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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

BMC NEUROscience 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Heterogeneous Error-Resilient Scheme for Spectral Analysis in Ultra-Low Power Wearable Electrocardiogram Devices

Heterogeneous Error-Resilient Scheme for Spectral Analysis i...

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IEEE computer Society Annual Symposium on VLSI

作者： Soumya Basu P. Garcia del Valle Georgios Karakonstantis Giovanni Ansaloni David Atienza Embedded Systems Laboratory Ecole Polytechnique Fédérale de Lausanne Switzerland Embedded Syst. Lab. Ecole Polytechnique Federale de Lausanne Lausanne VD CH Electrical Engineering and Computer Science Queen's University Belfast United Kingdom Faculty of Informatics Università della Svizzera Italiana Lugano Switzerland

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.

关键词： Discrete wavelet transforms Error correction codes Biomedical monitoring Electrocardiography Memory management Spectral analysis Energy efficiency

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A Novel Hybrid Discrete Cosine Transformation and Visual Cryptographic Technique for Securing Digital Images

A Novel Hybrid Discrete Cosine Transformation and Visual Cry...

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International Conference on computer Modeling and Simulation, UKSIM

作者： Quist-Aphetsi Kester Laurent Nana Anca Christine Pascu Sophie Gire Jojo M. Eghan Nii Narku Quaynor Department of Computer Science and Information Technology University of Cape Coast Cape Coast Ghana Faculty of Informatics Ghana Technology University College Accra Ghana Lab-STICC (UMR CNRS 6285) University of Brest France UFR Sci. et Tech & Lab.-STICC Eur. Univ. of Brittany Brest France University of Cape Coast Cape Coast Central GH

ISBN: (纸本)9781479987146

Security of digital images in today's cyber is a major concern. Transmission of compressed and uncompressed multimedia data is necessary for communication between different devices. Devices of different screen features and resolution need very efficient and fast compression techniques in order to maintain visual features of transmitted media. Robustness is of a key consideration and importance in image compression techniques. Full recovery of images after compression is a challenge for image compression algorithms. It is practically closely impossible for most encrypted-compressed-images or compressed-encryptedimages to be efficiently and fully reconstructed. In this paper we proposed a robust, efficient and fully recoverable encrypted-compressed image based on hybrid discrete cosine transformation and visual cryptographic technique for securing digital images. We first encrypted the image without pixel loss and then compressed the image which resulted into pixel loss during the compression phase. We decrypted the compressed image by obtaining perfect visuals but losses in pixel values. The analysis of the process proved to be an efficient way of encrypting images and compressing them for other channels with less data capacity without the worry of visual loss as well as ensuring security of the data during transmission. The programming and implementation was done using MATlab.

关键词： Image coding Discrete cosine transforms Visualization Digital images Encryption

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A dialogue system for ensuring safe rehabilitation

A dialogue system for ensuring safe rehabilitation

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8th International Conference on Universal Access in Human-computer Interaction, UAHCI 2014 - Held as Part of 16th International Conference on Human-computer Interaction, HCI International 2014

作者： Papangelis, Alexandros Galatas, Georgios Tsiakas, Konstantinos Lioulemes, Alexandros Zikos, Dimitrios Makedon, Fillia Heracleia Human Centered Computing Lab. Computer Science and Engineering Dept. University of Texas Arlington TX United States Institute of Informatics and Telecommunications NCSR Demokritos Athens Greece

ISBN: (纸本)9783319074450

Dialogue Systems (DS) are intelligent user interfaces, able to provide intuitive and natural interaction with their users, through a variety of modalities. We present, here, a DS whose purpose is to ensure that patients are consistently and correctly performing rehabilitative exercises, in a tele-rehabilitation scenario. More specifically, our DS operates in collab.ration with a remote rehabilitation system, where users suffering from injuries, degenerative disorders and others, perform exercises at home under the (remote) supervision of a therapist. The DS interacts with the users and makes sure that they perform their prescribed exercises correctly and according to the specified, by the therapist, protocol. To this end, various sensors are utilized, such as Microsoft's Kinect, the Wi-Patch and others. © 2014 Springer International Publishing.

关键词： Patient rehabilitation

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROscience 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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Combining Text Mining and Data Mining for Bug Report Classification

Combining Text Mining and Data Mining for Bug Report Classif...

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International Conference on Software Maintenance (ICSM)

作者： Yu Zhou Yanxiang Tong Ruihang Gu Harald Gall College of Computer Science Nanjing University of Aeronautics and Astronautics State Key Lab. of Novel Software Technology Nanjing University China Department of Informatics University of Zurich Switzerland

Misclassification of bug reports inevitably sacrifices the performance of bug prediction models. Manual examinations can help reduce the noise but bring a heavy burden for developers instead. In this paper, we propose a hybrid approach by combining both text mining and data mining techniques of bug report data to automate the prediction process. The first stage leverages text mining techniques to analyze the summary parts of bug reports and classifies them into three levels of probability. The extracted features and some other structured features of bug reports are then fed into the machine learner in the second stage. Data grafting techniques are employed to bridge the two stages. Comparative experiments with previous studies on the same data -- three large-scale open source projects -- consistently achieve a reasonable enhancement (from 77.4% to 81.7%, 73.9% to 80.2% and 87.4% to 93.7%, respectively) over their best results in terms of overall performance. Additional comparative empirical experiments on other two popular open source repositories confirm the findings and demonstrate the benefits of our approach.

关键词： Feature extraction Text mining Training Software Predictive models Bayes methods

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Time-bounded localization algorithm based on distributed Multidimensional Scaling for Wireless Sensor Networks

Time-bounded localization algorithm based on distributed Mul...

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IEEE International Conference on Communications (ICC)

作者： Ferdews Tlili Abderrezak Rachedi Abderrahim Benslimane ENSI University of Manouba HANA Research Group Tunis Tunisia University of Paris-Est (UPEM) Computer Science lab. (LIGM UMR8049) Marne-Ia-Vallee France French University of Egypt Informatics Research Center (CRI) Cairo Egypt

Many applications of Wireless Sensor Networks (WSN) require to achieve the positions of the sensor nodes within a given time bound. In this paper we study the relative and physical localizability of WSN in a given time bound. We propose a new distributed and time bounded localization algorithm based on Multidimensional Scaling (MDS) method in WSN called D-MDS localization time algorithm. We compare the proposed algorithm to the existing algorithm based on the well-known Trilateration method. The simulation results show that the proposed algorithm outperforms the existing approach based on Trilateration method in terms of the number of localized nodes in the network and the number of anchors required to physically localize the sensors. The D-MDS localization time algorithm localizes a large number of nodes for a low node degree in a time bound. Moreover it is able to physically localize the network with a low number of anchors compared with the algorithm based on Trilateration method.

关键词： Wireless sensor networks Time complexity Clustering algorithms Ad hoc networks Simulation Educational institutions Electronic mail

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ASIS&T annual meeting pre-conference activities: SIG/USE research symposium context in information behavior research

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Bulletin of the Association for Information science and Technology 2015年第3期41卷

作者： Lu Xiao Assistant Professor Kyung-Sun Kim Professor Rong Tang Associate Professor Lisa Given Professor Denise E. Agosto Associate Professor Gary Burnett Professor Amanda Waugh Ph.D. Student Faculty of Information & Media Studies Department of Computer Science at the University of Western Ontario School of Library and Information Studies University of Wisconsin Madison Simmons and director Simmons GSLIS Usability Lab. School of Information Studies Charles Sturt University College of Computing and Informatics at Drexel University College of Communication and Information at Florida State University College of Information Studies University of Maryland College Park

EDITOR'S SUMMARY ASIS&T's Special Interest Group/Information Needs, Seeking and Use (SIG/USE) met during the 2014 Annual Meeting for the group's 14th Annual Research Symposium, focusing on Context in Information Behavior Research . Keynote speaker J. David Johnson set the tone as he encouraged research into the context of information activities outside the usual settings and using varied theoretical perspectives and tools. Attendees also heard 14 lightning talks exploring conceptual and methodological issues. Speakers considered time and emotion as dominant contextual influences in information behavior, the role of information overload and ways diverse contexts affect seeking and providing information. Discussion of research methods encouraged a mixed-method approach and analytic bracketing and illuminated how study participants create their own information context. During the world café session, tablemates discussed how information context is constructed and evolves, research gaps and availab.e methodologies. The symposium ended with presentation of awards for outstanding research, best paper and poster and for travel to pursue studies. Gary Marchionini was recognized for his outstanding contributions to information behavior research throughout his career.

关键词： information needs information seeking information use user behavior contextual information honors

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AgreementMakerLight results for OAEI 2013 8

AgreementMakerLight results for OAEI 2013

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8th International Workshop on Ontology Matching, OM 2013, Co-located with the 12th International Semantic Web Conference, ISWC 2013

作者： Faria, Daniel Pesquita, Catia Santos, Emanuel Cruz, Isabel F. Couto, Francisco M. LASIGE Dept. Informatics Faculty of Sciences Portugal ADVIS Lab. Dept. Computer Science University of Illinois Chicago United States

AgreementMakerLight (AML) is an automated ontology matching framework based on element-level matching and the use of external resources as background knowledge. This paper describes the configuration of AML for the OAEI 2013 competition and discusses its results. Being a newly developed and still incomplete system, our focus in this year's OAEI were the anatomy and large biomedical ontologies tracks, wherein background knowledge plays a critical role. Nevertheless, AML was fairly successful in other tracks as well, showing that in many ontology matching tasks, a lightweight approach based solely on element-level matching can compete with more complex approaches.

关键词： Ontology

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CoDS: A representative sampling method for relational databases

CoDS: A representative sampling method for relational databa...

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24th International Conference on Database and Expert Systems Applications, DEXA 2013

作者： Buda, Teodora Sandra Cerqueus, Thomas Murphy, John Kristiansen, Morten Performance Engineering Lab. School of Computer Science and Informatics University College Dublin Ireland IBM Collaboration Solutions IBM Software Group Dublin Ireland

ISBN: (纸本)9783642402845

Database sampling has become a popular approach to handle large amounts of data in a wide range of application areas such as data mining or approximate query evaluation. Using database samples is a potential solution when using the entire database is not cost-effective, and a balance between the accuracy of the results and the computational cost of the process applied on the large data set is preferred. Existing sampling approaches are either limited to specific application areas, to single table databases, or to random sampling. In this paper, we propose CoDS: a novel sampling approach targeting relational databases that ensures that the sample database follows the same distribution for specific fields as the original database. In particular it aims to maintain the distribution between tables. We evaluate the performance of our algorithm by measuring the representativeness of the sample with respect to the original database. We compare our approach with two existing solutions, and we show that our method performs faster and produces better results in terms of representativeness. © 2013 Springer-Verlag.

关键词： Cost effectiveness

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