• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.28-37
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• 2011

With growing concerns about healthy life recently, although the podiatry which deals with the whole area for diagnosis, treatment of foot and leg, and prevention has been widely interested, research in our country is not active. Also, because most of the previous researches in data analysis performed the quantitative approaches, the reasonable level of reliability for clinical application could not be guaranteed. Clinical data mining utilizes various data mining analysis methods for clinical data, which provides decision support for expert's diagnosis and treatment for the patients. Because the decision tree can provide good explanation and description for the analysis procedure and is easy to interpret the results, it is simple to apply for clinical problems. This study investigate rules of item of diagnosis in disease types for adapting decision tree after collecting diagnosed data patients who are 2620 feet of 1310(males:633, females:677) in shoes clinic (department of rehabilitation medicine, Chungnam National University Hospital). and we classified 15 foot diseases followed factor of 22 foot diseases, which investigated diagnosis of 64 rules. Also, we analyzed and compared correlation relationship of characteristic of disease and factor in types through made decision tree from 5 class types(infants, child, adolescent, adult, total). Investigated results can be used qualitative and useful knowledge for clinical expert`s, also can be used tool for taking effective and accurate diagnosis.

• Journal of the Korea Institute of Building Construction
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• v.23 no.6
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• pp.851-862
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• 2023

This study introduces an objective and systematic framework for prioritizing buildings in the Gamyoung restoration project using a decision-support model. This model integrates evaluation criteria derived from a comprehensive literature review, refined through the Delphi method, and weights assigned via an Analytic Hierarchy Process(AHP) survey. Each building project is scored against these criteria to ascertain its priority for restoration, thereby facilitating informed decision-making for budget allocation in restoration projects. The effectiveness of the decision-support model was validated through a case study and expert consultations, demonstrating its practical utility in formulating concrete restoration project plans.

• Journal of Information Science Theory and Practice
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• v.7 no.4
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.5
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• pp.163-170
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• 2005

Urban transit is a complex system that is combined electrically and mechanically, it is necessary to construct maintenance system for securing safety accompanying high-speed driving and maintaining promptly. Expert system is a computer program which uses numerical or non-numerical domain-specific knowledge to solve problems. In this research, we intend to develop the expert system which diagnose failure causes quickly and display measures. For the development of expert system, standardization of failure code classification system and creation of BOM(Bill Of Materials) have been first performed. Through the analysis of failure history and maintenance manuals, knowledge base has been constructed. Also, for retrieving the procedure of failure diagnosis and repair linking with the knowledge base, we have built RBR(Rule Based Reasoning) engine by pattern matching technique and CBR(Case Based Reasoning) engine by similarity search method. This system has been developed based on web to maximize the accessibility.

• Journal of the Korea Society for Simulation
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• v.26 no.2
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• pp.59-65
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• 2017

Along with the development of M&S, modeling research utilizing AI technology is attracting attention because of the fact that the needs of fields including human decision making such as defense M&S are increased. Obviously AI is a way to solve complex problems. However, AI did not consider logical time such as input time and processing time required by M&S. Therefore, in this paper we proposed a "time-based expert system" which redesigned the representative AI technology rule-based expert system. It consists of a rule structure "IF-THEN-AFTER" and an inference engine, takes logical time into consideration. We also tried logical analysis using a simple example. As a result of the analysis, the proposal Time-based Expert System proved that the result changes according to the input time point and inference time.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.83-93
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• 2000

This paper proposes the use of the analytic hierarchy process(AHP) controller for obtaining optimal cycle time of traffic intersection signal. By means of simulations that have data from expert traffic estimators, the performance of AHP controller is compared with a fixed-time controller and fuzzy controller. A simulation was executed using data obtained from many expert interviewer of Ansan City hall rotary. The principal issue is how AHP controller algorithm can aid traffic signal supervisor to construct an expert system for traffic intersection signal control. This paper has two steps: (I) we shall present a new methodology based on the work of Satty for calculating a scale of importance of each of the objectives, (2) we also consider that the human's decision mechanism is represented by approximating reasoning where the fuzzy integral is used.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.71-80
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• 2005

Recently, water quality problems are emerging as important social issues since water quality in rivers and lakes are significantly deteriorated. Thus, an accurate prediction system on reservoir water quality is required, as well as an integrated system which can provide a solution for taking away contaminated materials. This research aims to develop an intelligent decision support system, which uses a GIS enabling management and spatial analysis. The developed system is a prototype that can be applied into real spot. This research area includes the following main subjects; system analysis and design, geometry data collection and database implementation, data acquisition and analysis on reservoir water quality, interface design and development GIS, and development of an expert system for water quality forecasting by WASPS.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.667-672
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• 2009

Gathering information and systemization of infrastructure disaster management is to reduce uncertainties in making decisions and maximize the number of alternations. The key objects of a sensor-based progress report and propagation automation systems are to provide objective data, realize and support decision making and deliver them to a certain area, department, manager and other people rapidly. The major findings and results of this study are as follows. 1) Application of international standard-based alerting protocol(CAP; Common Alerting Protocol). 2) Development of database of existing progress report and propagation manual in order to achieve networking of safety management on major social infrastructure of the nation. 3) Development middleware application programs to progress report and propagation data using SMS, FAX, EMS, VMS, MMS.

• Journal of the Ergonomics Society of Korea
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• v.19 no.3
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• pp.23-37
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• 2000

Usability is one of the most important factors that affect customers' decision to purchase a product. Several studies have been conducted to model the relationship between the product design variables and the product usability. Since there could be hundreds of design variables to be considered in the model, a variable screening method is required. Traditional variable screening methods are based on expert opinions (Expert screening) in most Kansei engineering studies. Suggested in this study are statistical methods for screening important design variables by using the principal component regression(PCR), cluster analysis, and partial least squares(PLS) method. Product variables with high effect (PCR screening and PLS screening) or representative variables (Cluster screening) can be used to model the usability. Proposed variable screening methods are used to model the usability for 36 audio/visual products. The three analysis methods (PCR, Cluster, and PLS) show better model performance than the Expert screening in terms of $R^2$, the number of variables in the model, and PRESS. It is expected that these methods can be used for screening the product design variables efficiently.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.3
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• pp.240-246
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• 1990

The security control can be defined as all control actions and counter-measures to return the operating state of the system to a normal state. In an emergency state, fault clearing and/or overload suppression is enabled as a security control in order to prevent the extension of the fault. In the alert state, counter-measures should be set up in advance for the dangerous points of the system operation in drder to protect the system from expected accidents. In the normal state, the routine scenario is conducted to analyze system state. In the decision-making of the classification of system states, the heuristic and experienced knowledge can be well applied and thus application of expert system to this area attains considerable achievements. In this study, it is attempted to extract empirical rules through heuristic analysis and establish the knowledge base. Finally, the incorporation method with the conventional program packages in proposed. The expert system is designed to select an appropriate method and to perform the corresponding package. The input data can be automatically set up by using the data base. The computation results can be automatically added to the data base.