• 음성과학
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• 제9권3호
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• pp.113-120
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• 2002

The purpose of this study was to determine the effects of group therapy on the language performance of aphasic patients. Four aphasic subjects participated in group therapy. Their aphasic types were TCMA (transcortical motor aphasia), conduction, anomie, and Broca's aphasia. The focus of the therapy was to stimulate cooperative learning skills. For this purpose, categorization tasks, semantic association tasks, convergent thinking, and divergent thinking tasks were employed. The results showed that all of the aphasic subjects demonstrated some improvement in writing ability, categorization ability, and speaking ability in sentences.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 하계종합학술대회 논문집
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• pp.486-490
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• 1989

In this paper, a program controlling an auto-audio media - cassette deck - by a 16 bit personal computer is studied in order to execute audio and visual learning in CAI. The results of this study are as follows. 1. Audio and visual learning is executed efficiently in CAI. 2. Access rate of voice information to text/image information is about 98% and 60% in "play" and "fast forward" respectively. 3. In "fast forward", quality of a cassette tape affects voice information access rate in propotion to motor driving speed. 4. Synchronizing signal may be mistaken by defects of tape itself.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제48권6호
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• pp.294-300
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• 1999

There is a growing interest in hybrid electric vehicles due to environmental concerns. Recent efforts are directed toward developing an improved main component systems for the hybrid electric vehicle applications. Soon after the introduction of electric starter for internal combustion engine early this century, despite being energy efficient and nonpolluting, electric vehicle lost the battle completly to internal combustion engine due to its limited range and inferior performance. Hybrid Electric vehicles offer the most promising solutions to reduce the emission of vehicles. This paper describes a method for cost reduction estimation of parallel hybrid electric vehicle. We used a cost reduction structure that consisted of five major subsystems (three-type and two-type motor) for parallel hybrid electric vehicle. Especially, we estimated the potential for cost reductions in parallel hybrid electric vehicle as a function of time using the learning curve. Also, we estimated the potentials of cost by depreciation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.229-229
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• 2000

Conventional gain-tuning methods such as Ziegler-Nickels methods, have many disadvantages that optimal control ler gain should be tuned manually. In this paper, modified PID controllers which include self-tuning characteristics are proposed. Proposed controllers automatically tune the PID gains in on-1ine using neural networks. A new learning scheme was proposed for improving learning speed in neural networks and satisfying the real time condition. In this paper, using a nonlinear mapping capability of neural networks, we derive a tuning method of PID controller based on a Back propagation(BP)method of multilayered neural networks. Simulated and experimental results show that the proposed method can give the appropriate parameters of PID controller when it is implemented to DC Motor.

• 한국항해학회지
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• 제22권2호
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• pp.47-52
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• 1998

Recently , there have been considerable researches about the fusion of fuzzy logic and neural networks. The propose of thise researches is to combine the advantages of both. After the function of approximation using GMDP (Generalized Multi-Denderite Product)neural network for defuzzification operation of fuzzy controller, a new fuzzy-neural network is proposed. Fuzzy membership function of the proposed fuzzy-neural network can be adjusted by learning in order to be adaptive to the variations of a parameter or the external environment. To show the applicability of the proposed fuzzy-nerual network, the proposed model is applied to a speed control o fDC sevo motor. By the hardware implementation, we obtained the desriable results.

• 산업경영시스템학회지
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• 제17권30호
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• pp.25-34
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• 1994

Mental workload has a improtant place in modern work environment such as human-computer interaction. Designing man-machine system requires knowledge and evaluation of the human cognitive process which controls information flow during our works. Many studies estimate reaction time as a index of menatal workload. This paper investigates what reflacts the workload of human information handling when the informations grow its degree. Experiment result introuce the memory time that explain the information-load more sensitive than react time. And react time shows learning effect but memory time does'nt show that effect So it can be concluded that cognitive learning or work schema needs more time to achieve dexterity than motor skill.

• Journal of Power Electronics
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• 제10권6호
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• pp.635-642
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• 2010

The paper presents a multimedia educational program of DC servo drives for distant learning with a special emphasis on sliding mode control. The program contains of three parts: animation, simulation and internet based measurement. The animation program explains the operation of DC motors, gives its time- and frequency-domain equations, transfer functions and the theoretical background necessary for controller design for DC servo motors. The simulation model of the DC servo motor and the controller can be designed by the students based on the animation program. The students can also test their controllers through the internet based measurement, which is the most important part from engineering point of view. After the measurements are executed, the students can download the measured data and compare them to the simulation results.

• International Journal of Internet, Broadcasting and Communication
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• 제11권2호
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• pp.11-18
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• 2019

One of the key objectives of control systems is to maintain a system in a specific stable state. To achieve this goal, a variety of control techniques can be used and it is often uses a feedback control method. As known this kind of control methods requires mathematical model of the system. This article presents seesaw unstable system with two propellers which are controlled without use of a mathematical model instead. The goal was to control it using training data. For system control we use a logistic regression technique which is one of machine learning method. We tested our controller on the real model created in our laboratory and the experimental results show that instability of the seesaw system can be fixed at a given angle using the decision boundary estimated from the classification method. The results show that this control method for structural equilibrium can be used with relatively more accuracy of the decision boundary.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2019년도 제31회 한글 및 한국어 정보처리 학술대회
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• pp.236-238
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• 2019

신경망 기계 번역(Neural Machine Translation)은 주로 지도 학습(Supervised learning)을 이용한 End-to-end 방식의 연구가 이루어지고 있다. 그러나 지도 학습 방법은 데이터가 부족한 경우에는 낮은 성능을 보이기 때문에 BERT와 같은 대량의 단일 언어 데이터로 사전학습(Pre-training)을 한 후에 미세조정(Finetuning)을 하는 Transfer learning 방법이 자연어 처리 분야에서 주로 연구되고 있다. 최근에 발표된 MASS 모델은 언어 생성 작업을 위한 사전학습 방법을 통해 기계 번역과 문서 요약에서 높은 성능을 보였다. 본 논문에서는 영어-한국어 기계 번역 성능 향상을 위해 MASS 모델을 신경망 기계 번역에 적용하였다. 실험 결과 MASS 모델을 이용한 영어-한국어 기계 번역 모델의 성능이 기존 모델들보다 좋은 성능을 보였다.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제8권1호
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• pp.101-112
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• 1997

본 연구의 목적은 학습 장애를 진단하는데 있어 성취도 검사인 기초학습기능검사의 유용성을 살펴보는 것이다. 학습 장애 집단은 두 유형으로 나누어 언어적 학습 장애 집단(VLD：Verbal Learning Disorder) 34명, 비언어적 학습 장애 집단(NVLD：Nonverbal Learning Disorder) 14명으로 총 48명으로 구성되었으며, 비교 집단으로는 Dysthymia 집단 11명, 정상아 20명을 대상으로 지능 검사 및 기초학습 기능검사의 수행을 비교하였다. 지능 검사에서 VLD집단은 어휘력 및 언어를 통한 학습 과제, 언어-청각적인 주의과제에서 의미있는 저하를 나타내었고, NVLD 집단은 시-지각의 정확도, 정신-운동성 기능의 협응 속도, 시각-공각적인 조직력 등 동작성 기능 전반에 걸쳐 비효율성을 나타내었다. 기초학습기능검사에서는 VLD 집단은 음운 부호화과제, 셈하기 능력, 단어 재인 과제에서 의미있는 저하를 나타내었다. 또한 지능 검사의 소검사들에 기초학습기능검사의 소검사들을 포함하여 판별 분석을 한 결과, 기초학습기능검사를 포함시키지 않은 경우보다 판별율이 높아졌을 뿐 아니라, VLD집단을 유의미하게 판별해 주는 판별 함수를 도출하였다. 각 소검사들의 속성을 분석하기 위하여 요인 분석을 실시하였으며 이를 통하여 소검사들을 유목화하였으며 마지막으로 현 논문의 제한점 및 기초학습기능검사의 제한점을 논의하였다.