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IEEE International Conference on Networks

作者： Mukaddim Pathan Rajkumar Buyya Grid Computing and Distributed Systems (GRIDS) Laboratory Department of Computer Science and Software Engineering University of Melbourne Parkville VIC Australia

A content delivery network (CDN) is expected to provide high performance content delivery, which requires scalable infrastructure to achieve global coverage. The provision of such infrastructure may form a substantial entry barrier for new CDN providers, as well as affecting commercial viability of the existing ones. Peering of CDNs can be a way to allow dynamic infrastructural cooperation between CDNs in a scalable manner, in order to mitigate the impact of flash crowds and to achieve better overall service times. In this paper, we present a quality of service (QoS)-driven model to evaluate the user perceived performance of CDN peering relationships. In this model, an overloaded CDN redirects a fraction of its incoming requests to peered CDNs and thereby can avoid the impact of flash crowds. The model-based approach also assists in making concrete QoS guarantee for a given CDN. Our approach endeavors to achieve scalability for a CDN in a user transparent manner.

关键词： Quality of service Web server Costs Delay Analytical models Grid computing Laboratories computer science software engineering Concrete

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Multi-objective optimization using genetic algorithm for gene selection from microarray data

Multi-objective optimization using genetic algorithm for gen...

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International Conference on computer and Communication engineering, ICCCE

作者： Mohd Saberi Mohamad Sigeru Omatu Safaai Deris Michifumi Yoshioka Department of Software Engineering Universiti Teknologi Malaysia Skudai Johore Malaysia Department of Computer Science and Intelligent Systems Osaka Prefecture University Sakai Osaka Japan

Microarray technology has been increasingly used in cancer research because of its potential for measuring expression levels of thousands of genes simultaneously in tissue samples. It is used to collect the information from tissue samples regarding gene expression differences that could be useful for cancer classification. However, this classification task faces many challenges due to availability of a smaller number of samples compared to the huge number of genes, and many of the genes are not relevant to the classification. It has been shown that selecting a small subset of genes can lead to an improved accuracy of the classification. Hence, this paper proposes a solution to the problem of gene selection by using a multi-objective approach in genetic algorithm. This approach is experimented on two microarray data sets such as lung cancer and mixed-lineage leukemia cancer. It obtains encouraging result on those data sets as compared with an approach that uses single objective approach.

关键词： Genetic algorithms Cancer Space technology Gene expression Filters Data engineering Genetic engineering computer science intelligent systems software engineering

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CARBON REDUCTION POTENTIAL WITH intelligent CONTROL OF POWER systems

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IFAC Proceedings Volumes 2008年第2期41卷 13952-13957页

作者： Ganesh K. Venayagamoorthy Gabriele Braband Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO 65409 USA Simmons & Simmons Dusseldorf Germany

Climate change caused by anthropogenic greenhouse gas (GHG) emissions such as carbon dioxide (CO 2 ) is now widely accepted as a real condition that has potentially serious consequences for human society and industries need to factor this into their strategic plans. One salient planning assumption is that energy - essential for every activity - will become more expensive relative to other inputs. Economic growth does not have to be linked to an increase of GHG emissions and can be attained in addition to the usage of renewable energy sources by using energy efficiency technologies for power system generation, transmission, and distribution. The development of intelligent energy-efficient control technologies will both soften negative effects of the climate change on the economy and enhance energy security. This paper outlines the significant carbon reduction potential with intelligent control and optimization techniques applied to power system generation and transmission systems with and without wind farms.

关键词： intelligent control Economics Emissions Optimization Power systems

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Real-Time Collaborative Routing Algorithm for Wireless Sensor Network Longevity

Real-Time Collaborative Routing Algorithm for Wireless Senso...

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IEEE International Symposium on intelligent Control (ISIC)

作者： Shishir Bashyal Ganesh Kumar Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department ofElectrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

ISBN: (纸本)9781424422241

Wireless sensor networks are being used in different scenarios including safety critical applications that require real-time communication framework such that the events detected by sensor nodes reach the base station within a limited timeframe. The ad-hoc nature of the sensor network makes it impossible to develop a static communication scheme that works well throughout the network lifetime. The network needs to be capable of adapting to the changes due to node failures and traffic congestions. This paper proposes an ant inspired dynamic routing algorithm in which individual sensor nodes collaborate with each other to discover a route that optimizes the network longevity while maintaining network delays to an acceptable level. Fuzzy logic is used to develop ant-like ability in sensor nodes to determine the suitability of the node to act as the cluster head. Using this algorithm, the nodes that are in the energy-rich region and have low end-to-end delay are more likely to be the cluster heads and thus the overall route offers lower communication delays and longer network life in terms of effective performance. As the algorithm relies on local collaboration for the route formation, the algorithm is highly scalable. Better end-to-end delay is achieved in simulation using this algorithm.

关键词： Availability Wireless sensor networks Delay Batteries Clustering algorithms Robot sensing systems Collaboration

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State feedback controller design of networked control systems with time delay and packet dropout

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IFAC Proceedings Volumes 2008年第2期41卷 6626-6631页

作者： Hongbo Li Zengqi Sun Mo-Yuen Chow Badong Chen Department of Computer Science and Technology State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing China 100084 Department of Electrical and Computer Engineering North Carolina State University Raleigh NC 27695-7911 USA

In this paper, the stability analysis and synthesis problems for networked control systems (NCSs) are investigated. By introducing the lifting technique into NCSs, a novel discrete-time switch model is proposed with the consideration of time delay and packet dropout during the transmission of packets. It describes NCSs as a switch system, and therefore enables us to apply the theory from switch systems to study NCSs in discrete-time domain. In terms of the given model, we give sufficient conditions for the existence of state feedback controller such that the closed-loop NCSs are asymptotically stable. Based on the obtained stability conditions, a homotopy-based iterative LMI algorithm is developed to get the state feedback gain. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

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A simple state feedback controller design method of networked control systems with time delay and packet dropout

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IFAC Proceedings Volumes 2008年第2期41卷 12575-12580页

This paper presents a simple yet effective method to design state feedback controller for networked control systems (NCSs). By introducing the lifting technique into NCSs and by considering the balance between effectiveness and simplicity, a novel discrete-time switch model is proposed with the consideration of time delay and packet dropout during the transmission of packets. In terms of the given model, we give sufficient conditions for the existence of state feedback controller such that the closed-loop NCSs are asymptotically stable. Based on the obtained stability conditions, a homotopy-based iterative LMI algorithm is developed to get the state feedback gain. Simulation and experimental results are given to demonstrate the effectiveness of the proposed approaches.

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The sliced Gaussian mixture filter for efficient nonlinear estimation

The sliced Gaussian mixture filter for efficient nonlinear e...

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International Conference on Information Fusion

作者： Vesa Klumpp Felix Sawo Uwe D. Hanebeck Dietrich Franken Intelligent Sensor-Actuator-Systems Laboratory Institute of Computer Science and Engineering Universität Karlsruhe Germany Data Fusion Algorithms and Software EADS Deutschland GmbH Ulm Germany

This paper addresses the efficient state estimation for mixed linear/nonlinear dynamic systems with noisy measurements. Based on a novel density representation - sliced Gaussian mixture density - the decomposition into a (conditionally) linear and nonlinear estimation problem is derived. The systematic approximation procedure minimizing a certain distance measure allows the derivation of (close to) optimal and deterministic estimation results. This leads to high-quality representations of the measurement-conditioned density of the states and, hence, to an overall more efficient estimation process. The performance of the proposed estimator is compared to state-of-the-art estimators, like the well-known marginalized particle filter.

关键词： Approximation methods Estimation Particle filters Function approximation Particle measurements Atmospheric measurements Nonlinear dynamical systems

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N-Most Interesting Closed Itemset Mining

N-Most Interesting Closed Itemset Mining

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International Conference on Convergence Information Technology

作者： Panida Songram Veera Boonjing Department of Mathematics and Computer Science Faculty of Science King Mongkuts Institute of Technology Ladkrabang Software Systems Engineering Laboratory Bangkok Thailand Department of Computer Science Faculty of Informatics Mahasarakham University Mahasarakham Thailand

In this paper, we propose an efficient algorithm, NCLOSED, for mining the N k-closed itemsets with the highest supports for 1 up to a certain k max value. The algorithm adopts best-first search strategy to generate closed itemsets with highest remaining supports. It does not keep closed itemsets mined in main memory to ensure that they are really closed. This is because this algorithm can directly generate closed itemsets. Moreover, duplicated closed itemsets are detected and discarded from this algorithm.

关键词： Itemsets Data mining computer science Information technology software systems systems engineering and theory Laboratories Mathematics Informatics software algorithms

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A low-cost pedestrian-detection system with a single optical camera

A low-cost pedestrian-detection system with a single optical...

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作者： Cao, Xian-Bin Qiao, Hong Keane, John IEEE Department of Computer Science and Technology University of Science and Technology of China Hefei 230026 China Anhui Province Key Laboratory of Software in Computing and Communication Hefei 230026 China Laboratory of Complex Systems and Intelligent Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China School of Informatics University of Manchester M60 1QD Manchester United Kingdom University of Manchester M13 9PL Manchester United Kingdom

The ultimate purpose of a pedestrian-detection system (PDS) is to reduce pedestrian-vehicle-related injury. Most such systems tend to adopt expensive sensors, such as infrared devices, in expectation of better performance. In comparison, a low-cost optical-camera-based system has much potential practical value, including a greater detection range, and can easily be trained to detect other objects. However, such low-cost systems are difficult to design (e.g., little original information can be collected, and the scene is very complex). To address these problems, an effective and reliable classifier is needed. The classifier should have a proper structure, its features need to be well selected, and a large number of high-quality samples are necessary for training. In this paper, we present a low-cost PDS which only uses a single optical camera. We design a cascade classifier to achieve an effective and reliable detection. First, our system scans two sequential frames at each zoom scale with a sliding window. Second, with each window, both appearance and motion features are extracted. A well-trained cascade classifier, combining statistical learning with a decomposed support-vector-machine classifier, then determines whether the window contains a human body. At the same time, to provide as much information as possible about the pedestrian, a small-scale weighted template tree trained by a coevolutionary algorithm is adopted to identify each pedestrian's direction, and the distance of each from the vehicle is also provided using an estimation algorithm. During the training procedure, we select key features by using the AdaBoost algorithm and a large number of high-quality samples. Experimental results demonstrate that the system is suitable for pedestrian detection in city traffic: The detection speed is more than 10 ft/s, the detection rate reaches 80%, and the false positive rate is no more than 0.3‰. © 2008 IEEE.

关键词： Pedestrian safety

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Network-centric localization in MANETs based on particle swarm optimization

Network-centric localization in MANETs based on particle swa...

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IEEE Swarm Intelligence Symposium, SIS

作者： Raghavendra V. Kulkarni Ganesh K. Venayagamoorthy Ann Miller Cihan H. Dagli Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA Department of Systems Engineering and Engineering Management Missouri University of Science and Technology Rolla MO USA

There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes need to locate a target or surround it. Severe resource constraints in MANETs call for energy efficient target localization and collaborative navigation. Centralized control of MANET nodes is not an attractive solution due to its high network utilization that can result in congestions and delays. In nature, many colonies of biological species (such as a flock of birds) can achieve effective collaborative navigation without any centralized control. Particle swarm optimization (PSO), a popular swarm intelligence approach that models social dynamics of a biological swarm is proposed in this paper for network-centric target localization in MANETs that are enhanced by mobile robots. Simulation study of two application scenarios is conducted. While one scenario focuses on quick target localization, the other aims at convergence of MANET nodes around the target. Reduction of swarm size during PSO search is proposed for accelerated convergence. The results of the study show that the proposed algorithm is effective in network-centric collaborative navigation. Emergence of converging behavior of MANET nodes is observed.

关键词： Particle swarm optimization Mobile ad hoc networks Collaboration Navigation Centralized control Biological system modeling Convergence Energy efficiency Birds Mobile robots

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