• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.411-421
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• 2012

The stagnant growth in 3D market due to 3D movie contents shortage is encouraging development of techniques for production cost reduction. Elimination of vertical disparity generated during image acquisition requires heaviest time and effort in the whole stereoscopic film-making process. This matter is directly related to competitiveness in the market and is being dealt with as a very important task. The removal of vertical disparity, i.e. image rectification has been treated for a long time in the photogrammetry field. While computer vision methods are focused on fast processing and automation, photogrammetry methods on accuracy and precision. However, photogrammetric approaches have not been tried for the 3D film-making. In this paper, proposed is a photogrammetry-based rectification algorithm that enable to eliminate the vertical disparity precisely by reconstruction of geometric relationship at the time of shooting. Evaluation of proposed algorithm was carried out by comparing the performance with two existing computer vision algorithms. The epipolar constraint satisfaction, epipolar line accuracy and vertical disparity of result images were tested. As a result, the proposed algorithm showed excellent performance than the other algorithms in term of accuracy and precision, and also revealed robustness about position error of tie-points.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.10 no.1
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• pp.1-11
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• 2012

The equation of the step-drawdown test "$s_w=BQ+CQ^p$" written by Rorabaugh (1953) is suitable for drawdown increased non-linearly in the fractured rocks. It was found that value of root mean square error (RMSE) between observed and calculated drawdowns was very low. The calculated $C$ (well head loss coefficient) and $P$ (well head loss exponent) value of well head losses ($CQ^p$) ranged $3.689{\times}10^{-19}{\sim}5.825{\times}10^{-7}$ and 3.459~8.290, respectively. It appeared that the deeper depth in pumping well the larger drawdowns due to pumping rate increase. The well head loss in the fractured rocks, unlike that in porous media, is affected by properties of fractures (fractures of aperture, spacing, and connection) around pumping well. The $C$ and $P$ value in the well head loss is very important to interpret turbulence interval and properties of high or low permeability of fractured rock. As a result, regression analysis of $C$ and $P$ value in the well head losses identified the relationship of turbulence interval and hydraulic properties. The relationship between $C$ and $P$ value turned out very useful to interpret hydraulic properties of the fractured rocks.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.493-502
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• 2007

An on-line registration technique is presented to register multi-view range images for the 3D reconstruction of real objects. Using a range camera, we first acquire range images and photometric images continuously. In the range images, we divide object and background regions using a predefined threshold value. For the coarse registration of the range images, the centroid of the images are used. After refining the registration of range images using a projection-based technique, we use a modified KLT(Kanade-Lucas-Tomasi) tracker to match photometric features in the object images. Using the modified KLT tracker, we can track image features fast and accurately. If a range image fails to register, we acquire new range images and try to register them continuously until the registration process resumes. After enough range images are registered, they are integrated into a 3D model in offline step. Experimental results and error analysis show that the proposed method can be used to reconstruct 3D model very fast and accurately.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.259-271
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• 2017

The present study was designed to examine the impact of socioeconomic, health-related, and health behavioral factors on the health-related quality of life (HRQoL) of the Korean elderly by gender. The subjects comprised 688 men and 898 women aged 65 or more who had participated in the Sixth Korea National Health and Nutrition Examination Survey conducted in 2014. The associations of factors with the HRQoL as measured with the European Quality of Life 5 Dimensions (EQ-5D) Index were examined in a general linear model. The most influential factor on the HRQoL was depression in both men and women. The perceived health status and walking activity were also associated with the HRQoL in both men and women. The living arrangement and educational status were associated with the HRQoL in women, while the body mass index was associated with the HRQOL in men. Depression management and the promotion of walking activity are essential to the HRQoL of the Korean elderly. Particular attention must be paid to the HRQoL of older women who live alone and have a lower level of education.

• Journal of Korean Society of Forest Science
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• v.79 no.1
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• pp.1-15
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• 1990

In this study the stem analysis program, which can be operated with personal computer was developed to reduce time and cost of calculation, and to increase accuracy of analysis. The stem analysis method used in this program was compared with other methods. The results obtained were as follows : The value, 1/100mm measured from the latest annual ring measurement machine (Jahrringme${\beta}$geraete Johan Type II) was automatically inputed to the computer and saved into given file name. Turbo Pascal program was written to do this. The measured data was analyzed by stem analysis calculation program written by Fortran-77. Volume and height increments were approximated by spline function, and diameter of the stem disk was calculated by quadratic mean method. The increment values calculated by the programs were printed annually and in every five-year. Stem analysis diagram and several increment graphs were also easily printed. The result compared between those analysis methods showed that quadratic mean could reduce the error caused from eccentric pith. When the stem taper curve method, approximated by spline function, was used in the calculation of tree height and volume, increments would be more exactly calculated.

• Journal of Korea Water Resources Association
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• v.37 no.11
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• pp.969-978
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• 2004

According to the report of hydrologic modeling study, from a quantitative point of view, a lumped model is more efficient than a distributed model. A distributed model has to simplify geospatial characteristics for the shake of restricted application on computer calculation and field observation. In this reason, a distributed model can not help having some errors of water quantity modelling. However, considering a distribution of rainfall-runoff reflected spatial characteristics, a distributed model is more efficient to simulate a flow of surface water, The purpose of this study is modeling of spatial rainfall-runoff of surface water using grid based distributed model, which is consisted of storage function model and essential basin-channel parameters( slope, flow direction & accumulation), and that procedure is able to be executed at a personal computer. The prototype of this model is developed in Heongseong Multipunose Dam basin and adapted in Hapchon Multipurpose Dam basin, which is larger than the former about five times. The efficiency coefficients in result of two dam basin simulations are more than about 0.9, but ones at the upstream water level gauge station meet with bad result owing to overestimated rating curves in high water level. As a result of this study, it is easily implemented that spatially distributed rainfall-runoff model using GIS, and geophysical characteristics of the catchment, hereafter it is anticipated that this model is easily able to apply rainfall data by real time.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.527-536
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• 2017

With the recent development of smart grid industry, the necessity for efficient EMS(Energy Management System) has been increased. In particular, in order to reduce electric load and energy cost, sophisticated electric load forecasting and efficient smart grid operation strategy are required. In this paper, for more accurate electric load forecasting, we extend the data collected at demand time into high time resolution and construct an artificial neural network-based forecasting model appropriate for the high time resolution data. Furthermore, to improve the accuracy of electric load forecasting, time series data of sequence form are transformed into continuous data of two-dimensional space to solve that problem that machine learning methods cannot reflect the periodicity of time series data. In addition, to consider external factors such as temperature and humidity in accordance with the time resolution, we estimate their value at the time resolution using linear interpolation method. Finally, we apply the PCA(Principal Component Analysis) algorithm to the feature vector composed of external factors to remove data which have little correlation with the power data. Finally, we perform the evaluation of our model through 5-fold cross-validation. The results show that forecasting based on higher time resolution improve the accuracy and the best error rate of 3.71% was achieved at the 3-min resolution.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.195-206
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• 2004

One of the main factors which reduces the efficiency of a sewage treatment plant is the Inflow/Infiltration(Ⅰ/Ⅰ) in the sewer First we must calculate the quantity of Ⅰ/Ⅰ via the investigation of each sewer to establish the reduction plan of Ⅰ/Ⅰ. However, in Korea, we apply the results of a surveyed sample to the entire study area to establish the reduction plan of Ⅰ/Ⅰ. This methodology just considers the total Ⅰ/Ⅰ for the entire study area but it does not consider the quantity of Ⅰ/Ⅰ for the individual sewer systems. Therefore, we may need the model to consider the Ⅰ/Ⅰ in the individual sewer systems and we develop the model to calculate the Ⅰ/Ⅰ that happen in urban sewer systems. We estimate the Ⅰ/Ⅰ of individual systems by the developed model and the estimated Ⅰ/Ⅰ are utilized as the basic data for the establishment of Ⅰ/Ⅰ reduction plan. The observed Ⅰ/Ⅰ for the entire study area is distributed into the individual sewer systems according to their defect states. Here, the weights of defect elements are calculated using AHP(Analytic Hierarchy Process) and we perform the uncertainty analysis for considering the errors using MCS(Monte Carlo Simulation).

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.143-154
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• 2012

As demand of water resources and attentions to changes in climate (e.g., due to ENSO) increase, long/short term prediction of precipitation is getting necessary in water planning. This research evaluated the ability of MM5 to predict precipitation in the Tampa Bay region over 23 year period from 1986 to 2008. Additionally MM5 results were statistically bias-corrected using observation data at 33 stations over the study area using CDF-mapping approach and evaluated comparing to raw results for each ENSO phase (i.e., El Ni$\tilde{n}$o and La Ni$\tilde{n}$a). The bias-corrected model results accurately reproduced the monthly mean point precipitation values. Areal average daily/monthly precipitation predictions estimated using block-kriging algorithm showed fairly high accuracy with mean error of daily precipitation, 0.8 mm and mean error of monthly precipitation, 7.1 mm. The results evaluated according to ENSO phase showed that the accuracy in model output varies with the seasons and ENSO phases. Reasons for low predictions skills and alternatives for simulation improvement are discussed. A comprehensive evaluation including sensitivity to physics schemes, boundary conditions reanalysis products and updating land use maps is suggested to enhance model performance. We believe that the outcome of this research guides to a better implementation of regional climate modeling tools in water management at regional/seasonal scale.

• Journal of Korea Water Resources Association
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• v.39 no.12 s.173
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• pp.997-1012
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• 2006

We have presented a nonparametric stochastic approach for the SOI(Southern Oscillation Index) series that used nonlinear methodology called Nonlinear AutoRegressive(NAR) based on conditional kernel density function and CAFPE(Corrected Asymptotic Final Prediction Error) lag selection. The fitted linear AR model represents heteroscedasticity, and besides, a BDS(Brock - Dechert - Sheinkman) statistics is rejected. Hence, we applied NAR model to the SOI series. We can identify the lags 1, 2 and 4 are appropriate one, and estimated conditional mean function. There is no autocorrelation of residuals in the Portmanteau Test. However, the null hypothesis of normality and no heteroscedasticity is rejected in the Jarque-Bera Test and ARCH-LM Test, respectively. Moreover, the lag selection for conditional standard deviation function with CAFPE provides lags 3, 8 and 9. As the results of conditional standard deviation analysis, all I.I.D assumptions of the residuals are accepted. Particularly, the BDS statistics is accepted at the 95% and 99% significance level. Finally, we split the SOI set into a sample for estimating themodel and a sample for out-of-sample prediction, that is, we conduct the one-step ahead forecasts for the last 97 values (15%). The NAR model shows a MSEP of 0.5464 that is 7% lower than those of the linear model. Hence, the relevance of the NAR model may be proved in these results, and the nonparametric NAR model is encouraging rather than a linear one to reflect the nonlinearity of SOI series.