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arXiv 2020年

作者： Wang, Sihua Chen, Mingzhe Yin, Changchuan Saad, Walid Hong, Choong Seon Cui, Shuguang Vincent Poor, H. Beijing Laboratory of Advanced Information Network Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States Department of Computer Science and Engineering Kyung Hee University Korea Republic of Chinese University of Hong Kong Shenzhen518172 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States

In this paper, the problem of minimizing energy and time consumption for task computation and transmission is studied in a mobile edge computing (MEC)-enabled balloon network. In the considered network, each user needs to process a computational task in each time instant, where high-altitude balloons (HABs), acting as flying wireless base stations, can use their powerful computational abilities to process the tasks offloaded from their associated users. Since the data size of each user's computational task varies over time, the HABs must dynamically adjust the user association, service sequence, and task partition scheme to meet the users' needs. This problem is posed as an optimization problem whose goal is to minimize the energy and time consumption for task computing and transmission by adjusting the user association, service sequence, and task allocation scheme. To solve this problem, a support vector machine (SVM)-based federated learning (FL) algorithm is proposed to determine the user association proactively. The proposed SVM-based FL method enables each HAB to cooperatively build an SVM model that can determine all user associations without any transmissions of either user historical associations or computational tasks to other HABs. Given the prediction of the optimal user association, the service sequence and task allocation of each user can be optimized so as to minimize the weighted sum of the energy and time consumption. Simulations with real data of city cellular traffic from the OMNILab at Shanghai Jiao Tong University show that the proposed algorithm can reduce the weighted sum of the energy and time consumption of all users by up to 16.1% compared to a conventional centralized method. Copyright © 2020, The Authors. All rights reserved.

关键词： Support vector machines

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Design and implementation of augmented reality cloud platform system for 3D entity objects 8

Design and implementation of augmented reality cloud platfor...

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8th International Congress of information and Communication Technology, ICICT 2018

作者： He, Zhimin Peng, Lin Han, Haiyun Xu, Min Wang, Gang Bao, Xingchuan Yu, Hai Hou, Zhansheng Wang, He Zhu, Liang Zhang, Zehao Global Energy Interconnection Research Institute Nanri Road 8 Nanjing210003 China State Grid Key Laboratory of Information and Network Security Beiqijia Beijing100000 China

This project is about design and implementation of Augmented Reality cloud recognition power platform for 3D Entity Objects. Typical power operations include equipment inspection, equipment maintenance, emergency repair, reverse brake operation, line operation and so on. Combining with the characteristics of electric power operation site, to improve the on-site operation mode, through the interactive collaboration such as terminal multidimensional exhibition, backstage data fusion, and custom services, the clouds recognition system will provide grid on-site an automatic and intelligent new solution based on AR. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Augmented reality

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An Associated Behavior Sequence Based User Authentication Approach in M2M Mobile Terminals

An Associated Behavior Sequence Based User Authentication Ap...

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IEEE Global Communications Conference

作者： Congcong Shi Miao Du Weidong Lu Sanglu Lu State Key Laboratory for Novel Software Technology Nanjing University Nanjing China State Grid Key Laboratory of Information & Network Security Global Energy Interconnection Research Institute co. Ltd Beijing China Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

With the rapid development of machine-to-machine (M2M) mobile smart terminals, M2M services can be used in a wide range of industries, including such as telemedicine, remote meter reading and public security. Since different industries and enterprise users have different requirements for M2M specific applications, the security identity authentication of M2M mobile terminals is particularly worthy of attention. Existing methods can effectively solve the unsustainable problem of one-time verification, however they cannot address the dynamic relevance characteristics of user behavior sufficiently. Thus, the accuracy of user identity authentication needs to be further improved. In this paper, we propose a terminal identity authentication technology based on user association behavior analysis. In order to identify the abnormal login during each behavior process of authenticated user, we take largest coincident part of the user behavior sequence and short coincide into consideration. In addition, we propose a Similarity-based Behavior Sequence Similarity Algorithm (BCS-SSA) based on the traditional sequence pattern of Behavior Common Subsequence. The experimental results demonstrate that the proposed method can effectively improve the accuracy of user's behavioral sequence, and prove the uniqueness of different sequences on the other hand.

关键词： Authentication Machine-to-machine communications Correlation Dynamic programming Industries Password

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A review of uncertainty quantification in deep learning: Techniques, applications and challenges

arXiv

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arXiv 2020年

作者： Abdar, Moloud Pourpanah, Farhad Hussain, Sadiq Rezazadegan, Dana Liu, Li Ghavamzadeh, Mohammad Fieguth, Paul Cao, Xiaochun Khosravi, Abbas Rajendra Acharya, U. Makarenkov, Vladimir Nahavandi, Saeid Deakin University Australia College of Mathematics and Statistics Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Shenzhen518060 China Dibrugarh University Dibrugarh India Department of Computer Science and Software Engineering Swinburne University of Technology Melbourne Australia Center for Machine Vision and Signal Analysis University of Oulu Oulu Finland Google research United States Department of Systems Design Engineering University of Waterloo Waterloo Canada State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China Department of Electronics and Computer Engineering Ngee Ann Polytechnic Clementi Singapore Department of Computer Science University of Quebec in Montreal MontrealQC Canada

—Uncertainty quantification (UQ) plays a pivotal role in the reduction of uncertainties during both optimization and decision making, applied to solve a variety of real-world applications in science and engineering. Bayesian approximation and ensemble learning techniques are two of the most widely-used UQ methods in the literature. In this regard, researchers have proposed different UQ methods and examined their performance in a variety of applications such as computer vision (e.g., self-driving cars and object detection), image processing (e.g., image restoration), medical image analysis (e.g., medical image classification and segmentation), natural language processing (e.g., text classification, social media texts and recidivism risk-scoring), bioinformatics, etc. This study reviews recent advances in UQ methods used in deep learning, investigates the application of these methods in reinforcement learning, and highlight the fundamental research challenges and directions associated with the UQ field. Copyright © 2020, The Authors. All rights reserved.

关键词： Image segmentation

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The Cognition Is Not Enough:Another Look on Existing Interesting Points Chosen Methods

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Chinese Journal of Electronics 2017年第2期26卷 416-423页

作者： FAN Guangjun ZHOU Yongbin ZHANG Hailong FENG Dengguo State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of Sciences State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Sciences

For classical template attacks,many papers suggested a guideline of choosing interesting points which is still not *** to now,many different methods of choosing interesting points were ***,it is still unclear that which approach will lead to the best classification performance for template *** comprehensively evaluate and compare the classification performance of template attacks when using different methods of choosing interesting *** results show that the Correlation power analysis based method and the Sum of squared pairwise t-differences based method will lead to the best classification *** find that some methods of choosing interesting points provide the same results in the same ***,we correctly prove the guideline of choosing interesting points is correct by presenting a new way of conducting template attacks.

关键词： Side-channel attacks Power analysis attacks Template attacks Interesting points

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Intelligent recommendation of related items based on naive bayes and collaborative filtering combination model

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Journal of Physics: Conference Series 2020年第1期1682卷

作者： Wei Wei Zhuo Wang Changlong Fu Robertas Damaševičius Rafal Scherer Marcin Wožniak School of Computer Science and Engineering Xi'an University of Technology Xi'an 710048 Shaanxi Key Laboratory for Network Computing and Security Technology China.

Nowadays, data plays a unique role in various fields. Based on the background of the era of big data, this paper collects user evaluations of certain commodities and labels the evaluations into positive emotions and negative emotions. We propose an intelligent recommendation algorithm based on Naive Bayes algorithm, which determines the user's preference for a product according to the user's opinion on a product, then uses the collaborative filtering algorithm to recommend other similar products according to the similarity between the product and other products, so as to realize the recommendation of other similar products. This can not only help users choose more goods in the environment, but also maximize the value of goods. In this paper, bayesian classifier was used for prediction, and the accuracy reached about 97%.

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A novel Image security Protection Method Based on DCT Compression Theory and Hyper-chaotic Mapping

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Journal of Physics: Conference Series 2021年第1期2066卷

作者： Xianglian Xue Haiyan Jin School of Computer Science and Engineering Xi'an University of Technology Xi'an 710077Shaanxi China Shaanxi University of Chinese Medicine Xianyang712046Shaanxi China Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an710077Shaanxi China

This paper studies the current situation of image compression encryption and analyzes the influence of low frequency (DC coefficient) and high frequency (AC coefficient) on image structure in DCT transformation. Based on this, a novel image security protection method based on DCT compression theory and hyper-chaotic mapping is proposed. First, the position of the pixel of the original image is disturbed, and converts the image from spatial domain into frequency domain by the two-dimensional DCT transformation and quantization. Second, change the pixel values by modifying the values of the sign bit of AC coefficient and DC coefficient. At last, the encrypted image is obtained by carrying out inverse quantization, inverse transformation and reverse operation by bit.

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Automatic Text Summarization Based on Transformer and Switchable Normalization

Automatic Text Summarization Based on Transformer and Switch...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Tao Luo Kun Guo Hong Guo College of Mathematics and Computer Sciences Fuzhou University Fuzhou China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China Key Laboratory of Spatial Data Mining & Information Sharing Ministry of Education Fuzhou University Fuzhou China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

With the development of text summarization research, the methods based on RNN with the Encoder-Decoder model gradually become the mainstream. However, RNN tends to forget previous context information and leads to the lack of original information. That will reduce the accuracy of the generated summarizations. The Transformer model uses the self-attention mechanism to encode and decode historical information so that it can achieve better performance than RNN in learning context information. In this paper, a text summarization model based on transformer and switchable normalization is proposed. The accuracy of the model is improved by optimizing the normalization layer. Compared with other models, the new model has a great advantage in understanding words' semantics and associations. Experimental results in English Gigaword dataset show that the proposed model can achieve high ROUGE values and make the summarization more readable.

关键词： Decoding Switches Context modeling Vocabulary Task analysis Data mining Semantics

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Survey of recent progress in semantic image segmentation with CNNs

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Science China(information Sciences) 2018年第5期61卷 107-124页

作者： Qichuan GENG Zhong ZHOU Xiaochun CAO State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Sciences

In recent years, convolutional neural networks(CNNs) are leading the way in many computer vision tasks, such as image classification, object detection, and face recognition. In order to produce more refined semantic image segmentation, we survey the powerful CNNs and novel elaborate layers, structures and strategies, especially including those that have achieved the state-of-the-art results on the Pascal VOC 2012 semantic segmentation challenge. Moreover, we discuss their different working stages and various mechanisms to utilize the structural and contextual information in the image and feature spaces. Finally, combining some popular underlying referential methods in homologous problems, we propose several possible directions and approaches to incorporate existing effective methods as components to enhance CNNs for the segmentation of specific semantic objects.

关键词： semantic image segmentation CNN Pascal VOC 2012 challenge multi-granularity features construction of contextual relationships

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Discussion and testing of 802.11ah wireless communication in intelligent substation 2

Discussion and testing of 802.11ah wireless communication in...

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2nd IEEE International Conference on Energy Internet, ICEI 2018

作者： Zheng, Zhe Qiao, Lei Wang, Liang Cui, Wenpeng Guo, Jinghong Research Department of Smart Chip Global Energy Interconnection Research Institute Co. Ltd Beijing China State Grid Key Laboratory of Information and Network Security State Grid Laboratory of Electric Power Communication Network Technology Beijing China

ISBN: (纸本)9781538641316

In response to the application and requirements of all things seamless interconnection, International Institute of Electrical and Electronics Engineers (IEEE) has put forward a new generation of standard 802.11 ah, working in Sub-1GHz frequencies, achieving low power consumption and larger wireless local area network coverage. It improves the performance of Wi-Fi which easily affected by the building block, transmission distance and coverage. The new features of 802.11ah makes it more suitable for use in the smart grid. Intelligent substation adopts advanced, reliable, integrated and environment-friendly intelligent equipment. It supports grid real-time controlling, smart adjustment, online analysis and decision-making, collaboration and interaction. All the basic operations, including the information collection, measurement, control, protection, metering and monitoring, are taken automatically. In this paper, the feasibility of the 802.11ah wireless communication applying in intelligent substation is discussed. Besides, the actual performance of 802.11ah module prototype in 110kV substation has been tested. The results are analyzed, further studies and improvements are suggested. © 2018 IEEE.

关键词： Internet of things

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