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arXiv 2019年

作者： Liu, Jingxian Xiong, Ke Fan, Pingyi Zhong, Zhangdui Letaief, Khaled Ben School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China Department of Electronic Engineering Tsinghua University Beijing100084 China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Hong Kong University of Science and Technology Hong Kong

This paper studies a simultaneous wireless information and power transfer (SWIPT)-aware fog computing network, where a multiple antenna fog function integrated hybrid access point (F-HAP) transfers information and energy to multiple heterogeneous single-antenna sensors and also helps some of them fulfill computing tasks. By jointly optimizing energy and information beamforming designs at the F-HAP, the bandwidth allocation and the computation offloading distribution, an optimization problem is formulated to minimize the required energy under communication and computation requirements, as well as energy harvesting constraints. Two optimal designs, i.e., fixed offloading time (FOT) and optimized offloading time (OOT) designs, are proposed. As both designs get involved in solving non-convex problems, there are no known solutions to them. Therefore, for the FOT design, the semidefinite relaxation (SDR) is adopted to solve it. It is theoretically proved that the rank-one constraints are always satisfied, so the global optimal solution is guaranteed. For the OOT design, since its non-convexity is hard to deal with, a penalty dual decomposition (PDD)-based algorithm is proposed, which is able to achieve a suboptimal solution. The computational complexity for two designs are analyzed. Numerical results show that the partial offloading mode is superior to binary benchmark modes. It is also shown that if the system is with strong enough computing capability, the OOT design is suggested to achieve lower required energy;Otherwise, the FOT design is preferred to achieve a relatively low computation complexity. Copyright © 2019, The Authors. All rights reserved.

关键词： Fog computing

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Optimal online transmission policy in wireless powered networks with urgency-aware age of information

arXiv

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arXiv 2019年

作者： Lu, Yang Xiong, Ke Fan, Pingyi Zhong, Zhangdui Letaief, Khaled Ben School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China Department of Electronic Engineering Tsinghua University Beijing100084 China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Hong Kong University of Science and Technology Hong Kong

This paper investigates the age of information (AoI) for a radio frequency (RF) energy harvesting (EH) enabled network, where a sensor first scavenges energy from a wireless power station and then transmits the collected status update to a sink node. To capture the thirst for the fresh update becoming more and more urgent as time elapsing, urgency-aware AoI (U-AoI) is defined, which increases exponentially with time between two received updates. Due to EH, some waiting time is required at the sensor before transmitting the status update. To find the optimal transmission policy, an optimization problem is formulated to minimize the long-term average U-AoI under constraint of energy causality. As the problem is non-convex and with no known solution, a two-layer algorithm is presented to solve it, where the outer loop is designed based on Dinklebach's method, and in the inner loop, a semi-closed-form expression of the optimal waiting time policy is derived based on Karush-Kuhn-Tucker (KKT) optimality conditions. Numerical results shows that our proposed optimal transmission policy outperforms the the zero time waiting policy and equal time waiting policy in terms of long-term average U-AoI, especially when the networks are non-congested. It is also observed that in order to achieve the lower U-AoI, the sensor should transmit the next update without waiting when the network is congested while should wait a moment before transmitting the next update when the network is non-congested. Additionally, it also shows that the system U-AoI first decreases and then keep unchanged with the increments of EH circuit's saturation level and the energy outage probability. Copyright © 2019, The Authors. All rights reserved.

关键词： Energy harvesting

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NPM: An Anti-attacking Analysis Model of the MTD system Based on Martingale Theory

NPM: An Anti-attacking Analysis Model of the MTD system Base...

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IEEE Symposium on computers and Communications (ISCC)

作者： Xin Yang Hui Li Han Wang Shenzhen Key Lab of Information Theory & Future Network Arch Future Network PKU Lab of National Major Research Infrastructure PKU Inst.of Big Data Technology Shenzhen Engineering Lab of Converged Networking Technology Huawei & PKU Jointly Engineering Lab of Future Network Based on SDN School of Electronic and Computer Engineering Peking University Shenzhen China

Moving target defense (MTD) techniques are effective solutions to improve the network security by continuously reconfiguring the system setting. On the other hand, continuously transforming also increase the cost of defenders, so it is important to analyze the effectiveness of MTDs compared with their cost. Current researches lack of analyzing the effectiveness by mathematical theory compared with analyzing by experiment. Motivated by the above, we propose a novel three-dimension model named NPM jointly use N-version programming, Poisson process, Markov chain and martingale theory to analyze the effectiveness of the proposed MTD model. Our analysis points out the difficulty for a successful adversary to defeat the MTD system, which is related to the system configuration, such as the number of executors and the judgment criterion in every node, the transforming period and rang of system MTD transformation. Finally, we give advices on the design of the system in the daily defense and the attacked defense, with the goal of guaranteeing security with minimal cost.

关键词： Security Analytical models Programming Markov processes Mathematical model computers Computational modeling

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Spatial image steganography based on generative adversarial network

arXiv

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arXiv 2018年

作者： Yang, Jianhua Liu, Kai Kang, Xiangui Wong, Edward K. Shi, Yun-Qing Guangdong Key Lab of Information Security School of Data and Computer Science Sun Yat-Sen University Guangzhou510006 China Department of Computer Science and Engineering New York University Tandon School of Engineering BrooklynNY11201 United States Department of ECE New Jersey Institute of Technology NewarkNJ07102 United States

With the recent development of deep learning on steganalysis, embedding secret information into digital images faces great challenges. In this paper, a secure steganography algorithm by using adversarial training is proposed. The architecture contain three component modules: a generator, an embedding simulator and a discriminator. A generator based on U-NET to translate a cover image into an embedding change probability is proposed. To fit the optimal embedding simulator and propagate the gradient, a function called Tanh-simulator is proposed. As for the discriminator, the selection-channel awareness (SCA) is incorporated to resist the SCA based steganalytic methods. Experimental results have shown that the proposed framework can increase the security performance dramatically over the recently reported method ASDL-GAN, while the training time is only 30% of that used by ASDL-GAN. Furthermore, it also performs better than the hand-crafted steganographic algorithm S-UNIWARD. Copyright © 2018, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

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The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H. Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A. Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J.G. Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, H Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierra Sur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen keskus (Centre for Social Data Science) Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Karolinska Institutet (Karolinska Institute) Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics University of Medical Sciences Ondo Ondo Nigeria Department of Veteri

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

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Synergistic interactions promote behavior spreading and alter phase transitions on multiplex networks

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Physical Review E 2018年第2期97卷 022311-022311页

作者： Quan-Hui Liu Wei Wang Shi-Min Cai Ming Tang Ying-Cheng Lai Web Sciences Center School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China Big Data Research Center University of Electronic Science and Technology of China Chengdu 611731 China Laboratory for the Modeling of Biological and Socio-technical Systems Northeastern University Boston Massachusetts 02115 USA College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Center for Polymer Studies and Department of Physics Boston University Boston Massachusetts 02215 USA School of Information Science Technology East China Normal University Shanghai 200241 China School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA

Synergistic interactions are ubiquitous in the real world. Recent studies have revealed that, for a single-layer network, synergy can enhance spreading and even induce an explosive contagion. There is at the present a growing interest in behavior spreading dynamics on multiplex networks. What is the role of synergistic interactions in behavior spreading in such networked systems? To address this question, we articulate a synergistic behavior spreading model on a double layer network, where the key manifestation of the synergistic interactions is that the adoption of one behavior by a node in one layer enhances its probability of adopting the behavior in the other layer. A general result is that synergistic interactions can greatly enhance the spreading of the behaviors in both layers. A remarkable phenomenon is that the interactions can alter the nature of the phase transition associated with behavior adoption or spreading dynamics. In particular, depending on the transmission rate of one behavior in a network layer, synergistic interactions can lead to a discontinuous (first-order) or a continuous (second-order) transition in the adoption scope of the other behavior with respect to its transmission rate. A surprising two-stage spreading process can arise: due to synergy, nodes having adopted one behavior in one layer adopt the other behavior in the other layer and then prompt the remaining nodes in this layer to quickly adopt the behavior. Analytically, we develop an edge-based compartmental theory and perform a bifurcation analysis to fully understand, in the weak synergistic interaction regime where the dynamical correlation between the network layers is negligible, the role of the interactions in promoting the social behavioral spreading dynamics in the whole system.

关键词： Cascades Percolation phase transition Spreading

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Energy efficient simulation computing of electrocardiogram with TK1 Board

IAENG International Journal of Computer Science

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IAENG International Journal of computer Science 2018年第1期45卷 177-187页

作者： Shen, Wenfeng Qiu, Feng Hu, Yaopeng Shen, Yanghua Zhu, Xin School of Computer Engineering Science Shanghai Institute for Advanced Communication and Data Science Shanghai University Nanchen Road Shanghai200444 China Department of Physiology School of Medicine Fukuoka University Fukuoka Fukuoka814-0180 Japan Biomedical Information Technology Lab The University of Aizu Aizu-Wakamatsu Fukushima965-8580 Japan

The computer simulation in cardiac models has become an increasingly powerful tool in the study of cardiac electrophysiology. To precise analysis the electrophysiological mechanism, it not only demands a significant computing capacity due to its heavy workload, but also has to be available and convenient in many medical experiments, which seems to be contradictory in a conventional computer perspective. However, with the emergence of new heterogeneous computing platforms, a surging number of scientific applications are dramatically improving upon the energy efficiency of existing solutions. Under such circumstances, this paper presents a metric method for energy efficiency and several optimizing strategies, to fully exploit the energy efficiency of applications. To verify these approaches, we describe a new experience adapting the computer simulation of electrocardiogram(ECG) based on a whole-heart model for a Jetson Tegra K1(TK1) System on Chip(SoC) board, which was previously only possible on desktop-level platforms. The experiments are conducted to evaluate the performance and power draw in different situations on different platforms. In order to investigate the characteristics of unified memory in TK1 board, an extra experiment was provided. The experimental results show that our proposed methods combining with the new hardware can lead to a encouraging consequence.

关键词： Electrocardiograms

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Automatic Chinese Multiple-Choice Question Generation for Human Resource Performance Appraisal

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Procedia computer Science 2018年 139卷 165-172页

作者： Pei Quan Yong Shi Lingfeng Niu Ying Liu Tianlin Zhang School of Computer and Control Engineering University of Academy of Sciences Beijing 100190 China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China Key Lab of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China College of Information Science and Technology University of Nebraska at Omaha NE 68182 USA

Performance appraisal has always been an important research topic in human resource management. A reasonable performance appraisal plan lays a solid foundation for the development of an enterprise. Especially as globalization and technology advance, in order to meet the fast-changing strategic goals and increasing cross-functional tasks, enterprises face new challenges in performance appraisal. How to improve employees’ ability to accept new knowledge efficiently and constantly has been an urgent problem for enterprises. In this paper, we propose an automatic method which generation multiple-choice questions by utilizing the relations between different terminology. Graphical model is used to extract core concept from different corpus while word embedding technology is used to indicate the relevant relations. Experimental results demonstrate that the proposed question generation method outperforms the traditional manual method in both efficiency and confusion.

关键词： Human resource management multiple-choice question generation natural language processing word embedding

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Taking the pulse of COVID-19: A spatiotemporal perspective

arXiv

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arXiv 2020年

作者： Yang, Chaowei Sha, Dexuan Liu, Qian Li, Yun Lan, Hai Guan, Weihe Wendy Hu, Tao Li, Zhenlong Zhang, Zhiran Thompson, John Hoot Wang, Zifu Wong, David Ruan, Shiyang Yu, Manzhu Richardson, Douglas Zhang, Luyao Hou, Ruizhi Zhou, You Zhong, Cheng Tian, Yifei Beaini, Fayez Carte, Kyla Flynn, Colin Liu, Wei Pfoser, Dieter Bao, Shuming Li, Mei Zhang, Haoyuan Liu, Chunbo Jiang, Jie Du, Shihong Zhao, Liang Lu, Mingyue Li, Lin Zhou, Huan NSF Spatiotemporal Innovation Center George Mason Univ. FairfaxVA22030 United States Department of Geography and GeoInformation Science George Mason Univ. FairfaxVA22030 United States Department of Geographical Sciences University of Maryland College ParkMD20742 United States Center for Geographic Analysis Harvard University CambridgeMA02138 United States Geoinformation and Big Data Research Lab Department of Geography University of South Carolina ColumbiaSC29208 United States Chinese Academy of Surveying and Mapping Beijing China Cloud Compute and Storage Operations Information Technology Services George Mason University FairfaxVA22030 United States Department of Geography Pennsylvania State University State CollegePA16801 United States School of Business Management East China Normal University Zhongshanbei Road Shanghai3663 China School of Mathematical Sciences East China Normal University Zhongshanbei Road Shanghai3663 China Department of Psychology George Mason University FairfaxVA22030 United States Department of Computer Science George Mason University FairfaxVA22030 United States Department of Information Technology George Mason University FairfaxVA22030 United States Department of Biology George Mason University FairfaxVA22030 United States College of Land Science and Technology China Agricultural University Beijing100083 China China Data Institute Ann ArborMI United States Institute of Remote Sensing and GIS Peking University Beijing100871 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and Architecture Beijing100044 China School of Geographical Sciences Nanjing University of Information Science & Technology 219 Ningliu Road Nanjing Jiangsu210044 China School of Resource and Environmental Sciences Wuhan University 129 Luoyu Rd Wuhan Hubei430079 China School of Geodesy a

The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, and most states of the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., and New York City became an epicenter of the pandemic by the end of March. In response to this national and global emergency, the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implemented strategies to rapidly respond to this crisis, for supporting research, saving lives, and protecting the health of global citizens. This perspective paper presents our collective view on the global health emergency and our effort in collecting, analyzing, and sharing relevant data on global policy and government responses, geospatial indicators of the outbreak and evolving forecasts;in developing research capabilities and mitigation measures with global scientists, promoting collaborative research on outbreak dynamics, and reflecting on the dynamic responses from human societies. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

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Author Correction:data augmentation in microscopic images for material data mining

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npj Computational Materials 2020年第1期6卷 476-476页

作者： Boyuan Ma Xiaoyan Wei Chuni Liu Xiaojuan Ban Haiyou Huang Hao Wang Weihua Xue Stephen Wu Mingfei Gao Qing Shen Michele Mukeshimana Adnan Omer Abuassba Haokai Shen Yanjing Su Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing China School of Materials Science and Engineering University of Science and Technology Beijing Beijing China School of Materials Science and Technology Liaoning Technical University Liaoning China The Institute of Statistical Mathematics Research Organization of Information and Systems Tachikawa Tokyo Japan National Intellectual Property Administration Beijing China Faculty of Engineering Sciences University of Burundi Bujumbura Burundi Faculty of Engineering and Technology Palestine Technical University – Kadoorie Tulkarem Palestine College of Information Science and Engineering China University of Petroleum Beijing China Key Lab of Petroleum Data Mining China University of Petroleum Beijing China

The original version of this article omitted the following from the Acknowledgements:“This work was supported by Beijing Top Discipline for Artificial Intelligent Science and engineering,University of Science and Tec... 详细信息

关键词： HTML knowledge mining

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