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Dynamic data aggregation in wireless sensor networks

Dynamic data aggregation in wireless sensor networks

引用

2007 IEEE 22nd international Symposium on intelligent Control, ISIC 2007

作者： Commuri, S. Tadigotla, V. School of Electrical and Computer Engineering University of Oklahoma Norman OK 73019 United States Xilinx Inc. Longmont CO 80501 United States

ISBN: (纸本)142440441X

Performance improvement in Wireless Sensor Networks (WSNs) through the use of reconfigurable cluster heads is addressed in this paper. The performance of a WSN is limited by the scarce on-board power in each sensor node. Since the sensed data in the WSN is transmitted to a sink from node to node in a multi-hop fashion, elimination of the redundancies in the data and aggregation of the data from multiple sources can improve the throughput and lifetime of the network. This, in practice, is infeasible because the aggregation to be performed depends on the requirements of the end user/application and is either unknown at the time of deployment or changes over time. In this paper, the problem of implementing dynamic data aggregation in WSNs is addressed through the design of reconfigurable cluster heads (RCHs) using Field Programmable Gate Arrays (FPGAs). Our results demonstrate that different data aggregation algorithms can be efficiently implemented on the RCHs in run-time. Such an implementation provides the necessary flexibility demanded by applications, while resulting in significant reduction in the query processing time and the overall power consumption in the network. © 2007 IEEE.

关键词： data acquisition

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Development of unsupervised and supervised learning systems for multilingual text categorization

Development of unsupervised and supervised learning systems ...

引用

22nd international conference on Computers and Their Applications 2007, CATA 2007

作者： Lee, Chung-Hong Yang, Hsin-Chang Dept of Electrical Engineering National Kaohsiung University of Applied Sciences Kaohsiung Taiwan Dept of Information Management National University of Kaohsiung Kaohsiung Taiwan

ISBN: (纸本)9781604237559

Due to the availability of a huge amount of textual data from a variety of sources, users of internationally distributed information networks need tools and methods that enable them to discover, retrieve and categorize relevant information, in whatever language and form it may have been stored. This drives a convergence of numerous interests from diverse research communities focusing on the issues related to multilingual text categorization. In this work we implemented and evaluated the performance of the leading supervised and unsupervised approaches for multilingual text categorization. We selected Support Vector Machines (SVM) and Latent Semantic Indexing (LSI) techniques as representatives of supervised and unsupervised methods for system implementation, respectively. The preliminary results show that our platform models including both supervised and unsupervised learning methods have the potentials for multilingual text categorization. Copyright © 2007 by the international Society for Computers and Their Applications (ISCA).

关键词： Semantics

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The marchitecture: A cognitive architecture for a robot baby

The marchitecture: A cognitive architecture for a robot baby

引用

AAAI-07/IAAI-07 Proceedings: 22nd AAAI conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence conference

作者： Marc Pickett, I. Oates, Tim Cognition Robotics and Learning Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle Baltimore MD 21250

ISBN: (纸本)1577353234

The Marchitecture is a cognitive architecture for autonomous development of representations. The goals of The Marchitecture are domain independence, operating in the absence of knowledge engineering, learning an ontology of parameterized relational concepts, and elegance of design. To this end, The Marchitecture integrates classification, parsing, reasoning, and explanation. The Marchitecture assumes an ample amount of raw data to develop its representations, and it is therefore appropriate for long lived agents. Copyright © 2007, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Cognitive systems

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Fuzzy logic based data association with target/sensor soft constraints

Fuzzy logic based data association with target/sensor soft c...

引用

2007 IEEE 22nd international Symposium on intelligent Control, ISIC 2007

作者： Stubberud, Stephen C. Kramer, Kathleen A. IEEE Rockwell Collins Poway CA 92064 United States Department of Engineering University of San Diego San Diego CA 92110 United States

ISBN: (纸本)142440441X

For the typical case in target association, where both the target tracks and the measurements are described with Gaussian random variables, the standard association uses the chi-squared metric, a weighted inner product of the residual formed by an estimated measurement and the true measurement. There are, however, cases where the measurements are not well described as Gaussian random variables, including when the Gaussian distribution is corrupted by sensor blockage or target constraints. Based upon the proven concept of the chi-squared metric, a straightforward fuzzy-logic based association method was developed to emulate this metric for Gaussian and non-Gaussian measurements. This approach was previously developed for the cases where non-Gaussian measurements and hard constraints were present. In actual operations, soft constraints on sensor performance and target capabilities are often present. This effort develops a penalty-method-based capability into the association scheme to handle operational concerns. © 2007 IEEE.

关键词： Fuzzy logic

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Random scaling of Quasi-Newton BFGS method to improve the O(N 2)-operation approximation of covariance-matrix inverse in Gaussian process

Random scaling of Quasi-Newton BFGS method to improve the O(...

引用

2007 IEEE 22nd international Symposium on intelligent Control, ISIC 2007

作者： Zhang, Yunong Leithead, W.E. Leith, D.J. Department of Electronics and Communication Engineering Sun Yat-Sen University Guangzhou 510275 China Department of Electronic and Electrical Engineering University of Strathclyde Glasgow G1 1QE United Kingdom Hamilton Institute National University of Ireland Maynooth Co. Kildare Ireland

ISBN: (纸本)142440441X

Gaussian process (GP) is a Bayesian nonparametric regression model, showing good performance in various applications. Similar to other computational models, Gaussian process frequently encounters the matrix-inverse problem during its model-tuning procedure. The matrix inversion is generally of O(N 3) operations where N is the matrix dimension. We proposed using the O(N2)-operation quasi-Newton BFGS method to approximate/replace the exact inverse of covariance matrix in the GP context. As inspired during a paper revision, in this paper we show that by using the random-scaling technique, the accuracy and effectiveness of such a BFGS matrix-inverse approximation could be further improved. These random-scaling BFGS techniques could be widely generalized to other machine-learning systems which rely on explicit matrix-inverse. © 2007 IEEE.

关键词： Covariance matrix

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A supervisory control methodology for a new pneumatic cart-seesaw system

A supervisory control methodology for a new pneumatic cart-s...

引用

2007 IEEE 22nd international Symposium on intelligent Control, ISIC 2007

作者： Lin, J. Zhan, J.H. Chang, Julian Department of Mechanical Engineering Ching Yun University 229 Chien-Hsin Rd. Jung-Li 320 Taiwan

ISBN: (纸本)142440441X

This paper describes mechanical configuration and control environment for a new cart-seesaw system. The system consists of a cart, which slides on the pneumatic rodless cylinder. The rodless cylinder is a double-acting one with carrier bracket on which a cart has been pinion mechanism to tracks. The task of the cart-seesaw system is to bring the cart to from any initial position to a desired position on the seesaw by applying an appropriate force to the cart and thereby changing the angle of the seesaw. The position of a cart represents the first degree of freedom, which is activated by a pneumatic proportional valve and the angle of the seesaw represents the second degree of freedom that is not actuated. Consequently, the proposed new pneumatic cart-seesaw system is simple to construct and direct to operate in different scenarios of performance. A state feedback controller is applied for stabilization of the equilibrium point of the system. Moreover, this work adds a supervisory controller that takes control action in extreme situations. Thus, the test results show excellent characteristics in control performance. Finally, the proposed product in this research can be extensively application in SAMS and pneumatic control for control laboratory. © 2007 IEEE.

关键词： Supervised learning

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Decentralized Å3ström-Wittenmark self-tuning regulator of a multi-agent uncertain coupled ARMAX system

Decentralized Å3ström-Wittenmark self-tuning regulator of ...

引用

2007 IEEE 22nd international Symposium on intelligent Control, ISIC 2007

作者： Ma, Hongbin Lum, Kai-Yew Ge, S.S. Temasek Laboratories National University of Singapore Singapore 117508 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore

ISBN: (纸本)142440441X

Adaptive control for a multi-agent uncertain dynamical system is studied in this paper. The system studied has the following characteristics: (i) there are many agents in this system and the state of each agent dynamically evolves with time;(ii) for each agent, its state evolves like an ARMAX model with unknown coefficients;(iii) each agent is locally intervened by neighborhood agents with unknown linear reactions;(iv) each agent can only use its history information and local information on its neighborhood agents to design its control law aimed at achieving its own local goal, i.e. tracking a local signal sequence. In this paper, the Åström-Wittenmark self-tuning regulator, which is a special case (with known high-frequency gain) of extended least squares (ELS) algorithm, is adopted by each agent to estimate the local unknown parameters (including internal parameters and coupling coefficients) and control the local states based on the "certainty equivalence" principle. For the decentralized Åström-Wittenmark self-tuning regulator discussed here, its stability and optimality are established rigorously in this paper. Simulation studies demonstrate the effectiveness of the local ELS learning and control algorithm. © 2007 IEEE.

关键词： Uncertain systems

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Improvements in SCADA and DCS systems security

Improvements in SCADA and DCS systems security

引用

22nd international conference on Computers and Their Applications 2007, CATA 2007

作者： Graham, James H. Mostafa, Mostafa S. Arazi, Benjamin Tantawy, Ashraf Hieb, Jeffrey Ralston, Patricia Patel, Sandip C. Computer Engineering and Computer Science Dept. Intelligent Systems Research Laboratory University of Louisville Louisville KY 40292 United States Dept. of Computer Science Western Kentucky University Bowling Green KY United States Dept. of Chemical Engineering University of Louisville Louisville KY United States Dept. of Information Science and Systems Morgan State University Baltimore MD United States

ISBN: (纸本)9781604237559

Supervisory control and data acquisition (SCADA) systems monitor, regulate, gather information from, and control the computer field units that control much of our industrial and utility infrastructure. Distributed Control Systems (DCS) is a broader term used in the chemical and process industries, and includes systems implemented with SCADA networks as their backbone. Security was not a high priority in the design of much of this equipment because it used obscure protocols and relatively secure, dedicated, communications links. This has all changed in recent years as many SCADA and DCS systems are now accessible, either deliberately or through system design flaws, through the public Internet. In this paper a new approach to the issue of intrusion detection and prevention in DCS and SCADA has been developed. Here, the cyber vulnerabilities specifically applicable to the control of chemical plants are directly addressed, rather than adopting in this environment generic solutions. Abnormal behavior signatures are directly associated with adaptive traffic matrix deviations. Spatial and temporal correlation techniques are then applied to enhance intrusion detection. This paper also discusses an experimental test-bed for generating attack data for a wide variety of SCADA and DCS configurations. Copyright © 2007 by the international Society for Computers and Their Applications (ISCA).

关键词： Intrusion detection

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learning large scale common sense models of everyday life

Learning large scale common sense models of everyday life

引用

AAAI-07/IAAI-07 Proceedings: 22nd AAAI conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence conference

作者： Pentney, William Philipose, Matthai Bilmes, Jeff Kautz, Henry Department of Computer Science and Engineering University of Washington Intel Research Seattle Department of Electrical Engineering University of Washington Department of Computer Science University of Rochester

ISBN: (纸本)1577353234

Recent work has shown promise in using large, publicly available, hand-contribuied commonsense databases as joint models that can be used to infer human state from day-to-day sensor data. The parameters of these models are mined from the web. We show in this paper that learning these parameters using sensor data (with the mined parameters as priors) can improve performance of the models significantly. The primary challenge in learning is scale, Since the model comprises roughly 50,000 irregularly connected nodes in each time slice, it is intractable either to completely label observed data manually or to compute the expected likelihood of even a single time slice. We show how to solve the resulting semisupervised learning problem by combining a variety of conventional approximation techniques and a novel technique for simplifying the model called context-based pruning. We show empirically that the learned model is substantially better at interpreting sensor data and an detailed analysis of how various techniques contribute to the performance. Copyright ©2007, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： database systems

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Transferring Naive Bayes classifiers for text classification

Transferring Naive Bayes classifiers for text classification

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AAAI-07/IAAI-07 Proceedings: 22nd AAAI conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence conference

作者： Dai, Wenyuan Xue, Gui-Rong Yang, Qiang Yu, Yong Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)1577353234

A basic assumption in traditional machine learning is that the training and test data distributions should be identical. This assumption may not hold in many situations in practice, but we may be forced to rely on a different-distribution data to learn a prediction model. For example, this may be the case when it is expensive to label the data in a domain of interest, although in a related but different domain there may be plenty of labeled data available. In this paper, we propose a novel transfer-learning algorithm for text classification based on an EM-based Naive Bayes classifiers. Our solution is to first estimate the initial probabilities under a distribution D of one labeled data set, and then use an EM algorithm to revise the model for a different distribution Du of the test data which are unlabeled. We show that our algorithm is very effective in several different pairs of domains, where the distances between the different distributions are measured using the Kullback-Leibler (KL) divergence. Moreover, KL-divergence is used to decide the trade-off parameters in our algorithm. In the experiment, our algorithm outperforms the traditional supervised and semi-supervised learning algorithms when the distributions of the training and test sets are increasingly different. Copyright ©2007, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Supervised learning

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