• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.2
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• pp.1-15
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• 1997

This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.

• The Journal of Engineering Geology
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• v.23 no.1
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• pp.57-65
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• 2013

We developed a computer program (CDFlow v. 1.0) to design countermeasures against debris flows in natural terrain. The program can predict the probability of landslides occurring in natural terrain and can estimate the zone of damage caused by a debris flow. It can also be used to design the location and size of countermeasures against the debris flow. The program is run using the ArcGIS Engine, which is one of the most well-known Geographic Information System (GIS) tools for developers. The quasi-dynamic wetness index and the infinite slope stability equation were applied to predict landslide probability as a type of slope safety factor. The calculated safety factor was compared with the required safety factor, and areas of high probable potential for landslides were then selected and represented on the digital map. The volume of debris flow was estimated using these areas of high probable potential for landslides and soil depth. The accumulated volume of debris flow can be calculated along the flow channel. To assess the accuracy of the program, it was applied to a real landslide site at Deoksan-ri, Inje-gun, Kangwon-Province, where four debris barriers have been installed in the watershed of the site. The results of soil tests and a field survey indicate that the program has great potential for estimating probable landslide areas and the trajectory of debris flows. Calculation of the capacity volume of existing debris barriers revealed that they had insufficient capacity to store the calculated amount of debris flow. Therefore, this program enables a rational estimation of the optimal location and size of debris barriers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.8
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• pp.975-981
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• 2013

A robust optimization is only one of the ways to minimize the effects of variances in design variables on the objective functions at the preliminary design stage. To predict the variances and to formulate the probabilistic constraints are the most important procedures for the robust optimization formulation. Though several methods such as the process capability index and the six sigma technique were proposed for the prediction and formulation of the variances and probabilistic constraints, respectively, there are few attempts using a percent defective which has been widely applied in the quality control of the manufacturing process for probabilistic constraints. In this study, the robust optimization for a lower control arm of automobile vehicle was carried out, in which the design space showing the mean and variance sensitivity of weight and stress was explored before robust optimization for a lower control arm. The 2nd order Taylor expansion for calculating the standard deviation was used to improve the numerical accuracy for predicting the variances. Simplex algorithm which does not use the gradient information in optimization was used to convert constrained optimization into unconstrained one in robust optimization.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.437-444
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• 2001

This paper discusses applications of neural network to forest stand field data processing and determining suitable tree species for site-specific stand characteristics. For site-specific species selection, considered were 5 major coniferous species : P. densiflora for. erecta, L. leptolepis, P. koraiensis, P. densiflora, P. thunbergii. Among 1,320 sample plot data sets, 200 data sets with the highest site index (40 data sets for each species) were chosen as the test sets for investigation. Each data set includes 13 factors describing the site characteristics of the corresponding sample plot. The results of this investigation indicate high performance of neural network in data processing procedures for extracting data sets or measurement parameters without any recognizable pattern. These data sets or measurement parameters are those which have rare effect on site-specific species suitability or disturb pattern classification procedures of neural network because of unrecognizable patterns involved. Also the results have shown high potential of neural network in determining the best-suitable tree species for site characteristics. The % accuracy of the neural network model in determining the best-suitable tree species for site characteristics ranges from 77.6% to 91.8% associated with the combination of Site factors.

• Korean Journal of Environment and Ecology
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• v.9 no.2
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• pp.197-201
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• 1996

A mixed forest community of Abies holophylla and broad-leaved trees in Odaesan National Park was studied to determine the adequate number of plots of shrub stratum for investigating forest community structure. Thirty 5m*5m plots were set up in the shrub stratum, and species-area curve and performance curve were made out. The minimum number of plots where a given percentage increase in number of plots produce in number of plots produced less than the same percentage increase in number of species was six. The minimum number of plots where a given percentage increase in number of plots produced less than the half of the percentage increase in number of plots was eleven. The minimum number of plots where the dominant species was distinguished from the subdominant species was five. The minimum numver of plots where the first subdominant species was distinguished from other subdominant species was ten. The diffrence of species diversity(H') between five or more plots and total thirty plots was less than 0.05. Similarity index was more than 70% between five or more plots and total thirty plots, and more than 80% between ten or more plots and total thirty plots. The conclusion is that the adequate number of 5m*5m plots for the shrub stratum was about 5 in general case and about 10 in case of requiring more accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.13-24
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• 2020

A systematic approach to assess the safety of corrugated steel plate structures has not been established yet. Therefore, an improved safety assessment procedure was proposed in this study by considering the characteristics of corrugated steel plate structures in which the dead load of backfill soil is dominant and the live load effect is minimized. The proposed procedure can consider the combined effect of axial force and bending moment on the safety, based on the Soil-Culvert Interaction (SCI) method, and can differentiate the maintenance scheme according to the calculated plasticity index. There is also an advantage in enhancing the accuracy of assessment, utilizing the measured displacements. Furthermore, improved methods were proposed by discussing various ways for reasonably improving the proposed assessment procedure. The safety of an actual structure and a full-scale test specimen was assessed by applying the proposed procedure. The conventional assessment procedure significantly overestimated the load-carrying capacity, whereas the proposed procedure resulted in a reasonable level of safety. Therefore, the procedure proposed in this study is expected to contribute to the establishment of proper maintenance plan such as the quantitative condition assessment and strengthening of corrugated steel plate structure.

• Journal of Environmental Health Sciences
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• v.46 no.5
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• pp.576-587
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• 2020

Objectives: This study calculated local residents exposures to VOCs (Volatile Organic Compounds) released into the atmosphere using the CalTOX model and carried out uncertainty analysis and sensitivity analysis. The model validity was analyzed by comparing the predicted and the actual atmospheric concentrations. Methods: Uncertainty was parsed by conducting a Monte Carlo simulation. Sensitivity was dissected with the regression (coefficients) method. The model validity was analyzed by applying r² (coefficient of determination), RMSE (root mean square error), and the Nash-Sutcliffe EI (efficiency index) formula. Results: Among the concentrations in the atmosphere in this study, benzene was the highest and the lifetime average daily dose of benzene and the average daily dose of xylene were high. In terms of the sensitivity analysis outcome, the source term to air, exposure time, indoors resting (ETri), exposure time, outdoors at home (ETao), yearly average wind speed (v_w), contaminated area in ㎡ (Area), active breathing rate (BRa), resting breathing rate (BRr), exposure time, and active indoors (ETai) were elicited as input variables having great influence upon this model. In consequence of inspecting the validity of the model, r² appeared to be a value close to 1 and RMSE appeared to be a value close to 0, but EI indicated unacceptable model efficiency. To supplement this value, the regression formula was derived for benzene with y=0.002+15.48x, ethylbenzene with y ≡ 0.001+57.240x, styrene with y=0.000+42.249x, toluene with y=0.004+91.588x, and xylene with y=0.000+0.007x. Conclusions: In consequence of inspecting the validity of the model, r² appeared to be a value close to 1 and RMSE appeared to be a value close to 0, but EI indicated unacceptable model efficiency. This will be able to be used as base data for securing the accuracy and reliability of the model.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.4
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• pp.417-424
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• 2010

The purpose of this study was to detect significant SNPs for carcass quality traits using DNA chips of high SNP density in Hanwoo populations. Carcass data of two hundred and eighty nine steers sired by 30 Korean proven sires were collected from two regions; the Hanwoo Improvement Center of National Agricultural Cooperative Federation in Seosan, Chungnam province and the commercial farms in Gyeongbuk province. The steers in Seosan were born between spring and fall of 2006 and those in Gyeonbuk between falls of 2004 and 2005. The former steers were slaughtered at approximately 24 months, while the latter steers were fed six months longer before slaughter. Among the 55,074 SNPs in the Illumina bovine 50K chip, a total of 32,756 available SNPs were selected for whole genome association study. After adjusting for the effects of sire, region and slaughter age, phenotypes were regressed on each SNP using a simple linear regression model. For the significance threshold, 0.1% point-wise p value from F distribution was used for each SNP test. Among the significant SNPs for a trait, the best set of SNP markers were selected using a stepwise regression procedure, and inclusion and exclusion of each SNP out of the model was determined at the p<0.001 level. A total of 118 SNPs were detected; 15, 20, 22, 28, 20, and 13 SNPs for final weight before slaughter, carcass weight, backfat thickness, weight index, longissimus dorsi muscle area, and marbling score, respectively. Among the significant SNPs, the best set of 44 SNPs was determined by stepwise regression procedures with 7, 9, 6, 9, 7, and 6 SNPs for the respective traits. Each set of SNPs per trait explained 20-40% of phenotypic variance. The number of detected SNPs per trait was not great in whole genome association tests, suggesting additional phenotype and genotype data are required to get more power to detect the trait-related SNPs with high accuracy for estimation of the SNP effect. These SNP markers could be applied to commercial Hanwoo populations via marker-assisted selection to verify the SNP effects and to improve genetic potentials in successive generations of the Hanwoo populations.

• Korean Journal of Environmental Agriculture
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• v.8 no.1
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• pp.30-36
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• 1989

To determine irrigated water temperature under the rice plant canopy, micrometeorological elements air temperature, relative humidity, water temperature, solar radiation, and the rice leaf area index the rice plant canopywere measured. Water temperature under the canopy was also estimated from these data. The results are as follows ; 1. Maximum and minimum temperatures of water in the paddy field were higher about $1-2^{\circ}C$ than those of air temperature. 2. Mean water temperature under the canopy became lower than mean air temperature when the leaf area indices were greater than 4, because of decreased light penetration rates 3. Penetration amounts of net radiation under the canopy can be estimated by an exponential equation 4. Estimated water temperatures under the canopy by a combination method model was adaptable in Suweon, a plain area, but its accuracy was lower in Jinbu, an alpine area.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1613-1613
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• 2001

Fats and molasses are used, at the present time, in a considerable proportion as ingredients for the animal feed industry. They are mainly used as energy sources, but also they provide other characteristics of technological and nutritional interest (dust reduction, increase in palatability, etc). Both semi-liquid ingredients have numerous aspects in common from the point of view of their use in livestock feeds, as well as of their analytical control. Feed manufacturers use several criteria to evaluate the quality of fat and molasses. Furthermore, the traditional methods currently used, for their evaluation (eg. fatty acids, sugars, etc) are expensive and more sophisticated that the traditionally used for solid ingredients. The objective of the present work is to carry out a viability study to evaluate the ability of NIRS technology for the quality control of fat and molasses. Samples of liquid molasses (n = 42) and liquid fat ( n = 61), provided by a feed manufacturer, were scanned in a FOSS-NIR Systems 6500 monochromator equipped with a spinning module. The samples were analysed by folded transmission, using a sample cup of 0.1mm pathlength and gold surface reflector. For molasses, calibration equations were developed for the prediction of moisture (SECV=1.69%; $r^2$=0, 42), gross protein (SECV=0, 14%; $r^2$=0, 99), ashy (SECV=0, 60%; $r^2$=0, 84), NaCl (SECV=0, 05%; $r^2$=0, 99) and sugars (SECV=1, 04%; $r^2$=0, 86). For animal fats calibrations were obtained for the prediction of moisture (SECV=0, 14%, $r^2$=0, 88), acidity index (SECV=0, 83%, $r^2$=0, 82), MIU (SECV=0, 38%, $r^2$=0, 94) and unsaponifiables (SECV=0, 45%, $r^2$=0, 87). High accuracy calibration equations were also obtained for the prediction of the fatty acid profile. The equations have $r^2$values around 0.9 or highest. The results showed that NIRS technology could provide rapid and accurate results and reduce analytical costs associated to the quality control of two Important feed ingredients of a well known chemical variability.