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Collaborative prediction for bus arrival time based on CPS

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Journal of Central South University 2014年第3期21卷 1242-1248页

作者：蔡雪松 software college East China Normal University Vehicle Information Department Shanghai Development Center of Computer Software Technology

To improve the accuracy of real-time public transport information release system, a collaborative prediction model was proposed based on cyber-physical systems architecture. In the model, the total bus travel time was divided into three parts: running time, dwell time and intersection delay time, and the data were divided into three categories of historical data, static data and real-time data. The bus arrival time was obtained by fusion computing the real-time data in perception layer together with historical data and static data in collaborative layer. The validity of the collaborative model was verified by the data of a typical urban bus line in Shanghai, and 1538 sets of data were collected and analyzed from three different perspectives. By comparing the experimental results with the actual results, it is shown that the experimental results are with higher prediction accuracy, and the collaborative prediction model adopted is able to meet the demand for bus arrival prediction.

关键词： prediction model cyber-physical system architecture bus arrival time collaborative prediction

MapReduce Scheduler by Characterizing Performance Interference

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China Communications 2016年第10期13卷 253-262页

作者： Lei Yang Yu Dai Bin Zhang college of Computer Science and Engineering Northeastern University China college of software Northeastern University China

Recently, virtualization has become more and more important in the cloud computing to support efficient flexible resource provisioning. However, performance interference among virtual machines(VMs) has become a challenge which may affect the effectiveness of resource provisioning. In a virtual cluster which runs the Map Reduce applications, the performance interference can also affect the performance of the Map and Reduce tasks and thus cause a performance degradation of the Map Reduce job. Accordingly, this paper presents a Map Reduce scheduling framework to mitigate this performance degradation caused by the performance interference. The framework includes a performance interference prediction module and an interference aware scheduling algorithm. To verify its effectiveness, we have done a set of experiments on a 24-node virtual Map Reduce cluster. The experiments illustrate that the proposed framework can achieve a performance improvement in the virtualized environment compared with other Map Reduce schedulers.

关键词： Map Reduce scheduler performance interference

An Immunization Strategy for Social Network Worms Based on Network Vertex Influence

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China Communications 2015年第7期12卷 154-166页

作者： YANG Wei WANG Haibo YAO Yu software college Northeastern University Heinz college Carnegie Mellon University college of Information Science and Engineering Northeastern University

Along with the rapid development of social networks, social network worms have constituted one of the major internet security problems. The root of worm is the inevitable software vulnerability during the design and implementation process of software. So it is hard to completely avoid worms in the existing software engineering systems. Due to lots of bandwidth consumption, the patch cannot be transmitted simultaneously by the network administrator to all hosts. This paper studies how to prevent the propagation of social network worms through the immunization of key nodes. Unlike existing containment models for worm propagation, a novel immunization strategy is proposed based on network vertex influence. The strategy selects the critical vertices in the whole network. Then the immunization is applied on the selected vertices to achieve the maximal effect of worm containment with minimal cost. Different algorithms are implemented to select vertices. Simulation experiments are presented to analyze and evaluate the performance of different algorithms.

关键词： social network worm immunization strategy network security worm propagation worm containment

Research on Virtual Agent Perception Model

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Journal of Donghua University(English Edition) 2006年第6期23卷 57-61页

作者：冯秀芳高保禄 college of Computer and software Taiyuan University of Technology

An intelligent virtual environment is described for training users in the operation of complex engineering systems. After analyzing the original model of virtual environment, a virtual agent perception model was put forward. The information layer was inserted into original virtual environment. The model classifies all kinds of information and offers a way for knowledge description of virtual environment, and contributes to set up feeling model for the Virtual Agent within virtual environment.

关键词： Intelligent Virtual Environment (IVE) virtual agent information layers.

Impulsive control of permanent magnet synchronous motors with parameters uncertainties

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Chinese Physics B 2008年第5期17卷 1678-1684页

作者：李东王时龙张小洪杨丹王慧 college of Mathematics & Physics Science Chongqing University college of Mechanical Engineering Chongqing University college of software Engineering Chongqing University college of Computer Science Chongqing University

The permanent magnet synchronous motors （PMSMs） may have chaotic behaviours for the uncertain values of parameters or under certain working conditions, which threatens the secure and stable operation of motor-driven. It is important to study methods of controlling or suppressing chaos in PMSMs. In this paper, robust stabilities of PMSM with parameter uncertainties are investigated. After the uncertain matrices which represent the variable system parameters are formulated through matrix analysis, a novel asymptotical stability criterion is established. Some illustrated examples are also given to show the effectiveness of the obtained results.

关键词： permanent magnet synchronous motors impulsive control parameters uncertainties robust stability

Intrusion detection based on rough set and artificial immune

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High Technology Letters 2016年第4期22卷 368-375页

作者：张玲 Sun Haiyan Cui Jiantao Yang Hua Huang Yan software Engineering college Zhengzhou University of Light Industry

In order to increase intrusion detection rate and decrease false positive detection rate,a novel intrusion detection algorithm based on rough set and artificial immune( RSAI-IDA) is *** artificial immune in intrusion detection,anomaly actions are detected adaptively,and with rough set,effective antibodies can be obtained. A scheme,in which antibodies are partly generated randomly and others are from the artificial immune algorithm,is applied to ensure the antibodies diversity. Finally,simulations of RSAI-IDA and comparisons with other algorithms are given. The experimental results illustrate that the novel algorithm achieves more effective performances on anomaly intrusion detection,where the algorithm's time complexity decreases,the true positive detection rate increases,and the false positive detection rate is decreased.

关键词： rough set artificial immune anomaly intrusion detection rough set and artificial immune(RSAI-IDA)

Community Discovery Algorithm Based on Multi-Relationship Embedding

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Computer Systems Science & Engineering 2023年第9期46卷 2809-2820页

作者： Dongming Chen Mingshuo Nie Jie Wang Dongqi Wang software college Northeastern UniversityShenyang110169China

Complex systems in the real world often can be modeled as network structures,and community discovery algorithms for complex networks enable researchers to understand the internal structure and implicit information of *** community discovery algorithms are usually designed for single-layer networks or single-interaction relationships and do not consider the attribute information of ***,many real-world networks consist of multiple types of nodes and edges,and there may be rich semantic information on nodes and *** methods for single-layer networks cannot effectively tackle multi-layer information,multi-relationship information,and attribute *** paper proposes a community discovery algorithm based on multi-relationship *** proposed algorithm first models the nodes in the network to obtain the embedding matrix for each node relationship type and generates the node embedding matrix for each specific relationship type in the network by node *** node embedding matrix is provided as input for aggregating the node embedding matrix of each specific relationship type using a Graph Convolutional Network(GCN)to obtain the final node embedding *** strategy allows capturing of rich structural and attributes information in multi-relational *** were conducted on different datasets with baselines,and the results show that the proposed algorithm obtains significant performance improvement in community discovery,node clustering,and similarity search tasks,and compared to the baseline with the best performance,the proposed algorithm achieves an average improvement of 3.1%on Macro-F1 and 4.7%on Micro-F1,which proves the effectiveness of the proposed algorithm.

关键词： Network representation learning multi-relationship node encoder attribute information

Toward earthquake early warning:A convolutional neural network for rapid earthquake magnitude estimation

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Artificial Intelligence in Geosciences 2023年第1期4卷 39-46页

作者： Fanchun Meng Tao Ren Zhenxian Liu Zhida Zhong software college of Northeastern University Shen YangChina

Earthquake early warning(EEW)is one of the important tools to reduce the hazard of *** contemporary seismology,EEW is typically transformed into a fast classification of earthquake magnitude,i.e.,large magnitude earthquakes that require warning are in the positive category and vice versa in the negative ***,the current standard information signal processing routines for magnitude fast classification are time-consuming and vulnerable to data ***,in this study,Deep Learning(DL)algorithms are introduced to assist with *** the three-component seismic waveform record of 7 s obtained from the China Earthquake Network Center(CENC),this paper proposes a DL model(EEWMagNet),which accomplishes the extraction of spatial and temporal features through DenseBlock with Bottleneck and Multi-Head *** experiments on Chinese field data demonstrate that the proposed model performs well in the fast classification of ***,the comparison experiments demonstrate that the epicenter distance information is indispensable,and the normalization has a negative effect on the model to capture accurate amplitude information.

关键词： Massive tectonic earthquakes Earthquake early warning Magnitude classification DenseBlock Multi-head attention

A system of general nonlinear variational inclusions in Banach spaces

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Applied Mathematics and Mechanics(English Edition) 2015年第12期36卷 1663-1672页

作者： Xieping DING SALAHUDDIN college of Mathematics and software Science Sichuan Normal University Department of Mathematics Jazan University

A new system of general nonlinear variational inclusions is introduced and studied in Banach spaces. An iterative algorithm is developed and analyzed by use of the resolvent operator techniques to find the approximate solutions of the system of general nonlinear variational inclusions involving different nonlinear operators in uniformly smooth Banach spaces.

关键词： system of general nonlinear variational inclusions strongly accretive mapping relaxed accretive mapping resolvent operator uniformly smooth Banach space