• Journal of Power Electronics
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• v.3 no.1
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• pp.10-16
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• 2003

Implementation and experimental verification of a simple neuro-controller (SNC) as a speed controller for a brush less DC (BLDC) motor is presented. The SNC with one weight and a linear hard limit activation function is trained on-line using the back propagation algorithm. A modified error function is used to ensure good performance during the on-line training, which has been used without previous off-line training. The SNC has been implemented using a computer-interface card mounted on a PC. The driving system performance has been investigated by a number of experimental tests for a variety of input reference speed trajectories.

• Journal of Power Electronics
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• v.11 no.6
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• pp.922-930
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• 2011

In this paper, two radial basis function neural networks (RBFNNs) are used to dynamically identify harmonics content in converter waveforms based on the p-q (real power-imaginary power) theory. The converter waveforms are analyzed and the types of harmonic content are identified over a wide operating range. Constant power and sinusoidal current compensation strategies are investigated in this paper. The RBFNN filtering training algorithm is based on a systematic and computationally efficient training method called the hybrid learning method. In this new methodology, the RBFNN is combined with the p-q theory to extract the harmonics content in converter waveforms. The small size and the robustness of the resulting network models reflect the effectiveness of the algorithm. The analysis is verified using MATLAB simulations.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.62-62
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• 2017

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.119-122
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• 2012

오늘날 콜센터는 고객과 의사소통을 담당하는 비대면 접촉채널의 대표적인 조직으로 고객 접촉을 담당하는 인적자원에 대한 중요성이 날로 증대되고 있다. 이에 콜센터들은 고객응대에 적합한 지식 기술 태도 등 상담사의 전문성 강화를 위해 교육훈련을 꾸준히 계획하며 실행하고 있다. 본 연구는 콜센터에서 실시하는 다양한 교육훈련이 상담사들의 직무몰입과 어떠한 관계가 있는지를 알아보려는데 그 목적이 있다. 이를 분석하기 위하여 교육훈련에 대한 만족도, 성취도, 적용도, 기여도를 중심으로 직무몰입과의 관계를 회귀분석을 통해 살펴보았다. 분석결과는 다음과 같다. 교육훈련 만족도와 적용도는 직무몰입과 직접적인 유의미한 영향관계가 나타나지 않았다. 반면에 성취도와 기여도는 직무몰입에 유의미한 정(+)의 영향을 미치는 것으로 나타났다. 이러한 결과는 교육훈련과정에서 교육내용의 가치와 재미를 찾아 잘 이해하고 습득할 수 있도록 하여 성취도를 높여주고, 교육훈련을 통한 조직생활에 대한 기여도에 대한 인식을 높여줄 때 직무몰입이 높게 나타남을 시사한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.83-86
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• 2012

본 논문에서는 야간에 보행자인식의 성능 향상을 위한 효율적인 인식 방법을 제안한다. 이 논문은 야간에 차량에 비치 된 Thermal Camera를 이용하여 적외선 영상을 얻은 후, 적응적 thresholding, Histogram Equalization, Morphology Operation, Labelling, HOG및 SVM Training 방법을 사용하여 보행자의 인식율을 높이도록 하였다. 3830개의 training 영상을 사용하였으며 실험결과 우수한 인식 결과를 얻었다.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.787-789
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• 1996

This paper describes a Transient Stability Education & Training Software that can make the students or beginners easily be familiar with power system stability problems. The Major objective of this study is to provide, for educational purpose, an interactive computer graphic tool that can facilitate power system study in highly user-friendly environment. The proposed software is designed to have the particular features such as follow : simulation with animation of the rotor, useful interactive scheme, various graphic illustrations related to critical factors of the stability, trace function including revival simulation with different processing speed. With these features, the software could be suitable for educational and training of students/beginners in power system stability engineering field.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1146-1151
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• 2018

Recently, researches on the intelligence of electric power facilities have been trying to apply artificial intelligence techniques as computer platforms have improved. In particular, faults occurring in substation should be able to quickly identify possible faults and minimize power fault recovery time. This paper presents fault location technique for 154kV substation using neural network. We constructed a training matrix based on the operating conditions of the circuit breaker and IED to identify the fault location of each component of the target 154kV substation, such as line, bus, and transformer. After performing the training to identify the fault location by the neural network using Weka software, the performance of fault location discrimination of the designed neural network was confirmed.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.8-13
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• 2019

Visual place recognition is widely researched area in robotics, as it is one of the elemental requirements for autonomous navigation, simultaneous localization and mapping for mobile robots. However, place recognition in changing environment is a challenging problem since a same place look different according to the time, weather, and seasons. This paper presents a feature extraction method using a deep convolutional auto-encoder to recognize places under severe appearance changes. Given database and query image sequences from different environments, the convolutional auto-encoder is trained to predict the images of the desired environment. The training process is performed by minimizing the loss function between the predicted image and the desired image. After finishing the training process, the encoding part of the structure transforms an input image to a low dimensional latent representation, and it can be used as a condition-invariant feature for recognizing places in changing environment. Experiments were conducted to prove the effective of the proposed method, and the results showed that our method outperformed than existing methods.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.14-20
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• 2021

The method of analysis and research is applied in the work methods of managing student activities. Effective forms and methods of student quality management are determined. The model of management of educational process of students is offered. The model is to activate the student's potential, while maintaining the classical educational paradigm. The analysis of features of management of activity of students in modern model of education is carried out.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.140-144
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• 2021

The article considers aspects of improving the quality of training of specialists based on the use of modern information and communication technologies in the educational process; the use of teaching methods and, as a result, an increase in the creative and intellectual components of educational activities; integration of various types of educational activities (educational, research, etc.); adaptation of information technology training to individual the characteristics of the student; ensuring continuity and consistency in learning; development of information technologies for distance learning; improving the software and methodological support of educational process.