瓦斯尾巷在高档普采工作面的应用

介绍了高档普采工作面利用掘送瓦斯尾巷等措施形成回风空间 ,从根本上解决高档普采工作面的瓦斯超限问题 ,其工艺有利于在其它采煤工作面内应用     

Metaheuristic downhill simplex method in combinatorial optimization

The concept of combinatorial objects is formalized. It allows strict definition of a combinatorial optimization problem (COP). An efficient metaheuristic method to solve COPs (H-method) is considered. It includes stochastic local search algorithms as a built-in procedure. A parallel implementation of the H-method is set forth and analyzed. The results from a numerical experiment and solution of some well-known COPs on personal computers and on the SKIT cluster supercomputer are presented. The study was supported by INTAS (Project 06-1000017-8909). __________ Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 70–79, November–December 2007.     

孤东油田的海油陆采进展

孤东油田极浅海区域新发现几个边际油藏。其中垦东401块水深-2m,距陆地2.7km,为稀油、疏松砂岩油藏,试油获14～25t/d工业油流。在三维地震、测井约束地震反演、数值模拟和油藏经营管理评价基础上编制了产能建设方案,通过修筑海公路、人工岛、丛式井组、大位移水平井、采用数据采集与控制的远程测控和紧急关断技术,能够无人职守、遥测遥控,整体实现了海油陆采。有效动用地质储量233×104t,钻井12口,建成年产油4×104t能力,累产油8.6×104t。目前在垦东12人工岛上钻打了26口井,推广了海油陆采经验。     

A design and analysis of objective function-based unsupervised neural networks for fuzzy clustering

Fuzzy clustering has played an important role in solving many problems. In this paper, we design an unsupervised neural network model based on a fuzzy objective function, called OFUNN. The learning rule for the OFUNN model is a result of the formal derivation by the gradient descent method of a fuzzy objective function. The performance of the cluster analysis algorithm is often evaluated by counting the number of crisp clustering errors. However, the number of clustering errors alone is not a reliable and consistent measure for the performance of clustering, especially in the case of input data with fuzzy boundaries. We introduce two measures to evaluate the performance of the fuzzy clustering algorithm. The clustering results on three data sets, Iris data and two artificial data sets, are analyzed using the proposed measures. They show that OFUNN is very competitive in terms of speed and accuracy compared to the fuzzy c-means algorithm.     

一种基于数据竞争的高分辨率图像的聚类分割算法

近些年,机器人技术得到了迅猛的发展,应用越来越广泛.随着机器人技术的推广和普及,对机器人使用的要求也越来越高,其中对智能机器人的要求尤显迫切.机器视觉是智能机器人研究领域的一个重要研究方向.在机器人视觉系统中,核心问题是目标提取,对目标实时、准确、快速提取的关键技术是图像分割.由于机器人感知的环境的复杂性及目标的多样性,往往导致机器人感知获得的图像数据量较大且图像本身存在不可预知的复杂性,这就对准确的目标分割和提取处理提出了挑战性问题.本文针对高分辨率图像数据集的分割处理,提出一种新的聚类算法,即根据数据点能量和的大小识别类代表点和类成员点,通过数据点间的竞争识别出最有能力成为簇成员的数据点,并将其与mean shift聚类算法有效地结合应用于彩色图像分割问题中,能够快速高效地实现高分辨率图像的目标分割,并得到较好的图像分割效果.实验结果表明,本文算法在分割效果和分割效率上明显优于传统聚类算法.     

Group technology based adaptive cell formation using predator-prey genetic algorithm

In recent years, there has been a considerable growth of application of group technology in cellular manufacturing. This has led to investigation of the primary cell formation problem (CFP), both in classical and soft-computing domain. Compared to more well-known and analytical techniques like mathematical programming which have been used rigorously to solve CFPs, heuristic approaches have yet gained the same level of acceptance. In the last decade we have seen some fruitful attempts to use evolutionary techniques like genetic algorithm (GA) and Ant Colony Optimization to find solutions of the CFP. The primary aim of this study is to investigate the applicability of a fine grain variant of the predator-prey GA (PPGA) in CFPs. The algorithm has been adapted to emphasize local selection strategy and to maintain a reasonable balance between prey and predator population, while avoiding premature convergence. The results show that the algorithm is competitive in identifying machine-part clusters from the initial CFP matrix with significantly less number of iterations. The algorithm scaled efficiently for large size problems with competitive performance. Optimal cluster identification is then followed by removal of the bottleneck elements to give a final solution with minimum inter-cluster transition cost. The results give considerable impetus to study similar NP-complete combinatorial problems using fine-grain GAs in future.     

Estimating room temperatures from fires along walls and in corners

Determination of temperatures associated with room fires provides a means of assessing an important aspect of fire hazard: the likelihood of the occurrence of flashover. Layer temperatures in excess of 600°C have been associated with the occurrence of flashover. A data correlation has previously been presented to estimate layer temperatures for fires burning in the center of rooms. For fires in corners and along walls, restricted entrainment results in higher layer temperatures than predicted by the previous correlation. Modification factors for the previous correlation are developed to extend its applicability to wall and corner burning geometries. The present analysis suggests that a fire in a corner may cause flashover with only half the heat release rate necessary for a fire burning in the center of a room. Reference: Frederick Mowrer and Robert Williamson, Estimating Room Temperatures from Fires along Walls and in Corners,Fire Technology, Vol. 23, May 1987, pp. 133–145.     

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.     

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.