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IEEE International Conference on Multimedia and Expo (ICME)

作者： Narayanan C. Krishnan Gaurav N. Pradhan Sethuraman Panchanathan Center of Cognitive Ubiquitous Computing Department of Computer Science and Engineering Arizona State University Tempe AZ USA

Processing of accelerometer data for recognizing short duration hand movements is a challenging problem. This paper focuses on characterization of acceleration data corresponding to hand movements (lift to mouth, scoop, stir, pour, unscrew cap) using aggregate statistical features and histograms computed from raw acceleration and derivative of the acceleration data. Data collected from an accelerometer placed on the wrist of subjects was used to perform the analysis. Supplementing the statistical features with raw acceleration histograms had a very marginal effect on the classification performance. However, the addition of derivative histograms resulted in a considerable improvement in the classification accuracy by nearly 8%. The effect of bin size of the derivative histograms was also conducted. It was observed that having a small number of bins decreased the classification accuracy by 3%. We thus show that adding features that capture the distribution of the changes in the acceleration data improve the classification performance.

关键词： Accelerometers Acceleration Histograms Mouth Wrist Feature extraction Wearable sensors Biomedical monitoring Biosensors Sensor phenomena and characterization

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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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LoSeCo: Location-based search computing for pervasive device augmentation

LoSeCo: Location-based search computing for pervasive device...

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IEEE International Conference on Pervasive computing and Communications (PerCom)

作者： Yiqiang Chen Zhuo Sun Juan Qi Derek Hao Hu Qiang Yang Pervasive Computing Center Institute of Computing Technology Chinese Academy and Sciences China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong China

Understanding human intention and performing different activities automatically is one of the key problems in pervasive computing. In this paper, a new location-based search computing framework (LoSeCo) is proposed to allow one's pervasive device to augment search devices. The objective of our problem is to recognize the real-time user goal through goal inference from traditional Wi-Fi localization techniques. We use accelerometer-based tracking to reduce the effort we need to collect Wi-Fi signals and save battery power consumption effectively. With the help of short-range search, the goal recognition module is enhanced, compared to previous ldquolocationonlyrdquo approaches. Therefore, we could augment our mobile devices by automatically analyzing our needs and connecting to corresponding devices. Experimental results on real-world wireless network environments validate the effectiveness of our approach and that even a rough localization accuracy can meet the need of QoS (Quality of Service) in search computing behaviors.

关键词： Pervasive computing Mobile handsets Quality of service Batteries computer networks Cloud computing Humans Energy consumption Printers Motion detection

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Machine learning based online performance prediction for runtime parallelization and task scheduling

Machine learning based online performance prediction for run...

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International Symposium on Performance Analysis of Systems and Software, ISPASS 2009

作者： Li, Jiangtian Ma, Xiaosong Singh, Karan Schulz, Martin De Supinski, Bronis McKee, Sally A. Dept. of Computer Science North Carolina State University Raleigh NC 27606 United States Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge TN 37831 United States Computer Systems Laboratory Cornell University Ithaca NY 14850 United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA 94550 United States Department of Computer Science and Engineering Chalmers University of Technology Göteborg Sweden

ISBN: (纸本)9781424441846

With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as well as developing next-generation software requires assistance from hardware, compilers and runtime systems to exploit parallelism transparently within applications. These systems must decompose applications into tasks that can be executed in parallel and then schedule those tasks to minimize load imbalance. However, many systems lack a priori knowledge about the execution time of all tasks to perform effective load balancing with low scheduling overhead. In this paper, we approach this fundamental problem using machine learning techniques first to generate performance models for all tasks and then applying those models to perform automatic performance prediction across program executions. We also extend an existing scheduling algorithm to use generated task cost estimates for online task partitioning and scheduling. We implement the above techniques in the pR framework, which transparently parallelizes scripts in the popular R language, and evaluate their performance and overhead with both a realworld application and a large number of synthetic representative test scripts. Our experimental results show that our proposed approach significantly improves task partitioning and scheduling, with maximum improvements of 21.8%, 40.3% and 22.1% and average improvements of 15.9%, 16.9% and 4.2% for LMM (a real R application) and synthetic test cases with independent and dependent tasks, respectively. © 2009 IEEE.

关键词： Scheduling algorithms

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Incentive framework using Shapley value for BitTorrent-like systems

Incentive framework using Shapley value for BitTorrent-like ...

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International Conference on Information, Communications and Signal Processing

作者： Xiaowei Chen Xiaowen Chu Xiaolei Chang Computer Science Department Hong Kong Baptist University Hong Kong China Computing Center Tsinghua University China

ISBN: (纸本)9781424446568

BitTorrent is the dominating protocol in nearly all regions. Various reputation models and incentive mechanisms are proposed in recent years. However, many of them are designed for general peer-to-peer networks, only a few are designed for BitTorrent even though some models and mechanisms assert that they can be applied to BitTorrent-like systems. In this paper, we propose an incentive framework based on reputation history instead of tit-for-tat in BitTorrent. It is derived from the coalition games concept of Shapley value that will encourage selfish peers who seek to maximize their own profits to converge to Nash equilibrium. We show that this profit sharing framework exhibits several fairness properties that support the argument that this distribution of profit is desirable. Moreover, we improve SepRep reputation model and tailor it to the needs of BitTorrent protocol. In particular, we utilize the tracker of BitTorrent to process global reputation and trust values assisting the local values maintained by each peer.

关键词： Protocols Peer to peer computing computer science Availability History Nash equilibrium Robustness Scalability Monitoring Telecommunication traffic

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Constellation Precoded Beamforming

Constellation Precoded Beamforming

引用

GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

作者： Hong Ju Park Ender Ayanoglu Center of Pervasive Communications and Computing Department of Electrical Engineering and Computer Science University of California Los Angeles Irvine USA

We present and analyze the performance of constellation precoded beamforming. This multi-input multi-output transmission technique is based on the singular value decomposition of a channel matrix. In this work, the beamformer is precoded to improve its diversity performance. It was shown previously that while single beamforming achieves full diversity without channel coding, multiple beamforming results in diversity loss. In this paper, we show that a properly designed constellation precoder makes uncoded multiple beamforming achieve full diversity order. We also show that partially precoded multiple beamforming gets better diversity order than multiple beamforming without constellation precoder if the subchannels to be precoded are properly chosen. We propose several criteria to design the constellation precoder. Simulation results match the analysis, and show that precoded multiple beamforming actually outperforms single beamforming without precoding at the same system data rate while achieving full diversity order.

关键词： Array signal processing MIMO Analytical models Transmitters Singular value decomposition Channel coding Bit error rate Receiving antennas Upper bound Pairwise error probability

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FAXtrac: Fast Extraction of Disk Layout

FAXtrac: Fast Extraction of Disk Layout

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International Conference on Networking, Architecture, and Storage (NAS)

作者： Xiaowen Chu Kai Ouyang Xiaolei Chang Department of Computer Science Hong Kong Baptist University Hong Kong China Computing Center Tsinghua University China

The low-level disk characteristics play a vital role for the I/O performance optimization in disk storage systems. This paper presents FAXtrac, a tool for automatically and efficiently extracting the exact disk layout, i.e., the number of sectors of each disk track. FAXtrac includes three algorithms, namely SptExplore, TrackExplore, and RemoveNoise, to ensure the correctness and speediness of the extraction of disk layout. We tested FAXtrac on a number of different disk models. It took only 75 minutes to extract the detailed disk layout for a 250 GB SATA disk, which shortened the time by two orders of magnitude as compared with an existing solution. We believe that FAXtrac is a valuable tool for the hard disk storage research community.

关键词： Hard disks Disk drives Magnetic heads computer architecture computer science Optimization Testing Internet Algorithm design and analysis Robustness

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Concept Analysis for Class Cohesion

Concept Analysis for Class Cohesion

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(CSMR) European Conference on Software Maintenance and Reengineering

作者： Padmaja Joshi Rushikesh K. Joshi Department of Computer Science and Engineering Center of Development of Advanced Computing Indian Institute of Technology Bombay Mumbai India Department of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai India

A concept lattice based approach for analysis of class cohesion is presented. The approach facilitates rapid identification of less cohesive classes. It also helps identify less cohesive methods, attributes and classes in one go. Further, the approach guides refactorings such as extract class, move method, localize attributes and remove unused *** effectiveness of the technique is demonstrated through examples.

关键词： Lattices Microscopy Software maintenance computer science Data mining Information analysis Unified modeling language Object oriented modeling Bridges Feedback

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A design method of fluency FIR filters with steep cut off - Towards small hardware

IEEJ Transactions on Electronics, Information and Systems

引用

IEEJ Transactions on Electronics, Information and Systems 2009年第3期129卷 406-417+2页

作者： Kawasaki, Shuji Katagishi, Kazuki Toraichi, Kazuo Murakami, Hitomi TARA Center University of Tsukuba 1-1-1 Ten-noudai Tsukuba Ibaraki 305-8577 Japan Academic Computing and Communications Center University of Tsukuba 1-1-1 Ten-noudai Tsukuba Ibaraki 305-8577 Japan Department of Computer and Information Science Seikei University 3-3-1 Kichijoji-Kita Musashino Tokyo 180-8633 Japan Seikei University Japan University of Tsukuba Japan

We propose a new design method of a class of FIR low-pass filters having steep cut-off with small number of taps. This is a significant improvement of our precedent result where desired frequency characteristics are realized by a set of frequency scalings of basic filters and their series connection. Though the method can realize an FIR filter with much smaller number of taps than conventional Remez method, the resulting characteristics can be such that their cut-off edges are not steep due to just the simple series connection of scaled filters. In this paper, we consider the series connection with each module consisting of a function of the basic filters. It turns out that the function can be written as a recursion with the basic filters, called mean operation. The mean operation is performed in such a way that the skirts of the transition region is subtracted recursively one by another to cancel the gradual slope, so that the resulting characteristics become steep. In a design example, the proposed method is compared with conventional ones and is shown to approximate a desired characteristics with smaller number of multiplies. © 2009 The Institute of Electrical Engineers of Japan.

关键词： FIR filters

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Web-Based Variant of the Lesk Approach to Word Sense Disambiguation

Web-Based Variant of the Lesk Approach to Word Sense Disambi...

引用

Mexican International Conference on Artificial Intelligence, MICAI

作者： Miguel Ángel Ríos Gaona Alexander Gelbukh Sivaji Bandyopadhyay Center for Computing Research National Polytechnic Institute Mexicali Mexico Computer Science & Engineering Department Jadavpur University Kolkata India

Word Sense Disambiguation (WSD) is the task of selecting the meaning of a word based on the context in which the word occurs. The principal statistical WSD approaches are supervised and unsupervised learning. The Lesk method is an example of unsupervised disambiguation. We present a measure for sense assignment useful for the simple Lesk algorithm. We use word co-occurrences of the gloss and the context, which is statistical information retrieved from the Web. In the SemCor data our method always gives an answer. On the Senseval 2 data, our variant of the Lesk method outperformed some other Lesk-based methods.

关键词： Artificial intelligence Information retrieval Cities and towns Knowledge acquisition Dictionaries computer science Unsupervised learning Costs Mice Testing

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