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2014 International Conference on Multisensor Fusion and Information Integration for Intelligent systems, MFI 2014

作者： Ma, Hengtai Yi, Xiaowei Wu, Xiaohui Gu, Dingfeng Pan, Hui Zheng, Changwen Sci. and Tech. on Integrated Information System Lab Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Information Security Institute of Info. Engineering Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479967322

Information hiding based on error correcting code is one of the difficulties in information hiding research. Current information hiding algorithms cannot confirm the upper bound of covert channel capacity when channels are interfered. In this paper, a capacity self-adaption information hiding algorithm based on RS code is proposed to solve this problem. Firstly, Channel covert communication model is designed to describe the realization of information hiding algorithms based on the m-sequence. Secondly, the upper bound of embedding capacity of secret information based on block code and RS code is separately analyzed in theory. Thirdly, simulation verification is implemented under the supposed channel environment. Experimental results demonstrated that experimental values are consistent with the theoretical values, and in terms of the embedding rate, the performance of the RS code is better than the performance of recurrent code and block code. © 2014 IEEE.

关键词： Channel capacity

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

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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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Inter-data-center large-scale database replication optimization - A workload driven partitioning approach

Inter-data-center large-scale database replication optimizat...

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25th International Conference on Database and Expert systems Applications, DEXA 2014

作者： Min, Hong Gao, Zhen Li, Xiao Huang, Jie Jin, Yi Bourbonnais, Serge Zheng, Miao Fuh, Gene IBM T.J. Watson Research Center Yorktown Heights NY United States IBM Silicon Valley Lab San Jose CA United States School of Software Engineering Tongji University Shanghai China Pivotal Inc. Beijing China IBM System and Technology Group United States

ISBN: (纸本)9783319100845

Inter-data-center asynchronous middleware replication between active-active databases has become essential for achieving continuous business availability. Near real-time replication latency is expected despite intermittent peaks in transaction volumes. Database tables are divided for replication across multiple parallel replication consistency groups;each having a maximum throughput capacity, but doing so can break transaction integrity. It is often not known which tables can be updated by a common transaction. Independent replication also requires balancing resource utilization and latency objectives. Our work provides a method to optimize replication latencies, while minimizing transaction splits among a minimum of parallel replication consistency groups. We present a two-staged approach: a log-based workload discovery and analysis and a history-based database partitioning. The experimental results from a real banking batch workload and a benchmark OLTP workload demonstrate the effectiveness of our solution even for partitioning 1000s of database tables for very large workloads. © 2014 Springer International Publishing Switzerland.

关键词： Middleware

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REED: A Reliable Energy-Efficient RAID

REED: A Reliable Energy-Efficient RAID

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International Conference on Parallel Processing (ICPP)

作者： Shu Yin Xuewu Li Kenli Li Jianzhong Huang Xiaojun Ruan Xiaomin Zhu Wei Cao Xiao Qin School of Information Science & Engineering National Supercomputing Center in Changsha Changsha China Dept. of Computer Science Huazhong Univ. of Sci. and Tech. Wuhan China Dept. of Computer Science West Chester Univ. of Pennsylvania PA Sci. & Tech. on Information System Eng. Lab National University of Defense Technology Changsha China Hubei Meteorological Information. & Technology Support Center Wuhan China Dept. of Compter Sci. & Software Eng. Auburn University AL

ISBN: (纸本)9781467375887

Recent studies indicate that the energy cost and carbon footprint of data centers have become exorbitant. It is a demanding and challenging task to reduce energy consumption in large-scale storage systems in modern data centers. Most energy conservation techniques inevitably have adverse impacts on parallel disk systems. To address the reliability issues of energy-efficient parallel disks, we propose a reliable energy-efficient RAID system called REED, which aims at improving both energy efficiency and reliability of RAID systems by seamlessly integrating HDDs and SSDs. At the heart of REED is a high-performance cache mechanism powered by SSDs, which are serving popular data. Under light workload conditions, REED spins down HDDs into the low-power mode, thereby offering energy conservation. Importantly, during an I/O access turbulence (i.e., I/O load is dynamically and frequently changing), REED is conducive to reducing the number of disk power-state transitions by keeping HDDs in the low-power mode while serving requests with SSDs. We build a model to quantitatively show that REED is capable of improving the reliability of energy-efficient RAIDs. We implement the REED prototype in a real-world RAID-0 system. Our experimental results demonstrate that REED improves the energy-efficiency of conventional RAID-0 by up to 73% while maintaining good reliability.

关键词： Reliability Solids Electronic mail Energy consumption Energy conservation Energy storage Power demand

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Positional translation language model for ad-hoc information retrieval

Positional translation language model for ad-hoc information...

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18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2014

作者： Tu, Xinhui Luo, Jing Li, Bo He, Tingting Gu, Jinguang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Department of Computer Science Central China Normal University Wuhan China State Key Lab. of Software Engineering Wuhan University Wuhan China

ISBN: (纸本)9783319066042

Most existing language modeling approaches are based on the term independence hypothesis. To go beyond this assumption, two main directions were investigated. The first one considers the use of the proximity features that capture the degree to which search terms appear close to each other in a document. Another one considers the use of semantic relationships between words. Previous studies have proven that these two types of information, including term proximity features and semantic relationships between words, are both useful to improve retrieval performance. Intuitionally, we can use them in combination to further improve retrieval performance. Based on this idea, this paper propose a positional translation language model to explicitly incorporate both of these two types of information under language modeling framework in a unified way. In the first step, we present a proximity-based method to estimate word-word translation probabilities. Then, we define a translation document model for each position of a document and use these document models to score the document. Experimental results on standard TREC collections show that the proposed model achieves significant improvements over the state-of-the-art models, including positional language model, and translation language models. © 2014 Springer International Publishing.

关键词： Information retrieval

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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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Stream-based event prediction using Bayesian and bloom filters 13

Stream-based event prediction using Bayesian and bloom filte...

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2013 4th ACM/SPEC International Conference on Performance engineering, ICPE 2013

作者： Wang, Miao Holub, Viliam Murphy, John O'Sullivan, Patrick Performance Engineering Lab. School of Computer Science and Informatics University College Dublin Dublin Ireland Collaboration Solution System IBM Software Group Dublin Ireland

ISBN: (纸本)9781450316361

Nowadays, enterprise software systems store a large amount of operational information in logs. Manually analysing these data can be time-consuming and error-prone. Although a static knowledge database eases the task to capture recurring problems, maintaining such a knowledge repository requires periodic knowledge updates by domain experts. Moreover, as the repository grows, the problem of memory efficiency will also arise. Our goal is to enable administrators to efficiently capture interesting data in a high volume stream of events in real-time. We are proposing a statistical approach for software applications to be automatically trained with a smaller dataset to efficiently predict interesting data under such conditions. The proposed solution maintains a stable memory usage by migrating keywords from a dynamic data structure to fixed sized data structures (Bloom Filter). In particular, the solution has achieved better prediction results by enhancing the Bayesian theory with belief modifiers. © 2013 ACM.

关键词： Forecasting

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Simulation error characteristics of grey model GM(1,1) under translation transformation

Simulation error characteristics of grey model GM(1,1) under...

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2013 5th International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2013

作者： Wang, Yong Song, Qinbao Zeng, Bo Liu, Jin Department of Computer Science and Technology Ocean University of China Qingdao China State Key Lab. of Software Engineering Wuhan University Wuhan China Department of Computer Science and Technology Xi'An Jiaotong University Xi'an China Department of Industry Management and System Engineering University of South Florida Tampa United States State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China

ISBN: (纸本)9780769551555

To reveal the change law of the simulation error of grey model GM(1,1) with translation transformation applying on the original sequence, in this paper, the experiments based on 55 real world data sequences have been conducted to study how the translation transformation influences the grey models' error characteristics. The results show that a larger translation transformation can make the total error between the model sequence and the original sequence toward zero, and the model precision remains independent. The conclusion implies that we can use translation transformation to change the original sequence data level to simplify the model building without changing the model precision. © 2013 IEEE.

关键词： Errors

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Tumor gene expressive data classification based on locally linear representation Fisher criterion

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9th International Conference on Intelligent Computing, ICIC 2013

作者： Li, Bo Tian, Bei-Bei Liu, Jin School of Computer Science and Technology Wuhan University of Science and Technology 430081 Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China State Key Lab. of Software Engineering Wuhan China

ISBN: (纸本)9783642394812

In this paper, a discriminant manifold learning method based on Locally Linear Embedding (LLE), which is named Locally Linear Representation Fisher Criterion (LLRFC), is proposed for the classification of tumor gene expressive data. In the proposed LLRFC, an inter-class graph and intra-class graph is constructed based on the class information of tumor gene expressive data, where the weights between nodes in both graph are optimized using locally linear representation trick. Moreover, a Fisher criterion is modeled to maximize the inter-class scatter and minimize the intra-class scatter simultaneously. Experiments on some benchmark tumor gene expressive data validate its efficiency. © 2013 Springer-Verlag.

关键词： Genes

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Dynamics of a congestion control model in a wireless access network

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Nonlinear Analysis: Real World Applications 2013年第1期14卷 671-683页

作者： Dong, Tao Liao, Xiaofeng Huang, Tingwen State Key Lab. of Power Transmission Equipment and System Security College of Computer Science Chongqing University Chongqing 400044 China College of Software and Engineering Chongqing University of Posts and Telecommunications Chongqing 400065 China Texas AandM University at Qatar Doha P.O. Box 23874 Qatar

In this paper, a congestion control algorithm with heterogeneous delays in a wireless access network is considered. We regard the communication time delay as a bifurcating parameter to study the dynamical behaviors, i.e., local asymptotical stability, Hopf bifurcation and resonant codimension-two bifurcation. By analyzing the associated characteristic equation, the Hopf bifurcation occurs when the delay passes through a sequence of critical value. Furthermore, the direction and stability of the bifurcating periodic solutions are derived by applying the normal form theory and the center manifold theorem. In the meantime, the resonant codimension-two bifurcation is also found in this model. Some numerical examples are finally performed to verify the theoretical results. © 2012 Published by Elsevier Ltd.

关键词： Codimension-two bifurcation Congestion control Hopf bifurcation Stability Wireless access network

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