Efficient multilevel image segmentation through fuzzy entropy maximization and graph cut optimization

The fuzzy c-partition entropy has been widely adopted as a global optimization technique for finding the optimized thresholds for multilevel image segmentation. However, it involves expensive computation as the number of thresholds increases and often yields noisy segmentation results since spatial coherence is not enforced. In this paper, an iterative calculation scheme is presented for reducing redundant computations in entropy evaluation. The efficiency of threshold selection is further improved through utilizing the artificial bee colony algorithm as the optimization technique. Finally, instead of performing thresholding for each pixel independently, the presented algorithm oversegments the input image into small regions and uses the probabilities of fuzzy events to define the costs of different label assignments for each region. The final segmentation results is computed using graph cut, which produces smooth segmentation results. The experimental results demonstrate the presented iterative calculation scheme can greatly reduce the running time and keep it stable as the number of required thresholds increases. Quantitative evaluations over 20 classic images also show that the presented algorithm outperforms existing multilevel segmentation approaches.     

Tool path generation framework for accurate manufacture of complex 3D sheet metal parts using single point incremental forming

The prototyping of complex sheet metal parts using single point incremental forming (SPIF) requires the generation of optimal tool paths and/or tool path sequences that ensure that the formed part is within geometric design specifications. The presence of a multitude of features on complex parts leads to multiple inaccuracy inducing phenomena occurring simultaneously due to interactions between the features. This paper proposes a network analysis methodology using topological conceptual graphs to capture the effects of different phenomena on the final accuracy of a sheet metal part manufactured by SPIF. Using this framework optimized tool paths can be generated that compensate for the inaccuracy inducing behavior. Tool path generation algorithms to create partial tool paths that account for the accuracy of specific features in the part based on the proposed framework are also presented. Finally, the creation of integrated tool paths maintaining complementarity between tool paths and desired continuity behavior using non-uniform cubic B-splines is illustrated. A number of case studies demonstrating the applicability of the integrated framework are discussed, where the maximum deviations in the part are significantly reduced and the average absolute deviations for the complete part are brought down to less than 0.5 mm.     

Strategies and methods for cloud migration

Legacy system migration to the cloud brings both great challenges and benefits, so there exist various academic research and industrial applications on legacy system migration to the cloud. By analyzing the research achievements and application status,we divide the existing migration methods into three strategies according to the cloud service models integrally. Different processes need to be considered for different migration strategies, and different tasks will be involved accordingly. The similarities and differences between the migration strategies are discussed, and the challenges and future work about legacy system migration to the cloud are proposed. The aim of this paper is to provide an overall presentation for legacy system migration to the cloud and identify important challenges and future research directions.     

A New Risk Assessment Approach for Cloud Consumer

The cloud computing introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. Consequently, there is a need of risk assessment approach adapted to cloud computing. With such an approach, the cloud consumers can be guaranteed the effectiveness of data security and the cloud providers can win the trust of their cloud consumers. This paper requires the formalization of risk assessment method for conventional system as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.     

变电运行倒闸操作的危险点及预防对策探究

在实际操作中,由于变电运行非常复杂,很容易出现危险,因此,做好相关危险点的分析和预防工作,对保证电力系统运行安全有着非常重要的意义。结合变电运行倒闸操作中的危险点,对其预防对策进行了分析和探讨。     

地籍测量中界址点的精度影响因素与技术对策

简单介绍了界址点精度及其测量方法,分析了棱镜偏心对测量误差的影响,并提出了一些技术对策。     

基于随机游走模型的维基百科语义关系研究

运用随机游走模型提出了一种基于维基百科的语义相关度的计算方法。维基百科中包含了丰富的链接结构,这些链接结构一定程度上能够反应词条之间概念上的相关性,以内容链接和外部链接关系来计算基于维基百科的语义相关度,并在WS-353数据集上进行了实验,取得了较好的准确性。     

一种融合多帧ICP和图优化的算法研究

当前基于迭代最近点拼接的同时定位与建图算法,存在误差积累、无法满足大范围定位精度的缺陷。为此,提出一种融合多帧迭代最近点和图优化的算法。在时域上处理点云拼接问题,将单帧迭代最近点算法推广到多帧进行最近点迭代,提取同一地点在不同时刻的数据特征,形成多个封闭循环,再运用基于最小二乘的图优化方法对点云拼接后的全网数据进行全局优化,消除累计误差,提升整体的定位精度。采用鲁巷和密歇根的数据进行测试,结果表明,该方法在一定程度上减少了匹配误差,平均误差为1.0m,最小误差为0.2m,可以满足大范围同步定位与建图的精度需求。     

基于自然语言处理的算法知识名称发现

网络中的很多程序资源在知识概念上有内在的联系,却没有超链接将它们连接在一起。将网络程序资源中的算法知识名称获取出来,组织成一个算法知识专家库文件,用于识别程序设计资源所含的知识点,即可将程序设计资源按知识点相互联系。为了自动获取程序资源中的算法知识名称,提出一种基于自然语言处理的算法知识名称发现方法。通过发现含有算法知识名称语句的字符串模式,从程序资源中提取可能含算法知识名称的字符串,从中找出最有可能出现在算法知识名称中的分词,并根据这些分词获取算法知识名称。实验结果表明,与原有人工整理出的算法知识名称集合相比,该方法新增了11.2%的算法知识点和13.6%的算法知识名称。