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Cyber-physical-social collaborative sensing： from single space to cross-space

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Frontiers of Computer Science 2018年第4期12卷 609-622页

作者： Fei YI zhiwen yu Huihui CHEN He DU Bin GUO School of Computer Science Northwestern Polytechnical University Xi'an 710072 China

The development of wireless sensor network ing, social networking, and wearable sensing techniques has advanced the boundaries of research on understanding so cial dynamics. Collaborative sensing, which utilizes diver sity sensing and computing abilities across different entities, has become a popular sensing and computing paradigm. In this paper, we first review the history of research in col laborative sensing, which mainly refers to single space col laborative sensing that consists of physical, cyber, and so cial collaborative sensing. Afterward, we extend this concept into crossspace collaborative sensing and propose a general reference framework to demonstrate the distinct mechanism of crossspace collaborative sensing. We also review early works in crossspace collaborative sensing, and study the de tail mechanism based on one typical research work. Finally, although crossspace collaborative sensing is a promising re search area, it ＂is still in its infancy. Thus, we identify some key research challenges with potential technical details at the end of this paper.

关键词： crossspace collaborative sensing human machine collaboration object matching space association

Mobile crowd sensing task optimal allocation： a mobility pattern matching perspective

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Frontiers of Computer Science 2018年第2期12卷 231-244页

作者： Liang WANG zhiwen yu Bin GUO Fei YI Fei XIONG School of Computer Science Northwestern Polytechnical University Xi'an 710072 China School of Electrical and Control Engineering Xi'an University of Science and Technology Xi'an 710054 China School of Electronic and Information Engineering Beijing Jiaotong University Beijing 100044 China

With the proliferation of sensor-equipped portable mobile devices, Mobile CrowdSensing （MCS） using smart devices provides unprecedented opportunities for collecting enormous surrounding data. In MCS applications, a crucial issue is how to recruit appropriate participants from a pool of available users to accomplish released tasks, satisfying both resource efficiency and sensing quality. In order to meet these two optimization goals simultaneously, in this paper, we present a novel MCS task allocation framework by aligning existing task sequence with users＇ moving regularity as much as possible. Based on the process of mobility repetitive pattern discovery, the original task allocation problem is converted into a pattern matching issue, and the involved optimization goals are transformed into pattern matching length and support degree indicators. To determine a trade-off between these two competitive metrics, we propose greedy- based optimal assignment scheme search approaches, namely MLP, MDP, IU1 and IU2 algorithm, with respect to matching length-preferred, support degree-preferred and integrated utility, respectively. Comprehensive experiments on real- world open data set and synthetic data set clearly validate the effectiveness of our proposed framework on MCS task optimal allocation.

关键词： mobile crowd sensing task allocation mobility regularity pattern matching

The mass,fake news,and cognition security

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Frontiers of Computer Science 2021年第3期15卷 1-13页

作者： Bin GUO Yasan DING yueheng SUN Shuai MA Ke LI zhiwen yu School of Computer Science Northwestern Polytechnical UniversityXi'an 710072China School of Cyber Security Tianjin UniversityTianjin 300350China School of Computer Science and Engineering Beihang UniversityBeijing 100191China

The widespread fake news in social networks is posing threats to social stability,economic development,and political democracy,*** studies have explored the effective detection approaches of online fake news,while few works study the intrinsic propagation and cognition mechanisms of fake *** the development of cognitive science paves a promising way for the prevention of fake news,we present a new research area called Cognition Security(CogSec),which studies the potential impacts of fake news on human cognition,ranging from misperception,untrusted knowledge acquisition,targeted opinion/attitude formation,to biased decision making,and investigates the effective ways for fake news *** is a multidisciplinary research field that leverages the knowledge from social science,psychology,cognition science,neuroscience,AI and computer *** first propose related definitions to characterize CogSec and review the literature *** further investigate the key research challenges and techniques of CogSec,including human-content cognition mechanism,social influence and opinion dif-fusion,fake news detection,and malicious bot ***,we summarize the open issues and future research directions,such as the cognition mechanism of fake news,influence maximization of fact-checking information,early detection of fake news,fast refutation of fake news,and so on.

关键词： cyberspace cognition security fake news crowd computing human-content interaction

Spotlight: Hot Target Discovery and Localization with Crowdsourced Photos

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Tsinghua Science and Technology 2020年第1期25卷 68-80页

作者： Jiaxi Gu Jiliang Wang Lan Zhang zhiwen yu Xiaozhe Xin yunhao Liu School of Computer Science Northwestern Polytechnical UniversityXi’an 710072China School of Software Tsinghua UniversityBeijing 100084China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China Beijing Sogou Technology Development Co. Ltd.Beijing 100084China

Camera-equipped mobile devices are encouraging people to take more photos and the development and growth of social networks is making it increasingly popular to share photos online. When objects appear in overlapping Fields Of View(FOV), this means that they are drawing much attention and thus indicates their popularity. Successfully discovering and locating these objects can be very useful for many applications, such as criminal investigations, event summaries, and crowdsourcing-based Geographical Information Systems(GIS).Existing methods require either prior knowledge of the environment or intentional photographing. In this paper, we propose a seamless approach called 'Spotlight', which performs passive localization using crowdsourced *** a graph-based model, we combine object images across multiple camera views. Within each set of combined object images, a photographing map is built on which object localization is performed using plane geometry. We evaluate the system’s localization accuracy using photos taken in various scenarios, with the results showing our approach to be effective for passive object localization and to achieve a high level of accuracy.

关键词： crowdsourcing localization multimedia mobile computing

Quantifying predictability of sequential recommendation via logical constraints

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Frontiers of Computer Science 2023年第5期17卷 133-143页

作者： En XU zhiwen yu Nuo LI Helei CUI Lina YAO Bin GUO School of Computer Science Northwestern Polytechnical UniversityXi’an 710129China School of Computer Science and Engineering University of New South WalesSydney NSW 2052Australia

The sequential recommendation is a compelling technology for predicting users’next interaction via their historical *** studies have proposed various methods to optimize the recommendation accuracy on different datasets but have not yet explored the intrinsic predictability of sequential *** this end,we consider applying the popular predictability theory of human movement behavior to this recommendation ***,it would incur serious bias in the next moment measurement of the candidate set size,resulting in inaccurate ***,determining the size of the candidate set is the key to quantifying the predictability of sequential ***,different from the traditional approach that utilizes topological constraints,we first propose a method to learn inter-item associations from historical behaviors to restrict the size via logical ***,we extend it by 10 excellent recommendation algorithms to learn deeper associations between user *** two methods show significant improvement over existing methods in scenarios that deal with few repeated behaviors and large sets of ***,a prediction rate between 64%and 80%has been obtained by testing on five classical datasets in three domains of the recommender *** provides a guideline to optimize the recommendation algorithm for a given dataset.

关键词： sequential recommendation information theory predictability

计及信誉值的虚拟电厂多主体合作博弈交易方法

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广东电力 2024年第8期37卷 26-34页

作者：王桂兰卓怀宇卢建刚余志文赵瑞锋华北电力大学控制与计算机工程学院河北保定071003 广东电网有限责任公司电力调度控制中心广东广州510600

随着分布式资源高比例接入,虚拟电厂作为聚合多方交易主体参与电力市场的新兴技术逐渐受到广泛关注。然而分布式资源出力不确定性和个体趋利性可能导致参与电力交易过程中造成违约行为。因此,提出计及信誉值的虚拟电厂聚合多方主体参与... 详细信息

随着分布式资源高比例接入,虚拟电厂作为聚合多方交易主体参与电力市场的新兴技术逐渐受到广泛关注。然而分布式资源出力不确定性和个体趋利性可能导致参与电力交易过程中造成违约行为。因此,提出计及信誉值的虚拟电厂聚合多方主体参与合作博弈电力交易方法。首先,针对虚拟电厂内各交易主体建立基于合约电量完成度的信誉值管理机制,并构建基于收益最大化的多主体合作出力模型;其次,采用合作博弈理论的Shapley值法确定初始收益分配方案;再次,为激励交易主体积极履行交易合约,合理转移交易风险,引入信誉值对初始方案进行修正,得出改进的收益分配方案;最后,基于MATLAB对算例进行计算,结果表明:合作前后各交易主体收益合计增长率约为101.16%,对比传统Shapley值法收益分配方案,最高和最低信誉值交易主体的收益增减幅度分别约为1.04%和3.13%,验证了所提交易方法的有效性与合理性。

关键词：虚拟电厂合作博弈信誉值 Shapley值法电力交易

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Numerical Hydrodynamics Study Around Turbine Array of Tidal Stream Farm in Zhoushan, China

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Journal of Ocean University of China 2017年第4期16卷 703-708页

作者： yu zhiwen ZHANG Jisheng ZHAI Yanyan ZHANG Tiantian ZHENG Jinhai State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering Hohai University Nanjing 210098 P. R. China College of Harbor Coastal and Offshore Engineering Hohai University Nanjing 210098 P. R. China Powerchina Water Environment Governance Shenzhen 518100 P. R. China China Three Gorges Corporation Beijing 100038 P. R. China

In recent decades,great efforts have been made to efficiently explore tidal stream energy due to its unique advantages of easy prediction and great *** recently launched a national tidal stream farm demonstration project in the waterway between Putuoshan and Hulu Islands in the Zhoushan *** deployment of the turbine array,it is necessary to understand the hydrodynamic changes associated with the construction of a turbine *** this study,we developed a depth-averaged hydrodynamics model that solves the shallow water governing equations to simulate the tidal hydrodynamics around the Zhoushan *** simulation results agree with field data in terms of the water elevation and stream *** considered two types of turbine arrays in this study and investigated their impacts on the local *** general,the stream velocity in the northern and southern areas is reduced due to the power take-off of the turbine array,whereas stream velocity in the western and eastern areas is slightly increased due to the blockage impact of the turbine array.

关键词： tidal stream farm turbine array tidal hydrodynamics numerical simulation demonstration project

CrowdDesigner:information-rich and personalized product description generation

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Frontiers of Computer Science 2022年第6期16卷 183-185页

作者： Qiuyun ZHANG Bin GUO Sicong LIU Jiaqi LIU zhiwen yu School of Computer Science Northwestern Polytechnical UniversityXi'an 710072China

1 Introduction Withthe rapid development of the E-commerce,more consumers turn to shop *** online shoppers search for products using keywords,the related products appear with their brief *** conduct a real-world survey and find that most shoppers are dissatisfied with the existing"onefit-all product descriptions"and they have to spend more time to scan detail ***,handcrafting the attractive product descriptions is always costly.

关键词： attractive Designer spend

Relative manifold based semi-supervised dimensionality reduction

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Frontiers of Computer Science 2020年第1期14卷 236-236页

作者： Xianfa CAI Guihua WEN Jia WEI zhiwen yu School of Medical Information Engineering Guangdong Pharmaceutical UniversityGuangzhou 510006China School of Computer Science and Engineering South China University of TechnologyGuangzhou 510006China Shenzhen Key Laboratory of High Performance Data Mining Shenzhen 518055China

Figure 8 of this article shows YaleB and CMU PIE with incorrect legend titles:YaleB(Tr=1900,Te=514,NOC=100)should be YaleB(Tr=1900,Te=514,d=100)(Fig.8(a));TIE(Tr=1200,Te=2880,d=100)should be PIE(Tr=1200,Te=2880,d=100)... 详细信息

关键词： Figure dimensionality correct