An integrative approach to requirements analysis: How task models support requirements reuse in a user-centric design framework

Many software systems fail to address their intended purpose because of a lack of user involvement and requirements deficiencies. This paper discusses the elaboration of a requirements-analysis process that integrates a critical-parameter-based approach to task modeling within a user-centric design framework. On one hand, adapting task models to capture requirements bridges the gap between scenarios and critical parameters which benefits design from the standpoint of user involvement and accurate requirements. On the other hand, using task models as a reusable component leverages requirements reuse which benefits design by increasing quality while simultaneously reducing development costs and time-to-market. First, we present the establishment of both a user-centric and reuse-centric requirements process along with its implementation within an integrated design tool suite. Secondly, we report the design, procedures, and findings of two user studies aimed at assessing the feasibility for novice designers to conduct the process as well as evaluating the resulting benefits upon requirements-analysis deliverables, requirements quality, and requirements reuse.     

A fuzzy modeling method via Enhanced Objective Cluster Analysis for designing TSK model

This paper proposes a fuzzy modeling method via Enhanced Objective Cluster Analysis to obtain the compact and robust approximate TSK fuzzy model. In our approach, the Objective Cluster Analysis algorithm is introduced. In order to obtain more compact and more robust fuzzy rule prototypes, this algorithm is enhanced by introducing the Relative Dissimilarity Measure and the new consistency criterion to represent the similarity degree between the clusters. By these additional criteria, the redundant clusters caused by iterations are avoided; the subjective influence from human judgment for clustering is weakened. Moreover the clustering results including the number of clusters and the cluster centers are considered as the initial condition of the premise parameters identification. Thus the traditional iteration modeling procedure for determining the number of rules and identifying parameters is changed into one-off modeling, which significantly reduces the burden of computation. Furthermore the decomposition errors and the approximation errors resulted from premise parameters identification by Fuzzy c-Means clustering are decreased. For the consequence parameters identification, the Stable Kalman Filter algorithm is adopted. The performance of the proposed modeling method is evaluated by the example of Box–Jenkins gas furnace. The simulation results demonstrate the power of our model.     

A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests

In this paper, we focus on the experimental analysis on the performance in artificial neural networks with the use of statistical tests on the classification task. Particularly, we have studied whether the sample of results from multiple trials obtained by conventional artificial neural networks and support vector machines checks the necessary conditions for being analyzed through parametrical tests. The study is conducted by considering three possibilities on classification experiments: random variation in the selection of test data, the selection of training data and internal randomness in the learning algorithm.The results obtained state that the fulfillment of these conditions are problem-dependent and indefinite, which justifies the need of using non-parametric statistics in the experimental analysis.     

基于OWL的软件工程数据建模

网络本体语言(Web ontology language,OWL)是语义网技术的一个重要组成部分,适合于对复杂的数据进行语义描述和建模.在软件系统的开发过程中通常会产生大量结构复杂、语义丰富的数据,而建立一个灵活的语义模型是对各类软件工程数据进行统一管理的基础.从设计和实现海量软件工程数据管理平台的需求出发,提出了一种基于OWL的软件工程数据描述模型.该模型不仅能够对源代码、需求、测试、版本和缺陷数据进行描述,同时还能对这些数据之问的语义关联进行描述.通过案例分析对模型的有效性进行了讨论.     

复杂适应系统的多层级建模研究

针对复杂系统仿真普遍缺乏层级思想,局限于广度模拟的情况,对复杂适应系统（CAS）层级建模进行研究,协同进化理论,从主体平均适应度的角度,分析中间子系统的生成、过渡和演化,得到层级结构产生的内在动因,提出层级CAS演化的数学模型和层级框架。该模型应用于多人重复囚徒博弈,结果证明其能在高N值时形成稳定高合作率。     

基于超螺旋模型的头发动态模拟方法

针对现有头发模型缺乏柔性的问题,提出一种改进的基于超螺旋模型的头发建模与仿真方法,将导引发丝构造成具有有限自由度的分段螺旋体,运用拉格朗日力学对发丝运动进行计算。通过改进卷发曲率和捻度的计算方法,并采用自适应控制结构对头发进行重组和细分,提高模拟过程的准确性和稳定性。实验结果证明,该方法可以获得较为逼真的动态模拟头发的效果。     

无线传感器网络的元胞自动机自组织算法

提出一种分布式、自适应的无线传感器网络元胞自动机(CA)自组织算法,将网络中的每个节点映射成CA中的元胞,通过控制节点在不同时间的状态转换(活跃/睡眠),消除与邻居节点间的频繁通信,从而降低能源消耗。仿真实验结果表明,该算法具有较强的目标检测能力。     

AGR元模型到组织抽象模型的建模方法

将目标驱动思想引入AGR中,提出一种从AGR元模型到多Agent系统（MAs）组织抽象模型的建模方法。对AGR进行综述,给出该方法的具体步骤和形式化过程。应用于某智能故障诊断系统的结果表明,该建模方法有利于设计人员直接利用AGR元模型构建MAS组织抽象模型,可适用于各种AGR扩展。     

基于MVC模式的Web用户界面建模

分析了企业信息系统的Web用户界面开发特性,研究了当前主流前端框架的MVC(模型-视图-控制器)设计模式应用,针对Web前端开发需求及最佳实践方法,提出了一种符合MVC用户界面开发最佳实践的组件化Web用户界面建模方法.设计一套抽象和描述Web用户界面组件的UML(统一建模语言)概要文件,从界面数据模型、界面组件模型到界面交互模型等3个方面完成Web用户界面建模.以一个装修行业定制型ERP(企业资源计划)系统为例,通过用户界面建模实践,验证了本建模方法的可行性、易用性和有效性.     

高速电磁阀的动态特性

高速电磁阀是重要的液压执行元件,因此其响应速度尤为重要.首先分析高速电磁阀的原理结构,再对电学、磁学、运动学进行建模,研究不同参数下系统的响应速度与时间的关系.研究结果表明:采用的控制变量仿真法可以清晰地看出不同参数对系统动态参数的影响,其中起励电压、线圈匝数与占空比对响应的影响比较明显,为项目研究提供参考.