• Proceedings of the Korea Concrete Institute Conference
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• 2000.04a
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• pp.874-879
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• 2000

A prototype expert system for normal concrete mix design was developed using an technical consulting system development tool, EXSYS Professional. The knowledge contained in the system was obtained from the standard specifications of Korea Concrete Institute, American Concrete Institute and from the related British Standards. The knowledge base and user interface will be expanded to cover wider scopes of the problems. If the system is successfully developed as an operational system, it will produce a great deal of economic benefits by reducing the time and money needed to obtain an expert's judgement and experience in decision making for repetitive tasks related to concrete mix proportions.

• Journal of the Korean Society for information Management
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• v.11 no.2
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• pp.131-164
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• 1994

This study shows the design and implementation of cataloging expert system using pattern recognition techniques. This system attemps to demonstrate the feasibility of cataloging in KORMARC format from title page and copyright page without the intervention of humans. The prototype was implemented as a rule-based system in Turbo C. To demonstrate the function and capability of the system, experimental document-group and control document-group was analyzed. The hit ratio of experimental document-group is 94%. On the other hand, the hit ratio of control document-group is 93%, a little bit lower than the experimental group.

• IE interfaces
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• v.17 no.1
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• pp.13-21
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• 2004

In this study, the prototype of a system for checking risk-factor of NC machine is proposed. The proposed system can get the risk-related information by monitoring the status of real-time processes of NC machines. Using the information, the accidents can be prevented by the background process of an expert system tool. This paper consists of 2 parts: (1) the method for gathering data and definition of the risk-related factors of NC machines and (2) the procedure for finding the proper actions by using the forward chaining of a rule-base. Proposed system is implemented with C++ language under MS-windows.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.145-162
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• 1992

This paper proposes two design principles for expert systems to solve a stock market timing (SMART) problems : machine knowledge and fuzzy post-adjustment, Machine knowledge is derived from past SMART instances by using an inductive learning algorithm. A knowledge-based solution, which can be regarded as a prior SMART strategy, is then obtained on the basis of the machine knowledge. Fuzzy post-adjustment (FPA) refers to a Bayesian-like reasoning, allowing the prior SMART strategy to be revised by the fuzzy evaluation of environmental factors that might effect the SMART strategy. A prototype system, named K-SISS2 (Knowledge-based Stock Investment Support System 2), was implemented using the two design principles and tested for solving the SMART problem that is aimed at choosing the best time to buy or sell stocks. The prototype system worked very well in an actual stock investment situation, illustrating basic ideas and techniques underlying the suggested design principles.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.26
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• pp.21-31
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• 1992

Today, manpower is used as a major factor in the production of service industry that is on the increasing trend. So the research on manpower structure have been regarded as a important field. The research on personnel scheduling, however, have got de-emphasizeed as compared wi th the field of manufacturing scheduling. As the increasing trend of service industry, an appropriate personnel scheduling for each type of service industry is needed urgently. This paper deals with nurse scheduling problem in the field of personnel scheduling. We aim at developing prototype of the expert nurse scheduling program which is easy to use when scheduling without help of expert, and satisfies the various request of hospital scheduling policy and nurse scheduling.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.3
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• pp.185-192
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• 2002

Prototyping for field inspection safety assessment expert system of bridge structures is presented in this paper. Knowledgebase with production rules is constructed using the semiautomatic method on the basis of bridge inspection manuals and working reports of the related agency. Backward inference method is taken with the aids of external shells as a inference engine of knowledge-based systems. Implementation of the developed prototype system on MS Windows98 will shows inspiring aspects useful to guide and standardize the field works. In the case to be reinforced with abundant knowledge bases, this will be expected to be educate the practicing engineers.

• Computers and Concrete
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• v.3 no.2_3
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• pp.145-161
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• 2006

This article involves architecting prototype-fuzzy expert system for designing the nominal cover thickness by means of fuzzy inference for quantitatively representing the environment affecting factor to reinforced concrete in chloride-induced corrosion environment. In this work, nominal cover thickness to reinforcement in concrete was determined by the sum of minimum cover thickness and tolerance to that defined from skill level, constructability and the significance of member. Several variables defining the quality of concrete and environment affecting factor (EAF) including relative humidity, temperature, cyclic wet and dry, and the distance from coast were treated as fuzzy variables. To qualify EAF the environment conditions of cycle degree of wet-dry, relative humidity, distance from coast and temperature were used as input variables. To determine the nominal cover thickness a qualified EAF, concrete grade, and watercement ratio were used. The membership functions of each fuzzy variable were generated from the engineering knowledge and intuition based on some references as well as some international codes of practice.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.13-34
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• 1999

Building a knowledge base effectively has been an important research area in the expert systems field. A variety of approaches have been studied including rules, semantic networks, and frames to represent the knowledge base for expert systems. As the size and complexity of the knowledge base get larger and more complicated, the integration of knowledge based with database technology cecomes more important to process the large amount of data. However, relational database management systems show many limitations in handing the complicated human knowledge due to its simple two dimensional table structure. In this paper, we propose Object-Oriented Knowledge Store (OOKS), a knowledge base model on the basis of a frame sturcture using an object-oriented database. In the proposed model, managing rules for inferencing and facts about objects in one uniform structure, knowledge and data can be tightly coupled and the performance of reasoning can be improved. For building a knowledge base, a knowledge script file representing rules and facts is used and the script file is transferred into a frame structure in database systems. Specifically, designing a frame structure in the database model as it is, it can facilitate management and utilization of knowledge in expert systems. To test the appropriateness of the proposed knowledge base model, a prototype system has been developed using a commercial ODBMS called ObjectStore and C++ programming language.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.370-374
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• 1993

This paper describes a study on the expert system based process planning of the block division process in shipbuilding. The prototype system developed deterines the block division line of the midship of crude-oil tanker. Case-based reasoning (CBR) approach relying on previous similar cases to solve the problem is applied instead of rule-based reasoning (RBR). Similar cases are retrieved from case base according to the similarity metrics between input problem and cases. The retrieved case with the highest priority is then adapted to fit to the input problem buy adaptation rules. The adapted solution is proposed as the division line for the input problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.57-65
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• 1989

This paper describes an artificial intelligence approach to machine diagnosis. Firstly, It considers how the knowledge could be organized and represented. Secondly, it considers which inference strategy could be chosen for contingent situations for the purpose of rationality, efficiency and user-friendliness. Finally, the prototype based on the suggested model is introduced briefly.