计算机软件的日常管理与维护

计算机的不断普及,再加上信息技术的持续快速发展,计算机软件在企业生产、居民生活中都得到大范围应用,发挥着重要的作用。做好计算机软件的日常管理工作,是提升计算机软件应用有效性的重要渠道。因而,在实际应用中,应结合计算机软件日常管理中存在的各种问题,并制定好相应的维护策略,方能持续提高计算机软件应用效率与质量,从而最大化发挥其在效率提升等方面的价值。笔者结合自身实际工作经验,探讨可行的计算机软件日常管理与维护策略。     

程序理解:现状与未来

程序理解是软件工程中的关键活动,在软件开发、维护、重用等任务中发挥着重要的作用.程序理解自软件工程出现以来,就一直是该领域的研究热点.随着软件应用的日益复杂和不断普及,程序理解研究的需求发生了新的变化,程序的自理解或自认知逐渐成为新的关注点,有必要对程序理解进行重新审视.从工程、学习和认知以及方法和技术这3个角度定位程序理解任务;随后,通过文献分析展示其研究布局,进而分别从认知过程、理解技术以及软件工程任务中的应用这3个方面,综合论述程序理解研究的发展脉络和研究进展.     

基于语义理解的智能搜索引擎的研究

目前网络上的搜索引擎主要是基于关键词索引查询技术设计的,这种技术的搜索范围很大,但由于关键词难以表达丰富的概念,导致查询效率很低。而基于语义理解的智能搜索引擎解决了传统搜索引擎中"忠实表达"和"表达差异"的问题,极大的提高了查找效率。基于语义理解的智能搜索引擎必将成为未来的研究热点。     

时空数据语义理解:技术与应用

随着移动互联网的发展与手持智能终端的普及,海量带有用户时空属性的数据被生成.理解这些数据表达的语义信息对推测用户需求,分析用户偏好,进而提供精准时空推荐和预测服务具有重要作用.因此,近些年来,时空数据语义理解正成为时空数据挖掘领域的研究热点.从技术和应用两个层面,对近些年来国内外研究者在该领域的研究成果进行了系统的归类和总结.技术层面上,依据语义理解的不同任务,提出了时空数据语义理解的研究框架;并依次从地理位置语义理解、用户行为语义理解、热点事件语义理解3个主要任务,归纳了时空数据语义理解所包含的相关研究成果和关键技术.应用层面上,分别总结了时空数据语义理解在时空推荐和时空预测中的应用.最后,从数据质量、算法模型和计算模式3个方面,归纳了时空数据语义理解面临的主要挑战以及未来的研究方向.     

图象理解的应用与发展

图象理解是关于图象工程中的关键环节,介绍了图象理解的概念,基本理论和方法。并指出了图象理解的应用和发展趋势。     

波形智能理解及其在检针仪中的应用

波形智能理解是信号动态检测中的一种新方法。本文通过检针器的例子，介绍了传感器的测量原理，并对分离得到波形特征进行描述。     

面向搜索引擎的自然语言理解的设计与实现*

提出了一种针对智能检索的自然语言理解的实现模型。该模型通过句模分析、分词和概念扩展的方法来理解问句,在一定程度上提高理解自然语言的能力。详细介绍了其系统架构、实现思想和原理。最后通过一系列的实例来对普通搜索引擎和加载了本模型的搜索引擎进行测试。实验结果表明,提出的模型能有效地分析自然语言提问,提高信息检索的准确性和智能性。     

软件维护中程序理解的应用与研究

程序理解是软件维护中的一项重要活动。从软件维护和认知学的角度分析了程序理解的任务,描述了几种主流的程序理解的模型。最后针对影响程序理解的因素提出了相应的对策,为提高维护效率提供帮助。     

软件维护中程序理解的应用与研究

程序理解是软件维护中的一项重要活动。从软件维护和认知学的角度分析了程序理解的任务，描述了几种主流的程序理解的模型。最后针对影响程序理解的因素提出了相应的对策，为提高维护效率提供帮助。     

基于智能交互的笔迹结构理解

基于多层次相互作用的结构理解,提出一种笔迹智能编辑方法.该方法先自下而上初步提取单字、行、段,然后自上而下利用整体信息对组成信息进行精确分割,提取的信息表示成一个多层次的结构.基于笔迹的结构,用户可以使用笔手势对笔迹进行编辑.实验评估表明,该方法对笔迹的智能编辑具有较好的效果.     

The use of Information and Communication technology when completing instrumental activities of daily living

Purpose of the studyAn important aspect of cognitive assessment is inquiry of the patient’s ability to manage instrumental activities of daily living (IADLs), including finances, medication, and transportation. Information and Communication technology (ICT, e.g. smartphones, computers) has become increasingly prevalent in American culture. We aimed to characterize what IADLs were being completed with ICT, and what factors predict ICT use to manage IADLs.Design and methodsWe administered a self-report survey to 505 Veterans seeking care at the VA Greater Los Angeles Healthcare System.ResultsSeventy percent reported regular ICT use. Of ICT users, 76% reported use for finances, 86% for shopping, 72% for health management, 75% for transportation, and 97% for communication. Logistic regression was used to identify predictors of high ICT use. Longer duration of computer use was significant in all models. Younger age, higher education, and better self-reported memory were associated with greater use for a subset of IADLs. Veterans with more health problems were more likely to use ICT to manage their healthcare.ImplicationsThese findings suggest that Veterans are using ICT to support IADLs. It appears appropriate for clinicians to incorporate questions about ICT use into IADLs assessment, which may assist in detecting subtle changes to day to day functioning and improve the accurate diagnosis of cognitive disorders.     

Situation-centered goal reinforcement of activities of daily living in smart home environments

Older adults with early-stage dementia (ED) can experience confusion or lack clarity when performing routine activities of daily living (ADLs). These circumstances predispose the older adult to safety-critical and often risky situations. A safety-critical risky situation is one that constitutes a hazard. To support independent living, a sensor-laden smart environment can be employed to mitigate such hazards. In this paper, we propose a situation-centered goal reinforcement framework that supports older adults with ED in their decision making, and guides them through their ADL in order to fulfill their goal or intention and avoid hazards. First, we employ an LSTM (Long Short-Term Memory) model to infer the current goal of the resident, using their previously observed normal ADL patterns. Secondly, we identify potentially risky situations in their currently observed goal path. We then incorporate a situ-learning agent (SLA) that helps an inhabitant to make the right decision, thus preventing adverse events while guiding her through the task sequence that leads to her goal state. In addition, we use a naïve agent to simulate episodes of confusion similar to those that might be experienced by older adults with ED. We validated our method against an open-source dementia dataset (Quesada et al., 2015) by considering four types of ADLs as case studies. We achieved an accuracy of 90.1% for our goal inference model, higher than the accuracies reported by related studies. We also reported other metrics including precision, recall and f1-score for goal inference model. Finally, SLA's action recommendations relevance was evaluated accordingly.     

模糊支持张量机图像分类算法及其应用

针对在小样本图像分类应用中,以向量空间作为输入的传统分类算法的不足,提出以张量理论为基础,结合模糊支持向量机思想的基于张量图像样本的模糊支持张量机分类器,利用张量表示图像样本,求解最优张量面。通过手写体数字图像样本实验仿真,验证该算法的性能,随后将其应用到羽绒菱节图像识别中进行对比,该算法较传统算法平均高出6.3%以上的识别率。实验证明该算法更适合应用于图像样本分类识别。     

半监督FSVM在羽绒菱节识别中的应用

目前,我国对羽绒种类的识别主要由人工借助于显微镜完成,这种方法存在许多不足。提出将半监督FSVM算法引入到羽绒识别中,用半监督学习方法以少量的训练样本为基础,扩大训练样本集的规模,同时利用FSVM的特性减少半监督学习所带来的误差;利用半监督FSVM对经过处理的羽绒二值化图像中的菱节进行识别。该方法提高了菱节识别的准确率。     

Robot semantic mapping through human activity recognition: A wearable sensing and computing approach

Semantic information can help robots understand unknown environments better. In order to obtain semantic information efficiently and link it to a metric map, we present a new robot semantic mapping approach through human activity recognition in a human–robot coexisting environment. An intelligent mobile robot platform called ASCCbot creates a metric map while wearable motion sensors attached to the human body are used to recognize human activities. Combining pre-learned models of activity–furniture correlation and location–furniture correlation, the robot determines the probability distribution of the furniture types through a Bayesian framework and labels them on the metric map. Computer simulations and real experiments demonstrate that the proposed approach is able to create a semantic map of an indoor environment effectively.     

具有捕食策略的混合随机优化算法及其多极值函数优化

SAGACIA是一种混合随机优化算法,该算法虽已吸收了模拟退火算法、遗传算法和趋化性算法的优点,但搜索过程中仍存在收敛速度慢以及采用固定步长影响搜索精度的缺点,而捕食搜索策略通过限制的调节能较快锁定最优区域,从而提高收敛速度。结合两者的优缺点,提出一种具有捕食搜索策略的自适应调整步长SAGACIA算法,改进后的算法通过捕食搜索策略平衡了算法的局域搜索和全局搜索,提高了收敛速度;邻域搜索采用自适应步长,避免了最优解附近的震荡,提高了搜索精度。实验仿真结果表明,改进后的SAGACIA算法具有较快的收敛速度和较高的寻优精度,证明了算法改进的有效性和可行性。     

Distributed Shared Arrays: An Integration of Message Passing and Multithreading on SMP Clusters

This paper presents a Distributed Shared Array runtime system to support Java-compliant multithreaded programming on clusters of symmetric multiprocessors (SMPs). As a hybrid of message passing and shared address space programming models, the DSA programming model allows programmers to explicitly control data distribution so as to take advantage of the deep memory hierarchy, while relieving them from error-prone orchestration of communication and synchronization at run-time. The DSA system is developed as an integral component of mobility support middleware for grid computing so that DSA-based virtual machines can be reconfigured to adapt to the varying resource supplies or demand over the course of a computation. The DSA runtime system also features a directory-based cache coherence protocol in support of replication of user-defined sharing granularity and a communication proxy mechanism for reducing network contention. We demonstrate the programmability of the model in a number of parallel applications and evaluate its performance on a cluster of SMP servers, in particular, the impact of the coherence granularity.     

OWS性能监测评价方法研究及其原型系统实现——以OGC WMS为例

针对互联网上所共享发布的开放地理空间联盟网络服务（OWS）经常会出现不能访问或运行速度缓慢而导致难以利用的问题,为测试和评价这些地理信息服务的可用性和性能,通过研究OWS服务的固有特点,提出了实时监测OWS状态的动态规划模型和基于评价因子、评价权重等参数的评价模型,用以实现对OWS的监测与评价;基于上述模型与因子,设计开发了面向OWS的实时监测和性能评价原型系统,并以OGC网络地图服务（WMS）为例对模型与原型系统进行了实验验证。结果表明：该系统能够对相应的OWS进行实时监测与评价,所提的监测与评价方法与模型可为用户在众多的服务资源中获取其所感兴趣的数据提供参考信息,为地理信息服务使用者查找更优的服务资源提供帮助。     

Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA): Past,Present and Future

This article reviews research work on set of experience knowledge structure (SOEKS)-decisional DNA (DDNA) done in the past, ongoing, and planned for the future. Firstly, the concept of the knowledge representation technique of SOEKS-DDNA is discussed, and then an attempt is made to organize the past research related with it in chronological order. This work focuses on the review on SOEKS-DDNA, its application in different domains, the various implementation platforms, as well as its benefits and its limitations. The second part of this article provides an idea of the SOEKS-DDNA-related research endeavors currently carried out by us and the last part is a sneak peek into our planned future work.     

Fault Detection and Isolation of discrete-time Markovian jump linear systems with application to a network of multi-agent systems having imperfect communication channels

This paper deals with the problem of Fault Detection and Isolation (FDI) for discrete-time Markovian Jump Linear Systems (MJLSs). A geometric property related to the unobservable subspace of an MJLS is first presented and the concept of unobservability subspace is introduced. Sufficient conditions for designing an H_∞-based FDI algorithm for MJLSs subject to input disturbances and measurement noise are presented and developed. Our proposed approach is then applied to the problem of fault detection and isolation in a network of multi-agent systems when imperfect communication channels exist among the agents. A discrete-time communication link with a stochastic packet dropping effect is considered based on the Gilbert–Elliott model and the entire network is modeled as a discrete-time MJLS. Simulation results are presented for formation flight of satellites to demonstrate and verify the effectiveness and performance capabilities of our proposed FDI algorithm.