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Performance index based learning controls for the partial non-regular systems using lifting technique

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控制理论与应用（英文版） 2009年第2期7卷 197-201页

作者： Shengyue YANG xiaoping fan Zhihua QU School of Information Science and Engineering Central South University Changsha Hunan 410075 China Department of Electrical and Computer Engineering University of Central Florida Orlando FL 32816 USA

Deficiencies of the performance-based iterative learning control （ILC） for the non-regular systems are investigated in detail, then a faster control input updating and lifting technique is introduced in the design of performance index based ILCs for the partial non-regular systems. Two ldnds of optimal ILCs based on different performance indices are considered. Finally, simulation examples are given to illustrate the feasibility of the proposed learning controls.

关键词： Iterative learning control Non-regular systems Lifting technique

Orthogonal-Gradient Measurement Matrix Construction Algorithm

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Chinese Journal of Electronics 2016年第1期25卷 81-87页

作者： TIAN Shujuan fan xiaoping LI Zhetao PAN Tian CHOI Youngjune SEKIYA Hiroo School of Information Science and Engineering Central South University The College of Information Engineering Xiangtan University Laboratory of Networked Systems Hunan University of Finance and Economics Department of Information and Computer Engineering Ajou University Graduate School of Advanced Integration Science Chiba University

An orthogonal-gradient measurement matrix construction algorithm is proposed for reducing the maximum and average mutual-coherence of sensing matrix. It shrinks Gram matrix based on equiangular tight frame theory. An orthogonal-gradient factor matrix is deduced. It obtains an optimized measurement matrix with the orthogonal-gradient factor matrix. The results of experiments show that the proposed algorithm effectively reduces the maximum and average mutual-coherence of sensing matrix. This leads to a better reconstruction performance for signals with different sparsities compared with Gaussian matrix, Elad’s, Xu’s, Vahid’s and Li’s methods.

关键词： Compressive sensing(CS) Measurement matrix Mutual-coherence Equiangular tight frame

IDSRadar:a real-time visualization framework for IDS alerts

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Science China(Information Sciences) 2013年第8期56卷 216-227页

作者： ZHAO Ying ZHOU fangfang fan xiaoping LIANG Xing LIU YongGang Information Science and Engineering School Central South University Laboratory of Networked Systems Hunan University of Finance & Economics

Intrusion Detection Systems(IDS) is an automated cyber security monitoring system to sense malicious ***,IDS often generates both a considerable number of alerts and false positives in IDS *** visualization allows users to discover and analyze large amounts of information through visual exploration and interaction *** with the aid of visualization,identifying the attack patterns and recognizing the false positives from a great number of alerts are still *** this paper,a novel visualization framework,IDSRadar,is proposed for IDS alerts,which can monitor the network and perceive the overall view of the security situation by using radial graph in *** utilizes five categories of entropy functions to quantitatively analyze the irregular behavioral patterns,and synthesizes interactions,filtering and drill-down to detect the potential *** conclusion,IDSRadar is used to analyze the mini-challenges of the VAST challenge 2011 and 2012.

关键词： visual analytics information visualization cyber security IDS log entropy

A Crowdsourcing Recommendation that Considers the Influence of Workers

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Computers, Materials & Continua 2021年第2期66卷 1379-1396页

作者： Zhifang Liao Xin Xu Peng Lan Liu Yang Yan Zhang xiaoping fan School of Computer Science and Engineering Central South UniversityChangsha410075China Glasgow Caledonian University GlasgowG40BAUK Hunan University of Finance and Economics Changsha410205China

In the context of the continuous development of the Internet,crowdsourcing has received continuous attention as a new cooperation model based on the relationship between enterprises,the public and *** them,a reasonably designed recommendation algorithm can recommend a batch of suitable workers for crowdsourcing tasks to improve the final task completion ***,this paper proposes a crowdsourcing recommendation framework based on workers’influence(CRBI).This crowdsourcing framework completes the entire process design from task distribution,worker recommendation,and result return through processes such as worker behavior analysis,task characteristics construction,and cost *** this paper,a calculation model of workers’influence characteristics based on the ablation method is designed to evaluate the comprehensive performance of *** the same time,the CRBI framework combines the traditional open-call task selection mode,builds a new task characteristics model by sensing the influence of the requesting worker and its task *** the end,accurate worker recommendation and task cost optimization are carried out by calculating model *** addition,for recommending workers to submit task answers,this paper also proposes an aggregation algorithm based on weighted influence to ensure the accuracy of task *** paper conducts simulation experiments on some public datasets of AMT,and the experimental results show that the CRBI framework proposed in this paper has a high comprehensive ***,CRBI has better usability,more in line with commercial needs,and can well reflect the wisdom of group intelligence.

关键词： Crowdsourcing recommendation framework workers’ influence worker recommendation weighted voting

Expanding Hot Code Path for Data Cleaning on Software Graph

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Computers, Materials & Continua 2020年第5期63卷 743-753页

作者： Guang Sun xiaoping fan Wangdong Jiang Hangjun Zhou Fenghua Li Rong Yang Institute of Big Data Hunan University of Finance and EconomicsChangsha410205China School of Engineering University of AlabamaTuscaloosa35487USA

Graph analysis can be done at scale by using Spark GraphX which loading data into memory and running graph analysis in *** this way,we should take data out of graph databases and put it into *** the limitation of memory size,the premise of accelerating graph analytical process reduces the graph data to a suitable size without too much loss of similarity to the original *** paper presents our method of data cleaning on the software *** use SEQUITUR data compression algorithm to find out hot code path and store it as a whole paths directed acyclic *** code path is inherent regularity of a *** 10 to 200 hot code path account for 40%-99%of a program’s execution *** hot paths are acyclic contribute more than 0.1%-1.0%of some execution *** expand hot code path to a suitable size which is good for runtime and keeps similarity to the original graph.

关键词： Hot code path expanded hot path software graph software graph

4.1 Ga old detrital zircon in western Tibet of China

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Chinese Science Bulletin 2007年第1期52卷 23-26页

作者： DUO Ji WEN ChunQi GUO JianCi fan xiaoping LI XiaoWen Tibet Bureau of Geology and Mineral Exploration and Development Lhasa 850000 China Chengdu University of Technology Chengdu 610059 China

4.1 Ga old detrital zircon was found by SHRIMP U-Pb dating for quartz schist from Buring County in western Tibet, Southwest China. This is the oldest zircon U-Pb age found in China so far. The detrital zircon is a zircon of magmatic origin because its Th/ U ratios are 0.76 to 0.86. Two dates older than 4.0 Ga were measured only in one grain. U-Pb ages of 35 measured spots in 24 zircons can be subdivided into 6 groups, corresponding to at least 6 episodes of magmatic activity in the target area. The present results provide an important geochronological constraint on the geological evolution of Qinghai-Tibet Plateau.

关键词：锆石中国西藏地层

Visual abstraction of dynamic network via improved multi-class blue noise sampling

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Frontiers of Computer Science 2023年第1期17卷 171-185页

作者： Yanni PENG xiaoping fan Rong CHEN Ziyao YU Shi LIU Yunpeng CHEN Ying ZHAO fangfang ZHOU School of Computer Science and Engineering Central South UniversityChangsha 410083China Institute of Big Data Hunan University of Finance and EconomicsChangsha 410205China Rail Data Research and Application Key Laboratory of Hunan Province Changsha 410083China

Massive sequence view (MSV) is a classic timeline-based dynamic network visualization approach. However, it is vulnerable to visual clutter caused by overlapping edges, thereby leading to unexpected misunderstanding of time-varying trends of network communications. This study presents a new edge sampling algorithm called edge-based multi-class blue noise (E-MCBN) to reduce visual clutter in MSV. Our main idea is inspired by the multi-class blue noise (MCBN) sampling algorithm, commonly used in multi-class scatterplot decluttering. First, we take a node pair as an edge class, which can be regarded as an analogy to classes in multi-class scatterplots. Second, we propose two indicators, namely, class overlap and inter-class conflict degrees, to measure the overlapping degree and mutual exclusion, respectively, between edge classes. These indicators help construct the foundation of migrating the MCBN sampling from multi-class scatterplots to dynamic network samplings. Finally, we propose three strategies to accelerate MCBN sampling and a partitioning strategy to preserve local high-density edges in the MSV. The result shows that our approach can effectively reduce visual clutters and improve the readability of MSV. Moreover, our approach can also overcome the disadvantages of the MCBN sampling (i.e., long-running and failure to preserve local high-density communication areas in MSV). This study is the first that introduces MCBN sampling into a dynamic network sampling.

关键词： dynamic network visualization massive sequence view multi-class blue noise sampling visual abstraction

A Distributed Approach of Big Data Mining for Financial Fraud Detection in a Supply Chain

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Computers, Materials & Continua 2020年第8期64卷 1091-1105页

作者： Hangjun Zhou Guang Sun Sha Fu xiaoping fan Wangdong Jiang Shuting Hu Lingjiao Li Hunan University of Finance and Economics Changsha410205China College of Engineering The University of AlabamaTuscaloosaUSA

Supply Chain Finance(SCF)is important for improving the effectiveness of supply chain capital operations and reducing the overall management cost of a supply *** recent years,with the deep integration of supply chain and Internet,Big Data,Artificial Intelligence,Internet of Things,Blockchain,etc.,the efficiency of supply chain financial services can be greatly promoted through building more customized risk pricing models and conducting more rigorous investment decision-making ***,with the rapid development of new technologies,the SCF data has been massively increased and new financial fraud behaviors or patterns are becoming more covertly scattered among normal *** lack of enough capability to handle the big data volumes and mitigate the financial frauds may lead to huge losses in supply *** this article,a distributed approach of big data mining is proposed for financial fraud detection in a supply chain,which implements the distributed deep learning model of Convolutional Neural Network(CNN)on big data infrastructure of Apache Spark and Hadoop to speed up the processing of the large dataset in parallel and reduce the processing time *** training and testing on the continually updated SCF dataset,the approach can intelligently and automatically classify the massive data samples and discover the fraudulent financing behaviors,so as to enhance the financial fraud detection with high precision and recall rates,and reduce the losses of frauds in a supply chain.

关键词： Big data mining deep learning fraud detection supply chain Internet of Things

Visualization Analysis for Business Performance of Chinese Listed Companies Based on Gephi

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Computers, Materials & Continua 2020年第5期63卷 959-977页

作者： Guang Sun Hongzhang Lv Dianyu Wang xiaoping fan Yi Zuo Yanfei Xiao Xu Liu Wenqian Xiang Ziyi Guo Institute of Big Data Hunan University of Finance and EconomicsChangsha410205China Housheng School of International Education Hunan University of Finance and EconomicsChangsha410205China School of Information Science and Engineering Central South UniversityChangsha410075China School of Finance and Economics Hunan University of Finance and EconomicsChangsha410205China

When conducting company performance evaluations,the traditional method cannot reflect the distribution characteristics of the company’s operating conditions in the entire securities *** is an efficient tool for data analysis and visualization in the era of big *** can convert the evaluation results of all listed companies into nodes and edges,and directly display them in the form of graphs,thus making up for the defects of traditional *** paper will take all the listed companies in the Shanghai and Shenzhen Stock Exchange as the analysis *** uses tushare and web crawlers to collect the financial statement data of these *** then,uses the Economic Value Added model to calculate the EVA of each listed company and build graph ***,import the graph data into gephi to generate the distribution graph of all listed companies’performance,and summarize the distribution characteristics of business ***,select a listed company that you want to analyze in detail,using the traditional DuPont analysis method to conduct micro level visualization analysis of the business performance to find the main factors affecting the company’s operating *** gephi into traditional performance analysis methods will make the results of traditional analytical methods more effective and complete.

关键词： EVA gephi visualization graph analysis business performance evaluation