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international conference on Information Sciences and Interaction Sciences (ICIS)

作者： Dianchuan Jin Xuebin Chen Shufen Zhang Hebei Polytechnic University Tangshan Hebei China

Along with the computer system information technology to the depth development, The cooperation is more and more important between information sharing and human's, people's working has communal, interactive, distributive and cooperative characteristics, the human society more and more becomes a close cooperation community. Using the computer network to support people's cooperative-work, and enhance the efficiency of community cooperation, so developing the computer supported cooperative-work (CSCW) calculation is inevitable trend. Meanwhile in order to improve the process information collaboration across enterprises in distributional collaborative business, this article will research in the XML> PSL and CSCW foundation, study the process information collaboration-mutuality methods across enterprises which based on XML. Through cope with the PSL deeply, will construct process information the description of Yuan model based on XML, utilize the PSL noumenon and XML to achieve the description for process information semantics and grammar levels. And an example of purchasing collaboration of supply chain belongs to process information, provide its the reality feasible, has provided the method for coordination interactive question about the commercial process information in enterprise distributional information resource.

关键词： Collaboration XML Computer networks Collaborative work distributed computing Information technology Humans Business Supply chains Information resources

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HiAL-Ckpt: A Hierarchical Application-Level Checkpointing for CPU-GPU Hybrid Systems

HiAL-Ckpt: A Hierarchical Application-Level Checkpointing fo...

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The 5th international conference on Computer Science & Education(第五届国际计算机新技术与教育学术研讨会 ICCSE'10)

作者： Xinhai Xu Yufei Lin Tao Tang Yisong Lin National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

In light of its powerful computing capacity and high energy efficiency, GPU (graphics processing unit) has become a focus in the research field of HPC (High Performance computing). CPU-GPU heterogeneous parallel systems have become a new development trend of super-computer. However, the inherent unreliability of the GPU hardware deteriorates the reliability of super-computer. We have researched on the fault-tolerance(FT) technique for CPU-GPU heterogeneous parallel systems, and introduced a new checkpointing mechanism, i.e., the hierarchical application-level checkpointing, for such systems. The basic idea of this new checkpointing mechanism is checkpointing at two independent levels, i.e., CPU level and GPU level, to tolerate CPU and GPU faults respectively. Based on the idea, we have also designed and implemented a hierarchical application-level checkpointing tool ”HiAL-Ckpt”. Using this tool, programmers can insert two kinds of directives, i.e., CPU directives and GPU directives into a program, and the compiler will transform the directives into CPU or GPU checkpointing codes according to their nature. From the case study of SWIM, a test bench from spec2000 benchmark suite, we have demonstrated the validity of the hierarchical application-level checkpointing technique. The experimental results show that the falut-tolerance temporal cost of HiAL-Ckpt for SWIM is only 2.25％, compared with the executing time of SWIM without any FT work.

关键词： GPU:heterogeneous systems:fault-tolerance checkpointing

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Person tracking using Kalman Filter in Wireless Sensor Network

Person tracking using Kalman Filter in Wireless Sensor Netwo...

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international conference on Advanced computing, ICAC

作者： V Vaidehi S. Vasuhi K. Sri Ganesh C. Theanammai N T Naresh Babu N Uthiravel P. Balamuralidhar Grish Chandra Parallel Processing Laboratory Department of Electronics Engineering Madras Institute of Technology Anna University India Department of Electronics Engineering Madras Institute of Technology Anna University TCS Limited Bangalore India TCS Bangalore India

Wireless Sensor Network (WSN) is an emerging technology for person detection and tracking. This paper proposes a scheme for detecting and tracking a person using WSN. In an organization where employees possess unique Radio Frequency Identification (RFID) tags, a WSN node detects the presence of a person using a PIR sensor and the identity of the person is obtained from the RFID tag. The accuracy of tracking a person in a WSN is limited due to the sensor's detection capabilities. Also, the sensor packets may be lost in the wireless medium. Moreover, the location information in the sensor is not accurate indoors. This paper proposes a multi-sensor and Kalman Filter (KF) based tracking scheme in a WSN oblivious to localization errors, errors due to missing events caused by failure of nodes etc. The accuracy of the proposed tracking has been validated for different scenarios.

关键词： Wireless sensor networks Radiofrequency identification Kalman filters Target tracking Particle filters Global Positioning System

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Building (1-ε) dominating sets partition as backbones in wireless sensor networks using distributed graph coloring 10

Building (1-ε) dominating sets partition as backbones in wi...

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Proceedings of the 6th IEEE international conference on distributed computing in Sensor Systems

作者： Dhia Mahjoub David W. Matula Bobby B. Lyle School of Engineering Southern Methodist University Dallas TX

ISBN: (纸本)9783642136504

We recently proposed in [19,20] to use sequential graph coloring as a systematic algorithmic method to build (1−ε) dominating sets partition in Wireless Sensor networks (WSN) modeled as Random Geometric Graphs (RGG). The resulting partition of the network into dominating and almost dominating sets can be used as a series of rotating backbones in a WSN to prolong the network lifetime for the benefit of various applications. Graph coloring algorithms in RGGs offer proven constant approximation guarantees on the chromatic number. In this paper, we demonstrate that by combining a local vertex ordering with the greedy color selection strategy, we can in practice, minimize the number of colors used to color an RGG within a very narrow window of the chromatic number and concurrently also obtain a domatic partition size within a competitive factor of the domatic number. We also show that the minimal number of colors results in the first (δ+1) color classes being provably dense enough to form independent sets that are (1−ε) dominating. The resulting first (δ+1) independent sets, where δ is the minimum degree of the graph, are shown to cover typically over 99% of the nodes (e.g. ε<0.01), with at least 20% being fully dominating. These independent sets are subsequently made connected through virtual links using localized proximity rules to constitute planar connected backbones. The novelty of this paper is that we extend our recent work in [20] into the distributed setting and present an extensive experimental evaluation of known distributed coloring algorithms to answer the (1−ε) dominating sets partition problem. These algorithms are both topology and geometry-based and yield O(1) times the chromatic number. They are also shown to be inherently localized with running times in O(Δ) where Δ is the maximum degree of the graph.

关键词： graph coloring distributed algorithm wireless sensor network domatic partition problem (1 - ε) dominating sets partition

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Fast forensic video event retrieval using geospatial computing 10

Fast forensic video event retrieval using geospatial computi...

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Proceedings of the 1st international conference and Exhibition on computing for Geospatial Research & Application

作者： Hongli Deng Mun Wai Lee Asaad Hakeem Omar Javed Weihong Yin Li Yu Andrew Scanlon Zeeshan Rasheed Niels Haering ObjectVideo Inc. Reston Virginia

ISBN: (纸本)9781450300315

This paper presents a fast forensic video events analysis and retrieval system in a geospatial framework. Starting from tracking targets and analyzing video streams from distributed camera networks, the system generates video tracking metadata for each video, maps and fuses them in a uniform geospatial coordinate. The combined metadata is saved into spatial database where target trajectories are represented in geometry and geography data type. Powered by spatial functions of database, various video events such as crossing a line, entering an area, loitering and meeting, are detected by executing stored procedures that we have implemented. Geographic information system(GIS) data of Tiger-Line and GeoNames are integrated with this system to provide contextual information for more advanced forensic queries. A semantic data mining system is also attached to generate text descriptions of events and scene contextual information. The NASA World Wind is the geobrowser used to submit queries and visualize result. The main contribution of this system is that it initiates in running video event retrieval using geospatial computing techniques. This interdisciplinary combination makes this system scalable and manageable for large amount of video data from distributed cameras. It also makes the online video search possible by filtering tremendous amount of data efficiently using geospatial index techniques. From the application point of view, it extends the frontier of geospatial application by presenting a forward-looking application model.

关键词： video surveillance video analysis video event search spatial database video retrieval

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Attention-Enhanced Ensemble Learning for Diabetic Retinopathy Classification with Interpretability

Attention-Enhanced Ensemble Learning for Diabetic Retinopath...

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international conference on Advanced Infocomm Technology (ICAIT)

作者： Keliang Wu Jincheng Peng Xiang Feng Zixuan Chen Happy Nkanta Monday Grace Ugochi Nneji Computing Chengdu University of Technology Chengdu China

ISBN: (数字)9798350391497

ISBN: (纸本)9798350391503

Diabetic Retinopathy (DR) is a severe complication of diabetes that significantly impacts vision and can potentially lead to blindness. The effective diagnosis and timely treatment of DR is crucial preventing vision loss. Convolutional Neural networks (CNNs) have emerged as a prominent tool in the field of medical image analysis for this purpose. This paper proposes a novel ensemble residual deep learning model that integrates parallel convolutional filters with shallow convolutional neural network enhanced by a channel attention mechanism for the classification of DR. The proposed model leverages the strength of residual learning and attention mechanism to improve feature extraction and classification performance. To validate the effectiveness of the model, this study conducted extensive experiment on DR data, where the model demonstrated robust diagnostic capabilities. The results were remarkable, achieving accuracy of 97.69 % , F1-score of 97.77 % , sensitivity of 97.02 %, specificity of 98.18%, precision and recall both at 97.77%. Furthermore, the model attained an area under curve of 98%, highlighting its potential to serve as an effective supplementary tool for the analysis of DR images. These findings underscore the model's potential to assist healthcare professionals in the early and accurate diagnosis of DR, ultimately contributing to better patient outcome.

关键词： Diabetic retinopathy Attention mechanisms Accuracy Sensitivity Image analysis Filters Medical services Data models Convolutional neural networks Medical diagnostic imaging

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distributed multiagent learning with a broadcast adaptive subgradient method 10

Distributed multiagent learning with a broadcast adaptive su...

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Proceedings of the 9th international conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1

作者： R. L. G. Cavalcante A. Rogers N. R. Jennings I. Yamada University of Southampton Tokyo Institute of Technology

ISBN: (纸本)9780982657119

Many applications in multiagent learning are essentially convex optimization problems in which agents have only limited communication and partial information about the function being minimized (examples of such applications include, among others, coordinated source localization, distributed adaptive filtering, control, and coordination). Given this observation, we propose a new non-hierarchical decentralized algorithm for the asymptotic minimization of possibly time-varying convex functions. In our method each agent has knowledge of a time-varying local cost function, and the objective is to minimize asymptotically a global cost function defined by the sum of the local functions. At each iteration of our algorithm, agents improve their estimates of a minimizer of the global function by applying a particular version of the adaptive projected subgradient method to their local functions. Then the agents exchange and mix their improved estimates using a probabilistic model based on recent results in weighted average consensus algorithms. The resulting algorithm is provably optimal and reproduces as particular cases many existing algorithms (such as consensus algorithms and recent methods based on the adaptive projected subgradient method). To illustrate one possible application, we show how our algorithm can be applied to coordinated acoustic source localization in sensor networks.

关键词： consensus distributed computing acoustic source localization decentralized convex optimization

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An Efficiency Approach for Identifying All Distribute Non-inferior Solutions of MODM

An Efficiency Approach for Identifying All Distribute Non-in...

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2011 IEEE international conference on Intelligent computing and Intelligent Systems(ICIS 2011)

作者： Zhixin Ma School of Information Science and Engineering Lanzhou University Lanzhou,China Shuyuan Xia

MODM(multiple objective decision making) is a discipline aimed at making decisions in the multiple,often conflicting ***,a lot of methods aiming at converting multiple objectives to a single objective have been *** most of these methods must be under the abstruse preference prior knowledge and the global optimality cannot be *** this paper,a new approach SBASM(skyline query based approach for solving MODM) is proposed based on our previous work,which uses intrinsic parallel mechanism and full optimization to search for solutions of MODM feasibly and ***,this method overcame the shortcomings that exist in the original methods in which only one solution can be obtained once a *** the SBASM successfully achieved the tradeoffs of different *** SBASM is divided into four *** is carried out as a first step toward transforming the original continuous area into a standard equally distributed grid *** the non-inferior solutions are initially identified at the second stage by applying a Quad-tree Based Algorithm(QBSQ).A skyline-decision tree is proposed at the third stage to effectively choose the preferred *** there are too many points to get once a *** we adopt CM. (conversational mode) to refine the discrete points step by *** this sequential process,the Preferred solution can be easily determined in a more systematic and meaningful *** experiments prove the efficiency and the accuracy of the new approach.

关键词： MODM skyline discretization optimization parallel non-inferior solution

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A Deep Learning-based Innovative Approach for Enhancing the Precision of Tool Wear Prediction

A Deep Learning-based Innovative Approach for Enhancing the ...

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international conference on Communication and Electronics Systems (ICCES)

作者： D. Vinod Karimulla Syed Sampath Kumar S B. Sankara Babu Shatrudhan Pandey Raja Velur Loganathan Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai Koneru Lakshmaiah Education Foundation Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore Department of CSE Gokaraju Rangaraju Institute of Engineering and Technology (Autonomous) Bachupally Telangana Department of Production and Industrial Engineering Birla Institute of Technology Ranchi Department of Mechanical Engineering Loyola Institute of Technology Chennai

Throughout the cutting operation, among the most crucial steps is that has a direct impact on machining accuracy and product quality is tool wear. If you can accurately forecast how quickly tools will wear out, you can make the necessary adjustments early on, minimizing downtime and maximizing product quality. The evaluation of cutting tool wears during the production stage is crucial. The main objective of this study is to track tool degradation over time to guarantee regular tool changes and prevent workpiece waste and potential machine damage from excessive tool wear or unexpected tool breakage. For this reason, it is necessary to develop a system that is both intelligent and capable of providing accurate solutions to these issues. The criteria of intelligent production are great, though, and traditional methods simply cannot match them. Because of this, a deep learning-based innovative approach is presented to advance the precision of tool wear prediction. parallel convolutional neural networks were constructed and used to achieve multi-scale feature fusion. To improve the model's efficiency, the channel attention mechanism was integrated with the residual connection to take into account the relative importance of each feature map. To prove that the created approach is superior, several experiments were carried out to anticipate tool wear, and the findings are more reliable and accurate than those obtained using existing methods. To guarantee the excellence of the engine cylinder and the steadiness of the machining procedure, a tool wear monitoring system was created. Using the PHM 2010 milling cutter wear dataset, tests were performed to validate the model effect. Based on the experimental data, this model has an average RMSE of 2.67 and an average MAE of 2.5. The trial outcomes proved the effectiveness of the suggested approach in evaluating the tool's wear.

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Preface

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JOURNAL OF SUPERcomputing 2010年第3期51卷 241-243页

作者： Huang, Zhiyi Hine, John Lefevre, Laurent McGregor, Tony Pan, Yi Shen, Hong Xu, Zhiwei Univ Otago Dunedin Otago New Zealand

This special issue titled "Emerging Research in parallel and distributed computing" reflects the recent research efforts of authors of the Ninth international conference on parallel and distributed computing, Applications and Technologies (PDCAT 2008). This special issue is divided into two sections: the first addresses the issues in multi-core computing, while the second contains the new developments in grid computing.

关键词： Grid computing Statement Public Speaking distributed computing Writers parallel Lines international conference

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