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检索条件"任意字段=2021 10th International Conference on Computing and Pattern Recognition"

共 1677 条记录，以下是331-340 订阅

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Comparing Evolutionary Optimization Algorithms for the Fog Service Placement Problem 16

Comparing Evolutionary Optimization Algorithms for the Fog S...

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16th IEEE/ACM international conference on Utility and Cloud computing (UCC) / 10th IEEE/ACM international conference on Big Data computing, Applications and Technologies (BDCAT)

作者： Vivo, Sergi Lera, Isaac Guerrero, Carlos Univ Balearic Isl Palma De Mallorca Mallorca Spain

ISBN: (纸本)9798400702341

In this work, we compare the performance of six popular evolutionary algorithms to address the problem of allocating applications to devices in a fog infrastructure. the optimization of application placement is carried out with the objectives of minimizing the number of devices assigned to applications and reducing the network distance between applications and the users who request them. We evaluate the algorithms based on their proximity to the true Pareto front and the diversity of the solution space they provide. the experimental phase demonstrates that the non-dominated sorting genetic algorithm family (NSGA) of algorithms achieves Pareto fronts that closely approach the true Pareto front, as determined by ILP optimization.

关键词： Fog computing Application placement Genetic algorithms Resource optimization

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A Proposed model for field workers Injuries' prevention based on machine learning 10

A Proposed model for field workers Injuries' prevention base...

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10th IEEE international conference on Intelligent computing and Information Systems, ICICIS 2021

作者： Abbas Sabet, Mohamed Farouk Dahroug, Ahmed Hegazy, Abdel Fattah Technology and Maritime Transport College of Computing and Information Technology Arab Academy for Science Cairo Egypt

ISBN: (纸本)9781665440769

the prosperity of the construction industry in Egypt at the expense of occupational safety and health of the worker there are several factors [1]. for the occurrence of these accidents, such as. Construction projects are being created temporarily. the difficulty of standardizing safety procedures in all construction projects;this study aims to design machine learning techniques, deep learning techniques, and failure to comply with the safe use of tools, and the association rules-based decision support system is objective to identify the reasons for injury and the results of the accident, effects of an accident at construction projects in Egypt also, explore the characteristics of top-ranking reason and effects. Various direct and indirect relations of top reasons and effects are also analyzed in this study. To determine the type of injury and reduce injuries the dataset was collected from Arab Contractors company in Egypt. the dataset consists of 5,800 work accident report from 2011 to 2019. © 2021 IEEE.

关键词： Deep neural networks

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10th international conference on theory and Practice of Natural computing, TPNC 2021

10th International Conference on Theory and Practice of Natu...

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10th international conference on theory and Practice of Natural computing, TPNC 2021

ISBN: (纸本)9783030904241

the proceedings contain 9 papers. the special focus in this conference is on theory and Practice of Natural computing. the topics include: Dynamic Heuristic Set Selection for Cross-Domain Selection Hyper-heuristics;on the Transfer Learning of Genetic Programming Classification Algorithms;on Injecting Entropy-Like Features into Deep Neural Networks for Content Relevance Assessment;ABCD: Analogy-Based Controllable Data Augmentation;MOEA/D with Adaptative Number of Weight Vectors;parallel Asynchronous Memetic Optimization for Freeform Optical Design;ant-Based Generation Constructive Hyper-heuristics for the Movie Scene Scheduling Problem.

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Two-Dimensional ISAR Imaging with pattern-Coupled Sparse Structure Based on 2D-RFISTA 10

Two-Dimensional ISAR Imaging with Pattern-Coupled Sparse Str...

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10th international conference on Control, Automation and Information Sciences, ICCAIS 2021

作者： Wei, Xu Yang, Jun Lv, Mingjiu Chen, Wenfeng Ma, Xiaoyan Xia, Saiqiang Early Warning Academy No. One Department Wuhan China Radar Nco School Early Warning Academy Wuhan China

ISBN: (纸本)9781665440295

In order to improve the imaging quality of two-dimensional inverse synthetic aperture radar (ISAR) under the conditions of low signal-to-noise ratio (SNR) and sparsity rate (SR), in view of pattern-coupled sparse structure (PCSS) of the imaging target, a novel two-dimensional joint sparse imaging algorithm, namely two-dimensional reweighted fast iterative shrinkage-thresholding algorithm (2D-RFISTA) is proposed. One dimensional RFISTA (1D-RFISTA) is extended to 2D-RFISTA by matrix processing and design of the pattern-coupled mode, which reduces the complexity of the algorithm and improves the imaging performance under noisy and sparse conditions. Experimental results based on measured data demonstrate that the proposed algorithm has excellent imaging quality and is suitable for the imaging scene with low time requirement. © 2021 IEEE.

关键词： Inverse synthetic aperture radar

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Research on modeling for the pattern library of interconnect parasitic capacitances in VLSI

Research on modeling for the pattern library of interconnect...

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2010 10th IEEE international conference on Solid-State and Integrated Circuit Technology

作者： Qu, Hui Xu, Xiaoyu Ren, Zhuoxiang Institute of Electrical Engineering Chinese Academy of Sciences Beijing 100190 China L2E UPMC University of Paris 6 4 place Jussieu F-75252 Paris France

ISBN: (纸本)9781424457984

At the present IC technologies, the accurately extraction of the interconnects parasitic parameters become more important. But for the time consuming, that computing the parameters of interconnects with field solver directly is impracticable. the common way is that establishing the pattern library according some typical Structures at the early design stage, then calculating the actual parameters after routing using these patterns. But for the pattern library establishment of interconnects parasitic parameters, how to determine the form of the pattern and how much sampling points should be selected, that are troublesome, which is related to both the time consuming and the accuracy of the model. In this paper, the authors provide a new modeling method, called error modification model method, and adopt a orthogonal sampling method, it can construct a parasitic parameter model in a relatively short time with high precision. ©2010 IEEE.

关键词： Capacitance

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DRFM Jamming Mode Identification Leveraging Deep Neural Networks 10

DRFM Jamming Mode Identification Leveraging Deep Neural Netw...

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10th international conference on Control, Automation and Information Sciences, ICCAIS 2021

作者： Gao, Jiannan Wang, Min Chen, Longbiao Hui, Bingwei Wang, Cheng Fan, Hongqi Xiamen University Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen China National University of Defense Technology National Key Laboratory of Science and Technology on Automatic Target Recognition Changsha China

ISBN: (纸本)9781665440295

In modern information warfare, radar must apply some anti-jamming technologies. Digital radio frequency memory (DRFM) and its technology can adapt to the complex threat signal environment and have an excellent jamming effect that other technical means in the past cannot match. Currently, traditional DRFM jamming identification is mainly based on the method of extracting and modeling radar signal features. It is unable to identify various types of jamming and lacks a large amount of radar data. In this work, we propose a three-phase framework to identify DRFM jamming. First, we design a hardware system based on PXI module to generate jamming signal data. Second, we perform range-doppler processing on the raw radar signal data to generate range-doppler map (RD-map) which can accurately represent jamming signals. Finally, we use deep learning to identify DRFM jamming and use pre-trained models to improve identification accuracy. We evaluate our proposed framework using real DRFM jamming data collected from PXI system. the valuation results confirm that our approach effectively identifies DRFM jamming, achieving an average accuracy of 84.4%. © 2021 IEEE.

关键词： Deep neural networks

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Conceptual framework supporting pattern design selection for scientificworkflow applications in cloud computing 10

Conceptual framework supporting pattern design selection for...

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10th international conference on Cloud computing and Services Science, CLOSER 2020

作者： Alkhanak, Ehab Nabiel Khan, Saif Ur Rehman Verbraeck, Alexander Van Lint, Hans Delft Netherlands Islamabad Pakistan Delft Netherlands

ISBN: (纸本)9789897584244

Scientific Workflow Applications (SWFA) play a vital role for both service consumers and service providers in designing and implementing large and complex scientific processes. Previously, researchers used parallel and distributed computing technologies, such as utility and grid computing to execute the SWFAs, these technologies provide limited utilization for the shared resources. In contrast, the scalability and flexibility challenges are better handled by using cloud-computing technologies for SWFA. Since cloud computing offers a technology that can significantly utilize the amounts of storage space and computing resources necessary for processing large-size and complex SWFAs. the workflow pattern design has provided the facility of re-using previously developed workflow solutions that enable the developers to adopt them for the considered SWFA. Inspired by this, the researchers have adopted several patterns of design to better design the SWFA. Effective pattern design that can consider challenges that may not become visible only in the implementation stage of a SWFA. However, the selection of the most effective pattern design in accordance with an execution method, data size, and problem complexity of a SWFA remains a challenging task. Motivated by this, we have proposed a conceptual framework that facilitates in recommending a suitable pattern design based on the quality requirements and capabilities are given and advertised by cloud consumers and providers, respectively. Finally, guidelines to assist in a smooth migrating of SWFA from other computation paradigms to cloud computing. © Copyright 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Cloud computing

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10th international conference on Innovations in Bio-Inspired computing and Applications, IBICA 2019 and 9th World Congress on Information and Communication Technologies, WICT 2019

10th International Conference on Innovations in Bio-Inspired...

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10th international conference on Innovations in Bio-Inspired computing and Applications, IBICA 2019 and 9th World Congress on Information and Communication Technologies, WICT 2019

ISBN: (纸本)9783030493387

the proceedings contain 38 papers. the special focus in this conference is on Innovations in Bio-Inspired computing and Applications. the topics include: Soft computing approach on minimisation of indirect losses in power generation for efficiency enhancing;a machine learning prediction of automatic text based assessment for open and distance learning: A review;analysis of pre-processing techniques for odia character recognition;cluster-based under-sampling using farthest neighbour technique for imbalanced datasets;vehicle detection and classification: A review;methods for automatic gait recognition: A review;comparative performance exploration and prediction of fibrosis, malign lymph, metastases, normal lymphogram using machine learning method;decision forest classifier with flower search optimization algorithm for efficient detection of bhp flooding attacks in optical burst switching network;welcome message;towards the speed enhancement of association rule mining algorithm for intrusion detection system;review and implementation of 1-bit adder in cmos and hybrid structures;design and analysis of lol-p textile antenna;analytical study of scalability in coastal communication using hybridization of mobile ad-hoc network: An assessment to coastal bed of odisha;effect of environmental and occupational exposures on human telomere length and aging: A review;a review on vlsi implementation in biomedical application;comparative analysis of a dispersion compensating fiber optic link using fbg based on different grating length and extinction ratio for long haul communication;unsupervised learning method for mineral identification from hyperspectral data;short term load forecasting using empirical mode decomposition (emd), particle swarm optimization (pso) and adaptive network-based fuzzy interference systems (anfis).

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Monitoring Insiders Activities in Cloud computing Using Rule Based Learning

Monitoring Insiders Activities in Cloud Computing Using Rule...

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Int Joint conference of 10th IEEE Int Conf on Trust, Security and Privacy in computing and Communications (TrustCom) / 8th IEEE Int Conf on Embedded Software and Systems (ICESS) / 6th Int Conf on Frontier of Computer Science and Technology (FCST)

作者： Khorshed, Md Tanzim Ali, A. B. M. Shawkat Wasimi, Saleh A. CQUniv Sch Informat & Commun Technol Rockhampton Qld 4702 Australia

ISBN: (纸本)9780769546001

One of the essential but formidable tasks in cloud computing is to detect malicious attacks and their types. A cloud provider's constraints or inability in monitoring its employees, and lack of transparency, may make the detection process even harder. We found these insiders' activities form similar pattern in the monitoring systems as some other cyber attacks because these also uses huge computer resources. In this paper we first provide a brief overview on the importance of monitoring insiders' activities through a literature survey on cloud computing security. then, we observe some of the real life insiders' activities that can be detected from the performance data in a hypervisor and its guest operating systems. Rule based learning is successfully used for identification of these activities in this research. We further observe that some of these insiders' activities can on occasions turn into a malicious insider's attack, and thus, need constant monitoring in the cloud environment.

关键词： Security threats machine learning cyber attacks cloud computing insiders

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Benchmarking Annotation Procedures for Multi-channel Time Series HAR Dataset

Benchmarking Annotation Procedures for Multi-channel Time Se...

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19th IEEE international conference on Pervasive computing and Communications (IEEE PerCom)

作者： Avsar, Hulya Altermann, Erik Reining, Christopher Rueda, Fernando Moya Fink, Gernot A. ten Hompel, Michael TU Dortmund Univ Chair Mat Handling & Warehousing Joseph von Fraunhofer Str 2-4 D-44227 Dortmund Germany TU Dortmund Univ Pattern Recognit Embedded Syst Grp Joseph von Fraunhofer Str 2-4 D-44227 Dortmund Germany

ISBN: (纸本)9781665404242

this contribution evaluates semi-automated annotation for generating high-quality data for multi-channel time series Human Activity recognition. For this purpose, time series data that consists of Optical Motion Capturing and inertial measurements from on-body devices for industrial deployment is created, annotated, and revised by four individuals. the semi-automated annotation consists of predictions from a temporal convolutional neural-network, and manual revisions for generating high-quality and fine-grained annotations for Human Activity recognition. this annotation approach reduces the annotation effort keeping similar quality as compared to manual annotation.

关键词： Human Activity recognition Labelling Annotation Human Reliability Logistics Warehousing Deep Learning Semi-Automatic Annotation

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