Reusable Knowledge-based Components for Building Software Applications: A Knowledge Modelling Approach

In computer science, different types of reusable components for building software applications were proposed as a direct consequence of the emergence of new software programming paradigms. The success of these components for building applications depends on factors such as the flexibility in their combination or the facility for their selection in centralised or distributed environments such as internet. In this article, we propose a general type of reusable component, called primitive of representation, inspired by a knowledge-based approach that can promote reusability. The proposal can be understood as a generalisation of existing partial solutions that is applicable to both software and knowledge engineering for the development of hybrid applications that integrate conventional and knowledge based techniques. The article presents the structure and use of the component and describes our recent experience in the development of real-world applications based on this approach

The TRIZ-CBR synergy: A knowledge based innovation process

Today innovation is recognised as the main driving force in the market. This complex process involves several intangible dimensions, such as creativity, knowledge and social interactions among others. Creativity is the starting point of the process, and knowledge is the force that transforms and materialises creativity in new products, services and processes. In this paper a synergy that aims to assists the innovation process is presented. The synergy combines several concepts and tools of the theory of inventive problem solving (TRIZ) and the case-based reasoning (CBR) process. The main objective of this synergy is to support creative engineering design and problem solving. This synergy is based on the strong link between knowledge and action. In this link, TRIZ offers several concepts and tools to facilitate concept creation and to solve problems, and the CBR process offers a framework capable of storing and reusing knowledge with the aim of accelerating the innovation process

Design acceleration in chemical engineering

Nowadays, Chemical Engineering has to face a new industrial context with for example: the gradually falling of hydrocarbon reserves after 2020-2030, relocation, emerging of new domains of application (nano-micro technologies) which necessitate new solutions and knowledges… All this tendencies and demands accelerate the need of tool for design and innovation (technically, technologically). In this context, this paper presents a tool to accelerate innovative preliminary design. This model is based on the synergy between: TRIZ (Russian acronym for Theory of Inventive Problem Solving) and Case Based Reasoning (CBR). The proposed model offers a structure to solve problem, and also to store and make available past experiences in problems solving. A tool dedicated to chemical engineering problems, is created on this model and a simple example is treated to explain the possibilities of this tool

The management of intelligence-assisted finite element analysis technology

Artificial Intelligence (AI) approaches to Finite Element Analysis (FEA), have had tentative degrees of success over the last few years and some authors have argued that effective FEA can help in the manufacture reliability and safety aspects of engineered artefacts. The author of this paper reviews how such AI techniques have been applied and in this light, the author then uses a Fuzzy Cognitive Mapping (FCM), to develop a framework for the management of intelligence-assisted FEA

On the design of systems-oriented university curricula

This paper proposes a tool called the Systems Education Matrix (SEM) for use in informing the work of developers of systems-oriented curricula at colleges and universities around the world. The SEM was developed by Team 1 at the 2008 IFSR Fuschl Conversation held at Fuschl am See in Austria. In order to manage the complex problems we are dealing with today, systems thinking is essential. It is clear that systems education should be acknowledged as an important 'scientific method' that can help today's society to deal with the complexities of contemporary issues. To serve this role effectively, systems education needs to be focused towards the various needs that exist. The members of Team 1 have focused on the nature of systems education that will be required to not only train systems specialists, but to make systems thinking and analysis an integral part of discipline focused research and management

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Can Thomas Kuhn's paradigms help us understand software engineering

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