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2008 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, DySPAN 2008

作者： Kim, Hyoil Shin, Kang G. Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2121 United States

ISBN: (纸本)9781424420179

We address the problem of rapidly discovering spectrum opportunities for seamless service provisioning for secondary users (SUs) in cognitive radio networks (CRNs). Specifically, we propose an efficient sensing-sequence that incurs a small opportunity-discovery delay by considering (1) the probability that a spectrum band (or a channel) may be available at the time of sensing, (2) the duration of sensing on a channel, and (3) the channel capacity. We derive the optimal sensing-sequence for channels with homogeneous capacities, and a suboptimal sequence for channels with heterogeneous capacities for which the problem of finding the optimal sensing-sequence is shown to be NP-hard. To support the proposed sensing-sequence, we also propose a channel-management strategy that optimally selects and updates the list of backup channels. A hybrid of maximum likelihood (ML) and Bayesian inference is also introduced for flexible estimation of ON/OFF channel-usage patterns and prediction of channel availability when sensing produces infrequent samples. The proposed schemes are evaluated via in-depth simulation. For the scenarios we considered, the proposed suboptimal sequence is shown to achieve close-to-optimal performance, reducing the opportunity-discovery delay by up to 47% over an existing probability-based sequence. The hybrid estimation strategy is also shown to outperform the ML-only strategy by reducing the overall opportunity-discovery delay by up to 34%. ©2008 IEEE.

关键词： Bayesian networks

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ARCMA: Attack-resilient collaborative message authentication in Wireless Sensor Networks 08

ARCMA: Attack-resilient collaborative message authentication...

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4th International Conference on Security and Privacy in Communication Networks, SecureComm'08

作者： Cho, Min-Gyu Shin, Kang G. Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2121 United States

ISBN: (纸本)9781605582412

Data Centric Storage (DCS) is a well-known data storage and query processing mechanism for Wireless Sensor Networks (WSNs), storing sensed data or their metadata at pre-specified locations. Queries issued by mobile users are sent to, and processed at, such storage nodes. However, securing DCS is very difficult because WSNs usually operate in an unattended environment and hence are subject to node-capture attacks. Even after capturing a single node, an attacker may be able to subvert the entire system by using the keying material extracted from the captured node. To remedy/alleviate the above problem, we propose Attack-Resilient Collaborative Message Authentication (ARCMA), in which sensor nodes collaboratively authenticate messages to be sent to, or received from, remote nodes. In ARCMA, each node belongs to one of k groups, and constructs an Authentication Tree (AT) which is formed with k nodes, each from a distinct group. Each node collaborates with the other nodes in its AT to authenticate messages. We propose two heuristics, called MIN and OPT, to construct ATs. Our analysis shows that the security of ARCMA does not degrade until the attacker capture k or more nodes. We also evaluate the overhead of constructing ATs and the cost of authenticating messages using ATs. Copyright 2008 ACM.

关键词： Authentication

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Statistical learning approaches for discriminant features selection

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Journal of the Brazilian computer Society 2008年第2期14卷 7-22页

作者： Giraldi, Gilson A. Rodrigues, Paulo S. Kitani, Edson C. Sato, João R. Thomaz, Carlos E. Department of Computer Science National Laboratory for Scientific Computing LNCC Petrópolis Rio de Janeiro Brazil Department of Electrical Engineering University of São Paulo USP São Paulo São Paulo Brazil University of São Paulo USP São Paulo São Paulo Brazil Department of Computer Science Centro Universitário da FEI FEI São Bernardo do Campo São Paulo Brazil Department of Electrical Engineering Centro Universitário da FEI FEI São Bernardo do Campo São Paulo Brazil

Supervised statistical learning covers important models like Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA). In this paper we describe the idea of using the discriminant weights given by SVM and LDA separating hyperplanes to select the most discriminant features to separate sample groups. Our method, called here as Discriminant Feature Analysis (DFA), is not restricted to any particular probability density function and the number of meaningful discriminant features is not limited to the number of groups. To evaluate the discriminant features selected, two case studies have been investigated using face images and breast lesion data sets. In both case studies, our experimental results show that the DFA approach provides an intuitive interpretation of the differences between the groups, highlighting and reconstructing the most important statistical changes between the sample groups analyzed.

关键词： Support vector machines

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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Frequency offset estimation for multi-static radar system

Frequency offset estimation for multi-static radar system

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Eunjung Yang Joohwan Chun Scientific Computing Laboratory Department of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology Daejeon South Korea

Bi-static and multi-static radar requires synchronization between transmitter(s) and receiver(s) due to their separated locations. Especially, for the target Doppler estimation, the carrier frequency offset occurred by the discord between the transmit and the receive ends should be estimated before the processing. In this paper, the system model for multi-static radar is provided as a similar form of multi-input multi-output (MIMO) communication system. However, unlike the MIMO case the frequency offset for each receiver is not identical to each other which makes the modeling and problem complicated. Based on the system model, the joint maximum likelihood (ML) solution and the suboptimal estimation is presented for frequency offset compensation. In this approximated approach, each receiver frequency offset is decoupled to others and the computational complexity becomes extremely low while it provides reasonable error performance for small frequency offsets and high signal to noise ratio (SNR).

关键词： Frequency estimation Maximum likelihood estimation Frequency synchronization MIMO Transmitters Delay effects Doppler radar Signal to noise ratio Oscillators Global Positioning System

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Lattice Reduction Aided Precoding Combined with SDM for Clusters of Correlated Users

Lattice Reduction Aided Precoding Combined with SDM for Clus...

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IEEE Conference on Wireless Communications and Networking

作者： Jaehyun Park Joohwan Chun Scientific Computing Laboratory Department of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology Daejeon South Korea

We present a lattice reduction (LR) aided preceding scheme combined with spatial division multiplexing (SDM) for clusters of correlated multiple users. Previously, the LR aided precoding schemes are deeply studied to transmit different symbols, simultaneously, to multiple users since it shows superior performance to linear precoding schemes like zero-forcing (ZF) algorithm. However, it has high complexity compared with linear precoding schemes. To resolve it, we exploit the spatial separability between clusters. That is, we apply the LR aided scheme for highly correlated users in a same cluster and to suppress the interferences from other clusters, we apply the ZF algorithm. Furthermore, we also propose a new SDM scheme to maximize the transmit signal to interference and noise ratio, which is formulated by generalized eigenvalue problem. We verify the performance of the proposed schemes by Monte-Carlo simulations and compare the computation complexities of them with the conventional LR aided precoding scheme.

关键词： Lattices MIMO Clustering algorithms Signal to noise ratio Transmitting antennas Linear discriminant analysis Interference Eigenvalues and eigenfunctions Receiving antennas Communications Society

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Fast Discovery of Spectrum Opportunities in Cognitive Radio Networks

Fast Discovery of Spectrum Opportunities in Cognitive Radio ...

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IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, DySPAN

作者： Hyoil Kim Kang G. Shin Real-Time Computing Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

关键词： Sensors Channel capacity Delay Algorithm design and analysis Availability Channel estimation Maximum likelihood estimation

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Flexible Electronics: Ultrathin Silicon Circuits With Strain‐Isolation Layers and Mesh Layouts for High‐Performance Electronics on Fabric, Vinyl, Leather, and Paper (Adv. Mater. 36/2009)

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Advanced Materials 2009年第36期21卷

作者： Dae‐Hyeong Kim Yun‐Soung Kim Jian Wu Zhuangjian Liu Jizhou Song Hoon‐Sik Kim Yonggang Y. Huang Keh‐Chih Hwang John A. Rogers Department of Materials Science and Engineering Beckman Institute for Advanced Science and Technology and Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana Illinois 61801 (USA) Department of Civil and Environmental Engineering Northwestern University Evanston IL 60208 (USA) Department of Mechanical Engineering Northwestern University Evanston IL 60208 (USA) Institute of High Performance Computing 1 Fusionopolis Way #16‐16 Connexis 138632 Singapore (Singapore) Department of Mechanical and Aerospace Engineering University of Miami Coral Gables FL 33146 (USA) FML Departments of Engineering Mechanics Tsinghua University Beijing 100084 (P. R. China) Department of Chemistry Beckman Institute for Advanced Science and Technology and Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana Illinois 61801 (USA) Department of Mechanical Science and Engineering Beckman Institute for Advanced Science and Technology and Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana Illinois 61801 (USA) Department of Electrical and Computer Engineering Beckman Institute for Advanced Science and Technology and Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana Illinois 61801 (USA)

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Platform presentations

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Surgical and radiologic anatomy : SRA 2009年第1期31 Suppl 1卷 49-93页

作者： Jaime Pereda Gen Niimi Jagat Mohini Kaul Sabita Mishra Babita Pangtey Daniele Peri Vincenza Cannella Giovanni Peri A Valentino Francesco Li Volsi Rosaria Lo Verde E Russo A Sciuto Annalisa Sunseri Giuseppe Modica Gianpiero Gravante Seok Ling Ong Matthew Metcalfe David Lloyd Ashley Dennison Veronica Macchi Andrea Porzionato Anna Parenti Raffaele De Caro Kawthar I F Al-Harmni Zohair I F Rahemo Hussain I A Al-Khan Vedat Bakan Gulen Demirpolat Mahmut Bozkurt Yakup Gumusalan Niyazi Acer Mehmet Demir Hulusi Taskoparan Akcan Akkaya Birdal Yildirim Mehmet Camurdanoglu Gul Guven Hilmi Ozden Sahin Kabay Cengiz Ustuner Dilek Burukoglu Derya Ustuner Irfan Degirmenci Fahrettin Akyuz Neslihan Tekin Fulya Kucuk Firdevs Gurer M Cengiz Ustuner Davut Ozbag Mesut Ozkaya Harun Ciralik Fatma Inanc Tolun Fatih Yuzbasioglu Seda Arslan Ghazaleh Moshkdanian Fatemeh Pouya Amirmahdi Nematollahi-Mahani Seyed Noureddin Nematollahi-Mahani Ralph Ger Jeremy Nikfarjam Kathy Dooley Shuwei Liu Zhenping Li Xiangtao Lin Haiwei Meng Cheng Liu Lei Feng Min Suk Chung Dong Sun Shin Eric Havet Anne-Claire Dujardin Fabrice Duparc Pierre Freger Anitha Oommen Christoph Stosch Jürgen Koebke Stefan Herzig Adam Jqbal Paul Gazzani Tim Rattay Birgit Fruhstorfer Anil Vohrah Richard M Wellings Stephen Brydges Gregory R Smith Jamie Roebuck Peter H Abrahams Vaclav Baca Michal Otcenasek Filip Svatos Tereza Smrzova Robert Grill David Kachlik Jan Skubal Valer Dzupa Alena Doubkova Ivo Klepacek Josef Stingl Muddathir Ali Yahya Bedir Günther Weber Karim Malek Amos Patrick Brent Rochambeau Phil Knickelbein Da-Yae Choi Mi-Sun Hur Kwan-Hyun Youn Kyung-Seok Hu Hee-Jin Kim Fadullah Aksoy Yavuz Selim Yildirim Orhan Ozturan Hurtan Acar Hasan Demirhan Bayram Veyseller Jean Michel Prades Andrei Timoshenko Alexander Asanau Marie Gavid Christian Martin Benoit Ayestaray Isabelle Auquit-Auckbur Pierre-Yves Millez Burcu Ercakmak Alp Bayramoglu Hakan Ozsoy Deniz Demiryurek Eray Tuccar Keiichi Akita Kumiko Yamaguchi Atsuo Kato Tomoyuki Mochizuki Julien Beldame Jean-Philippe Mure Benjamin School of Medicine Universidad de Santiago de Chile Santiago Chile. jaime.pereda@usach.cl. Laboratory of Electron Microscopy Fujita Health University Toyoake Aichi Japan. Department of Anatomy Maulana Azad Medical College New Delhi India. Department of Computer Engineering University of Palermo Palermo Italy. Department of Experimental Medicine University of Palermo Palermo Italy. Department of Surgery and Oncology University of Palermo Palermo Italy. Department of Hepatobiliary and Pancreatic Surgery University Hospitals of Leicester Leicester UK. Department of Human Anatomy and Physiology Institute of Anatomy University of Padova Padova Italy. Department of Medical Diagnostic Sciences and Special Therapies Section of Pathology University of Padova Padova Italy. Department of Biology College of Science University of Mosul Mosul Iraq. Department of Pediatric Surgery Kahramanmaras Sutcu Imam University Faculty of Medicine Kahramanmaras Turkey. Department of Radiology Kahramanmaras Sutcu Imam University Faculty of Medicine Kahramanmaras Turkey. Department of Radiology Erzurum Numune State Hospital Erzurum Turkey. Department of Anatomy Kahramanmaras Sutcu Imam University Faculty of Medicine Kahramanmaras Turkey. Department of Anatomy School of Health Sciences Mugla University Mugla Turkey. Vocational School of Higher Education For Health Services Kilis 7 Aralik University Gaziantep Turkey. Department of Urology Mugla Governmental Hospital Mugla Turkey. Department of Anesthesiology Mugla Governmental Hospital Mugla Turkey. Department of Emergency Services Mugla Governmental Hospital Mugla Turkey. Department of Radiology Mugla Governmental Hospital Mugla Turkey. Department of Anatomy Eskisehir Osmangazi University Faculty of Medicine Eskisehir Turkey. Department of Anatomy Eskisehir Osmangazi University Faculty of Medicine Eskisehir Turkey. Department of Urology Dumlupinar University Faculty of Medicine Kutahya Turkey. Department of Medical Bio

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Improving data availability for a cluster file system through replication

Improving data availability for a cluster file system throug...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Jin Xiong Jianyu Li Rongfeng Tang Yiming Hu Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences China Department of Electrical & Computer Engineering and Computer Science University of Cincinnati USA

Data availability is a challenging issue for large- scale cluster file systems built upon thousands of individual storage devices. Replication is a well-known solution used to improve data availability. However, how to efficiently guarantee replicas consistency under concurrent conflict mutations remains a challenge. Moreover, how to quickly recover replica consistency from a storage server crash or storage device failure is also a tough problem. In this paper, we present a replication-based data availability mechanism designed for a large-scale cluster file system prototype named LionFS. Unlike other replicated storage systems that serialize replica updates, LionFS introduces a relaxed consistency model to enable concurrent updating all replicas for a mutation operation, greatly reducing the latency of operations. LionFS ensures replica consistency if applications use file locks to synchronize the concurrent conflict mutations. Another novelty of this mechanism is its light-weight log, which only records failed mutations and imposes no overhead on failure-free execution and low overhead when some storage devices are unavailable. Furthermore, recovery of replica consistency needs not stop the file system services and running applications. Performance evaluation shows that our solution achieves 50-70% higher write performance than serial replica updates. The logging overhead is shown to be low, and the recovery time is proportional to the amount of data written during the failure.

关键词： File systems Genetic mutations computer crashes Large-scale systems Availability Peer to peer computing Delay Bandwidth Laboratories computer architecture

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