• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.1-8
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• 2006

Many researchers have been studied for the automatic chromosome karyotype classification and analysis. For the automatic classify the each chromosome which is the image in microscope, it is necessary to process the sub-procedure, ie. image pre-processing, implementing karyotype classifier. The image pre-processing proceeded the each chromosome separation, the noise exception and the feature parameter extraction. The extracted morphological feature parameter were the centromeric index(C.I.), the relative length ratio(R.L.), and the relative area ratio(R.A.). In this paper, the fuzzy classifier was implemented for the human chromosome karyotype classification. The extracted morphological feature parameter were used in the input parameter of fuzzy classifier. We studied about the selection of the membership function for the optimal fuzzy classifier in each chromosome groups.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1391-1396
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• 2012

It is introduced an approach to model for numerical analysis of a sound absorbing material that has different absorbing coefficient according to frequency. For modeling of a sound absorbing material, we tried to model by a traditional modeling method. But it had large differences on frequency domain, especially a capacitance component due to increasing of frequency. We approach to model a sound absorbing material by the Debye polarization technique with non-linear least square method. At first, we estimated parameters form a polyurethane with thickness 25 mm, then we could model a polyurethane with thickness 50 mm using same parameters. Therefor, we could find that the Debye polarization is an useful way to model sound absorbing materials.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.8
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• pp.813-821
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• 2015

In this paper, we analyzed the problems of a batch-type sterilizer and design a continuous sterilizer to control the temperature deviation. The temperature deviation is analyzed with respect to design parameters such as a nozzle diameter, hole diameter, and nozzle length. The significant temperature parameters are optimized using the response surface methodology. An experimental apparatus is developed using the optimized design parameters. Using a field test, we show that the target temperature is obtained in about 7.3 minutes and the temperature deviation is improved about $0.84^{\circ}C$. The optimized parameters from the test are equal to the analytical parameters.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.17-29
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• 2008

A volume-delay function(VDF) has been used to describe the relation between traffic volumes and delay experienced by travelers on the roads traveling from origin to destination, which has been usually adopted in traffic assignment. For the purpose of more precise description of traffic pattern, we have to estimate the parameters of VDF in advance. This paper presents a methodology for estimating the parameters, which combined with golden section method. By using the method we have estimated the parameters with real data based on KTDB(2006), and validated them. Compared to the existing values of the parameters, newly estimated values are found to be closer to real world.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.4
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• pp.15-23
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• 2011

An interleaver rearranges a channel-encoded data in the symbol unit to spread burst errors occurred in channels into random errors. Thus, the interleaving process makes it difficult for a receiver, who does not have information of the interleaver parameters used in the transmitter, to de-interleave an unknown interleaved signal. Recently, various researches on the reconstruction of an unknown interleaved signal have been studied in many places of literature by estimating the interleaver parameters. They, however, have been mainly focused on the estimation of the block interleaver parameters required to reconstruct the de-interleaver. In this paper, as an extension of the previous researches, we estimate the convolutional interleaver parameters, e.g., the number of shift registers, a shift register depth, and a codeword length, required to de-interleave the unknown data stream, and propose the de-interleaving procedure by reconstructing the de-interleaver.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1542-1550
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• 2019

Legacy studies for classifying arrhythmia have been studied to improve the accuracy of classification, Neural Network, Fuzzy, etc. Deep learning is most frequently used for arrhythmia classification using error backpropagation algorithm by solving the limit of hidden layer number, which is a problem of neural network. In order to apply a deep learning model to an ECG signal, it is necessary to select an optimal model and parameters. In this paper, we propose optimal parameter extraction method based on a deep learning. For this purpose, R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval segment is modelled. And then, the weights were learned by supervised learning method through deep learning and the model was evaluated by the verification data. The detection and classification rate of R wave and PVC is evaluated through MIT-BIH arrhythmia database. The performance results indicate the average of 99.77% in R wave detection and 97.84% in PVC classification.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.31-38
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• 2024

This study proposes hyper-parameter settings for developing a generative AI-based learning support tool to facilitate programming education in online distance learning. We implemented an experimental tool that can set research hyper-parameters according to three different learning contexts, and evaluated the quality of responses from the generative AI using the tool. The experiment with the default hyper-parameter settings of the generative AI was used as the control group, and the experiment with the research hyper-parameters was used as the experimental group. The experiment results showed no significant difference between the two groups in the "Learning Support" context. However, in other two contexts ("Code Generation" and "Comment Generation"), it showed the average evaluation scores of the experimental group were found to be 11.6% points and 23% points higher than those of the control group respectively. Lastly, this study also observed that when the expected influence of response on learning motivation was presented in the 'system content', responses containing emotional support considering learning emotions were generated.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.757-759
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• 2004

본 연구에서는 초음파 영상에서 간실질의 에코 명도를 비롯한 픽셀 정보분포를 분석하여 정량화 지방간 진단 파라미터를 구하기 위해 규준화 에코 명도 값 및 다수의 텍스쳐 파라미터 값을 추출하여 선형결합을 통해 지방간의 진행 정도와의 상관성을 연구하였다. 임상 지방간 지수와 본 연구의 추정 지방간 지표 값과의 선형 상관계수를 구하였다 신장대조 방법으로 추출한 규준화 에코 명도 및 회색도 픽셀분포의 텍스쳐 특성 파라미터를 계산하여 임상결과와 비교한 결과 임상 지방간 지수와 높은 상관성을 보임을 알 수 있었고, 지방간 진단의 보조사료로 유용함을 확인하였다. 계산된 지방간 지수와 임상결과 간의 선형상관계수는 0.84-0.93이다.

• Journal of the Korean Geotechnical Society
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• v.17 no.4
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• pp.279-288
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• 2001

암반내에 존재하는 불연속면은 지하구조물의 안정성에 큰 영향을 미친다. 불연속면을 해석하기 위한 구성법칙에 대한 많은 연구가 진행되어 왔으나, 객관적인 거칠기 파라미터를 이용한 전단거동 모사에 관한 연구는 아직 미흡한 실정이다. 본 연구에서는 정량적인 거칠기 파라미터를 이용한 두 가지의 새로운 구성방정식을 만들어 절리 거동을 모사하였다. 첫 번째 구성법칙은 탄소성 이론에 근거하여 두께가 없는 개별절리요소 이용한 방법이고, 두 번째 구성법칙은 3차원 레이저 변위 측정 데이터를 직접 이용하여 Ohnishi가 제안한 거칠기 손상모델을 도입하였다. 제안된 두 모델을 가지고 직접 전단시험을 모사해본 결과 실제 실험에 나타나는 변형률 경화 및 연화현상 그리고 잔류전단강도와 같은 현상을 볼 수 있었다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.439-440
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• 2014

본 논문에서는 기업의 기존 특허 포트폴리오를 비즈니스 모델 컴포넌트의 관점에서 사업타당성 평가를 수행할 수 있는 연구개발 비즈니스 모델링 및 시뮬레이션 시스템을 제안한다. 제안 시스템은 기업이 보유하고 있는 기존 특허들의 기술적 가치를 평가하는 것이 아니라, 비즈니스 모델의 9가지 컴포넌트 관점에서 특허가 보유하고 있는 비즈니스적 특징을 분석할 수 있는 시스템이다. 평가 모델은 4가지 세부 평가모델로 구성하였으며, 시뮬레이션을 수행할 수 있는 기본 파라미터와 제어 파라미터를 제공하여서 파라미터들의 값을 조정하면서 다양한 환경에서의 평가 결과값을 실시간으로 확인할 수 있도록 구현하였다.