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International Conference on Communication and Computational Intelligence (INCOCCI)

作者： R. Muralidharan C. Chandrasekar Department of Computer Applications KSR College of Engineering Tiruchengode India Department of Computer Science Periyar University Salem India

Feature extraction is the first and foremost activity in object recognition and detection processing. It reduces the amount of data by representing the image in the form of distinctive, representative interest points. This paper deals with the extraction of global features from the pre-processed images. Geometric Moment invariant produces a set of seven normalized moment invariants that are invariant under shifting, scaling and rotation. Geometric Moment invariant is widely used to extract global features for pattern recognition due to its discrimination power and robustness. After the feature extraction is done the dimensionality of the feature is reduced using the concept of Principal Component Analysis. Finally, the reduced feature vector is used for the recognition of object using the Nearest Neighbor.

关键词： Image edge detection Feature extraction Object recognition Pixel Classification algorithms Principal component analysis Pattern recognition

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Automatic facial skin defect detection system

Automatic facial skin defect detection system

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International Conference on Broadband, Wireless Computing, Communication and applications

作者： Chang, Chuan-Yu Li, Shang-Cheng Chung, Pau-Choo Kuo, Jui-Yi Tu, Yung-Chin Dept. of Computer Science and Information Engineering National Yunlin University of Science and Technology Taiwan Department of Electrical Engineering National Cheng Kung University Tainan Taiwan Innovative DigiTech-Enabled Applications and Services Institute Institute for Information Industry Kaohsiung Taiwan Department of Electronic Engineering Kun Shan University Yung Kang Tainan Taiwan

ISBN: (纸本)9780769542362

Skin analysis is one of the most important procedures before medical cosmetology. Most conventional skin analysis systems are semi-automatic. They often require human intervention. In this study, an automatic facial skin defect detection approach is proposed. The system first detects human face in the facial image. Based on the detected face, facial features are extracted to locate regions of interest. Then, a pattern recognition approach is applied to detect facial skin defects, such as spots and wrinkles, in the regions of interest. For a specific kind of defect, a classifier is designed to provide higher performance for recognition. Using few features extracted from the region of interest, the proposed approach can successfully detect the skin defects. Experimental results demonstrate effectiveness of the proposed approach. © 2010 IEEE.

关键词： Defects

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Modelling and simulation of ADaptive buffer management mechanism using nested autoregressive process-based MPEG-encoded traffic model

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International Journal of Modelling and Simulation 2010年第2期30卷 263-271页

作者： Kaushal, S. Sharma, R.K. Department of Computer Science and Engineering University Institute of Engineering and Technology Panjab University Chandigarh India School of Mathematics and Computer Applications Thapar University Patiala India

High speed networks provide real-time variable bit rate (VBR) service with diversified traffic flow characteristics and quality requirements. The VBR traffic has stringent delay and packet loss requirements. The burstiness of the correlated traffic makes dynamic management highly desirable to satisfy the Quality of Service (QoS) requirements. Buffer management in queueing systems plays important role towards effective control of QoS for various types of applications. In this paper, ADaptive Partial Buffer Sharing (ADPBS) scheme for priority queueing system is proposed and analyzed. The input to the queue has been taken using auto-regressive (AR) process of order 2 for MPEG-encoded VBR video traffic. The results of simulations indicate that dynamically controlled threshold in ADPBS contributes in reducing the packet loss of different priority classes as compared with static partial buffer sharing queue and first-in first-out queue based on threshold control parameters and the traffic type.

关键词： Quality of service

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Cluster mining with ant colony optimizer using fuzzy inferences

Cluster mining with ant colony optimizer using fuzzy inferen...

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International Conference on Computing and Networking Technology (ICCNT)

作者： K. Sankar K. Krishnamoorthy Department of Master of Computer Applications KSR College of Engineering Tiruchengode India Department of Computer Science and Engineering SONA College of Technology Salem India

Ant-based techniques are designed to take biological inspirations on the behavior of these social insects. Data clustering techniques are classification algorithms that have a wide range of applications, from Biology to Image processing and Data presentation. Since real life ants do perform clustering and sorting of objects among their many activities, we expect that a study of ant colonies can provide new insights for clustering techniques. The aim of clustering is to separate a set of data points into self-similar groups such that the points that belong to the same group are more similar than the points belonging to different groups. Each group is called a cluster. Data may be clustered using an iterative version of the Fuzzy C means (FCM) algorithm, but the draw back of FCM algorithm is that it is very sensitive to cluster center initialization because the search is based on the hill climbing heuristic. The ant based algorithm provides a relevant partition of data without any knowledge of the initial cluster centers. In the past researchers have used ant based algorithms which are based on stochastic principles coupled with the k-means algorithm. The proposal in this work use the Fuzzy C means algorithm as the deterministic algorithm for ant optimization. The proposed model is used after reformulation and the partitions obtained from the ant based algorithm were better optimized than those from randomly initialized hard C Means. The proposed technique executes the ant fuzzy in parallel for multiple clusters. This would enhance the speed and accuracy of cluster formation for the required system problem.

关键词： Clustering algorithms Partitioning algorithms Optimization Iris Algorithm design and analysis Classification algorithms Sorting

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Fast Fourier-Galerkin methods for first-kind logarithmic-kernel integral equations on open arcs

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science China Mathematics 2010年第1期53卷 1-22页

作者： WANG Bo1,WANG Rui2 & XU YueSheng3,4,1Academy of Mathematics and Systems science,Chinese Academy of sciences,Beijing 100190,China 2School of Information science and engineering,Graduate University of the Chinese Academy of sciences,Beijing 100190,China 3department of Mathematics,Syracuse University,Syracuse,NY 13244,USA 4department of Scientific Computing and computer applications,Sun Yat-sen University,Guangzhou 510275,China 1. Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China2. School of Information Science and Engineering Graduate University of the Chinese Academy of Sciences Beijing 100190 China3. Department of Mathematics Syracuse University Syracuse NY 13244 USA4. Department of Scientific Computing and Computer Applications Sun Yat-sen University Guangzhou 510275 China

We propose a fully discrete fast Fourier-Galerkin method for solving an integral equation of the first kind with a logarithmic kernel on a smooth open arc,which is a reformulation of the Dirichlet problem of the Laplace equation in the *** optimal convergence order and quasi-linear complexity order of the proposed method are established.A precondition is *** this method with an efficient numerical integration algorithm for computing the single-layer potential defined on an open arc,we obtain the solution of the Dirichlet problem on a smooth open arc in the *** examples are presented to confirm the theoretical estimates and to demonstrate the efficiency and accuracy of the proposed method.

关键词： Dirichlet problem open arc singular boundary integral equations Fourier-Galerkin methods logarithmic potentials

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Ant Colony algorithm for routing problem using rule-mining

Ant Colony algorithm for routing problem using rule-mining

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IEEE International Conference on Computational Intelligence and Computing Research

作者： K. Sankar K. Krishnamoorthy Department of Master of Computer Applications KSR College of Engineering Tiruchengode India Department of Computer Science and Engineering KUPPAM Engineering College Kuppam Andhra Pradesh India

The proposed work presented a modified MAX-MIN Ant System (MMAS) algorithm to solve the routing problem, in which known demand are supplied from a store house with parallel routes for new local search. Routing Problem is an optimization problem and solved to nearly optimum by heuristics. The objective of routing issues is to use a fleet of vehicles with specified capacity to serve a number of users with dissimilar demands at minimum cost, without violating the capacity and route length constraints. Many meta-heuristic approaches like Simulated Annealing (SA), Tabu Search (TS) and An Improved Ant Colony System (IACS) algorithm are compared for the performance result analysis. The well-founded theory of fuzzy sets is a special way to model the uncertainty. The rules in a fuzzy model contain a set of propositions, each of which restricts a fuzzy variable to a single fuzzy value by means of the predicate equivalency. That way, each rule covers a single fuzzy region of the fuzzy grid. The proposed system of this thesis extends this structure to provide more general fuzzy rules, covering the input space as much as possible. In order to do this, new predicates are considered and a Max-Min Ant System is proposed to learn such fuzzy rules.

关键词： Routing Heuristic algorithms Classification algorithms Vehicles Ant colony optimization Optimal scheduling

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Hybrid Machine Learning Approach in Data Mining

Hybrid Machine Learning Approach in Data Mining

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International Conference on Machine Learning and Computing

作者： Jyothi Bellary Bhargavi Peyakunta Sekhar Konetigari Department of Computer Applications Sri Venkateswara University College of Engineering Madanapalle India Department of Computer Science Madanapalle Institute of Technology and Science Angallu India

In this paper we discuss various machine learning approaches used in mining of data. Further we distinguish between symbolic and sub-symbolic data mining methods. We also attempt to propose a hybrid method with the co... 详细信息

关键词： Machine learning Data mining Artificial neural networks Data analysis Databases Information systems Learning systems Classification tree analysis Data visualization Hospitals

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Implementation and Performance Evaluation of AODV in Wireless Mesh Networks using NS-3

Implementation and Performance Evaluation of AODV in Wireles...

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2010 2nd International Conference on Education Technology and computer(第二届IEEE教育技术与计算机国际会议 ICETC 2010)

作者： Shantanu Konwar Upola Gogoi Angshuman Chakraborty Nilufar Yeshmin Amrita Bose Paul Sukumar Nandi Department of Computer Applications Assam Engineering CollegeGuwahati Assam India Department of Computer Science & Engineering Indian Institute of Technology GuwahatiGuwahati Assam

Wireless Mesh Networks (WMNs) are a radio-based network technology that has gained considerable importance in network research community. It is a multi-hop wireless access network where nodes can act both as a host as well as a router. One of the factors that influence the performance of WMNs is the underlying routing protocol used. Since implementation of wireless routing protocols in a real test bed is difficult, hence, simulation environment is being considered for performance evaluation of a routing protocol in a wireless scenario. Recently, a new network simulator called NS-3, which is in its developing stage, demands a great potential (as claimed by the developers group) for performance analysis of different routing protocols. In this paper, we aim to implement and analyze the performance of Ad hoc On-Demand Distance Vector (AODV) routing protocol in NS-3, which is one of the candidate routing protocol proposed by IETF group for WMNs. For this, we have implemented AODV in NS-3.6 and extensive simulations have been carried out for calculation of Throughput, Packet Delivery Ratio (PDR), and Normalized Routing Overhead (NRO).

关键词： WMNs AODV WLANs NS-3 NRO PDR IETF

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A trust agent based incentive mechanism for file sharing in P2P networks

A trust agent based incentive mechanism for file sharing in ...

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Trendz in Information sciences & Computing (TISC)

作者： S. Moses Dian B. Ramadoss Department of Computer Science & Engineering National Institute of Technology Trichy India Department of Computer Applications National Institute of Technology Trichy India

Peer-to-Peer (P2P) network allow peer to distribute and obtain a file to be shared cooperatively. The successful growth of P2P network and its application is plagued by two important problems like Free Rider and Tragedy of commons, i.e. some selfish peers only download files without sharing its resources. This paper investigates the Free Rider and Tragedy of Common problem and encourages a peer to participate by proposing a trust agent based incentive mechanism. After applying this system theoretically, it improves the performance of the P2P system. Result obtained shows significant improvement which concludes that the proposed incentive mechanism will reduce the impact of Free Rider problem and effectively achieve fair sharing in P2P system.

关键词： Peer to peer computing Bandwidth Internet Robustness Communities Servers Incentive schemes

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Performance Study of Parallel Programming on Cloud Computing Environments Using MapReduce

Performance Study of Parallel Programming on Cloud Computing...

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International Conference on Information science and applications (ICISA)

作者： Wen-Chung Shih Shian-Shyong Tseng Chao-Tung Yang Department of Information Science and Applications Asia University Taichung Taiwan Department of Computer Science and Information Engineering Tunghai University Taichung Taiwan

ISBN: (纸本)9781424459421;9781424459438

Divisible load applications have such a rich source of parallelism that their parallelization can significantly reduce their total completion time on cloud computing environments. However, it is a challenge for cloud users, probably scientists and engineers, to develop their applications which can exploit the computing power of the cloud. Using MapReduce, novice cloud programmers can easily develop a high performance cloud application. To examine the performance of programs developed by this approach, we apply this pattern to implement three kinds of applications and conduct experiments on our cloud test-bed. Experimental results show that MapReduce programming is suitable for regular workload applications.

关键词： Parallel programming Cloud computing Programming profession Application software Testing Parallel processing Concurrent computing Data mining Processor scheduling Grid computing

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