Markus Schedl | Thursday, 1st October 2015 | 14:00 | E.2.42

Abstract:
Social media represent an unprecedented source of information about every topic of our daily lives. Since music plays a vital role for almost everyone, information about music items and artists is found in abundance in user-generated data. In this talk, I will report on our recent research on exploiting social media to extract music-related information, aiming to improve music retrieval and recommendation. More precisely, I will elaborate on the following questions:

• Which factors are important to human perception of music?
• How to extract and annotate music listening events from social media, in particular microblogs?
• What can this kind of data tell us about the music taste of people around the world?
• How to make accessible music listening data from social media in an intuitive way?
• How to build music recommenders tailored to user characteristics?

Bio:
Markus Schedl is an associate professor at the Johannes Kepler University Linz / Department of Computational Perception. He graduated in Computer Science from the Vienna University of Technology and earned his Ph.D. in Technical Sciences from the Johannes Kepler University Linz. Markus further studied International Business Administration at the Vienna University of Economics and Business Administration as well as at the Handelshögskolan of the University of Gothenburg, which led to a Master’s degree.
Markus (co-)authored more than 100 refereed conference papers and journal articles (among others, published in ACM Multimedia, SIGIR, ECIR, IEEE Visualization; Journal of Machine Learning Research, ACM Transactions on Information Systems, Springer Information Retrieval, IEEE Multimedia). Furthermore, he is associate editor of the Springer International Journal of Multimedia Information Retrieval and serves on various program committees and reviewed submissions to several conferences and journals (among others, ACM Multimedia, ECIR, IJCAI, ICASSP, IEEE Visualization; IEEE Transactions of Multimedia, Elsevier Data & Knowledge Engineering, ACM Transactions on Intelligent Systems and Technology, Springer Multimedia Systems).
His main research interests include web and social media mining, information retrieval, multimedia, and music information research.
Since 2007, Markus has been giving several lectures, among others, „Music Information Retrieval“, „Exploratory Data Analysis“, „Multimedia Search and Retrieval“, „Learning from User-generated Data“, „Multimedia Data Mining“, and „Intelligent Systems“. He further spent guest lecturing stays at the Universitat Pompeu Fabra, Barcelona, Spain, the Utrecht University, the Netherlands, the Queen Mary, University of London, UK, and the Kungliga Tekniska Högskolan, Stockholm, Sweden.

Contact Details:
Dr. Markus Schedl
Deptartment of Computational Perception
Johannes Kepler University
Altenberger Straße 69
4040 Linz, Austria
Tel.: +43 732 2468 1512
e-mail: markus.schedl@jku.at
Website: http://www.cp.jku.at/people/schedl
Full publication record is available at http://www.cp.jku.at/people/schedl/publications.html

Mustafa Alkhazraji | Thursday, 24th September 2015 | 11.00 am | B04, L4101

Abstract: The tremendous growth of mass applications such as digital cameras, Liquid-Crystal displays (LCD), Light Emission Diode (LED) displays and smart phones is due to the low cost of the integrated sensor manufacturing. Color sensors like CMOS photosensors are used as the main part of different applications. In this research, a fully integrated photo sensor in standard CMOS technology is presented, which enables light spectral analysis in the visible light range without additional optional component such as color filters. A new CMOS photo sensor has been proposed as a low cost alternative solution for the color sensing applications. The aim of this research is to investigate and implement integrated Digital Signal Processor (DSP) device as a complementary part of the proposed CMOS color sensor. The DSP has been designed to reconstruct and match the non-ideal output signals from the new CMOS color sensor structure with the tristimulus values X, Y and Z (color standards) by using linear transformation. The implemented design has been analyzed and verified at each stage of the work, using MATLAB, Modelsim from MentoGraphics, Design Compiler from Synopsys and Velocity/Encounter from Cadence Design Systems. In the end, the final layout of the design has been presented. Finally, due to the implementation of the DSP, a high number of sensor output signals enable the high accuracy of the colorimetric measurement by using pseudo-inverse matrix. Furthermore, the number of the word length has been used to represent the photosensor output signals and the linear transformation matrix. The latter is directly proportional to the measured tristimulus values X, Y and Z as well as the power and the silicon-chip area.

Keywords: Color sensor, CMOS technology, Digital Signal Processor, Integrated sensor, Color standards.

Der Rückblick zum TEWI-Kolloquium von Carlo Combi and Roberto Posenato am 9.7.2015 beinhaltet die Videoaufzeichnung:

Video

Click here!

Abstract: Business Process (BP) technology has emerged as one of the leading technologies in modeling, redesigning, and executing organisational processes in several different application domains. Among them, the representation and management of health and clinical processes have been attracting a growing interest. Such processes are in general related to the way each health organization provides the required healthcare services. Health and clinical processes underlie the specification and application of clinical protocols, clinical guidelines, clinical pathways, and the most common clinical/administrative procedures. Current BP systems are lacking in effective management of three general key aspects that are common (not only) in the clinical/health context: data dependencies, exception handling, and temporal constraints. In this talk we will first introduce and discuss recent advances in business process modeling with respect to the healthcare/medical domain. Then, we will introduce some recent results on algorithms for checking temporal properties of business processes in presence of explicit temporal constraints among tasks.

Bio Carlo Combi: In 1987 he received the Laurea Degree in E.E. by the Politecnico of Milan. In 1993 he received the Ph.D. degree in biomedical engineering. Since November 2001, he is with the Department of Computer Science of the University of Verona: from November 2001 to February 2005, he was Associate Professor of Computer Science; since March 2005, he is Professor of Computer Science. From October 2007 to September 2012 he was head of the Computer Science Department. Main research interests are related to the database and information system field, with an emphasis on the management of clinical information. The two main areas are temporal information systems (time-oriented data and process modelling) and multimedia databases. He is author of more than 100 papers published on international journals and proceedings of international conferences. He is author, with Elpida Keravnou – University of Cyprus and Yuval Shahar – Ben-Gurion University of the Negev, of the book “Temporal Information Systems in Medicine”, Springer, 2010. He is involved in the scientific activity of several scientific international journals and conferences. Since January 1999 he is editorial Board Member, journal Artificial Intelligence in Medicine. Since July 2009 he is chair of the Artificial Intelligence in Medicine Society (AIME). He is guest editor of several special issues of international journals (Methods of Information in Medicine, Annals of Mathematics and Artificial Intelligence, Artificial Intelligence in Medicine, Journal of Intelligent Information Systems, Computers in Biology and Medicine, ACM Transactions on Intelligent Systems and Technology).

Bio Roberto Posenato: He took a degree in Computer Science in 1991 and a doctor’s degree in Computational Mathematics in 1996 at the University of Milan (Italy). Since November 2000, he is assistant professor at the same department. He has been lecturerPosenato for some courses in the theory of algorithms and computational complexity since 1996. Main research interests are related to approximation algorithms for combinatorial optimization problems, with emphasis for graph-based problems; moreover, he is interested into the study of time reasoning in workflow/business process systems and in temporal constraint networks. He is reviewer for national and international journals, magazines, and conferences and he has been involved in several national research projects.

Abstract:

In recent years many times sustainability and renewable energy consumption have been set on the agenda. However, the pressing issue how to make people reduce their amount of energy consumed – or their switching  towards green alternatives – has received far less research attention. The academic discipline of behavioral economics has much to offer to this debate. In the presentation we will summarize prior research on the role of individual differences and various pricing and framing techniques that have proven to be helpful in making people switch to green energy. We will also address challenges and future directions in behavioral energy economics.

Bio:

Laurens Rook is Assistant Professor at Delft University of Technology, the Netherlands. He received his Ph.D. from the Erasmus University Rotterdam (in 2008), and his bachelor and master’s degrees from the  University of Amsterdam, the Netherlands (in 2001; MA Thesis on Mass Psychology in Fine Art and Advertising).  His research focuses on herd and imitative behavior in creative context, and is published in the Creativity Research Journal.  His second focus is on behavioral informatics. Laurens collaborates with the Learning Agents Research Group at Erasmus (LARGE). A recent paper on using social media apps to make people consume green energy  (together with University of Connecticut, USA) was awarded best poster  award (2nd prize, the 2014 Conference on Information Systems and Technology).  He lectures on Research Methodology,   Statistics, and Group Dynamics, but also is a graduated professional artist (Academy of Arts Rotterdam, 1997) with collected work in the Municipal Archives of Rotterdam, the Netherlands, and the National Art Collection of Ireland.

Abstract:
Well-studied and commonly used in database query languages, aggregates form an intuitive means of representing knowledge. Since logic programs can be viewed as a database query language, it is natural to consider aggregates also in their context. However, logic programs allow for recursive specifications, which are either disallowed or allowed only in a restricted form in most database query languages. It turns out that aggregates used in connection with recursion raise a number of semantic issues, some of them reminiscent of issues with the semantics of negation, a hot topic in logic programming about three decades ago. One of the semantics for logic programs with negation that emerged and has proved itself to be viable is the stable model semantics or answer set semantics. In this talk we will show how ideas from this semantics can be transferred to programs with aggregates, what issues arise when doing so, and what options there are to overcome these. Furthermore, we will outline properties of the resulting semantics and the availability of system support. Finally, we show that all of these considerations are not really limited to aggregates, but more general constructs, such as those found in HEX programs or description logic programs.

Bio:
Wolfgang Faber serves as Professor of Artificial Intelligence at the University of Huddersfield (UK). Before that, he was a Reader at the same university, an Associate Professor at the University of Calabria (Italy), and an Assistant Professor at the Vienna University of Technology, where he also obtained his PhD in 2002. From 2004 to 2006 he was on an APART grant of the Austrian Academy of Sciences. His general research interests are in knowledge representation, logic programming, nonmonotonic reasoning, planning, and knowledge-based agents. He has published more than 100 refereed articles in major journals, collections and conference proceedings in these areas. He is one of the architects of DLV, a state-of-the-art system for computing answer sets of disjunctive deductive databases, which is used all over the world. He has acted as a chair for several workshops and conferences, and has been on the program committees of many of the major conferences of his research areas, and has served on the editorial board and as a reviewer for many journals and conferences on Artificial Intelligence, Knowledge Representation, and Logic Programming.

Abstract:

Business Process (BP) technology has emerged as one of the leading technologies in modeling, redesigning, and executing organisational processes in several different application domains. Among them, the representation and management of health and clinical processes have been attracting a growing interest. Such processes are in general related to the way each health organization provides the required healthcare services. Health and clinical processes underlie the specification and application of clinical protocols, clinical guidelines, clinical pathways, and the most common clinical/administrative procedures. Current BP systems are lacking in effective management of three general key aspects that are common (not only) in the clinical/health context: data dependencies, exception handling, and temporal constraints.
In this talk we will first introduce and discuss recent advances in business process modeling with respect to the healthcare/medical domain. Then, we will introduce some recent results on algorithms for checking temporal properties of business processes in presence of explicit temporal constraints among tasks.

Bio Carlo Combi:

In 1987 he received the Laurea Degree in E.E. by the Politecnico of Milan. In 1993 he received the Ph.D. degree in biomedical engineering. Since November 2001, he is with the Department of Computer Science of the University of Verona: from November 2001 to February 2005, he was Associate Professor of Computer Science; since March 2005, he is Professor of Computer Science. From October 2007 to September 2012 he was head of the Computer Science Department. Main research interests are related to the database and information system field, with an emphasis on the management of clinical information. The two main areas are temporal information systems (time-oriented data and process modelling) and multimedia databases. He is author of more than 100 papers published on international journals and proceedings of international conferences. He is author, with Elpida Keravnou – University of Cyprus and Yuval Shahar – Ben-Gurion University of the Negev, of the book „Temporal Information Systems in Medicine“, Springer, 2010. He is involved in the scientific activity of several scientific international journals and conferences. Since January 1999 he is editorial Board Member, journal Artificial Intelligence in Medicine. Since July 2009 he is chair of the Artificial Intelligence in Medicine Society (AIME). He is guest editor of several special issues of international journals (Methods of Information in Medicine, Annals of Mathematics and Artificial Intelligence, Artificial Intelligence in Medicine, Journal of Intelligent Information Systems, Computers in Biology and Medicine, ACM Transactions on Intelligent Systems and Technology).

Bio Roberto Posenato:

He took a degree in Computer Science in 1991 and a doctor’s degree in Computational Mathematics in 1996 at the University of Milan (Italy). Since November 2000, he is assistant professor at the same department. He has been lecturer for some courses in the theory of algorithms and computational complexity since 1996. Main research interests are related to approximation algorithms for combinatorial optimization problems, with emphasis for graph-based problems; moreover, he is interested into the study of time reasoning in workflow/business process systems and in temporal constraint networks. He is reviewer for national and international journals, magazines, and conferences and he has been involved in several national research projects.

Antrittsvorlesung von Univ.-Prof. Dr. Andrea M. Tonello | 23. Juni 2015 | 17 Uhr c.t. im HS 2

ANDREA M. TONELLO received the laurea in electrical engineering (1996) and the Ph.D in telecommunications (2003) from the University of Padova, Italy. On February 1997, he joined Lucent Technologies where he worked on cellular communications in the Bell Labs Advanced Wireless Technology Laboratory, Whippany, NJ. He was promoted to technical manager in 2002 and appointed managing director of the Bell Labs Italy di- vision. In January 2003, he joined the Uni- versity of Udine, Italy. He became aggregate professor in 2005 and associate professor in 2014. Herein, he founded the Wireless and Power Line Communications Lab and the spin-off company WiTiKee. He was awarded the Italian full professor habilitation in 2013. In September 2014, he became full professor at the University of Klagenfurt, Austria, where he chairs the group on Embedded Communication Systems.

His research focuses on wireless and power line communications, embed- ded and smart systems. He received the Bell Labs Recognition of Excellence award (2003), the Distinguished Visiting Fellowship from the Royal Academy of Engineering, UK (2010) and the Distinguished Lecturer Award by the IEEE Vehicular Technology Society (2011-15). He is the co-recipient of five best paper awards. He was the general chair of IEEE ISPLC 2011 and IEEE Smart- GridComm 2014. He serves as an associate editor for the IEEE Transactions on Communications and IEEE Access. He is the chair of the IEEE ComSoc Technical Committee on Power Line Communications.

Wir freuen uns sehr auf Ihre/Deine Teilnahme und bitten um kurze Bestätigung per E-Mail an marlene.starc@aau.at.

Der Rückblick zum TEWI-Kolloquium von Prof. Stefan Wagner am 1.6.2015 beinhaltet die Folien:

Abstract: Cloning means the use of copy-paste as method in developing software artefacts. This practice has several problems, such as unnecessary increase of these artefacts, and thereby increased comprehension and change efforts, as well as potential inconsistencies. The automatic detection of clones has been a topic for research for several years now and we have made huge progress in terms of precision and recall. This led to a series of empirical analyses we have performed on the effects and the amount of cloning in code, models and requirements. We continue to investigate the effects of cloning and work on extending clone detection to functionally similar code. This talk will give insights into how clone detection works and the empirical results we have gathered.

Short CV: Stefan Wagner is full professor for software engineering at the University of Stuttgart. He holds a PhD in computer science from TU Munich, where he also worked as a post-doc. His main research interests are quality engineering, requirements engineering, agile software development and safety engineering; all tackled using empirical research.

Abstract:
Side-channel analysis have been introduced in the late nineties by Kocher et al. [1] to recover the secret keys of cryptographic implementations by exploiting the information leaked over side-channels. For embedded cryptographic devices typical side-channels are represented by the power consumption or by the electro-magnetic (EM) field emanations of physical implementations when executing cryptographic algorithms. Over the last two decades a lot of side-channel attacks have been developed and a variety of countermeasures have been proposed in literature to thwart side-channel analysis. Nevertheless, the quest after improved attacks and countermeasures is still a very active area of research, as testified by the many conferences and recent developments. In this talk, we provide an introduction to side-channel attacks covering some main topics like measurement setup, leakage models and statistical analysis. Then, we provide an overview on typical countermeasures against side-channel attacks covering different level of abstractions (circuit, algorithmic and protocol level).

[1] P. Kocher, J. Jaffe, and B. Jun. Differential Power Analysis. In M.J. Wiener, editor, Advances in Cryptology – CRYPTO ?99, volume 1666 of Lecture Notes in Computer Science, pages 388-397. Springer, 1999.

CVs:
Hermann Seuschek studied electrical engineering and information technology at Technische Universität München. Afterwards he worked for the central research and development department within the Siemens AG on topics related to applied cryptography and security for embedded systems. He left Siemens and joined the Institute for Security in Information Technology at Technische Universität München to pursue research in the field of automated side channel hardening of cryptographic algorithms.

Fabrizio De Santis studied computer engineering at Politecnico di Milano and completed his thesis at Advanced System Technology (AST) Laboratories (R&D) of STMicroelectronics. In 2011 he joined the Institute for Security in Information
Technology at Technische Universität München. In the period 2011 – 2013 he worked on the development of secure cryptographic implementations at Infineon Technologies AG in München.

Abstract:
The goal of the lecture is to present the latest achievements in Answer Set Programming (ASP). In particular, the focus of the lecture is on algorithms for solving optimization problems in ASP, that is, problems encoded by ASP programs with weak constraints. As usual in ASP, solutions of a problem instance are represented by its stable models, or answer sets. If the input program also comprises weak constraints, each of its stable model is associated with a cost determined by the unsatisfied weak constraints. Hence, weak constraints define a cost function, so that stable models of smaller cost are preferred.
The lecture overviews several algorithms for computing the most preferred, or optimal, stable models, and provides some details on core-guided algorithms, which proved to be effective on industrial instances of MaxSAT, the optimization variant of the satisfiability problem for propositional formulas. These algorithms work by iteratively checking satisfiability of a formula that is relaxed at each step by using the information provided by unsatisfiable cores, i.e., sets of weak constraints that cannot be jointly satisfied by any stable model of the input program.
The lecture is of the interest for both students visiting Logic Programming course as well as researchers of technical faculty working on declarative solving of hard problems.

Bio:
Dr. Mario Alviano received his master degree from University of Calabria in 2007 and his PhD in 2010 from the same university. Both works were distinguished by awards: the master thesis won the “Italian best thesis in Artificial Intelligence” a prize awarded by AI*IA, the Italian Association for Artificial Intelligence and PhD thesis was one among three dissertations awarded with a honorable mention by the European Coordinating Committee for Artificial Intelligence (ECCAI). Since 2011 he worked as a post doc and then as Assistant Professor at the Department of Mathematics and Computer Science, University of Calabria. The research interests of Dr. Alviano are spread throughout the field of knowledge representation and reasoning with the main focus on theoretical background and applications of answer set programming.