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IEEE International Symposium on Biomedical Imaging

作者： S. Klein M. Loog F. van der Lijn T. den Heijer A. Hammers M. de Bruijne A. van der Lugt R.P.W. Duin M.M.B. Breteler W.J. Niessen Biomedical Imaging Group Rotterdam Departments of Radiology & Medical Informatics Erasmus MC-University Medical Center Rotterdam Rotterdam Netherlands Pattern Recognition Laboratory Faculty of Electrical Engineering Mathematics Computer Science Delft University of Technnology Netherlands Department of Neurology Erasmus MC-University Medical Center Rotterdam Rotterdam Netherlands Neurodis Foundation CERMEP PET Centre Lyon France MRC Clinical Sciences Centre and Division of Neuroscience and Mental Health Imperial College Hammersmith Hospital London UK Department of Computer Science University of Copenhagen Copenhagen Denmark Department of Radiology Erasmus MC-University Medical Center Rotterdam Rotterdam Netherlands Department of Epidemiology & Biostatistics Erasmus MC-University Medical Center Rotterdam Rotterdam Netherlands Imaging Science & Technology Department of Applied Sciences Delft University of Technnology Netherlands

ISBN: (纸本)9781424441259

This article studies the possibility of detecting dementia in an early stage, using nonrigid registration of MR brain scans in combination with dissimilarity-based pattern recognition techniques. Instead of focussing on the shape of a single brain structure, we take into account the shape differences within the entire brain. Imaging data was obtained from a longitudinal, population based study of the elderly. A set of 29 subjects was identified, who were asymptomatic at the time of scanning, but were diagnosed as having dementia within 0.7 to 5 years after the scan, and a set of 29 age and gender matched healthy controls were selected. Each subject was registered to all other subjects, using a nonrigid registration algorithm. Based on statistics of the deformation field in the brain, a dissimilarity measure was calculated between each pair of subjects, yielding a 58×58 dissimilarity matrix. A kNN classifier was trained on the dissimilarity matrix and the performance was tested in a leave-one-out experiment. A classification accuracy of 81% was attained (spec. 83%, sens. 79%). This demonstrates the potential of whole-brain intersubject dissimilarities to aid in early diagnosis of dementia.

关键词： Dementia Brain Pattern recognition Shape Radiology computer science Biomedical imaging Senior citizens Diseases Biomarkers

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Enabling data structure oriented performance analysis with hardware performance counter support

Enabling data structure oriented performance analysis with h...

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Workshops on Parallel Processing, Euro-Par 2008: VHPC 2008, UNICORE 2008, HPPC 2008, SGS 2008, PROPER 2008, ROIA 2008, and DPA 2008

作者： Fürlinger, Karl Terpstra, Dan You, Haihang Mucci, Phil Moore, Shirley Computer Science Division EECS Department University of California at Berkeley United States Innovative Computing Laboratory Department of Electrical Engineering and Computer Science University of Tennessee United States

ISBN: (纸本)3642009549

An interesting and as of yet under-represented aspect of program development and optimization are data structures. Instead of analyzing data with respect to code regions, the objective here is to see how performance metrics are related to data structures. With the advanced performance monitoring unit of Intel's Itanium processor series such an analysis becomes possible. This paper describes how the hardware features of the Itanium 2 processor are exploited by the perfmon and PAPI performance monitoring APIs and how PAPI's support for address range restrictions has been integrated into an existing profiling tool to achieve the goal of data structure oriented profiling in the context of OpenMP applications. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Data structures

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Impact of mobility on spectrum sensing in cognitive radio networks

Impact of mobility on spectrum sensing in cognitive radio ne...

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2009 ACM Workshop on Cognitive Radio Networks, CoRoNet'09, Co-located with the Mobile computing and Networking Conference, MobiCom'09

作者： Min, Alexander W. 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)9781605587387

In cognitive radio networks (CRNs), spectrum sensing is key to opportunistic spectrum access while preventing any unacceptable interference to primary users' communications. Although cognitive radios function as spectrum sensors and move around, most, if not all, of existing approaches assume stationary spectrum sensors, thus providing inaccurate sensing results. As part of our effort to solve/alleviate this problem, we consider the impact of sensor mobility on spectrum sensing performance in a joint optimization framework for sensor cooperation and sensing scheduling. We show that sensor mobility increases spatio-temporal diversity in received primary signal strengths, and thus, improves the sensing performance. This is intuitively plausible, but have not been tested previously. Based on this observation, we propose a sensing strategy that minimizes the sensing overhead by finding an optimal combination of the number of sensors to cooperate and the number of times spectrum sensing must be scheduled. This result provides a useful insight to understand the spectrum sensing and its coupling with sensor mobility. Copyright 2009 ACM.

关键词： Cognitive radio

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Scheduling parallel applications on Utility Grids: Time and cost trade-off management

Scheduling parallel applications on Utility Grids: Time and ...

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32nd Australasian computer science Conference, ACSC 2009

作者： Garg, Saurabh Kumar Buyya, Rajkumar Siegel, H.J. Grid Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne VIC 3010 Australia Electrical and Computer Engineering Department Colorado State University Fort Collins United States Computer Science Department Colorado State University Fort Collins United States

ISBN: (纸本)9781920682729

With the growth of Utility Grids and various Grid market infrastructures, the need for efficient and cost effective scheduling algorithms is also increasing rapidly, particularly in the area of meta-scheduling. In these environments,users not only may have conflicting requirements with other users, but also they have to manage the trade-off between time and cost such that their applications can be executed most economically in the minimum time. Thus, choosing of the best Grid resources becomes a challenge in such a competitive market. This paper presents two novel heuristics for scheduling parallel applications on Utility Grids that manage and optimize the trade-off between time and cost constraints. The performance of the heuristics is evaluated through extensive simulations of a real-world environment with real parallel workload models to demonstrate the practicality of our algorithms. We compare our scheduling algorithms against other common algorithms used by current meta-schedulers. The results shows that our algorithms outperform other algorithms by minimizing the time and cost of application execution on Utility Grids. Copyright © 2009, Australian computer Society, Inc.

关键词： Scheduling algorithms

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Ontology engineering

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Nature Biotechnology 2010年第2期28卷 128-130页

作者： Alterovitz, Gil Xiang, Michael Hill, David P. Lomax, Jane Liu, Jonathan Cherkassky, Michael Dreyfuss, Jonathan Mungall, Chris Harris, Midori A. Dolan, Mary E. Blake, Judith A. Ramoni, Marco F. Children's Hospital Informatics Program Harvard-MIT Division of Health Sciences and Technology Harvard Medical School Boston MA United States Partners Healthcare Center for Personalized Genetic Medicine Boston MA United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA United States Jackson Laboratory Bar Harbor ME United States EMBL-EBI Wellcome Trust Genome Campus Hinxton United Kingdom Department of Biology Massachusetts Institute of Technology Cambridge MA United States Lawrence Berkeley National Laboratory Berkeley CA United States

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Spectral derivative feature coding for hyperspectral signature analysis

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Pattern Recognition 2009年第3期42卷 395-408页

作者： Chang, Chein-I Chakravarty, Sumit Chen, Hsian-Min Ouyang, Yen-Chieh Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Environmental Restoration and Disaster Reduction Research Center National Chung Hsing University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Department of Radiology China Medical University Hospital Taichung Taiwan

This paper presents a new approach to hyperspectral signature analysis, called spectral derivative feature coding (SDFC). It is derived from texture features used in texture classification to dictate gradient changes among adjacent bands in characterizing spectral variations so as to improve better spectral discrimination and classification. In order to evaluate its performance, two known binary coding methods, spectral analysis manager (SPAM) and spectral feature-based binary coding (SFBC) are used to conduct comparative analysis. Experimental results demonstrate that the proposed SDFC performs more effectively in capturing spectral characteristics than do SPAM and SFBC. © 2008 Elsevier Ltd. All rights reserved.

关键词： Spectrum analysis

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Predictive routing of contexts in an overlay network

Predictive routing of contexts in an overlay network

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IFIP/IEEE International Symposium on Integrated Network Management

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

While mobile nodes (MNs) undergo handovers across inter-wireless access networks, their contexts must be propagated for seamless re-establishment of on-going application sessions, including IP header compression, secure mobile IP, authentication, authorization, and accounting services, to name a few. Routing contexts via an overlay network either on-demand or based on prediction of an MNs' mobility, introduces a new challenging requirement of context management. This paper proposes a context router (CXR) that manages contexts in an overlay network. A CXR is responsible for (1) monitoring of MNs' cross-handover, (2) analysis of MNs' movement patterns, and (3) context routing ahead of each MN's arrival at an AP or a network. The predictive routing of contexts is performed based on statistical learning of (dis)similarities between the patterns obtained from vector distance measurements. The proposed CXR has been evaluated on a prototypical implementation based on an MN mobility model in an emulated access network. Our evaluation results show that the prediction mechanisms applied on the CXR outperform a Kalman-filter-based method with respect to both prediction accuracy and computation performance.

关键词： Routing Context-aware services Authentication Authorization Monitoring Pattern analysis Performance evaluation Statistical learning Distance measurement Prototypes

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Enhancing the surgeons reality: Smart visualization of bolus time of arrival and blood flow anomalies from time lapse series for safety and speed of cerebrovascular surgery

Enhancing the surgeons reality: Smart visualization of bolus...

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38th Applied Imagery Pattern Recognition Workshop: Vision: Humans, Animals, and Machines, AIPRW 2009

作者： Copeland, Andrew Mangoubi, Rami Desai, Mukund Mitter, Sanjoy Malek, Adel C.S. Draper Laboratory Cambridge MA United States Department of Electrical Engineering and Computer Science MIT Cambridge MA United States Department of Neurosurgery Tufts-New England Medical Center Boston MA United States

ISBN: (纸本)9781424451463

A noise adaptive Cusum-based algorithm for determining the arrival times of contrast at each spatial location in a 2D time sequence of angiographic images is presented. We employ a new group-wise registration algorithm to remove the effect of patient motions during the acquisition process. By using the registered image the proposed arrival time provides accurate results without relying on a priori knowledge of the shape of the time series at each location or even on the time series at each location having the same shape under translation.

关键词： Time series

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Scheduling of Battery Charge, Discharge, and Rest

Scheduling of Battery Charge, Discharge, and Rest

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Real-Time Systems Symposium (RTSS)

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

Electric vehicles operate inefficiently with a naive battery management system that charges or discharges battery cells in a pack based solely on application load demands. The battery pack's operation-time and lifetime can be extended significantly by effectively scheduling (the cyber part) battery charge, discharge, and rest activities, based on the battery characteristics (the physical part). We propose a set of policies for scheduling battery-cell activities, called the weighted-k round-robin (kRR) scheduling framework. This framework dynamically adapts battery-cell activities to load demands and the condition of individual cells, thereby extending the battery pack's operation-time and making them robust to anomalous voltage-imbalances. The framework comprises two key components. First, an adaptive filter estimates the upcoming load demand. Then, based on the estimated load demand, the kRR scheduler determines the number of parallel-connected cells to be discharged simultaneously. The scheduler also effectively partitions the cells in the pack, allowing the cells to be simultaneously charged and discharged in coordination with the battery reconfiguration system we developed earlier [17]. Besides the kRR scheduling framework, we characterize the discharge and recovery efficiency of a Lithium-ion battery cell. The kRR scheduling framework is shown to outperform three alternative scheduling mechanisms with respect to the operation-time by 7-56%, and improve the tolerance of voltage-imbalance by up to 50%.

关键词： Real time systems Robustness Global warming Threshold voltage Processor scheduling Laboratories Battery powered vehicles Battery management systems Application software Adaptive filters

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On Dynamic Reconfiguration of a Large-Scale Battery System

On Dynamic Reconfiguration of a Large-Scale Battery System

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IEEE Symposium on Real-Time and Embedded Technology and Applications

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

Electric vehicles powered with large-scale battery packs are gaining popularity as gasoline price soars. Large-scale battery packs usually consist of an estimated 12,000 battery cells connected in series and parallel, which are susceptible to battery-cell failures. Unfortunately, current battery-management systems are unable to handle the inevitable battery-cell failures very well. To address this problem, we propose a dynamic reconfiguration framework that monitors, reconfigures, and controls large-scale battery packs online. The framework is built upon a syntactic bypassing mechanism that provides a set of rules for changing the battery-pack configuration, and a semantic bypassing mechanism by which the battery-cell connectivity is reconfigured to recover from a battery-cell failure. In particular, the semantic bypassing mechanism is dictated by constant-voltage-keeping and dynamic-voltage-allowing policies. The former policy is effective in preventing unavoidable voltage drops during the battery discharge, while the latter policy is effective in supplying different amounts of power to meet a wide-range of application requirements. Our experimental evaluation has shown the proposed framework to enable the battery packs to be 9 times as fault-tolerant as a legacy scheme.

关键词： Large-scale systems Vehicle dynamics Centralized control Control systems Voltage Real time systems Battery management systems Application software Embedded computing Power engineering computing

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