• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.461-472
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• 2005

In this paper, we design and implement a graphical bio-ontology management system based on OWL(Web Ontology Language). It allows domain experts to easily manage sophisticated bio-ontologies in which biological knowledge is encoded. The knowledge can be seamlessly modeled into the ontology by well defined graphical notations, which capture most of subtle semantics inherently existing between biological terms. Our system provides a new construction mechanism, which can determine a considerable part of relationships between terms by their inheritance and inverse-inheritance. For keeping their semantics to be consistent, the mechanism supplies domain experts with information available from relationships being constructed or already constructed. The constructed ontology is basically formatted by OWL, which may benefit from its powerful semantic expressiveness. Additionally, it can be automatically translated into other standard languages without semantic loss, such as RDF/RDFS, DAML+OIL and so on. The main characteristics of our system is that it enables domain experts to delicately model the bio-ontology by the visualized construction mechanisms adopting well-defined graphical notations based on OWL.

• Journal of Information Technology Applications and Management
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• v.20 no.4
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• pp.235-247
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• 2013

The evolution of information technology and proliferation of hospital management and managerial applications of computing has led to change in the characteristics, uses and evaluations of software for the hospital management. With the growing proliferation of microcomputer use and the value-added for management strategies, more and more software has been massively developed, produced and distributed for the hospital industry. The user is faced with an increasingly difficult choice in the evaluation and selection of software. For many reasons, users frequently must rely on expert evaluations of the technical functions and quality of software. The objectives of this study are to provide selection criteria for an Electronic Medical Record (EMR) and to develop an evaluation framework for the Hospital Information Systems. The major findings of our study are as follows (1) the identification of EMR evaluation characteristics (2) the design and development of EMR selection model and (3) the evaluation of the importance for EMR characteristics using Analytic Hierarchy Process (AHP). We identify 6 characteristics and 22 sub-characteristics of the EMR, calculate their weights, and decide the best configuration. Especially, the AHP methodology can be applied to gather knowledge from multiple experts. Because AHP can 1) facilitate the participation of multiple experts 2) increase group productivity and therefore result in both quantitatively and qualitatively superior outcomes than that of a single individual's work 3) provide a mechanism for reconciling conflict from multiple expert 4) validate the acquired knowledge, providing consistency of facts, and 5) enhance the accuracy reliability of the acquired knowledge increase through of the reliability provided by consensus across multiple experts. Although some further research is required, the proposed model can be regarded as a basis for the selection of EMR.

• Journal of Technologic Dentistry
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• v.38 no.4
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• pp.365-380
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• 2016

Purpose: The purpose of this study was to ascertain the need to reform curriculums for digital experts in a way that include the practical and educational aspects of dental labs by determining why educational reforms are needed to comply with changes in dental technology business that are brought by the applications of digital scanning and what changes are being actually brought by the use of CAD/CAM. Methods: This study analyzed the need of education and practice in relation to CAD/CAM by using the independent sample t-test and One-way ANOVA. in accordance with the participants demographic characteristics and job-related variables and factors related to CAD/CAM, and provided only some of the analysis results that were found statistically significant. Concerning the need of education and practice in relation to CAD/CAM, the study also used the independent sample t-test to measure difference in the perception of that need within each of the three groups, or those of job performance, job efficiency and knowledge gain at the signficance level of ${\alpha}=.05$. Results: Dental technologists surveyed here were perceiving that the use of CAD/CAM would bring changes in their job performance, job efficiency and knowledge gain. They were expecting that the biggest changes would be made in work climate and product quality as sub-areas of job performance. However, they said that in terms of job efficiency, the use of CAD/CAM would change job contribution, job satisfaction and job efficiency, but not lead to staffing. These results suggest that more special programs for CAD/CAM education are needed to bring up CAD/CAM experts who are more specialized. Conclusion: Among 13 skills related to CAD/CAM, what is most needed to be educated to dental technologists was "molding the occlusal surface" (M=4.19), followed by "designing the 3-D work" (M=4.17), "final shape modification" (M=4.16), "molding the border" (M=4.15) and "checking the fit of prothesis" (M=4.14) in order.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.

• International Journal of High-Rise Buildings
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• v.4 no.1
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• pp.85-90
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• 2015

Advances in the technology of computational design are giving architects and engineers the opportunity to analyze buildings with complex geometries. This study explores the optimization and automation process using the parametric design method, and uses digital tools to achieve surface representation and panelization for curved shaped office buildings. In this paper, we propose parametric algorithms of dimensional and geometric constraints using the Knowledge-ware scripts embedded in Gehry Technologies' Digital Project. The knowledge-based design methods proposed in this study can be used to systemize the knowledge possessed by experts in the form of data. Such knowledge is required to promote collaboration between designers and engineers in the process of CAD/CAE/CAM. The aim of this study is to integrate the process into design, which establishes an integrated process. This integration enables two-way feedback between design and construction data by combining the methods used in designing, engineering, and construction.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.664-667
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• 2000

Although managing knowledge about business processes has been recognized as an important aspect of Knowledge Management System (KMS), it has not been satisfactorily addressed academically or commercially. This paper proposes a KMS architecture to effectively manage business process as knowledge. It expands commonly recognized KMS functions with the process packaging module that defines business processes, monitors and evaluates process instances, keeps process instance history, and provides link between processes and other knowledge items such as documents and experts. The users can not only find the best practice of a business process but also learn from mistakes. A prototype system is implemented to show the feasibility of the proposed architecture. The results of this paper can contribute to expand current KMSs to help use knowledge to enhance the users' performance in their business processes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.315-320
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• 1997

Rule minimization technique adapted from rough set theory was applied to remove redundant knowledge which is not necessary to make a knowledge base. New algorithm to diagnose fault using Improved Fuzzy Cognitive Maps(I-FCMs), and Fuzzy Associative Memory(FAM) is proposed. I-FCM[22] is superior to gathering knowledge from many experts and descries dynamic behaviors of systems very well. I-FCM is not only a knowledge base, but also a inference engine. FAM has learning capability like neural network[12]. Rule minimization and composition of I-FCM and FAM make it possible to construct compact knowledge base and breaks the border between inference engine and knowledge base.

• Design & Manufacturing
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• v.9 no.2
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• pp.6-9
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• 2015

The objective of manufacturing knowledge sharing platform is to convert the production experience like a worker's know-how into quantitative values, to construct database of the process technologies and to share the technologies systematically via web portal service. In addition, the knowledge sharing platform contains the total production processes of automobile and mobile products such as information of experts, facilities, and cutting-edge R&D outputs. Automobile, telecommunication mobile, and semiconductors account for a large amount of Korea's export industry rate. These industries need production technology which is a result of converting worker's know-how and R&D. Manufacturing knowledge portal aims to enable transforming production experience such as worker's know-how into standardized form for constructing database and sharing technologies systematically. Manufacturing knowledge portal can contribute to small and mid-sized manufacturing companies with further improvements.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.215-222
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• 2001

The task for chromosome analysis and diagnosis by experienced cytogenetists are being concerned as repetitive, time consuming job and expensive. FOr that reason, chromosome analysis system based on knowledge base for CAI had been established to be able to analyze chromosomes and obtain necessary advises from the knowledge base instead of human experts. That s to say, knowledge base by IF THEN production rule was implemented to a knowledge domain with normal and abnormal chromosomes, and then the inference results by knowledge base could enter the inference data into the database. Experimental data were composed of normal chromosome of 2,736 patients'cases and abnormal chromosomes of 259 patients'cases that have been obtained from GTG-banding metaphase peripheral blood and amniotic fluid samples. The complete system provides variously morphological information by analysis of normal or abnormal chromosomes and it also has the advantage of being able to consult with user on chromosome analysis and diagnosis.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.9-12
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• 2004

Developing an efficient knowledge base construction mechanism as an input method for expert systems (ES) development is of extreme importance due to the fact that an input process takes a lot of time and cost in constructing an ES. Most ES require experts to explicit their tacit knowledge into a form of explicit knowledge base with a full sentence. In addition, the explicit knowledge bases were composed of strict grammar and keywords. To overcome these limitations, this paper proposes a knowledge conceptualization and construction mechanism for automated knowledge acquisition, allowing an efficient decision. To this purpose, we extended traditional knowledge map (KM) construction process to dynamic knowledge map (DKM) and combined this algorithm with relational database (RDB). In the experiment section, we used medical data to show the efficiency of our proposed mechanism. Each rule in the DKM was characterized by the name of disease, clinical attributes and their treatments. Experimental results with various disease show that the proposed system is superior in terms of understanding and convenience of use.