• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.40-48
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• 2012

In this paper, we suggests methods for determining optimal representative value and the optimal size of historical data for reliable travel speed prediction. To evaluate the performance of the proposed method in real world environments, we did field tests at four roadway links in Seoul on Tuesday and Sunday. According to the results of applying the methods to historical data of Central Traffic Information Center, the optimal representative value were analyzed to be average and weighted average. Second, it was analyzed that 2 months data is the optimal size of historical data used for travel speed prediction.

• Atmosphere
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• v.31 no.1
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• pp.17-28
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• 2021

We investigated the impact of domain size on the simulated summer precipitation over the Korean Peninsula using the Weather Research and Forecasting (WRF) model. Two different domains are integrated up to 72-hours from 29 June 2017 to 28 July 2017 when the Changma front is active. The domain sizes are adopted from previous RDAPS (Regional Data Assimilation and Prediction System) and current LDAPS (Local Data Assimilation and Prediction System) operated by the Korea Meteorological Administration, while other model configurations are fixed identically. We found that the larger domain size showed better prediction skills, especially in precipitation forecast performance. This performance improvement is particularly noticeable over the central region of the Korean Peninsula. Comparisons of physical aspects of each variable revealed that the inflow of moisture flux from the East China Sea was well reproduced in the experiment with a large model domain due to a more realistic North Pacific high compared to the small domain experiment. These results suggest that the North Pacific anticyclone could be an important factor for the precipitation forecast during the summer-time over the Korean Peninsula.

• The korean journal of orthodontics
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• v.39 no.2
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• pp.112-119
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• 2009

Objective: To develop a mixed dentition analysis method in consideration of the normal variation of tooth sizes. Methods: According to the tooth-size of the maxillary central incisor, maxillary 1st molar, mandibular central incisor, mandibular lateral incisor, and mandibular 1st molar, 307 normal occlusion subjects were clustered into the smaller and larger tooth-size groups. Multiple regression analyses were then performed to predict the sizes of the canine and premolars for the 2 groups and both genders separately. For a cross validation dataset, 504 malocclusion patients were assigned into the 2 groups. Then multiple regression equations were applied. Results: Our results show that the maximum errors of the predicted space for the canine, 1st and 2nd premolars were 0.71 and 0.82 mm residual standard deviation for the normal occlusion and malocclusion groups, respectively. For malocclusion patients, the prediction errors did not imply a statistically significant difference depending on the types of malocclusion nor the types of tooth-size groups. The frequency of prediction error more than 1 mm and 2 mm were 17.3% and 1.8%, respectively. The overall prediction accuracy was dramatically improved in this study compared to that of previous studies. Conclusions: The computer aided calculation method used in this study appeared to be more efficient.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.131-139
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• 2012

In this study, we developed a simulation program for the prediction of tractive performance of a tractor, by applying a widely used empirical model for tractive performance prediction of single tire, Brixius. The tractive performance prediction program can readily predict and estimate tractive performance according to various soil conditions and different specifications of tractors. The program was developed with the considerations of tractor's specification-related parameters (e.g., weight, tire size, and wheelbase of the tractor), a soil parameter (i.e., cone index which represents the soil strength), and operating conditions of the tractor (e.g., theoretical speed and driving types such as 2WD and 4WD). Also, the program was designed to provide tractive performance prediction results of tractors such as gross traction, motion resistance, net traction, and tractive efficiency, in the form of not only numerical values but also graphical visualization. To evaluate the feasibility of the program, we input three different soil conditions (which have different cone indexes each other) and tractor operating conditions to the program and analyzed the tractive performance from each input condition. From the analysis, it can be concluded that the developed program can be effectively utilized to predict the tractive performance under various soil conditions and driving types of tractors with different specifications.

• YAKHAK HOEJI
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• v.59 no.1
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• pp.29-39
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• 2015

In recent years, physiologically based pharmacokinetic (PBPK) modeling has been widely used in pharmaceutical industries as well as regulatory health authorities for drug discovery and development. Several application areas of PBPK have been introduced so far including drug-drug interaction prediction, transporter-mediated interaction prediction, and pediatric PK prediction. The purpose of this review is to introduce PBPK and illustrates one of its application areas, particularly pediatric PK prediction by utilizing existing adult PK data and in vitro data. The evaluation of the initial PBPK for adult was done by comparing with experimental PK profiles and the scaling from adult to pediatric was conducted using age-related changes in size such as tissue compartments, and protein binding etc. Sotalol and lorazepam were selected in this review as model drugs for this purpose and were re-evaluated using the PBPK models by GastroPlus$^{(R)}$. The challenges and strategies of PBPK models using adult PK data as well as appropriate in vitro assay data for extrapolating pediatric PK at various ages were also discussed in this paper.

• Journal of information and communication convergence engineering
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• v.5 no.4
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• pp.339-345
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• 2007

Video transcoding is a technique used to convert a compressed input video stream with an arbitrary format, size, and bitrate into a different attribute video stream different attributes to provide a efficient video streaming service for the customers is dispersed in the heterogeneous networks. Specifically, frames deletion occur in a transcoding scheme that exploits the adjustment of frame rate, and at this time, the loss in temporal relation among frames due to frame deletion is compensated for the prediction of motion estimation by reusing motion vectors in the would-be deleted frames. But the processing time for transcoding don't have an improvement as much as our expectation because transcoding is done only within the transcoder. So in this paper, we propose a new transcoding algorithm based on prediction period to improve transcoding-related processing time. For this, we also modify the existing encoder so as to adjust dynamically frame rate based on the prediction period and deletion period of frames. To check how the proposed algorithm works nicely, we implement a video streaming system with the new transcoder and encoder to which it is applied. The result of the performance test shows that the streaming system with proposed algorithm improve 60% above in processing time and also PSNR have a good performance while the quality of pictures is preserved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2464-2479
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• 2014

Multi-view video coding is an international encoding standard that attains good performance by fully utilizing temporal and inter-view correlations. However, it suffers from high computational complexity. This paper presents a fast encoder design to reduce the level of complexity. First, when the temporal correlation of a group of pictures is sufficiently strong, macroblock-based inter-view prediction is not employed for the non-anchor pictures of B-views. Second, when the disparity between two adjacent views is above some threshold, frame-based inter-view prediction is disabled. Third, inter-view prediction is not performed on boundary macroblocks in the auxiliary views, because the references for these blocks may not exist in neighboring views. Fourth, finer partitions of inter-view prediction are cancelled for macroblocks in static image areas. Finally, when estimating the disparity of a macroblock, the search range is adjusted according to the mode size distribution of the neighboring view. Compared with reference software, these techniques produce an average time reduction of 83.65%, while the bit-rate increase and peak signal-to-noise ratio loss are less than 0.54% and 0.05dB, respectively.

• Structural Engineering and Mechanics
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• v.73 no.4
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• pp.455-462
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• 2020

The hybrid method using the extended finite element method (XFEM) and the forward Euler approach is widely employed to predict the fatigue life of plate structures. Due to the accuracy of the forward Euler approach is determined by a small step size, the performance of fatigue life prediction of the hybrid method is not agreeable. Instead the forward Euler approach, a prediction method using midpoint method and support vector regression (SVR) is presented to evaluate the stress intensity factors (SIFs) and the fatigue life. Firstly, the XFEM is employed to calculate the SIFs with given crack sizes. Then use the history of SIFs as a function of either number of fatigue life cycles or crack sizes within the current cycle to build a prediction model. Finally, according to the prediction model predict the SIFs at different crack sizes or different cycles. Three numerical cases composed by a homogeneous plate with edge crack, a composite plate with edge crack and center crack are introduced to verify the performance of the proposed method. The results show that the proposed method enables large step sizes without sacrificing accuracy. The method is expected to predict the fatigue life of complex structures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.821-827
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• 2008

This paper presents the prediction model of attenuation characteristics of satellite communication signals operating in the range from 1 to 20GHz, associated with the effects of the Asian Dust. And this paper analyze the effects of the Asian Dust in theory that dust particles size and density, OPC, signal levels, exponentail distribution and the permittivity. The prediction model of the dust attenuation was got, combining the formula of the complex dielectric constant of Asian dust. Expressions for specific attenuation and attenuation are derived in terms of the height, visibility. Therefore it make an investigate to the prediction model of attenuation characteristics continuously.

• Journal of Navigation and Port Research
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• v.48 no.2
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• pp.109-115
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• 2024

To develop a shipping company insolvency prediction model, we sampled shipping companies that closed between 2005 and 2023. In addition, a closed company and a normal company with similar asset size were selected as a paired sample. For this study, data of a total of 82 companies, including 42 closed companies and 42 general companies, were obtained. These data were randomly divided into a training set (2/3 of data) and a testing set (1/3 of data). Training data were used to develop the model while test data were used to measure the accuracy of the model. In this study, a prediction model for Korean shipping insolvency was developed using financial ratio variables frequently used in previous studies. First, using the LASSO technique, main variables out of 24 independent variables were reduced to 9. Next, we set insolvent companies to 1 and normal companies to 0 and fitted logistic regression, LDA and QDA model. As a result, the accuracy of the prediction model was 82.14% for the QDA model, 78.57% for the logistic regression model, and 75.00% for the LDA model. In addition, variables 'Current ratio', 'Interest expenses to sales', 'Total assets turnover', and 'Operating income to sales' were analyzed as major variables affecting corporate insolvency.