• Computers and Concrete
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• v.21 no.1
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• pp.21-30
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• 2018

In this study, we analyze the behavior of concrete which contains zeolite and diatomite. In order to achieve the goal, we utilize expert system methods. The utilized methods are artificial neural network and adaptive network-based fuzzy inference systems. In this respect, we exploit seven different mixes of concrete. The concrete mixes contain zeolite, diatomite, mixture of zeolite and diatomite. All seven concrete mixes are exposed to 28, 56 and 90 days' compressive strength experiments with 63 specimens. The results of the compressive strength experiments are used as input data during the training and testing of expert system methods. In terms of artificial neural network and adaptive network-based fuzzy models, data format comprises seven input parameters, which are; the age of samples (days), amount of Portland cement, zeolite, diatomite, aggregate, water and hyper plasticizer. On the other hand, the output parameter is defined as the compressive strength of concrete. In the models, training and testing results have concluded that both expert system model yield thrilling medium to predict the compressive strength of concrete containing zeolite and diatomite.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.11
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• pp.596-603
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• 2004

This paper proposes an expert system based on the pattern recognition method which can enhance the accuracy and effectiveness of real-time bus reconfiguration strategy for the transfer of faulted load when a main transformer fault occurs in the automated substation. The minimum distance classification method is adopted as the pattern recognition method of expert system. The training pattern set is designed MTr by MTr to minimize the searching time for target load pattern which is similar to the real-time load pattern. But the control pattern set, which is required to determine the corresponding bus reconfiguration strategy to these trained load pattern set is designed as one table by considering the efficiency of knowledge base design because its size is small. The training load pattern generator based on load level and the training load pattern generator based on load profile are designed, which are can reduce the size of each training pattern set from max L/sup (m+f)/ to the size of effective level. Here, L is the number of load level, m and f are the number of main transformers and the number of feeders. The one reduces the number of trained load pattern by setting the sawmiller patterns to a same pattern, the other reduces by considering only load pattern while the given period. And control pattern generator based on exhaustive search method with breadth-limit is designed, which generates the corresponding bus reconfiguration strategy to these trained load pattern set. The inference engine of the expert system and the substation database and knowledge base is implemented in MFC function of Visual C++ Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and pattern recognition solution based on diversity event simulations for typical distribution substation.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.63-73
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• 2011

The purpose of this study was to suggest the education and training program for disaster management by comparison between DACUM technique applied curriculum and curriculum by expert committee, and curriculum development. First, DACUM technique applied curriculum development. Job Classification of Disaster management was consisted of four jobs - mitigation, preparedness, response and recovery - by three times discussions of expert panels. Job analysis and curriculum development were performed by the DACUM panels who consisted of three subject-matter experts and one educational expert on each field. Curriculum developed mitigation was nine courses, preparedness was twelve courses, response was seven courses, and recovery was four courses. Second, Expert committee developed curriculum. Expert committee consisted of five experts and three educational expert. Expert committee was held four times. Curriculum developed thirty five courses. Then disaster management curriculum determined by discussion of experts. disaster management curriculum considered (1)mitigation and preparedness was thirty one courses, (2)response and recovery was fourteen courses, (3)man-made was six courses, (4)manager level was four courses.

• International Journal of Railway
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• v.2 no.2
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• pp.50-59
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• 2009

Numerous train operating companies provide training by means of driving simulators. A detailed analysis in the course of the rail research project 2TRAIN has shown that the simulation technology, the purposes of training and the overall concept of simulator-based training are rather diverse (Schmitz & Maag, 2008). A joint factor however are weak assessment capabilities and the fact that the simulator training is often not embedded into the overall competence management. This fact hinders an optimal use of the simulators. Therefore, 2TRAIN aims at the development of enhanced training and assessment tools. Taking into account that several simulators are already in use, the focus lays on the extension of existing simulation technology instead of developing entirely new systems. This extension comprises (1) a common data simulation interface (CDSI), (2) a rule-based expert system (ExSys), (3) a virtual instructor (VI), and (4) an _assessment database (AssDB). The foundation of this technical development is an assessment concept (PERMA concept) that is based on performance markers. The first part of the paper presents this assessment concept and a process model for the two major steps of driver performance assessment, i.e. (1) the specification of exercise and assessment and (2) the assessment algorithm and execution of the assessment. The second part describes the rationale and the functionalities of the simulator add-on tools. Finally, recommendations for further technical improvement and appropriate usage are given. based on the results of a pilot study.

• Journal of Korea Ship Safrty Technology Authority
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• s.32
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• pp.57-71
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• 2012

Recently, the navigation risk is increasing significantly with growing of vessels' volume and propelling marine facilities, water bridges and port development etc. At this point of time, the Ministry of Land, Transport, and Maritime Affairs introduced the Maritime Safety Audit(MSA) in amendment of the Korea Marine Traffic Law. audit results were survey for the last two years. As a result, appropriate certificate appears 11% among audit report, is an urgent need for improved quality of audit reports. This study is aimed to propose about Audit Personnel Education & Training System. To these solve, this paper analyzed the tendency of Audit Personnel Training. And also the opinions of user and experts were investigated and analyzed using Questionnaire survey methods. As a result, this paper was suggested, the construction of Audit Personnel Training System and the curriculum and training contents for 5-days of basic course, 2-days of expert course, 3-days of Qualification Maintain course.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.475-483
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• 1997

Industrial safety management program consists of three part which is education, technology and control. The effectiveness of industrial safety control program rely on the ability of controlling hardware system, technology and software, training and management. How to design and develop the sharing machine fault and safety diagnosis system using expert system technique is presented on this paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.231-240
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• 2001

Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.492-495
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• 2003

Fuzzy Min-Max Neural Network(FMMNN) is a powerful classifier, It has, however, some problems. Learning result depends on the presentation order of input data and the training parameter that limits the size of hyperbox. The latter problem affects the result seriously. In this paper, the new approach to alleviate that without loss of on-line learning ability is proposed. The committee machine is used to achieve the multi-resolution FMMNN. Each expert is a FMMNN with fixed training parameter. The advantages of small and large training parameters are used at the same time. The parameters are selected by performance and independence measures. The Decision of each expert is guided by the gating network. Therefore the regional and parametric divide and conquer scheme are used. Simulation shows that the proposed method has better classification performance.

• Journal of Physiology & Pathology in Korean Medicine
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• v.32 no.4
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• pp.185-196
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• 2018

The purpose of this study is to evaluate the current inter-expert agreement of Sasang Constitution Medicine (SCM), to expand the current knowledge on the causes of imperfect inter-expert agreement, and to explore possible solutions for improving inter-expert agreement. A literature search was conducted to gather data on the studies on diagnosis of SCM. The 127 articles included in this analysis had a mean 4.1 publications per year, 56.0% published in the Journal of Sasang Constitutional Medicine between the year of 1987 and 2017. SCM specialist participated in 96.3% of all the expert judgment cases. Inter-expert agreement was reported in 14.8% of the cases that had two or more experts. We recommend that expert panels integrate the results of current status of diagnostic consensus into guideline development and strengthen expert education and training with the aim of improving SCM diagnostic accuracy.

• Journal of the Korean Dietetic Association
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• v.17 no.4
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• pp.403-415
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• 2011

The present study was performed to evaluate the job training needs of school nutrition teachers in order to enhance their specialty. Three hundred and forty questionnaires were distributed to school nutrition teachers working at primary and high schools in the Gyeongbuk area while 45 were distributed to professors during 2010~2011. Three hundred and two questionnaires from school nutrition teachers and 33 from professors were returned and analyzed. The rate of teachers practicing nutrition education was 54%, and the educational content was obtained mainly from the internet. The top three problems the teachers encountered were 'lack of standardized educational materials', 'inexperience of teaching', and 'insufficiency of expert knowledge'. The teachers recognized 'training program' as the best solution. However, the job training program operated immediately after teachers were appointed scored only 3.03 out of 5.00. Important contents of the training program ranked highly by the teachers were 'development of education materials', 'nutrition counseling', and 'teaching method'. The professors included 'expert knowledge' in their top three contents. Both the teachers and professors agreed to increase the frequency of 'practice' in training methods. Other factors the teachers considered to be important were high quality, diversity, ability of the instructor, training cycle, and the institution in charge. From these results, it can be concluded that efficient job training programs are needed for school nutrition teachers according to the importance of the education contents and training methods. It is therefore suggested that a cooperation committee be composed of an educator, educatee, and related personal in a local education office in order to operate the program.