• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.561-573
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• 2023

National forests have an advantage over private forests in terms of higher investment in capital, technology, and labor, allowing for more intensive management. As such, national forests are expected to serve not only as a strategic reserve of forest resources to address the long-term demand for timber but also to stably perform various essential forest functions demanded by society. However, most forest stands in the current national forests belong to the fourth age class or above, indicating an imminent timber harvesting period amid an imbalanced age class structure. Therefore, if timber harvesting is not conducted based on systematic management planning, it will become difficult to ensure the continuity of the national forests' diverse functions. This study was conducted to determine the optimal volume of timber production in the national forests to improve the age-class structure while sustainably maintaining their economic and public functions. To achieve this, the study first identified areas within the national forests suitable for timber production. Subsequently, a forest management planning model was developed using multi-objective linear programming, taking into account both the national forests' economic role and their public benefits. The findings suggest that approximately 488,000 hectares within the national forests are suitable for timber production. By focusing on management of these areas, it is possible to not only improve the age-class distribution but also to sustainably uphold the forests' public benefits. Furthermore, the potential volume of timber production from the national forests for the next 100 years would be around 2 million m³ per year, constituting about 44% of the annual domestic timber supply.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.12
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• pp.1696-1702
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• 2015

The objective of this study was to compare the effects of body weight growth adjustment methods on genetic parameters of body growth and tissue among three pig breeds. Data collected on 101,820 Landrace, 281,411 Yorkshire, and 78,068 Duroc pigs, born in Korean swine breeder farms since 2000, were analyzed. Records included body weights on test day and amplitude (A)-mode ultrasound carcass measures of backfat thickness (BF), eye muscle area (EMA), and retail cut percentage (RCP). Days to 90 kg body weight (DAYS90), through an adjustment of the age based on the body weight at the test day, were obtained. Ultrasound measures were also pre-adjusted (ABF, EMA, AEMA, ARCP) based on their test day measures. The (co)variance components were obtained with 3 multi-trait animal models using the REMLF90 software package. Model I included DAYS90 and ultrasound traits, whereas model II and III accounted DAYS90 and pre-adjusted ultrasound traits. Fixed factors were sex (sex) and contemporary groups (herd-year-month of birth) for all traits among the models. Additionally, model I and II considered a linear covariate of final weight on the ultrasound measure traits. Heritability ($h^2$) estimates for DAYS90, BF, EMA, and RCP ranged from 0.36 to 0.42, 0.34 to 0.43, 0.20 to 0.22, and 0.39 to 0.45, respectively, among the models. The $h^2$ estimates of DAYS90 from model II and III were also somewhat similar. The $h^2$ for ABF, AEMA, and ARCP were 0.35 to 0.44, 0.20 to 0.25, and 0.41 to 0.46, respectively. Our heritability estimates varied mostly among the breeds. The genetic correlations ($r_G$) were moderately negative between DAYS90 and BF (-0.29 to -0.38), and between DAYS90 and EMA (-0.16 to -0.26). BF had strong $r_G$ with RCP (-0.87 to -0.93). Moderately positive $r_G$ existed between DAYS90 and RCP (0.20 to 0.28) and between EMA and RCP (0.35 to 0.44) among the breeds. For DAYS90, model II and III, its correlations with ABF, AEMA, and ARCP were mostly low or negligible except the $r_G$ between DAYS90 and AEMA from model III (0.27 to 0.30). The $r_G$ between AEMA and ABF and between AEMA and ARCP were moderate but with negative and positive signs, respectively; also reflected influence of pre-adjustments. However, the $r_G$ between BF and RCP remained non-influential to trait pre-adjustments or covariable fits. Therefore, we conclude that ultrasound measures taken at a body weight of about 90 kg as the test final should be adjusted for body weight growth. Our adjustment formulas, particularly those for BF and EMA, should be revised further to accommodate the added variation due to different performance testing endpoints with regard to differential growth in body composition.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1095-1105
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• 2021

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.26-33
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• 2008

The analysis of wide-angle seismic reflection and refraction data plays an important role in lithospheric-scale crustal structure study. However, it is extremely difficult to develop an appropriate velocity structure model directly from the observed data, and we have to improve the structure model step by step, because the crustal structure analysis is an intrinsically non-linear problem. There are several subjective processes in wide-angle crustal structure modelling, such as phase identification and trial-and-error forward modelling. Because these subjective processes in wide-angle data analysis reduce the uniqueness and credibility of the resultant models, it is important to reduce subjectivity in the analysis procedure. From this point of view, we describe two software tools, PASTEUP and MODELING, to be used for developing crustal structure models. PASTEUP is an interactive application that facilitates the plotting of record sections, analysis of wide-angle seismic data, and picking of phases. PASTEUP is equipped with various filters and analysis functions to enhance signal-to-noise ratio and to help phase identification. MODELING is an interactive application for editing velocity models, and ray-tracing. Synthetic traveltimes computed by the MODELING application can be directly compared with the observed waveforms in the PASTEUP application. This reduces subjectivity in crustal structure modelling because traveltime picking, which is one of the most subjective process in the crustal structure analysis, is not required. MODELING can convert an editable layered structure model into two-way traveltimes which can be compared with time-sections of Multi Channel Seismic (MCS) reflection data. Direct comparison between the structure model of wide-angle data with the reflection data will give the model more credibility. In addition, both PASTEUP and MODELING are efficient tools for handling a large dataset. These software tools help us develop more plausible lithospheric-scale structure models using wide-angle seismic data.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.49-62
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• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.2
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• pp.187-195
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• 2015

The gas explosions in offshore installations are known to be very severe according to its geometry and environmental conditions such as leak locations and wind directions, and a dynamic response of structures due to blast loads depends on the load profile. Therefore, a parametric study has to be conducted to investigate the effects of the dynamic response of structural members subjected to various types of load shapes. To do so, a series of CFD analyses was performed using a full-scale FPSO topside model including detail parts of pipes and equipments, and the time history data of the blast loads at monitor points and panels were obtained by the analyses. In this paper, we focus on a structural dynamic response subjected to blast loads changing the magnitude of positive/negative phase pressure and time duration. From the results of linear/nonlinear transient analyses using single degree of freedom(SDOF) and multi-degree-of freedom(MDOF) systems, it was observed that dynamic responses of structures were significantly influenced by the magnitude of positive and negative phase pressures and negative time duration.

• Journal of Preventive Medicine and Public Health
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• v.43 no.6
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• pp.479-485
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• 2010

Objectives: The Korean Genome and Epidemiology Study (KoGES), a multicenter-based multi-cohort study, has collected information on body composition using two different bioelectrical impedence analysis (BIA) machines. The aim of the study was to evaluate the possibility of whether the test values measured from different BIA machines can be integrated through statistical adjustment algorithm under excellent inter-rater reliability. Methods: We selected two centers to measure inter-rater reliability of the two BIA machines. We set up the two machines side by side and measured subjects' body compositions between October and December 2007. Duplicated test values of 848 subjects were collected. Pearson and intra-class correlation coefficients for inter-rater reliability were estimated using results from the two machines. To detect the feasibility for data integration, we constructed statistical compensation models using linear regression models with residual analysis and R-square values. Results: All correlation coefficients indicated excellent reliability except mineral mass. However, models using only duplicated body composition values for data integration were not feasible due to relatively low $R^2$ values of 0.8 for mineral mass and target weight. To integrate body composition data, models adjusted for four empirical variables that were age, sex, weight and height were most ideal (all $R^2$ > 0.9). Conclusions: The test values measured with the two BIA machines in the KoGES have excellent reliability for the nine body composition values. Based on reliability, values can be integrated through algorithmic statistical adjustment using regression equations that includes age, sex, weight, and height.

• The Journal of Korean Society for Radiation Therapy
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• v.14 no.1
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• pp.175-186
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• 2002

The purpose of this study is directly measure and evaluate about absorbed dose change according to nominal energy and electron cone or medical accelerator on isodose curve, percentage depth dose, contaminated X-ray, inhomogeneous tissue, oblique surface and irradiation on intracavitary that electron beam with high energy distributed in tissue, and it settled standard data of hish energy electron beam treatment, and offer to exactly data for new dote distribution modeling study based on experimental resuls and theory. Electron beam with hish energy of $6{\sim}20$ MeV is used that generated from medical linear accelerator (Clinac 2100C/D, Varian) for the experiment, andwater phantom and Farmer chamber md Markus chamber und for absorbe d dose measurement of electron beam, and standard absorbed dose is calculated by standard measurements of International Atomic Energy Agency(IAEA) TRS 277. Dose analyzer (700i dose distribution analyzer, Wellhofer), film (X-OmatV, Kodak), external cone, intracavitary cone, cork, animal compact bone and air were used for don distribution measurement. As the results of absorbed dose ratio increased while irradiation field was increased, it appeared maximum at some irradiation field size and decreased though irradiation field size was more increased, and it decreased greatly while energy of electron beam was increased, and scattered dose on wall of electron cone was the cause. In percentage depth dose curve of electron beam, Effective depth dose(R80) for nominal energy of 6, 9, 12, 16 and 20 MeV are 1.85, 2.93, 4.07, 5.37 and 6.53 cm respectively, which seems to be one third of electron beam energy (MeV). Contaminated X-ray was generated from interaction between electron beam with high energy and material, and it was about $0.3{\sim}2.3\%$ of maximum dose and increased with increasing energy. Change of depth dose ratio of electron beam was compared with theory by Monte Carlo simulation, and calculation and measured value by Pencil beam model reciprocally, and percentage depth dose and measured value by Pencil beam were agreed almost, however, there were a little lack on build up area and error increased in pendulum and multi treatment since there was no contaminated X-ray part. Percentage depth dose calculated by Monte Carlo simulation appeared to be less from all part except maximum dose area from the curve. The change of percentage depth dose by inhomogeneous tissue, maximum range after penetration the 1 cm bone was moved 1 cm toward to surface then polystyrene phantom. In case of 1 cm and 2 cm cork, it was moved 0.5 cm and 1 cm toward to depth, respectively. In case of air, practical range was extended toward depth without energy loss. Irradiation on intracavitary is using straight and beveled type cones of 2.5, 3.0, 3.5 $cm{\phi}$, and maximum and effective $80\%$ dose depth increases while electron beam energy and size of electron cone increase. In case of contaminated X-ray, as the energy increase, straight type cones were more highly appeared then beveled type. The output factor of intracavitary small field electron cone was $15{\sim}86\%$ of standard external electron cone($15{\times}15cm^2$) and straight type was slightly higher then beveled type.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.149-162
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• 2005

This paper suggest a way to detect a specific wanted figure in public places such as subway stations and banks by comparing color face images extracted from the real time CCTV with the face images of designated specific figures. Assuming that the characteristic of the surveillance camera allows the face information in screens to change arbitrarily and to contain information on numerous faces, the accurate detection of the face area was focused. To solve this problem, the normalization work using subsampling with $20{\times}20$ pixels on arbitrary face images, which is based on the Perceptron Neural Network model suggested by R. Rosenblatt, created the effect of recogning the whole face. The optimal linear filter and the histogram shaper technique were employed to minimize the outside interference such as lightings and light. The addition operation of the egg-shaped masks was added to the pre-treatment process to minimize unnecessary work. The images finished with the pre-treatment process were divided into three reception fields and the information on the specific location of eyes, nose, and mouths was determined through the neural network. Furthermore, the precision of results was improved by constructing the three single-set network system with different initial values in a row.

• Journal of Korean Society of Steel Construction
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• v.9 no.3 s.32
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• pp.287-300
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• 1997

In this study, an effective application method of AE technique for the detection of fatigue crack in multi-girder steel bridges has been proposed. The applicability has been examined through the laboratory works with bridge model. The proposed analytical method which evaluates the remaining fatigue lives of structural members may improve the rational determination of the priority of inspection for structural members assuming to have fatigue cracks. Laboratory tests for the application of AE technique to steel girder bridges show that the frequency bands of traffic noise are in the range between 10 show that the frequency bands of traffic noise are in the range between 100~200 kHz and the AE signal raised from fatigue cracks is concentrated around 400~500 kHz. Therefore. R30 sensor is proved to be the most suitable for the detection of cracks in steel girder bridges. A linear proportionality between the crack propagation and the frequency of AE signals has been obtained. In addition, an economic and effective source location method for steel girder bridges was studied through experiments.