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Social sensing enhanced time estimation for bus service

Concurrency and Computation: Practice and Experience 2015年第15期27卷

作者： Jin Liu Juan Li Xiaohui Cui Xiaoguang Niu Xiaoping Sun Jing Zhou State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEA s and road condition attributions PRCA s. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEA s of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： social sensing in-time bus service bus route arrival time estimation

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Model Predictive Control for Household Energy Management based on Individual Habit

Model Predictive Control for Household Energy Management bas...

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第25届中国控制与决策会议

作者： keyu Long Zaiyue Yang State Key Lab. of Industrial Control Technology Zhejiang University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781467355339

This paper focuses on the load shifting problem in a household scenario with a large-capacity battery. We propose a novel Model Predictive Control （MPC） framework to control the charge/discharge power of battery, hence to shave the peak load. Being different from other studies, the framework is designed on the base of individual habit of energy consumption, as it is envisioned that the individual habit is critical for choosing the suitable energy services. In this paper, the habit is modeled as a Markov process and gradually learned by an iterative algorithm;thus, the habit can be utilized for the prediction of future energy consumption. Then, the rolling optimization is applied for the optimal control of the charge/discharge power of battery. It is shown by numerical simulations that the proposed approach can significantly reduce the peak load.

关键词： Habit Model Predictive Control Markov Chain Nonlinear Optimization Household Energy Management

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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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Saliency Detection Using Color Spatial Variance Weighted Graph Model

Saliency Detection Using Color Spatial Variance Weighted Gra...

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Asian Conference on Pattern Recognition (ACPR)

作者： Xiaoyun Yan Yuehuan Wang Mengmeng Song Man Jiang National Key Lab of Science & Technology on Multi-spectral Information Processing Huazhong University of Science & Technology Wuhan China

Saliency detection as a recently active research field of computer vision, has a wide range of applications, such as pattern recognition, image retrieval, adaptive compression, target detection, etc. In this paper, we propose a saliency detection method based on color spatial variance weighted graph model, which is designed rely on a background prior. First, the original image is partitioned into small patches, then we use mean-shift clustering algorithm on this patches to get sorts of clustering centers that represents the main colors of whole image. In modeling stage, all patches and the clustering centers are denoted as nodes on a specific graph model. The saliency of each patch is defined as weighted sum of weights on shortest paths from the patch to all clustering centers, each shortest path is weighted according to color spatial variance. Our saliency detection method is computational efficient and outperformed the state of art methods by higher precision and better recall rates, when we took evaluation on the popular MSRA1000 database.

关键词： Image color analysis Clustering algorithms Visualization Image segmentation Image edge detection Algorithm design and analysis Computational modeling

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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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An optimized band selection scheme for hyperspectral imagery analysis 5

An optimized band selection scheme for hyperspectral imagery...

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5th Workshop on Hyperspectral Image and Signal processing: Evolution in Remote Sensing, WHISPERS 2013

作者： Su, Hongjun Du, Qian Du, Peijun School of Earth Sciences and Engineering Hohai University China Department of Electrical and Computer Engineering Mississippi State University United States Department of Geographical Information Science Nanjing University China Jiangsu Key Lab. of Spectral Imaging and Intelligent Sense Nanjing University of Science and Technology China

ISBN: (纸本)9781509011193

A particle swarm optimization (PSO)-based automatic system to determine the number of optimal band sets and corresponding bands is proposed. A simple searching criterion function, called minimum estimated abundance covariance (MEAC), requiring class signatures only, is used in this method. The experimental results show that the PSO-based algorithm outperforms the popular sequential forward selection (SFS) method. The two PSOs can achieve the balance between the two objectives, and it may provide even better accuracy than a single-objective PSO. © 2013 IEEE.

关键词： Hyperspectral imaging

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A REVIEW ON ARTERY WALL SEGMENTATION TECHNIQUES AND INTIMA-MEDIA THICKNESS MEASUREMENT FOR CAROTID ULTRASOUND IMAGES

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Journal of Innovative Optical Health Sciences 2012年第1期5卷 75-84页

作者： XIN YANG WANJI HE KAITONG LI JIAOYING JIN XUMING ZHANG MING YUCHI MINGYUE DING State Key Laboratory for Multi-Spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI)Huazhong University of Science and Technology Wuhan 430074HubeiChina Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074HubeiChina

Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and *** is important for the early stage diagnosis and monitoring medical intervention of the *** stenosis is a classical atherosclerotic lesion with vessel wall narrowing down and accumulating plaques *** carotid artery of intima-media thickness(IMT)is a key indicator to the *** the development of computer assisted diagnosis technology,the imaging techniques,segmentation algorithms,measurement methods,and evaluation tools have made considerable *** imaging,being real-time,economic,reliable,and safe,now seems to become a standard in vascular assessment methodology especially for the measurement of *** review firstly attempts to discuss the clinical relevance of measurements in clinical practice at first,and then followed by the challenges that one has to face when approaching the segmentation of ultrasound ***,the commonly used methods for the IMT segmentation and measurement are ***,discussion and evaluation of different segmentation techniques are *** overview of summary and future perspectives is given finally.

关键词： Ultrasound(US)images carotid artery intima-media thickness(IMT) atherosclerosis image segmentation computer assisted diagnosis(CAD)

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Fast template matching with partial skipping using sub-template

Fast template matching with partial skipping using sub-templ...

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2012 3rd IEEE/IET International Conference on Audio, Language and Image processing, ICALIP 2012

作者： Zhang, Qiao Gao, Huijie Kang, Zhen State Key Lab. of Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Tech. Wuhan 430074 China School of Mathematic and Computer Science Wuhan Polytechnic University Wuhan 430023 China

ISBN: (纸本)9781467301718

This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with threshold, if some SAD exceeds the threshold, set the new threshold equal to this SAD value and this point is one potential optimization location, when all points in the current window are compared, we will get a minimum value and a optimization location, then skip the other points whose SAD is not the minimum value. In other words, the searching step is that template size subtracts the subtemplate size, and we set the next threshold equal to the current optimization SAD value, we update the threshold and the optimal point until the end of the searched image like this, then will find the global minimum points and its SAD value. Experimental results show that the proposed method is near one hundred times faster than the conventional template match method. © 2012 IEEE.

关键词： Global optimization

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FRPWPS: A filter driver and reverse proxy based web protection system

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Journal of Networks 2012年第6期7卷 997-1005页

作者： He, Qian Wang, Yong Zhao, Bang Yao, Linlin Chen, Hongbin Key Laboratory of Cognitive Radio and Information Processing Ministry of Education Guilin University of Electronic Technology Guilin 541004 China State Key Lab. of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876 China

Website attack has seriously affected the owner's profit and the security of the Internet. In this paper, a Filter Driver and Reverse Proxy based Web Protection System (FRPWPS) with a version control-based safe recovery mechanism is proposed. FRPWPS consists of five sub systems including web file monitor, content publish, web reverse proxy, backup and recovery, and monitor center. The file filter driver is used to protect web program files from illegally tampered. The protected websites are run behind a web proxy with intrusion detection function. The backup and recovery subsystem is realized by a FTP protocol. Experiments analyze the functions and costs of FRPWPS, and results show that it can work well and achieve good performance for web protection. © 2012 Academy Publisher.

关键词： Recovery

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Fast Template Matching with Partial Skipping Using Sub-template

Fast Template Matching with Partial Skipping Using Sub-templ...

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International Conference on Audio, Language and Image processing

作者： Qiao Zhang Huijie Gao Zhen Kang State Key Lab. of Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence School of Mathematic & Computer Science Wuhan Polytechnic University

ISBN: (纸本)9781467301732

This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with threshold, if some SAD exceeds the threshold, set the new threshold equal to this SAD value and this point is one potential optimization location, when all points in the current window are compared, we will get a minimum value and a optimization location, then skip the other points whose SAD is not the minimum value. In other words, the searching step is that template size subtracts the sub-template size, and we set the next threshold equal to the current optimization SAD value, we update the threshold and the optimal point until the end of the searched image like this, then will find the global minimum points and its SAD value. Experimental results show that the proposed method is near one hundred times faster than the conventional template match method.

关键词： Computational efficiency Prediction algorithms Search problems Accuracy Correlation Signal processing algorithms Pattern recognition

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