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2012 IEEE 2nd International Conference on Cloud Computing and intelligence Systems

作者： Vilen Looga Zhonghong Ou Yang Deng Antti Yl-Jski Data Communications Software Lab Department of Computer Science and EngineeringSchool of ScienceAalto University

Internet of Things (IoT) is increasingly used in a plethora of fields to enable radically new ways for various purposes, ranging from monitoring the environment to enhancing the wellbeing of human life. With the ever-increasing size of such networks, it is fundamental to understand the issues that come with scaling on different networking layers. A cost-efficient approach to examine large-scale networks is to use simulators or emulators to test the infrastructure and its ability to support the desired applications. In this paper, we investigate and compare the currently available simulation/emulation software. We found out that the current solutions are mostly appropriate for small- and medium-scale emulation, however they are not suitable for large-scale testing that reaches millions of node running concurrently. We then propose a large-scale IoT emulator called MAMMotH and present a brief overview of its design. Finally we discuss some of the current issues and future directions, e.g. radio link simulation.

关键词： Internet of Things (IoT) Large-scale emulation Simulation

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Reports of the AAAI 2011 fall symposia

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AI Magazine 2012年第1期33卷 71-78页

作者： Blisard, Sam Carmichael, Ted Ding, Li Finin, Tim Frost, Wende Graesser, Arthur Hadzikadic, Mirsad Kagal, Lalana Kruijff, Geert-Jan M. Langley, Pat Lester, James McGuinness, Deborah L. Mostow, Jack Papadakis, Panagiotis Pirri, Fiora Prasad, Rashmi Stoyanchev, Svetlana Varakantham, Pradeep Interactive Systems Section Naval Research Laboratory Washington DC United States Department of Software and Information Systems University of North Carolina Charlotte United States Qualcomm Inc. United States Department of Computer Science and Electrical Engineering University of Maryland Baltimore County United States Department of Psychology Institute of Intelligent Systems University of Memphis United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Germany Department of Computer Science and Engineering Arizona State University Tempe AZ United States Department of Computer Science North Carolina State University United States Department of Computer Science and Cognitive Science Rensselaer Polytechnic Institute United States School of Computer Science Carnegie Mellon University United States Department of Informatics and Systems University of Sapienza Rome Italy Department of Informatics and Systems ALCOR Lab University of Sapienza Rome Italy Department of Health Informatics and Administration University of Wisconsin-Milwaukee United States Columbia University United States School of Information Systems Singapore Management University Singapore Singapore

The Association for the Advancement of Artificial intelligence was pleased to present the 2011 Fall Symposium Series, held Friday through Sunday, November 4-6, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia are as follows: (1) Advances in Cognitive Systems;(2) Building Representations of Common Ground with Intelligent Agents;(3) Complex Adaptive Systems: Energy, Information, and intelligence;(4) Multiagent Coordination under Uncertainty;(5) Open Government Knowledge: AI Opportunities and Challenges;(6) Question Generation;and (7) Robot-Human Teamwork in Dynamic Adverse Environments. The highlights of each symposium are presented in this report. Copyright © 2012, Association for the Advancement of Artificial intelligence. All rights reserved.

关键词： Intelligent agents

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Practical privacy for value-added applications in vehicular ad hoc networks 5th

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5th International Conference on Internet and Distributed Computing Systems, IDCS 2012

作者： Zhang, Lei Wu, Qianhong Qin, Bo Domingo-Ferrer, Josep Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University Shanghai China UNESCO Chair in Data Privacy Dept. of Comp. Eng. and Maths Universitat Rovira i Virgili TarragonaCatalonia Spain Key Lab. of Aerospace Information Security and Trusted Computing Ministry of Education Wuhan University School of Computer China Department of Maths School of Science Xi’an University of Technology China

ISBN: (纸本)9783642348822

Advances in mobile networking and information processing technologies have triggered vehicular ad hoc networks (VANETs) for traffic safety and value-added applications. Most efforts have been made to address the security concerns while little work has been done to investigate security and privacy for value-added applications in VANETs. To fill this gap, we propose a value-added application, specifically, a security and privacy preserving location-based service (LBS) scheme for VANETs. For each LBS transaction, the scheme provides authentication, integrity and non-repudiation for both the service provider and the user. A user can obtain the service in an anonymous way and hence user privacy is well protected. However, a tracing procedure can be invoked to find malicious users, thereby efficiently preventing users from abusing the anonymity provided by the system. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Location based services

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Large scale report generation in data consolidation environments of banks

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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 5-8页

作者： Qin, Xiongpai Zhou, Xiaoyun Wu, Zhongxin Yang, Hongzhi Wang, Wei Ministry of Education Key Lab of Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China Information School Renmin University of China Beijing 100872 China Computer Science Department Jiangsu Normal University Xuzhou 221116 Jiangsu China Beijing Nantian Software Co. Ltd. Beijing 100085 China

To generate large number of reports in a limited time window, four techniques were proposed, including ROLAP&SQL, Shared Scanning, Hadoop based Solution, and MOLAP&Cube Sharding, an algorithm that performs in memory aggregation was designed for the second solution. The experiment results show that all techniques except ROLAP&SQL can meet the time window constraint, the Hadoop based solution is a promising technique owe to its highly scalability. Considering maturity of the techniques and their performance, we put MOLAP&Cube Sharding into practice while keeping an eye on Hadoop for future adoption.

关键词： Custom report data consolidation Hadoop Large bank MOLAP ROLAP

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Reports of the AAAI 2010 fall symposia

Reports of the AAAI 2010 fall symposia

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作者： Azevedo, Roger Biswas, Gautam Bohus, Dan Carmichael, Ted Finlayson, Mark A. Hadzikadic, Mirsad Havasi, Catherine Horvitz, Eric Kanda, Takayuki Koyejo, Oluwasanmi Lawless, William F. Lenat, Doug Meneguzzi, Felipe Mutlu, Bilge Oh, Jean Pirrone, Roberto Raux, Antoine Sofge, Donald A. Sukthankar, Gita Van Durme, Benjamin Yorke-Smith, Neil Department of Educational and Counseling Psychology McGill University Canada Center for Intelligent Systems Vanderbilt University United States Microsoft Research Redmond United States Department of Software and Information Systems University of North Carolina Charlotte United States Complex Systems Institute United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Media Lab. Massachusetts Institute of Technology United States ATR Intelligent Robotics and Communication Laboratories Kyoto Japan Department of Electrical and Computer Engineering University of Texas Austin United States Department of Mathematics Paine College Augusta GA United States Cycorp Austin TX United States Robotics Institute Carnegie Mellon University United States Department of Computer Sciences University of Wisconsin Madison United States University of Palermo Italy Honda Research Institute United States Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory Washington DC United States Department of Electrical Engineering and Computer Science University of Central Florida United States Department of Computer Science Johns Hopkins University United States American University of Beirut Lebanon SRI International's Artificial Intelligence Center United States

The Association for the Advancement of Artificial intelligence (AAAI) presented the 2010 Fall Symposium Series on November 11-13, 2010. The eight symposia included Cognitive and Metacognitive Educational Systems, Commonsense Knowledge, Complex Adaptive Systems: Resilience, Robustness, and Evolvability, Computational Models of Narrative, Dialog with Robots, Manifold Learning and Its Applications, Proactive Assistant Agents and Quantum Informatics for Cognitive, Social, and Semantic Processes. Cognitive and Metacognitive Educational Systems aimed to provide a comprehensive definition of metacognitive educational systems that is inclusive of the theoretical, architectural, and educational aspects of this field. The AAAI Commonsense Knowledge Fall Symposium had the goal of bringing together the diverse elements of this community whose work benefits from or contributes to the representation of general knowledge about the world. One of the specific goals of Proactive symposium was to gather the researchers from various projects in assistant agents to share their wisdom in retrospect.

关键词： Semantics

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An interactive high-fidelity haptic needle simulator with GPU acceleration

An interactive high-fidelity haptic needle simulator with GP...

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9th ACM SIGGRAPH International Conference on VR Continuum and Its Applications in Industry, VRCAI 2010

作者： Zhang, Ji-Shuai Chen, Hui Wu, Wen Heng, Pheng-Ann Shenzhen Institute of Advanced Integration Technology Chinese Academy of Sciences Chinese Univ. of Hong Kong Shenzhen China Intelligence Engineering Lab. Institute of Software Chinese Academy of Sciences Beijing China Department of Computer and Information Science Faculty of Science and Technology University of Macau China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9781450304597

Needle operation is one of the fundamental operations in many surgeries such as acupuncture, liver biopsy and anesthesia. During such procedure, the haptic perception is especially important for surgeons to manipulate the needles. In this paper, a simulator with realistic visual and haptic interaction for the needle insertion operation is presented. A fast graphics processing unit (GPU) computation for soft tissue deformation is implemented based on Compute Unified Device Architecture (CUDA) architecture. Novel haptic models for different tissues are developed to generate the resultant force. Besides, an interpolating method of haptic frequency is proposed to acquire more satisfied smooth haptic rendering effect. Experimental results show that a high multi-tissue identification rate can be achieved in the needle interactive simulation system with the real-time soft tissue deformation performed even on the large-scale models. Copyright © 2010 by the Association for Computing Machinery, Inc.

关键词： Tissue

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An associative memory system for incremental learning and temporal sequence

An associative memory system for incremental learning and te...

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2010 6th IEEE World Congress on Computational intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

作者： Shen, Furao Yu, Hui Kasai, Wataru Hasegawa, Osamu State Key Laboratory for Novel Software Technology Jiangyin Information Technology Research Institute Nanjing University Nanjing 210093 China Department of Computer Intelligence and Systems Science Tokyo Institute of Technology Yokohama 226-8503 Japan Imaging Science and Engineering Lab. Tokyo Institute of Technology R2-52 4259 Nagatsuda Midori-ku Yokohama 226-8503 Japan

ISBN: (纸本)9781424469178

An associative memory (AM) system is proposed to realize incremental learning and temporal sequence learning. The proposed system is constructed with three layer networks: The input layer inputs key vectors, response vectors, and the associative relation between vectors. The memory layer stores input vectors incrementally to corresponding classes. The associative layer builds associative relations between classes. The proposed method can incrementally learn key vectors and response vectors;store and recall both static information and temporal sequence information;and recall information from incomplete or noise-polluted inputs. Experiments using binary data, real-value data, and temporal sequences show that the proposed method works well. © 2010 IEEE.

关键词： Vectors

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Reports of the AAAI 2010 conference workshops

Reports of the AAAI 2010 conference workshops

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作者： Aha, David W. Boddy, Mark Bulitko, Vadim D'Avila Garcez, Artur S. Doshi, Prashant Edelkamp, Stefan Geib, Christopher Gmytrasiewicz, Piotr Goldman, Robert P. Halevy, Alon Hitzler, Pascal Isbell, Charles Josyula, Darsana Kaelbling, Leslie Pack Kersting, Kristian Kunda, Maithilee Lamb, Luis C. Marthi, Bhaskara McGreggor, Keith Mihalkova, Lilyana Nastase, Vivi Natarajan, Sriraam Provan, Gregory Raja, Anita Ram, Ashwin Riedl, Mark Russell, Stuart Sabharwal, Ashish Smaus, Jan-Georg Sukthankar, Gita Tuyls, Karl Van Der Meyden, Ron Adaptive Systems Section Naval Research Laboratory Washington DC United States Adventium Labs. Minneapolis MN United States Department of Computer Science University of Alberta Canada City University London United Kingdom University of Georgia United States University of Bremen Germany School of Informatics University of Edinburgh United Kingdom University of Illinois Chicago United States Smart Information Flow Technologies LLC Minneapolis MN United States Structured Data Group Google Research United States Department of Computer Science Wright State University Dayton OH United States School of Interactive Computing Georgia Institute of Technology Atlanta GA United States Department of Computer Science Bowie State University United States Department of Computer Science and Engineering Massachusetts Institute of Technology United States Statistical Relational Mining Group Fraunhofer IAIS Germany Department of Computer Science Federal University of Rio Grande Do sul Brazil Willow Garage Inc. CA United States Computer Science Department University of Maryland College Park United States Heidelberg Institute for Theoretical Studies Heidelberg Germany Department of Computer Science University of Wisconsin Madison United States University College Cork Ireland Cork Complex Systems Lab. Ireland Department of Software and Information Systems University of North Carolina Charlotte United States Department of Computer Science and Engineering University of California Berkeley United States Department of Computer Science Cornell University United States Institute for Computational Sustainability United States University of Freiburg Germany School of Electrical Engineering and Computer Science University of Central Florida United States Maastricht University Netherlands University of New South Wales NICTA Australia

The AAAI-10 workshop program was held on July 11-12, 2010, at the Westin Peachtree Plaza in Atlanta, Georgia. The workshop program included 13 workshops covering a wide range of topics in artificial intelligence. There were several presentations on particular formalisms for combining the levels of planning from the perspectives of classical planning, motion planning, POMDPs, search-based planning, and temporal logic-based constraints. Henry Lieberman from Massachusetts Institute of Technology Media laboratory presented work developing a platform for knowledge acquisition and usage from expert users, built upon experience with eliciting information from nonexperts in a collaborative manner. The objective of the AAAI Workshop on Goal-Directed Autonomy (GDA) was to encourage discussion and novel contributions on intelligent agents that can self-select their goals. Jeremy Baxter from QinetiQ focused on user interaction, while Nick Hawes described a goal-directed reasoning framework for controlling a mobile robot.

关键词： Motion planning

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Asymmetric group key agreement

Asymmetric group key agreement

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28th Annual International Conference on the Theory and Applications of Cryptographic Techniques, EUROCRYPT 2009

作者： Qianhong, Wu Yi, Mu Susilo, Willy Bo, Qin Domingo-Ferrer, Josep Universitat Rovira i Virgili Dept. of Comp. Eng. and Maths UNESCO Department of Data Privacy Tarragona Catalonia Spain Key Lab. of Aerospace Information Security and Trusted Computing School of Computer Wuhan University China Centre for Computer and Information Security Research School of Computer Science and Software Engineering University of Wollongong Australia Dept. of Maths School of Science Xi'an University of Technology China

ISBN: (纸本)3642010008

A group key agreement (GKA) protocol allows a set of users to establish a common secret via open networks. Observing that a major goal of GKAs for most applications is to establish a confiDential channel among group members, we revisit the group key agreement definition and distinguish the conventional (symmetric) group key agreement from asymmetric group key agreement (ASGKA) protocols. Instead of a common secret key, only a shared encryption key is negotiated in an ASGKA protocol. This encryption key is accessible to attackers and corresponds to different decryption keys, each of which is only computable by one group member. We propose a generic construction of one-round ASGKAs based on a new primitive referred to as aggregatable signaturebased broadcast (ASBB), in which the public key can be simultaneously used to verify signatures and encrypt messages while any signature can be used to decrypt ciphertexts under this public key. Using bilinear pairings, we realize an efficient ASBB scheme equippe d with useful properties. Following the generic construction, we instantiate a one-round ASGKA protocol tightly reduced to the decision Bilinear Diffie-Hellman Exponentiation (BDHE) assumption in the standard model. © International Association for Cryptologic Research 2009.

关键词： Public key cryptography

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An Anomaly Detection-Based Classification System

An Anomaly Detection-Based Classification System

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Congress on Evolutionary Computation

作者： Haiyu Hou G. Dozier Applied Computational Intelligence Lab Department of Computer Science and Software Engineering Aubum University USA

In this paper, we describe the construction of a classification system based on an anomaly detection system that employs constraint-based detectors, which are generated using a genetic algorithm. The performance of the classification system was evaluated using two benchmark datasets including the Wisconsin breast cancer dataset and the Fisher's iris dataset.

关键词： Detectors Immune system Fault detection Computational intelligence computer science software engineering Breast cancer Iris Training data Target recognition

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