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Annual Conference of the IEEE Industrial Electronics Society

作者： Najd Ouhajjou Peter Palensky Matthias Stifter Jessen Page Stefan Fenz A. Min Tjoa Energy Department AIT Austrian Institute of Technology Institute of Systems Engineering University of Applied Sciences and Arts Institute of Software Technology and Interactive Systems Technical University of Vienna

ISBN: (纸本)9781479902255

Two-thirds of the overall primary energy in the world is consumed in cities, resulting in 71 percent of all energy related greenhouse gas emissions. There are many ongoing initiatives to develop strategies to lower the high amount of emissions at the level of cities. However, energy planners face problems that are related to the complexity of the urban energy systems, encapsulating the components of the city together with their properties and interactions that are relevant to the planning process. The complexity of the problem increases given the unavailability of data and their multiple levels of detail (LOD). Therefore, there is a need for adequate tools to support the development of integrated energy strategies, defining specific quantifiable CO_2 reduction measures to be implemented at the city level. In this research, we perform an analysis of urban energy planning processes. Then, we extract the general requirements of decision support in this discipline. Then, we perform a general data availability review in cities. This process results in formalizing a modular methodology for the development of urban energy planning support software. This methodology is specific to urban energy planning, it ensures the modularity of the development process, it leads to flexible software that operates under different available LODs of data, and it addresses the problem of data availability at the development stage.

关键词： Ontology Energy planning support software development methodology Decision support Semantics Semantics PROCESS DEVELOPMENT data availability energy plan city Support programs Modularity decision making support Ontology software design city energy Energy strategies computer software

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Asynchronous Stereo Vision for Event-Driven Dynamic Stereo Sensor Using an Adaptive Cooperative Approach

Asynchronous Stereo Vision for Event-Driven Dynamic Stereo S...

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International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Ewa Piatkowska Ahmed Nabil Belbachir Margrit Gelautz Safety and Security Department AIT Austrian Institute of Technology Vienna Austria Institute for Software Technology and Interactive Systems Vienna University of Technology Vienna Austria

This paper presents an adaptive cooperative approach towards the 3D reconstruction tailored for a bio-inspired depth camera: the stereo dynamic vision sensor (DVS). DVS consists of self-spiking pixels that asynchronously generate events upon relative light intensity changes. These sensors have the advantage to allow simultaneously high temporal resolution (better than 10μs) and wide dynamic range (>120dB) at sparse data representation, which is not possible with frame-based cameras. In order to exploit the potential of DVS and benefit from its features, depth calculation should take into account the spatiotemporal and asynchronous aspect of data provided by the sensor. This work deals with developing an appropriate approach for the asynchronous, event-driven stereo algorithm. We propose a modification of the cooperative network in which the history of the recent activity in the scene is stored to serve as spatiotemporal context used in disparity calculation for each incoming event. The network constantly evolves in time - as events are generated. In our work, not only the spatiotemporal aspect of the data is preserved but also the matching is performed asynchronously. The results of the experiments prove that the proposed approach is well suited for DVS data and can be successfully used for our efficient passive depth camera.

关键词： Voltage control Stereo vision Cameras Cooperative systems Robot sensing systems Spatiotemporal phenomena Heuristic algorithms

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A Survey on Environmental Open Data in Austria

A Survey on Environmental Open Data in Austria

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IEEE International Conference on systems, Man, and Cybernetics

作者： Peter Wetz Amin Anjomshoaa A Min Tjoa Doctoral College Environmental Informatics Vienna University of Technology Vienna Austria Institute of Software Technology and Interactive Systems Vienna University of Technology Vienna Austria

ISBN: (纸本)9781479906505

Environmental Open Data has the potential to become a key strategy for the global endeavor of preserving the world's ecosphere. Therefore, this paper aims at researching the status quo of such data in Austria and exploring related advantages and shortcomings. First, the presented survey is motivated and put in perspective to relevant related work. Then, the approach to gaining the datasets is described and important parameters are specified. Subsequently, the results of the conducted survey are presented. Positive as well as negative highlights are pointed out. Many datasets with good features have been identified, however, there are still some drawbacks concerning data quality, diversity and content. Dealing with these issues and ultimately providing Linked Open Data would greatly improve the datasets and, ultimately, would allow for significantly better utilisation thereof. The goal of this work is to bring the concept of Open Data into the environmental domain by evaluating the environmental Open Data landscape in Austria.

关键词： Open Data Linked Open Data Environmental Informatics Austria open data environmental informatics semantic networks Dataset ecosphere

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On Visualizing Knowledge Flows at a University Department

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Procedia - Social and Behavioral Sciences 2013年 100卷 127-143页

作者： Florian Windhager Michael Smuc Lukas Zenk Paolo Federico Jürgen Pfeffer Wolfgang Aigner Department for Knowledge and Communication Management Danube University Krems Krems A-3500 Austria Institute of Software Technology and Interactive Systems Technical University Vienna Vienna A-1040 Austria CASOS Center Institute for Software Research Carnegie Mellon University Wean Hall 4103 USA

The analysis of dynamic network data has become an increasingly relevant research issue, showing a high potential for applied use in organizations. To unlock its potential also for the target user group of non-domain experts, we introduce a software prototype, which provides different views on network dynamics, intertwining network analytical measures with options of visual exploration. To demonstrate, how this approach can provide new access to questions of knowledge management and accessibility, a case study of a university department will be discussed. By combining multi-relational data of communication networks with attribute data of individual knowledge domains, we show how essential knowledge and change management issues can be reframed from a social network perspective and further developed towards integrated applications in organizations.

关键词： social network analysis network dynamics visual analytics knowledge management

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Replication data management: Needs and solutions - An initial evaluation of conceptual approaches for integrating heterogeneous replication study data

Replication data management: Needs and solutions - An initia...

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2013 ACM / IEEE International Symposium on Empirical software Engineering and Measurement, ESEM 2013

作者： Biffl, Stefan Serral, Estefania Winkler, Dietmar Condori-Fernandez, Nelly Dieste, Oscar Juristo, Natalia Institute of Software Technology and Interactive Systems CDL-Flex Vienna University of Technology Vienna Austria ProS Research Center Universitat Politècnica de València Valencia Spain Facultad de Informática Universidad Politécnica de Madrid Boadilla del Monte Spain Department of Computer Science and Engineering University of Oulu Oulu Finland

[Context] Replication Data Management (RDM) aims at enabling the use of data collections from several itera-tions of an experiment. However, there are several major chal-lenges to RDM from integrating data models and data from em-pirical study infrastructures that were not designed to cooperate, e.g., data model variation of local data sources. [Objective] In this paper we analyze RDM needs and evaluate conceptual RDM approaches to support replication researchers. [Method] We adapted the ATAM evaluation process to (a) analyze RDM use cases and needs of empirical replication study research groups and (b) compare three conceptual approaches to address these RDM needs: central data repositories with a fixed data model, heterogeneous local repositories, and an empirical ecosystem. [Results] While the central and local approaches have major issues that are hard to resolve in practice, the empirical ecosys-tem allows bridging current gaps in RDM from heterogeneous data sources. [Conclusions] The empirical ecosystem approach should be explored in diverse empirical environments. © 2013 IEEE.

关键词： Knowledge management

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Multi-dimensional Information Ordering to Support Decision-Making Processes

Multi-dimensional Information Ordering to Support Decision-M...

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IEEE Conference on Commerce and Enterprise Computing, CEC

作者： Stéphane Marchand-Maillet Birgit Hofreiter Department of Computer Science Centre Universitaire Informatique University of Geneva Carouge Switzerland Electronic Commerce Group Institute of Software Technology and Interactive Systems Vienna University of Technology Vienna Austria

ISBN: (纸本)9781479908585

Massive amounts of textual and digital data are created daily from business or public activities. The organisation, mining and summarization of such a rich and large information source is required to capture the essential and critical knowledge it contains. Such a mining is of strategic importance in many domains including innovation (eg to mine technological reviews and scientific literature) and electronic commerce (eg to mine customer reviews). Information content generally bears several important aspects, mapped onto visualisation dimensions, whose number needs to be reduced to enable relevant interactive exploration. In this paper, we propose a novel strategy to mine and organise document sets, in order to present them in a consistent manner and to highlight interesting and relevant information patterns they contain. We base our method on the formulation of a global optimisation problem solved by using the Traveling Salesman Problem (TSP) approach. We show how this compact formulation opens interesting possibilities for the mining of document collections mapped onto multidimensional information sets. We discuss the issue of scalability and show that associated scalable solutions exist. We demonstrate the effectiveness of our method over several types of documents, embedded into real business cases.

关键词： Data mining Vectors Feature extraction Scalability Monitoring Sorting Optimization

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Erratum to: Making sense of big data in health research: towards an EU action plan

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Genome medicine 2016年第1期8卷 118页

作者： Charles Auffray Rudi Balling Inês Barroso László Bencze Mikael Benson Jay Bergeron Enrique Bernal-Delgado Niklas Blomberg Christoph Bock Ana Conesa Susanna Del Signore Christophe Delogne Peter Devilee Alberto Di Meglio Marinus Eijkemans Paul Flicek Norbert Graf Vera Grimm Henk-Jan Guchelaar Yi-Ke Guo Ivo Glynne Gut Allan Hanbury Shahid Hanif Ralf-Dieter Hilgers Ángel Honrado D Rod Hose Jeanine Houwing-Duistermaat Tim Hubbard Sophie Helen Janacek Haralampos Karanikas Tim Kievits Manfred Kohler Andreas Kremer Jerry Lanfear Thomas Lengauer Edith Maes Theo Meert Werner Müller Dörthe Nickel Peter Oledzki Bertrand Pedersen Milan Petkovic Konstantinos Pliakos Magnus Rattray Josep Redón I Màs Reinhard Schneider Thierry Sengstag Xavier Serra-Picamal Wouter Spek Lea A I Vaas Okker van Batenburg Marc Vandelaer Peter Varnai Pablo Villoslada Juan Antonio Vizcaíno John Peter Mary Wubbe Gianluigi Zanetti European Institute for Systems Biology and Medicine 1 avenue Claude Vellefaux 75010 Paris France. cauffray@***. CIRI-UMR5308 CNRS-ENS-INSERM-UCBL Université de Lyon 50 avenue Tony Garnier 69007 Lyon France. cauffray@***. Luxembourg Centre for Systems Biomedicine University of Luxembourg 7 Avenue des Hauts Fourneaux 4362 Esch-sur-Alzette Luxembourg. rudi.balling@uni.lu. Wellcome Trust Sanger Institute Wellcome Genome Campus Hinxton Cambridge CB10 1SA UK. Health Services Management Training Centre Faculty of Health and Public Services Semmelweis University Kútvölgyi út 2 1125 Budapest Hungary. Centre for Personalised Medicine Linköping University 581 85 Linköping Sweden. Translational & Bioinformatics Pfizer Inc. 300 Technology Square Cambridge MA 02139 USA. Institute for Health Sciences IACS - IIS Aragon San Juan Bosco 13 50009 Zaragoza Spain. ELIXIR Wellcome Genome Campus Hinxton Cambridge CB10 1SD UK. CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Lazarettgasse 14 AKH BT25.2 1090 Vienna Austria. Department of Laboratory Medicine Medical University of Vienna Lazarettgasse 14 AKH BT25.2 1090 Vienna Austria. Max Planck Institute for Informatics Campus E1 4 66123 Saarbrücken Germany. Príncipe Felipe Research Center C/Eduardo Primo Yúfera 3 46012 Valencia Spain. University of Florida Institute of Food and Agricultural Sciences (IFAS) 2033 Mowry Road Gainesville FL 32610 USA. Bluecompanion Ltd 6 London Street (second floor) London W2 1HR UK. Technology Data & Analytics KPMG Luxembourg Société Coopérative 39 Avenue John F. Kennedy 1855 Luxembourg Luxembourg. Department of Human Genetics Department of Pathology Leiden University Medical Centre Einthovenweg 20 2333 ZC Leiden The Netherlands. Information Technology Department European Organization for Nuclear Research (CERN) 385 Route de Meyrin 1211 Geneva 23 Switzerland. Julius Center for Health Sciences and Primary Care University Medical Center

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2013年 7804 LNCS卷 V-VI页

作者： Mustofa, Khabib Neuhold, Erich J. Tjoa, A. Min Weippl, Edgar You, Ilsun Universitas Gadjah Mada Department of Computer Science and Electronics Sekip Utara Bls Yogyakarta 55281 Indonesia University of Vienna Faculty of Computer Science Währinger Straße 29 1190 Wien Austria Vienna University of Technology Institute of Software Technology and Interactive Systems Favoritenstraße 9-11 1040 Wien Austria Vienna University of Technology SBA Research Institute of Software Technology and Interactive Systems Favoritenstraße 9-11 1040 Wien Austria Korean Bible University School of Informatic Science 16 Danghyun 2-gil Nowon-gu Seoul 139-791 Korea Republic of

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Semantic inter-organizational performance analysis using the balanced scorecard methodology

Semantic inter-organizational performance analysis using the...

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35th International Convention on Information and Communication technology, Electronics and Microelectronics, MIPRO 2012

作者： Krathu, Worarat Pichler, Christian Zapletal, Marco Werthner, Hannes Institute for Software Technology and Interactive Systems Vienna University of Technology Austria

ISBN: (纸本)9789532330724

Evaluating inter-organizational relationships (IORs) is important in todays businesses for increasing competitiveness and business potential. Typically, IORs are measured by high-level key performance indicators (KPIs) such as trust, knowledge sharing, and others. However, these high-level KPIs are difficult to be measured quantitatively. It is therefore difficult to determine IORs and their outcomes since the evaluation of IORs results in a complex and ambiguous task. In this vision paper, we propose a set of research questions dealing with measuring and evaluating IORs. Based on these research questions, we define a conceptual framework including (i) the identification of KPIs from inter-organizational processes in combination with business information derived from EDIFACT messages and (ii) the alignment of KPIs to business goals by means of the Balanced Scorecard methodology and semantic technology. Having the approach at hand supports us in lifting operational information to the business level. The alignment between KPIs and business goals allows evaluating an organizations' IORs and results in two distinct advantages. First, the explicit connection between KPIs and business goals results in a justification of the relation between IORs and business achievements. Second, the evaluation of IORs against strategic goals can be achieved semi-automatically. © 2012 MIPRO.

关键词： Semantics

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Facilitating comprehensive benchmarking experiments on the million song dataset

Facilitating comprehensive benchmarking experiments on the m...

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13th International Society for Music Information Retrieval Conference, ISMIR 2012

作者： Schindler, Alexander Mayer, Rudolf Rauber, Andreas Institute of Software Technology and Interactive Systems Vienna University of Technology Austria

ISBN: (纸本)9789727521449

The Million Song Dataset (MSD), a collection of one million music pieces, enables a new era of research of Music Information Retrieval methods for large-scale applications. It comes as a collection of meta-data such as the song names, artists and albums, together with a set of features extracted with the The Echo Nest services, such as loudness, tempo, and MFCC-like features. There is, however, no easily obtainable download for the audio files. Furthermore, labels for supervised machine learning tasks are missing. Researchers thus are currently restricted on working solely with these features provided, limiting the usefulness of MSD. We therefore present in this paper a more comprehensive set of data based on the MSD, allowing its broader use as benchmark collection. Specifically, we provide a wide and growing collection of other well-known features in the MIR domain, as well as ground truth data with a set of recommended training/test splits. We obtained these features from audio samples provided by ***, and metadata from the All Music Guide. While copyright prevents re-distribution of the audio snippets per se, the features as well as metadata are publicly available on our website for benchmarking evaluations. In this paper we describe the pre-processing and cleansing steps applied, as well as feature sets and tools made available, together with first baseline classification results. © 2012 International Society for Music Information Retrieval.

关键词： Benchmarking

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