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Further results on constructions of generalized bent Boolean functions

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Science China(Information Sciences) 2016年第5期59卷 242-244页

作者： Fengrong ZHANG shixiong xia Pantelimon STANICA Yu ZHOU School of Computer Science and Technology China University of Mining and Technology State Key Laboratory of Integrated Services Networks Xidian University Naval Postgraduate School Applied Mathematics Department Science and Technology on Communication Security Laboratory

Dear editor,Boolean bent functions were introduced by Rothaus in 1976 as an interesting combinatorial object with the important property of having optimal nonlinearity[1].Since bent functions have many applications in sequence design,cryptography and algebraic coding,they have been extensively studied during the last thirty years[2,3].Over the past decades,based on bent functions,several constructions of highly nonlinear balanced functions were presented[4,5].

关键词： Further results on constructions of generalized bent Boolean functions Zn

Real-Time Visual Tracking with Compact Shape and Color Feature

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Computers, Materials & Continua 2018年第6期55卷 509-521页

作者： Zhenguo Gao shixiong xia Yikun Zhang Rui Yao Jiaqi Zhao Qiang Niu Haifeng Jiang School of Computer Science and Technology China University of Mining and TechnologyXuzhou221116China School of Computer Science The University of AdelaideAdelaideSA 5005Australia

The colour feature is often used in the object *** tracking methods extract the colour features of the object and the background,and distinguish them by a ***,these existing methods simply use the colour information of the target pixels and do not consider the shape feature of the target,so that the description capability of the feature is ***,incorporating shape information often leads to large feature dimension,which is not conducive to real-time object ***,the emergence of visual tracking methods based on deep learning has also greatly increased the demand for computing resources of the *** this paper,we propose a real-time visual tracking method with compact shape and colour feature,which forms low dimensional compact shape and colour feature by fusing the shape and colour characteristics of the candidate object region,and reduces the dimensionality of the combined feature through the Hash *** structural classification function is trained and updated online with dynamic data flow for adapting to the new ***,the classification and prediction of the object are carried out with structured classification *** experimental results demonstrate that the proposed tracker performs superiorly against several state-of-the-art algorithms on the challenging benchmark dataset OTB-100 and OTB-13.

关键词： Visual tracking compact feature colour feature structural learning

Research on the User Interest Modeling of Personalized Search Engine

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Wuhan University Journal of Natural Sciences 2007年第5期12卷 893-896页

作者： LI Zhengwei xia shixiong NIU Qiang xia Zhanguo School of Computer Science and Technology China University of Mining and Technology Xuzhou 221008 Jiangsu China

At present, how to enable Search Engine to construct user personal interest model initially, master user＇s personalized information timely and provide personalized services accurately have become the hotspot in the research of Search Engine area. Aiming at the problems of user model＇s construction and combining techniques of manual customization modeling and automatic analytical modeling, a User Interest Model （UIM） is proposed in the paper. On the basis of it, the corresponding establishment and update algorithms of User lnterest Profile （UIP） are presented subsequently. Simulation tests proved that the UIM proposed and corresponding algorithms could enhance the retrieval precision effectively and have superior adaptability.

关键词： personalization Search Engine User Interest Model intellectual agent

一种面向嵌入式系统的进程间消息信方法的设计

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计算机工程 2005年第10期31卷 81-83页

作者：刘鹏夏士雄中国矿业大学计算机学院徐州221008

描述了具有典型意义的多CPU嵌入式系统的体系结构,详细介绍了一种应用于此种嵌入式系统的分布式操作系统进程间消息通信的方法,又将此方法和常用的分布式操作系统的进程间消息通信方法进行了比较。

关键词：嵌入式系统分布式操作系统进程间消息通信

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基于广义信息距离的直接聚类算法

计算机研究与发展 2007年第4期44卷 674-679页

作者：丁世飞史忠植靳奉祥夏士雄中国矿业大学计算机科学与技术学院徐州221008 中国科学院计算技术研究所智能信息处理重点实验室北京100080 山东科技大学地球信息科学与工程学院青岛266510

提出了基于广义信息距离的直接聚类算法.基于信息理论给出了离散量的基本概念,讨论并证明了离散量的一个基本不等式,进而给出了离散增量的概念.在分析距离测度的基础上,提出了广义信息距离(GID)、改进的广义信息距离(IGID),建立了基于GI... 详细信息

提出了基于广义信息距离的直接聚类算法.基于信息理论给出了离散量的基本概念,讨论并证明了离散量的一个基本不等式,进而给出了离散增量的概念.在分析距离测度的基础上,提出了广义信息距离(GID)、改进的广义信息距离(IGID),建立了基于GID,IGID的直接聚类算法,并对土地肥力数据资料进行了聚类分析.结果表明,建立的算法与传统的聚类算法相比,算法原理简便、对数据本身的维数与分布要求不高,且具有较好的聚类效果.

关键词：离散量离散增量广义信息距离直接聚类

Study on association rules mining based on semantic relativity

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Journal of Southeast University(English Edition) 2008年第3期24卷 358-360页

作者：张磊夏士雄周勇夏战国中国矿业大学计算机科学与技术学院徐州221116

An association rules mining method based on semantic relativity is proposed to solve the problem that there are more candidate item sets and higher time complexity in traditional association rules *** relativity of ontology concepts is used to describe complicated relationships of domains in the *** item sets with less semantic relativity are filtered to reduce the number of candidate item sets in association rules *** ontology hierarchy relationship is regarded as a directed acyclic graph rather than a hierarchy tree in the semantic relativity *** only direct hierarchy relationships,but also non-direct hierarchy relationships and other typical semantic relationships are taken into *** results show that the proposed method can reduce the number of candidate item sets effectively and improve the efficiency of association rules mining.

关键词： ontology association rules mining semantic relativity

基于三角形重心扫描的改进APIT无线传感器网络自定位算法

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计算机研究与发展 2009年第4期46卷 566-574页

作者：周勇夏士雄丁世飞张磊敖欣中国矿业大学计算机科学与技术学院江苏徐州221008 华南理工大学电子与信息学院广州510640

传感器节点的自定位问题是无线传感器网络的重要研究内容之一.APIT是一种主要的非基于测距的定位算法.相对于其他非基于测距定位算法,APIT具有定位精度高、通信开销小等优点.但是,APIT要求有较高的锚节点密度,而且在APIT测试过程中,边... 详细信息

传感器节点的自定位问题是无线传感器网络的重要研究内容之一.APIT是一种主要的非基于测距的定位算法.相对于其他非基于测距定位算法,APIT具有定位精度高、通信开销小等优点.但是,APIT要求有较高的锚节点密度,而且在APIT测试过程中,边界效应以及低邻居节点密度容易增加InToOut和OutToIn测试错误的发生次数.另外,APIT算法中的网格扫描算法对于OutToIn错误的容错性较差且其执行效率低.针对以上问题,提出了一种基于三角形重心扫描的改进APIT算法.首先,分析了APIT测试中的两种典型错误InToOut和OutToIn错误产生的原因,引入了对APIT测试方法的两处改进;然后,分析了网格扫描算法对节点定位精度和算法执行效率的影响,提出了一种三角形重心扫描法,有效改进了算法的定位精度和执行效率;最后,通过仿真实验验证了改进后的算法不但可以有效地减少InToOut和OutToIn两类错误发生的次数,提高平均定位精度,改善算法的性能,而且对OutToIn错误的容错性更强,执行效率更高,能够显著地提高节点的平均精度.

关键词：无线传感器网络自定位算法 APIT 网格扫描三角形重心扫描

Clustering analysis algorithm for security supervising data based on semantic description in coal mines

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Journal of Southeast University(English Edition) 2008年第3期24卷 354-357页

作者：孟凡荣周勇夏士雄中国矿业大学计算机科学与技术学院徐州221116

In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is ***,the semantic and numerical-based hybrid description method of security supervising data in coal mines is ***,the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is ***,taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference,an improved CURE clustering algorithm based on the grid is ***,the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.

关键词： semantic description clustering analysis algorithm similarity measurement

基于SVM二叉决策树方法的矿井提升机故障诊断

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微计算机信息 2008年第10期24卷 198-199,286页

作者：张磊夏士雄牛强中国矿业大学计算机科学与技术学院江苏徐州221008

介绍了几种传统的支持向量机(SVM)多分类方法,分析了其存在的问题及缺点。提出了一种基于二叉决策树的SVM多分类方法,该方法具有简单、直观,训练样本少的特点。通过将其应用于提升机运行状态的故障诊断,结果表明,采用该方法比传统多类SV... 详细信息

介绍了几种传统的支持向量机(SVM)多分类方法,分析了其存在的问题及缺点。提出了一种基于二叉决策树的SVM多分类方法,该方法具有简单、直观,训练样本少的特点。通过将其应用于提升机运行状态的故障诊断,结果表明,采用该方法比传统多类SVM方法和BP神经网络具有更高的诊断正确率。

关键词：支持向量机故障诊断二叉决策树矿井提升机