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作者： Zhu, Suguo Fang, Zhenying Gao, Fei Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China State Key Laboratory of Integrated Services Networks Xidian University Xian710071 China

Recently, deep learning is widely developed in computer vision applications. In this paper, a novel simple tracker with deep learning is proposed to complete the tracking task. A simple fully convolutional Siamese network is applied to capture the similarity between different frames. Nevertheless, the detailed information from lower layers, which is also important for locating the target object, is not considered into the tracking task. In this paper, the detailed information from two lower layers is considered into the response map to improve the performance and not to increase much time spent. This leads more significant improvement for feature representation and localization of the target object. The experimental results demonstrate that the proposed algorithm is efficient and robust compared with the baseline and the state-of-the-art trackers. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Deep neural networks

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Cooperative Control for Satellite Formation Reconfiguration Via Cyclic Pursuit Strategy

Cooperative Control for Satellite Formation Reconfiguration ...

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The 2012 International Conference on Advanced Material and Manufacturing science (ICAMMS 2012)

作者： YANG Tao HU Zhengdong YANG Libo Beijing Institute of Special Electromechanical Technology Science and Technology on Complex Systems Simulation Laboratory

This paper investigates a methodology for group coordination and cooperative control of satellites with the aim to achieve formation reconfiguration such as radius enlargement and phase angle *** proposed approach separates the control law into two distinct stages:planar movement control and orthogonal displacement *** in plane approach is based on a cyclic pursuit strategy,where satellite i pursues satellite i +*** phase angle adjustment,a control law that makes use of "beacon's guidance" is synthesized to maintain the circling centre *** the orthogonal direction,a linear feed back control on displacement and velocity is *** of two missions with low thrust are provided,which high light the over all effectiveness of the proposed approach.

关键词： Cyclic pursuit Beacon's guidance Satellite formation reconfiguration

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A practical approach for test equipment perception and virtualization in cloud manufacturing

A practical approach for test equipment perception and virtu...

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Chinese Intelligent systems Conference, CISC 2017

作者： Xu, Yuyan Zhang, Lin Luo, Xiao Zhang, Han School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Engineering Research Center of Complex Product Advanced Manufacturing Systems Ministry of Education Beijing100191 China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing100854 China

ISBN: (纸本)9789811064982

As an advanced manufacturing paradigm, Cloud Manufacturing provides a new way to solve the problems in the testing process. In cloud manufacturing, resource perception and resource virtualization are the foundation of building an actual service platform. According to the characteristic of test equipment, a practical approach for test equipment perception and virtualization is proposed, which is based on cloud computing, Automatic Test Markup Language (ATML) description and data mapping. A test service platform prototype is given to validate the feasibility of this approach. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Virtualization

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The simulation of cluster bombs' damage efficiency and analysis of damage factor

The simulation of cluster bombs' damage efficiency and analy...

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2014 International Conference on Future Communication technology and Engineering (FCTE 2014)

作者： S.Liu X.J.Zhao F.Zhao X.Wei W.F.Li Science and Technology on Complex Land Systems Simulation Laboratory Chinese Defense Science and Technology Information Centre

First, the paper emulated cluster bombs' random point of fall, the radius of damage of the bombs,drew the bombs' damage range, and counted the damage effect. The final damage efficiency of cluster bombs was calculated and the influence from each damage factor of the cluster bombs was studied through many random experiences. The method solved the tough problem of the precise calculation of damage efficiency, which was caused by the overlapped damage size.

关键词： The simulation of cluster bombs damage efficiency and analysis of damage factor simulation

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Architecture Transformation Research on Joint Border Defense systems-of-systems

Architecture Transformation Research on Joint Border Defense...

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作者： Mengmeng Zhang Shuanghui Yi Menglong Lin Honghui Chen Science and Technology on Information Systems Engineering Laboratory National Key Laboratory for Complex System Simulation

Currently,with the deepening of development and open of China's border,issues of border joint defense become increasingly *** means of cooperation and coordination are far from being able to align requirements;information systems of different joint defense units are difficult to interconnect and interoperate;the previous results of joint defense informatization are difficult to *** main reason is the lack of border joint defense information construction with a top-level design *** the lens of top-level design,this paper establishes a multi-viewpoint architecture framework and transformation process,develops the as-is and to-be joint defense architecture,and finally analyzes transformation principles from the as-is architecture to to-be *** paper mainly explores the architecture transformation mechanisms under the border joint defense scenario.

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PARDA: A dataset for scholarly PDF document metadata extraction evaluation 14th

PARDA: A dataset for scholarly PDF document metadata extract...

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14th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2018

作者： Fan, Tiantian Liu, Junming Qiu, Yeliang Jiang, Congfeng Zhang, Jilin Zhang, Wei Wan, Jian School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou310018 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9783030129804

Metadata extraction from scholarly PDF documents is the fundamental work of publishing, archiving, digital library construction, bibliometrics, and scientific competitiveness analysis and evaluations. However, different scholarly PDF documents have different layout and document elements, which make it impossible to compare different extract approaches since testers use different source of test documents even if the documents are from the same journal or conference. Therefore, standard datasets based performance evaluation of various extraction approaches can setup a fair and reproducible comparison. In this paper we present a dataset, namely, PARDA(Pdf Analysis and Recognition DAtaset), for performance evaluation and analysis of scholarly documents, especially on metadata extraction, such as title, authors, affiliation, author-affiliation-email matching, year, date, etc. The dataset covers computer science, physics, life science, management, mathematics, and humanities from various publishers including ACM, IEEE, Springer, Elsevier, arXiv, etc. And each document has distinct layouts and appearance in terms of formatting of metadata. We also construct the ground truth metadata in Dublin Core XML format and BibTex format file associated this dataset. © 2019, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Metadata

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Energy aware edge computing: a survey 2nd

Energy aware edge computing: a survey

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2nd International Workshop on High Performance Computing for Advanced Modeling and simulation in Nuclear Energy and Environmental science, HPCMS 2018, and 1st International Workshop on HPC Supported Data Analytics for Edge Computing, HiDEC 2018 held at the 32nd ACM International Conference on Supercomputing, ACM ICS 2018

作者： Fan, Tiantian Qiu, Yeliang Jiang, Congfeng Wan, Jian Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou310018 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9789813299863

Edge computing is an emerging paradigm to meet the ever-increasing computation demands from pervasive devices such as sensors, actuators, and smart things. Though the edge devices can execute complex applications, it is necessary for some applications to migrate to centralized servers. By offloading the computation from the edge nodes to the edge servers or cloud servers, the quality of computation experience could be greatly improved. However, it may cause delay and increase network overheads, and energy consumption eventually. Therefore, an optimal offloading strategy should take into account what task should be offloaded, when to offload and where to offload to avoid the overheads. Thus, it is important to tradeoff between energy consumption, computation delay and throughput when the system makes the computation offloading to achieve high energy efficiency. In this paper, we conduct a survey of energy aware edge computing, including the existing work on computation offloading frameworks and strategies in edge computing. Specifically, we describe the strategies from the perspective of energy aware offloading, energy optimization offloading and offloading algorithms. © Springer Nature Singapore Pte Ltd 2019.

关键词： Energy efficiency

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Towards computation offloading in edge computing: A survey 2nd

Towards computation offloading in edge computing: A survey

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作者： Cheng, Xiaolan Zhou, Xin Jiang, Congfeng Wan, Jian Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou310018 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9789813299863

The explosive growth of massive data generation from Internet of Things in industrial, agricultural and scientific communities has led to a rapid increase in cloud data centers for data analytics. The ubiquitous and pervasive demand for near-data processing urges the edge computing paradigm in recent years. Edge computing is promising for less network backbone bandwidth usage and thus less data center side processing, as well as enhanced service responsiveness and data privacy protection. Computation offloading plays a crucial role in network packets transmission and system responsiveness through dynamic task partitioning between cloud data centers and edge servers and edge devices. In this paper a thorough literature review is conduct to reveal the state-of-the-art of computation offloading in edge computing. Various aspects of computation offloading, including energy consumption minimization, Quality of Services (QoS), and Quality of Experiences (QoE) are surveyed. Resource scheduling approaches, gaming and tradeoffing among system performance and system overheads for offloading decision making are also reviewed. © Springer Nature Singapore Pte Ltd 2019.

关键词： computation offloading

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An edge computing platform for intelligent internet data center operational monitoring 2nd

An edge computing platform for intelligent internet data cen...

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作者： Qiu, Yeliang Jiang, Congfeng Fan, Tiantian Wan, Jian Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou310018 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9789813299863

The explosive growth in cloud-based services, big data analytics, and artificial intelligence related services provisioning leads to the rapid growth of construction of large scale Internet data centers (IDCs). Modern IDCs are equipped with various sensors to monitor its healthy operation and maintenance states, such as temperature, thermal distribution, air flow, etc. However, fine-grained, single-node level and even mainboard level monitoring including server resource consumption and power consumption is still needed for more progressive resource multiplexing and job scheduling in IDCs. In this paper, we propose an edge computing platform for intelligent Internet data center operational monitoring, which integrates wireless sensors and on-board built-in sensors to sense and collect the data of data center operation and maintenance. The edge computing based solution reduces the latency for data transportation to central clouds and reduces the amount of data and enhances the real time resource capping decisions in data centers. © Springer Nature Singapore Pte Ltd 2019.

关键词： Energy efficiency

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FISS GAN:A Generative Adversarial Network for Foggy Image Semantic Segmentation

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1428-1439页

作者： Kunhua Liu Zihao Ye Hongyan Guo Dongpu Cao Long Chen Fei-Yue Wang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering Jilin University(Campus Nanling)Changchun 130025China Mechanical and Mechatronics Engineering Department at the University of Waterloo 200 University Avenue West WaterlooON N2L 3G1Canada State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.

关键词： Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation

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