• Journal of Wetlands Research
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• v.21 no.4
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• pp.384-391
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• 2019

Nutrients in stormwater runoff have raised concerns regarding water quality degradation in the recent years. Low impact development (LID) technologies are types of nature-based solutions developed to address water quality problems and restore the predevelopment hydrology of a catchment area. Two LID facilities, infiltration trench (IT) and infiltration planter (IP), are known for their high removal rate of nutrients through sedimentation and vegetation. Long-term monitoring was conducted to assess the performance and cite the advantages and disadvantages of utilizing the facilities in nutrient removal. Since a strong ionic bond exists between phosphorus compounds and sediments, reduction of total phosphorus (TP) (more than 76%), in both facilities was associated to the removal of total suspended solids (TSS) (more than 84%). The efficiency of nitrogen in IP is 28% higher than IT. Effective nitrification occurred in IT and particulate forms of nitrogen were removed through sedimentation and media filters. Decrease in ammonium- nitrogen (NH₄-N) and nitrite-nitrogen (NO₂-N), and increase in nitrate-nitrogen (NO₃-N) fraction forms indicated that effective nitrification and denitrification occurred in IP. Hydrologic factors such as rainfall depth and rainfall intensity affected nutrient treatment capabilities of urban stormwater LID facilities The greatest monitored rainfall intensity of 11 mm/hr for IT yielded to 34% and 55% removal efficiencies for TN and TP, respectively, whereas, low rainfall intensities below 5 mm resulted to 100 % removal efficiency. The greatest monitored rainfall intensity for IP was 27 mm/hr, which still resulted to high removal efficiencies of 98% and 97% for TN and TP, respectively. Water quality assessment showed that both facilities were effective in reducing the amount of nutrients; however, IP was found to be more efficient than IT due to its additional provisions for plant uptake and larger storage volume.

• The Korean Journal of Pesticide Science
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• v.19 no.1
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• pp.5-13
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• 2015

A chromatographic method for the determination of imazapyr, a non-selective herbicide, in agricultural commodities was developed to use safety control of pesticide residue on crops, and was fully validated as an official method for residue analysis. Agricultural commodities, mandarin (fruit), hulled rice (cereal grains), pepper (vegetables), potato (potatoes) and soybean (beans) were extracted with methanol and partitioned with dichloromethane to remove the interference obtained from sample extracts, adjusting pH to 2.5 by 4N hydrochloric acid. Finally, they were analyzed by high performance liquid chromatography coupled to UV detector (HPLC-UVD). The developed method had the linearity in the range of test concentrations with coefficients of determination ($r^2$) more than 0.99. Recovery studies were carried out at three concentration levels (LOQ, 10LOQ, and 50LOQ) performing five replicates at each level. Recoveries were ranged between 72.1 to 108.0%, with relative standard deviations less than 10%. A consistent recovery was determined according to the CODEX guidelines (CAC/GL40, 2003). Finally, LC/MS with selected ion monitoring was also applied to confirm the suspected residues of imazapyr in agricultural samples. This developed method for determination of imazapyr residues in agricultural commodities. can be used as an official method.

• Korean Journal of Ecology and Environment
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• v.42 no.2
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• pp.200-211
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• 2009

A mathematical modeling program called Soil and Water Assessment Tool (SWAT) developed by USDA was applied to Kyongan stream watershed. It was run under BASINS (Better Assessment Science for Integrating point and Non-point Sources) program, and the model was calibrated and validated using KTMDL monitoring data of 2004${\sim}$2008. The model efficiency of flow ranged from very good to fair in comparison between simulated and observed data and it was good in the water quality parameters like flow range. The model reliability and performance were within the expectation considering complexity of the watershed and pollutant sources. The results of pollutant loads estimation as yearly (2004${\sim}$2008), pollutant loadings from 2006 were higher than rest of year caused by high precipitation and flow. Average non-point source (NPS) pollution rates were 30.4%, 45.3%, 28.1% for SS, TN and TP respectably. The NPS pollutant loading for SS, TN and TP during the monsoon rainy season (June to September) was about 61.8${\sim}$88.7% of total NPS pollutant loading, and flow volume was also in a similar range. SS concentration depended on precipitation and pollution loading patterns, but TN and TP concentration was not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. SWAT based on BASINS was applied to the Kyongan stream watershed successfully without difficulty, and it was found that the model could be used conveniently to assess watershed characteristics and to estimate pollutant loading including point and non-point sources in watershed scale.

• Journal of Food Hygiene and Safety
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• v.34 no.1
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• pp.65-72
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• 2019

This study was aimed at investigating the levels of the natural preservatives of benzoic, sorbic and propionic acids in cereal grains, nuts and seeds. Benzoic and sorbic acid were analyzed by high-performance liquid chromatography with a diode-array detector (HPLC-DAD) and further confirmed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), whereas propionic acid was analyzed using a gas chromatography-flame ionization detector (GC-FID) and further confirmed by gas chromatography-mass spectrometry (GC-MS). Benzoic, sorbic and propionic acids were found in 44, 22, and 550 samples out of 702 samples, respectively. From the total of 702 samples. The concentrations of benzoic, sorbic and propionic acid were ranged from not detected (ND) to 23.74 mg/L, from ND to 7.90 mg/L, and from ND to 37.39 mg/L in cereal grains, nuts and seeds, respectively. The concentration ranges determined in this study could be used as standard criteria in the process of inspecting cereal grains, nuts and seeds for preservatives as well as to address consumer complaints or trade disputes.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.277-283
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• 2018

The crop growth model has been widely used for climate change impact assessment. Crop growth model require genetic coefficients for simulating growth and yield. In order to determine the genetic coefficients, regional growth monitoring data or yield trial data of crops has been used to calibrate crop growth model. The aim of this study is to verify that yield trial data of corn is appropriate to calibrate genetic coefficients of CERES-MAIZE. Field experiment sites were Suwon, Jinju, Daegu and Changwon. The distance from the weather station to the experimental field were from 1.3km to 27km. Genetic coefficients calibrated by yield trial data showed good performance in silking day. The genetic coefficients associated with silking are determined only by temperature. In CERES-MAIZE model, precipitation or irrigation does not have a significant effect on phenology related genetic coefficients. Although the effective distance of the temperature could vary depending on the terrain, reliable genetic coefficients were obtained in this study even when a weather observation site was within a maximum of 27 km. Therefore, it is possible to estimate the genetic coefficients by yield trial data in study area. However, the yield-related genetic coefficients did not show good results. These results were caused by simulating the water stress without accurate information on irrigation or rainfall. The yield trial reports have not had accurate information on irrigation timing and volume. In order to obtain significant precipitation data, the distance between experimental field and weather station should be closer to that of the temperature measurement. However, the experimental fields in this study was not close enough to the weather station. Therefore, When determining the genetic coefficients of regional corn yield trial data, it may be appropriate to calibrate only genetic coefficients related to phenology.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.127-137
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• 2019

Recidivism prediction has been a subject of constant research by experts since the early 1970s. But it has become more important as committed crimes by recidivist steadily increase. Especially, in the 1990s, after the US and Canada adopted the 'Recidivism Risk Assessment Report' as a decisive criterion during trial and parole screening, research on recidivism prediction became more active. And in the same period, empirical studies on 'Recidivism Factors' were started even at Korea. Even though most recidivism prediction studies have so far focused on factors of recidivism or the accuracy of recidivism prediction, it is important to minimize the prediction misclassification cost, because recidivism prediction has an asymmetric error cost structure. In general, the cost of misrecognizing people who do not cause recidivism to cause recidivism is lower than the cost of incorrectly classifying people who would cause recidivism. Because the former increases only the additional monitoring costs, while the latter increases the amount of social, and economic costs. Therefore, in this paper, we propose an XGBoost(eXtream Gradient Boosting; XGB) based recidivism prediction model considering asymmetric error cost. In the first step of the model, XGB, being recognized as high performance ensemble method in the field of data mining, was applied. And the results of XGB were compared with various prediction models such as LOGIT(logistic regression analysis), DT(decision trees), ANN(artificial neural networks), and SVM(support vector machines). In the next step, the threshold is optimized to minimize the total misclassification cost, which is the weighted average of FNE(False Negative Error) and FPE(False Positive Error). To verify the usefulness of the model, the model was applied to a real recidivism prediction dataset. As a result, it was confirmed that the XGB model not only showed better prediction accuracy than other prediction models but also reduced the cost of misclassification most effectively.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.589-600
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• 2020

Effective conservation and management of protected areas require monitoring the settlement of invasive alien species and reducing their dispersion capacity. We simulated the potential distribution of invasive alien plant species (IAPS) using three representative species distribution models (Bioclim, GLM, and MaxEnt) based on the IAPS distribution in the forest genetic resource reserve (2,274ha) in Uljin-gun, Korea. We then selected the realistic and suitable species distribution model that reflects the local region and ecological management characteristics based on the simulation results. The simulation predicted the tendency of the IAPS distributed along the linear landscape elements, such as roads, and including some forest harvested area. The statistical comparison of the prediction and accuracy of each model tested in this study showed that the GLM and MaxEnt models generally had high performance and accuracy compared to the Bioclim model. The Bioclim model calculated the largest potential distribution area, followed by GLM and MaxEnt in that order. The Phenomenological review of the simulation results showed that the sample size more significantly affected the GLM and Bioclim models, while the MaxEnt model was the most consistent regardless of the sample size. The optimal model overall for predicting the distribution of IAPS among the three models was the MaxEnt model. The model selection approach based on detailed flora distribution data presented in this study is expected to be useful for efficiently managing the conservation areas and identifying the realistic and precise species distribution model reflecting local characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.599-609
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• 2021

A novel grounding system, which is presented in IEC 60364, has been adopted since 2021. A safety evaluation for the human body on the grounding system is required due to the various characteristics of the touch voltage and current passing when the human body experiences an electric shock. The Korea Electrical Safety Corporation (KESCO) and Korea Electric Association (KEA) have been conducting a safety technical education on the grounding system. On the other hand, it is difficult to instruct the electrical safety manager because of a lack of safety evaluations for the test equipment on the grounding system. Therefore, this paper modeled and implemented a test device for a safety evaluation depending on the grounding system of IEC 60364. Namely, this paper presents the modeling of the test device for a safety evaluation using PSCAD/EMTDC S/W, which is composed of an AC grid section, s test device section on the grounding system, and a sub-device section. This paper implemented a test device for safety evaluation, which consisted of an AC grid section, TT grounding system section, TN-S grounding system section, and monitoring section. From the simulation and test results with the safety characteristics of the human body in the TT and TN-S grounding system, when the fault impedances are 0[Ω], 10[Ω], and 100[Ω], the currents passing through the human body in the TT grounding system are 104[mA], 87.4[mA], and 35.5[mA], respectively. The corresponding currents in the TN-S grounding system are 54.9[mA], 4.1[mA], and 0.4[mA], respectively. Based on the results, the protection performance for an electric shock to the human body in the TN-S system is better than the TT system. This can be improved when the existing grounding system is changed from the TT system to the TN-S system.

• Journal of Food Hygiene and Safety
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• v.36 no.3
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• pp.239-247
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• 2021

In order to confirm the impact of the Positive List System (PLS) being applied to all agricultural products from January 1, 2019, we analyzed 28,693 points of inspection-related data on agricultural products distributed in Gyeonggi-do from 2018 to 2020. The ratio of cases exceeding the standard for the total inspection performance was 1.0% in 2018, 1.2% in 2019, and 1.2% in 2020. Out of the 114 cases exceeding the standard in 2019, 55 were applied on a Maximum Residue Limit (MRL) of 0.01 mg/kg, and out of the 115 cases exceeding the standard in 2020, 66 were applied on a MRL of 0.01 mg/kg. To improve this, it seems necessary to manage unintentional pollution, conventional use for unregistered crops, and illegal pesticides. Fluquinconazole detection resulted from unintentional contamination, and diazinon, chlorothalonil, and methabenzthiazuron detection resulted from conventional use in unregistered crops. Chinomethionat is a pesticide component that was discarded in the past and its current use has been attributed to the smuggling of pesticides. This study and future monitoring data can be used as reference data for system supplementation and on-site management reinforcement.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.316-328
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• 2021

In this study, the leaf Na content prediction model for spring potato was established using 400-1000 nm hyperspectral sensor to develop the multispectral sensor for the salinity monitoring in reclaimed land. The irrigation conditions were standard, drought, and salinity (2, 4, 8 dS/m), and the irrigation amount was calculated based on the amount of evaporation. The leaves' Na contents were measured 1st and 2nd weeks after starting irrigation in the vegetative, tuber formative, and tuber growing periods, respectively. The reflectance of the leaves was converted from 5 nm to 10 nm, 25 nm, and 50 nm of FWHM (full width at half maximum) based on the 10 nm wavelength intervals. Using the variance importance in projections of partial least square regression(PLSR-VIP), ten band ratios were selected as the variables to predict salinity damage levels with Na content of spring potato leaves. The MLR(Multiple linear regression) models were estimated by removing the band ratios one by one in the order of the lowest weight among the ten band ratios. The performance of models was compared by not only R2, MAPE but also the number of band ratios, optimal FWHM to develop the compact multispectral sensor. It was an advantage to use 25 nm of FWHM to predict the amount of Na in leaves for spring potatoes during the 1st and 2nd weeks vegetative and tuber formative periods and 2 weeks tuber growing periods. The selected bandpass filters were 15 bands and mainly in red and red-edge regions such as 430/440, 490/500, 500/510, 550/560, 570/580, 590/600, 640/650, 650/660, 670/680, 680/690, 690/700, 700/710, 710/720, 720/730, 730/740 nm.