部队装备保障训练质量管理模式研究

对基于＂符合规定性＂质量观和基于＂符合需要性＂质量观的部队装备保障训练质量的内涵和实施过程进行了对比分析,指出了基于＂符合规定性＂质量观部队装备保障训练的局限性,建立了基于＂符合需要性＂质量观确定必训科目、训练需求和受训者的过程模型。     

基于能力的指挥信息系统体系需求分析过程?

借鉴了联合能力集成与分析系统的活动流程，根据指挥信息系统体系需求的特点，建立了基于能力的指挥信息系统体系需求分析的过程模型，围绕能力需求的获取、定义、分析与实现划分为4个子过程：背景分析、能力领域分析、能力需求分析、能力需求方案分析，并给出了4个阶段的基本活动和逻辑关系，为指挥信息系统体系需求的分析提供了规范的过程和活动指导。     

Artisanal small-scale opal mining (ASOM) insecurity in the Delanta wereda,Ethiopia: The shifting landscape of multidimensional insecurity in the face of emergent ASOM wealth

The commencement of opal mining in Ethiopia a decade ago has attracted the involvement of poor peasants, wealthy traders and traffickers. Although the academic and official literature on artisanal small-scale opal mining (ASOM) has primarily focused on the loss of wealth owing to a lack of skill and its traditional nature, this study explores the multidimensional insecurity that the discovery and mining of opal stones in the Delanta wereda of Wollo has brought about. This study contends that the ASOM industry has brought a new and previously unknown body of wealth to a society that is not used to the circulation of huge amounts of money in its narrow geography of commerce, engendering multidimensional insecurity. To make things worse, the network of patrimony and rentierism connecting locals with powerful people at the regional and federal level has given licence to illegal wealth extraction at the cost of exacerbating local insecurity. The qualitative data for the study was collected using interviews, focus group discussions, non-participant observations and document analyses at Delanta mining sites, the Wegel Tena town administration and Dessie city.     

智能化作战指挥模式需求

智能装备已经走入军队、走向战场,创建智能化作战指挥模式是智能化时代作战指挥的必然发展趋势,智能化作战指挥模式需求分析可为智能作战问题研究提供有效的信息。智能化作战指挥模式的需求分析已经具备了一定的物质、理论和技术基础,同时,也具有了一定的构建思路、实践条件和实验平台。在此基础上,本文从军事需求、功能需求和技术需求以及构建要求四个不同角度进行需求分析,以找准创建需求,为后续工作进一步展开奠定基础。     

基于多视图的指挥信息系统军事需求分析方法

针对目前指挥信息系统军事需求分析领域存在的一系列问题,提出了一套符合指挥信息系统特点要求的基于多视图的指挥信息系统军事需求分析方法.该方法主要根据军事指挥人员、参谋业务人员以及系统管理人员等不同类型人员的特点,从作战、系统以及管理等多个角度分析指挥信息系统军事需求.文中重点对该方法的3个重要组成部分,即需求体系框架、描述方法体系和集成开发环境,进行了分析研究.     

基于组件的C~4ISR系统需求开发方法

如何获得完整、准确的需求文档以及如何提高需求描述的重用性一直是C4ISR系统需求研究的重点,是C4ISR需求工程研究的重要组成部分.从研究C4ISR需求文档的现状出发,提出了基于组件的C4ISR系统需求开发方法,即将组件化封装、重用的思想引入到C4ISR系统需求的开发.对C4ISR需求组件体系的外部结构和内部结构进行了研究,并对需求组件的重用性进行了研究,给出了基于组件的C4ISR系统需求开发过程框架.该方法提高了需求的可用性和重用性,为撰写高质量的C4ISR需求文档提供了一条有效的途径.     

海军作战指挥综合仿真系统

在分析作战仿真的基本概念和应用领域的基础上,描述了作战仿真系统的军事需求,提出了海军作战指挥综合仿真系统的总体设计要求,分析了仿真系统的体系结构、组成及运行方式,阐述了仿真系统研究中的主要关键技术和应用方向.为海军新型作战指挥系统的研制建立了一个集成综合作战仿真系统.     

基于效果驱动和探索性分析的作战能力需求生成方法

针对基于威胁和基于能力的作战能力需求研究存在的不足,在描述作战能力需求要素的基础上,提出了基于效果驱动和探索性分析的作战能力需求生成方法:通过作战目标及效果、作战行动及效果双重驱动,依次探索生成逻辑作战任务、作战能力、物理作战任务、任务条件和任务标准,将多元不确定威胁转化生成作战能力需求。此方法能有效综合作战指挥人员和军事需求人员的观点,其分析结果在实际应用中具有良好的适应性和健壮性。     

智能化计量管理信息系统设计及应用价值

针对当前军事计量管理信息系统数据类型复杂、可扩展性差和智能化程度低等问题,提出了一种基于大数据的智能化计量管理信息系统。在给出系统总体架构的基础上,介绍了系统实现的关键技术和计量大数据应用价值等内容,该系统的开发和应用,可实现军事计量业务辅助决策、测试设备健康状况分析及质量预测,对推动军事计量技术的提升与发展具有重要意义。     

A novel facial emotion recognition scheme based on graph mining

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. To reduce the number of generated sub-graphs, overlap ratio metric is utilized for this purpose. After encoding the final selected sub-graphs, binary classification is then applied to classify the emotion of the queried input facial image using six levels of classification. Binary cat swarm intelligence is applied within each level of classification to select proper sub-graphs that give the highest accuracy in that level. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the final system accuracy was 90.00%. The results show significant accuracy improvements (about 2%) by the proposed system in comparison to current published works in SAVEE database.