• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.257-264
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• 2015

In this paper, Enhanced binary block matching method for Constrained one-bit transform (C1BT) based motion estimation is proposed. Binary motion estimation exploits the Number of non-matched points (NNMP) as a block matching criterion instead of the Sum of Absolute Differences (SAD) for low complex motion estimation. The motion estimation using SAD could use the smaller block for more accurate motion estimation. In this paper the enhanced binary block matching method using smaller motion estimation block for C1BT is proposed to the more accurate binary matching. Experimental results shows that the proposed algorithm has better Peak Signal to Noise Ration (PSNR) results compared with conventional binary transform algorithms.

• Elastomers and Composites
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• v.47 no.1
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• pp.9-17
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• 2012

Herein, life time prediction based on the deterioration of physical properties of chloroprene rubber (CR)aged by heat and seawater was performed. CR samples were experienced an accelerated test at $80^{\circ}C$, $100^{\circ}C$, $120^{\circ}C$ for heat aging, and $40^{\circ}C$, $60^{\circ}C$, $80^{\circ}C$ for seawater aging for 20,000 hrs. The change in tensile strength, maximum elongation,hardness was measured. As a result, the decrease in elongation was a major factor causing failure. The life time estimated using an Arrhenius model was 125 years at $23^{\circ}C$ for thermal aging and 9 years at $23^{\circ}C$ for seawater aging. SEM and elemental analysis reveal that cracks were generated and the content of oxygen was increased for CR agined by seawater. FT-IR spectrum shows the new C-O and C = O bonds were generated by the chemical reaction with seawater. Also, the glass transtion temperature was increased and the thermal decomposition was decreased by seawater aging.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.241-244
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• 2004

전민동 성당은 얕은 팔각뿔대 형상의 지붕을 가진 팔각기둥의 형태로 재설계되었다. 팔각기둥의 형상은 마주보는 4쌍의 벽들로 인하여 공간에서 정상파가 발생하기 쉽고, 지붕 또한 둥근 형태로 음향 초점이 발생할 수 있는 등 여러가지 문제점을 가지고 있다. 이러한 형태의 전민동 성당에 대하여 여러 가지 음향 인자들을 예측하였고, 예측치와 측정치를 비교하였다. 사용된 음장해석 프로그램은 $CATT^{TM}$이고 예측 또는 측정된 음향인자는 RT, D50, C80 등이다. 건축물만의 특성과 전기음향설비가 포함된 음향특성을 비교하기 위하여, 무지향성 스피커를 이용한 측정과 성당에 장착된 전기음향장치를 이용한 측정을 수행하였다. 공연장과 마찬가지로 성당의 신도석에서도 음이 고르게 분포되는 것이 바람직하며, 신도석에서의 음압분포를 예측과 측정을 통하여 비교하여 보았다.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.5
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• pp.23-28
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• 1993

이 논문에서는 관벽온도에 따른 방전램프의 동작전압과 전류를 예측할 수 있는 수식 모델이 전개된다. 저압 수은-아르곤 가스 방전을 이용하는 형광램프가 모델로 사용된다. 저압 수은-아르곤 가스 방전에서 여기 원자와 전자의 연속방정식, 전자의 에너지 보존식, 열전도도 방정식과 이상기체 상태 방정식이 방전의 물리량을 예측하는데 이용된다. 이들 방정식과 회로 방정식을 이용하여 방전램프의 관벽온도의 효과로 인한 D.C. 저압 방전의 전기적인 특성을 예측한다. 이러한 예측은 방전램프의 설계를 하는 데 있어서 많은 도움이 되리라고 생각된다.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.296-297
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• 2011

A series of thermogravimetric analysis tests were conducted to predict the lifetime of the PTFE electrical insulation material. The prepared PTFE samples were heated from $25^{\circ}C$ to $700^{\circ}C$ at different heating rates. The kinetic energy of the PTFE was calculated from the logarithmic heating rate versus reciprocal temperature curves at constant conversion levels. Also, the lifetime of the PTFE for a given operating temperature can be predicted using the relationship between the activation energy and the estimated lifetime proposed by Toop.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.5
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• pp.832-836
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• 2013

To develop a predictive model for the shelf-life of fish cake, fish cake was stored at 30, 35, or $40^{\circ}C$ and populations of total aerobic bacteria were determined during storage. Gompertz model parameters were determined and their dependence on temperature formulated as a quadratic equation for applications toward shelf-life prediction. The predicted shelf-life values for fish cake used in this study were 6.9, 5.5, and 3.8 days at 0, 4, and $10^{\circ}C$, respectively. The shelf-life prediction equation was appropriate based on statistical analyses that reveal accuracy and bias factors. These results suggest that our prediction model is applicable for estimating the shelf-life of fish cake.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.569-575
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• 2021

Deep learning shows differences in prediction performance depending on data quality and model. This study uses various input data and multiple deep learning models to build an optimal deep learning model for predicting solar radiation, which has the most influence on power generation prediction. did. As the input data, the weather data of the Korea Meteorological Administration and the clairvoyant meteorological image were used by segmenting the image of the Korea Meteorological Agency. , comparative evaluation, and predicting solar radiation by constructing multiple deep learning models connecting the models with the best error rate in each model. As an experimental result, the RMSE of model A, which is a multiple deep learning model, was 0.0637, the RMSE of model B was 0.07062, and the RMSE of model C was 0.06052, so the error rate of model A and model C was better than that of a single model. In this study, the model that connected two or more models through experiments showed improved prediction rates and stable learning results.

• Electronics and Telecommunications Trends
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• v.9 no.2
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• pp.77-86
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• 1994

부품 고장률은 시스템 신뢰도를 계산하는데 기본이 되는 요인이다. 신뢰도 예측은 부품고장률에서 회로팩, 블록, 서브시스템 및 시스템 신뢰도 순으로 계산되는 Bottom-up 방식으로 수행되기 때문이다. 본 고에서는 부품 고장률 계산시 일반적으로 사용되고 있는 미 국방부 전자부품 신뢰도 예측방법인 MIL-HDBK-217를 이용한 Microcircuit의 부품 고장률 계산방법을 나타냈다. 또한 Microcircuit의 신뢰도를 MIL-HDBK-217 예측방법 및 예측결과와 외국 예측방법 및 예측결과로 비교하여 나타냈다.

• Journal of Aerospace System Engineering
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• v.13 no.6
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• pp.17-25
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• 2019

PHM (Prognostics and Health Management) of aircraft engines is applied to predict the remaining useful life before failure or the lifetime limit. There are two methods to establish a predictive model for this: The physics-based method and the data-driven method. The physics-based method is more accurate and requires less data, but its application is limited because there are few models available. In this study, the data-driven method is applied, in which a multi-layer perceptron based neural network algorithms is applied for the life prediction. The neural network is trained using the data sets virtually made by the C-MAPSS code developed by NASA. After training the model, it is applied to the test data sets, in which the confidence interval of the remaining useful life is predicted and validated by the actual value. The performance of proposed method is compared with previous studies, and the favorable accuracy is found.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.489-490
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• 2008

본 고에서는 체내 심실신호를 농하여 신경학적 분석 및 다형성의 측면에서 심실세동이 일어나는 것을 예측하는 분석 알고리즘을 설계하였다. 신경학적 측면에서는 시계열 신호의 Peak to Peak Interval을 예측법과 0.15Hz를 기준으로 HRV 신호의 AR Burg 모델링을 통하여 고주파성과 저주파성을 나누어 교감신경과 부교감신경의 활동성 통한 신경학적 예측법을 제시하였으며 또한 체내 심실신호의 비선형적 특성을 고려한 Fractal Dimension을 생성시킴으로서 주기성의 특성과 다형성 통한 예측법을 제시하였다. 체내 심전도를 기반으로 Simulation 하였으며 각 분석별 조합을 통하여 최적의 예측 구조를 찾고자 하였다. 의학적 의미가 있는 민감도와 특이도를 판별하였으며 예측을 위한 수행시간을 실험하였다. 이를 통하여 자율신경 활성도와 다형성 판별을 조합한 방법이 심실세동 예측을 위한 민감도의 측면에서 가장 우수함을 나타내었고 시뮬레이션을 위만 시뮬레이터(Simulator) UI(User Interface)를 제시하였다.