Deformation Transfer to Multi‐Component Objects

We present a simple and effective algorithm to transfer deformation between surface meshes with multiple components. The algorithm automatically computes spatial relationships between components of the target object, builds correspondences between source and target, and finally transfers deformation of the source onto the target while preserving cohesion between the target's components. We demonstrate the versatility of our approach on various complex models.     

基于VXI总线的噪声测试系统设计与应用

武器发射时产生的脉冲噪声对人员和仪器会造成很大的危害,因此噪声测试在武器勤务性能考核巾具有重要意义,针对脉冲噪声信号特性,开发了一套基于VXI总线的噪声测试系统;详细介绍了系统硬件结构设计、基于LabWindows/CVI虚拟仪器开发平台的软件设计和系统功能;设计的系统具有存储容量大、采样率高和软件功能强等特点,能够用于各种武器单发或连发射击时的噪声测试,也可以用于武器非行驶状态下的稳态噪声测试;通过在试验中的应用,表明本系统操作简便,工作可靠.     

空间数据库中一种自适应的缓存替换策略

随着近年来空间数据库研究和应用的不断深入,针对空间数据库中数据组织和查询的特征来设计缓存页面替换策略成为一个新的研究问题.Voronoi图是一种重要的空间数据库组织技术,在处理kNN查询时具有非常好的性能.针对Voronoi图组织的空间数据库,首先利用空间局部性提出了一种基于欧氏距离的替换策略,在发生页面失效时选择距离上一次访问页面欧氏距离最远的页面进行替换;进一步,针对不同kNN查询的搜索空间大小差异非常大的特点,在LIRS替换策略基础上提出一种自适应替换策略,通过对HIR页面占缓存比例自动调整来适应不同的查询.综合两者,形成基于欧氏距离的自适应缓存页面替换算法AELIRS.大量实验表明,在缓存大小与搜索空间大范围变动中,AELIRS始终优于其他替换策略.     

基于粗糙集与粗糙元神经网络的三峡库区水质评价模型

粗糙集和粗糙元神经网络相结合进行三峡库区水质评价.针对评价因子较多,通过粗糙集进行数据预处理,降低模型的复杂性.对于库区数据非精确值或范围值时,采用粗糙元神经网络建立评价模型,提高了系统的正确性和可理解性,并将其应用在三峡库区水环境安全系统中.     

Disc cutters plane layout design of the full-face rock tunnel boring machine (TBM) based on different layout patterns

The quality of plane layout design of the disc cutters for the full-face rock tunnel boring machine (TBM) directly affects the balance of force distribution on the cutter head during the excavating. Various layout patterns have been adopted in practice during the layout design of the disc cutters. Considering the engineering technical requirements and the corresponding structure design requirements of the cutter head, this study formulates a nonlinear multi-objective mathematical model with multiple constraints for the disc cutters plane layout design, and analyses the characteristics of a multi-spiral layout pattern, a dynamic star layout pattern and a stochastic layout pattern. And then a genetic algorithm is employed to solve a disc cutters’ multi-spiral layout problem, and a cooperative co-evolutionary genetic algorithm (CCGA) is utilized to solve a disc cutters’ star or stochastic layout problems. The emphasis was put on the study of superiority of three different layout patterns. Finally, an instance of the disc cutters’ plane layout design was solved by the proposed methods using three different kinds of layout patterns. Experimental results showed the effectiveness of the method of combining the mathematical model with the algorithms, and the pros and cons of the three layout patterns.     

Identifying mislabeled training data with the aid of unlabeled data

This paper presents a new approach for identifying and eliminating mislabeled training instances for supervised learning algorithms. The novelty of this approach lies in the using of unlabeled instances to aid the detection of mislabeled training instances. This is in contrast with existing methods which rely upon only the labeled training instances. Our approach is straightforward and can be applied to many existing noise detection methods with only marginal modifications on them as required. To assess the benefit of our approach, we choose two popular noise detection methods: majority filtering (MF) and consensus filtering (CF). MFAUD/CFAUD is the new proposed variant of MF/CF which relies on our approach and denotes majority/consensus filtering with the aid of unlabeled data. Empirical study validates the superiority of our approach and shows that MFAUD and CFAUD can significantly improve the performances of MF and CF under different noise ratios and labeled ratios. In addition, the improvement is more remarkable when the noise ratio is greater.     

Face recognition based on extreme learning machine

Extreme learning machine (ELM) is an efficient learning algorithm for generalized single hidden layer feedforward networks (SLFNs), which performs well in both regression and classification applications. It has recently been shown that from the optimization point of view ELM and support vector machine (SVM) are equivalent but ELM has less stringent optimization constraints. Due to the mild optimization constraints ELM can be easy of implementation and usually obtains better generalization performance. In this paper we study the performance of the one-against-all (OAA) and one-against-one (OAO) ELM for classification in multi-label face recognition applications. The performance is verified through four benchmarking face image data sets.     

HIMAC协处理器流量控制设计与实现

为了防止非法的业务流消耗系统过多的资源,并且控制每个端口占用的带宽,需要对进入HINOC系统的业务流流量进行限制.本文提出了HINOC MAC (HIMAC)的流量控制方案.本设计的特别之处在于,它允许根据各个端口业务量的大小,动态地调整分配给它们的带宽,并且设计方案简单可行.     

基于数据挖掘技术网络化训练分析系统研究与实现

对于教育测评所积累的大量数据,通过数据挖掘技术能产生出对学生、教师、教育管理者有用的知识。为此,从教育测评的目的、数据准备、数据积累方法,到数据的知识挖掘等几个方面,系统地研究了教育测评的知识发现的过程,并分别就三种需求的知识发现方法进行探讨,以改变教育测评仅能提供定性的结论而不能发现知识的状况,丰富教育测评的内涵。