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Incorporating metapath interaction on heterogeneous information network for social recommendation

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Frontiers of computer Science 2024年第1期18卷 33-48页

作者： Yanbin JIANG Huifang ma Xiaohui ZHANG Zhixin LI liang CHANG college of computer Science and engineering Northwest Normal UniversityLanzhou 730070China Guangxi Key Lab of Multi-source information Mining and Security Guangxi Normal UniversityGuilin 541001China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China

Heterogeneous information network(HIN)has recently been widely adopted to describe complex graph structure in recommendation systems,proving its effectiveness in modeling complex graph *** existing HIN-based recommendation studies have achieved great success by performing message propagation between connected nodes on the defined metapaths,they have the following major *** works mainly convert heterogeneous graphs into homogeneous graphs via defining metapaths,which are not expressive enough to capture more complicated dependency relationships involved on the ***,the heterogeneous information is more likely to be provided by item attributes while social relations between users are not adequately *** tackle these limitations,we propose a novel social recommendation model MPISR,which models MetaPath Interaction for Social Recommendation on heterogeneous information ***,our model first learns the initial node representation through a pretraining module,and then identifies potential social friends and item relations based on their similarity to construct a unified *** then develop the two-way encoder module with similarity encoder and instance encoder to capture the similarity collaborative signals and relational dependency on different *** experiments on five real datasets demonstrate the effectiveness of our method.

关键词： heterogeneous information network social reco-mmender system metapath interaction attention mechanism

A NEWε-GENERALIZED PROJECTION METHOD OF STrongLY SUB-FEASIBLE DIRECTIONS FOR INEQUALITY CONSTRAINED OPTIMIZATION

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Journal of Systems Science & Complexity 2011年第3期24卷 604-618页

作者： Jinbao JIAN Guodong ma Chuanhao GUO college of mathematics and information Science Guangxi University Nanning 530004 China Department of mathematics and computer Science Yulin Normal University Yulin 537000 China college of Science Shanghai University Shanghai 200444 China.

In this paper, the nonlinear optimization problems with inequality constraints are discussed. Combining the ideas of the strongly sub-feasible directions method and the s-generalized projection technique, a new algorithm starting with an arbitrary initial iteration point for the discussed problems is presented. At each iteration, the search direction is generated by a new s-generalized projection explicit formula, and the step length is yielded by a new Armijo line search. Under some necessary assumptions, not only the algorithm possesses global and strong convergence, but also the iterative points always get into the feasible set after finite iterations. Finally, some preliminary numerical results are reported.

关键词： E-generalized projection global and strong convergence inequality constraints method of strongly sub-feasible directions optimization.

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Applying Hybrid Clustering in Pulsar Candidate Sifting with Multi-modality for FAST Survey

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Research in Astronomy and Astrophysics 2024年第3期24卷 283-296页

作者： Zi-Yi You Yun-rong Pan Zhi ma Li Zhang Shuo Xiao Dan-Dan Zhang Shi-Jun Dang Ru-Shuang Zhao Pei wang Ai-Jun Dong Jia-Tao Jiang Ji-Bing Leng Wei-An Li Si-Yao Li School of Physics and Electronic Science Guizhou Normal UniversityGuiyang 550025China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal UniversityGuiyang 550025China college of Big Data and information engineering Guizhou UniversityGuiyang 550025China CAS Key Laboratory of FAST National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China Key Laboratory of information and Computing Guizhou Province Guizhou Normal UniversityGuiyang 550001China School of Big data and computer Science Guizhou Normal UniversityGuiyang 550025China Guizhou Software engineering Research Center Guiyang 550000China

Pulsar search is always the basis of pulsar navigation,gravitational wave detection and other research ***,the volume of pulsar candidates collected by the Five-hundred-meter Aperture Spherical radio Telescope(FAST)shows an explosive growth rate that has brought challenges for its pulsar candidate filtering ***,the multi-view heterogeneous data and class imbalance between true pulsars and non-pulsar candidates have negative effects on traditional single-modal supervised classification *** this study,a multi-modal and semi-supervised learning based on a pulsar candidate sifting algorithm is presented,which adopts a hybrid ensemble clustering scheme of density-based and partition-based methods combined with a feature-level fusion strategy for input data and a data partition strategy for *** on both High Time Resolution Universe SurveyⅡ(HTRU2)and actual FAST observation data demonstrate that the proposed algorithm could excellently identify pulsars:On HTRU2,the precision and recall rates of its parallel mode reach0.981 and 0.988 *** FAST data,those of its parallel mode reach 0.891 and 0.961,meanwhile,the running time also significantly decreases with the increment of parallel nodes within ***,we can conclude that our algorithm could be a feasible idea for large scale pulsar candidate sifting for FAST drift scan observation.

关键词： methods data analysis-surveys-methods numerical

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A Fault-Tolerant Mobility-Aware Caching Method in Edge Computing

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computer Modeling in engineering & Sciences 2024年第7期140卷 907-927页

作者： Yong ma Han Zhao Kunyin Guo Yunni Xia Xu wang Xianhua Niu Dongge Zhu Yumin Dong School of computer information engineering Jiangxi Normal UniversityNanchang330000China School of Digital Industry Jiangxi Normal UniversityShangrao334000China The college of computer Science Chongqing UniversityChongqing400044China college of Mechanical and Vehicle engineering Chongqing UniversityChongqing400030China School of computer and Software engineering Xihua UniversityChengdu610039China Electric Power Research Institute of State Grid Ningxia Electric Power Company Ltd. Yinchuan750002China college of computer and information Science Chongqing Normal UniversityChongqing401331China

Mobile Edge Computing(MEC)is a technology designed for the on-demand provisioning of computing and storage services,strategically positioned close to *** the MEC environment,frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery,ultimately enhancing the quality of the user ***,due to the typical placement of edge devices and nodes at the network’s periphery,these components may face various potential fault tolerance challenges,including network instability,device failures,and resource *** the dynamic nature ofMEC,making high-quality content caching decisions for real-time mobile applications,especially those sensitive to latency,by effectively utilizing mobility information,continues to be a significant *** response to this challenge,this paper introduces FT-maACC,a mobility-aware caching solution grounded in multi-agent deep reinforcement learning and equipped with fault tolerance *** approach comprehensively integrates content adaptivity algorithms to evaluate the priority of highly user-adaptive cached ***,it relies on collaborative caching strategies based onmulti-agent deep reinforcement learningmodels and establishes a fault-tolerancemodel to ensure the system’s reliability,availability,and *** results unequivocally demonstrate that FTmaACC outperforms its peer methods in cache hit rates and transmission latency.

关键词： Mobile edge networks mobility fault tolerance cooperative caching multi-agent deep reinforcement learning content prediction

用Java实现基于CORBA的Agent应用系统开发

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计算机工程与应用 2004年第12期40卷 116-118页

作者：孙华志马希荣北京科技大学信息工程学院天津师范大学计算机与信息工程学院天津300074 天津师范大学计算机与信息工程学院

由于Agent在适应软件开发需求方面的有效性,利用Agent技术开发实际应用系统引起了人们的高度重视,但是基于Agent系统的开发仍然缺乏开发环境和编程工具的支持。笔者在构建远程智能教育通信平台的过程中,尝试借鉴Agent思想解决分布式智... 详细信息

由于Agent在适应软件开发需求方面的有效性,利用Agent技术开发实际应用系统引起了人们的高度重视,但是基于Agent系统的开发仍然缺乏开发环境和编程工具的支持。笔者在构建远程智能教育通信平台的过程中,尝试借鉴Agent思想解决分布式智能应用问题,采用Java语言实现了基于CORBA的多Agent系统监控模型(CAMM)。文章描述了采用Java多线程机制实现Agent生命周期控制、采用对象序列化机制实现移动Agent的思想方法和技术手段。

关键词： CORBA Mobile Agent IDL KQML 通信

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Restoration method of characters on Jiagu rubbings based on Poisson distribution and fractal geometry

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Science china(information Sciences) 2010年第7期53卷 1296-1304页

作者： GU ShaoTong1,2,3, FENG GeFei1,2,3, ma XiaoHu1,2,4 & YANG YiMing1,2,3 1Institute of Linguistics, Xuzhou normal university, Xuzhou 221009, china 2Jiangsu college Key Lab of Linguistic Sciences and Neuro-cognition engineering, Xuzhou normal university, Xuzhou 221009, china 3Linguistic Science college, Xuzhou normal university, Xuzhou 221009, china 4School of computer Science and Technology, Soochow university, Suzhou 215006, china 1. Institute of Linguistics Xuzhou Normal University Xuzhou 221009 China2. Jiangsu College Key Lab of Linguistic Sciences and Neuro-cognition Engineering Xuzhou Normal University Xuzhou 221009 China3. Linguistic Science College Xuzhou Normal University Xuzhou 221009 China4. School of Computer Science and Technology Soochow University Suzhou 215006 China

A scheme for character restoration of Jiagu rubbings based on Poisson distribution and fractal geometry is proposed in this paper. The distribution characteristics of the connected regions on Jiagu rubbings is analyzed, and all the connected regions are recognized according to differences between these and their mathematical expectations. Regions are recognized as noise regions and filled if the differences are negative, while stroke regions are reserved. The attributes of the character image edges on Jiagu rubbings are also analyzed. The fractal dimensions of the character edge of Jiagu rubbings are calculated by means of statistics. The feature points are obtained using the cosine of the angle between the two vectors of the point and the consecutive two points. Different compression transformations with weighted coordinates are performed on different strokes and segments of the characters so as to smoothen the character edge of Jiagu rubbings images. Experimental results show that our scheme could successfully clear noise regions and polish the character edge of Jiagu rubbings.

关键词： Jiagu rubbings Poisson distribution fractal geometry fractal dimension compression transformation character restoration

Proactive Caching at the Wireless Edge:A Novel Predictive User Popularity-Aware Approach

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computer Modeling in engineering & Sciences 2024年第8期140卷 1997-2017页

作者： Yunye Wan Peng Chen Yunni Xia Yong ma Dongge Zhu Xu wang Hui Liu Weiling Li Xianhua Niu Lei Xu Yumin Dong college of computer Science Chongqing UniversityChongqing400044China School of computer and Software engineering Xihua UniversityChengdu610039China School of computer and information engineering Jiangxi Normal UniversityNanchang330022China Electric Power Research Institute of State Grid Ningxia Electric Power Co. Ltd.Yinchuan750002China college of Mechanical and Vehicle engineering Chongqing UniversityChongqing400030China School of computer Science and Technology Beijing Institute of TechnologyBeijing100083China School of computer Science and Technology Dongguan University of TechnologyDongguan523808China School of Emergency management Xihua UniversityChengdu610039China college of computer and information Science Chongqing Normal UniversityChongqing401331China

Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as *** an MEC environment,servers are deployed closer to mobile terminals to exploit storage infrastructure,improve content delivery efficiency,and enhance user ***,due to the limited capacity of edge servers,it remains a significant challenge to meet the changing,time-varying,and customized needs for highly diversified content of ***,techniques for caching content at the edge are becoming popular for addressing the above *** is capable of filling the communication gap between the users and content providers while relieving pressure on remote cloud ***,existing static caching strategies are still inefficient in handling the dynamics of the time-varying popularity of content and meeting users’demands for highly diversified entity *** address this challenge,we introduce a novel method for content caching over MEC,i.e.,*** synthesizes a content popularity prediction model,which takes users’stay time and their request traces as inputs,and a deep reinforcement learning model for yielding dynamic caching *** results demonstrate that PRIME,when tested upon the MovieLens 1M dataset for user request patterns and the Shanghai Telecom dataset for user mobility,outperforms its peers in terms of cache hit rates,transmission latency,and system cost.

关键词： Mobile edge computing content caching system average cost deep reinforcement learning collaborative mechanism

A Lightweight IoT malware Detection and Family Classification Method

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Journal of computer and Communications 2024年第4期12卷 201-227页

作者： Changguang wang Ziqi ma Qingru Li Dongmei Zhao Fangwei wang college of computer and Cyber Security Hebei Normal University Shijiazhuang China Key Laboratory of Network and information Security of Hebei Province Hebei Normal University Shijiazhuang China

A lightweight malware detection and family classification system for the Internet of Things (IoT) was designed to solve the difficulty of deploying defense models caused by the limited computing and storage resources of IoT devices. By training complex models with IoT software gray-scale images and utilizing the gradient-weighted class-activated mapping technique, the system can identify key codes that influence model decisions. This allows for the reconstruction of gray-scale images to train a lightweight model called LMDNet for malware detection. Additionally, the multi-teacher knowledge distillation method is employed to train KD-LMDNet, which focuses on classifying malware families. The results indicate that the model’s identification speed surpasses that of traditional methods by 23.68%. Moreover, the accuracy achieved on the malimg dataset for family classification is an impressive 99.07%. Furthermore, with a model size of only 0.45M, it appears to be well-suited for the IoT environment. By training complex models using IoT software gray-scale images and utilizing the gradient-weighted class-activated mapping technique, the system can identify key codes that influence model decisions. This allows for the reconstruction of gray-scale images to train a lightweight model called LMDNet for malware detection. Thus, the presented approach can address the challenges associated with malware detection and family classification in IoT devices.

关键词： IoT Security Visual Explanations Multi-Teacher Knowledge Distillation Lightweight CNN

BambooBase:A comprehensive database of bamboo omics and systematics

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Molecular Plant 2024年第5期17卷 682-685页

作者： Yun-Long Liu Shu-Yang Gao Guihua Jin Meng-Yuan Zhou Qijuan Gao Cen Guo Yi-Zhou Yang liang-Zhong Niu Enhua Xia Zhen-Hua Guo Peng-Fei ma De-Zhu Li Germplasm Bank of Wild Species&Yunnan Key Laboratory of Crop Wild Relatives Omics Kunming Institute of BotanyChinese Academy of SciencesKunmingYunnan 650201China Kunming college of Life Science University of Chinese Academy of SciencesKunmingYunnan 650201China State Key Laboratory of Tea Plant Biology and Utilization Anhui Agricultural UniversityHefeiAnhui 230036China School of computer and Artificial Intelligence Hefei Normal UniversityHefeiAnhui 230061China Key Laboratory for Plant Diversity and Biogeography in East Asia Kunming Institute of BotanyChinese Academy of SciencesKunmingYunnan 650201China

Dear Editor,Bamboos(Bambusoideae,Poaceae)are of significant economic and ecological importance,supporting billions of people and contributing to international trade(Wu et al.,2023).They play a crucial role in carbon fixation and support a multitude of other species including the giant panda(Clark et al.,2015).Since the release of the first draft genome of moso bamboo(Phyllostachys edulis)(Peng et al.,2013),there has been a notable increase in the sequencing,assembly,and annotation of diverse bamboo genomes(Guo et al.,2019;Zheng et al.,2022;ma et al.,2024).An existing resource for bamboo genomics,BambooGDB(Zhao et al.,2014),provides information based on the individual draft reference genome of moso *** is needed,however,is a resource reinforcing multiple genome assemblies in Bambusoideae to enable researchers to unravel the evolutionary history of chromosomes and genes through cladespecific comparative genomic ***,we present BambooBase(https://***/),a newly developed web-based database designed to provide a seamless user experience for bamboo omics and systematics.

关键词： enable supporting Bamboo