基于DoDAF的武器装备体系需求分析方法

武器装备体系是为提供预期能力而组合在一起的相互依赖的武器装备系统的集合,武器装备体系需求分析是当前装备需求论证的热点和难点问题.在简要分析了武器装备体系需求研究现状的基础上,通过对比结构化分析方法和面向对象分析方法的优缺点,提出综合利用两类方法,基于DoDAF标准进行体系需求组合建模的基本思路和基本步骤,从体系的角度实现作战需求向装备需求的映射,对如何进一步完善体系需求分析方法提出针对性的建议.     

基于案例表示及语义匹配的装备故障辅助诊断方法

为满足装备故障快速诊断需求,将案例推理技术与文本语义相似度算法相结合,构建了一种基于句向量的装备故障案例的语义相似度匹配算法。根据装备故障信息的特点,结合面向对象的案例表示方法,在优选装备故障现象文本相似度计算方法和装备故障信息的权重合理分配的基础上,提出了基于句向量的装备故障案例相似度综合计算方法（综合法）。针对1 000个故障案例,在有无增加干扰项的情况下开展实验分析,结果表明,提出的综合法在有无干扰项情况下都能取得最好的故障案例匹配效果,既能根据案例相似度给出推荐案例的正确排序,又有较好的区分度。     

基于相对相似度关系的三角模糊数型不确定多属性决策法

针对属性权重未知的三角模糊数型不确定多属性决策问题, 提出一种新的规范三角模糊数与决策方案的相对相似度定义和三角模糊数相对相似度关系理论; 借鉴合作博弈中可能度最大化算法提出一种基于三角模糊数相对相似度关系的属性权重确定方法; 利用备选方案对象在方案集中的总体相对相似度值大小选取最优对象并排序, 以此给出三角模糊数型不确定多属性决策的相对相似度关系算法, 最后通过算例分析表明了所提出算法的可行性和有效性.     

基于多视图的武器装备体系需求分析方法

为了有效、正确地进行武器装备体系需求分析,提出基于多视图的武器装备体系需求分析方法。该方法以多视图方法论的思想为基础,提出武器装备体系的需求描述框架,该框架包括能力需求、装备需求和保障需求等三个视图,每个视图又包括一系列的产品;介绍武器装备体系需求的分析过程,并分析每个过程的含义和任务。     

装备保障信息系统需求分析中的问题及对策

为了开发满足需求的装备保障信息系统,就必须以需求为牵引,将需求分析作为信息系统开发的关键环节.而目前装备保障信息系统开发的需求分析实践中,存在着过于强调系统功能设计、缺乏stakeholders间协调和沟通机制、缺少统一有效的交流沟通语言以及忽视和淡化需求易变性等问题.针对需求分析存在的上述问题,对以结构化分析方法和面向对象分析方法为代表的主流需求分析方法的不足进行了反思,提出了基于SSM解决需求分析中"软"问题的策略.     

基于相似理论的装备研制MPT分析系统研究与实现

针对装备研制阶段预测人力、人员及训练MPT(manpower,personnel and training)需求的问题,提出了基于相似理论及新系统、原系统、基准比较系统和建议系统的MPT需求分析思想,建立了由多级相似元组成的装备相似比较模型,并确定了MPT需求分析的过程和输入、输出.在上述分析的基础上,设计和开发了装备研制MPT需求分析系统(EDMPTRAS),主要包括系统总体设计、功能设计和数据库设计.最后,结合某自行火炮的研制过程进行了系统实现和应用,证明了系统的可用性和有效性.     

面向过程的装备需求论证信息资源获取方法

为提高装备需求论证过程中信息资源服务的针对性与有效性,面向装备需求论证业务过程,提出一种信息资源获取方法。基于WBS方法,提出装备需求论证过程的活动组成及其元模型;通过构建活动-信息需求矩阵,提出装备需求论证信息资源的分类、内容及其描述要求;定义装备需求论证信息资源描述框架,提出信息资源实例的生成方法。采用该方法能够实现面向装备需求论证过程的信息资源按需服务能力。以作战任务需求分析活动的信息资源需求分析为例,验证了该方法的可用性和有效性。     

基于石油领域本体的概念相似度级联模型

提出了一种利用级联模型来计算本体中概念间相似度的新方法.在模型的第一阶段,采用了基于距离的语义相似度计算方法,计算出概念对在本体中的路径得分;第二阶段,采用IC （Information Content）算法精确计算概念对间相似度得分,并利用概念的公共子代集合对算法进行了扩展;第三阶段我们采用了特征整合策略,将所有的相似性得分构建成特征向量来描述概念对,并且使用权重来平衡第一阶段与第二阶段的相似度结算得分.最后使用BP神经网络确定两个概念的相似性.我们对新提出的语义相似度算法进行了评估,并与现有的方法相比.实验结果表明,该方法有效提高相似度算法的准确性和科学性.     

一种自发性口语评测文本语义相似度评分特征提取方法

自发性口语评测中如何提取文本语义相似度评分特征是一个非常困难的问题。针对这个问题本文采用基于词网络(WordNet)的Lesk算法计算词与词之间的语义相似度,在词义相似度的基础上提出了词与文本之间的语义相似度算法,提出了一种完整的基于词网络的文本语义相似度评分特征提取方法。实验利用该方法在考生答案与标准答案之间中提取文本语义相似度评分特征,并利用该特征与老师评分进行相关度分析,实验结果表明该算法可以有效的表征考生答案和标准答案之间的文本语义相似度。     

用户评论中产品特征的抽取及聚类

在用户评论中蕴含了大量的产品特征和用户对这些特征的观点和态度.本研究提出了基于Apriori关联规则算法的产品特征抽取方法,利用与种子特征集合的互信息和与观点词的共现度对候选特征进行过滤;并提出了一种特征自动聚类方法,以特征词间的字符串相似度和语义相似度以及特征所对应的观点词作为衡量产品特征之间关联程度的特征,采用K-means聚类算法对产品特征进行聚类.本研究采用大众点评网对美食店铺的评论语料,对该方法进行了数据实验,实验结果初步验证了该方法有效性.     

Fast and precise points-to analysis

Many software engineering applications require points-to analysis. These client applications range from optimizing compilers to integrated program development environments (IDEs) and from testing environments to reverse-engineering tools. Moreover, software engineering applications used in an edit-compile cycle need points-to analysis to be fast and precise.In this article, we present a new context- and flow-sensitive approach to points-to analysis where calling contexts are distinguished by the points-to sets analyzed for their call target expressions. Compared to other well-known context-sensitive techniques it is faster in practice, on average, twice as fast as the call string approach and by an order of magnitude faster than the object-sensitive technique. In fact, it shows to be only marginally slower than a context-insensitive baseline analysis. At the same time, it provides higher precision than the call string technique and is similar in precision to the object-sensitive technique. We confirm these statements with experiments using a number of abstract precision metrics and a concrete client application: escape analysis.     

源代码分析技术的理论与实践发展

源代码分析技术对于软件安全缺陷分析是一项非常重要的手段.分析了软件源代码分析工具的技术手段和发展过程,最后对源代码分析的理论和实践进行了分析总结.     

C语言的别名分析方法研究

别名分析对于数据流分析、程序优化和分析工具的实现非常重要.文章提出了一种需求驱动,流非敏感的分析算法来解决指针别名问题.通过构造程序表达式图(PEG)把指针别名问题转化成判断两个指针节点是否是联通的问题,它不同于传统的别名分析方法,它不需要构造别名集合和对其求交集,所以提高了分析指针别名的效率.     

The use of protocol analysis for determining ability requirements for personnel selection on a computer-based task

Abstract

The role of cognitively oriented tasks in the workplace continues to increase as automation of physical task components advances. Difficulties in automating the operator's cognitive processes have placed a renewed emphasis on the human component in advanced manufacturing systems. While traditional task analysis techniques have made significant contributions to improving productivity when important task elements are visually observable, their focus on manual task procedures make them less effective for cognitively oriented activities. This research has made a first attempt at integrating techniques from several disciplines to develop a cognitive task analysis methodology. The utility of this combined approach is examined for a new system being tested in the United States Postal Service. This task requires operators to encode, via a keyboard, addresses presented on a video display terminal. Results support the hypothesis that, for cognitively oriented tasks, a consensus based analysis technique (the Position Analysis Questionnaire) can be significantly improved by including data from task analysis provided the methodology is suitable for identifying non-physical task components.     

A system to assist survey analysts

The researcher who knows little about computers but wants to conduct a survey and analyse the results by computer can land himself in some difficulty if he does not appreciate some of the problems of computerization. This paper describes a system which is designed to aid such a person by providing assistance with the design of the questionnaire, the capturing of the data and the final analyses.     

A novel analysis space for pointer analysis and its application for bug finding

The size of today’s programs continues to grow, as does the number of bugs they contain. Testing alone is rarely able to flush out all bugs, and many lurk in difficult-to-test corner cases. An important alternative is static analysis, in which correctness properties of a program are checked without running it. While it cannot catch all errors, static analysis can catch many subtle problems that testing would miss.We propose a new space of abstractions for pointer analysis—an important component of static analysis for C and similar languages. We identify two main components of any abstraction—how to model statement order and how to model conditionals, then present a new model of programs that enables us to explore different abstractions in this space. Our assign-fetch graph represents reads and writes to memory instead of traditional points-to relations and leads to concise function summaries that can be used in any context. Its flexibility supports many new analysis techniques with different trade-offs between precision and speed.We present the details of our abstraction space, explain where existing algorithms fit, describe a variety of new analysis algorithms based on our assign-fetch graphs, and finally present experimental results that show our flow-aware abstraction for statement ordering both runs faster and produces more precise results than traditional flow-insensitive analysis.     

基于因子分析法和聚类分析法的副省级城市宜居情况聚类评价

重点选取了15个副省级城市的第一产业比重、人口密度、人均绿地、园林面积、医院数目,市政建设面积、地方财政税收等42个指标,使用SPSS作为计算工具,使用因子分析方法简化评价指标,计算相关系数矩阵,判别因子分析可行性,利用主成分分析法求因子载荷,将因子进行旋转得出更有实际意义的因子解释,并计算因子得分,利用该结果计算Mi...     

Cost analysis of object-oriented bytecode programs

Cost analysis statically approximates the cost of programs in terms of their input data size. This paper presents, to the best of our knowledge, the first approach to the automatic cost analysis of object-oriented bytecode programs. In languages such as Java and C#, analyzing bytecode has a much wider application area than analyzing source code since the latter is often not available. Cost analysis in this context has to consider, among others, dynamic dispatch, jumps, the operand stack, and the heap. Our method takes a bytecode program and a cost model specifying the resource of interest, and generates cost relations which approximate the execution cost of the program with respect to such resource. We report on COSTA, an implementation for Java bytecode which can obtain upper bounds on cost for a large class of programs and complexity classes. Our basic techniques can be directly applied to infer cost relations for other object-oriented imperative languages, not necessarily in bytecode form.     

数据分析需求与实现

数据分析是从海量数据中发现隐含信息或知识的过程。基于一个公安破案辅助数据分析系统,深入研究数据分析任务的需求与实现,提出首先规划分析思路、细化分析功能,然后用多视角数据透视和智能分析两种手段,从微观与宏观、定量与定性等不同角度互为补充地使系统具有完备的分析功能。该研究对如何开发具有实用价值的数据分析系统有普遍的指导意义。