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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012年 7145 LNCS卷 62-73页

作者： Fan, Wenshan Wang, Bin Chan, Bin Paul, Jean-Claude Sun, Jiaguang School of Software Tsinghua University China Beijing Aerospace Control Center China Department of Computer Science and Technology Tsinghua University China Key Laboratory for Information System Security Ministry of Education China Tsinghua National Laboratory for Information Science and Technology China University of Hong Kong Hong Kong INRIA France

ISBN: (纸本)9783642290497

This paper presents a new approach for constructing normal maps that capture high-frequency geometric detail from dense models of arbitrary topology and are applied to the simplified version of the same models generated by any simplification method to mimic the same level of detail. A variant of loose octree scheme is used to optimally calculate the mesh normals. A B-spline surface fitting based method is employed to solve the issue of thin plate. A memory saving Breadth-First Search (BFS) order construction is designed. Furthermore, a speedup scheme that exploits access coherence is used to accelerate filtering operation. The proposed method can synthesize good quality images of models with extremely high number of polygons while using much less memory and render at much higher frame rate. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Graphics processing unit

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Discovering aero-space information network hub node between units based on topological dimensional rollup

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Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) 2012年第SUPPL.1期40卷 280-283页

作者： Yang, Shangqian Li, Chuan Tang, Changjie Zeng, Wei College of Computer Science Sichuan University Chengdu 610065 China National Key Laboratory of Air Control Automation System Technology Chengdu 610065 China

In order to improve the efficiency of traditional algorithms in aerospace information network hub finding, the idea of inter-unit hub node mining was proposed, the algorithm for detecting inter-unit hub nodes was designed and implemented. Experiments was taked to test the time, space efficiency, scalability and effectiveness of the algorithm was analyzed.

关键词： Data mining

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On Global Consensus of Linear Multi-agent systems Subject to Input Saturation

On Global Consensus of Linear Multi-agent Systems Subject to...

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American control Conference

作者： Ziyang Meng Zhiyun Zhao Zongli Lin Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 USA

ISBN: (纸本)9781457710957

This paper studies the leader-following consensus problem for a group of agents with identical linear systems subject to control input saturation. We focus on two classes of linear systems, neutrally stable systems and double integrator systems. For neurally stable systems, we establish that global consensus can be achieved by linear local feedback laws over an undirected fixed or a switching communication topology. For double integrator systems, we establish that global consensus can be achieved by linear local feedback laws over a fixed communication topology and, with the help of a simple saturation function in the local feedback laws, global consensus can also be achieved over a switching undirected topology. Simulation results illustrate the theoretical results.

关键词： Lead Topology Switches Multiagent systems Linear systems Trajectory

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Distributed Finite-time Cooperative Tracking of Networked Lagrange systems via Local Interactions

Distributed Finite-time Cooperative Tracking of Networked La...

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American control Conference

作者： Ziyang Meng Zongli Lin Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 USA

ISBN: (纸本)9781457710957

This paper studies the finite-time cooperative tracking problem for networked Lagrange systems with a time-varying leader's generalized coordinate derivative. First, a finite-time state feedback control protocol is proposed for each follower by using only local information, under which the states of the followers are shown to converge to those of the leader in finite time. The results of the static feedback design are then extended to those of the dynamic feedback design. The finite-time cooperative tracking problem of networked Lagrange systems over a directed switching communication topology is proposed. With the help of a so-called finite-time consensus-based observer, we show that cooperative tracking of networked Lagrange systems can be achieved in finite time if the leader has directed information paths to each follower at each time instant and the control parameters satisfy certain conditions.

关键词： Lagrange Mentoring tracking problem local information. control parameter

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ESICM LIVES 2016: part one Milan, Italy. 1-5 October 2016 Abstracts

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INTENSIVE CARE MEDICINE EXPERIMENTAL 2016年第SUPPL 1期4卷 1-1页

作者： [Anonymous] Academic Medical Center University of Amsterdam Amsterdam Netherlands UMCU Utrecht Netherlands Autonomous University of Barcelona Barcelona Spain Hospital São Francisco Xavier Lisbon Portugal CHU Henri Mondor Medical ICU Créteil France Université de Paris Est-Créteil Groupe de Recherche Clinique CARMAS Créteil France Hôpital Tenon APHP Medical and Surgical ICU Paris France Université Paris Diderot Sorbonne Paris Cité UMR 1153 Paris France Interdepartmental Division of Critical Care University of Toronto Toronto Canada University Health Network University of Toronto Critical Care Medicine Toronto Canada University of Milan - Bicocca Health Sciences School of Medicine and Surgery Monza Italy St Michael’s Hospital University of Toronto Anesthesia Toronto Canada CHU d’Angers Medical ICU Angers France Interdepartmental Division of Critical Care University of Toronto Saint Michael’s Hospital and Keenan Research Centre Toronto Canada University of Birmingham Institute for Inflammation and Ageing Birmingham UK University of Sheffield Mathematics and Statistics Help Centre Sheffield UK Heart of England NHS Foundation Trust Intensive Care Medicine Birmingham UK Department of Surgery University Hospitals Birmingham NHS Trust Birmingham UK University Hospitals Birmingham NHS Trust Anaesthesia and Critical Care Medicine Birmingham UK Queen’s University of Belfast Wellcome-Wolfson Institute for Experimental Medicine Belfast UK Royal Victoria Hospital Intensive Care Medicine Belfast UK University of Warwick Warwick Clinical Trials Unit Coventry UK University of Bari ‘Aldo Moro’ Bari Italy Hospital Israelita Albert Einstein São Paulo Brazil Mayo Clinic Jacksonville USA Mahidol University Faculty of Tropical Medicine Bangkok Thailand University Medical Center Utrecht Intensive Care Utrecht Netherlands University Medical Center Utrecht Julius Center for Health Sciences and Primary Care Utrecht Netherlands Academic Medical Center University of Amste

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Interpolation of Orientation Distribution Functions (ODFs) in Q-ball Imaging

Interpolation of Orientation Distribution Functions (ODFs) i...

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Iranian Conference of Biomedical Engineering

作者： Maryam Afzali Emad Fatemizadeh Hamid Soltanian-Zadeh Department of Electrical Engineering Biomedical Signal and Image Processing Laboratory(BiSIPL) Sharif University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence(CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran & Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit Michigan USA

ISBN: (纸本)9781467331289

Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain but in the regions with crossing fibers, it fails. To resolve this problem, high angular resolution diffusion imaging (HARDI) with a large number of diffusion encoding directions is used and for reconstruction, the Q-ball method is applied. In this method, orientation distribution function (ODF) of fibers can be calculated. Mathematical models play a crucial role in the field of ODF. For instance, in registering Q-ball images for applications like group analysis or atlas construction, one needs to interpolate ODFs. To this end, principal diffusion directions (PDDs) of each ODF are needed. In this paper, PDDs are defined as vectors that connect the corresponding local maxima of ODF values. Then, ODFs are interpolated using PDDs. The proposed method is evaluated and compared with previous protocols. Experimental results show that the proposed interpolation algorithm preserves the principal direction of fiber tracts without producing any deviations in the tracts. It is shown that changes in the entropy of the interpolated ODFs are almost linear and the bloating effect (blurring of the principal directions) can be removed.

关键词： High angular resolution diffusion imaging (HARDI) Q-ball imaging Orientation distribution function (ODF) Interpolation Principal diffusion direction (PDD)

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Impaired Resting State Networks in Temporal Lobe Epilepsy: A Resting State fMRI Study

Impaired Resting State Networks in Temporal Lobe Epilepsy: A...

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Iranian Conference of Biomedical Engineering

作者： Marzie Fereidouni Hamid Soltanian-Zadeh Quan Jiang Kost V. Elisevich Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran NMR Laboratory Department of Neurology Henry Ford Hospital Detroit Michigan USA epartment of Clinical Neurosciences Spectrum Health System Grand Rapids Michigan USA

ISBN: (纸本)9781467331289

Temporal lobe epilepsy (TLE) is the most common type of human refractory epilepsy and can cause widespread impairments in brain functionality. Previous studies show functional and structural abnormalities in different regions of TLE patients' brain in comparison with normal subjects. However, limited studies have been done on connectivity abnormalities of resting state networks (RSN) in TLE patients and most of them studied default mode network (DMN) only. In this paper, nine independent spatial maps of the brain were identified by applying independent component analysis (ICA) on functional magnetic resonance images (fMRI) of the subjects. These maps were classified into four resting state networks: visual network, auditory network, default mode network, and attention network (including right and left fronto-parietal networks and core network). Functional connectivity between time courses of the nine components were computed and then compared between TLE patients and healthy subjects. Results show that there are significant between-group differences in functional connectivity among different brain networks including decrease in functional connections of visual cortex with two other networks, DMN and attention network, and decrease in functional connectivity between DMN and left fronto-parietal network. An increase in functional connectivity between DMN and core network and also between right fronto-parietal network and auditory network is observed.

关键词： Temporal lobe epilepsy Functional connectivity Resting state networks

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Hippocampal shape analysis in the Laplace Beltrami feature space for temporal lobe epilepsy diagnosis and lateralization

Hippocampal shape analysis in the Laplace Beltrami feature s...

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IEEE International Symposium on Biomedical Imaging

作者： Rosita Shishegar Ziba Gandomkar Hamid Soltaman-Zadeh Seyed Reza Moghadasi Control and Intelligent Processing Centre of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Department of Mathematics Sharif University of Technology Tehran Iran

Shape analysis plays an important role in many medical imaging studies. One of the recent shape analysis methods uses the Laplace Beltrami operator which is also used in this paper for hippocampal shape comparison. We proposed a feature vector which consists of size measures and shape descriptors based on Laplace Beltrami eigenvalues and eigenfunctions. The aforementioned feature space is utilised for automatic differentiating normal subjects from epileptic patients as well as distinguishing epileptic patients with left temporal lobe epilepsy (LTLE) from patients with right temporal lobe epilepsy (RTLE). Achieved results are diagnostic accuracy of 93% with 95% sensitivity and lateralization accuracy of 86%. The results are comparable to spherical harmonic based shape analysis results and notably improved in comparison to volumetric analysis results.

关键词： Shape Temporal lobe Epilepsy Abstracts Indexes Eigenvalues and eigenfunctions Feature extraction

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Extending CSP to detect motor imagery in a four-class BCI

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Journal of Information and Computational Science 2012年第1期9卷 143-151页

作者： Fang, Yonghui Chen, Minyou Zheng, Xufei Harrison, R.F. State Key Laboratory of Power Transmission Equipment and System Security New Technology Chongqing University Chongqing 400044 China School of Electronic and Information Engineering Southwest University Chongqing 400715 China College of Computer Science Sichuan University Chengdu 610065 China Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom

Brain computer Interface (BCI) provides a direct communication channel from brain to peripheral equipment. Common Spatial Patterns (CSP) is wildly used to extract features for electroencephalogram (EEG). However, basic CSP only suits two-class discrimination and is unable to solve multi-class discrimination problems. This paper proposes a modified CSP method termed Bisearch Common Spatial Patterns (BCSP) to solve a four-class BCI problem. In BCSP, the Fisher's Linear Discriminant Analysis (LDA) is used to discriminate among the four motor imagery tasks. The BCSP can effectively reduce the number of the basic CSP, and thus makes the overall classification procedure more efficient. The Graz BCI data set from the BCI 2008 competition be used to verify the effectiveness of the BCSP. Simulation results show that BCSP has better performance than other extension schemes. © 2012 Binary Information Press January 2012.

关键词： Brain computer interface

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Efficient discovery of Hub nodes in complex aero-space information network

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Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) 2012年第SUPPL.1期40卷 394-397页

作者： Zeng, Wei Li, Chuan Tang, Changjie Yang, Shangqian College of Computer Science Sichuan University Chengdu 610065 China National Key Laboratory of Air Control Automation System Technology Sichuan University Chengdu 610065 China

Aero-space information network characteristic of high complexity, real-time, large-scale in data. Through a large number of experimental analysis, an algorithm of efficient discovery of Top-k closeness centrality key nodes in information network based on additional window(AW) was proposed. Experiments show that the new proposed algorithm can guarantee accuracy rate of more than 80% on both artificial and real-world datasets with processing time reduced by about 50% on given several AWs.

关键词： Complex networks

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