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

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 rating scale and FANP to determine the important weight of learning competency for students’ assessment

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AIP Conference Proceedings 2016年第1期1755卷

作者： Sri Andayani Sri Hartati Retantyo Wardoyo Djemari Mardapi 1Doctoral program of Computer Science Universitas Gadjah Mada Yogyakarta Indonesia 2Department of Computer Science and Electrical Universitas Gadjah Mada Yogyakarta Indonesia 3Study Program of Educational Research and Evaluation Graduate School Universitas Negeri Yogyakarta Indonesia

Determining the important weight of learning competency is an important problem for students’ assessment in credentialing and certification decision-making. Learning competencies should have importance weight that definitely affect the final decision, and can represent strengths and weaknesses of student achievement of certain competencies. The weight of learning competency is determined based on its difficulty level, which is identified by the depth, scope and complexity of material involved in it. The dependency among learning competencies must also be considered in determining the weight. Therefore, this study aims to develop a weighting method based on combining rating scale and fuzzy analytic network process (FANP) to determine the weight of learning competency. Using the proposed method, the weight of learning competency is obtained and then can be used in calculating the final score for students’ assessment.

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Scratchpad memory management using data-prefetching

Scratchpad memory management using data-prefetching

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Conferencia Latinoamericana En Informatica (CLEI)

作者： Ivan Saraiva Silva Hildebrando Segundo Department of Computing Federal University Piauí Teresina Brazil Computer Science Graduate Program Federal University of Piauí Teresina Brazil

Nowadays, multicore processors including dozens of cores are a reality and the challenge of designing microprocessors with hundreds of cores does not appear far from being achieved. However, some questions remain open, despite the proposals found in the literature. Memory latency, data locality and programmability are some of the more critical ones. As the number of cores in multi-core processor architectures increases, so does the need of more efficient memory hierarchy and resource management scheme. The design of efficient memory hierarchy and memory management policy becomes a very important research subject in multi core architecture field. The usage of resource allocation strategies becomes increasingly necessary. This paper presents the design and implementation of a multi-core node with support to memory configuration and hardware-based scratchpad memory management. The node consists of 9 cores (8 slave cores and a master core) and a configurable local memory. The proposed architecture was implemented with VHDL and prototyped with FPGA development boards. Experimental results show that the proposed hardware-based scratchpad memory management unit can achieve 99,0 of hits in data address prediction and 97,1% of hit when searching data-frames in the local memory.

关键词： Multicore processing Resource management Memory management Hardware program processors Microprocessors

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Dimensioning Microwave Wireless Networks

Dimensioning Microwave Wireless Networks

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IEEE International Conference on Communications

作者： Alvinice Kodjo Brigitte Jaumard Napoleao Nepomuceno Mejdi Kaddour David Coudert Inria France & Univ. Nice Sophia Antipolis Department of Computer Science and Software Engineering Concordia University Montreal Graduate Program in Applied Informatics University of Fortaleza Department of Computer Science University of Oran

ISBN: (纸本)9781467364300

We aim at dimensioning fixed broadband microwave wireless networks under unreliable channel conditions. As the transport capacity of microwave links is prone to variations due to, e.g., weather conditions, such a dimensioning requires special attention. It can be formulated as the determination of the minimum cost bandwidth assignment of the links in the network for which traffic requirements can be met with high probability, while taking into account that transport link capacities vary depending on channel conditions. The proposed optimization model represents a major step forward since we consider dynamic routing. Experimental results show that the resulting solutions can save up to 45% of the bandwidth cost compared to the case where a bandwidth over-provisioning policy is uniformly applied to all links in the network planning. Comparisons with previous work also show that we can solve much larger instances in significantly shorter computing times, with a comparable level of reliability.

关键词： Bandwidth Modulation Pricing Reliability Microwave communication Routing

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A Kinect-Aided Method to Estimate the Fundus Camera Extrinsic Parameters for Three-Dimensional Reconstruction of Retinal Blood Vessels

A Kinect-Aided Method to Estimate the Fundus Camera Extrinsi...

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Future Technologies Conference

作者： E. Hernandez-Sanchez M. Elena Martinez-Perez A. Gastelum-Strozzi Engineering Graduate Program Universidad Nacional Autónoma de México. Ciudad de México Computer Science Department IIMAS Universidad Nacional Autónoma de México. Apartado Postal 20-126 Ciudad de México C.P. 01000 CCADET-HGM. Universidad Nacional Autónoma de México. Ciudad de México

ISBN: (纸本)9781509041725

This paper deals with the estimation of intrinsic and extrinsic parameters in a fundus camera system. These parameters are fundamental to retrieve three-dimensional reconstruction of eye's structure, in our case, retinal blood vessels. In this paper we used the Zhang's algorithm to estimate the intrinsic parameters of the optical system. Besides, an alternative method to estimate the extrinsic parameters is proposed based on the kinect one sensor. These modifications provide an easy way to characterise the whole fundus camera system. Experimental validation was carried out to verify the accuracy of the proposed method. A cylindrical known object was reconstructed having and average error of 3.96%. A real eye's structure was also reconstructed from a fundus image pair.

关键词： Fundus images 3D reconstruction Camera calibration Retinal blood vessels

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TODIM Based Method to Process Heterogeneous Information

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Procedia computer science 2015年 55卷 318-327页

作者： Rodolfo Lourenzutti Renato A. Krohling Graduate Program in Computer Science PPGI UFES Federal University of Espirito Santo Av. Fernando Ferrari 514 Vitoria CEP 29075-910 Brazil Department of Production Engineering & Graduate Program in Computer Science PPGI UFES - Federal University of Espirito Santo Av. Fernando Ferrari 514 Vitoria CEP 29075-910 Esprito Santo ES Brazil

Multicriteria decision making (MCDM) problems are getting increasingly difficult over the years. Nowadays, it is very common to have a problem where heterogeneous types of information must be processed before making a decision. From a wide variety of MCDM methods, just a few of them are able to process mixed types of information at the same time and most of these methods relies on transformations that may cause problems and/or be unjustified. In this paper we bring a modular interpretation of the TODIM (an acronym in Portuguese for Interative Multi-criteria Decision Making) method to handle heterogeneous data types simultaneously, in a systematic way. We argue that the method have a modular capacity which is the novelty of our approach. Using this interpretation, the whole problem with heterogeneous information is broken into modules and processed in a straightforward way. Two examples are used to illustrate the approach showing the effectiveness and practicability.

关键词： Multi-criteria decision making (MCDM) TODIM heterogeneous information interval numbers fuzzy numbers intuitionistic fuzzy numbers.

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A Data Mining Analysis of Asthma Risk Factors

A Data Mining Analysis of Asthma Risk Factors

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International Conference on Applied Computing and Information Technology/International Conference on Computational science and Intelligence (ACIT-CSI)

作者： Alma Pochini Ben M. Williams Hasanboy M. Isomitdinov Gongzhu Hu Departments of Finance Law & Departments of Mathematics Data Mining Graduate Certificate Program Department of Economics Department of Computer Science Central Michigan University Michigan USA

Asthma is a chronic inflammatory disease of the airways. Although causes of asthma may directly related to environment factors such as dust mites, pollens, cold air, etc.,we would like to find out if demographic, social and behavior factors also play a role. In this paper, we present a study of the behavioral rick factors in relation to people getting asthma. This study applies data mining techniques to the 2013 Behavioral Risk Factor Surveillance System (BRFSS) dataset of over 490,000 observations with 336 variables. The results reveal some relationships between some of these variables and asthma that may help asthma prevention.

关键词： Logistics Diseases Data mining Neural networks Regression tree analysis

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Incorporating OMA Lightweight M2M protocol in IoT/M2M standard architecture

Incorporating OMA Lightweight M2M protocol in IoT/M2M standa...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Christian Antonia Lusiarta Putera Fuchun Joseph Lin EECS International Graduate Program National Chiao Tung University Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781509003679

IoT/M2M aims to integrate a large number of heterogeneous devices which are constantly required to be discovered and reconfigured in order to bring them up to date or to recover from their failures. A device management protocol enables the abstraction of an IoT/M2M device as a managed object to ease the management of the device. The M2M standards, such as ETSI and OneM2M, have adopted the use of OMA Lightweight M2M Device Management Protocol to manage and configure the IoT/M2M devices from the IoT/M2M platform. However, how to incorporate and do resource mapping of OMA LWM2M in the IoT/M2M standard architecture is not well addressed by those standards. In this paper, we present and analyze how to incorporate the OMA LWM2M in the IoT/M2M standard architecture. Through this seamless incorporation, an IoT/M2M application is enabled to manage IoT/M2M devices from the IoT/M2M service platform at a higher level of abstraction.

关键词： Protocols Servers Standards computer architecture Performance evaluation Authorization

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Optimization Process of Glycerol Esterification Using Real Time Adaptive Control

Optimization Process of Glycerol Esterification Using Real T...

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International Conference on Advanced computer science and Information Systems

作者： Iwan Aang Soenandi Ani Suryani Taufik Djatna Irzaman Post Graduate Program of Agro-industrial Technology Bogor Agricultural University Dramaga Indonesia Lecturer Faculty of Engineering and Computer Science Krida Wacana Christian University Post Graduate Program of Agro-industrial Technology Bogor Agricultural University. Dramaga Indonesia Post Graduate Program of Agro-industrial Technology and Graduate Program of Computer Science Bogor Agricultural University. Dramaga Indonesia Department of Physics Faculty Mathematics and Natural Sciences Bogor Agricultural University. Dramaga Indonesia

ISBN: (纸本)9781509003648

The synthesis reaction used in esterification needs high energy consumption and a precise processing time to get the best yield of target. In this study, a model was formulated to optimize glycerol esterification process by minimizing the time needed for the process and maximizing the yield of Mono-glycerides. This optimization has gained importance for boosting the esterification industry and improving the production efficiency. Optimization through adaptive monitoring and control has provided significant advances in the process efficiency, a lower energy consumption and a better product quality. This paper presents the optimization with a computational algorithm in real time and adaptive control (RTAC), as compared to the conventional (traditional) methods to monitor and control of glycerol esterification processes. The identification of esterification status based on temperature and time are evaluated to strengthen the optimization. An adaptive method as feature selection to select wavelength IR sensors at specified intervals was carried out with Relief algorithm and Adaptive Pillar K-means clustering method to set the parameter control was proposed in this paper. Many combinations were evaluated from real time condition process, to achieve the best optimization results. The experimental results demonstrate that real time adaptive control can be achieved by using three clusters, which are heating up, stabilizing and finishing. In RTAC, each cluster has its own parameter to set the control point by the servo motor that was attached to magnetic stirrer-heater. By using optimization parameter for each cluster, esterification process time can be shortened by 15-20 minutes with a higher yield (7% or more), lower range stirrer rotation (300rpm-450 rpm) and a lower final temperature of 200℃ - 210℃.

关键词： Optimization Real Time Adaptive Control Glycerol Esterification

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FragGeneScan-plus for scalable high-throughput short-read open reading frame prediction

FragGeneScan-plus for scalable high-throughput short-read op...

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IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)

作者： Dongjae Kim Aria S. Hahn Shang-Ju Wu Niels W. Hanson Kishori M. Konwar Steven J. Hallam Department of Computer Science University of British Columbia Vancouver Canada Department of Microbiology University of British Columbia Vancouver Canada Graduate Program in Bioinformatics University of British Columbia Vancouver Canada

A fundamental step in the analysis of environmental sequence information is the prediction of potential genes or open reading frames (ORFs) encoding the metabolic potential of individual cells and entire microbial communities. FragGeneScan, a software designed to predict intact and incomplete ORFs on short sequencing reads combines codon usage bias, sequencing error models and start/stop codon patterns in a hidden Markov model to find the most likely path of hidden states from a given input sequence, provides a promising route for gene recovery in environmental datasets with incomplete assemblies. However, the current implementation of FragGeneScan does not scale efficiently with increasing input data size. Thus, FragGeneScan cannot be applied to contemporary environmental datasets that can exceed 100s of Gb. Here, we present FragGeneScan-Plus, an improved implementation of the FragGeneScan gene prediction model that leverages algorithmic thread synchronization and efficient in-memory data management to utilize multiple CPU cores without blocking I/O operations. FragGeneScan-Plus can process data approximately 5-times faster than FragGeneScan using a single core and approximately 50-times faster using eight hyper-threaded cores when benchmarked against simulated and real world environmental datasets.

关键词： Instruction sets Buffer storage Hidden Markov models Synchronization Predictive models Prediction algorithms Soil

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