Juhyoung Sung;Sungyoon Cho;Da-Eun Jung;Jongwon Kim;Jeonghwan Park;Kiwon Kwon;Young Myoung Ko
Journal of Internet Computing and Services
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v.24
no.1
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pp.61-69
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2023
Recently, as the fishery resources are depleted, expectations for productivity improvement by 'rearing fishery' in land farms are greatly rising. In the case of land farms, unlike ocean environments, it is easy to control and manage environmental and breeding factors, and has the advantage of being able to adjust production according to the production plan. On the other hand, unlike in the natural environment, there is a disadvantage in that operation costs may significantly increase due to the artificial management for fish growth. Therefore, profit maximization can be pursued by efficiently operating the farm in accordance with the planned target shipment. In order to operate such an efficient farm and nurture fish, an accurate growth prediction model according to the target fish species is absolutely required. Most of the growth prediction models are mainly numerical results based on statistical analysis using farm data. In this paper, we present a growth prediction model from a stochastic point of view to overcome the difficulties in securing data and the difficulty in providing quantitative expected values for inaccuracies that existing growth prediction models from a statistical point of view may have. For a stochastic approach, modeling is performed by introducing a Gaussian process regression method based on water temperature, which is the most important factor in positive growth. From the corresponding results, it is expected that it will be able to provide reference values for more efficient farm operation by simultaneously providing the average value of the predicted growth value at a specific point in time and the confidence interval for that value.
Purpose: Through the establishment of a computerized system of risk assessment, the purpose is to analyze the case of whether the co-workers who are subject to the risk assessment at the construction site can easily fill it out and expect disaster reduction through efficient risk assessment activities. Method: By providing the risk factors and safety measures for the work by selecting the type of work, the risk estimation and the establishment of countermeasures can be made, and a system has been established to enable practical disaster prevention activities by presenting disaster cases for the work. Result: Through the analysis of the change in the scaled disaster rate for the years following the on-site application after the establishment of the risk assessment computer system of H Construction Company, it was confirmed that the scaled disaster rate of the domestic construction industry increased, while the conversion disaster rate of H Construction Company decreased. Conclusion: Through the computational systemization of risk assessments, workers in the field can easily access the risk assessment, evaluate the risk factors of the process and establish risk prevention measures, and it has been analyzed that there is an impact on the reduction of the disaster rate during the operational analysis period.
This study examines the possible problem in the rainfall-runoff analysis process using the VIC (Variable Infiltration Capacity) model caused by using the effective soil depth instead of the soil depth. The parameters of the model are determined as follows. First, parameters that can be determined using available numerical information are fixed. For parameters related to direct runoff and base runoff, the recommended values of the VIC model are applied. In the case of soil depth, four cases are considered: (1) the effective soil depth is applied as the soil depth, (2) 1.5 times of the effective soil depth is applied as the soil depth by reflecting the vertical structure of the soil layer, (3) 1.25 times of the effective soil depth, and (4) 2.0 times of the effective soil depth as alternative soil depths. This study simulates the rainfall-runoff for the period from 1983 to 2020 targeting the Chungju Dam and Soyang River Dam basins of the Han River system. As a result of the study, it is confirmed that when the effective soil depth is applied instead of the soil depth, direct runoff and baseflow have opposite effects, and direct runoff increases by more than 3% while base runoff decreases by the same scale. In addition, the most influential factor in the estimation of the effective soil depth in the Chungju Dam and Soyanggang Dam basins is found to be the proportion of rock outcrop area. The difference between the direct runoff ratio and the base runoff ratio in the two basins is conformed significantly different due to the influence of the rock outcrop area.
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.4D
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pp.395-402
/
2010
The seriousness of a traffic accident appears relatively higher on the curve sections compared with the straight sections due to a change in speed caused by a change in the driver's sight. In particular, the visual distortion phenomenon, one of the dangerous factors taking place on the curve sections, appears different according to the road's geometric design. Although it is a genuinely principal design factor which should be necessarily considered in designing a road, the previous researches on establishing the design standards for it have been insufficiently conducted. As a result, the establishment of the road design standards for the curve sections considering the sight distortion phenomenon is desperately required. This research examined the previous researches on the driver's behaviors, the driver's sight characteristics and the perceived curve radius on the curve sections, and developed the theoretical model of perceived curve radius to which a mathematical technique is applied in consideration of the visual distortion phenomenon on the two-lane curve sections in a local area. In addition, after the theoretical visual distortion was calculated on the basis of the theoretical model of perceived curve radius, the range of error on the theoretical recognition radius model formula was verified through comparing it with the previous researches' experiential visual distortion level and analyzing both of them. As a result, it was observed that as the curve radius practically increases in the theoretical recognition curve radius, the range of error tends to go down, which reflects well the characteristics of the curve sections on the road. Based on this research, it is expected that this research will be helpful to eliminate the safety defects when designing the curve sections and contribute to develop the road design standards considering human factors in the future.
KSCE Journal of Civil and Environmental Engineering Research
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v.26
no.4A
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pp.753-759
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2006
To predict service life of concrete structures exposed to chloride attack, surface chloride concentration, diffusion coefficient of chloride ion, and chloride corrosion threshold value in concrete, are used as important factors. Of these, as the diffusion coefficient of chloride ion for concrete is strongly influenced by concrete quality and environmental conditions of structures and may significantly change the service life of structures, it is considered as the most important factor for service life prediction. The qualitative factors affecting the penetration and diffusion of chloride ion into concrete are water-cement (W/C) ratio, age, curing conditions, chloride ion concentration of given environment, wet and dry conditions, etc. In this paper the influence of W/C ratio and curing conditions on the diffusion characteristics of chloride ion in concrete was investigated through the chloride ion diffusion test. In the test, the voltages passing through the diffusion cell were measured by accelerated test method using potential difference, and then with the consideration of IR drop ratio the diffusion coefficient of chloride ion for concrete with different W/C ratios were estimated by Andrade's model. Furthermore, under different curing conditions formulas for the estimation of the diffusion coefficient of chloride ion have been proposed by the regression analysis considering the effect of W/C ratio and age.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.28
no.4
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pp.158-177
/
2023
An estuary is a transitional water area that links the land and sea through rivers and streams, transporting various components from the land to the sea, which plays an important role in determining primary productivity in the coastal environment, and this coastal ecosystem captures a huge amount of carbon into biomass, known as blue carbon, which mitigates climate change as a potential carbon reservoir. This study examined the variation of mean grain size and organic carbon content of the surface sediments for 6 years and analyzed their relationship in the western and southern estuarine areas (Han River Estuary, Geum River Estuary, Yeongsan River Estuary, Seomjin River Estuary, and Nakdong River Estuary) and the East Sea upwelling area. During the sampling period (2015 to 2020), seasonal variation of both properties was not observed, because their variations might be controlled by diverse oceanographic environments and hydrographic conditions within each survey area. However, despite the synoptic problem of all samples, the positive relationship was obtained between the averages of mean grain size and organic carbon content, which clearly distinguishes each survey area. The unique positive relationship in all estuarine areas implies that the same process by sediment clay particles is important in the organic carbon accumulation. However, additional important factor may be expected in the organic carbon accumulation in the East Sea upwelling area. Further necessary data (sedimentation rate, dry bulk density etc) should be required for the estimation of carbon stock to evaluate the major estuaries in Korea as potential carbon reservoirs in the coastal environment.
Hyo Sang Lee;Yeongkuk Kim;Doo Ho Lee;Dongwon Seo;Dong Jae Lee;Chang Hee Do;Phuong Thanh N. Dinh;Waruni Ekanayake;Kil Hwan Lee;Duhak Yoon;Seung Hwan Lee;Yang Mo Koo
Journal of Animal Science and Technology
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v.65
no.4
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pp.720-734
/
2023
In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (Me) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between Me and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between Me and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the Me, the higher the accuracy of EBV.
Kyung-Su Choo;Dong-Ho Kang;Byung-Sik Kim;In-Jae Song
Journal of Korean Society of Disaster and Security
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v.16
no.2
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pp.49-56
/
2023
Impact based forecast refers to providing information on potential socioeconomic risks according to weather conditions, away from the existing weather factor-oriented forecast. Developed weather countries are investing manpower and finances in technology development to provide and spread impact information, but awareness of impact based forecasts has not spread in Korea. In addition, the focus is on disasters such as floods and typhoons, which cause a lot of damage to impact based forecasts, and research on evaluating the impact of vehicle risks due to strong winds in the transportation sector with relatively low damage is insufficient. In Korea, there are not many cases of damage to vehicle conduction caused by strong winds, but there are cases of damage and the need for research is increasing. Road vulnerability is required to evaluate the risk of vehicles caused by strong winds, and the purpose of this study was to calculate the criteria for road vulnerability. The road vulnerability evaluation was evaluated by the altitude of the road, the number of lanes, the type of road. As a result of the analysis, it was found that the vulnerable area was well reproduced. It is judged that the results of this study can be used as a criterion for preparing an objective evaluation of potential risks for vehicle drivers.
KSCE Journal of Civil and Environmental Engineering Research
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v.43
no.6
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pp.775-784
/
2023
In terms of flood management, it is necessary to analyze quantitative rainfall and runoff from a spatial and temporal perspective and to analyze runoff for heavy rainfall events that are concentrated within a short period of time. The simulation and analysis results of rainfall-runoff models vary depending on the type and input data. In particular, rainfall data is an important factor, so calculating areal mean rainfall is very important. In this study, the areal mean rainfall of the Samcheok Osipcheon(Riv.) watersheds located in the mountainous terrain was calculated using the Arithmetic Mean Method, Thiessen's Weighting Method, and the Isohyetal Method, and the rainfall-runoff results were compared by applying the distributional model S-RAT and the lumped model HEC-HMS. The results of the temporal transferability study showed that the combination of the distributional model and the Isohyetal Method had the best statistical performance with MAE of 64.62 m3/s, RMSE of 82.47 m3/s, and R2 and NSE of 0.9383 and 0.8547, respectively. It is considered that this study was properly analyzed because the peak flood volume occurrence time of the observed and simulated flows is within 1 hour. Therefore, the results of this study can be used for frequency analysis in the future, which can be used to improve the accuracy of simulating peak flood volume and peak flood occurrence time in mountainous watersheds with steep slopes.
Yongseok Kim;Jina Hur;Eung-Sup Kim;Kyo-Moon Shim;Sera Jo;Min-Gu Kang
Korean Journal of Agricultural and Forest Meteorology
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v.26
no.1
/
pp.53-62
/
2024
In this study, we built a model to estimate frost occurrence in South Korea using single-input deep learning and multi-input deep learning. Meteorological factors used as learning data included minimum temperature, wind speed, relative humidity, cloud cover, and precipitation. As a result of statistical analysis for each factor on days when frost occurred and days when frost did not occur, significant differences were found. When evaluating the frost occurrence models based on single-input deep learning and multi-input deep learning model, the model using both GRU and MLP was highest accuracy at 0.8774 on average. As a result, it was found that frost occurrence model adopting multi-input deep learning improved performance more than using MLP, LSTM, GRU respectively.
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