• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.382-387
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• 1998

The adaptive hysteresis band current control method using neural network is proposed to hold the switching frequency of PWM inverter constant at any operating points of ac motor. The adaptive hysteresis band equation is derived as the teaching signal of neural network. and then the structure and learning algorithm of the neural network a are suggested. The simulation results show that the switching frequency of PWM inverter is held constant at any operating conditions of ac motor and the proposed method has good transient performance of stator current.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.315-327
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• 2017

This study was carried out to examine the converging factors related to academic burnout in students from health-related majors who are involved in studying for the Test of English for International Communication (TOEIC). Research subjects included 291 randomly selected students from the J-region, who were enrolled in TOEIC classes. Data collection took place from April 3, 2017 to April 14, 2017, using anonymous self-administered questionnaires. The results of a multiple regression analysis in female students showed higher academic burnout pertaining to studying for the TOEIC when sleeping hours, self-worth, self-efficacy, school adaptation resilience, and study immersion were low, and job-seeking stress and test anxiety were high. The explanatory power of this model was 65%. Based on these results, to reduce academic burnout pertaining to studying for the TOEIC in health majors, it is first necessary to increase sleeping hours, self-worth, self-efficacy, school adaptation resilience, and study immersion, and to make efforts to manage self-competence, job-seeking stress, and test anxiety. The results of this study may be used to decrease the academic burnout caused by studying for the TOEIC in health major students and to increase their aptitude for studying English, to cultivate globalized capabilities. Future studies need to conduct an effect analysis on the control and mediation effect that these factors have on academic burnout.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2001.11a
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• pp.43-47
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• 2001

본 논문은 신경망 이론중 하나인 Adaptive Resonance Theory(ART)을 사용하여 네트워크 상의 불법적인 침입을 탐지하는 기법에 대한 연구이다. ART는 비교사 학습을 하는 신경망으로써, 적응적인 학습능력이 있으며, 또 새로운 패턴에 대해서 새로운 클러스터를 생산하는 능력이 있다. ART의 이러한 특성을 이용하여, 여러 가지 침입패턴을 네트워크상에서 생산하여 학습을 시키고, 또 test 했으며, test 이후에도 on-line 상에서 새로운 공격 pattern도 찾아냄을 보였다. 따라서, 이미 알려진 침입뿐만 아니라 새롭게 발생하는 침입 기법에 대해서도 새로운 rule의 첨가 없이 적극적으로 대처할 수 있을 것으로 예측된다.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.413-425
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• 2019

This study was conducted to identify factors affecting depression in junior nursing students(JNS). The number of the participants was 144 at a college in S and G city. The data were collected using questionnaires about somatic symptoms(SS), sleep quality, stress, adaptation to college life(AC), depression. Mean score of depression was 18.89, 58.3% are experiencing depression that requires clinical treatment. The significant predictors of JNS were levels of depression AC(β=-.503, p=.000) and SS(β=.263, p=.000) respectively, explaining 58.9% of variance. In order to control the depressive symptoms of JNS, it is necessary to diagnose basic learning ability from the beginning of admission and provide guidance management plans to help students adapt to academic activities by providing customized programs for each level to improve learning ability. It is necessary to develop and apply various intervention programs to alleviate physical symptoms such as fatigue/low energy experienced by JNS.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.31-39
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• 2008

Until now, there are many technologies to improve studying ability using e-learning system. In most of e-learning system, learners are studying through the lecture materials and studying problems. The studying ability and intention, however, can be improved through the shared materials and discussion. In this case, learning materials are shared by the learners' discussion and shared materials through the board Internet and MSN. Such data was not classified by learners; it was not easy for the learners to search related valuable information. Therefore, it was not helping to learning. The technologies of most text mining extract summary data from the collection of document or classify into similar document from the complex document. In this paper, we implemented e-learning system for learners to improve learning abilities and especially, applied text mining technology to classify learning material for helping learners.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.31-34
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• 1998

본 연구는 음소 단위의 CHMM을 이용한 연속어 숫자음 인식에 관한 내용이다. ETRI 445 데이터를 사용하여 초기의 모델은 ML 추정법을 이용하여 작성하였고 적응화를 위해 최대 사후 확률 추정법을 사용하였다. 또한 한국어 숫자음 음성의 음향학적 특성을 고려하여 발성 사전을 작성하였고 음절 다누이로 되어있는 한국어 숫자음의 모든 경우를 고려하여 복수개의 단어를 사전에 등록하였다. 또한 적응화 학습에 있어서 숫자음의 앞 뒤 모든 경우를 고려하여 작성한 21 종류의 7자리 전화번호 숫자음 DB로 사용하였고 이의 효율성을 입증하기 위하여 ETRI에서 작성한 35종류의 4연속 숫자음 목록을 대상으로 인식실험을 수행하였다. 그 결과 5인의 화자에 대하여 4연속 숫자음에 대하여 96%의 인식률을 보이고 있으며 7연속 숫자음에 대하여도 약 91%의 결과를 보여주고 있다. 또한 후처리를 두어 연음 현상으로 인한 오인식의 경우에 대해서도 약 2%의 인식률의 증가를 보여주었다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.297-300
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• 2006

본 논문에서는 비선형 기동표적의 추적에 대한 새로운 접근 방식을 소개한다. 이 논문에서는 표적의 가속도를 시변 변수인 표적의 추가적인 잡음으로 두고 각각의 가속도 간격의 정도에 따라 얻어지는 모든 잡음에 대한 변수에 의해 각각의 하부 모델들을 특성화시켰다. 표적의 기동중에 나타나는 가속도를 효과적으로 다루기 위하여, 잡음의 크기가 급격히 증가할 경우 증가분을 가속도로 인식하여 기동표적 관계식에 이용하였다. 또한 모르는 가속도에 따른 시변 변수를 적응적으로 어립잡기는 어렵기 때문에 정밀한 계산을 위하여 퍼지 뉴럴 네트워크와 적응 상호작용 다중모델 기법을 이용하였다. 퍼지 뉴럴 네트워크의 동정을 위해서는 오차 역전파 학습법을 사용하였다. 그리고 제안된 알고리즘의 수행 가능성을 보여주기 위하여 몇 가지 예를 제시하였다.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.625-641
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• 2015

Recent research shows that emotion is closely related to memory and learning. Although a growing number of educators have high interest in affective aspects of learning processes and outcomes, there are few studies to investigate systematically instructional strategies and learning environments based on learners' emotion. Despite the efforts to understand the role of emotion and to facilitate positive emotion for meaningful learning in face-to-face and online environments, it is still a challenging issue to measure emotion in a valid and reliable way. To implement emotion-based education, it is essential to overcome the limitation of self-report surveys on emotion, which rely on the memory of learners. The current study surveyed emotion measurement tools, which are recently developed in education and other domains, in terms of self-report, neurophysiology, and behavioral responses. This study also discussed how emotion measurement tools can be used in authentic learning and teaching situations. Particularly, this study focused on cutting-edge technologies that would enable educators to collect and analyze learners' emotion easily in real-world contexts. This study will contribute to the research about the role of emotion in education and the design of adaptive learning environments that consider the change of learners' emotion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.289-292
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• 2005

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But it is difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose an adaptive PID controller based on a gradient descent learning. This algorithm has a simple structure like conventional PID controller and robustness to system parameters variation. To verify performances of the proposed adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.149-154
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• 2006

In this paper, for auto temperature-controlled, we developed a system that an adaptive fuzzy controller using fuzzy control rule base, fuzzy variable and fuzzy inference can get same results as an expert of temperature -controlled gas furnace system by experience and obtained a good result by experiment. It's results showed that temperature error is less than ${\pm}2^{\circ}C$ and widely used in the area of industrial fields. For measurement of error rate of sintered ceramic products between the manual system and the proposed system, we tested two times sample A and B respectively. We verified the improvement of error rate was mean 50.5% and 48.4% for each sample A and B. Through the experiments, we confirmed that it has very superior performance compared with the conventional gas furnace system by manual.