A robust critical path in an environment with hybrid uncertainty

In this article, we consider the project critical path problem in an environment with hybrid uncertainty. In this environment, the duration of activities are considered as random fuzzy variables that have probability and fuzzy natures, simultaneously. To obtain a robust critical path with this kind of uncertainty a chance constraints programming model is used. This model is converted to a deterministic model in two stages. In the first stage, the uncertain model is converted to a model with interval parameters by alpha-cut method and distribution function concepts. In the second stage, the interval model is converted to a deterministic model by robust optimization and min-max regret criterion and ultimately a genetic algorithm with a proposed exact algorithm are applied to solve the final model. Finally, some numerical examples are given to show the efficiency of the solution procedure.     

燃煤锅炉供热系统的模糊控制

介绍燃煤锅炉供热系统的自动化节能模糊控制方案,燃煤锅炉供热系统是一个大惯性的滞后系统,传统的单纯PID控制效果不理想,而基于工人熟练的经验和专家知识的模糊控制能够达到比较好的效果。系统中对控制参考量水温和炉膛负压这两个输入量模糊化处理,由控制规则推出输出模糊子集,再应用模糊推理合成规则得出PID的系数,PID控制器根据输出量来控制鼓风机、引风机、炉排电机和水泵的变频器。     

低温裂纹张开位移预测方法的讨论

把低温影响下的COD试验数据用灰色理论中的累加方法进行累加，可以使一组没有规律的数据成为一条光滑的曲线．然后利用人工神经网络和自适应模糊推理系统两种方法进行预测，算例的结果表明用一次累加后的数列预测精度较高。     

电液系统位置精度的模糊控制

针对电液位置控制系统 ,建立了其数学模型 ,研究了模糊控制器在该场合的应用及其设计 ,并在SIMULINK环境下对模糊控制系统进行了仿真。结果显示模糊控制用于电液系统位置控制能获得令人满意的效果     

Characterization and Reconstitution of Human Lipoyl Synthase (LIAS) Supports ISCA2 and ISCU as Primary Cluster Donors and an Ordered Mechanism of Cluster Assembly

Lipoyl synthase (LIAS) is an iron–sulfur cluster protein and a member of the radical S-adenosylmethionine (SAM) superfamily that catalyzes the final step of lipoic acid biosynthesis. The enzyme contains two [4Fe–4S] centers (reducing and auxiliary clusters) that promote radical formation and sulfur transfer, respectively. Most information concerning LIAS and its mechanism has been determined from prokaryotic enzymes. Herein, we detail the expression, isolation, and characterization of human LIAS, its reactivity, and evaluation of natural iron–sulfur (Fe–S) cluster reconstitution mechanisms. Cluster donation by a number of possible cluster donor proteins and heterodimeric complexes has been evaluated. [2Fe–2S]-cluster-bound forms of human ISCU and ISCA2 were found capable of reconstituting human LIAS, such that complete product turnover was enabled for LIAS, as monitored via a liquid chromatography–mass spectrometry (LC–MS) assay. Electron paramagnetic resonance (EPR) studies of native LIAS and substituted derivatives that lacked the ability to bind one or the other of LIAS’s two [4Fe–4S] clusters revealed a likely order of cluster addition, with the auxiliary cluster preceding the reducing [4Fe–4S] center. These results detail the trafficking of Fe–S clusters in human cells and highlight differences with respect to bacterial LIAS analogs. Likely in vivo Fe–S cluster donors to LIAS are identified, with possible connections to human disease states, and a mechanistic ordering of [4Fe–4S] cluster reconstitution is evident.     

基于模糊数学的高维稀疏数据聚类统计方法设计

传统的数据聚类统计方法仅适用于低维数据聚类问题,为此,本研究设计了基于模糊数据的高维稀疏数据聚类统计方法,以期提升高维稀疏数据的聚类统计效果。以模糊C均值聚类算法为基础,通过优化初始聚类中心解决局部最优问题,缩短聚类统计时间;然后引入权重机制,令该方法适用于高维稀疏数据聚类统计。基于此,以余弦距离替换原有的欧几里德距离,提高高维稀疏数据聚类统计效果。实验证明：在数据维度不同时,该方法均有较优的聚类统计效果。当数据维度较低时,分块比例为10%时聚类统计效果最优;当数据维度较高时,分块比例为40%时聚类统计效果最优。在不同稀疏度等级时,该方法的命中率和聚类统计效率均较高。     

基于数据融合的ABC-SVM社区疾病预测方法

针对现有社区医疗服务中的疾病预测方法存在数据利用率低、疾病分析类型单一、自动化程度差、疾病预测效果不理想等不足,提出在物联网大数据环境下可用于社区医疗的健康数据融合及疾病预测方法. 通过主成分分析(PCA)和聚类分析对社区中居民的生理指标数据进行特征提取;结合人工蜂群(ABC)算法构造支持向量机(SVM)非线性分类器对数据进行特征级融合分析并预测潜在疾病. 实验结果表明,所提方法的疾病识别准确率达到93.10%,相较于传统SVM方法和BP神经网络方法分别提高17.24% 和72.41%. 该方法能够在提高数据利用率、降低计算资源消耗的前提下有效识别多种潜在疾病,可实现疾病早发现、早预防、早治疗;可广泛应用于社区健康管理、老年社区监护甚至临床医疗.     

一种新颖的低层视觉特征到高层语义的映射方法*

通过在低层视觉特征上提取图像的局部颜色和纹理特征,再利用模糊神经网络建立低层视觉特征和高层语义特征之间的映射,实现了图像属性信息的有效传递和可靠检索.最后,为了提高检索效率,把相关反馈引进到图像检索系统中.实验证明,该方法取得了较好的检索查全率和准确率.     

基于邻域彩色变化矢量场的图像边缘检测技术研究*

首先进行了边缘检测系统结构设计,建立了图像邻域彩色变化矢量场的数理模型,提出了用图像邻域彩色变化方向锐度描述图像边缘,进而应用模糊聚类自适应检测边缘.实验表明:与基于梯度的边缘检测技术相比,该方法在噪声抑制以及边缘准确定位上均取得了好的效果,是一种应用广泛的优秀边缘检测算法.     

C JDBC：可扩展的数据库集群中间件

多层软件结构中已经成功地应用了集群,但在后台数据库上还缺乏这种工具,所以当数据库层出现瓶颈时,就得在硬件上花费高额的费用.开源数据库集群中间件--C-JDBC解决了上述问题.它通过JDBC接口引进了一个虚拟数据库,只要基于拥有JDBC驱动的数据库上面的应用程序,程序无须任何改动就能运行.C-JDBC具有灵活的体系结构,支持大型复杂的数据库集群体系结构,为数据库集群提供的高性能、强容错能力、易用的平台.