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3rd IEEE International Conference on Big Data Analysis, ICBDA 2018

作者： Zhou, Aiping Zhu, Huisheng Liu, Lijun Zhu, Chengang School of Computer Science and Technology Taizhou University Taizhou China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing China School of Computer Science and Engineering Southeast University Nanjing China

ISBN: (纸本)9781538647936

Detection of super nodes is the task of determining hosts which contact with numerous hosts in the time window or have significant connection change between two continuous time windows. This is a basic problem with many practical applications, for example, traffic measurement and anomaly detection. The main challenge is to detect super nodes in real time in the constraint of limited memory. To solve the problem, we propose a novel solution to detect super nodes based on parallel sketch using connection metrics (connection number and connection change), called PSketch. It constructs a novel data structure, and combines connection number and connection change, so that the accuracy and time efficiency of our algorithm is improved obviously. The experimental results illustrate that our algorithm is superior to CSE (Compact Spread Estimator) and JDS (Joint Data Streaming and Sampling) in terms of accuracy, memory utilization and time efficiency. © 2018 IEEE.

关键词： Anomaly detection

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Relevant emotion ranking from text constrained with emotion relationships

Relevant emotion ranking from text constrained with emotion ...

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2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018

作者： Zhou, Deyu Yang, Yang He, Yulan School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China School of Engineering and Applied Science Aston University United Kingdom

ISBN: (纸本)9781948087278

Text might contain or invoke multiple emotions with varying intensities. As such, emotion detection, to predict multiple emotions associated with a given text, can be cast into a multi-label classification problem. We would like to go one step further so that a ranked list of relevant emotions are generated where top ranked emotions are more intensely associated with text compared to lower ranked emotions, whereas the rankings of irrelevant emotions are not important. A novel framework of relevant emotion ranking is proposed to tackle the problem. In the framework, the objective loss function is designed elaborately so that both emotion prediction and rankings of only relevant emotions can be achieved. Moreover, we observe that some emotions co-occur more often while other emotions rarely coexist. Such information is incorporated into the framework as constraints to improve the accuracy of emotion detection. Experimental results on two real-world corpora show that the proposed framework can effectively deal with emotion detection and performs remarkably better than the state-of-The-Art emotion detection approaches and multi-label learning methods. © 2018 The Association for Computational Linguistics.

关键词： Classification (of information)

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Secrecy capacity bounds for visible light communications with signal-dependent noise

arXiv

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arXiv 2021年

作者： Wang, Jin-Yuan Fu, Xian-Tao Wang, Jun-Bo Lin, Min Cheng, Julian Alouini, Mohamed-Slim Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China National Mobile Communications Research Laboratory Southeast University Nanjing211111 China School of Engineering The University of British Columbia KelownaBCV1V 1V7 Canada Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In physical-layer security, one of the most fundamental issues is the secrecy capacity. The objective of this paper is to determine the secrecy capacity for an indoor visible light communication system consisting of a transmitter, a legitimate receiver and an eavesdropping receiver. In such a system, both signal-independent and signal-dependent Gaussian noises are considered. Under non-negativity and average optical intensity constraints, lower and upper secrecy capacity bounds are first derived by the variational method, the dual expression of the secrecy capacity, and the concept of "the optimal input distribution that escapes to infinity". Numerical results show that the secrecy capacity upper and lower bounds are tight. By an asymptotic analysis at large optical intensity, there is a small performance gap between the asymptotic upper and lower bounds. Then, by adding a peak optical intensity constraint, we further analyze the exact and asymptotic secrecy capacity bounds. Finally, the tightness of the derived bounds is verified by numerical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Asymptotic analysis

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Hierarchical Cooperative Caching in Fog Radio Access networks: A Brain Storm Optimization Approach

Hierarchical Cooperative Caching in Fog Radio Access Network...

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GLOBECOM 2020 - 2020 IEEE Global Communications Conference

作者： Xuan Chen Yanxiang Jiang Baotian Fan Fu-Chun Zheng Dusit Niyato Xiaohu You Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China School of Computer Engineering Nanyang Technological University (NTU) Singapore National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

In this paper, the cooperative caching problem in fog radio access networks (F-RANs) is investigated. To minimize the content request delay, we formulate the hierarchical cooperative caching optimization problem to find the optimal caching policy. Considering the non-deterministic polynomial hard (NP-hard) property of this problem, we propose a brain storm optimization (BSO) approach which utilizes the penaltybased fitness function in individuals evaluation to meet the storage capacity constraint and the genetic algorithm (GA) in new individuals generation to meet the integer constraint, respectively. To further reduce the computational complexity, we propose to implement the convergent operation in the objective space via individuals classification. Simulation results show that our proposed BSO-based hierarchical cooperative caching policy achieves remarkable performance in minimizing the content request delay.

关键词： Delays Cooperative caching Servers Optimization Computational complexity Storms Statistics

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COSINE:a software development model integrating collective intelligence, service and ecosystem

COSINE:a software development model integrating collective i...

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IEEE World Congress on Services (SERVICES)

作者： Hongbing Wang Tianjing Hong Jian Cao Haijun Zhang Changhai Nie Bo Cheng Yangfan He Li Kuang Dunwei Gong Wuhui Chen Yuliang Shi Deyi Huang School of Computer Science and Engineering and Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China Shanghai Jiaotong University Shanghai China College of Computer Science and Technology Harbin Institute of Technology Shenzhen China Nanjing University Nanjing China Wuhan University Wuhan China Research Institute of Network Technology Beijing University of Posts and Telecommunications Beijing China Software College Central South University Changsha China College of information and control engineering China University of mining and technology Xuzhou China College of data science and computer science Zhongshan University Guangzhou China Shandong University Jinan China Landry Company Shenzhen China

ISBN: (数字)9781728182032

ISBN: (纸本)9781728182049

With the development of the internet technology, a large amount of softwares have emerged to meet users' increasing needs. At the mean time, software systems have been faced with a problem that they must adapt to the dynamic network environment. It is obvious that a variety of software development models have been proposed in the past few decades. However, the majority of these methods are gradually unadaptable to new circumstances. In this paper, we proposed a new software development model integrating collective intelligence, service and ecosystem. On the one hand, we have introduced the model in detail. On the other hand, We took a practical example to demonstrate the effectiveness of the proposed model.

关键词： Adaptation models Biological system modeling Ecosystems Collective intelligence Software systems

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Coalition game based user association for mmWave mobile relay systems in rail traffic scenarios

arXiv

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arXiv 2021年

作者： Chen, Chen Niu, Yong Mao, Shiwen Zhang, Xiaodan Han, Zhu Ai, Bo Gao, Meilin Xiao, Huahua Wang, Ning The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States The School of Management Shenzhen Institute of Information Technology Shenzhen518172 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China The Tsinghua Space Center Tsinghua University Beijing100091 China The ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China

Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobile relay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nash-stable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a near-optimal performance and outperforms two baseline schemes in terms of average system throughput. Copyright © 2021, The Authors. All rights reserved.

关键词： Game theory

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An effective copy-move forgery detection algorithm using fractional quaternion Zernike moments and improved PatchMatch algorithm

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Journal of southeast university(English Edition) 2019年第4期35卷 431-439页

作者： Chen Beijing Gao Ye Yu Ming Wu Peng Shu Huazhong School of Computer and Software Nanjing University of Information Science and TechnologyNanjing 210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and TechnologyNanjing 210044China Key Laboratory of Computer Network Technology of Jiangsu Province Southeast University Nanjing 210096China Laboratory of Image Science and Technology Southeast UniversityNanjing 210096China

An effective algorithm is proposed to detect copy-move *** this algorithm,first,the PatchMatch algorithm is improved by using a reliable order-statistics-based approximate nearest neighbor search algorithm(ROSANNA)to modify the propagation ***,fractional quaternion Zernike moments(FrQZMs)are considered to be features extracted from color forged ***,the extracted FrQZMs features are matched by the improved PatchMatch *** experimental results on two publicly available datasets(FAU and GRIP datasets)show that the proposed algorithm performs better than the state-of-the-art algorithms not only in objective criteria F-measure value but also in ***,the proposed algorithm is robust to some attacks,such as additive white Gaussian noise,JPEG compression,rotation,and scaling.

关键词： quaternion fractional Zernike moments PatchMatch algorithm copy-move forgery detection

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A Smart Content Caching and Replacement Scheme for UAV-Assisted Fog Computing network

A Smart Content Caching and Replacement Scheme for UAV-Assis...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Xujie Li Jichang Shen Ying Sun Ziya Wang Xuedong Zheng College of Computer and Information Engineering Hohai University Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Key Lab for Wireless Sensor network and Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Nanjing China-Spacenet Satellite Telecom Co.Ltd China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

For unmanned aerial vehicle (UAV)-assisted fog computing system, content caching is an effective way to reduce network delay. How to smartly sense the future requirement of the user equipment and cache the contents in advance is a big challenge. Meanwhile, the impact of cache content size and other related factors on cache performance are often overlooked, which results in low cache hit ratio. Therefore, this paper proposes a smart caching and caching replacement scheme based on valuation function of content caching for UAV-assisted fog computing network. Firstly, the effect of the content popularity, content size and available cache storage space on system performance is analysed. Then the valuation function combing these factors is defined. Based on the presented valuation function, a smart content caching and caching replacement scheme for UAV-assisted fog computing network is proposed. Finally, the simulation results validate the effectiveness of the proposed scheme. The scheme can be applied into the design the deployment of the UVA-assisted fog computing network.

关键词： Edge computing Cost accounting Unmanned aerial vehicles Performance evaluation Delays Indexes Quality of service

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Question-answering aspect classification with hierarchical attention network 17th

Question-answering aspect classification with hierarchical a...

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17th China National Conference on Computational Linguistics, CCL 2018 and 6th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2018

作者： Wu, Hanqian Liu, Mumu Wang, Jingjing Xie, Jue Shen, Chenlin School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of Computer Network and Information Integration of Ministry of Education Southeast University Nanjing China NLP Lab School of Computer Science and Technology Soochow University Suzhou China Southeast University-Monash University Joint Graduate School Suzhou China

ISBN: (纸本)9783030017156

In e-commerce websites, user-generated question-answering text pairs generally contain rich aspect information of products. In this paper, we address a new task, namely Question-answering (QA) aspect classification, which aims to automatically classify the aspect category of a given QA text pair. In particular, we build a high-quality annotated corpus with specifically designed annotation guidelines for QA aspect classification. On this basis, we propose a hierarchical attention network to address the specific challenges in this new task in three stages. Specifically, we firstly segment both question text and answer text into sentences, and then construct (sentence, sentence) units for each QA text pair. Second, we leverage a QA matching attention layer to encode these (sentence, sentence) units in order to capture the aspect matching information between the sentence inside question text and the sentence inside answer text. Finally, we leverage a self-matching attention layer to capture different importance degrees of different (sentence, sentence) units in each QA text pair. Experimental results demonstrate that our proposed hierarchical attention network outperforms some strong baselines for QA aspect classification. © Springer Nature Switzerland AG 2018.

关键词： Text processing

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Saiqin Long Zhetao Li Zihao Liu Qingyong Deng Sangyoon Oh Nobuyoshi Komuro Key Laboratory of Hunan Province for Internet of Things and Information Security Hunan International Scientific and Technological Cooperation Base of Intelligent network School of Computer Science Xiangtan University Xiangtan China Science and Technology on Parallel and Distributed Processing Laboratory (PDL) National University of Defense Technology Changsha China Ajou University Suwon South Korea Graduate School of Advanced Integration Science Chiba University Chiba Japan

ISBN: (数字)9781728190747

ISBN: (纸本)9781728183824

Deduplication is a data redundancy elimination technique, designed to save system storage resources by reducing redundant data in cloud storage systems. With the development of cloud computing technology, deduplication has been increasingly applied to cloud data centers. However, traditional technologies face great challenges in big data deduplication to properly weigh the two conflicting goals of deduplication throughput and high duplicate elimination ratio. This paper proposes a similarity clustering-based deduplication strategy (named SCDS), which aims to delete more duplicate data without significantly increasing system overhead. The main idea of SCDS is to narrow the query range of fingerprint index by data partitioning and similarity clustering algorithms. In the data preprocessing stage, SCDS uses data partitioning algorithm to classify similar data together. In the data deletion stage, the similarity clustering algorithm is used to divide the similar data fingerprint superblock into the same cluster. Repetitive fingerprints are detected in the same cluster to speed up the retrieval of duplicate fingerprints. Experiments show that the deduplication ratio of SCDS is better than some existing similarity deduplication algorithms, but the overhead is only slightly higher than some high throughput but low deduplication ratio methods.

关键词： Cloud computing Clustering algorithms Estimation Fingerprint recognition Throughput Partitioning algorithms Classification algorithms

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