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11th German Conference on Chemoinformatics (GCC 2015) Abstracts

JOURNAL OF CHEMINFORMATICS 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

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Systematic use of computational methods allows stratification of treatment responders in glioblastoma multiforme

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Systems Biomedicine 2013年第2期1卷 130-136页

作者： Riku Louhimo Viljami Aittom?ki Ali Faisal Marko Laakso Ping Chen Kristian Ovaska Erkka Valo Leo Lahti Vladimir Rogojin Samuel Kaski Sampsa Hautaniemi* Systems Biology Laboratory Genome-scale Biology Research Program University of Helsinki Helsinki Institute of Information Technology (HIIT) Department of Information and Computer Science Aalto University

Background:Cancers are complex diseases whose comprehensive characterization requires genome-scale molecular data at multiple levels from genetics to transcriptomics and clinical data. Using our recently published Anduril bioinformatics framework and novel computational approaches, such as dependency analysis, we identify key variables at miRNA, copy number variation, expression, methylation, and pathway levels in glioblastoma multiforme (GBM) progression and drug resistance. Furthermore, we identify characteristics of clinically relevant subgroups, such as patients treated with temozolomide and patients with an EGFRvIII mutation, which is a constitutively active variant of ***:We identify several novel genomic regions and transcript profiles that may contribute to GBM progression and drug resistance. All results and Anduril scripts are available at http://***/camda/.Conclusions:Our results highlight the need for approaches that define context at several levels in order to identify genomic regions or transcript profiles playing key roles in cancer progression and drug resistance.

关键词： data integration data mining dependency analysis

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Implementation of a low cost home energy saver based on OpenWrt

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International Conference on IT Convergence and Security, ICITCS 2012

作者： Park, Se-Hwan Shin, Hyun-Jun Kim, Myoung-Seo Kim, Cheong-Ghil ReSEAT Program Korea Institute of Science and Technology Information Daejeon Korea Republic of Department of Computer Science Namseoul University Cheonan Korea Republic of Department of EECS Henry Samueli School of Engineering University of California Irvine CA United States

ISBN: (纸本)9789400758599

This paper introduces a system that can effectively save home energy by applying a small embedded system through remote control. We used a wireless router based on OpenWrt for the platform to develop an embedded system and a smart phone for the remote LED light control. The system was implemented by connecting a wireless router with an OS of OpenWrt installed and an interface board with an LED attached. The smart phone, which was the remote control device, was implemented by TCP/IP programming. The operation of the remote control system was verified by socket communication between the smart phone and the wireless router, and by USB communication between the wireless router and the interface board. © 2013 Springer Science+Business Media.

关键词： Energy conservation

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Privacy Preservation Scheme for Multicast Communications in Smart Buildings of the Smart Grid

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Smart Grid and Renewable Energy 2013年第4期4卷 313-324页

作者： Depeng Li Zeyar Aung Srinivas Sampalli John Williams Abel Sanchez Computing and Information Science Program Masdar Institute of Science and Technology Abu Dhabi UAE Faculty of Computer Science Dalhousie University Halifax Canada Massachusetts Institute of Technology (MIT) Cambridge USA.

Privacy preservation is a crucial issue for smart buildings where all kinds of messages, e.g., power usage data, control commands, events, alarms, etc. are transmitted to accomplish the management of power. Without appropriate privacy protection schemes, electricity customers are faced with various privacy risks. Meanwhile, the natures of smart grids and smart buildings—such as having limited computation power of smart devices and constraints in communication network capabilities, while requiring being highly reliable—make privacy preservation a challenging task. In this paper, we propose a group key scheme to safeguard multicast privacy with the provisions of availability, fault-tolerance, and efficiency in the context of smart buildings as a part the smart grid. In particular, hybrid architecture accommodating both centralized and contributory modes is constructed in order to achieve both fault-tolerance and efficiency with only one set of group key installed. Key trees are sophisticatedly managed to reduce the number of exponentiation operations. In addition, an individual rekeying scheme is introduced for occasional joining and leaving of member smart meters. Experimental results, on a simulation platform, show that our scheme is able to provide significant performance gains over state-of-the-art methods while effectively preserving the participants’ privacy.

关键词： AMI Building Area Networks Group Key Multicasting Privacy Smart Building Smart Grid

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Hands-on learning of Cooperation technology: Combining knowledge construction and reflection

Hands-on learning of Cooperation Technology: Combining knowl...

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IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

作者： Mikhail Fominykh Ekaterina Prasolova-Førland Monica Divitini Sobah Abbas Petersen Program for learning with ICT Norwegian University of Science and Technology Trondheim Norway Department of Computer and Information Science Norwegian University of Science and Technology Trondheim Norway

Project work is an important part of university education and workplace activities. However, cooperation problems are common in the learning process. The purpose of the study we present is to address these challenges by designing a Cooperation technology course and studying its outcomes. We applied social constructivist and reflective learning approaches and used various technologies as platforms for project work. Based on study data, we analyze collaborative workflows in and between student groups, use of technological ecologies, and the outcomes of their work. As a result, we provide implications for combining social constructivist and reflective learning approaches in course design.

关键词： Collaboration Reflection Communities Educational institutions Media computers

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Cross-camera complementary vehicle matching via feature expandsion for video forensics

Cross-camera complementary vehicle matching via feature expa...

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IEEE International Symposium on Consumer Electronics (ISCE)

作者： Chao-Yung Hsu Chih-Yang Lin Li-Wei Kang Hong-Yuan Mark Liao Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science and Information Engineering Asia University Taichung Taiwan Graduate School of Engineering Science and Technology-Doctoral Program and Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781467361989

In this paper, we will investigate a more challenging vehicle matching problem. The problem is formulated as invariant image feature matching among opposite viewpoints of cameras, i.e. complementary object matching. For example, a front vehicle object may be given as a query to retrieve a rear vehicle object of the same vehicle. To solve the complementary object matching, invariant image feature is first extracted based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, the ASIFT feature is expanded via a special vehicle database. As a result, cross-camera vehicle matching with the help of complementary part can be greatly improved. Experimental results demonstrate the effectiveness of the proposed algorithm and the feasibility to video forensics applications.

关键词： Vehicles Cameras Databases Feature extraction Visualization Digital forensics

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Cross-camera vehicle tracking via affine invariant object matching for video forensics applications

Cross-camera vehicle tracking via affine invariant object ma...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Chao-Yung Hsu Li-Wei Kang Hong-Yuan Mark Liao Institute of Information Science Academia Sinica Taipei Taiwan Graduate School of Engineering Science and Technology-Doctoral Program and Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781479900145

The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications.

关键词： Vehicles Visualization Cameras Feature extraction Transforms Robustness Forensics

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Music Recommendation Based on Multiple Contextual Similarity information

Music Recommendation Based on Multiple Contextual Similarity...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Chih-Ming Chen Ming-Feng Tsai Jen-Yu Liu Yi-Hsuan Yang Department of Computer Science & Program in Digital Content and Technology National Chengchi University Taipei Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan

This paper proposes a music recommendation approach based on various similarity information via Factorization Machines (FM). We introduce the idea of similarity, which has been widely studied in the filed of information retrieval, and incorporate multiple feature similarities into the FM framework, including content-based and context-based similarities. The similarity information not only captures the similar patterns from the referred objects, but enhances the convergence speed and accuracy of FM. In addition, in order to avoid the noise within large similarity of features, we also adopt the grouping FM as an extended method to model the problem. In our experiments, a music-recommendation dataset is used to assess the performance of the proposed approach. The datasets is collected from an online blogging Web site, which includes user listening history, user profiles, social information, and music information. Our experimental results show that, with various types of feature similarities the performance of music recommendation can be enhanced significantly. Furthermore, via the grouping technique, the performance can be improved significantly in terms of Mean Average Precision, compared to the traditional collaborative filtering approach.

关键词： Feature extraction Frequency modulation Vectors Recommender systems History Music Data mining

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Natural language cognition of humor by humans and computers: A computational semantic approach

Natural language cognition of humor by humans and computers:...

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IEEE International Conference on Cognitive Informatics

作者： J. M. Taylor V. Raskin Department of Computer and Information Technology and Center for the Education and Research in InformationAssurance and Security Purdue University West Lafayette IN USA Department of English Linguistics Program and Center for the Education and Research in Information Assurance and Security Purdue University West Lafayette IN USA

This paper deals with a contribution of computational analysis of verbal humor to natural language cognition. After a brief introduction to the growing area of computational humor and of its roots in humor theories, it describes and compares the results of a human-subject and computer experiment. The specific interest is to compare how well the computer, equipped with the resources and methodologies of the Ontological Semantic technology, a comprehensive meaning access approach to natural language processing, can model several aspects of the cognitive behaviors of humans processing jokes from the Internet.

关键词： Instruments computers Psychology Semantics Cognition Internet Natural languages

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Available bandwidth-aware cell selection for expanded regions of small cells adopting ABS

Available bandwidth-aware cell selection for expanded region...

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International Conference on information and Communication technology Convergence (ICTC)

作者： Mncedisi Bembe Jeongchan Kim Thomas Olwal Youngnam Han Global Information and Telecommunication Technology Program KAIST Daejeon Republic of Korea Department of Electrical Engineering and Computer Science KAIST Daejeon Republic of Korea Meraka Institute CSIR Pretoria South Africa

ISBN: (纸本)9781479906963

Cell selection in current LTE-Advanced depend on reference signal received power or reference signal received quality which results to low user association probability. Therefore, we propose an aggregate objective cell selection technique based on enhanced inter-cell interference coordination technique developed by 3GPP in Rel-10 known as almost blank subframe. We also adopt the use of cell range expansion technique as means to encourage offloading. Cell range expansion was introduced in LTE-advanced, it encourages user equipment to select a small cell with a weakest signal as thier serving cell by adding a positive bias in cell selection process. Simulation shows that the proposed scheme results to high user association probability, while giving superior performance in average throughput compared to conventional single objective base cell selection for cell range expansion.

关键词： Interference Macrocell networks Bandwidth Linear programming Gain Long Term Evolution Base stations

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