• Korean Journal of Poultry Science
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• v.50 no.1
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• pp.41-50
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• 2023

Over the last decade, avian influenza (AI) has been considered an emerging disease that would become the next pandemic, particularly in countries like South Korea, with continuous animal outbreaks. In this situation, risk assessment is highly needed to prevent and prepare for human infection with AI. Thus, we developed the risk assessment matrix for a high-risk area of human infection with AI in South Korea based on the notion that risk is the multiplication of hazards with vulnerability. This matrix consisted of highly pathogenic avian influenza (HPAI) in poultry farms and the number of poultry-associated production facilities assumed as hazards of avian influenza and vulnerability, respectively. The average number of HPAI in poultry farms at the 229-municipal level as the hazard axis of the matrix was predicted using a negative binomial regression with nationwide outbreaks data from 2003 to 2018. The two components of the matrix were classified into five groups using the K-means clustering algorithm and multiplied, consequently producing the area-specific risk level of human infection. As a result, Naju-si, Jeongeup-si, and Namwon-si were categorized as high-risk areas for human infection with AI. These findings would contribute to designing the policies for human infection to minimize socio-economic damages.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.17-27
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• 2023

Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.

• The Journal of Engineering Geology
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• v.33 no.3
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• pp.371-388
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• 2023

A stratum with a complex composition and a distributed low-permeability soil layer is difficult to remediate quickly because the soil remediation does not proceed easily. For efficient purification, the permeability should be improved and the soil remediation agent (H₂O₂) should be injected into the contaminated section to make sufficient contact with the TPH (Total petroleum hydrocarbons). This study analyzed a method for crack formation and effective delivery of the soil remediation agent based on pneumatic fracturing, plasma blasting, and vacuum suction (the PPV method) and compared its improvement effect relative to chemical oxidation. A demonstration test confirmed the effective delivery of the soil remediation agent to a site contaminated with TPH. The injection amount and injection time were monitored to calculate the delivery characteristics and the range of influence, and electrical resistivity surveying qualitatively confirmed changes in the underground environment. Permeability tests also evaluated and compared the permeability changes for each method. The amount of soil remediation agent injected was increased by about 4.74 to 7.48 times in the experimental group (PPV method) compared with the control group (chemical oxidation); the PPV method allowed injection rates per unit time (L/min) about 5.00 to 7.54 times quicker than the control method. Electrical resistivity measurements assessed that in the PPV method, the diffusion of H₂O₂2 and other fluids to the surface soil layer reduced the low resistivity change ratio: the horizontal change ratio between the injection well and the extraction well decreased the resistivity by about 1.12 to 2.38 times. Quantitative evaluation of hydraulic conductivity at the end of the test found that the control group had 21.1% of the original hydraulic conductivity and the experimental group retained 81.3% of the initial value, close to the initial permeability coefficient. Calculated radii of influence based on the survey results showed that the results of the PPV method were improved by 220% on average compared with those of the control group.

• Exercise Science
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• v.21 no.2
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• pp.183-190
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• 2012

This study is to evaluate the availability of cardiorespiratory fitness measurement by 20 m shuttle run test based upon energy contribution rates of elite athletes in different sports type. Sixty-seven elite athletes attending K national university participated in this study. They were divided by three groups based upon sports type, composed of Anaerobic Group (sprint, jumps, weightlifting, throw; n=35), Aerobic Group (medium-long distance; n=9), and Combat Sport Group (judo; n=23). 20 m shuttle run test was conducted by Leger et al.(1982) method and calculating acceleration using measured shuttle run repetitions was conducted by Brewer et al.(1988) method. To test the usefulness of VO₂max, graded exercise treadmill test was conducted and standing long jump and 50 m run were measured as power fitness factors. Z-jump was used for measuring power, agility, and muscular endurance. Standing long jump and 50 m run of Anaerobic Group (AnG) was significantly higher than that of Aerobic Group (AeG) and Combat Sport Group (CG) (p<0.05). However, Z-jump of CG was significantly higher than that of AnG and AeG(p<.05). There was a higher correlation of 20 m shuttle run test and VO₂max in AnG(r= 0.577, p<.0001) and CG(r= 0.760, p<.0001). Otherwise, there was a low correlation of 20 m shuttle run test and VO₂max in AeG. There was no significant group difference to test the availability of 20 m shuttle run test and there was a reduced error when converting 20 m shuttle run results into VO₂max. This study examined the usefulness of 20 m shuttle run test by converting 20 m shuttle run repetition results into VO₂max calculation, which showed reduced error. Therefore, this study confirmed that it would be needed to convert 20 m shuttle run results into VO₂max for universal and practical use in the field without dividing sports type.

• Journal of Korean Living Environment System
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• v.16 no.2
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• pp.89-100
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• 2009

The present study was designed to observe the thermal dynamics of core and skin temperatures during sub-maximal treadmill exercise; to investigate the effect of regional body cooling during short rest after the treadmill exercise on the thermal dynamics. Three conditions (No cooling, Head/Hand cooling, Leg cooling) were simulated in a climatic chamber at 24±1℃ and 50±5%RH. Subjects performed two bouts of treadmill exercise at a rate of 80%HR_max followed by rest. Body cooling with a hood, long gloves, and a blanket that circulated water set at 15℃ was assigned during two bouts of rest. The results showed that (1) rectal temperature (T_re) did not show significant difference between three conditions; (2) Skin temperatures had specific features, depending on body regions. In particular, the initial fall phenomena of skin temperatures at the onset of exercise were noteworthy in the chest, thigh, calf, and finger tip. Of these, the most significant initial fall was found in finger temperature (T_fing). (3) During the period of the initial fall in skin temperatures, T_re gradually increased. (4) The magnitude of the fall of T_fing at the onset of 2^nd running was on average 4.8, 5.1 and 3.4℃ for Control, HH cooling, and Leg cooling, respectively (p<0.05). The initial drop of T_fing at the onset of running was maintained for an average of 8.1, 7.9 and 6.3 minutes for Control, HH cooling, and Leg cooling, with no significant differences. In conclusion, the initial fall phenomena at the onset of treadmill exercise reflected non-thermal factors, as opposed to internal thermal status. The magnitude of the initial fall in T_fing was affected by legs cooling. Therefore, the initial fall phenomenon should be considered when interpreting the thermal status of the shell during heavy works/exercises that assigned with intermittent regional body cooling.

• Journal of the Korean Regional Science Association
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• v.39 no.1
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• pp.53-66
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• 2023

Due to COVID-19, the external activities of urban residents have greatly shrunk, causing a lot of damage to the commercial district, such as a decrease in population and sales. The downturn in commercial districts means the collapse of the infrastructure of the national economy, and can have serious side effects on the local economy and individual lives. Therefore, it is necessary to look at the alley commercial area, which is closely related to the national local economy, and pay attention to the damage and stagnation of the alley commercial area where small business owners are concentrated. The purpose of this study is to classify alley commercial districts into growth commercial districts and decline commercial districts by using commercial sales time series data and DTW time series group analysis for the pre- and post-COVID-19 period. The main findings of the study are as follows. First, using the time series data on commercial sales before and after COVID-19, the alley commercial districts were divided into growth commercial districts and decline commercial districts, and it was confirmed that the distribution of growth commercial districts and decline commercial districts was regionally different. Therefore, it is necessary to actively manage commercial districts in areas where many declining commercial districts are distributed, and it is required to prepare policies for each region in consideration of the spatial distribution of declining commercial districts. Second, during the COVID-19 period, face-to-face essential industries, density of guest facilities, and population density negatively affected the sustainability of commercial districts, which is the opposite of previous studies. This is the result of empirically confirming the specificity of the COVID-19 period and the negative effects of the integrated economy, and can be used as basic data for effective commercial district management and policy preparation in the event of a national disaster in the future. Third, the characteristics of the background of the commercial district had a significant effect on the sustainability of the commercial district, and the negative effect of the attracting facilities inducing population concentration in the background area was found. This suggests that it is necessary to consider the characteristics of the background as well as the inside of the commercial district when establishing policies to revitalize the commercial district and support small business owners in a national disaster situation.

• 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.

• Korean Journal of Environmental Biology
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• v.40 no.2
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• pp.164-171
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• 2022

Frankliniella occidentalis is an invasive pest insect, which affects over 500 different species of host plants and transmits viruses (tomato spotted wilt virus; TSWV). Despite their efficiency in controling insect pests, pesticides are limited by residence, cost and environmental burden. Therefore, a fixed-precision level sampling plan was developed. The sampling method for F. occidentalis adults in pepper greenhouses consists of spatial distribution analysis, sampling stop line, and control decision making. For sampling, the plant was divided into the upper part(180 cm above ground), middle part (120-160 cm above ground), and lower part (70-110 cm above ground). Through ANCOVA, the P values of intercept and slope were estimated to be 0.94 and 0.87, respectively, which meant there were no significant differences between values of all the levels of the pepper plant. In spatial distribution analysis, the coefficients were derived from Taylor's power law (TPL) at pooling data of each level in the plant, based on the 3-flowers sampling unit. F. occidentalis adults showed aggregated distribution in greenhouse peppers. TPL coefficients were used to develop a fixed-precision sampling stop line. For control decision making, the pre-referred action thresholds were set at 3 and 18. With two action thresholds, N_max values were calculated at 97 and 1149, respectively. Using the Resampling Validation for Sampling Program (RVSP) and the results gained from the greenhouses, the simulated validation of our sampling method showed a reasonable level of precision.

• Korean Journal of Environmental Biology
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• v.40 no.2
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• pp.125-137
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• 2022

To assess the characteristics of meiofaunal community fluctuations related to environmental factors, seasonal surveys were conducted in the subtidal zone of Hallyeohaesang National Park. The average depth of the study area was about 20 m, and the average water temperature at the bottom was low in winter(11.33℃) and high in summer(17.95℃). The sedimentary particles mainly comprised silt and clay at most stations. The abundance of meiofauna ranged from 81.7 to 1,296.5 Inds. 10 cm^-2, and the average abundance was 589.3 Inds. 10 cm^-2. The average abundance of meiofauna in each season was the lowest at 416.5 Inds. 10cm^-2 in winter and the highest at 704.5Inds.10 cm^-2 in spring. The dominant taxa were nematodes (about 92%) and harpacticoids (about 5%). In the cluster analysis of meiofaunal communities, they were divided into four significant groups. The largest group mainly contained spring and summer samples, and contained stations with a high nematode density of over 500 Inds. 10 cm^-2 and harpacticoids below 50 Inds. 10 cm^-2 with a high composition ratio of nematodes. In the cluster analysis, no regional division was found between the stations, and it was thought to be divided by the seasons with high abundance according to seasonal variation and the composition ratio of nematodes and harpacticoids. In the Spearman rank correlation analysis, the density of total meiofauna and the most dominant taxa, nematodes, was not significantly related to environmental factors. However, the density of harpacticoids had a significant positive correlation with water depth and a negative correlation with sediment particle size.

• The Korean Journal of Mycology
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• v.50 no.4
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• pp.281-289
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• 2022

Fusarium head blight is an important disease of small grains. It is mainly caused by members of the Fusarium graminearum species complex (FGSC). Barley and wheat growers spray fungicides, especially demethylation-inhibitor fungicides, to suppress the disease. The objective of this study was to examine the changes in the sensitivity of the FGSC population to the triazole fungicide, propiconazole. A total of 124 and 350 isolates of FGSC were obtained from barley and wheat in Jeolla Province during 2010-2016 and 2020-2021, respectively. The species identity and trichothecene chemotypes of the FGSC isolates were determined based on polymerase chain reaction assays targeting translation elongation factor 1-alpha and TRI12 genes, respectively. Sensitivity to propiconazole was determined based on the effective concentration that reduced 50% of the mycelial growth (EC₅₀) using the agar dilution method. Of all isolates, F. asiaticum with the nivalenol chemotype was the most common (83.9% in 2010-2016 and 96.0% in 2020-2021), followed by F. asiaticum with the 3-acetyl deoxynivalenol chemotype (12.1% in 2010-2016 and 2.9% in 2020-2021). The EC₅₀ values of the isolates collected in 2010-2016 and 2020-2021 ranged from 0.0180 to 11.0166 ㎍/mL and 1.3104 to 17.9587 ㎍/mL, respectively. The mean EC₅₀ value of the isolates increased from 3.8648 ㎍/mL in 2010-2016 to 5.9635 ㎍/mL in 2020-2021. The baseline resistance to propiconazole was determined to be 7 ㎍/mL, based on the EC₅₀ value of isolates collected in 2010-2016, and the ratio of resistant isolates increased from 9.7% in 2010-2016 to 28.6% in 2020-2021.