• IE interfaces
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• v.15 no.4
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• pp.374-381
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• 2002

In this paper, we design and implement a real-time route guidance system(RGS) in large-scale networks. Coupled with the well-known mathematical routing algorithms, we devise an RGS for knowledge aquisition and self-learning ability within the framework of the expert system. Through off-line construction of database, on-line treatment of unexpected traffic accidents, etc., the developed RGS can provide drivers with good quality real-time routing information. The practical effectiveness of the proposed system is demonstrated in terms of response time and route appropriateness.

• Journal of Nutrition and Health
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• v.19 no.6
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• pp.402-408
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• 1986

Since diet is an essential component of the treatment for diabetic mellitus, a progressive educational plan was designed to educate diabetic children for the proper selection of their foods. Seven suspicious children were chosen according to the previous oral glucose tolerance test and present blood glucose levels (fasting and postprandial 2 hours). The education program includes the basic nutrition study, learning of the five basic food groups. familiarization with the food exchange lists. calorie calculation and menu planning, and follow-up evaluation by checking every day -food intake. The duration of the education was five weeks. The levels of fasting blood glucose and postprandial -2 hours blood sugar of the seven children were significantly reduced after the 5-weeks education:FBS:from 92-125mg% to 67-80mg%, pp-2hours BS: from 130-169mg% to 69-90mg%. The children have felt much better with profound self-confidence after to program . Their oral glucose tolerance test levels were also significantly decreased after the 5-weeks education in comparison with those of one year ago.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.182-186
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• 2017

Maintaining a proper lookout activity routine is integral to preventing ship collision accidents caused by human errors. Various subjective measures such as interviewing, self-report diaries, and questionnaires have been widely used to monitor the lookout activity patterns of navigators. An objective measurement of a lookout activity pattern classification system is required to improve lookout performance evaluation in a real navigation setting. The purpose of this study was to develop an objective navigator lookout activity classification system using wearable accelerometers. In the training session, 90.4% accuracy was achieved in classifying five fundamental lookout activities. The developed model was then applied to predict real-lookout activity in the second session during an actual ship voyage. 86.9% agreement was attained between the directly observed activity and predicted activity. Based on these promising results, the proposed unobstructed wearable system is expected to objectively evaluate navigator lookout patterns to provide a better understanding of lookout performance.

• Proceedings of the KAIS Fall Conference
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• 2010.11a
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• pp.341-343
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• 2010

The parameters of PID controller should be readjusted whenever system character change. In spite of a rapid development of control theory, this work needs much time and effort of expert. In this paper, to resolve this defect, after the sample of parameters in the changeable limits of system character is obtained, these parametrs are used as desired values of back propagation learning algorithm, also neural network auto tuner for PID controller is proposed by determing the optimum structure of neural network. Simulation results demonstrate that auto-tuning proper to system character can work well.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.423-432
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• 2002

Web Based electronic texts are studied on the statistics education fields. In this paper, we discuss the current problems encountered by many statistics electronic texts. We also suggest a new design concept for the Web Based interactive material. In addition, we presented several examples to demonstrate.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1910-1914
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• 2015

Human posture recognition is an attractive and challenging topic in computer vision due to its promising applications in the areas of personal health care, environmental awareness, human-computer-interaction and surveillance systems. Human posture recognition in video sequences consists of two stages: the first stage is training and evaluation and the second is deployment. In the first stage, the system is trained and evaluated using datasets of human postures to ‘teach’ the system to classify human postures for any future inputs. When the training and evaluation process is deemed satisfactory as measured by recognition rates, the trained system is then deployed to recognize human postures in any input video sequence. Different classifiers were used in the training such as Multilayer Perceptron Feedforward Neural networks, Self-Organizing Maps, Fuzzy C Means and K Means. Results show that supervised learning classifiers tend to perform better than unsupervised classifiers for the case of human posture recognition.

• Korean Journal of Human Ecology
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• v.12 no.1
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• pp.63-73
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• 2003

The purpose of this study was to quantify the hands of fabrics for the Korean folk clothes using both a KES-FB and an artificial neural network. In order to select the proper input parameters, we calculated the correlation using step-wise regression between mechanical properties and the hand value of fabrics. For the classification, the primary hand values and total hand value, five neural networks with three-layered structure were constructed using the error back propagation algorithm and, in order to reduce errors and to speed up learning, the momentum method was selected. From the analysis of the primary and total hands using a self-constructed artificial intelligence system, the error rates of sleekness, stiffness, silkiness, and roughness compared with the judgement of expert panels were found to be 3.3%, 3.3%, 1.6%, and 4.9%, respectively, while that of the total hand was 9.83%.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.149-154
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• 2002

운송 컨테이너의 식별자를 추출하고 인식하는 것은 컨테이너 식별자들의 크기나 위치가 정형화되어 있지 않고 외부의 잡음으로 인하여 식별자의 형태가 훼손되어 있기 때문에 어렵다. 본 논문에서는 이러한 특성을 고려하여 컨테이너 영상에 대해 Canny 에지 추출 기법을 이용하여 컨테이너의 식별자 영역을 추출하고 추출된 컨테이너 식별자 영역에서 히스토그램 방법과 윤곽선 추적 알고리즘을 결합하여 개별 식별자를 추출한다. 추출된 컨테이너 개별 식별자 인식은 ART1을 수정하여 지도 학습 방법과 결합한 개선된 자가생성 지도학습 알고리즘을 제안하여 적용한다. 실험결과에서는 제안된 컨테이너 식별자 추출 및 인식 방법이 다양한 컨테이너 영상에 대해 효율적인 것을 보인다.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.764-770
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• 2001

본 연구는 초등학생들에게 능동성과 책임감을 바탕으로 하여 자기주도적으로 과제를 해결할 수 있도록 도와줄 수 있는 웹 학습실을 설계하고 개발한다. 이를 위하여 먼저 학생들이 자기주도적으로 학습을 해 나갈 수 있도록 학년별, 단원별, 차시별로 구성된 사회과 학습실이라는 웹 환경을 마련하였다. 두 번째로 학생들이 스스로 학습 과제를 선정하고, 다양한 도서와 멀티 자료, 기타 관련 웹 사이트 등 과제 해결에 필요로 하는 자료와 정보를 검색하여 자신이 설정한 과제를 해결해 나가는 일련의 과정을 실시할 수 있는 과제 학습실이라는 웹 환경을 마련하였다. 이러한 사회과 웹 학습실 운영을 통하여 얻어지는 효과는 초등학생들의 컴퓨터 활용 능력을 향상시키고, 학습에 대한 흥미도와 참여도를 높이며, 게시판이나 대화방을 통해 과제를 선정하고, 역할분담, 자료 수집, 분류해 나가는 과정에서 학습활동에 대한 책임의식과 학습에 대한 자기주도성 신장에 기여할 것으로 기대된다.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.846-849
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• 2010

본 연구는 2010년 2월부터 2010년 7월까지 B. 뇌 훈련 센터에 자기주도학습 능력 향상을 위하여 방문한 내담자 60명(실험군 30명, 대조군 30명)의 뇌파를 검사하여 뉴로피드백 훈련 전과 훈련 후의 뇌기능과 자기주도학습 능력 변화를 보고자 하였다. 자기주도학습 능력에 영향을 미치는 특정한 뇌 기능의 훈련 전과 후의 결과를 시계열 선형분석으로 비교하였다. 연구의 결과로는 자기조절지수, 훈련모드, 자기주도학습 능력에서 집단 간에 유의미한 차이가 나타났다. 이는 뉴로피드백의 기술을 적용한 뇌 훈련은 자기조절지수와 자기주도학습 능력에 긍정적인 영향을 미친다고 볼 수 있겠다.