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Multiuser Computation Offloading for Long-Term Sequential Tasks in Mobile Edge Computing Environments

Tsinghua Science and technology 2023年第1期28卷 93-104页

作者： Huanhuan Xu Jingya Zhou Wenqi Wei Baolei Cheng School of Computer Science and Technology Soochow UniversitySuzhou 215006China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125China Provincial Key Laboratory for Computer Information Processing Technology Soochow UniversitySuzhou 215006China School of Computer Science Georgia Institute of TechnologyAtlantaGA 30332USA

Mobile edge computing has shown its potential in serving emerging latency-sensitive mobile applications in ultra-dense 5G networks via offloading computation workloads from the remote cloud data center to the nearby network ***,current computation offloading studies in the heterogeneous edge environment face multifaceted challenges:Dependencies among computational tasks,resource competition among multiple users,and diverse long-term *** applications typically consist of several functionalities,and one huge category of the applications can be viewed as a series of sequential *** this study,we first proposed a novel multiuser computation offloading framework for long-term sequential ***,we presented a comprehensive analysis of the task offloading process in the framework and formally defined the multiuser sequential task offloading ***,we decoupled the long-term offloading problem into multiple single time slot offloading problems and proposed a novel adaptive method to solve *** further showed the substantial performance advantage of our proposed method on the basis of extensive experiments.

关键词： mobile edge computing sequential tasks computation offloading dependency

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The system design of a node of P2P networks for intrusion detection

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Journal of Networks 2013年第8期8卷 1920-1927页

作者： Ding, Lei Yu, Fei Yang, Zhenghua Yue, Guangxue School of Information Science and Engineering Jishou University Jishou 416000 China Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Soochow 215006 China School of Mathematic and Computer Jiaxin University Jiaxin 314001 China

To improve the measuring accuracy of intrusion detection, a system design of a node for intrusion detection is proposed in this paper. First, the technology that applies the traditional intrusion detection method, such as anomaly detection and misuse detection, into P2P networks is presented. Next, to build the trust relationship among the nodes, and realize the cooperation mechanism of data detection, collection and response among the nodes of P2P networks, the corresponding solving plans, such as topological structure, trust model, information share and information fusion, are proposed in this paper. Then the concept of network telescope is presented to broaden the field of vision of malicious attacks and abnormal network packets in the propagation path. Finally, a system design of a node for intrusion detection using the honeypot technology is proposed in this paper. © 2013 ACADEMY PUBLISHER.

关键词： Intrusion detection

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Study on Wikipedia for translation mining for CLIR

Study on Wikipedia for translation mining for CLIR

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International Conference on Machine Learning and Cybernetics

作者： Yao, Jian-Min Sun, Chang-Long Hong, Yu Ge, Yun-Dong Zhu, Qiao-Min Key Laboratory of Computer Information Processing Suzhou University Jiangsu Province Suzhou 215006 China

ISBN: (纸本)9781424465262

The query translation of Out of Vocabulary (OOV) is one of the key factors that affect the performance of Cross-Language information Retrieval (CLIR). Based on Wikipedia data structure and language features, the paper divides translation environment into target-existence and target-deficit environment. To overcome the difficulty of translation mining in the target-deficit environment, the frequency change information and adjacency information is used to realize the extraction of candidate units, and establish the strategy of mixed translation mining based on the frequency-distance model, surface pattern matching model and summary-score model. Search engine based OOV translation mining is taken as baseline to test the performance on TOP1 results. It is verified that the mixed translation mining method based on Wikipedia can achieve the precision rate of 0.6279, and the improvement is 6.98% better than the baseline. © 2010 IEEE.

关键词： Search engines

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Dependency-driven feature-based learning for extracting protein-protein interactions from biomedical text

Dependency-driven feature-based learning for extracting prot...

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23rd International Conference on Computational Linguistics, Coling 2010

作者： Liu, Bing Qian, Longhua Wang, Hongling Zhou, Guodong Jiangsu Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow University China

Recent kernel-based PPI extraction systems achieve promising performance because of their capability to capture structural syntactic information, but at the expense of computational complexity. This paper incorporates dependency information as well as other lexical and syntactic knowledge in a feature-based framework. Our motivation is that, considering the large amount of biomedical literature being archived daily, feature-based methods with comparable performance are more suitable for practical applications. Additionally, we explore the difference of lexical characteristics between biomedical and newswire domains. Experimental evaluation on the AIMed corpus shows that our system achieves comparable performance of 54.7 in F1-Score with other state-of-the-art PPI extraction systems, yet the best performance among all the feature-based ones.

关键词： Syntactics

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Dependency-driven anaphoricity determination for coreference resolution

Dependency-driven anaphoricity determination for coreference...

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23rd International Conference on Computational Linguistics, Coling 2010

作者： Kong, Fang Zhou, Guodong Qian, Longhua Zhu, Qiaoming JiangSu Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow University China

This paper proposes a dependency-driven scheme to dynamically determine the syntactic parse tree structure for tree kernel- based anaphoricity determination in coreference resolution. Given a full syntactic parse tree, it keeps the nodes and the paths related with current mention based on constituent dependencies from both syntactic and semantic perspectives, while removing the noisy information, eventually leading to a dependency-driven dynamic syntactic parse tree (D-DSPT). Evaluation on the ACE 2003 corpus shows that the D-DSPT outperforms all previous parse tree structures on anaphoricity determination, and that applying our anaphoricity determination module in coreference resolution achieves the so far best performance.

关键词： Syntactics

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Combining event-level and cross-event semantic information for event-oriented relation classification by SCNN 15th

Combining event-level and cross-event semantic information f...

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15th China National Conference on Chinese Computational Linguistics, CCL 2016 and 4th International Symposium on Natural Language processing Based on Naturally Annotated Big Data, NLP-NABD 2016

作者： Ding, Siyuan Hong, Yu Zhu, Shanshan Yao, Jianmin Zhu, Qiaoming Provincial Key Laboratory of Computer Information Processing Technology Soochow University Suzhou China

ISBN: (纸本)9783319476735

Previous researches on event relation classification primarily rely on lexical and syntactic features. In this paper, we use a Shallow Convolutional Neural Network (SCNN) to extract event-level and cross-event semantic features for event relation classification. On the one hand, the shallow structure alleviates the over-fitting problem caused by the lack of diverse relation samples. On the other hand, the utilization and combination of event-level and cross-event semantic information help improve relation classification. The experimental results show that our approach outperforms the state of the art. © Springer International Publishing AG 2016.

关键词： Neural networks

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A survey on video-based vehicle behavior analysis algorithms

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Journal of Multimedia 2012年第3期7卷 223-230页

作者： Wu, Jian Cui, Zhi-Ming Chen, Jian-Ming Zhang, Guang-Ming The Institute of Intelligent Information Processing and Application Soochow University Suzhou 215006 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou 215006 China Jiangsu Yihe Traffic Engineering Co. Ltd Suzhou 215002 China

Analysis of the Vehicle Behavior is mainly to analyze and identify the vehicles' motion pattern, and describe it by the use of natural language. It is a considerable challenge to analyze and describe the vehicles' behavior in a complex scene. This paper first hackles the development history of the intelligent transportation system and analysis of vehicles' behavior, and then conducts an indepth analysis of current situation of vehicle behavior analysis from the video processing, video analysis and video understanding, summarizes the achieved results and the key technical problems, and prospects the future development of vehicle behavior analysis. © 2012 ACADEMY PUBLISHER.

关键词： Video signal processing

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Coverage Enhancement Strategy Based on Novel Perception and Co-evolution for Multimedia Sensor Networks

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电子学报(英文版) 2013年第1期22卷 135-140页

作者： XIAO Fu WANG Jing SUN Lijuan WANG Ruchuan GUO Jian College of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing 210003 China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing 210003 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou 215006 China

Coverage enhancement is one of the hot research topics in wireless multimedia sensor net- works. A novel Coverage-enhancing algorithm based on three-dimensional Directional perception and co-evolution (DPCCA) is proposed in multimedia sensor networks on the basis of the model whose pitch angle and deviation angle can be adjusted. Based on the proposed elliptical cone sensing model, we can derive the coverage area of the node and calculate the optimal pitch angle according the information of monitoring area and the nodes, and then the deviation angle is optimized based on co-evolution al- gorithm, which eliminate the overlapped and blind sensing area effectively. A set of simulations demonstrate the ef- fectiveness of our algorithm in coverage ratio.

关键词：无线多媒体传感器网络网络覆盖协同进化感知增强算法网络工程测量模型

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Restoration-enhanced reversible information steganography network for CT images in the Internet of Medical Things

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Chen, Kai Chen, Yang Coatrieux, Gouenou Wu, Jiasong Coatrieux, Jean-Louis School of Cyber Science and Engineering Southeast University Nanjing210096 China Southeast University Nanjing210096 China IMT Atlantique Inserm LaTIM UMR1101 Brest29000 France Laboratoire Traitement du Signal et de L'Image Université de Rennes 1 RennesF-35000 France Centre de Recherche en Information Biomédicale Sino-francais Rennes35042 France National Institute for Health and Medical Research RennesF-35000 France Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing School of Computer Science and Engineering Southeast University Nanjing210096 China Jiangsu Key Laboratory of Molecular and Functional Imaging Department of Radiology Zhongda Hospital Southeast University Nanjing210009 China Ministry of Education Nanjing210096 China Ministry of Education Nanjing210096 China

Smart health and emotional care powered by the Internet of Medical Things (IoMT) are revolutionizing the healthcare industry by adopting several technologies related to multimodal physiological data collection, communication, intelligent automation, and efficient manufacturing. The security of medical images containing private patient information distributed in IoMT is of paramount importance in social communication, and guaranteeing their reliability has attracted widespread attention. Some existing medical image steganography methods fail to guarantee the original image's integrity, authenticity, and lossless restoration. To solve this problem, a restoration-enhanced reversible adaptive information steganography network, MediSR-Net, is proposed. Specifically, MediSR-Net consists of an analysis module and an encoding module. The image degradation-restoration strategy is exploited by the analysis module to improve the effectiveness of information embedding and perceptual field to reduce the error of pixel prediction. An information distillation and attention machine-based approach are adopted to achieve degradation-restoration of CT medical images at any scale and focus more on the degradation-restoration effect with small magnification factors. The encoding module is responsible for the embedding and extraction of privacy information. Ten state-of-the-art are compared with the MediSR-Net method concerning steganographic effect, embedding rate, distortion analysis, and prediction error. The qualitative and quantitative results demonstrate the effectiveness and superiority of MediSR-Net. © 1963-2012 IEEE.

关键词： Steganography

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Sub-pixel change detection for urban land-cover analysis via multi-temporal remote sensing images

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Geo-Spatial information Science 2014年第1期17卷 26-38页

作者： Peijun DU Sicong LIU Pei LIU Kun TAN Liang CHENG Key Laboratory for Satellite Mapping Technology and Application of National Administration of Surveying Mapping and GeoinformationNanjing UniversityNanjing CityJiangsu ProvinceP.R.China Department of Information Engineering and Computer Science University of TrentoTrentoItaly Jiangsu Provincial Key Laboratory for Resources and Environment Information Engineering China University of Mining and TechnologyXuzhouJiangsu ProvinceP.R.China

Conventional change detection approaches are mainly based on per-pixel processing,which ignore the sub-pixel spectral variation resulted from spectral *** for medium-resolution remote sensing images used in urban landcover change monitoring,land use/cover components within a single pixel are usually complicated and heterogeneous due to the limitation of the spatial ***,traditional hard detection methods based on pure pixel assumption may lead to a high level of omission and commission errors inevitably,degrading the overall accuracy of change *** order to address this issue and find a possible way to exploit the spectral variation in a sub-pixel level,a novel change detection scheme is designed based on the spectral mixture analysis and decision-level *** spectral mixture model is selected for spectral unmixing,and change detection is implemented in a sub-pixel level by investigating the inner-pixel subtle changes and combining multiple composition *** proposed method is tested on multi-temporal Landsat Thematic Mapper and China–Brazil Earth Resources Satellite remote sensing images for the land-cover change detection over urban *** effectiveness of the proposed approach is confirmed in terms of several accuracy indices in contrast with two pixel-based change detection methods(*** vector analysis and principal component analysis-based method).In particular,the proposed sub-pixel change detection approach not only provides the binary change information,but also obtains the characterization about change direction and intensity,which greatly extends the semantic meaning of the detected change targets.

关键词： change detection sub-pixel level processing multi-temporal images spectral mixture model back propagation neural network remote sensing

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