水库移民后期扶持监测评估研究

根据监测评估实践,对水库移民后期扶持监测评估的主要内容、指标体系、调查表格、工作步骤、方法等进行了系统总结。指出:水库移民后期扶持评估内容主要包括扶持政策实施情况,扶持资金的征收、使用和管理情况,扶持政策实施效果等;后期扶持监测评估指标体系由资金发放、项目实施、政策实施保障和政策实施效果4个一级指标构成,下设16个二级指标、40个三级指标;评估方法有统计分析、对比分析、参与式评价和综合评价。     

黏性浆液在小孔隙多孔介质中扩散的流固耦合分析

该文基于有效应力原理建立了描述黏性浆液在小孔隙多孔介质中扩散的流固耦合模型.通过对小孔隙多孔介质注浆过程中的浆液渗流场分布与固体骨架的应力应变特性的流固耦合分析,得到了各动态参数如孔隙率、应变率等的相互关系并在施工现场进行了试验.经过与施工现场试验数据对比,得到的数值分析结果与试验结果基本一致,验证了该流固耦合模型运用于注浆工程的可行性与实用性,可作为小孔隙多孔介质地层防渗注浆设计和注浆效果的初步评判.     

臭味层次分析法在上海市饮用水中的应用

介绍了臭味层次分析法(FPA)培训内容及其在上海市饮用水臭味识别中的应用。结果表明,经过培训的FPA臭味识别小组能够对水样中不同种类的异臭味进行定性和定量的评价分析;臭味检测人员对上海市水体中含有的典型致臭土霉味物质甲基异莰醇-2和腥臭味物质二甲基三硫的嗅阈值可分别达到1.69ng/L和24.4ng/L,并对这两种物质的强度等级评价有较好的重现性。采用FPA评价上海市地区原水及不同供水区域自来水的臭味特征及加标后不同浓度条件下的臭味强度特征,结果表明,FPA优于现行使用的臭味评价方法,能够及时、快速地反映水质问题,是可靠的感官分析方法。     

基于主题深度搜索的数学领域教育平台研究

论文综合利用主题搜索技术、深网信息集成技术和Wiki技术,设计并实现了一个面向数学领域的教育平台.此平台是一个集数学资源共享和用户交流的开放平台,用户在此平台可以利用数学Wiki添加、编辑、评论数学领域信息,提升自主学习能力,实现广泛交流.同时,还能利用数学搜索引擎搜索到专业的数学知识,定制URL检索,扩大检索范围,提高了平台的个性化服务水平及搜索的准确率.实验结果表明,文中基于SVM分类算法的数学主题网页分类器具有较高的准确率和召回率.     

基于Matlab GUI的干涉衍射实现方法的研究

在光的干涉和衍射理论的基础上,介绍了一种基于Matlab GUI的干涉和衍射的仿真方法,并有针对性地设计了Matlab程序,只需用户输入一些基本的设计参数,即可获得双缝干涉、单缝衍射、圆孔衍射或者光栅衍射的图样和光强分布曲线,具有操作简单、使用方便 和显示直观等特点,能够加深学生对波动光学的认识,并达到激发其学习兴趣的目的.     

Research in the Development of Finite Element Software for Creep Damage Analysis

This paper reports the development of finite element software for creep damage analysis. Creep damage deformation and failure of high temperature structure is a serious problem for power generation and it is even more technically demanding under the current increasing demand of power and economic and sustainability pressure. This paper primarily consists of three parts： （1） the need and the justification of the development of in-house software; （2） the techniques in developing such software for creep damage analysis; （3） the validation of the finite element software conducted under plane stress, plane strain, axisymmetric, and 3 dimensional cases. This paper contributes to the computational creep damage mechanics in general.     

A new image fusion performance metric based on visual information fidelity

Because subjective evaluation is not adequate for assessing work in an automatic system, using an objective image fusion performance metric is a common approach to evaluate the quality of different fusion schemes. In this paper, a multi-resolution image fusion metric using visual information fidelity (VIF) is presented to assess fusion performance objectively. This method has four stages: (1) Source and fused images are filtered and divided into blocks. (2) Visual information is evaluated with and without distortion information in each block. (3) The visual information fidelity for fusion (VIFF) of each sub-band is calculated. (4) The overall quality measure is determined by weighting the VIFF of each sub-band. In our experiment, the proposed fusion assessment method is compared with several existing fusion metrics using the subjective test dataset provided by Petrovic. We found that VIFF performs better in terms of both human perception matching and computational complexity.     

A chaotic non-dominated sorting genetic algorithm for the multi-objective automatic test task scheduling problem

Solving a task scheduling problem is a key challenge for automatic test technology to improve throughput, reduce test time, and operate the necessary instruments at their maximum capacity. Therefore, this paper attempts to solve the automatic test task scheduling problem (TTSP) with the objectives of minimizing the maximal test completion time (makespan) and the mean workload of the instruments. In this paper, the formal formulation and the constraints of the TTSP are established to describe this problem. Then, a new encoding method called the integrated encoding scheme (IES) is proposed. This encoding scheme is able to transform a combinatorial optimization problem into a continuous optimization problem, thus improving the encoding efficiency and reducing the complexity of the genetic manipulations. More importantly, because the TTSP has many local optima, a chaotic non-dominated sorting genetic algorithm (CNSGA) is presented to avoid becoming trapped in local optima and to obtain high quality solutions. This approach introduces a chaotic initial population, a crossover operator, and a mutation operator into the non-dominated sorting genetic algorithm II (NSGA-II) to enhance the local searching ability. Both the logistic map and the cat map are used to design the chaotic operators, and their performances are compared. To identify a good approach for hybridizing NSGA-II and chaos, and indicate the effectiveness of IES, several experiments are performed based on the following: (1) a small-scale TTSP and a large-scale TTSP in real-world applications and (2) a TTSP used in other research. Computational simulations and comparisons show that CNSGA improves the local searching ability and is suitable for solving the TTSP.     

A genetic algorithm for finding a path subject to two constraints

Multi-constrained routing (MCR) aims to find the feasible path in the network that satisfies multiple independent constraints, it is usually used for routing multimedia traffic with quality-of-service (QoS) guarantees. It is well known that MCR is NP-complete. Heuristic and approximate algorithms for MCR are not effective in dynamic network environment for real-time applications when the state information of the network is out of date. This paper presents a genetic algorithm to solve the MCR problem subject to transmission delay and transmission success ratio. Three key design problems are investigated for this new algorithm, i.e., how to encode the problem in genetic representation, how to avoid the illegal chromosomes in the process of population initialization and genetic operation, and how to design effective genetic operator. We propose the gene structure (GS) to deal with the first problem, and the gene structure algorithm (GSA) to generate the GS. Based on the GS, we provide the heuristic chromosome initialization and mutation operator to solve the last two problems. Computer simulations show that the proposed GA exhibits much faster computation speed so as to satisfy the real-time requirement, and much higher rate of convergence than other algorithms. The results are relatively independent of problem types (network scales and topologies). Furthermore, simulation results show that the proposed GA is effective and efficient in dynamic network environment.     

An efficient quantum search engine on unsorted database

We consider the problem of finding one or more desired items out of an unsorted database. Patel has shown that if the database permits quantum queries, then mere digitization is sufficient for efficient search for one desired item. The algorithm, called factorized quantum search algorithm, presented by him can locate the desired item in an unsorted database using O( $log_4N$ ) queries to factorized oracles. But the algorithm requires that all the attribute values must be distinct from each other. In this paper, we discuss how to make a database satisfy the requirements, and present a quantum search engine based on the algorithm. Our goal is achieved by introducing auxiliary files for the attribute values that are not distinct, and converting every complex query request into a sequence of calls to factorized quantum search algorithm. The query complexity of our algorithm is O( $log_4N$ ) for most cases.