• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.632-637
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• 2008

In real system application, the propeller shaft rate (PSR) estimation algorithm for the feature extraction of the sonar target operates with the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family composed of the fundamental and its harmonics from the multiple spectral lines in the frequency spectrum-based sonar target classification, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. To verify the performance of the proposed algorithm, a sonar target PSR estimation is performed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.141-150
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• 2000

There are three significant drawbacks in extant fuzzy rule-based expert system languages. First, they lack the functionality of composite object inference. Second, they do not support fuzzy reasoning semantically easy to understand and conceptually simple to use. Third, knowledge representation and reasoning style of their model have a great semantic gap with those of current database models. Therefore, it is very difficult for the two models to be seamlessly integrated with each other. This paper provides the formal specification of a fuzzy object inference model to solve the three drawbacks. GIS(Geographic Information System) application domain is used to demonstrate that our model naturally models complex GIS information in terms of composite objects and successfully performs fuzzy inference between them.

• Journal of the Korean Institute of Navigation
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• v.23 no.2
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• pp.1-9
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• 1999

A trailer truck is a major equipment for transporting containers, and its driving is difficult due to two degrees of freedom which exist in the joint part between truck and trailer. Especially Backing a trailer truck to a parking home is a difficult exercise for all but the most skilled truck drivers. Normal driving instincts lead to erroneous movements. When watching a truck driver backing toward a parking home, one often observes the driver backing, going forward, backing again, going forward, etc., and finally backing to the desired position along the parking home. This paper discusses the design of the controller to control the steering of a trailer truck while only backing up to a parking home from an initial position. In this paper, we propose a backing up control system for a container trailer truck using fuzzy theory where the primitive fuzzy control rules are macroscopically designed using an expert's knowledge, and the control rules are regulated by LIBL(Linguistic Instruction Based Learning) to enable to back up successfully the trailer tuck to a parking home from arbitrary initial position. The validity of the proposed parking control system is shown by applying it to some initial positions on the simulator for container trailer truck.

• Journal of Sport and Applied Science
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• v.3 no.1
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• pp.1-14
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• 2019

Numerous types of sporting events have been hosted in Korea during the last decades. Sport events produce various types of data, and there is a clear necessity of storing and utilizing this information. From this background, the purpose of this study is to draw complex sports categories from international sport events life cycles in order to categorize standards of knowledges management system. This study utilized qualitative methods: expert groups discussion for overall life cycle steps and in-depth interviews for detail life cycle steps. The results show that there are several life cycle steps: bidding, preparation, operation, evaluation, post management steps. To be more specific, for the bidding step, there are check, plan, implementing detail phase; and the preparation step is based on event preparation Basis Build, event preparation implementation, test and supplementation phases. For the operation step, event operation system switch, event operation during the period, finish operation phases are deducted. Evaluation and post management step do not have detail phases. Efforts to store and utilize knowledge can be one of the starting points to make the operation of sport events efficiently.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.133-149
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• 2017

As cities face increasing problems such as aging, environmental pollution and growth limits, we have been trying to incorporate sustainability into urban planning and related policies. However, it is very difficult to generate a 'sustainable spatial plans' because there are trade-offs among environmental, society, and economic values. This is a kind of non-linear problem, and has limitations to be solved by existing qualitative expert knowledge. Many researches from abroad have used the meta heuristic optimization algorithms such as Genetic Algorithms(GAs), Simulated Annealing(SA), Ant Colony Optimization(ACO) and so on to synthesize competing values in spaces. GAs is the most frequently applied theory and have been known to produce 'good-enough plans' in a reasonable time. Therefore we collected the research on 'spatial optimization model based GAs' and analyzed in terms of 'study area', 'optimization objective', 'fitness function', and 'effectiveness/efficiency'. We expect the results of this study can suggest that 'what problems the spatial optimization model can be applied to' and 'linkage possibility with existing planning methodology'.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.980-983
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• 2000

The world faces a legacy of serious environmental problems such as exhaustion of natural resources and lack of landfill sites. To address these problems, recycling of materials and products has been proposed, but at present, it is realized only within a few fields. This is because most industrial products consist of various components made of different materials and their recycling are based on the assumption that they can be separated and classified easily, the actual situation however cannot satisfy this assumption. The issue in recycling the components and wastes of used cars, in turn, gives rise to emphasis on the disassembly process. For the efficient disassembly, the component materials and their easy separation as well as the recyclability must be taken into account as early as in the design process. It should be developed an almost perfect design catalogue with existing technologies by analyzing design characteristics, manufacturing, assembly and disassembly processes for major parts and components of automobiles in terms of existing and newly proposed recycling technologies. Also it is essential to provide more technical know-how and application methods that may be helpful to utilize different components and component groups.

• Journal of Information Technology Services
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• v.20 no.2
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• pp.91-109
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• 2021

Recently, social and economic environment has been rapidly changed. In particular, the development of IT technology accelerated the introduction of databases, communication networks, information processing and analyzing systems, making the use of such information and communication technology an essential factor for corporate management innovation. This change also affected the accounting areas. The purpose of this study is to document changes in accounting areas due to the adoption of IT technologies in the era of technology and information, to define the required accounting professions in this era, and to present the efficient educational methodologies for training such accounting experts. An accounting expert suitable for the era of technology and information means an accounting profession not only with basic accounting knowledge, competence, independency, reliability, communication skills, and flexible interpersonal skills, but also with IT skills, data utilization and analysis skills, the understanding big data and artificial intelligence, and blockchain-based accounting information systems. In order to educate future accounting experts, the accounting curriculum should be reorganized to strengthen the IT capabilities, and it should provide a wide variety of learning opportunities. It is also important to provide a practical level of education through industry and academic cooperation. Distance learning, web-based learning, discussion-type classes, TBL, PBL, and flipped-learnings will be suitable for accounting education methodologies to foster future accounting experts. This study is meaningful because it can motivate to consider accounting educational system and curriculum to enhance IT capabilities.

• Journal of dental hygiene science
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• v.17 no.3
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• pp.193-201
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• 2017

This study was conducted to derive core and detailed competencies of dental hygienists to be utilized as educational targets to be reached by graduation as well as basic data that can be reflected in the development and improvement of dental hygiene curricula. This study analyzed publication reports from the Korean Dental Hygienists Association, the International Federation of Dental Hygienists, the Commission on Dental Accreditation, and the American Dental Education Association. Based on the academic classification system for dental hygiene studies, the components of core and detailed competencies of dental hygiene school at the time of graduation were extracted and developed through expert panel discussions. This study defined competencies at the graduation level of dental hygiene school and derived eight core competencies and their 52 detailed competencies to serve as educational objectives from four areas: professionalism, communication, clinical practice, and community and health promotion. In the future, it will be necessary to conduct self-assessments of competencies based on those developed in this study, at time of the graduation from dental hygiene school, as well as to continuously develop competency-based curricula according to entry level, knowledge level, and graduation level. Thus, it is urgently necessary to develop a system that can evaluate the competencies of dental hygienists after graduation and put this system into practical use.