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A HYBRID PETRI-NET MODEL OF GRID WORKFLOW

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Journal of Electronics(China) 2008年第2期25卷 283-288页

作者： ji yimu Wang Ruchuan Ren Xunyi Nanjing University of Posts and Telecommunications Nanjing 210003 China Nanjing University Nanjing 210003 China

In order to effectively control the random tasks submitted and executed in grid workflow,a grid workflow model based on hybrid petri-net is presented. This model is composed of random petri-net,colored petri-net and general petri-net. Therein random petri-net declares the relationship between the number of grid users' random tasks and the size of service window and computes the server intensity of grid system. Colored petri-net sets different color for places with grid services and provides the valid interfaces for grid resource allocation and task scheduling. The experiment indicated that the model presented in this letter could compute the valve between the number of users' random tasks and the size of grid service window in grid workflow management system.

关键词：计算机网络工作流随机petri网任务控制

SQLS:A Storm-Based Query Language System for Real-Time Stream Data Analysis

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Chinese Journal of Electronics 2016年第6期25卷 1025-1033页

作者： ji yimu ZHANG Dianchao SUN Yanfei ZHAO Chuanxin HE jing WANG Ruchuan CHEN Guoliang Computer of Science Nanjing University of Posts and Telecommunications jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Key Laboratory of Computer Network and Information Integration Southeast University Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science and Technology Computer of Telecommunications Nanjing University of Posts and Telecommunications Department of Computer Anhui Normal University Engineering and Science Victoria University

In this work, a Storm-based query language System(SQLS) is proposed for real-time data stream analysis. The system is compatible with Continuous query language(CQL) specification. It supports both continuous queries and one-time queries over streaming data, and meets the requirements of user experience(traditional SQL queries) and Qo S(such as real-time and throughput). In order to better meet the requirement of throughput and enhance the processing efficiency, the load shedding algorithm and cache optimization are employed during the implementation of SQL-like operators. Finally, performance testing of the proposed SQLS has been conducted on standalone Storm platform and Storm clusters. Experimental results show that our system can not only meet the needs of users, but also extend the function of real-time streaming queries processing.

关键词： Continuous query Ad hoc query Storm CQL Real-time query processing

Collaborative filtering recommendation algorithm based on interactive data classification

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The Journal of China Universities of Posts and Telecommunications 2020年第5期27卷 1-12页

作者： ji yimu Li Ke Liu Shangdong Liu Qiang Yao Haichang Li Kui School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing 210023China jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing University of Posts and TelocommunicutionsNanjing 210003China Institue of High Performance Computing and Bigdata Nanjing University of Posts and TelecommunicationsNanjing 210003China Nanjing Center of HPC China Nanjing University of Posts and TelocommunicutionsNanjing 210003China jiangsu HPC and Intelligent Processing Engineer Research Center Nanjing University of Posts and Telocommunicutions Nanjing 210003China

In the matrix factorization(MF)based collaborative filtering recommendation method,the most critical part is to deal with the interaction between the features of users and items.The mainstream approach is to use the inner product for MF to describe the user-item relationship.However,as a shallow model,MF has its limitations in describing the relationship between data.In addition,when the size of the data is large,the performance of MF is often poor due to data sparsity and noise.This paper presents a model called PIDC,short for potential interaction data clustering based deep learning recommendation.First,it uses classifiers to filter and cluster recommended items to solve the problem of sparse training data.Second,it combines MF and multi-layer perceptron(MLP)to optimize the prediction effect,and the limitation of inner product on the model expression ability is eliminated.The proposed model PIDC is tested on two datasets.The experimental results show that compared with the existing benchmark algorithm,the model improved the recommendation effect.

关键词： personalized recommendation deep learning clustering collaborative filtering

Research on Security of Key Algorithms in Intelligent Driving System

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Chinese Journal of Electronics 2019年第1期28卷 29-38页

作者： LIU Shangdong WU Ye ji yimu CHEN Chen BI Qiang jiAO Zhipeng GONG jian WANG Ruchuan School of Computer Science and Engineering Southeast University School of Computer Science Nanjing University of Posts and Telecommunications jiangsu Provincial Key Laboratory of Computer Network Technology jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks

With the rapid development of the smart driving technology, the security of smart driving algorithms is becoming more and more important. Four core smart driving algorithms are determined by studying the architecture of smart driving algorithm. These algorithms comprise local path planning, pedestrian detection, lane detection and obstacle detection. The security issues of these algorithms are investigated by closely examining the work carried out by the algorithms. We found that there are vulnerabilities in all four algorithms. These vulnerabilities can cause abnormality and even road accidents for the smart cars. The final experiment shows that the vulnerabilities of these algorithms do exist under certain circumstances and therefore have high security risks. This study will lay a foundation to improve the security of the smart driving system.

关键词： Smart driving algorithm Local path planning Pedestrian detection Lane line detection Obstacle detection

An Analysis and Proof on Self-Similarity Property of Flash P2P Internet Video Traffic

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Chinese Journal of Electronics 2015年第1期24卷 26-32页

作者： ji yimu YUAN Yongge HAN Zhijie WANG Hao HAN Lei SUN Yanfei WANG Ruchuan Computer of Science Nanjing University of Posts and Telecommunications Institute of Advanced Technology Nanjing University of Posts and Telecommunications

In order to study the amount of bandwidth resource loss caused by flash P2 P technique, its influence on network load and its maintenance cost, the characteristic of Internet traffic of flash P2 P is studied. On the basis of analysis of features of Real time media flow protocol(RTMFP), the traffic of flash P2 P can be identified from the Internet traffic. By extraction and analysis of the traffic of the three largest online video content providers in China(Youku, Iqyi and Sohu Video) and the calculation of probability distribution of the traffic, it is found that the transmission time of flash P2 P traffic and the transmission time interval obeys the heavy-tailed distribution. This accounts for the self-similarity of the flash P2 P traffic. To better explain the phenomenon, the long-range dependent model is established based on the current traffic. By the established mathematical model, it is strictly proved that flash P2 P traffic has self-similar characteristic.

关键词： Video traffic Flash P2P Self-similarity Empirical mode decomposition(EMD) Autoregressive integrated moving average(ARAMA) model.

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融合数据挖掘和评分预测的推荐算法

南京邮电大学学报（自然科学版） 2024年第1期44卷 101-108页

作者：林啸轩季一木刘尚东李玲娟南京邮电大学计算机学院江苏南京210023

针对传统UserCF算法存在的数据稀疏、相似度计算开销大且不够准确的问题,以提高推荐准确率、覆盖率和时间效率为目标,设计了融合数据挖掘和评分预测的推荐算法DRR。首先用PCA降维算法解决用户评分矩阵过大且稀疏的问题;再用Canopy算法... 详细信息

针对传统UserCF算法存在的数据稀疏、相似度计算开销大且不够准确的问题,以提高推荐准确率、覆盖率和时间效率为目标,设计了融合数据挖掘和评分预测的推荐算法DRR。首先用PCA降维算法解决用户评分矩阵过大且稀疏的问题;再用Canopy算法对降维后的矩阵进行处理得到聚类个数K,以余弦相似度为距离度量,用K-means算法对用户聚类,并用Apriori算法挖掘簇内项目之间潜在的关联规则,计算项目关联因子;最后以目标用户所在簇内的其他用户为其近邻,基于历史评分、余弦相似度和项目关联因子预测目标用户对项目的评分,在降低寻找最近邻时耗的同时挖掘出长尾项目。在movieLens数据集、豆瓣电影数据集上与UserCF算法、基于K-means聚类的协同过滤算法和基于谱聚类的协同过滤算法的对比实验结果表明,DRR算法的准确率、召回率、F1值、覆盖率,以及时间效率都有所提升。

关键词：降维聚类关联规则长尾项目评分预测

基于CSI实例标准化的域泛化人体动作识别模型

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通信学报 2024年第6期45卷 196-209页

作者：王杨许佳炜王傲夏慧娟赵传信季一木安徽师范大学计算机与信息学院安徽芜湖241002 南京邮电大学计算机学院江苏南京210003

为了实现完全不依赖目标域数据的Wi-Fi跨域人体动作感知,提出了一种基于CSI实例标准化的域泛化人体动作识别模型INDG-Fi。INDG-Fi使用实例标准化去除CSI特征表示的领域信息,接着构建共享特征提取的动作分类器和域分类器,并通过动作偏向... 详细信息

为了实现完全不依赖目标域数据的Wi-Fi跨域人体动作感知,提出了一种基于CSI实例标准化的域泛化人体动作识别模型INDG-Fi。INDG-Fi使用实例标准化去除CSI特征表示的领域信息,接着构建共享特征提取的动作分类器和域分类器,并通过动作偏向学习和对抗性的域学习,将编码层提取的特征偏向人体动作引起的信号特征,同时远离领域信号影响。为了让模型关注受人体动作影响更显著的子载波信号,在编码层中加入子载波注意力模块。实现结果表明,所提INDG-Fi在不可见的用户和位置的感知性能分别为97.99%和92.73%,能够实现鲁棒的跨域感知。

关键词：信道状态信息无线感知人体动作识别域泛化

A NEW PRIVACY-PRESERVING EUCLID-DISTANCE PROTOCOL AND ITS APPLICATIONS IN WSNS

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Journal of Electronics(China) 2013年第2期30卷 190-197页

作者： Chen Ping ji yimu Wang Ruchuan Huang Haiping Zhang Dan College of Computer Nanjing University of Posts and Telecommunications jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education Nanjing University of Posts and Telecommunications

Recently, privacy concerns become an increasingly critical issue. Secure multi-party computation plays an important role in privacy-preserving. Secure multi-party computational geometry is a new field of secure multi-party computation. In this paper, we devote to investigating the solutions to some secure geometric problems in a cooperative environment. The problem is collaboratively computing the Euclid-distance between two private vectors without disclosing the private input to each other. A general privacy-preserving Euclid-distance protocol is firstly presented as a building block and is proved to be secure and efficient in the comparison with the previous methods. And we proposed a new protocol for the application in Wireless Sensor Networks (WSNs), based on the novel Euclid-distance protocol and Density-Based Clustering Protocol (DBCP), so that the nodes from two sides can compute cooperatively to divide them into clusters without disclosing their location information to the opposite side.

关键词： Secure multi-party computation Privacy-preserving Euclid-distance protocol Wireless Sensor Networks (WSNs) Density-Based Clustering Protocol (DBCP)

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传感数据:智能时代学习分析的新视角

南京邮电大学学报（社会科学版） 2024年第2期26卷 56-64页

作者：肖婉季一木南京邮电大学教育科学与技术学院江苏南京210023 南京邮电大学计算机学院江苏南京210023

智能时代,各种智慧教育场所、移动智能终端和可穿戴设备中应用的传感技术可以对学习者的生理特征、行为动作及学习场所等相关数据进行捕捉,使学习者“身体”重新回归到教育者视野,并通过低倾入性的方式采集真实情境中的序列数据,为实现... 详细信息

智能时代,各种智慧教育场所、移动智能终端和可穿戴设备中应用的传感技术可以对学习者的生理特征、行为动作及学习场所等相关数据进行捕捉,使学习者“身体”重新回归到教育者视野,并通过低倾入性的方式采集真实情境中的序列数据,为实现全方位、情境性和过程性的学习分析提供条件。当前,在教育实践中,传感数据已逐步应用于认知监测、行为分析、情感识别以及自适应情境学习等方面,为智能化学习分析与评价提供了良好支持。随着技术与实践的发展,学习分析中的传感技术将从“有感”走向“无感”,传感设备将从单一设备转变为集成系统,应用目的将从对学习过程的合理解释走向精准干预,并从实验研究走向多样化实践。在传感数据应用于学习分析的实践中,教育部门、研究机构和企业应共同努力,以应对理论基础、技术成本和伦理隐私等方面的挑战。

关键词：传感数据学习分析教育大数据智能化教育信息化