Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

A conceptualization of intended learning outcomes supporting self‐regulated learners in indicating learning paths

Intended learning outcomes (ILOs) indicate what learners will be able to achieve after they are taught. Traditionally, ILOs are expressed as plain text or unstructured documents. What if all ILOs of a specific course of study can be conceptualized through a structured diagrammatic technique? It was hypothesized that learners can benefit from this conceptualization in learning, especially in self‐regulated learning. The aim of this study was to investigate whether the ILOs represented in unstructured or structured formats can facilitate learners to identify learning paths. The results revealed that the mean ratings of all learning paths were statistically significantly higher with structured ILOs.     

An intelligent web-page classifier with fair feature-subset selection

The explosion of on-line information has given rise to many manually constructed topic hierarchies (such as Yahoo!!). But with the current growth rate in the amount of information, manual classification in topic hierarchies results in an immense information bottleneck. Therefore, developing an automatic classifier is an urgent need. However, classifiers suffer from enormous dimensionality, since the dimensionality is determined by the number of distinct keywords in a document corpus. More seriously, most classifiers are either working slowly or they are constructed subjectively without any learning ability. In this paper, we address these problems with a fair feature-subset selection (FFSS) algorithm and an adaptive fuzzy learning network (AFLN) for classification. The FFSS algorithm is used to reduce the enormous dimensionality. It not only gives fair treatment to each category but also has ability to identify useful features, including both positive and negative features. On the other hand, the AFLN provides extremely fast learning ability to model the uncertain behavior for classification so as to correct the fuzzy matrix automatically. Experimental results show that both FFSS algorithm and the AFLN lead to a significant improvement in document classification, compared to alternative approaches.     

实体造型中的几何约束

实体造型是一个基于约束的过程，完成从功能约束到几何约束、再到代数约束的转化而得到实体模型。本文讨论了几何约束的层次性及其表示，并且对几何约束同设计意图的关系进行了研究，提出了基于ＣＳＧ／ＧＣＧ／Ｂ－ｒｅｐ的模型表示。     

Factors influencing feature usage in work-related communication

Two studies are presented. The first aimed to identify possible barriers to the uptake and use of commonly available telephony features and to determine whether greater knowledge of features/access codes and availability of user manuals could increase feature usage under certain conditions. Results showed that feature-usage patterns were not affected by any of the manipulations, but that they were determined by specific job demands. Using Constantine and Lockwood's (1999) conceptualization of user roles, a method to support feature bundling decisions for specific target markets was developed and tested in the second study. The method - Strategic User Needs Analysis (SUNA) - was shown to yield a useful balance between high- and low-level information about selected roles. SUNA provided sufficient information to distinguish between PDA feature usage patterns of two similar target user groups as well as to suggest additional features each of the two target groups would find useful. The development of SUNA and observational findings of actual PDA usage are reported.     

MALL在中国的现状及其建筑设计要点

该文介绍了Mall的产生条件和国内发展概况，并结合实例分析，着重论述建筑设计方面的有关问题。     

固定背景下的随机波形提取模型

分析了当前对于从固定背景下的特征符号与背景符号相粘连的图表中提取信息所存在的问题，设计了适用于此类问题的方法模型。提出了一种在固定背景下通过背景符号检测和背景符号擦除来实现随机波形提取的方法。