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IEEE International Conference on Image Processing

作者： Qingyu Pang Jing Yu Weidong Sun State Key Lab. of Intelligent Technology & Systems Tsinghua National Lab. for Information Science & Technology Dept. of Electronic Engineering Tsinghua University College of Computer Science and Technology Beijing University of Technology

ISBN: (纸本)9781479983407

With the rapid development of the hyperspectral technology, spectra unmixing has received more and more attentions. In this paper, in order to measure the similarity between the extracted endmember spectra and the actual corresponding spectra of land covers and maintain the spectral absorption feature, a wavelet weighted similarity is presented. And by introducing it into the minimum distance constrained nonnegative matrix factorization method, a spectral unmixing method based on the wavelet weighted similarity is proposed. Base on the experiments with real hyperspectral image, the feasibility and real performance of our method has been examined and compared with that of unsupervised spectral unmixing method.

关键词： Spectral unmixing Wavelet weighted similarity Nonnegative matrix factorization

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GROUP-BASED HYPERSPECTRAL IMAGE DENOISING USING LOW RANK REPRESENTATION

GROUP-BASED HYPERSPECTRAL IMAGE DENOISING USING LOW RANK REP...

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IEEE International Conference on Image Processing

作者： Mengdi Wang Jing Yu Weidong Sun State Key Lab. of Intelligent Technology & Systems Tsinghua National Lab. for Information Science & Technology Dept. of Electronic Engineering Tsinghua University College of Computer Science and Technology Beijing University of Technology

ISBN: (纸本)9781479983407

For the hyperspectral image (HSI) denoising problem, we propose a group-based low rank representation (GLRR) method. A corrupted HSI is divided into overlapping patches and the similar patches are combined into a group. The group is denoised as a whole using low rank representation (LRR). Our method can employ both the local similarity within the patch and the nonlocal similarity across the patches within a group simultaneously, while nonlocal similar patches within the group can bring extra structure information for the corrupted patch, which makes the noise more significant to be detected as outliers. Since the uncorrupted patches have an intrinsic low-rank structure, LRR is employed for the denoising of the patch group. Both simulated and real data are used in the experiments. The effectiveness of our method is proved both qualitatively and quantitatively.

关键词： Denoising Hyperspectral image Low rank representation Nonlocal similarity Noise reduction hyperspectral imagery Patches images AKR1B10 gene outliers

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An effective spatial-temporal denoising approach for dept. images

An effective spatial-temporal denoising approach for depth i...

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International Conference on Digital Signal Processing (DSP)

作者： Bor-Shing Lin Wei-Ren Chou Chu Yu Po-Hsun Cheng Po-Jui Tseng Sao-Jie Chen Dept. of Computer Science and Information Engineering National Taipei University New Taipei City Taiwan Dept. of Electronic Engineering National Ilan University Yilan Taiwan Department of Software Engineering National Kaohsiung Normal University Kaohsiung City Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9781479980598

Image retrieval and computer vision rely heavily on noise removal and image hole padding to ensure the accurate rendering of images from dept. cameras. Noise can undermine the accuracy of dept. values, resulting in object occlusion and temporal variation in dept. pixels. This paper proposes an efficacious approach to dealing with this problem based on an exemplar-based inpainting method for the removal of noise from object-removed images obtained using RGB-D cameras. The proposed method was also applied to the Tsukuba Stereo database, which provides 3D video with ground truth disparity maps. Experiment results were evaluated in terms of peak signal-to-noise ratio (PSNR) and computation time. Moreover, the self-recorded RGB-D dept. images database was used to verify the corrections in spatial and temporal variation of dept. values. Our results demonstrate the effectiveness of the proposed method by comparing the original occluded dept. images with the images being processed.

关键词： Cameras Filtering Databases Image edge detection Noise Noise reduction Three-dimensional displays

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Merits of Organizational Metrics in Defect Prediction: An Industrial Replication 15

Merits of Organizational Metrics in Defect Prediction: An In...

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International Conference on software engineering (ICSE)

作者： Bora Caglayan Burak Turhan Ayse Bener Mayy Habayeb Andriy Miransky Enzo Cialini Department of Mathematics Ryerson University Canada Dept. of Information Processing Science University of Oulu Finland Mechanical and Industrial Engineering Ryerson University Canada Department of Computer Science Ryerson Unniversity Canada IBM Toronto Software Laboratory Canada

Defect prediction models presented in the literature lack generalization unless the original study can be replicated using new datasets and in different organizational settings. Practitioners can also benefit from replicating studies in their own environment by gaining insights and comparing their findings with those reported. In this work, we replicated an earlier study in order to investigate the merits of organizational metrics in building defect prediction models for large-scale enterprise software. We mined the organizational, code complexity, code churn and pre-release bug metrics of that large scale software and built defect prediction models for each metric set. In the original study, organizational metrics were found to achieve the highest performance. In our case, models based on organizational metrics performed better than models based on churn metrics but were outperformed by pre-release metric models. Further, we verified four individual organizational metrics as indicators for defects. We conclude that the performance of different metric sets in building defect prediction models depends on the project's characteristics and the targeted prediction level. Our replication of earlier research enabled assessing the validity and limitations of organizational metrics in a different context.

关键词： Measurement software Organizations software engineering Predictive models Context Principal component analysis

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Parameterized spatial query processing based on social probabilistic clustering 14

Parameterized spatial query processing based on social proba...

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22nd ACM SIGSPATIAL International Conference on Advances in Geographic information systems, ACM SIGSPATIAL GIS 2014

作者： Tang, Liang Chen, Haiquan Ku, Wei-Shinn Sun, Min-Te Dept. of Computer Science and Software Engineering Auburn University United States Dept. of Mathematics and Computer Science Valdosta State University United States Dept. of Computer Science and Information Engineering National Central University Taiwan

ISBN: (纸本)9781450331319

In this paper, we propose two parameterized frameworks, namely the Uniform Watchtower (UW) framework and the Hot zonebased Watchtower (HW) framework, for the evaluation of spatial queries on large road networks. The motivation of this research is twofold: (1) how to answer spatial queries efficiently on large road networks with massive POI data and (2) how to take advantage of social data in spatial query processing. In UW, the network traversal terminates once it acquires the Point of Interest (POI) distance information stored in watchtowers. In HW, by observing that users' movements often exhibit strong spatial patterns, we employ probabilistic clustering to model mobile user check-in data as a mixture of 2-dimensional Gaussian distributions to identify hot zones so that watchtowers can be deployed discriminatorily. Our analyses verify the superiority of HW over UW in terms of query response time. Copyright 2014 ACM.

关键词： Roads and streets

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Plexe: A platooning extension for Veins

Plexe: A platooning extension for Veins

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2014 IEEE Vehicular Networking Conference, VNC 2014

作者： Segata, Michele Joerer, Stefan Bloessl, Bastian Sommer, Christoph Dressler, Falko Cigno, Renate Lo Computer and Communication Systems Institute of Computer Science University of Innsbruck Austria Dept. of Information Engineering and Computer Science University of Trento Italy Distributed Embedded Systems Dept. of Computer Science University of Paderborn Germany

ISBN: (纸本)9781479976607

Cooperative driving in general and Cooperative Adaptive Cruise Control (CACC) or platooning in particular require blending control theory, communications and networking, as well as mechanics and physics. Given the lack of an integrated modeling framework and theory as well as the prohibitively high costs of using prototypes for what-if studies, simulation remains the fundamental instrument to evaluate entire cooperative driving systems. This work presents Plexe, an Open Source extension to Veins that offers researchers a simulation environment able to run experiments in realistic scenarios, taking into account physics and mechanics of the vehicles, communications and networking impairments, and Inter-Vehicle Communication (IVC) protocol stacks. Plexe is easily extensible and already implements protocols to support platooning and cooperative driving applications and several state of the art cruise control models. We describe the structure of the simulator and the control algorithms that Plexe implements and provide two use cases which show the potential of our framework as a powerful research tool for cooperative driving systems. © 2014 IEEE.

关键词： Blending

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The meter tells you are at home! Non-intrusive occupancy detection via load curve data

The meter tells you are at home! Non-intrusive occupancy det...

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IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Guoming Tang Kui Wu Jingsheng Lei Weidong Xiao Dept. of Computer Science University of Victoria B.C Canada University of Victoria Victoria BC CA School of Computer and Information Engineering Shanghai University of Electric Power Shanghai China Sci. & Technol. on Information Systems Engineering Lab National University of Defense Technology Changsha China

Occupancy detection can greatly facilitate HVAC and lightning control for building energy saving. Sensor based occupancy detection is usually costly and may suffer from high false positive rates. As such, occupancy detection using load curve data has been proposed. Such type of methods, however, normally relies on tedious and nontrivial model training process. To overcome this pitfall, we develop a simple, non-intrusive occupancy detection approach that does not require any model training and only uses load curve data and readily-available appliance knowledge. The method consists of three main steps: i) the appliances' mode states are firstly decoded via a carefully designed total variation minimization problem; ii) the human actions are recovered with a-priori knowledge of human-activated switching events; iii) the occupancy states are then inferred based on the recovered human actions along with empirical association rules. We evaluate our approach and compare with existing methods with real-world data. The results show that our approach can achieve similar performance to those using supervised machine learning.

关键词： Home appliances Switches Power demand Buildings Training Smart grids Hidden Markov models

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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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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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Diagnosis of balance disorders using decision support systems based on data mining techniques 15

Diagnosis of balance disorders using decision support system...

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15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015

作者： Exarchos, Themis P. Stefanou, Kostas Rigas, George Bibas, Athanasios Kikidis, Dimitris Nikitas, Christos Wuyts, Floris L. Ihtijarevic, Berina Maes, Leen Cenciarini, Massimo Maurer, Christoph Iliopoulou, Dimitra Macdonald, Nora Bamiou, Doris Eva Luxon, Linda Prasinos, Marios Spanoudakis, George Koutsouris, Dimitrios Fotiadis, Dimitrios I. Institute of Communication and Computer Systems National Technical University of Athens Greece Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering University of Ioannina Ioannina Greece National and Kapodistrian University of Athens Athens Greece Antwerp University Research Centre for Equilibrium and Aerospace Antwerp Belgium Ghent University Ghent Belgium University Medical Center Freiburg Freiburg Germany University College London Ear Institute London United Kingdom City University London United Kingdom

ISBN: (纸本)9781467379830

In this work we present the decision support of the EMBalance platform. EMBalance is a platform for the management of balance disorders in terms of diagnosis, treatment and evolution. The EMBalance platform aims to extend existing but generic and currently uncoupled balance modelling activities leading to a multi-scale and patient-specific balance model, which will be incorporated in a Decision Support System (DSS), towards the early diagnosis, prediction and the efficient treatment planning of balance disorders. The diagnosis part of the decision support system uses various data ranging from demographic characteristics to clinical examinations, auditory and vestibular tests. Currently we present some initial technical choices and indicative results of the decision support system for diagnosing balance disorders, based on data mining techniques and clinical guidelines. © 2015 IEEE.

关键词： Decision support systems

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