• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.417-419
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• 2012

국내의 자동차 정비 훈련 교육 현장에는 훈련교사가 빠르게 발전되고 있는 자동차 정비 기술 수준에 맞춰 교육하는데 어려움이 있다. 이 같은 어려움을 해결하기 위한 이-트레이닝(E-training) 시스템은 체험형 훈련이 가능하면서도 높은 학습 효과를 가져올 것이라 기대되고 있다. 자동차 정비 훈련을 위한 이-트레이닝 시스템은 훈련교사가 자동차 고장 항목을 설정하면, 훈련생이 고장 진단을 위한 다양한 시도를 하여 고장을 인지하고, 그에 따른 조치를 통해 주어진 문제를 해결함으로써 학습효과가 높아질 것이라 기대되는 시스템이다. 하지만 이-트레이닝 시스템은 이미 설정되어 있는 시나리오에 따른 일방적인 교육, 학습자에 대한 지속적인 관리의 어려움, 학습자의 행동을 추론하여 정확한 결과를 도출해내기가 어렵다는 한계가 있다. 본 논문에서는 이-트레이닝 시스템의 문제점을 해결하기 위한 방법으로 자동차 정비를 위한 자동차 몸체, 엔진, 정비 도구에 대한 온톨로지를 구축하고 추론하여 효과적인 자동차 정비 훈련 교육이 될 수 있도록 하는 방법을 제안하고자 한다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.1
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• pp.75-81
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• 2007

This paper dealt with the design and implementation of an expert system to monitor and diagnose the lightning arresters in GIS substations. The expert system consists of a data acquisition module(DAM) based on microprocessor and diagnostic algorithms. The DAM measures and analyzes several parameters necessary for the arrester diagnosis such as system voltages, leakage current components, and temperatures. Also, it includes an intelligent surge counter which can record the date and tin, the polarity, and the amplitude of surge currents. All the data acquired is transmitted to a remote computer by a low rate wireless network specified in IEEE 802.15.4 to avoid electromagnetic intereference under high voltage and large current environments. The decision-making for the arrester diagnosis completes with a Java Expert System Shell(JESS) which is composed of a knowledge base, an inference engine and a graphic user interface(GUI).

• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.1079-1087
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• 2003

A lot of expert systems have been developed in the area of medical diagnosis and prescription, but there has been relatively little effort to develop medical expert systems using domestic technologies. In this paper, a medical expert system for gastroenteritis is developed, which can be easily used on the Internet. This system is implemented using Java technologies and Jess, which is a Java expert system shell. Therefore. the system can be used independently from a specific platform on the Internet. In addition, facts and rules of a knowledge base in the system ate represented separately making the system updatable and expandable with ease.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.185-193
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• 2008

In spite of rapid development of IT-related meteorology and services, human users still ought to check the weather information manually as they did before because traditional weather information retrieval is based on pull-type and human interpretation. Furthermore, the automatic machine-driven weather information processing has been neglected for a long time although the intelligent weather information processing is expected to be very useful for personal daily life and ubiquitous computing. In this paper, we discussed a design of GRIB based ontology to enable smart weather information processing. GRIB is the general purposed and world-wildly used weather data format approved by the World Meteorological Organization. With the designed ontology and the inference system containing Jess engine, several intelligent weather applications have been implemented and tested to verify the virtue of machine-driven weather information processing.

• Journal of the Korea Society for Simulation
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• v.23 no.2
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• pp.73-84
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• 2014

Recently, researches on the application of IT technology to various fields including traditional industries are becoming more popular. One challenge in the field of education is to understand the way how technology may support learning, and research on self-directed learning has been accelerated by integrating education and IT technology. The process of self-directed learning in e-learning applications such as Car Maintenance Training is very difficult and complicated. Previous studies on car maintenance training applications provided simple training scenarios with predetermined action sequences. To incorporate self-directed learning in car maintenance training, however, trainees must be able to perform various maintenance operations himself and experience various situations. To provide such functionality, it is necessary to obtain an accurate response for various operations of trainees, but it requires complicated calculations with respect to varieties in the electrical and mechanical processes of a car. In this paper, we develop a logic simulation agent using JESS inference engine in which self-directed learning is achieved by capturing the behavior of trainees and simulating car operations without complicated physical simulations in car maintenance training.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.555-556
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• 2011

액티브 RFID를 기반으로 실시간 위치정보 서비스를 구현하는 모델인 RTLS는 보안, 의료, 건설, 항공, 항만, 운송, 국방, 교통, 레저 등 실시간 위치정보가 필요한 분야에 효과적으로 활용되고 있다. 이 논문에서는 RTLS 응용 시스템을 위한 지능형 위치정보 관리시스템을 제안한다. 제안 시스템은 일반적인 데이터 관리의 기능 이외에도 상황인식 시스템에서 사용되는 규칙기반 미들웨어 Jess(Java expert system shell)를 활용하는 구조를 가진다. 규칙을 이용한 추론 기능을 도입함으로써 응용 시스템의 정확성을 높일 수 있는 특징을 가진다.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1566-1574
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• 2008

Researches of current information searching focus on providing personalized results as well as matching needed queries in an enormous amount of information. This paper aims at discovering hidden knowledge to provide personalized and inferred search results based on the ontology with categorized concepts and relations among data. The current searching occasionally presents too much redundant information or offers no matching results from large volumes of data. To lessen this disadvantages in the information searching, we propose an inference algorithm that supports associated and inferred searching through the Jess engine based on the OWL ontology constraints and knowledge expressed by SWRL with association rules. After constructing the personalized preference ontology for domains such as restaurants, gas stations, bakeries, and so on, it shows that new knowledge information generated from the ontology and the rules is provided with an example of the domain of gas stations.

• The Journal of Korean Association of Computer Education
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• v.11 no.5
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• pp.77-88
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• 2008

Having observed the restriction of the current Web technology, the semantic Web has been developed, and it now has grown up with the core help of the W3C to a level where it recommends the OWL Web ontology language. Besides, in order to deduce the information out of OWL data, several inference systems have been developed such as Jena, Jess, and JTP. Unfortunately, however, quite few systems can effectively handle recently developed OWL data, and further, due to the limitation of file-based operation, the current inference systems cannot meet the requirements for handing huge OWL data. An efficient method for storing and searching ontology data is essential for ensuring stable information inference processes. In this study, firstly, we proposed a model based on the database management system to transform and store OWL data and to enable deduction process from the database. Secondly, we designed and implemented an effective OWL storing system based on our model. Finally, we compare our system with the previous inference systems through experimental performance analysis.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.105-113
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• 2009

The feature models are widely used to model the commonalities and variabilities among the products in the domain engineering phase of software product line developments. The findings and corrections of the errors or consistencies in the feature models are essential to the successful software product line engineering. The aids of the automated tools are needed to perform the validation of the feature models effectively. This paper describes the approach based on JESS rule-base system to validate the feature models and proposes the feature model validation tool using this approach. The tool of this paper validates the feature models in real-time when modeling the feature models. Then it provides the information on existence of errors and the explanations on causes of those errors, which allows the feature modeler to create the error-free feature models. This attempt to validate the feature model using the rule-based system is supposed to be the first time in this research field.

• The International Journal of Costume Culture
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• v.8 no.2
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• pp.71-84
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• 2005

Fibulae have been used as clothing fasteners throughout history. They were especially popular with the Celts, but were also used by the Greeks, Romans, Saxons, and Vikings, to name a few. The earliest examples are found in the Mediterranean and Middle East, and date from 800 B. C. and earlier. Their use continues today, in the form of the modern safety pin. The first fibulae of the Bronze Age were very simple, much like modern safety pins. The form of this small functional object varies from simple to extravagant since it is also seen as a piece of jewelry, and is thus subject to the evolution of style. Its size depends on the thick/Jess of the clothing to be attached. Its fabrication demonstrates a great mastery of metal work. Fibulae would vary with the taste and wealth of the wearer. The Fibulae were divided into 10 styles according to the shape, Fibulae with Safety pin shaped style, Penannular shaped style, Animal shaped style, Diamond shaped style, Radiated head shaped style, Horsefly shaped style, Arched bow shaped style, Fan-shaped style, Trumpet shaped style, Arched-fan shaped style.