• Analytical Science and Technology
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• v.28 no.3
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• pp.187-195
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• 2015

The heat of sublimation (HOS) is an essential parameter used to resolve environmental problems in the transfer of organic contaminants to the atmosphere and to assess the risk of toxic chemicals. The experimental measurement of the heat of sublimation is time-consuming, expensive, and complicated. In this study, quantitative structural property relationships (QSPR) were used to develop a simple and predictive model for measuring the heat of sublimation of organic compounds. The population-based forward selection method was applied to select an informative subset of descriptors of learning algorithms, such as by using multiple linear regression (MLR) and the support vector machine (SVM) method. Each individual model and consensus model was evaluated by internal validation using the bootstrap method and y-randomization. The predictions of the performance of the external test set were improved by considering their applicability to the domain. Based on the results of the MLR model, we showed that the heat of sublimation was related to dispersion, H-bond, electrostatic forces, and the dipole-dipole interaction between inter-molecules.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.255-264
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• 2007

In the current domestic and overseas standards concerning seismic design, especially on the capacity & demand spectra in the multi-story building, failure is caused more by story drift than by displacement; and the existing capacity spectrum method (CSM) does not make a close estimate of story drift because response is derived using displacement. Therefore, this paper proposes an improved CSM to estimate story drift and its direct effect on the collapse of structures, yet still maintaining the same advantage and convenience of the existing CSM about a most basic model of multi-story building: shear building. To establish its reliability, the proposed method is applied to an example model and results are then compared with those obtained through nonlinear time-history analysis.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.106-114
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• 2009

In this paper we proposed a fast method for a K-Means Clustering algorithm. The main characteristic of this method is that it uses precalculated data which possibility of change is high in order to speed up the algorithm. When calculating distance to cluster centre at each stage to assign nearest prototype in the clustering algorithm, it could reduce overall computation time by selecting only those data with possibility of change in cluster is high. Calculation time is reduced by using the distance information produced by K-Means algorithm when computing expected input data whose cluster may change, and by using such distance information the algorithm could be less affected by the number of dimensions. The proposed method was compared with original K-Means method - Lloyd's and the improved method KMHybrid. We show that our proposed method significantly outperforms in computation speed than Lloyd's and KMHybrid when using large size data which has large amount of data, great many dimensions and large number of clusters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9C
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• pp.697-703
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• 2008

The H.264/AVC video coding standard provides higher coding efnciency compared to the conventional MPEG-2 standard. Since a lot of videos have been encoded using MPEG-2, the format conversion from MPEG-2 to H.264 is essential. In this paper, we propose an efficient method for the conversion of DCT coefficients to H.264/AVC transform coefficients. This conversion is essential, since $8{\times}8$ DCT and $4{\times}4$ integer transform are used in MPEG-2 and H.264/AVC, respectively. The mathematical analysis and computer simulation show that the computational complexity of the proposed algorithm is reduced compared to the conventional algorithm, while the loss caused by the conversion is negligible.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.135-142
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• 2009

Since hold-type display systems have been developed, frame-rate up conversion (FRUC) is an essential technique to improve the temporal resolution in the display. FRUC improves the temporal resolution by interpolating one or multiple intermediate frames between two adjacent frames. In this paper, a new frame-rate up-conversion algorithm based on bilateral motion refinement with rotation is proposed. First, we perform bi-directional motion estimation between adjacent two frames to obtain a motion vector for each block. Then, we apply a modified median filtering to motion vectors for outlier-rejection and motion field smoothing. The filtered motion vectors are updated by the bilateral motion refinement with rotation. After the refined motion vector is obtained, the intermediate frame is generated by applying the overlapped block motion compensation (OBMC). Experimental results show that the proposed algorithm provides a better performance than the previous methods subjectively and objectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.358-358
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• 2018

대청댐은 준공이후 현재까지 37년의 수문자료가 축적되었으며 총 43회의 수문방류를 하여 연간 1.16회의 수문방류를 시행하였다. 본 연구에서는 그동안 수문방류와 지속적으로 최신화한 K-water 저류함수법을 이용하여 수문방류기간중 총강우량 현황과 강우량에 따른 11개의 강우분포형(증가, 감소, 증가감소, 균일, 감소증가, 증가계단, 감소계단, Huff1, Huff2, Huff3, Huff4)의 현황분석, 강우량별 분포형별 유출율을 분석하여 금년도 및 향후 발생이 예상되는 홍수시 수문방류결정에 활용하기 위함이다. 홍수발생 원인을 살펴보면 홍수기 초반에는 장마전선으로 인한 강우가 원인이며, 장마가 끝난 7월말~8월경에는 태풍의 영향을 받는다. 또한, 최근 엘리뇨 및 라니냐 현상의 출현에 따른 기후변화 및 이상기후의 영향으로 예측이 어려운 국지성 돌발호우의 증가로 홍수관리에 어려움을 겪기도 한다. 그러나 최근 가뭄발생이 잦아 우리나라 전역에 가뭄피해가 발생하고 있으며 또한, 홍수기에도 많은 강우가 내리지 않아 2013년 이후에는 수문방류 실적이 전무한 편이다. 홍수로 인한 재해는 인명피해 및 재산피해를 동반하는 우리나라에서 가장 심각한 재해중의 하나이며, 재해예방을 위한 홍수예보는 강우예측과 유출해석으로 나뉠 수 있다. 강우예측은 정교한 강우모형과 기상전문가의 몫이며, 정확한 유출해석은 수문학자들에 의한 연구과제였다. 우리나라 홍수유출해석에 주로 사용되는 모형은 저류함수법이며, 1961년 일본의 Kimura에 의해 창안된 이래 여러 학자들에 의한 다각도의 모형개선을 통해 수차례 모형 성능 향상이 되었다. 그동안 축적된 홍수수문자료를 바탕으로 대청댐 준공이후 수문방류기간중 강우량-강우분포-유출율 관계를 통해 강우량별, 강우분포별, 매개변수별, 유출율, 홍수조절율에 대한 통계분석 및 상관분석을 시행하여 향후 발생가능한 홍수관련 업무에 활용하고자 한다. 또한, 수문방류기간중 호우원인(장마전선, 태풍, 국지성홍수 등)에 대한 분석을 시행하고 호우사상별 매개변수를 산정하여 해당 호우에 대한 특성을 파악하고자 한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.42-52
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• 2022

Bus Information System (BIS) services are expanding nationwide to small and medium-sized cities, including large cities, and user satisfaction is continuously improving. In addition, technology development related to improving reliability of bus arrival time and improvement research to minimize errors continue, and above all, the importance of information accuracy is emerging. In this study, accuracy performance was evaluated using LSTM, a machine learning method, and compared with existing methodologies such as Kalman filter and neural network. As a result of analyzing the standard error for the actual travel time and predicted values, it was analyzed that the LSTM machine learning method has about 1% higher accuracy and the standard error is about 10 seconds lower than the existing algorithm. On the other hand, 109 out of 162 sections (67.3%) were analyzed to be excellent, indicating that the LSTM method was not entirely excellent. It is judged that further improved accuracy prediction will be possible when algorithms are fused through section characteristic analysis.

• Ocean and Polar Research
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• v.46 no.1
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• pp.17-30
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• 2024

A real-time numerical prediction system was developed to predict sea surface temperature (SST) in Cheonsu Bay to minimize damages caused by marine heatwaves. This system assimilated observation data using an ensemble Kalman filter and produced 7-day forecasts. Bias in the temperature forecasts were corrected based on observed data, and the bias-corrected predictions were evaluated against observations. Using this real-time numerical prediction system, daily SSTs were predicted in real-time for 7 days from July to August 2021. The forecasted SSTs from the numerical model were adjusted using observational data for bias correction. To assess the accuracy of the numerical prediction system, real-time hourly surface temperature observations as well as temperature and salinity profiles observed along two meridional sections within Cheonsu Bay were compared with the numerical model results. The root mean square error (RMSE) of the forecasted temperatures was 0.58℃, reducing to 0.36℃ after bias-correction. This emphasizes the crucial role of bias correction using observational data. Sensitivity experiments revealed the importance of accurate input of freshwater influx information such as discharge time, discharge volume, freshwater temperature in predicting real-time temperatures in coastal ocean heavily influenced by freshwater discharge. This study demonstrated that assimilating observational data into coastal ocean numerical models and correcting biases in forecasted SSTs can improve the accuracy of temperature prediction. The prediction methods used in this study can be applied to temperature predictions in other coastal areas.

• Management & Information Systems Review
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• v.33 no.1
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• pp.219-235
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• 2014

This study investigate the smart phone that is not included in the studies that test the effect of added functionalities to convergence products. There are several questions that PDA, MP3 players that are added a certain function can be good convergence product that consumers love and these are the products that has problem of decrease of sales volume because of the development of smart phone. It is a little bit strange to test these product for this study, so this study suggest a little different research tool compared to the past studies. The research implications are follows like theses. Brand awareness is important factor that decrease the uncertainties and risks specially when a innovative tech is added to smart phone. A situation that a innovative tech is added to smart phone is best to get the consumer's perceived innovativeness, value, and buying intention. And a situation that a innovative tech is added to smart phone in the context of low brand awareness is better than a situation that various normal teches are added to it.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.98-106
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• 2011

Since prediction processes such as motion estimation motion compensation are not at the WZ video encoder but at its decoder, WZ video compression cannot have better performance than that of conventional video encoder. In order to implement the prediction process with low complexity at the encoder, WZ residual coding was proposed. Instead of original WZ frames, WZ residual coding encodes the residual signal between key frames and WZ frames. Although the proposed WZ residual coding has good performance in pixel domain, it does not have any improvements in transform domain compared to transform domain WZ coding. The WZ residual coding in transform domain is difficult to have better performance, because pre-defined quantization matrices in WZ coding are not compatible with WZ residual coding. In this paper, we propose a new quantization method modifying quantization matrix and quantization step size adaptively for transform domain WZ residual coding. Experimental result shows 22% gain in BDBR and 1.2dB gain in BDPSNR.