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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Yu Su Shiguang Shan Xilin Chen Wen Gao School of Computer Science and Technology Harbin Institute of Technology China Digital Media Research Center Institute of Computing Technology CAS China Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences China Institute for Digital Media Peking University China

Real-world face recognition systems often have to face the single sample per person (SSPP) problem, that is, only a single training sample for each person is enrolled in the database. In this case, many of the popular face recognition methods fail to work well due to the inability to learn the discriminatory information specific to the persons to be identified. To address this problem, in this paper, we propose an Adaptive Generic Learning (AGL) method, which adapts a generic discriminant model to better distinguish the persons with single face sample. As a specific implementation of the AGL, a Coupled Linear Representation (CLR) algorithm is proposed to infer, based on the generic training set, the within-class scatter matrix and the class mean of each person given its single enrolled sample. Thus, the traditional Fisher's Linear Discriminant (FLD) can be applied to SSPP task. Experiments on the FERET and a challenging passport face database show that the proposed method can achieve better results compared with other common solutions to the SSPP problem.

关键词： Face recognition Principal component analysis Linear discriminant analysis computer science Content addressable storage Laboratories Deductive databases Information processing Scattering Image databases

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SVLC: Service Value Life Cycle Model

SVLC: Service Value Life Cycle Model

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IEEE International Conference on Cloud computing, CLOUD

作者： Zhongjie Wang Xiaofei Xu Research Center of Intelligent Computing of Enterprises and Services School of Computer Science and Technology Harbin Institute of Technology Harbin China

Value plays a central role in services and is considered as the ultimate objective that both providers and customers pursue through providing and consuming a service. In this paper, based on a brief discussion of the service value concept, we present a service value life cycle model (SVLC), where the value delivery process is decomposed into 7 phases (bi-lateral searching, bi-lateral negotiation, unilateral preparation, co-production, transferring, usage, and payment). Each phasepsilas repeatable tasks, output, quality metrics of the process and output, and possible innovative design decisions, were elaborately analyzed. A C2C service system, ***, is briefly discussed to help understand SVLC in the real world. Comparisons between SVLC and traditional service research shows that SVLC provides some significance to systematical service innovations and service quality metrics design from life cycle (temporal) point of view. Potential effects on service computing research and some future work are also discussed.

关键词： Technological innovation Cloud computing Ice computer science Electronic mail Collaborative work Production Quality of service Innovation management Problem-solving

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Cross-layer design for adaptive data reporting in wireless sensor networks

Cross-layer design for adaptive data reporting in wireless s...

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IEEE International Conference on Pervasive computing and Communications (PerCom)

作者： Hyun Jung Choe Preetam Ghosh Sajal K. Das Center of Research in Wireless Mobility and Networking (CReWMaN) Department of Computer Science and Engineering University of Texas Arlington USA School of Computing University of Southern Mississippi USA

In this paper, we propose an integrated cross-layer data reporting scheme focusing on communication protocols in wireless sensor networks. The scheme operates based on the various application demands and available resources to provide an adaptive quality of service (QoS). The goal of this work is to achieve the expected information quality at the end system by efficiently controlling data reporting functions in communication layers considering parameters from other layers. The main work of this paper focuses on the QoS-aware data reporting tree construction scheme, called QRT, and the QoS-aware node scheduling scheme, called QNS. QRT constructs a data reporting tree based on the conditions of the end-to-end delay and the traffic load to find data reporting paths from each cluster head, which has already collected data from its cluster members, to a sink. QNS schedules a certain number of nodes that are selected based on the QoS requirements in a cluster to report data to its cluster head in a collision-free manner. Simulation results show that these schemes provide good throughput performance while providing stable data reporting that is not affected by network density.

关键词： Cross layer design Wireless sensor networks Quality of service Protocols Routing Delay Throughput Remote monitoring Sensor phenomena and characterization Temperature sensors

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Class-Based Data Reporting Scheme in Heterogeneous Wireless Sensor Networks

Class-Based Data Reporting Scheme in Heterogeneous Wireless ...

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International Conference on computer Communications and Networks (ICCCN)

作者： Hyun Jung Choe Preetam Ghosh Kalyan Basu Sajal K. Das Center of Research in Wireless Mobility and Networking (CReWMaN) Department of Computer Science and Engineering University of Texas Arlington USA School of Computing University of Southern Mississippi USA

Data reporting strategy in heterogeneous wireless sensor networks can be differentiated based on task-specific requirements. In this paper, we propose a novel two-phase data reporting (TDR) scheme that supports class-based QoS to sensor nodes in different priority classes. In the first phase, time slots are divided into separate data reporting round defined for each class, while in the second phase, the sensor nodes in the same class are scheduled to particular time slots depending on the given number of slots calculated in the first phase. In TDR, sensor nodes compete with other nodes in the same class only, while nodes in different classes have differentiated channel access opportunity. TDR is performed in a single-hop cluster-based topology, and a cluster head acts as a node assignment manager (NAM). Sensor nodes wake up for their scheduled time slots; otherwise, they go into sleep mode to save energy. TDR supports both schedule- based and contention-based channel access mechanisms and is scalable due to its distributed nature.

关键词： Wireless sensor networks Quality of service Sensor phenomena and characterization Telecommunication traffic Scalability Programmable control Adaptive control Multiaccess communication Broadcasting Access protocols

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AAAI 2008 workshop reports

AAAI 2008 workshop reports

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作者： Anand, Sarabjot Singh Bunescu, Razvan Carvcdho, Vitor Chomicki, Jan Conitzer, Vincent Cox, Michael T. Dignum, Virginia Dodds, Zachary Dredze, Mark Furcy, David Gabrilovich, Evgeniy Göker, Mehmet H. Guesgen, Hans Hirsh, Haym Jannach, Dietmar Junker, Ulrich Ketter, Wolfgang Kobsa, Alfred Koenig, Sven Lau, Tessa Lewis, Lundy Matson, Eric Metzler, Ted Mihalcea, Rada Mobasher, Bamshad Pineau, Joelle Poupart, Pascal Raja, Anita Ruml, Wheeler Sadeh, Norman Shani, Guy Shapiro, Daniel Smith, Trey Taylor, Matthew E. Wagstaff, Kiri Walsh, William Zhou, Rong Department of Computer Science University of Warwick United Kingdom School of Electrical Engineering and Computer Science Ohio University United States Microsoft Live Labs United States computer science and engineering University at Buffalo United States Computer science and economics Duke University United States Intelligent Computing group of BBN Technologies Utrecht University Netherlands Department of Computer science Harvey Mudd College United States University of Pennsylvania United States University of Wisconsin United States Yahoo Research PricewaterhouseCoopers Center for Advanced Research United States Department of Computer science School of Engineering and Advanced Technology Massey University New Zealand Departent of Computer science Rutgers University United States Department of Computer Science Dortmund University of Technology. Germany ILOG Rotterdam School of Management Erasmus University Netherlands Donald Bren School of Information and Computer Sciences University of California Irvine United States Depatrment of Computer science University of Southern California United States IBM Almaden Research Center United States Department of Computer Information Technology Southern New Hampshire University United States Computer and Information Technology Program College of Technology Purdue University United States Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computer Science and Engineering University of North Texas United States School of Computing DePaul University United States Department of Computer Science McGill University Canada School of Computer Science University of Waterloo Canada Department of Software and Information Systems University of North Carolina Charlotte United States University of New Hampshire United States Microsoft Research Institute for the Study of Learning and Expertise Applied Reactivity Inc. United States NASA Ames Research Center Carnegie Mellon University West

AAAI was pleased to present the AAAI-08 Workshop Program, held Sunday and Monday, July 13-14, in Chicago, Illinois, USA. The program included the following 15 workshops: Advancements in POMDP Solvers;AI Education Workshop Colloquium;Coordination, Organizations, Institutions, and Norms in Agent Systems, Enhanced Messaging;Human Implications of Human-Robot Interaction;intelligent Techniques for Web Personalization and Recommender Systems;Metareasoning: Thinking about Thinking;Multidisciplinary Workshop on Advances in Preference Handling;Search in Artificial Intelligence and Robotics;Spatial and Temporal Reasoning;Trading Agent Design and Analysis;Transfer Learning for Complex Tasks;What Went Wrong and Why: Lessons from AI research and Applications;and Wikipedia and Artificial Intelligence: An Evolving Synergy. Copyright © 2009, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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3D interval wavelet moments for 3D objects

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Journal of Information and Computational science 2009年第4期6卷 1799-1810页

作者： Cui, Li Li, Ying Li, Hua Laboratory of Mathematics and Complex Systems Ministry of Education School of Mathematical Sciences Beijing Normal University Beijing 100875 China College of Computer Science and Technology Jilin University Changchun 130021 China National Research Center for Intelligent Computing Systems Institute of Computing Technology Chinese Acad. of Sci. Beijing 100080 China Graduate University of Chinese Acad. of Sci. Beijing 100049 China

In this paper, we introduce wavelets on the interval [0, 1] in 3D wavelet moments, which we call 3D interval wavelet moments. Based on these, new descriptors for 3D objects are put forward. They are invariant to translation, rotation and scale, and have the multi-resolution features in the radial direction, which can handle noise to some extent and provide multi-level features to satisfy various requirements. Furthermore the new method is prior to the original 3D wavelet moments on the presentation of the edge of the objects. They have fast Mallat algorithm too. With the Pearson correction in each level, we give a new method to measure the similarity of two objects. © 2009 Binary Information Press.

关键词： Correlation methods

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A general approach for optimizing degree of variability of software components

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Information Technology Journal 2008年第3期7卷 474-481页

作者： Wang, Zhongjie Zhan, Dechen Xu, Xiaofei Research Center of Intelligent Computing for Enterprises and Services School of Computer Science and Technology Harbin Institute of Technology No. 92 West Da Zhi Street Harbin Heilongjiang China

In this research, we put forward a general approach for designing components from multiple domain applications by optimizing degree of variability of components, to reach a global optimization between usefulness and usability and maximize global reusability performance of components. A simplified software component model and its usability metrics are firstly introduced. Then process of variability optimization oriented component design is put forward. Three important issues in this approach, i.e., choosing variability policies (negative or positive), determining degree of variability based on semantics abstraction tree (SAT) partitioning and component structure design by composing multiple dimensions, with some primary solutions, are briefly discussed. © 2008 Asian Network for Scientific Information.

关键词： Global optimization

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Anonymizing Streaming Data for Privacy Protection

Anonymizing Streaming Data for Privacy Protection

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International Conference on Data Engineering

作者： Jianzhong Li Beng Chin Ooi Weiping Wang School of Computer Science and Technology Harbin Institute of Technology Harbin China School of Computing National University of Singapore Singapore ICT CAS National Research Center of Intelligent Computer Systems Beijing China

ISBN: (纸本)9781424418367;1424418364

In many applications, transaction data arrive in the form of high speed data streams. These data contain a lot of information about customers, not just transactions, and thus have to be carefully managed to protect customers' privacy. This paper presents a novel method called SKY (stream K-anon Ymtiy) to continuously facilitate k-anonymity on data streams. Experimental results show that SKY is efficient and effective.

关键词： Data privacy Protection Joining processes Books computer science intelligent systems Application software Wireless sensor networks Engines Telephony

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Reports of the AAAI 2008 Spring Symposia

Reports of the AAAI 2008 Spring Symposia

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作者： Balduccini, Marcello Baral, Chitta Brodaric, Boyan Colton, Simon Fox, Peter Gutelius, David Hinkelman, Knut Horswill, Ian Huberman, Bernardo Hudlicka, Eva Lerman, Kristina Lisetti, Christine McGuinness, Deborah Maher, Mary Lou Musen, Mark A. Sahami, Mehran Sleeman, Derek Thönssen, Barbara Velasquez, Juan Ventura, Dan Eastman Kodak Company Arizona State University Tempe AZ United States Geological Survey of Canada Department of Computing Imperial College London United Kingdom National Center for Atmospheric Research Artificial Intelligence Center SRI International Menlo Park CA United States University of Applied Sciences Zurich Switzerland Department of Computer Science Northwestern University Evanston IL United States Social Computing Lab. Hewlett-Packard Laboratories Psychometric Associates USC Information Sciences Institute University of Southern California Los Angeles CA United States Computer Science Department University of Southern California Los Angeles CA United States School of Computing and Information Sciences Florida International University Miami FL United States Rensselaer Polytechnic Institute Information and Intelligent Systems Division National Science Foundation University of Sydney Sydney NSW Australia Faculty of Architecture Design and Planning University of Sydney Sydney NSW Australia Department of Medicine Biomedica Informatics Research Department Stanford University Stanford CA United States Computer Science Department Stanford University Stanford CA United States Department of Computing Science University of Aberdeen Aberdeen United Kingdom MIT CSAIL Department of Computer Science Brigham Young University Provo UT United States

The Association for the Advancement of Artificial Intelligence (AAAI) was pleased to present the AAAI 2008 Spring Symposium Series, held Wednesday through Friday, March 26-28, 2008, at Stanford University, California. The eight symposia were titled (1) AI Meets Business Rules and Process Management, (2) Architectures for intelligent Theory-Based Agents, (3) Creative intelligent Systems, (4) Emotion, Personality, and Social Behavior, (5) Semantic Scientific Knowledge Integration, (6) Social Information Processing, (7) Symbiotic Relationships between Semantic Web and Knowledge Engineering, (8) Using Al to Motivate Greater Participation in computer science. The goal of the AI Meets Business Rules and Process Management AAAI symposium was to investigate the various approaches and standards to represent business rules, business process management, and the semantic web with respect to expressiveness and reasoning capabilities. The focus of the Architectures ror intelligent Theory-Based Agents AAAI symposium was the definition or architectures for intelligent theory-based agents, comprising languages, knowledge representation methodologies, reasoning algorithms, and control loops. The Creative intelligent Systems symposium included five major discussion sessions and a general poster session (in which all contributing papers were presented). The purpose of this symposium was to explore the synergies between creative cognition and intelligent systems. The goal of the Emotion, Personality, and Social Behavior symposium was to examine fundamental issues in affect and personality in both biological and artificial agents, focusing on the roles of these factors in mediating social behavior. The Semantic Scientific Knowledge Integration symposium brought together the semantic technologies community with the scientific information technology community in an effort to build the general semantic science information community. The Social Information Processing symposium's goal was to

关键词： Knowledge representation

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Privacy protection on sliding window of data streams

Privacy protection on sliding window of data streams

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3rd International Conference on Collaborative computing: networking, Applications and Worksharing, CollaborateCom 2007

作者： Wang, Weiping Li, Jianzhong Ai, Chunyu Li, Yingshu National Research Center for Intelligent Computing Systems Institute of Computing Technology Chinese Academy of Sciences School of Computer Science and Technology Harbin Institute of Technology Department of Computer Science Georgia State University

ISBN: (纸本)1424413176

In many applications, transaction data arrive in the form of high speed data streams. These data contain a lot of information about customers that needs to be carefully managed to protect customers' privacy. In this paper, we consider the problem of preserving customer's privacy on the sliding window of transaction data streams. This problem is challenging because sliding window is updated frequently and rapidly. We propose a novel approach, SWAF (Sliding Window Anonymization Framework), to solve this problem by continuously facilitating kanonymity on the sliding window. Three advantages make SWAF practical: (1) Small processing time for each tuple of data steam. (2) Small memory requirement. (3) Both privacy protection and utility of anonymized sliding window are carefully considered. Theoretical analysis and experimental results show that SWAF is efficient and effective.

关键词： Data privacy

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