to their level of cultural expression.
Bibliography:
Course notes Further reading:
Koichi Miyase (Ed.). (2008) Think globally act locally. Think locally act globally: 01 Designers. Movement. Culture. From JAPAN to the WORLD. Japan Issue. Tokyo, Japan: Bueno! Books.
Further reading will be handed out in class.
Contact: [email protected]
Assessment: Report including: Detailed description of the process both visual and written, Sketchbook, Reflection, Prototype of a culturally inspired design of an interactive product
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_TU/e_DBB03: Qualitative Research Methods for Interaction Design
Hours: 40 Credits: 5
Teacher(s): Prof. Dr. ir. P. Markopoulos
Abstract:
The aim of this course is to familiarize PhD Candidates with methods and processes for performing qualitative
research to support interaction design.
Qualitative research methods have developed largely within the social sciences and recently have been applied to
the field of interaction design. This application is usually combined with a mix of creativity and elements of surprise
introduced in the research, but also often with a lack of the methodological knowledge needed to analyze the data
collected or to put the findings into perspective.
This course aims to provide interaction designers with an awareness of processes for analysing non numerical data,
but also related caveats and opportunities. It aims also to provide them with a reference framework so that the
numerous combinations and variations of known methods that they may apply in a particular project can be related
to each other. Most of all, the objective is to break mental barriers between research and design and to show how a
scientific approach to studying humans may be revealing and rewarding for interaction designers.
Program:
Lecture: Introductory overview of Qualitative Research Methods
Exercise: revisiting the data collection and data analysis of an earlier project
Study Case: 'Handling Interruptions at the Office'
Method Card assignment
Bibliography:
Brenda Laurel, Design Research, MIT Press, 2003.
Berg, B.L., Qualitative Research Methods for Social Sciences, 2nd edition, 1995.
In addition a selection of papers shall be given to PhD Candidates for use in the study case.
Contact: [email protected] Assessment:
- Report 'How would I do this study again and how would I
analyze the data'
- Presentation describing the particular qualitative method
chosen for study case and the analysis process, including
reflection on limitations and strengths of the method used.
- Presentation and report on process and result of study
case.
- Hand in an extended method card.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_TU/e_DB214: Sense your heart
Hours: 40 Credits: 5
Teacher(s): Prof.dr. S. Bambang Oetomo, Prof. dr.ir. L.M.G. Feijs, dr. W. Chen, dr. J. Hu, dr. ir. G.R. Langereis, G.J.A.
van den Boomen
Abstract: Some of you, who have followed biology classes at high school, may already know that the human body uses electricity to feel, move and think. Where this electricity originates from and what the possibilities of measuring bio-electricity are, will be discussed. Common applications are ECG (electric measurements on the heart) and EEG (measurements on the brain). These signals can be used to develop various applications, for example, health monitoring at hospital and home, sport applications, etc. This course aims to help PhD Candidates gain essential knowledge about the principles of physiological signal (e.g. ECG) measurements on the human body. PhD Candidates will learn how nerve cells interact and how the heart and the brain functions, understand the measurement principles of ECG, and gain skills to integrate the ECG frontend designed by ID.
Program:
Lecture “Monitoring heart function”
Lecture “Einthoven’s Triangle”
Lecture “ECG amplifier”
Workshop on “ECG measurement system”
Lecture “Heart rate variability”
Lecture “Filters for ECG”
Design an application involving ECG measurements
Bibliography:
Course notes Further reading:
Wilson FN, Johnston FD, Rosenbaum FF, Erlanger H, Kossmann CE, Hecht H, Cotrim N, Menezes de Olivieira R, Scarsi R, Barker PS (1944): The precordial electrocardiogram. Am. Heart J. 27: 19-85.
Lederer W.J in Medical Physiology by Boron and Boulpaep eds. 2003.
Park MK, Guntheroth WG: How to read pediatric ECGs, ed 3, St Louis, 1992, Mosby
W. Chen, S. T. Nguyen, R. Coops, S. Bambang Oetomo, L. Feijs, “Wireless Transmission Design for Health Monitoring at Neonatal Intensive Care Units”, IEEE the 2nd international symposium on applied sciences in biomedical and communication technologies (ISABEL 2009),ISBN 978-80-227-3216-1, Bratislava, Slovakia, Nov. 2009.
S. Bouwstra, W. Chen, L. Feijs, S. Bambang Oetomo, “Smart jacket design for neonatal monitoring with wearable sensors”, Proceedings of Body Sensor Networks (BSN), 2009, Berkeley, USA, pp. 162 - 167.
Contact: [email protected]
Assessment: - Development of a prototype of your own application which uses ECG. - A report on the system design, implementation (including
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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schematics, diagrams, photo of the ECG circuit board and coding), results (including screenshots from oscilloscope, ECG signals shown on the interface, heart rate calculation, or HRV or filtering) and possible application idea. - Short presentation / demonstration of the application.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
26
ICE_UNIGE_01: Data Fusion and Bayesian Interaction Modeling for Cognitive Ambient Intelligence
Hours: 25 Credits: 5
Teacher(s): Carlo Regazzoni
Abstract: The course aims at providing PhD PhD Candidates knowledge on basic tools in data fusion domain together with more advanced theories for representing, modelling and automatically interpreting interactions occurring between users, between users and artificial systems etc. within a smart cognitive environment. A Bayesian approach is used as a main methodological track in the course. In particular this module aims at :
providing a common framework to identify and to describe methodologies and techniques for integrating
multisensorial contextual data by using Data Fusion paradigms and techniques
providing a common framework for defining behavioural artificial models for context based, adaptive and
personalized decision steps used by cognitive system to address and react with respect to different
contextual working situations.
Showing examples and applications of specific techniques within cognitive telecommunication systems by
means of description of two main case studies: cognitive radio and multisensor/multimodal cognitive
human-machine interfaces in smart spaces.
Program:
Data Fusion methodologies and techniques for integrating multisensorial contextual data Data Fusion
models: the JDL model and its extensions: signals, objects, situations, threats, processes and cognitive
refinement. Alignment, association, state extimations steps in data fusion levels. Alignment techniques:
Space, Time, Frequency calibration techniques in video and radio based systems. Multisensor data
association techniques: nearest neighbour, PDAF and JPDAF. State estimation techniques: from Kalman
filter to non linear and non Gaussian state estimation techniques (extended Kalman Filter, Unscented
Kalman Filter, Mean Shift, Particle Filters). Bayesian Networks for scene interpretation. Distributed Data
Fusion (DDF): models and techniques. Distributed decision theory.
Interaction Modeling. Bio-inspired behavioral cognitive artificial models for context based, adaptive and
personalized decision. Neural basis of consciousness: the Damasio model (core-self, protoself,
autobiographical memory and autobiographical self). The brain, memory and prediction. Adaptive and
UNIGE Courses 2012-2013
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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personalized embodied decision models for analyzing situations and driving actions and re-actions within
cognitive systems. Decision space representation. Autobiographical memories and their representation and
estimation through Bayesian learning techniques.
Applications and case studies: Cognitive radio: Behavioral models for interactions between base stations
and mobile terminals. Cognitive safety and physical security systems (smart patrolling in cooperative
environments, preventive automotive vehicles, smart buidings, etc.)
Bibliography:
Course slides will be provided and made available at www.icephd.org
Further reading:
David L. Hall, James Llinas, “Handbook of Multisensor Data Fusion”, CRC Press, 2001;
Y.Bar-Shalom, W.D.Blair, “Multitarget-Multisensor Tracking: Applications and Advances”, second edition,
Artech House, 2000;
Pramod Varshney, “Distributed Dtection and Data Fusion”, Springer, 1997
Joseph Mitola III, “Aware, Adaptive and Cognitive Radio: The Engineering Foundations of Radio XML”
Wiley-Interscience, 2006
Anthonio Damasio, “The feeling of what happens: Body and Emotion in the Making of Consciousness”
(1999)”, Harcourt Brace & Company,
Contact: [email protected] Assessment: Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through an oral presentation.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
28
ICE_UNIGE_02: Theory and Practice of Learning from Data
Hours: 20 Credits: 5
Teacher(s): Davide Anguita
Abstract: This course aims at unifying the different views of model building from experimental data, as addressed by many research fields like Computational Intelligence, Pattern Recognition, Data Mining, Machine Learning and Statistics. The problem of building a model for understanding a physical phenomenon is traditionally approached by creating a reasonable mathematical representation and subsequently tuning and validating it through experimental data. Then, the obtained model can be used to better understand and make effective predictions about the events under observation. A more modern approach, instead, which has been named the “learning” approach, tries to automate this procedure, starting from the available data and building the optimal model, according to some quality measures, limiting or avoiding any user intervention. The course will present the theoretical background of learning from data as well as practical applications in several areas including industrial (e.g. automotive, robotics, etc.), scientific (e.g. cognitive science, medical- and bio-informatics) and economic (e.g. time series prediction, market analysis) fields.
Program:
Data, information and models: induction, deduction and transduction
Statistical inference: Bayesians vs. Frequentists
Simple models: Associations rules, Classification trees, Naïve Bayes
Classification and Regression
Nonlinear models: Neural Networks and Kernel methods
Model selection and error estimation
Clustering, Novelty Detection and Ranking
Bibliography:
Course notes will be provided and made available at www.icephd.org Further readings:
V.Cherkassky, F.Mulier, “Learning from Data: Concepts, Theory and Methods”, 1998.
T.Hastie, R.Tibshirani, J.Friedman, “The Elements of Statistical Learning: Data Mining, Inference and Prediction”, 2009.
Contact: [email protected] Assessment: Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through an oral presentation.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
29
ICE_UniGe_03: Modelling, simulations and games
Hours: 20
Credits: 5
Teacher(s): Francesco Bellotti
Abstract: The course aims at providing PhD students with knowledge on principles, design theories and development tools for modelling and simulation. Applications in the Serious Gaming field is a major focus of the course.
Program: Modeling and simulation
Simulation examples
Concepts in Discrete-Event Simulation
List Processing
Simulation software
Statistical models in simulation
Queing models
Input modeling
Verification and calibration of simulation models
Serious Game Applications.
State of the art of Serious Games for educational domains such as: safety, crisis management, cultural heritage
o Targets, achievements and research perspectives
Requirements from target users and stakeholders o Gathering requirements and defining specifications
Pedagogical and psychological foundations
Architectures o Game engines and additional Artificial Intelligence modules o Programming languages o Interoperability and semantics
Contents o Authoring tools
Deployment and testing o Integration of SGs in educational contexts and in corporate training o Qualitative and quantitative methods for impact assessment
Bibliography:
Course notes will be provided and made available at www.icephd.org
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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Further reading:
Banks, Carson II, Nelson, Nicol, Discrete-event system simulation, Pearson
Buckland, Programming Game AI by Example, Wordware
Akenine-Moeller, Haines, Hoffman, Real-Time Rendering, A K Peters
Zeigler, Praehofer, Kim, Theory of Modeling and Simulation, Academic Press
Nitschke , Professional XNA Game Programming: For Xbox 360 and Windows , John Wiley & Sons
Prensky, Teaching Digital Natives---Partnering for Real Learning, Corwin
Prensky, Digital Game-Based Learning, McGraw-Hill
Contact: [email protected]; [email protected] Assessment: Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through an oral presentation.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
31
ICE_UNIGE_04: Green Netwoking
Hours: 20 Credits: 5
Teacher(s): Raffaele Bolla
Abstract: The concept of energy-efficient networking has begun to spread in the past few years, gaining increasing popularity. Besides the widespread sensitivity to ecological issues, such interest also stems from economic needs, since both energy costs and electrical requirements of Telecom Operators' and Internet Service Providers' infrastructures around the world show a continuously growing trend. In this respect, a common opinion among networking researchers is that the sole introduction of low consumption silicon technologies may not be enough to effectively curb energy requirements. Thus, for disruptively boosting the network energy efficiency, these hardware enhancements must be integrated with ad-hoc mechanisms that explicitly manage energy saving, by exploiting network-specific features. This tutorial aims at providing a twofold contribution to green networking. At first, we explore current perspectives in power consumption for next generation networks. Energy consumption trends from word-wide telecom operators will be analyzed, and decomposed in contributions representing different the network segments (e.g., wireless and wire-line, access and core networks, data centers, etc.). Then, the focus will be moved on wire-line networks, and, in particular, on single network devices with the aim of deeply understanding how different functionalities and device building blocks weight on the overall energy requirements. Secondly, we provide a detailed survey on emerging technologies, projects, and work-in-progress standards, which can be adopted in networks and related infrastructures in order to reduce their carbon footprint. From a general point of view, the largest part of undertaken approaches is founded on few base concepts, which have been generally inspired by energy-saving mechanisms and power management criteria that are already partially available in computing systems. These base concepts can be classified as follows: i) re-engineering, ii) dynamic adaptation, iii) sleeping/standby..
Program:
Modern Telecommunication Networks – Status and Trends o The Internet and the Future Internet o Reasons for going green o Carbon footprint o Does the fixed network matter (in terms of consumption and OPEX)?
Energy Consumption Breakdown in Network Segments and Network Devices
A Wrap-up on the Structure and Functionalities of Fixed Network Devices
Taxonomy of Green Networking Approaches
Potential Savings (or, is there room for network energy optimization?)
Dynamic Adaptation I – Link Protocols
Dynamic Adaptation II – Packet Processing Engine
Standby and Virtualization
Modeling and Optimization o An Introduction to Network Queuing Models o Traffic Models and Traffic Engineering
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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o Queues with Vacations o Modeling Line Card Queues o Power-Performance Tradeoff o Device- and Network-Level Optimizations
Ongoing Projects
Research Challenges
Bibliography:
Course notes will be provided and made available at www.icephd.org Further reading:
R. Bolla, R. Bruschi, F. Davoli, F. Cucchietti, “Energy Efficiency in the Future Internet: A Survey of Existing Approaches and Trends in Energy-Aware Fixed Network Infrastructures,“ IEEE Communications Surveys and Tutorials (IEEE COMST), vol. 13, no. 2, pp. 223-244, 2nd Qr. 2011 .
R. Bolla, R. Bruschi, K. Christensen, F. Cucchietti, F. Davoli, and S. Singh, “The Potential Impact of Green Technologies in Next-Generation Wireline Networks – Is There Room for Energy Saving Optimization?,” IEEE Communication Magazine (IEEE COMMAG), Special Topic in “Green Communications,” to appear.
R. Bolla, R. Bruschi, A. Carrega, F. Davoli, “An Analytical Model for Designing and Controlling New-Generation Green Devices,” Proc. 3rd IEEE Workshop on Green Communications (GreenCom), co-located with GLOBECOM 2010, Miami, FL, USA. Winner of the Best Paper Award.
R. Bolla, R. Bruschi, A. Cianfrani, M. Listanti, “Introducing Standby Capabilities into Next-generation Network Devices,” Proc. ACM SIGCOMM Workshop on Programmable Routers for Extensible Services of Tomorrow (ACM SIGCOMM PRESTO), Philadelphia, PA, USA, Nov. 2010.
R. Bolla, R. Bruschi, A. Carrega, F. Davoli, "Theoretical and technological limitations of power scaling in network devices", Proc. Australasian Telecommunication Networks and Applications Conf. 2010 (ATNAC 2010), Auckland, New Zealand, Nov. 2010.
R. Bolla, R. Bruschi, A. Ranieri “Green Support for PC-based Software Router: Performance Evaluation and Modeling,” Proc. 2009 IEEE International Conference on Communications (IEEE ICC 2009), Dresden, Germany, June 2009. Winner of the Best Paper Award.
R. Bolla, R. Bruschi and F. Davoli, “Energy-aware Performance Optimization for Next Generation Green Network Equipment”, Proc. ACM SIGCOMM 2009 Workshop on Programmable Routers for Extensible Services of Tomorrow (ACM PRESTO 2009), Barcelona, Spain, Aug. 2009, pp. 49-54.
R. Bolla, R. Bruschi, F. Davoli, “Energy-aware Resource Adaptation for Next Generation Network Equipment,” Proc. 2009 IEEE Global Communications Conference (IEEE GLOBECOM 2009), Honolulu, Hawaii, USA, Dec. 2009.
R. Bolla, R. Bruschi, A. Carrega, F. Davoli, “Green Networking Technologies and the Art of Trading-off,” Proc. INFOCOM 2011 Workshop on Green Communications and Networking, Shanghai, China, April 2011.
R. Bolla, R. Bruschi, A. Cianfrani, M. Listanti, “Putting Backbone Networks to Sleep,” IEEE Network Magazine, Special Issue on “Green Networking”, vol. 25, no. 2, pp. 26-31, March/April 2011.
Contact: [email protected] Assessment: Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through an oral presentation.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
33
UNIKLU Courses 2012-2013
ICE_UNIKLU_01: Mobile and Wireless Communications
Hours: 30 Credits: 5
Teacher(s): Prof. Christian Bettstetter
Abstract: The lectures Mobile and Wireless Communications and Networking give a bottom-up introduction to the area of mobile and wireless communication systems. The main goal is to give a fundamental understanding of the principles behind wireless transmission and networking. Current technologies, such as UMTS and IEEE 802.11, are used as examples to explain these principles. Moreover, a whole chapter is dedicated to ad hoc networks. The lectures are complemented by group projects, whose results are discussed in class. A tutorial course with exercises is offered for the 1st lecture.
Program:
Introduction and Overview (2 hours). History of wireless communications; Different kinds of mobility; Overview and classification of current wireless technologies; Key challenges in mobile and wireless systems; Transmission chain.
Antennas (2 hours). Antenna types; How are radio waves generated? Energy and power aspects of radio waves; Directivity and gain; How much power is received at a certain distance?
Radio Propagation (7 hours). Path loss and shadowing (propagation in free space, generalized path loss models, shadow fading); Multipath propagation (small-scale fading models, time spread, frequency spread, time-variant behavior; frequency-variant behavior, relationships); Overview of fading mitigation techniques (diversity schemes, equalization, spread-spectrum communications, error control and interleaving, multicarrier modulation); Group project "Path loss and shadowing".
Coding, Modulation, and Duplexing (9 hours). o Representation of signals. Conversion from analog to digital. o Channel coding (overview, block coding, convolutional coding, coding gain, channel coding in
practice). o Digital modulation (overview, linear modulation, coherent demodulation, modulation in practice,
spead spectrum modulation). o Duplexing. o Group project "Convolutional coding".
Multiple Access and Cellular Concept (2.5 hours). Ideas behind TDMA, FDMA, CDMA, SDMA. Cellular concept and channel reuse. Group project "Orthogonal Frequency Division Multiplexing (OFDM)"
Bibliography:
Course notes Further reading:
M. Schwartz: Mobile Wireless Communications, Cambridge University Press, 2005
A. Goldsmith: Wireless Communications, Cambridge University Press, 2005
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
34
T. S. Rappaport: Wireless Communications, Prentice Hall, 2001
A. F. Molisch: Wireless Communications, Wiley-IEEE Press, 2005
Contact: [email protected] Assessment:
ICE_UNIKLU_02: Pervasive Computing
Hours: 30 Credits: 5
Teacher(s): Prof. Bernhard Rinner
Abstract: This lecture focuses on the fundamentals of pervasive computing. Pervasive computing integrates computation into the environment, rather than having computers which are distinct objects. Computation is embedded into the environment and everyday objects and would enable people to interact with information-processing devices more naturally and casually than they currently do, and in ways that suit whatever location or context they find themselves in. Most topics will be presented by the lecturer. Depending on the number of participants PhD Candidates may prepare and present special topics such as applications and case studies of pervasive computing.
Program:
Introduction
Spontaneous Networking
Localization
Identification
Context-Aware Computing
Sensor Networks
Wearable Computing
Middleware Systems
Applications
Bibliography:
Course notes https://elearning.uni-klu.ac.at/moodle/course/view.php?id=3728
Further reading:
Stefan Poslad. Ubiquitous Computing. Wiley 2009
Hansmann, Merk, Nicklous, Stober. Pervasive Computing. Springer 2003
Adelstein, Gupta, Richard, Schwiebert. Fundamentals of Mobile and Pervasive Computing. McGraw-Hill. 2005
Contact: [email protected] Assessment:
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
35
ICE_UNIKLU_03: Mobile and Wireless Networks
Hours: 30 Credits: 5
Teacher(s): Prof. Christian Bettstetter
Abstract: The lectures Mobile and Wireless Communications and Networking give a bottom-up introduction to the area of mobile and wireless communication systems. The main goal is to give a fundamental understanding of the principles behind wireless transmission and networking. Current technologies, such as UMTS and IEEE 802.11, are used as examples to explain these principles. Moreover, a whole chapter is dedicated to ad hoc networks. The lectures are complemented by group projects, whose results are discussed in class. A tutorial course with exercises is offered for the 1st lecture.
Program:
Medium Access Control (MAC) Protocols (3 hours). ALOHA. Slotted ALOHA. CSMA. CSMA/CA. Performance studies
Wireless LAN 802.11 (1 hour).
Network Architecture and Mobility Protocols (7 hours). o Architecture of cellular networks (General architecture; system components in GSM, UMTS, and
LTE). o Mobility in cellular networks (Addressing and location updating; Routing to mobile users; Roaming
and handover). o Mobility in the Internet (Addressing and mobility problem; Autoconfiguration; Device mobility with
Mobile IP; Service mobility). o Group project "Internet mobility protocols".
Security in Mobile Networks (2 hours). Basics. Security in UMTS.
Ad Hoc Networks (8 hours). Introduction and Applications. Routing. Relaying. Connectivity and Capacity.
Economic, Health, and Social Aspects (2 hours)
Bibliography:
Course notes Further reading:
M. Schwartz: Mobile Wireless Communications, Cambridge University Press, 2005
J. Eberspächer, H.-J. Vögel, C. Bettstetter, C. Hartmann: GSM: Architecture, Protocols, and Services, 3rd ed., Wiley, 2008
B. H. Walke: Mobile Radio Networks, 2nd ed., Wiley, 2002
B. H. Walke, P. Seidenberg, A.-P. Althoff: UMTS: The Fundamentals, Wiley, 2003
H. Kaaranen, A. Ahtiainen, L. Laitinen, S. Naghian, V. Niemi: UMTS Networks: Architecture, Mobility, and Services, 2nd ed., Wiley, 2005
E. Dahlman, S. Parkvall, J. Sköld, P. Beming: 3G Evolution: HSPA and LTE for Mobile Broadband, 2nd edition, Wiley, 2008
R. S. Koodli and C. E. Perkins: Mobile Inter-Networking with IPv6: Concepts, Principles, and Practices, Wiley, 2007
C. E. Perkins (Ed.): Ad Hoc Networking, Addison-Wesley Longman, 2001
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
36
ICE_UNIKLU_04: Sensor Networks
Hours: 30 Credits: 5
Teacher(s): Prof. Bernhard Rinner
Abstract: Due to the advances in electronics and (wireless) communication, the development of networks of low-cost, low-power, multi-functional sensors has received increasing attention. These sensor networks are a new type of networked, embedded computing systems and are expected to become a key technology for many pervasive computing applications. This lecture covers the fundamental concepts of sensor networks, including architectures, various networking aspects, power-awareness and sensor fusion. The lecture is complemented by a lab course where PhD Candidates can get hands-on experience in developing sensor network applications.
Program:
Introduction
Sensor Technology
Networking Aspects (Media Access, Routing, Data dissemination)
Power- and Energy-Awareness
Synchronization
Sensor Fusion
Applications and Case Studies
Bibliography:
Course notes https://elearning.uni-klu.ac.at/moodle/course/view.php?id=4531
Further reading:
F. Zhao, L. Guibas. Wireless Sensor Networks. Morgan Kaufmann 2004
Dressler. Self-Organization in Sensor and Actor Networks. Wiley 2007
Stojmenovic. Handbook of Sensor Networks. Wiley 2005
M. Ilyas, I. Mahgoub. Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems. CRC Press 2005
Contact: [email protected]
Assessment:
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
37
ICE_UNIKLU_05: Embedded Communications
Hours: 30 Credits: 5
Teacher(s): Prof. Mario Huemer
Abstract: This lecture deals with the architecture of modern wireless communication systems. All main functional blocks of a mobile phone platform including the baseband processor and the RF (radio frequency) transceiver are addressed. Different board level and chip level architectures will be presented. In the "Digital Baseband Transceiver" chapter important baseband algorithms (equalization, channel estimation, OFDM modulation technique, MIMO signal processing,…), possible implementation options, and corresponding complexity considerations are discussed. The "Analog Transceiver" chapter deals with the analog signal processing tasks of a wireless device. Modern transmitter and receiver architectures are discussed, and future trends on the way to Software Defined Radio (SDR) architectures are presented. In parallel a practical course will be offered (optional). Systems and algorithms presented in the lecture will be simulated and tested in the MATLAB/SIMULINK environment.
Program:
Review of Communications Engineering Basics
The Mobile Radio Channel
Abstract Hardware View on a Mobile Phone Terminal Platform (Functional Blocks, Partitioning, Technology, Power Consideration)
The Digital Baseband Transceiver (Equalization, Channel Estimation, OFDM versus Single Carrier Transmission, MIMO Concepts)
The Analog Transceiver (Receiver Architectures, Transmitter Architectures, Future Trends)
Bibliography:
Course notes Further reading:
Nevio Benvenuto, Giovanni Cherubini, Algorithms for Communications Systems, John Wiley & Sons Ltd., 2002.
Karl Dirk Kammeyer, Nachrichtenübertragung, Vieweg & Teubner Verlag, Wiesbaden 2008.
Behzad Razavi, RF Microelectronics, Prentice Hall Inc., Upper Saddle River, 1998.
Contact: [email protected] Assessment:
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
38
ICE_UNIKLU_06: Interactive Systems
Hours: 30 Credits: 5
Teacher(s): Prof. Martin Hitz
Abstract: The lecture provides an introduction into the field of Human-Computer-Interaction (HCI). PhD Candidates will learn the essential characteristics of human-machine communication processes (including perceptive and cognitive issues), know how to design usable interfaces (especially GUIs), understand the principle architecture of modern GUIs, be able to implement a GUI, and know the principles of usability engineering processes.
Program:
Introduction (Interaction with everyday things, interaction models, history of HCI)
Interaction styles
Classical GUIs
Interface Modeling
Perceptive and cognitive issues of interface design
Usability
Usability Engineering
Bibliography:
Dix et al., Human-Computer Interaction, Prentice-Hall, 2003.
Shneiderman & Plaisant, Designing the User Interface, 4th edition, Addison-Wesley, 2004.
Raskin, The Humane Interface, Addison-Wesley, 2000.
Norman, The Psychology of Everyday Things, BasicBooks, 1988
Contact: [email protected]
Assessment:
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
39
ICE_UNIKLU_07: Signal Processing Architectures
Hours: 30 Credits: 5
Teacher(s): Prof. Mario Huemer
Abstract: This lecture deals with signal processing algorithms and with appropriate implementation architectures that focus on embedded applications. As a consequence low power consumption and low chip area are of great importance for the regarded architectures. The course starts with a short repetition of important signal processing theory and algorithms (FFT, digital filters). In the following the focus lies on implementation oriented issues like fixed point effects and architectural options for various important signal processing algorithms and applications. In parallel a lab will be offered (optional), which will cover the following:
MATLAB part: the effects and architectures covered in the lecture are in-depth studied with the help of MATLAB/SIMULINK simulations
Review of VHDL programming
Implementation of signal processing architectures on FPGAs Program:
Introduction & review of digital signal processing basics
DSP arithmetic
DSP hardware: DSPs, FPGAs and ASICs
CORDIC-algorithm: theory, architectures and applications
Fixed point effects in digital filtering
Multirate signal processing (interpolation, decimation, filter banks): theory and low power - low area HW-architectures
Low cost digital filters
Sigma-delta modulation and oversampling ADCs
Numerically controlled oscillators
Bibliography:
Course notes Further reading:
Peter Pirsch, Architectures for Digital Signal Processing, John Wiley & Sons Ltd., 2001.
Uwe Meyer-Baese, Digital Signal Processing with Field Programmable Gate Arrays, Springer Berlin Heidelberg New York, 2007.
Contact: [email protected]
Assessment:
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
40
ICE_UNIKLU_08: Adaptive and Statistical Signal Processing
Hours: 30 Credits: 5
Teacher(s): Prof. Mario Huemer
Abstract: Statistical and adaptive signal processing algorithms can be found at the heart of many electronic systems designed to transmit, receive, store or extract information. These systems include radar, sonar, speech, image analysis, biomedicine, communications, control… and many more. This lecture gives an introduction to the most prominent concepts. We will adopt the theory to a large number of applications from the engineering world (mainly from communications engineering and radar). Algorithms presented in the theory part will be simulated and tested in the MATLAB/SIMULINK environment.
Program:
Random Variables and Vectors (short review)
Classical Estimation in Signal Processing (Bounds, Linear Models, ML, BLUE, LS)
Bayesian Estimation in Signal Processing (MMSE, MAP, LMMSE)
Discrete Time Stochastic Processes
Wiener Filters, LS Filters and their Applications
Adaptive Filters (LMS, RLS Algorithms) and their Applications
Bibliography:
Course notes Further reading:
Steven M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice Hall PTR, Upper Saddle River, New Jersey, 1993.
Dimitris G. Manolakis, Vinay K. Ingle, Stephen M. Kogon, Statistical and Adaptive Signal Processing, Artech House, Norwood, 2005.
Paulo S. R. Diniz, Adaptive Filtering – Algorithms and Practical Implementation, Kluwer Academic Publishers, Boston /Dordrecht / London, 1997.
Contact: [email protected]
Assessment:
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
41
ICE_UNIKLU_09: Novel Topics in Digital Signal Processing for PhD Students
Hours: 30
Credits: 5
Teacher(s): Mario Huemer
Abstract:
This seminar addresses PhD students that work in the field of signal processing. Novel topics appearing in the field of signal processing shall be studied, and presentations shall be given in front of an audience. In-depth discussions shall help to penetrate the topic.
Program:
E-Learning
Cooperation: e.g. online discussions, wikis, video conferences or peer-reviews etc.
Bibliography:
Scientific publications
Contact: [email protected]
Assessment: Presentation
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
42
ICE_UNIKLU_10: Doctoral Seminar NES
Hours: 45 Credits: 5
Teacher(s): Professors Bettstetter, Huemer, Rinner, Hitz
Abstract:
In this seminar PhD PhD Candidates give presentations on their own research work. PhD Candidates learn to present, discuss and argue about a research topic within the scientific setting.
Program:
Individual presentations and discussions within a small group of professors and PhD Candidates
Bibliography:
Course notes
Contact: [email protected]
Assessment:
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
43
ICE_UNIKLU_11: Research Paradigms in Computer Science
Hours: 30 Credits: 5
Teacher(s): Prof. Johann Eder
Abstract:
This lecture is devoted to the different research paradigms used in computer science research.
Program:
Topics:
Research Proposals
Hypothesis and Research Goals
Research Methods
Bibliography:
Further reading:
Martin S. Olivier: Information Technology Research, Van SCheik Publishers, 2007
Contact: [email protected]
Assessment:
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
44
UPC Courses 2012-2013
ICE_UPC_1: Artificial Intelligence applied to Robotics
Hours: 125 Credits: 5
Teacher(s): Andreu Català, Cecilio Angulo, Francisco J. Ruiz
Abstract: The objective of the course is to familiarize to the student with the structures of data and the techniques of developed reasoning and learning in the scope of the Artificial intelligence that have found application in Robotics.
Program: 1. OBJECT/ACTION/REPRESENTATIÓN OF THE SPACE 1.1 Symbolic versus subsymbolic 1.2 Graphs and search 1.3 Sensorimotor Functions 1.4 Symbol grounding/anchoring 2. CONTROL ARCHITECTURES 2.1 Subsumption 2.2 Agents 3. ADAPTABILITY - NEURONAL NETWORKS 3.1 Perceptual grouping 3.2 Sensorimotor functions adaptation 3.3 Neurophysiologics models of control for the motor 3.4 Genetic algorithms and evolutionary computation 4. DECISION SYSTEMS AND PLANNING 4.1 Fuzzy control 4.2 Case based reasoning 4.3 Bayesian networks 4.4 Planners based on logics 5. LEARNING IN ROBOTS 5.1 Reinforcement learning: exploration 5.2 Interaction human - robot 5.3 Imitation and learning by demonstration 6. ADVANCED SUBJECTS 6.1 Ambient intelligence 6.2 Ubiquitous and contextual computing
Bibliography: S. Russel and P. Norving, “Artificial Intelligence: A modern Approach” (second edition), Prentice Hall, 2003.
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B. Martín del Brío, A. Sanz. Redes Neuronales y Sistemas Borrosos. RA-MA Ed. (2001) Copeland, J. (1996). "Inteligencia Artificial". Alianza Editorial. Brown, M., Harris, C.J. (1994). "Neurofuzzy Adaptive Modelling and Control". Prentice Hall. Kecman, V. (2001). "Learning and Soft Computing: Support Vector Machines, Neural Networks and Fuzzy Logic Models". MIT Press.
Contact: Andreu Català [email protected] Cecilio Angulo [email protected] [email protected]
Assessment: The evaluation fundamentally is based on the degree and level of participation of the student throughout the course in the sessions of class (contribution to the debate of the subjects, exposition and resolution of questions...), and in the development, conclusions and presentation of its works of practices. Complementarily, and based on the development of the course, partial tests of one or several of the parts are made that the subject consists. These tests are made up fundamentally of conceptual questions that they require short answers.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
46
ICE_UPC_2: Artificial intelligence Applied to the Control and the Identification of Systems
Hours: 125 Credits: 5
Teacher(s): Cecilio Angulo, Francisco J. Ruiz, Andreu Català
Abstract: To know which are the branches of the Artificial intelligence that can contribute to the process control as well as to its modeling, understand the most excellent techniques of these branches and their foundations, and to be able to apply them in tasks of control and identification of systems.
Program: 1. INTRODUCTION TO THE ARTIFICIAL INTELLIGENCE 1.1 Definitions 1.2 Bases of the IA. Intelligent action 1.3 Representation of the Knowledge. Traditional Methods. 1.4 Search and Optimization 2. REPRESENTATION OF THE KNOWLEDGE. NEURONAL NETWORKS 2.1 Reasoning and Inference 2.2 Foundations of neuronal networks 2.3 Perceptron – Delta Rule 2.4 MultiLayer Perceptron – Backpropagation 2.5 New techniques of machine learning: RBF networks and Support Vector Machines (SVM) 3. SYSTEMS OF FUZZY LOGIC AND APPLICATIONS 3.1 Introduction 3.2 Basic elements of a fuzzy inference system 3.3 Examples of operation 3.4 Type of fuzzy logic controller 3.5 Neuro-fuzzy schemes 4. COMPLEX SYSTEMS. EVOLUTIONARY ALGORITHMS 4.1 Introduction – motivation 4.2 General scheme of an evolutionary algorithm 4.3 Evolutionary and neuro-evolutionary schemes 5. APPLICATIONS OF THE IA TO THE INTELLIGENT CONTROL OF PROCESSES 5.1 Application to the identification and the modeling of nonlinear systems 5.2 Application to the control and the supervision 6. AGENTS AND MULTIAGENT SYSTEMS IN CONTROL 6.1 Definitions 6.2 Physical agents and holonics systems
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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Bibliography: Hastie, T., Tibshirani, R., Friedman, J. (2001). “The Elements of Statistical Learning. Data Mining, Inference and Prediction”. Springer Nørgaard, M., Ravn, O., Poulsen, N.K., Hansen, L.K.. (2000) “Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner’s Handbook”, Springer-Verlag, Brown, M., Harris, C.J. (1994). "Neurofuzzy Adaptive Modelling and Control". Prentice Hall. Passino, K. (2004). “Biomimicry for Optimization, Control and Automation”. Springer Kecman, V. (2001). "Learning and Soft Computing: Support Vector Machines, Neural Networks and Fuzzy Logic Models". MIT Press. Dreyfus, G. (2005). “Neural Networks: Methodology and Applications” Springer Verlag.
Contact: Cecilio Angulo [email protected] [email protected] Andreu Català [email protected]
Assessment: The evaluation fundamentally is based on the degree and level of participation of the student throughout the course in the sessions of class (contribution to the debate of the subjects, exposition and resolution of questions...), and in the development, conclusions and presentation of its works of practices. Complementarily, and based on the development of the course, partial tests of one or several of the parts are made that the subject consists. These tests are made up fundamentally of conceptual questions that they require short answers.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_UPC_3: Information Skills in Information Technologies
Hours: 30 Credits: 1,2
Teacher(s): Conrado Martínez
Abstract: This subject provides the procedures, concepts and necessary values to solve problems that imply the research, selection, organization, analysis and communication of information. This means, to learn to manage documental information, to transform it into knowledge, and to communicate it.
Program:
1. The value of the information in the process of research Bibliotècnica, the digital library of UPC. Information in the 21st century 2. Typology of scientific and technical documents The Scientific Method. Basic documents: handbook, course book, magazines, etc. Advanced documents: report, patent, dissertation, journals, conference proceedings, etc. 3. The catalog of the UPC libraries Searching by author, subject, title, keyword. Journal searching, monograph searching, etc. 4. Elaboration of a search strategy Information needs. Terminological findings: dictionaries, thesaurus… Noise and Silence in information retrieval. Boolean operators, proximity commands, truncation, ... 5. The scientific publication in Internet Open Access initiatives Pre-prints, post-prints, and dissertation repositories. 6. Databases of journal articles and conference papers Scope and search options. INSPEC, IEEEXplore, Safari TechBooks, Elsevier Science Direct, ACM Digital Library, CSIC ICYT. 7. Bibliographic reference managers Bibliographic citations, reference managers, location of specific documents 8. Searching information on the Internet
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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Different approaches to Search Engines and Internet directories. Advanced search options: natural speaking, delimitators, Boolean operators, etc. The invisible web 9. Oral communication Recommendations to communicate orally the results of a research in an effective way. 10. Criteria for information evaluation and selection 11. Models to elaborate, to structure and to communicate the master thesis 12. What's on? Alert services. 13. Practices and resolution of doubts about the final work of the subject
Bibliography:
Beumala, Àngel; Aragüés, Montse; Roca, Marta HITI: [BRGF], 2007
Contact: [email protected] Assessment:
The evaluation will consist of a final work, and 4 compulsory exercises which it will be necessary to give along the course. The punctuation of 4 compulsory exercises represents 40% of the final mark. The punctuation of the final work represents 60% of the final mark
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_UPC_4: Advanced Techniques in Machine Learning
Hours: 150 Credits: 5
Teacher(s): Javier Béjar
Abstract:
Goals: This course is an extension of the methodologies learned from the previous machine learning courses. The main subjects treated in this course include unsupervised learning from different perspectives (machine learning, intelligent data analysis, knowledge discovery) and case based reasoning
Program: Part I – Unsupervised Learning 1. Unsupervised Learning and Data Mining 2. Elements of the process of unsupervised learning Data representation Data preprocessing and transformation Distance functions 3. Unsupervised learning ouside machine learning Cognitive Psicology Numerical Taxonomy Data analysis 4. Machine learning perspective Conceptual Clustering Concept formation Evaluation of unsupervised learning Sintatic Biasing, Semantic Biasing 5. Unsupervised Learning in Knowledge Discovery/Data Mining Clustering Algorithms for Knoledge Discovery Unsupervised Learning from patterns and structures Association Rules, Time Series, Trees, Graphs Part II – Case Based Learning and Reasoning 1. Introduction 2. CBR Foundations Basic cicle of reasoning Models for expertise representation 3. CBR Applications Academic application: CHEF, CASEY, JULIA, HYPO, PROTOS Practical application to complex domains OPENCASE: A domain independent CBR system
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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4. Cases representation and organization Representation structures Library structures 5. CBR system phases Case retrieval Similarity evaluation Adaptation strategies and/or methods Learning 6. Reflective reasoning in CBR 7. Applications and tools for CBR developement Industrial applicacions Software tools 8. CBR evaluation 9. Advanced Research in CBR
Bibliography: # Course notes
Contact: [email protected] Assessment: A Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through an oral presentation.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
52
ICE_UPC_5: Artificial Intelligence Applications
Hours: 150 Credits: 5
Teacher(s): Ulises Cortés
Abstract:
The objective of this subject is to complement and broaden what students learn in the compulsory subject Artificial Intelligence and the optional subjects Learning and Natural Language Processing. To achieve this goal, the subject will be redesigned and updated every semester. To enhance students' receptivity of the subject matter, this subject has an eminently practical approach and gives students a set of problems that they must solve and implement. In recent years, the subject has placed emphasis on autonomous agents and their use in e-business. Given the importance of the practical component in this subject, it has an important weight of the students' final assessment. At the end of this subject, students will have a broader vision of the methods used in artificial intelligence and their applications in the real world
Program: 1. Artificial Intelligence perspectives Introduction to fields in which AI can be applied. 2. Introduction to intelligent agents What is an agent? Agents as basic building blocks. Agent types. agent-building architectures. 3. Ontologies What is an ontology? Methods for constructing ontologies. Description logics. Ontological languages. 4. Logic systems for Artificial Intelligence Reasoning for AI applications. Modal logics. Temporal logics. Reasoning under uncertainty. 5. Communication The need for communication between agents. Speech Act Theory. Languages for establishing communication between agents. 6. Advanced search algorithms Best search algorithms. Tabu Search, meta-heuristics. Genetic algorithms. 7. Planning Description of planning problems. Planning algorithms: Linear planning, with partial order, hierarchy. 8. Co-ordination, negotiation Need for co-ordination in multi-agent systems. Negotiation between agents.
Bibliography:
Stuart J. Russell and Peter Norvig Artificial intelligence : a modern approach- third edition, Prentice Hall, 2011.
Zbigniew Michalewicz, David B. Fogel How to solve it : modern heuristics, Springer,, 2004. Asunción Gómez-Pérez, Mariano Fernández-López, and Oscar Corcho Ontological engineering : with
examples from the areas of knowledge management, e-commerce and the semantic Web, Springer-Verlag, 2004.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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Ghallab Malik, Dana Nau, Paolo Traverso Automated planning : theory and practice, Elsevier/Morgan Kaufmann, 2004.
Weiming Shen, Douglas H. Norrie and Jean-Paul A. Barthès Multi-agent systems for concurrent intelligent design and manufacturing, Taylor & Francis, 2001
Contact: [email protected]
Assessment: Evaluation is based on a final exam and a part exam, grading of course assignments, and a grade for lab work. The final and part exams will test the theoretical knowledge and the methodology acquired by students during the course. The grade for course assignments will be based on submissions of small problems set during the course. Lab grades will be based on students" reports and lab practical work carried out throughout the course. At about half of the 4-moth term there will be an exemptive part exam, testing the first half of the course (exemptive only if the grade is 5 or more). The final exam will test both the first and the second part of the course. The first half is compulsory for those students who didn"t pass the part exam, and optional for the rest. The maximum of both grades (or the only one for the part exam) will stand as the grade for the first part. The final grade will be calculated as follows: GPar = part exam grade GEx1 = 1st half of the final exam grade GEx2 = 2nd half of the final exam grade Total Exams grade = [max(Npar, NEx1) + NEx2]/2 Final grade= Total Exams grade * 0.5 + Exercises grade * 0.2 + lab grade * 0.3.
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE_UPC_6: SEMINAR on Artificial Intelligence
Hours: 75 Credits: 3
Teacher(s): Miquel Sánchez Marré
Abstract: To introduce new and current research themes in Artificial Intelligence field.
Program:
Development of the theoretical content by the teachers. Each academic year the content could be changed. See the Course schedules section for detailed information of current content.
Bibliography:
Contact: [email protected] Assessment: Evaluation will normally be based in some assignments to the students
Erasmus Mundus Joint Doctorate in
Interactive and Cognitive Environments
(EMJD ICE)
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ICE PhD Courses - General Rules
This note contains some general rules to ensure that all the courses offered in the ICE PhD program follow high-quality standards and present to the PhD Candidates a comprehensive and harmonized view of the ICE PhD courses.
1. Language
Both the lectures and the teaching material are in English.
2. Syllabus and EMJD ICE General Regulation
The present syllabus refers and is subject to EMJD ICE Regulation, in particular to the annex document “Conditions for Obtaining the Joint/Double Doctorate”.
3. Didactical Material
Each course provides the didactical material (slides, lecture notes, software, etc.) in advance through the ICE web site and/or through the Professor(s) and/or through the Didactic Manager.
4. Assessment
Each course assesses the PhD Candidates through a final test, shortly after the completion of the lectures. The assessment is carried out by the same people who taught the course.
The assessment consists in one of the following:
Written exam: multiple choice test, free response test or exercises;
Position paper: the candidate should write a short position paper on how the topics dealt with during the course can be of interest for his/her research and defend it through a oral presentation.
The final outcome of the test is “passed”/”failed”.
5. ECTS Definition and assignation
European Credit Transfer and Accumulation System (ECTS) is a standard for comparing the study attainment and performance of PhD Candidates of higher education across the European Union and other collaborating European countries. For successfully completed studies, ECTS credits are awarded. One academic year
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corresponds to 60 ECTS-credits that are equivalent to 1500–1800 hours of study in all countries irrespective of standard or qualification type and is used to facilitate transfer and progression throughout the Union.
The ECTS will be complemented by the European credit transfer system for vocational education and training (ECVET) which the ministers responsible for vocational training in 32 European countries agreed to develop in the Maastricht Communiqué of 14 December 2004.
ECTS also includes a standard ECTS grading scale, intended to be shown in addition to local (i.e. national) standard grades1.
According to the agreements settled during the Conference Call of the Management Board, that took place on 28 June 2010, the assignation of credits is based on the effort and the more advanced contents of the courses. The specific PhD Courses account for 8 ECTS; the MSc Courses or the soft skills assign 5 ECTS.
Conditions for Obtaining the ICE Joint/Double Doctorate
Joint Degree
The ICE Joint Doctorate is a three year international PhD programme with a total of 180 ECTS. The PhD Candidates must conduct the programme in at least two different institutions. The joint title shall only be awarded after the student has completed his/her studies at the selected institutions and has fulfilled the following minimum requirements:
(1) Successful application and nomination to enter the programme;
Details about the application and selection procedure are described in the “ICE Call for Application Model”.
(2) Study and perform research for at least 18 months at the primary institution and at least 12 months at the secondary institution;
The PhD Candidates will be jointly supervised by two supervisors—one at the primary institution and one at the secondary institution. A maximum period of 6 months can be spent at any institution participating in the ICE programme.
The student has to give a presentation about his research during her/his stay at the secondary institution.
(3) Pursued courses of a total of 20 ECTS;
The PhD Candidates must pursue courses of at least 10 ECTS from the ICE course modules of the primary institution and courses of at least 5 ECTS from the ICE course modules of the secondary institution. The lectures of the ICE course modules of all institutions are specified jointly by the PSC on a yearly basis.
1 For any further detailed information refer to http://en.wikipedia.org/wiki/European_Credit_Transfer_and_Accumulation_System.
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(4) Approved research skills of a total of 40 ECTS;
The PhD Candidates must demonstrate their research skills by an active participation at the ICE summer school and/or authorship of scientific papers. Each year an ICE summer school will be organized which accounts for the following credits.
- active participation at the ICE summer school: 10 ECTS
- presentation of the thesis contribution (preferably in third year): 10 ECTS
Active participation includes (i) providing a report about the scientific activities performed during the previous year, (ii) participating in the lectures and talks, and (iii) giving a presentation about the state of their own research. The PhD Candidates are required to participate in at least two ICE summer schools. The presentation of the thesis contribution is required.
The PhD Candidates can demonstrate their research skills by authorship of papers accepted in refereed journal or refereed conferences. One accepted scientific paper accounts for 5 ECTS; at most 2 papers can be taken into account.
(5) Supplementary skills of a total of 20 ECTS;
The following supplementary skills can get accounted for the PhD programme:
- Additional courses selected from any ICE course modules (max 10 ECTS)
- Soft-skills and non-technical courses (max 10 ECTS)
These courses must get approved by both supervisors at the primary and the secondary institution.
- International recognition of scientific contribution (max 10 ECTS)
An international recognition of a scientific contribution of the student such as a best paper award accounts for 5 ECTS. No credits can be accounted for an international recognition of a scientific paper, if credits for the same paper have already been taken into account under “approved research skills” (paragraph 4).
- External research collaboration (max 10 ECTS)
PhD Candidates can perform research at an external institution, i.e., the associated ICE partner institutions, during their PhD programme. An external research period of one month accounts for 5 ECTS. The external research collaboration has to be approved in advance by the supervisors at the primary and the secondary institutions.
(6) Approved dissertation (100 ECTS);
The dissertation must be approved by at least the supervisor at the primary institution and the supervisor at the secondary institution.
(7) PhD defence;
A PhD defence at the primary institution completes the PhD programme. The defence is performed in front of an international committee composed of members of at least the primary and the secondary institution. Members from other institutions of the ICE consortium may be part of the international committee as well.
Erasmus Mundus Joint Doctorate in
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Double Degree
The ICE Double Doctorate is a three year international PhD programme with a total of 180 ECTS. The PhD Candidates
must conduct the programme in at least two different institutions. The double title shall only be awarded after the
student has completed his/her studies at the selected institutions and has fulfilled the following minimum
requirements:
(1) Successful application and nomination to enter the programme;
Details about the application and selection procedure are described in the annexed document “ICE Call for
Application Model”.
Study and perform research for at least: 18 months in the Primary Institution; 12 months in the Secundary
institution; 6 months to be spent according to Primary and Secundary Institution regulations, taking into
account candidates PhD track activities. The PhD Candidates will be jointly supervised by two supervisors—
one at the primary institution and one at the secondary institution.
The student has to give a presentation about his research during her/his stay at the secondary institution.
(2) Pursued courses of a total of 20 ECTS;
The PhD Candidates must pursue courses of at least 10 ECTS from the ICE course modules of the primary
institution and courses of at least 5 ECTS from the ICE course modules of the secondary institution. The
lectures of the ICE course modules of all institutions are specified jointly by the PSC on a yearly basis.
(3) Approved research skills of a total of 40 ECTS;
The PhD Candidates must demonstrate their research skills by an active participation at the ICE summer
school and/or authorship of scientific papers. Each year an ICE summer school will be organized which
accounts for the following credits.
- active participation at the ICE summer school: 10 ECTS
- presentation of the thesis contribution (preferably in third year): 10 ECTS
Active participation includes (i) providing a report about the scientific activities performed during the
previous year, (ii) participating in the lectures and talks, and (iii) giving a presentation about the state of their
own research. The PhD Candidates are required to participate in at least two ICE summer schools. The
presentation of the thesis contribution is required.
The PhD Candidates can demonstrate their research skills by authorship of papers accepted in refereed
journal or refereed conferences. One accepted scientific paper accounts for 5 ECTS; at most 2 papers can be
taken into account.
(4) Supplementary skills of a total of 20 ECTS;
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The following supplementary skills can get accounted for the PhD programme:
- Additional courses selected from any ICE course modules (max 10 ECTS)
- Soft-skills and non-technical courses (max 10 ECTS)
These courses must get approved by both supervisors at the primary and the secondary institution.
- International recognition of scientific contribution (max 10 ECTS)
An international recognition of a scientific contribution of the student such as a best paper award
accounts for 5 ECTS. No credits can be accounted for an international recognition of a scientific
paper, if credits for the same paper have already been taken into account under “approved research
skills” (paragraph 4).
- External research collaboration (max 10 ECTS)
PhD Candidates can perform research at an external institution, i.e., the associated ICE partner
institutions, during their PhD programme. An external research period of one month accounts for 5
ECTS. The external research collaboration has to be approved in advance by the supervisors at the
primary and the secondary institutions.
(5) Approved dissertation (100 ECTS);
The dissertation must be approved by at least the supervisor at the primary institution and the supervisor at
the secondary institution.
(6) PhD defence;
A defense at the primary institution;
A defense at the secondary institution as well;
Both defenses are performed in front of an international committee composed by at least one member from the hosting institution plus at least one member from another institution from the ICE consortium that may require their presence. Members from other institutions of the ICE consortium may be part of the international committee as well.
Credits Assignment (Example)
CRITERION ACTIVITY TYPE OF EXAM ECTS
Knowledge Following at least four teaching modules Oral presentation of a research topic related to the courses
evaluated by the lecturer 20
Skills & Capabilities Report and official recognition of
research performance. Active participation at the ICE summer school and/or authorship of
scientific papers; report about the scientific activities performed. 40
Supplementary Skills/knowledge
Achievement of complementary skills and expertise.
Additional courses, Soft-skills and non-technical courses, International recognition of scientific contribution, External research
collaboration. 20
Outcome Approved Final Dissertation
The dissertation must be approved by at least two international supervisors (preferably from the primary and the secondary
institution. 100