Integrating customer's preferences in the QFD planning process using a combined benchmarking and imprecise goal programming model

Quality function deployment (QFD) is a customer-oriented design tool for developing new or improved products to achieve higher customer satisfaction by integrating various functions of an organization. The engineering characteristics (ECs) affecting the product performances are designed to match the customer attributes (CAs). However, from the viewpoint of the QFD team, product design processes are performed in imprecise environments, and more than one factor must be taken into account in determining the target levels of ECs, especially the limited resources and increased market competition. This paper presents an imprecise goal programming (GP) approach to determine the optimum target levels of ECs in QFD for maximizing customer satisfaction under resource limitation and considerations of market competition. Based on benchmarking data of CAs, the concept of satisfaction functions is utilized to formulate explicitly the customer's preferences and to integrate the competitive analysis of target market into the modelling and solution process. In addition, the relationships linking CAs and ECs and the ECs to each other are integrated by functional relationships. The proposed approach will be illustrated through a car door design example.     

微机原理与应用课程改革与实践

为适应新技术对信息化人才培养要求,在分析微机原理与应用课程特点及教学状况的基础上,从教学目标、教学内容入手,阐述微机原理与应用课程改革思路和方法,从适应科技发展的角度,提出调整课程教学内容,构建微机原理与应用多媒体及网络教学平台系统,改革课程考试方式。     

一种可行的可用性测试过程

文章综述用户模型法、用户调查法、专家评审法和观察法4类可用性测试方法,根据可用性测试的经验,总结出一套合理实用的可用性测试过程,使得可用性测试的效率高、代价低,尽可能发现更多的可用性问题;提出在程序设计类课程的教学中,应适当向学生介绍可用性测试的方法和过程,以培养学生对自己开发的软件系统进行可用性测试的能力。     

Models to predict the deformation modulus and the coefficient of subgrade reaction for earth filling structures

Determination of deformation modulus and coefficient of subgrade reaction of soils have major importance, whether the projects are in design, and construction or compaction assessment stage of earth filling structures. Plate load test is one of the frequently used method to directly determine the parameters but the method is both costly and time consuming. For this reason, this paper is concerned with the applications of artificial neural networks (ANN) and simple-multiple regression analysis to predict deformation modulus and coefficient of subgrade reaction of compacted soils from compaction parameters (such as maximum dry density (MDD) and optimum moisture content (OMC), field dry density (FDD), and field moisture content (FMC)). Regression analysis and artificial neural network estimation indicated that there are acceptable correlations between deformation modulus and coefficient of subgrade reaction and these parameters. Artificial neural networks model exhibits higher performance than traditional statistical model for predicting deformation modulus and coefficient of subgrade reaction.     

Preliminary evaluation of electroencephalographic entrainment using thalamocortical modelling

Abstract: The concept of linked oscillators in biological control systems has long been established. Frequency entrainment is a predominant explanation behind many biological rhythms. In this paper a preliminary examination of electroencephalographic entrainment is made to survey the possibility and methods of achieving signal entrainment at the highest level of neurological organization and function. A model of the thalamocortical system is employed to generate simulated electroencephalographic signals and is tested in various configurations in the search for entrainment under very simple conditions. Additionally, an analysis of the coupled Van der Pol model of the circadian rhythm controller is performed to identify the possibility of affecting that system with a drastically different coupling input signal. We were able to conclude that overall signal shape can have a significant impact on the entrainment characteristics of the system. Due to the nature of the underlying mathematical structure of the model, by examining the circadian rhythm controller, we found that it is unsuitable for entrainment to an incident entraining signal of much higher frequency.     

Combining feature spaces for classification

In this paper we offer a variational Bayes approximation to the multinomial probit model for basis expansion and kernel combination. Our model is well-founded within a hierarchical Bayesian framework and is able to instructively combine available sources of information for multinomial classification. The proposed framework enables informative integration of possibly heterogeneous sources in a multitude of ways, from the simple summation of feature expansions to weighted product of kernels, and it is shown to match and in certain cases outperform the well-known ensemble learning approaches of combining individual classifiers. At the same time the approximation reduces considerably the CPU time and resources required with respect to both the ensemble learning methods and the full Markov chain Monte Carlo, Metropolis-Hastings within Gibbs solution of our model. We present our proposed framework together with extensive experimental studies on synthetic and benchmark datasets and also for the first time report a comparison between summation and product of individual kernels as possible different methods for constructing the composite kernel matrix.     

基于Python的实时嵌入式软件测试脚本

基于Python语言设计一种实时测试脚本,开发扩展模块,实现测试脚本与嵌入式软件仿真测试环境（ESSTE）的接口。该测试脚本使用简便,实时性高、描述能力强、具有良好的可复用性,目前已成功应用到ESSTE中。对多个实时嵌入式软件进行测试,结果验证了该测试脚本的正确性和实时性。     

一致性测试的静态需求测试研究

针对一致性测试中的静态需求测试通常采用手工方法而产生的效率低问题,提出一种基于统计学习的方法,包括静态需求的关联规则表示,并对采样的协议数据进行关联规则挖掘,如果得到的规则与需求规则一致,静态需求就可以得到统计上的测试检验。该方法在OSPFv3协议测试中取得了较好的效果。     

一种改进的GUI测试框架DART

针对当前的图形用户界面自动化测试中存在的局限性,提出一种每日自动回归测试（DART）框架的改进方案。研究DART流程、事件流图,包含了事件关联图的方法,实现对事件流图的优化,并采用权重选择法对DART方法进行改进,使之成为一种高效、简洁的自动冒烟测试框架。