面向对象的产品设计知识库的研究

文章立足产品设计知识库的功能需求分析,采用面向对象的方法构建产品设计知识库.首先,阐述了面向对象产品设计知识库的构建原理,也就是对产品设计知识抽象分类得到知识类信息并用专用的数据库进行管理,然后采取相应的程序接口生成知识管理的界面,并通过此界面完成产品设计知识的录入和其他管理工作.最后,文中接着简单介绍了面向对象产品设计知识库具体实现的几个重要方法.     

Managing knowledge on communication and information flow in global software projects

Communication is a key success factor of distributed software projects. Poor communication has been identified as a main obstacle to successful collaboration. Global projects are especially endangered by information gaps between collaborating sites. Different communication styles, technical equipment, and missing awareness of each other can cause severe problems. Knowledge about actual and desired channels, paths, and modes of communication is required for improving communication in a globally distributed project. However, many project participants know little about communication and information flow in their projects. In this contribution, we focus on knowledge about communication and information flow. It is acquired by modelling on‐going and desired flows of information, including documented and non‐documented channels of information flow. We analyzed a distributed software project from the information flow perspective. Based on the findings, we developed specific techniques to improve information flow in distributed software development according to the FLOW Method. In a second distributed project, we evaluated one of the techniques. We found the FLOW mapping technique to be suitable for effectively spreading knowledge about communication and information flow in global software projects.     

Integration by communication: knowledge exchange in global outsourcing of product software development

Global outsourcing is a growing trend among independent software vendors. In these projects like other distributed work, distances have negative effects on communication and coordination, directly impacting performance. We present a normative model designed to address this issue by improving communication and knowledge exchange. The model consists of six distinct practices and a tool blueprint, each coming with practical guidelines. It is based in part on two case studies of Dutch software vendors who have successfully outsourced part of their activities to an Eastern European outsourcing vendor, and validated by a panel of six experts from industry and the scientific community. It is concluded that knowledge exchange in global software outsourcing is a by‐product of efforts to enhance communication and coordination, rather than specific technical solutions. By committing to sharing knowledge, emphasizing transparency and integrating the outsourcing team into their organizations, customers from the product software business can realize the benefits of global outsourcing.     

Perception of own and robot engagement in human–robot interactions and their dependence on robotics knowledge

Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human’s own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot’s engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human–robot interactions without affecting the impact of the type of signal sent by the robot.     

智能化结构分析建模方法

建立正确的模型是进行机械结构分析的关键技术之一。提出了一种基于知识的结构分析建模方法,给出了基于知识结构分析建模方法的总体结构,讨论了知识的获取、分类与表达,提出了推理机制以及智能求解策略,提高了结构有限元分析建模方法的实用性和有效性。最后用实例说明了应用效果。     

Credit rating with a monotonicity-constrained support vector machine model

Deciding whether borrowers can fulfill their obligations is a major issue for financial institutions, and while various credit rating models have been developed to help achieve this, they cannot reflect the domain knowledge of human experts. This paper proposes a new rating model based on a support vector machine with monotonicity constraints derived from the prior knowledge of financial experts. Experiments conducted on real-world data sets show that the proposed method, not only data driven but also domain knowledge oriented, can help correct the loss of monotonicity in data occurring during the collecting process, and performs better than the conventional counterpart.     

基于先验知识的自适应多叉树防碰撞算法

为提高无线射频识别(RFID)系统快速识别大量标签的能力,提出一种基于先验知识的自适应多叉树防碰撞算法。利用标签访问的规律性和标签分布的随机性,在不同的搜索深度,根据已有的先验知识和碰撞比特信息估计待识别的标签数量,从而动态地自适应选择搜索叉树。通过有效减少碰撞和空闲时隙数,大幅提高读写器搜索和识别标签的能力。理论分析与仿真实验结果表明,该算法能克服传统自适应多叉树防碰撞算法的缺点,合理选择初始搜索叉树,尤其在待识别标签数量较多的场合,可有效提高RFID系统的吞吐率。     

基于粗糙集的焦炉加热工序控制规则提取

应用粗糙集(RS)理论对焦炉直行温度的控制规则进行了提取。首先收集人工成功控制直行温度的原始样本,添加可控与不可控参数,得到初始决策表;指出模糊控制方法因输入参数过少,从而会导致不确定性决策;然后利用RS理论对初始决策表进行约简,发现了关键影响因素及潜在规律,最终得到两组仅含有三个参数,简洁、一致、完备的控制规则,并经实际运行检验了规则的适用性。     

二维参数化图形技术研究进展

近几年来，参数化图形技术得到了不断的发展。目前已有多种参数化图形方法及系统。这些参数化图形方法可分为３种，即变分几何法、几何推理法和过程法。主要介绍这３种方法的研究进展。     

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting.