A methodology to conceive a case based system of industrial diagnosis.

International audienceThe objective of this paper is to address the diagnosis knowledge-oriented system in terms of artificial intelligence, particular by the Case-Based Reasoning (CBR) approach. Indeed, the use of CBR, which is an approach to problem solving and learning, in diagnosis goes back to a long time with the appearance of diagnostic support systems based on CBR. A diagnostic system by CBR implements an expertise-base composed of past experiences through which the origins of failure and the maintenance strategy are given according to a description of a specific situation of diagnostic. A study is made on the different diagnostic systems based on CBR. This study showed that there was no common methodology for building a CBR system. This design depends primarily on the case representation and knowledge models of the domain application. Consequently, this paper proposes a general design approach of a diagnostic system based on the CBR approach

Composite Ontology-Based Medical Diagnosis Decision Support System Framework

Current medical decision support systems have evolved from the automation of medical decision routines to improving the quality of health care services. Knowledge-based systems, compared to conventional data-driven techniques, are promising to support medical decision making. However, knowledge acquisition is usually a bottleneck in the process of developing such systemsOne possibility for acquiring medical knowledge, particularly tacit knowledge, is to use data or cases in both syntactic and semantic ways. Case-based Reasoning (CBR) methodology provides a practical way of problem solving with recalled knowledge memory of solved cases. To reduce the difficulty of knowledge acquisition, this paper proposes a design of the system framework that utilizes the simplified medical knowledge:disease-symptom ontology for prediagnosis, given patients symptoms and signs as input. In the first stage, simple pattern matching is used to gather candidate diseases in diagnosis. Following that, case-based reasoning is used to refine diagnostic decision. The case base is structured with ontological knowledge model. The case retrieval process is based on semantic similarity. The diagnostic system uses a composite knowledge base, and will allow automated diagnosis recommendation. The system framework also aims at facilitating semantic explanations to the solution derived

Situation awareness approach to context-aware case-based decision support.

Context-aware case-based decision support systems (CACBDSS) use the context of users as one of the features for similarity assessment to provide solutions to problems. The combination of a context-aware case-based reasoning (CBR) with general domain knowledge has been shown to improve similarity assessment, solving domain specific problems and problems of uncertain knowledge. Whilst these CBR approaches in context awareness address problems of incomplete data and domain specific problems, future problems that are situation-dependent cannot be anticipated due to lack of data by the CACBDSS to make predictions. Future problems can be predicted through situation awareness (SA), a psychological concept of knowing what is happening around you in order to know the future. The work conducted in this thesis explores the incorporation of SA to CACBDSS. It develops a framework to decouple the interface and underlying data model using an iterative research and design methodology. Two new approaches of using situation awareness to enhance CACBDSS are presented: (1) situation awareness as a problem identification component of CACBDSS (2) situation awareness for both problem identification and solving in CACBDSS. The first approach comprises of two distinct parts; SA, and CBR parts. The SA part understands the problem by using rules to interpret cues from the environment and users. The CBR part uses the knowledge from the SA part to provide solutions. The second approach is a fusion of the two technologies into a single case-based situation awareness (CBSA) model for situation awareness based on experience rather than rule, and problem solving predictions. The CBSA system perceives the users context and the environment and uses them to understand the current situation by retrieving similar past situations. The futures of new situations are predicted through knowledge of the history of similar past situations. Implementation of the two approaches in flow assurance control domain to predict the formation of hydrate shows improvements in both similarity assessment and problem solving predictions compared to CACBDSS without SA. Specifically, the second approach provides an improved decision support in scenarios where there are experienced situations. In the absence of experienced situations, the second approach offers more reliable solutions because of its rule-based capability. The adaptation of the user interface of the approaches to the current situation and the presentation of a reusable sequence of tasks in the situation reduces memory loads on operators. The integrated research-design methodology used in realising these approaches links theory and practice, thinking and doing, achieving practical as well as research objectives. The action research with practitioners provided the understanding of the domain activities, the social settings, resources, and goals of users. The user-centered design process ensures an understanding of the users. The agile development model ensures an iterative work, enables faster development of a functional prototype, which are more easily communicated and tested, thus giving better input for the next iteration

Applied formative evaluation in the webbased environment.

The use of the Internet and specifically the World, Wide Web (Web) as a media for collaboration and problem-solving is an evolving solution to the problem of increasing numbers of students in the university setting. A variety of virtual universities are appearing on the Web to address this dilemma. There are gaps, however, in these Systems which do not meet the needs of the participants. This research examines the use of applied formative evaluation (feedback) methodologies and protocols, used between the stakeholders of a web-based learning environment, to facilitate the learning process. Principles are established to guide the learning environment designer (LED), the mediator between the subject expert (SE) or teacher and the interactive multimedia web-based design team, in creating a student-centred learning space on the web. The principles and protocols developed in this research are illustrated through the D E L B E R T (Digital Environment Learning-Based Evaluation Response Theory) Tutorial system. This web-based collaborative, problem-solving seminar makes use of on-line tools such as; e-mail, H T M L forms, Javascript and video conferencing to promote communication through a guided-discovery delivery methodology. The case studies conducted with the system support the methodologies proposed in this thesis. Telecommunication in the area of educational technology is a rapidly changing field. Therefore, the focus of this research is not in the development of software or programming which may be out of date before its implementation. Instead, this research contributes to the design process of a web-based educational environment. The principles and protocols are aimed at supporting the applied formative evaluation methodology between the participants in the on-line learning process. In this way the research can be adapted to new technologies, beyond those adapted to the D E L B E RT Tutorial system, thus, not limiting itself as a contribution to the science of educational technology

A case-based reasoning approach to the designing of building envelopes

Building-envelope design is an information-intensive process that requires experiential knowledge. Confronted with such a process, a human expert adds to well-known domain knowledge his own experience, or the experience of others, to support his reasoning process and guide him in typical situations. The problem-solving paradigm where reasoning is supported by reusing past experiences is called Case-Based Reasoning ( CBR ), and it was added to the Artificial Intelligence ( AI ) methodology following research in cognitive psychology. Instead of relying solely on general knowledge of a problem domain, or making associations along generalized relationships between problem descriptors and conclusions, CBR is able to utilize the specific knowledge of previous experienced problem situations called cases. CBR is a technology that solves problem by storing, retrieving, and adapting past cases. CBR systems have been proposed as an alternative to rule-based systems whenever the knowledge engineering process of eliciting rules is difficult or unmanageable. Instead, many experiences (or cases) with solutions, warnings, plans, and so forth are collected and new situations are related to a stored recollection of these past cases. New solutions are adapted from the old ones. Research in Knowledge-Based Expert Systems ( KBES ) for building-envelope design has shown a similar trend. While computerized assistance was imposed by the large amount of data to be processed, domain knowledge. Such fields where most of the knowledge is based on experience are often labeled as "weak theory domains," and they are prime candidates for adopting a CBR approach. This thesis proposes a CBR framework for selecting the construction alternatives during the preliminary stage of the building-envelope design process. The methodology presented aims to find the most suitable design for a new building envelope from a library of prototypical building cases and adapts it to meet the requirements of ASHRAE Standard 90.1/1989 for energy efficient building design. The study outlines the potential benefits of using CBR technology and the key issues encountered while attempting to define the CBR model for building-envelope design. Developing a hierarchy of building-envelope components identifies cases and features for design. The envelope design problem is solved through decomposition, and by combining case-based and rule-based reasoning methods. In searching for a best match to achieve a higher degree of case filtering, a connection between case-based reasoning and Artificial Neural Networks ( ANN ) is proposed. An ANN-based filtering mechanism is designed to improve the quality of case-matching outcome while enforcing the economy of case representation. The framework proposed by this research has been implemented into the CRED software system demonstrating the feasibility and advantages of using CBR methodology for building envelope design. CRED blends several Al techniques (such as ANN, CBR and KBES) while aiming to offer expert assistance to building design professionals for browsing and selecting building-envelope alternatives

Teaching Construction in the Virtual University: the WINDS project

This paper introduces some of the Information Technology solutions adopted in Web based INtelligent Design Support (WINDS) to support education in A/E/C design. The WINDS project WINDS is an EC-funded project in the 5th Framework, Information Society Technologies programme, Flexible University key action. WINDS is divided into two actions: ·The research technology action is going to implement a learning environment integrating an intelligent tutoring system, a computer instruction management system and a set of co-operative supporting tools. ·The development action is going to build a large knowledge base supporting Architecture and Civil Engineering Design Courses and to experiment a comprehensive Virtual School of Architecture and Engineering Design. During the third year of the project, more than 400 students all over Europe will attend the Virtual School. During the next three years the WINDS project will span a total effort of about 150 man-years from 28 partners of 10 European countries. The missions of the WINDS project are: Advanced Methodologies in Design Education. WINDS drives a breakdown with conventional models in design education, i.e. classroom or distance education. WINDS implements a problem oriented knowledge transfer methodology following Roger Schank's Goal Based Scenario (GBS) pedagogical methodology. GBS encourages the learning of both skills and cases, and fosters creative problem solving. Multidisciplinary Design Education. Design requires creative synthesis and open-end problem definition at the intersection of several disciplines. WINDS experiments a valuable integration of multidisciplinary design knowledge and expertise to produce a high level standard of education. Innovative Representation, Delivery and Access to Construction Education. WINDS delivers individual education customisation by allowing the learner access through the Internet to a wide range of on-line courses and structured learning objects by means of personally tailored learning strategies. WINDS promotes the 3W paradigm: learn What you need, Where you want, When you require. Construction Practice. Construction industry is a repository of ""best practices"" and knowledge that the WINDS will profit. WINDS system benefits the ISO10303 and IFC standards to acquire knowledge of the construction process directly in digital format. On the other hand, WINDS reengineers the knowledge in up-to-date courses, educational services, which the industries can use to provide just-in-time rather than in-advance learning. WINDS IT Solutions The missions of the WINDS project state many challenging requirements both in knowledge and system architecture. Many of the solutions adopted in these fields are innovative; others are evolution of existing technologies. This paper focuses on the integration of this set of state-of-the-art technologies in an advanced and functionally sound Computer Aided Instruction system for A/E/C Design. In particular the paper deals with the following aspects: Standard Learning Technology Architecture The WINDS system relies on the in progress IEEE 1484.1 Learning Technology Standard Architecture. According to this standard the system consists of two data stores, the Knowledge Library and the Record Database, and four process: System Coach, Delivery, Evaluation and the Learner. WINDS implements the Knowledge Library into a three-tier architecture: 1.Learning Objects: ·Learning Units are collections of text and multimedia data. ·Models are represented in either IFC or STEP formats. ·Cases are sets of Learning Units and Models. Cases are noteworthy stories, which describes solutions, integrate technical detail, contain relevant design failures etc. 2.Indexes refer to the process in which the identification of relevant topics in design cases and learning units takes place. Indexing process creates structures of Learning Objects for course management, profile planning procedures and reasoning processes. 3.Courses are taxonomies of either Learning Units or a design task and Course Units. Knowledge Representation WINDS demonstrates that it is possible and valuable to integrate a widespread design expertise so that it can be effectively used to produce a high level standard of education. To this aim WINDS gathers area knowledge, design skills and expertise under the umbrellas of common knowledge representation structures and unambiguous semantics. Cases are one of the most valuable means for the representation of design expertise. A Case is a set of Learning Units and Product Models. Cases are noteworthy stories, which describe solutions, integrate technical details, contain relevant design failures, etc. Knowledge Integration Indexes are a medium among different kind of knowledge: they implement networks for navigation and access to disparate documents: HTML, video, images, CAD and product models (STEP or IFC). Concept indexes link learning topics to learning objects and group them into competencies. Index relationships are the base of the WINDS reasoning processes, and provide the foundation for system coaching functions, which proactively suggest strategies, solutions, examples and avoids students' design deadlock. Knowledge Distribution To support the data stores and the process among the partners in 10 countries efficiently, WINDS implements an object oriented client/server as COM objects. Behind the DCOM components there is the Dynamic Kernel, which dynamically embodies and maintains data stores and process. Components of the Knowledge Library can reside on several servers across the Internet. This provides for distributed transactions, e.g. a change in one Learning Object affects the Knowledge Library spread across several servers in different countries. Learning objects implemented as COM objects can wrap ownership data. Clear and univocal definition of ownerships rights enables Universities, in collaboration with telecommunication and publisher companies, to act as "education brokers". Brokerage in education and training is an innovative paradigm to provide just-in-time and personally customised value added learning knowledg

Towards a Design Methodology for Decision Support Systems

The authors propose the use of process models for DSS design. The kind of process models suggested are task structures and decision structures with simple graphical syntax and semantics. The process models form the basis for a coherent DSS design methodology, based upon the bounded rationality paradigm. The history of DSS and DSS design is discussed to form a theoretical position. The resulting methodology has been tested and evaluated in a laboratory experiment. The results of this evaluation will be used for continuous improvement of the methodolog

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