• Nuclear Engineering and Technology
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• v.28 no.1
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• pp.36-43
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• 1996

In this work, a PC-based thermal performance monitoring system is developed for the nuclear power plants. The system performs real-time thermal performance monitoring and diagnosis during plant operation. Specifically, a prototype for the KORI-2 nuclear power unit is developed and examined in this work. The analysis and the fault identification of the thermal cycle of a nuclear power plant is very difficult because the system structure is highly complex and the components are very much inter-related. In this study, some major diagnostic performance parameters are selected in order to represent the thermal cycle effectively and to reduce the computing time. The Fuzzy ARTMAP, a self-organizing neural network, is used to recognize the characteristic pattern change of the performance parameters in abnormal situation. By examination, this algorithm is shown to be able to detect abnormality and to identify the fault component or the change of system operation condition successfully. For the convenience of operators, a graphical user interface is also constructed in this work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2150-2157
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• 2007

In this paper, we have proposed a self disease diagnosis system for ordinary persons to help the decision of access methods to a specialized medical management, and for medical specialities to discover new diseases and their symptoms easily, using verification of an individual#s health status by a series of processes performed by oneself. In the proposed self disease diagnosis system, illness is decided by 60 kinds of diseases selected using the report called #Diseases that Koreans take seriously# published by Ministry of Health & Welfare and medical contents called #Engel Pharm#, and also using 161 representative symptoms for the 60 kinds of diseases. An individual#s health information is extracted by diagnosis of one#s health status by a clustering of the 60 kinds of diseases using enhanced ART2 algorithm and input vectors from the results of questions for symptoms of each disease.

• Journal of The Korean Association of Information Education
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• v.11 no.3
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• pp.299-306
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• 2007

It is urgent to have learning support for children with learning disability according to the survey made by the government educational organization. To this end, we developed a learning support system for children with learning disability. First, the system diagnoses the children with learning disability using a decision tree based on the pre-test results. Secondly, it supports for children with learning disability one of audio-, vision- and tactility-oriented learning types according to the results from the psychological learning style test. Thirdly, one-to-one study is supported for failed students at the achievement test. For the evaluation of the system, the children with disability were divided into an experimental group and a control group and the educational achievement was evaluated. We found that 10% on the average was improved in case that learning was made after the psychological test for learning styles.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1298-1311
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• 2022

Purpose To develop and validate a deep learning-based screening tool for the early diagnosis of scoliosis using chest radiographs with a semi-supervised generative adversarial network (GAN). Materials and Methods Using a semi-supervised learning framework with a GAN, a screening tool for diagnosing scoliosis was developed and validated through the chest PA radiographs of patients at two different tertiary hospitals. Our proposed method used training GAN with mild to severe scoliosis only in a semi-supervised manner, as an upstream task to learn scoliosis representations and a downstream task to perform simple classification for differentiating between normal and scoliosis states sensitively. Results The area under the receiver operating characteristic curve, negative predictive value (NPV), positive predictive value, sensitivity, and specificity were 0.856, 0.950, 0.579, 0.985, and 0.285, respectively. Conclusion Our deep learning-based artificial intelligence software in a semi-supervised manner achieved excellent performance in diagnosing scoliosis using the chest PA radiographs of young individuals; thus, it could be used as a screening tool with high NPV and sensitivity and reduce the burden on radiologists for diagnosing scoliosis through health screening chest radiographs.

• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.107-118
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• 2004

This study aims to design and implement individual complete learning system based on IPI(Individually Prescribed Instruction) model. Most of current web based learning systems do not consider individual students' ability and just follow the sequence of instructing contents $\rightarrow$ providing problems $\rightarrow$ presenting the result of evaluating. However, this system focuses on individual ability prior to studying subjects. In individual complete learning system, it is acknowledged that a period and a pace to complete each task will differ from students to students, therefore until they complete the whole unit, they are not allowed to move onto the next unit. After completing each unit, there will be a process of evaluating students' performance. It is necessary to show the correct completion of 80% of the evaluation to move onto next step; for those who are evaluated as inadequate to move on, an individual supplementary instruction will be provided. Therefore, this study intends to supplement the deficit of prior learning and provide feedback dependent on individual's learning ability so that the goal of Individual Whole Complete Learning could be accomplished.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.662-665
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• 2013

ITS(Intelligent Tutoring System) is a system that provides active and flexible tutoring conditions to learners, having adopted artificial intelligence to overcome the limitations of CAI(Computer Assisted Instruction). However, the existing ITS has a few problems; the system provides the same contents to every learner, not considering main variants of their learning and achievement, characters and levels, and therefore, it does not generate satisfactory results; the system does not offer a properly designed course schedule. Therefore, this thesis proposes ARS(Adaptive Recommendation System), founded on ITS, that provides contents designed based on the characters and levels of learners. To catch the characters of learners, the important variant for successful learning, ARS applies and embodies a module of self-assessment test. Also, it puts weighs according to the areas of learning which is different from the simplified assessment that asks for short and mechanical answers for the purpose of knowing the levels of the learners.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.377-384
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• 2022

Whether voluntary or involuntary in the field of education, learner participation is a basic premise for all teaching-learning. It is true that behaviorism and cognitive educational psychology have helped the development of teaching-learning theory so far but the reality is that it has not been of great help to provide learner-centered education according to the learner's learning type. We have professional theological knowledge and insight in theological college and having the knowledge to diagnose and solve difficulties and problems in the pastoral field and it is an increasingly difficult reality to educate students to have spiritual leadership that can lead the future society. We know that each student should understand the characteristics of each student and teach according to their learning type but the reason why it is difficult to implement is that each learner has different competencies, conditions, and cultural backgrounds and has particularly diverse learning types. in this respect, in order to increase the learning effect of individuals, individual learning considering the learning type of students is effective.

• Journal of Oral Medicine and Pain
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• v.35 no.1
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• pp.1-18
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• 2010

I'd like to introduce a teaching method to improve learning efficiency. Most students are likely to ignore what they don't understand in the class of a course. The subject of Occlusion is essential to understanding prosthodontic and orthodontic subjects. It is necessary to let students know and review what they don't understand among parts of a chapter in the course of Occlusion. Therefore I look over the examination papers after every examination and input the problems that each student didn't solve into the C-language computer program and print the list of the contents that each student must study particularly. I give the lists to students and let them review and present their own weak parts of a chapter in the course of Occlusion in the next class. This teaching method leads to improvement in learning and is helpful to students as well as lecturers.

• Journal of the Korean earth science society
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• v.30 no.2
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• pp.257-264
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• 2009

The purpose of this study was to examine the effects of the game application learning 8th graders' scientific attitude, which was utilized as a strategy to improve the teaching skills and methods in the lesson of 'the history of the earth and diastrophism'. The subjects of this study were 120 students of 8th grade at a middle school located in a metropolitan city in Korea. To start off with homogeneity of a group, this study recruited participants by the results of a diagnostic test taken early in the year and a mid-term examination taken at the end of April. As a result, a total of 4 male classes that showed similar results on the two tests were selected and divided into two groups: one in experimental and the other in control. In addition, the top 20% students and the low 20% students were chosen for comparison of their scientific attitudes based on the results of the mid-term examination. The traditional teachings were offered to the control groups while the experimental lessons with the game activities performed at the stages of application and summary in teaching were offered to the experimental groups over 10 periods. Results of the pre- and post-test on the students' scientific attitude demonstrated that there was a statistical significance between the two groups, which suggested that the experimental group showed a meaningful improvement in the scientific attitude after experimental intervention lesson activities with game applications. Also, the more meaningful improvement in the scientific attitude was found in the lower group than in the higher group. It implies that lessons with the game activities motivated the students to voluntarily participate in school science learning by enhancing their interests. Therefore, it is suggested that game application learning be a new teaching-learning material that helps to encourage learners to actively participate in middle school science learning.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.166-166
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• 2017

모돈의 건강 상태를 정량 지수화 하기 위한 연구를 수행 중이다. 지제이상, 섭식 불량, 수면 패턴 등의 운동 특성 분석을 위하여 복수의 초음파 센서를 이용하였다. 시계열 계측 신호를 분석하여 정량 지수화를 수행하는 과정에서 주파수 도메인 분석을 시도하였다. 이 과정에서 주파수 도메인의 분해능에 따른 편차 극복을 위한 비선형 모델링을 수행하였다. 또한 인접한 시계열 데이터 구간 간의 상관성 분석이 가능하면 대용량 데이터의 실시간 처리로 인한 지연 시간 극복 및 기대되는 예후에 대한 조기 진단이 가능할 것이다. 본 연구에서는 구글에서 제공하는 Tensorflow와 NVIDIA에서 제공하는 CUDA 엔진을 동시 적용한 심층 학습 시스템을 이용하였다. 전 처리를 위하여 주파수 분해능 (2분, 3분, 5분, 7분, 11분, 13분, 17분, 19분)에 따른 데이터 집합을 1단계로 두고, 상위 10 순위 안에 드는 파워 스펙트럼 밀도의 크기를 2단계로 하여, 총 2~10개의 입력 노드를 순차적으로 선정하였고, 동일한 방식으로 인접한 시계열의 파워 스펙터럼 밀도를 순위를 변화시켜 지정하였다. 대표적인 심층학습 모델인 Softmax regression with a multilayer convolutional network를 이용하여 Recursive feature selection 경우의 수를 $8{\times}9{\times}9$로 총 648 가지 선정하고, Epoch는 10,000회로 지정하였다. Calibration 모델링의 경우 Cost function이 10% 이하인 경우 해당 경우의 학습을 중단하였으며, 모델 간 상호 교차 검증을 수행하기 위하여 $_8C_2{\times}_8C_2{\times}_8C_2$ 경우의 수에 대한 Verification test를 수행하였다. Calibration 과정 상 모든 경우에 대하여 10% 이하의 Cost function 값을 보였으나, 검증 테스트 과정에서 모든 경우에 대하여 $r^2$ < 0.5 인 결정 계수 값이 나타났다. 단적으로 심층학습 모델의 과도한 적합(Over fitting) 방식의 한계를 보인 것이라 판단할 수 있다. 적합한 Feature selection 및 심층 학습 모델에 대한 지속적이고 추가적인 고려를 통해 과도적합을 해소함과 동시에 실효적이고 활용 가능한 Classification을 위한 입, 출력 노드 단의 전후 Indexing, Quantization에 대한 고려가 필요할 것이다. 이를 통해 모돈 생체 정보 정량화를 위한 지능형 현장 진단 기술 연구를 지속할 것이다.