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IEEE Conference on Innovative Technologies in Intelligent systems and Industrial Applications (CITISIA)

作者： Mohammad Reza H. Fatemi Hasan F. Ates Rosli Salleh Department of Computer System & Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Electronics Engineering Isik University Istanbul Turkey

Bit-serial architectures offer a number of attractive features over their bit-parallel counterparts such as smaller area cost, lower density interconnection, a reduced number of pins, higher clock frequency, simpler routing and etc. These attractive features make them suitable for using in VLSI design and reduce overall production cost. In this paper, we propose the first least significant bit (LSB) bit-serial sum of absolute difference (SAD) hardware accelerator for integer variable block size motion estimation (VBSME) of H.264. This hardware accelerator is based on a previous state-of-art bit-parallel architecture namely propagate partial SAD. In order to reduce area cost and improve throughput, pixel truncation technique is adopted. Due to the bit-serial pipeline architecture and using small processing elements, our architecture works at much higher clock frequency (at least 4 times) and reduces area cost about 32% compared with its bit-parallel counterpart. The proposed hardware accelerator can be used in different disciplines from low bit rate to high bit rate by making a tradeoff between the degree of parallelism or using fast algorithm or a combination of both.

关键词： Motion estimation Costs Hardware Clocks Frequency Bit rate Pins Routing Very large scale integration Production

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H∞ filtering convergence and it's application to SLAM

H∞ filtering convergence and it's application to SLAM

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SICE Annual Conference

作者： Hamzah Ahmad Toru Namerikawa Division of Electrical Engineering and Computer Science Kanazawa University Kanazawa Ishikawa Japan Department of System Design Engineering Keio University Yokohama Japan

KF-SLAM (Kalman filter-SLAM) have been used as a popular solution by researchers in many SLAM application. Nevertheless, it shortcomings of assumption for Gaussian noise limited its efficiency and demand researcher to consider better filter and algorithm to achieve a promising result of estimation. In this paper, we proposed one of its family, the H infin filter-based SLAM to determine its competency for SLAM problem. Unlike Kalman filter, H infin filter able to work in an unknown statistical noise behavior and thus more robust. It rely on a guess that the noise is in bounded energy and does not require a priori knowledge about the system. Therefore, we proposed the H infin filter as other available technique to infer the location for both robot and landmarks while simultaneously building the map. From the results of simulation, H infin filter produces better outcome than the Kalman filter especially in the linear case estimation. As a result, H infin filter may provides another available estimation methods with the capability to ensure and improve estimation for the robotic mapping problem especially in SLAM.

关键词： Simultaneous localization and mapping Filters Application software Robots Convergence Electronic mail Gaussian noise Noise robustness Space exploration Performance analysis

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Optimal path planning in the workspace for articulated robots using mixed integer programming

Optimal path planning in the workspace for articulated robot...

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2009 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Hao Ding Mingxiang Zhou Olaf Stursberg Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Germany Institute of Automatic Control Engineering Munchen Germany

This paper considers the task of path planning for articulated robots such that the end effector is driven optimally between two points in the workspace while collision with dynamic obstacles is avoided. Compared to path planning in the configuration space, approaches in the workspace save the computationally expensive step of mapping obstacles from the workspace into the configuration space. The method presented here builds on a problem formulation as a mixed-integer program considering time-varying constraints resulting from moving obstacles, as well as state and input constraints depending on the region of the work space. The method is applied to a two-link robot with static and moving obstacles and is evaluated for different situations.

关键词： Path planning Linear programming Orbital robotics Intelligent robots Dynamic programming Trajectory Collision avoidance Motion planning Robotics and automation Automatic control

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GIMC structure based Anti-Windup control considering L2 performance

GIMC structure based Anti-Windup control considering L2 perf...

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IEEE Conference on Control Technology and Applications (CCTA)

作者： Yusuke Nakashima Toru Namerikawa Division of Electrical Engineering and Computer Science Kanazawa University Kakuma Kanagawa Japan Department of System Design Engineering Keio University Yokohama Japan

This paper deals with GIMC (generalized internal model control) structure based anti-windup (AW) control system design. First, we setup a L 2 performance criterion based on GIMC structure for anti-windup control problems. The design problem is formulated as an optimization problem with a parameter Q. Then we calculate the optimization problem and find an optimal Q. Finally, the effectiveness of proposed method is shown by experimental results for a magnetic suspension system.

关键词： Control systems Design optimization Design methodology Control system synthesis Robust control Robust stability Magnetic levitation Feedback control Observers Processor scheduling

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Improving the generalization performance of RBF neural networks using a linear regression technique

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Expert systems with Applications 2009年第10期36卷 12049-12053页

作者： Lin, C.L. Wang, J.F. Chen, C.Y. Chen, C.W. Yen, C.W. Department of Mechanical and Electro-Mechanical Engineering National Sun Yat-Sen University Kaohsiung 80441 Taiwan Department of Management Information System Yung-Ta Institute of Technology and Commerce 316 Jong Shan Rd. Lin Luoh Pingtung 90941 Taiwan Department of Logistics Management Shu-Te University Kaohsiung 82445 Taiwan Department of Computer Science National Pingtung University of Education No. 4-18 Ming Shen Rd Pingtung 90003 Taiwan

In this paper we present a method for improving the generalization performance of a radial basis function (RBF) neural network. The method uses a statistical linear regression technique which is based on the orthogonal least squares (OLS) algorithm. We first discuss a modified way to determine the center and width of the hidden layer neurons. Then, substituting a QR algorithm for the traditional Gram-Schmidt algorithm, we find the connected weight of the hidden layer neurons. Cross-validation is utilized to determine the stop training criterion. The generalization performance of the network is further improved using a bootstrap technique. Finally, the solution method is used to solve a simulation and a real problem. The results demonstrate the improved generalization performance of our algorithm over the existing methods. © 2009.

关键词： Radial basis function networks

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Threats Identification in Healthcare Information systems using Genetic Algorithm and Coz Regression

Threats Identification in Healthcare Information Systems usi...

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The Fifth International Conference on Information Assurance and Security(第五届信息保障与安全国际会议)

作者： Rabiah Ahmad Ganthan Narayana Samy Nuzulha Khilwani Ibrahim Peter A.Bath Zuraini Ismail Centre for Advanced Software Engineering (CASE) Faculty of Computer Science and Information Systems Department of Computer Systems and Communications Faculty of Computer Science and Information System Department of Information Studies University of Sheffield UK Department of Science College of Science and Technology Universiti Teknologi Malaysia (UTM) Malaysia

ISBN: (纸本)9781424451012

Threats to information security for healthcare information system increased tremendously. There are various factors contribute to information security threats, many researchers focused only to certain factors which interest them (e.g., virus attack). Certain factors which may be important remain unexplored. In addition, lack of tools and technologies directed to limited number of threats traced in healthcare system. Thus it introduces bias in threat analysis. This study explored the use of biological computational termed Genetic Algorithm (GAs) combined with Cox regression (CoRGA) in identifying a potential threat for healthcare system. The results show that variable described “misused of e-mail” is the major information security threats for healthcare system. Results were compared with manual analysis using the same data, and it is shows that GAs not just introducing new threats for healthcare system but it was similar with others threats proposed by previous researches.

关键词： Healthcare Information systems (HIS) Risk Analysis Threats Information Security Genetic Algorithm and Coz Regression

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An ontological conceptualization approach for awareness in domain-independent design groupware

An ontological conceptualization approach for awareness in d...

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International Conference on computer Supported Cooperative Work in Design

作者： Jesus Gallardo Ana I. Molina Crescencio Bravo Miguel A. Redondo Cesar A. Collazos School of Computer Science and Engineering Universidad de Castilla La Mancha Spain System Department Universidad del Cauca Colombia

ISBN: (纸本)9781424435340

One of the most important aspects of groupware systems is the concept of awareness, which refers to the perception and knowledge of the group and its activities. This paper extends a previously developed ontology-based conceptualization for the development of user interfaces in groupware systems that support awareness. Specifically, we are interested in domain-independent design groupware. We propose an awareness ontology that conceptualizes the most important aspects of awareness in such systems and can be used to automatize the development of their user interfaces. In order to validate the usefulness of this ontology, we have related the concepts included in our ontology to the awareness dimensions exposed in a well-known awareness framework.

关键词： Ontologies Collaborative software Collaborative work User interfaces Collaboration Proposals computer science Design engineering Knowledge engineering Protocols

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Receiver Centric Fuzzy Logic Congestion Control for TCP Throughput Improvement over Wireless Networks

Receiver Centric Fuzzy Logic Congestion Control for TCP Thro...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Kai Shi Yantai Shu Qingfeng Song Department of Computer Science Tianjin University TJU Tianjin China Institute of System Engineering Tianjin University TJU Tianjin China

In this paper, we propose a novel fuzzy logic congestion control mechanism to improve throughput performance of transmission control protocol (TCP) in wireless high-bandwidth delay networks. It is based on a receiver centric method of which the available bandwidth is measured at the receiver. The available bandwidth utilization serves as an incipient network congestion indicator, which acts as one input to a fuzzy logic controller to help represent the network congestion level, then the congestion control mechanism adjusts the TCP congestion window size based on the output congestion level of the fuzzy logic controller, the trend of available bandwidth variation and the packet loss information. The advantages of our mechanism are accurate bandwidth estimation and congestion prediction, and improved bandwidth utilization. Simulation results in various scenarios validate the effectiveness of our mechanism.

关键词： Fuzzy logic Throughput Wireless networks Bandwidth Delay Control systems Size control Protocols Fuzzy systems Switches

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Metric for strategy implementation: Measuring and monitoring the performance

Metric for strategy implementation: Measuring and monitoring...

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IEEE Symposium on Industrial Electronics & Applications (ISIEA)

作者： Okfalisa Rose Alinda Alias Naomie Salim Kuan Yew Wong Computer Science and Information System Department Universiti Teknologi Malaysia Skudai Malaysia Mechanical Engineering Department Universiti Teknologi Malaysia Skudai Malaysia

The strategy formulation in organizations will be useless unless it is well implemented. Measuring and monitoring the performance of strategy implementation are one way solution to identify the success achievement of organizational objectives. To measure and monitor the implementation process based on document analysis and annual report are not enough anymore. Therefore, this paper studies the performance of strategy implementation by investigating the exploration of tangible and intangible knowledge within the organization. The stakeholders' knowledge process while making the quality of decision making is discussed. The complexity of problems and knowledge, the dynamic changes and the environment uncertainty in decision making will be considered as indicators in knowledge management metrics development. To identify the knowledge process in strategy implementation, case study is conducted at Universiti Teknologi Malaysia (UTM). From these interviews, the conceptual metrics are developed. Hence, the strategy implementation can be measured and monitored.

关键词： Control systems Knowledge management Disaster management computerized monitoring Decision making Total quality management Industrial electronics Application software computer science Information systems

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A three-dimensional self-organizing neural network architecture for three-dimensional object extraction from a noisy perspective

A three-dimensional self-organizing neural network architect...

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International Conference on Advanced Computing, ICAC

作者： Kousik Dasgupta Siddhartha Bhattacharyya Paramartha Dutta Department of Computer Science and Engineering Kalyani Government Engineering College Kalyani West Bengal India Department of Computer Science Information Technology Golapbag (North) University Institute of Technology University of Burdwan Burdwan India Department of Computer and System Sciences Visva Bharati University Santiniketan India

Processing of three-dimensional image data for quality enhancement, segmentation and analysis is a challenging proposition due to the enormity of the underlying data content as well due to the inadequacy of data description standards. Extraction of objects from 3-dimensional image information is no exception. In this article, a novel three-dimensional neural network architecture is presented for faithful extraction of 3-dimensional objects from a noisy perspective. The proposed network architecture operates in a self-supervised mode assisted by fuzzy measures. Results of application of the proposed architecture are demonstrated on several synthetic and real life three-dimensional binary voxelized images. The efficacy of the architecture in different types of noises indicates encouraging avenues.

关键词： Neural networks Data mining Image processing Image analysis Solid modeling Data visualization computer architecture Graphics computer science Data engineering

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