• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.567-575
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• 2021

Residents in Dangjin, South Chungcheong Province, in which large-scale emissions facilities such as coal-fired power plants and steel mills are concentrated, are very much concerned about their health despite the local government's aggressive efforts to improve air quality and reduce greenhouse gases. To understand the impact of coal-fired power plants and external factors on local air pollution, the origins of local pollutants were investigated using stable carbon isotopes that are generally used as tracers of the provenance of fine or ultrafine dust. The origins of the pollutants were analyzed with the data library, built using the seasonally measured data for the two separate locations selected considering the distance from the coal-fired power plant and the analysis of previous studies, and with the back trajectory analysis. As a result of analyzing stable isotope ratios, the tendency of high concentration was found in the order of winter > spring > fall > summer. According to the data matching with the library, the mobile pollutants and open-air incineration had a relatively higher impact on the local air pollution. It is believed that this study, as a pilot study, should focus on securing the reliability of the study results through continuous monitoring and data accumulation.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.457-464
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• 2021

The advent of the big data era has enabled the rapid development of deep learning that learns rules by itself from data. In particular, the performance of CNN algorithms has reached the level of self-adjusting the source data itself. However, the existing image processing method only deals with the image data itself, and does not sufficiently consider the heterogeneous environment in which the image is generated. Images generated in a heterogeneous environment may have the same information, but their features may be expressed differently depending on the photographing environment. This means that not only the different environmental information of each image but also the same information are represented by different features, which may degrade the performance of the image analysis model. Therefore, in this paper, we propose a method to improve the performance of the image color constancy model based on Adversarial Learning that uses image data generated in a heterogeneous environment simultaneously. Specifically, the proposed methodology operates with the interaction of the 'Domain Discriminator' that predicts the environment in which the image was taken and the 'Illumination Estimator' that predicts the lighting value. As a result of conducting an experiment on 7,022 images taken in heterogeneous environments to evaluate the performance of the proposed methodology, the proposed methodology showed superior performance in terms of Angular Error compared to the existing methods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.37-47
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• 2023

The black cutworm, Agrotis ipsilon (Hufnagel), is an important crop pest worldwide that feeds more than 80 plant species including cabbage, potato, maize, wheat and bean, and this moth is a typical pest attacking underground parts of crops. It has been known in farm booklets that the larvae of A. ipsilon overwinter in the soil in Korea, but no definitive data exist yet. This study was conducted to evaluate that the specific appearance time of A. ipsilon observed actually in the field could be explained when we assumed that this pest overwinters in a form of larvae or pupae. Degree day-based phenology models were applied for tracking forward or backward to find the predicted developmental stage which developed at a specific stage found in the field. As a result of the analysis, it was confirmed that an initial population could be established in a group that does not overwinter as larvae or pupae in Korea. In other words, the appearance of adults in early March to April could not be explained by the presence of domestic overwintering populations. Populations that overwinter as larvae or pupae in Korea were able to emerge as adults in June to July at the earliest. Therefore, the group of adults appearing in early spring is highly likely to be a population that migrated from outside Korea. Taken together, it was estimated that the colony of A. ipsilon in Korea would be formed by a mixture of a migrant population through long-distance migration and a overwintering population.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.909-930
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• 2022

Although the electricity tariff for each customer class in Korea has an institutional basis which can be linked to cost fluctuations caused by the increase in fuel cost, there is a situation in which it cannot be raised in a timely manner, considering the national economic burden such as inflation. There can be some disagreements about unconditionally raising electricity rates when cost increases occur. It is, however, well known that Korean domestic electricity rates are very low around the world and are in an environment in which rates are not easily adjusted. Moreover, as Korean electricity rates cannot be easily raised due to various factors, domestic electricity rates for each customer class itself have not delivered a desirable price signal for power consumption. Based on historical data such as fuel costs and power production by power source from 2017 to 2020, this study estimated how much power consumption would change if electricity rates were adjusted in 2030 and price signal distortion was resolved. As a result of the estimation, power consumption will be reduced by 9,000 GWh if the current electricity bill is adjusted to a level which can be 100% recovered even with the supply cost alone. This led to a reduction of about 3.82 million CO₂tons of greenhouse gas emissions in the Korean power sector.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2B
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• pp.225-231
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• 2006

The nonpoint source control is based on TPLMS (Total Pollution Load Management System) program. Recently, the Ministry of Environment in Korea has programed TPLMS for 4 major large rivers to improve the water quality in rivers by controling the total pollutant loadings from the watershed area. Usually the urbanization is the main pollutant sources, particularly for nonpoint pollutants, because of high imperviousness and high pollutant mass emissions. The stormwater runoff from urban areas is containing various pollutants such as sediments, metals and toxic chemicals due to human and vehicle activities. Of the various landuses, the highways are highly polluted landuses because of high pollutant accumulation rate by vehicle activities during dry periods. Therefore, this research is achieved to provide pollutant EMCs (Event Mean Concentrations) and mass loadings washed-off from highways during rainfall periods. Five monitoring locations were equipped with an automatic rainfall gage and an flow meter. The results show that the EMC ranges for 95% confidence intervals in highway land use are 45.52-125.76 mg/L for TSS, 52.04-95.48 mg/L for COD, 1.77-4.48 mg/L for TN, 0.29-0.54 mg/L for TP. The ranges of washed- off mass loading are $712.7-2,418.4mg/m^2$ for TSS and $684.1-1,779.6mg/m^2$ for COD.

• Journal of Animal Science and Technology
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• v.65 no.6
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• pp.1180-1193
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• 2023

Most carcass and meat quality traits are moderate to highly heritable, indicating that they can be improved through selection. Genetic evaluation for these types of traits is performed using performance data obtained from commercial and progeny testing evaluation. The performance data from commercial farms are available in large volume, however, some drawbacks have been observed. The drawback of the commercial data is mainly due to sorting of animals based on live weight prior to slaughter, and this could lead to bias in the genetic evaluation of later measured traits such as carcass traits. The current study has two components to address the drawback of the commercial data. The first component of the study aimed to estimate genetic parameters for carcass and meat quality traits in Korean Hanwoo cattle using a large sample size of industry-based carcass performance records (n = 469,002). The second component of the study aimed to describe the impact of sorting animals into different contemporary groups based on an early measured trait and then examine the effect on the genetic evaluation of subsequently measured traits. To demonstrate our objectives, we used real performance data to estimate genetic parameters and simulated data was used to assess the bias in genetic evaluation. The results of our first study showed that commercial data obtained from slaughterhouses is a potential source of carcass performance data and useful for genetic evaluation of carcass traits to improve beef cattle performance. However, we observed some harvesting effect which leads to bias in genetic evaluation of carcass traits. This is mainly due to the selection of animal based on their body weight before arrival to slaughterhouse. Overall, the non-random allocation of animals into a contemporary group leads to a biased estimated breeding value in genetic evaluation, the severity of which increases when the evaluation traits are highly correlated.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.98-106
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• 2019

The coefficient and exponent of the MUSLE(Modified Universal Soil Loss Equation) runoff factor in the SWAT(Soil and Water Assessment Tool) model are 11.8 and 0.56 respectively, which are equally applied to the estimation of soil erosion regardless of land use. they could derive overestimation or underestimation of soil erosion, which can cause problems in the selection of soil erosion-vulnerable area and evaluation of reduction management. However, there are no studies about the estimation of coefficients and exponent for the MUSLE runoff factor by land use and their applicability to the SWAT model. Thus, in order to predict soil erosion and sediment behavior accurately through SWAT model, it is necessary to estimate the coefficient and exponent of the MUSLE runoff factor by land use and evaluate its applicability. In this study, the coefficient and exponent of MUSLE runoff factor by land use were estimated for Gaa-cheon Watershed, and the differences in soil erosion and sediment from SWAT model were analyzed. The coefficient and exponent of runoff factor estimated by this study well reflected the characteristics of soil erosion in domestic highland watershed. Therefore, in order to apply the MUSLE which developed based on observed data of US agricultural basin to the domestic watershed, it is considered that a sufficient modification and supplementation process for the coefficient and exponent of the MUSLE runoff factor depending on land use is necessary. The results of this study can be used as a basic data for selecting soil erosion vulnerable area in the non-point source management areas and establishing and evaluating soil erosion reduction management.

• Health Policy and Management
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• v.11 no.2
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• pp.141-168
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• 2001

Healthcare service organizations can apply the cost of quality(COQ) model as a method to evaluate a service quality improvement project such as Total Quality Management (TQM). COQ model has been used to quantify and evaluate the efficiency and effectiveness of TQM project through estimation between cost and benefit in intervention for a quality Improvement to provide satisfied services for a customer, and to identify a non value added process. For estimating cost of quality, We used activities and activity costs based on Activity Based Costing(ABC) system. These procedures let the researchers know whether the process is value-added by each activity, and identify a process to require improvement in TQM project. Through the series of procedures, health care organizations are service organizations can identify a problem in their quality improvement programs, solve the problem, and improve their quality of care for their costumers with optimized cost. The study subject was a quality improvement program of the department of radiology department in a hospital with n bed sizes in Metropolitan Statistical Area (MSA). The principal source of data for developing the COQ model was total cases of retaking shots for diagnoses during five months period from December of the 1998 to April of the 1999 in the department. First of the procedures, for estimating activity based cost of the department of diagnostic radiology, the researchers analyzed total department health insurance claims to identify activities and activity costs using one year period health insurance claims from September of the 1998 to August of the 1999. COQ model in this study applied Simpson & Multher's COQ(SM's COQ) model, and SM's COQ model divided cost of quality into failure cost with external and internal failure cost, and evaluation/prevention cost. The researchers identified contents for cost of quality, defined activities and activity costs for each content with the SM's COQ model, and finally made the formula for estimating activity costs relating to implementing service quality improvement program. The results from the formula for estimating cost of quality were following: 1. The reasons for retaking shots were largely classified into technique, appliances, patients, quality management, non-appliances, doctors, and unclassified. These classifications by reasons were allocated into each office doing re-taking shots. Therefore, total retaking shots categorized by reasons and offices, the researchers identified internal and external failure costs based on these categories. 2. The researchers have developed cost of quality (COQ) model, identified activities by content for cost of quality, assessed activity driving factors and activity contribution rate, and calculated total cost by each content for cost for quality, except for activity cost. 3. According to estimation of cost of quality for retaking shots in department of diagnostic radiology, the failure cost was ￦35,880, evaluation/preventive cost was ￦72,521, two times as much as failure cost. The proportion between internal failure cost and external failure cost in failure cost is similar. The study cannot identify trends on input cost and quality improving in cost of qualify over the time, because the study employs cross-sectional design. Even with this limitation, results of this study are much meaningful. This study shows possibility to evaluate value on the process of TQM subjects using activities and activity costs by ABC system, and this study can objectively evaluate quality improvement program through quantitative comparing input costs with marginal benefits in quality improvement.

• Economic and Environmental Geology
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• v.52 no.5
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• pp.499-508
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• 2019

Based on the preliminary surveys for the occurrences of the Muwellut chrome-nickel mineralized zone ($800km^2$) in northwestern Myanmar, Bophivum area was selected as the detailed exploration area after considering data source, geological potential, metallogenic province, necessity of resource development on target mineral, exploration activity, grade, ore deposit type, nearby operating mine, infrastructure and exploration prediction effect. From 2013 to 2016, KIGAM and DGSE carried out geological and geochemical survey with 1:1,000 scale, magnetic survey(areal extent, $1.672km^2$), trench survey(19 trench, total length 392 m), pitting survey(18 pit, total depth 42.6m), exploration drilling(6holes 600m, 2015; 13holes 617.4m). We analyzed Cr and Ni contents of 77 drill cores with specific gravity in Yangon DGSE analytical center. Considering surface geological survey, geochemical exploration, magnetic survey, trench survey and drilling data, we divided Bophivum area into 8 blocks. Resource estimation are divided into measured and indicated resources. Measured resource is about 9,790t and indicated resource is about 12,080t with the average grade of Cr 11.8% and Ni 0.34%. In case of Bophivum area, if we develop by tying up Webula chrome mineralized zone in the south, it will be possible to upgrade the medium-scale mine. Geologically, the ophiolite belt are distributed in the western and eastern part in Myanmar. So, the exploration technology obtained from exploation in Bophivum area will be helpful to discover the hidden chromitite ore body in Myanmar ophiolite belt in the future.