• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.11
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• pp.1515-1522
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• 2008

Monitoring the pesticide residues in agricultural products is essential to protect consumers, obtain data for risk assessment, and ensure fair trade practices. We developed a multi-residue method for the analysis of 37 pesticides with different physico-chemical properties in agricultural products and analyzed the amount of pesticide residues on about 1,000 samples circulated in South Korea. The samples consisted of 26 different types of agricultural products selected at markets in 14 major cities; cereals (2 species), nuts (1 species) potatoes (1 species), beans (2 species), fruits (3 species), vegetables (16 species), and mushrooms (1 species). In this study, residual pesticides were detected in 23 samples (2.2%) and one sample was detected to be over maximum residue limits (MRLs, 0.1%) for pesticides in foods by the Korea food code. In leafy vegetables such as pepper leaves, radish leaves, cham-na-mul, shin-sun-cho, crown daisy, chwi-na-mul and citrus fruits such as kumquat, 8 kinds of pesticides were detected. Specially, diazinon were detected over MRLs and also, endosulfan, ethoprophos and phenthoate were detected frequently. Based on these results, we investigated the risk assesment from amount of residual pesticide, total %ADI was 1.262%, but the value has not effected on human health.

• Journal of Wetlands Research
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• v.16 no.2
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• pp.161-171
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• 2014

Recession of hydrograph gives a significant contribution to estimation of baseflow using rainfall-runoff models and baseflow separation methods, because recession affects baseflow. This study attempted to enhance the accuracy of streamflow predictions using a Soil and Water Assessment Tool (SWAT) model and to separate baseflow from the predicted streamflow. For this, this study used two scenarios: 1) to calibrate eleven parameters using an auto-calibration tool with the alpha factor obtained from RECESS (S1); and 2) to calibrate twelve SWAT parameters including alpha factor (one of SWAT parameters) using an auto-calibration tool (S2). Then, baseflow spearation from the predicted streamflow was conducted by using Web-based Hydrograph Analysis Tool (WHAT). The results show that there is no significant difference between Nash-Sutcliffe efficiency (NSE) values of S1 and S2 for calibrations to streamflow. However, calibrations to baseflow showed that NSEs are 0.777 for S1 and 0.844 for S2, which means a significant difference. Quantitatively compared to the observed streamflow, relative errors were 20.78 % for S1 and 6.59 % for S2. Finally, this study showed the importance of recession in baseflow separated from the predicted streamflow using a rainfall-runoff model.

• Korean Journal of Food Science and Technology
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• v.37 no.4
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• pp.513-518
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• 2005

Capillary electrophoresis (CE) method was developed to determine (+)-catechin and (-)-epicatechin contents in grape seed ethanol extract. CE separation was achieved using 100 mM phosphate and borate buffer at pH 6.0 as background electrolyte and fused silica capillary with 50 microns x 375 microns O.D. (effective length 20.0cm) maintained at $25^{\circ}C$. The applied voltage was 10kV, and detection was performed by DAD at 210 nm, Two catechins were well separated within 6 min with repeatability of <0.8% RSD for migration time and <2.0% RSD for peak area, and correlation coefficients higher than 0.994 were obtained from 58.0 to 174.0 mg/L with detection limit of 0.035 mg/L. Separated compounds were successfully determined. CE method was easy to handle and showed good reproducibility. CE method was compared with conventional coloring and HPLC methods, and main advantages of CE method were low amount of sample required, simple pre-sample treatment, good recovery rate, and short analysis time.

• Korean journal of applied entomology
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• v.60 no.3
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• pp.263-268
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• 2021

The venom of honeybees (Apis mellifera L.) is used to treat many diseases because of its anti-inflammatory and analgesic effects. Bee venom consists of several biologically active molecules and exhibits remarkable anti-cancer effects. However, biological amines, which exhibit diverse functionality such as anti-inflammatory and antibacterial effects, have not been previously reported in bee venom. In this study, we determined the content of putrescine in bee venom by using ultra-performance liquid chromatography. The specificity, accuracy, and precision of the assay were assessed, and the assay validated. The linearity of the putrescine assay was r ≥ 0.99, indicating a moderate level of putrescine in the bee venom. The limit of detection and limit of quantification were both 0.9 ㎍/mL, while the rate of recovery was 96.4%-99.9%. The relative standard deviation (RSD) of the intra-day precision and inter-day precision of the putrescine assay were 0.16% - 0.23% and 0.09% - 0.36%, respectively, with the RSD ≤ 5% indicating excellent precision. Thus, the linearity, limit of detection, limit of quantification, and recovery rate of the putrescine assay were satisfactory. The analysis of the bee venom showed that the putrescine content was 3.1 ± 0.09 mg/g. This study provides fundamental data on putrescine content in bee venom, which will prove useful in further studies of its bioactivity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.833-835
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• 2014

On this study, we have developed respiratory training system to improve stability of respiration, one of the most important factors of Respiratory Gated Radiation Therapy, RGRT. Respiratory training system that we developed was applied to personal respiratory cycle so that it could provide comfortable respiratory triggering to patients. To give sufficient time for practice, we used modular portable device to practice easily and to be undetered by time and place. We have intended to improve efficiency and accuracy by providing it to patients. We are now planning to conduct experiment of 10 peoples to find out stability, degree of durability betterment and regularity of respiration when patients are using respiratory training system. There are three kinds of breathing style. First is free breathing that Individual patients can breathe freely. Second is guide breathing that patients apply to personal respiration cycle through the guiding sight and hearing program. Third is prediction breathing that patients breathe after respiratory training without guiding sight and hearing program. By using these 3 data of respiration method, we have evaluated usability of respiratory training system by quantitatively analyzing respiration period, amplitude and area's variation.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.45-51
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• 2021

With the development of deep learning, semantic segmentation methods are being studied in various fields. There is a problem that segmenation accuracy drops in fields that require accuracy such as medical image analysis. In this paper, we improved PSPNet, which is a deep learning based segmentation method to minimized the loss of features during semantic segmentation. Conventional deep learning based segmentation methods result in lower resolution and loss of object features during feature extraction and compression. Due to these losses, the edge and the internal information of the object are lost, and there is a problem that the accuracy at the time of object segmentation is lowered. To solve these problems, we improved PSPNet, which is a semantic segmentation model. The multi-scale attention proposed to the conventional PSPNet was added to prevent feature loss of objects. The feature purification process was performed by applying the attention method to the conventional PPM module. By suppressing unnecessary feature information, eadg and texture information was improved. The proposed method trained on the Cityscapes dataset and use the segmentation index MIoU for quantitative evaluation. As a result of the experiment, the segmentation accuracy was improved by about 1.5% compared to the conventional PSPNet.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.775-780
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• 2024

In this study, a simultaneous analysis method was developed using reversed-phase high-performance liquid chromatography(RP-HPLC) for the main components of motion sickness medication: Dimenhydrinate, Caffeine, Methyl Paraben, and Propyl Paraben. The analysis was conducted after pretreating the four components, utilizing a C18 column with Acetonitrile and H₂O as the mobile phase. UV detection was carried out at a wavelength of 254nm. As a result of the experiment, the values of Resolution(Rs) was well over Rs > 1.5, which indicates that the separation of the four components was efficient. Additionally, the symmetry factor of the components was 0.989, 1.120, 1.256, and 1.280, respectively, showing their symmetrical stability. In the stability assessment, the calibration curves for the four components showed excellent linearity with R² > 0.9991 to 0.9998. Furthermore, the limit of detection(LOD) ranged between 0.017 to 3.060㎍/ml, while the limit of quantification(LOQ) ranged between 0.050 to 9.180 ㎍/ml. The recovery rates range from 98.28% to 101.71%, and repeatability showed precision within the range of 0.447 to 0.550, and robustness confirmed values with %RSD < 2. The quantitative analysis results of this study demonstrated the effectiveness of a simultaneous analysis method for motion sickness medication components.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.1-21
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• 2021

As the global business environment changes, uncertainties in technology development and market needs increase, and competition among companies intensifies, interests and demands for R&D activities of individual companies are increasing. In order to cope with these environmental changes, R&D companies are strengthening R&D investment as one of the means to enhance the qualitative competitiveness of R&D while paying more attention to facility investment. As a result, facilities or R&D investment elements are inevitably a burden for R&D companies to bear future uncertainties. It is true that the management strategy of increasing investment in R&D as a means of enhancing R&D capability is highly uncertain in terms of corporate performance. In this study, the structural factors that influence the R&D capabilities of companies are explored in terms of technology management capabilities, R&D capabilities, and corporate classification attributes by utilizing data mining techniques, and the characteristics these individual factors present according to the level of R&D capabilities are analyzed. This study also showed cluster analysis and experimental results based on evidence data for all domestic R&D companies, and is expected to provide important implications for corporate management strategies to enhance R&D capabilities of individual companies. For each of the three viewpoints, detailed evaluation indexes were composed of 7, 2, and 4, respectively, to quantitatively measure individual levels in the corresponding area. In the case of technology management capability and R&D capability, the sub-item evaluation indexes that are being used by current domestic technology evaluation agencies were referenced, and the final detailed evaluation index was newly constructed in consideration of whether data could be obtained quantitatively. In the case of corporate classification attributes, the most basic corporate classification profile information is considered. In particular, in order to grasp the homogeneity of the R&D competency level, a comprehensive score for each company was given using detailed evaluation indicators of technology management capability and R&D capability, and the competency level was classified into five grades and compared with the cluster analysis results. In order to give the meaning according to the comparative evaluation between the analyzed cluster and the competency level grade, the clusters with high and low trends in R&D competency level were searched for each cluster. Afterwards, characteristics according to detailed evaluation indicators were analyzed in the cluster. Through this method of conducting research, two groups with high R&D competency and one with low level of R&D competency were analyzed, and the remaining two clusters were similar with almost high incidence. As a result, in this study, individual characteristics according to detailed evaluation indexes were analyzed for two clusters with high competency level and one cluster with low competency level. The implications of the results of this study are that the faster the replacement cycle of professional managers who can effectively respond to changes in technology and market demand, the more likely they will contribute to enhancing R&D capabilities. In the case of a private company, it is necessary to increase the intensity of input of R&D capabilities by enhancing the sense of belonging of R&D personnel to the company through conversion to a corporate company, and to provide the accuracy of responsibility and authority through the organization of the team unit. Since the number of technical commercialization achievements and technology certifications are occurring both in the case of contributing to capacity improvement and in case of not, it was confirmed that there is a limit in reviewing it as an important factor for enhancing R&D capacity from the perspective of management. Lastly, the experience of utility model filing was identified as a factor that has an important influence on R&D capability, and it was confirmed the need to provide motivation to encourage utility model filings in order to enhance R&D capability. As such, the results of this study are expected to provide important implications for corporate management strategies to enhance individual companies' R&D capabilities.

• Geophysics and Geophysical Exploration
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• v.19 no.1
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• pp.1-10
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• 2016

The hypocenter distribution of microseismic events generated by hydraulic fracturing for shale gas development provides essential information for understanding characteristics of fracture network. In this study, we evaluate how inaccurate velocity models influence the inversion results of two widely used location programs, hypoellipse and hypoDD, which are developed based on an iterative linear inversion. We assume that 98 stations are densely located inside the circle with a radius of 4 km and 5 artificial hypocenter sets (S0 ~ S4) are located from the center of the network to the south with 1 km interval. Each hypocenter set contains 25 events placed on the plane. To quantify accuracies of the inversion results, we defined 6 parameters: difference between average hypocenters of assumed and inverted locations, $d_1$; ratio of assumed and inverted areas estimated by hypocenters, r; difference between dip of the reference plane and the best fitting plane for determined hypocenters, ${\theta}$; difference between strike of the reference plane and the best fitting plane for determined hypocenters, ${\phi}$; root-mean-square distance between hypocenters and the best fitting plane, $d_2$; root-mean-square error in horizontal direction on the best fitting plane, $d_3$. Synthetic travel times are calculated for the reference model having 1D layered structure and the inaccurate velocity model for the inversion is constructed by using normal distribution with standard deviations of 0.1, 0.2, and 0.3 km/s, respectively, with respect to the reference model. The parameters $d_1$, r, ${\theta}$, and $d_2$ show positive correlation with the level of velocity perturbations, but the others are not sensitive to the perturbations except S4, which is located at the outer boundary of the network. In cases of S0, S1, S2, and S3, hypoellipse and hypoDD provide similar results for $d_1$. However, for other parameters, hypoDD shows much better results and errors of locations can be reduced by about several meters regardless of the level of perturbations. In light of the purpose to understand the characteristics of hydraulic fracturing, $1{\sigma}$ error of velocity structure should be under 0.2 km/s in hypoellipse and 0.3 km/s in hypoDD.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.452-458
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• 2019

Coix lacryma-jobi var. ma-yuen (Rom. Caill.) Stapf (CL), which contains riboflavin and coixol, has traditionally been used to treat cancer and arthritis. However, no method for the simultaneous determination of riboflavin and coixol in CL sprouts has been established. In this study, we established and validated a high-performance liquid chromatography-diode array detection (HPLC-DAD) method for the identification and quantification of two reference markers, riboflavin and coixol, in CL sprout extracts. CL sprouts (whole sprouts and leaves) were subjected to extraction with 70% ethanol at room temperature and at 80 ℃ under reflux conditions. The two extractions were validated with respect to specificity, accuracy, precision, and linearity. The content of the two reference markers was highest in leaves extracted under reflux conditions (riboflavin, 8.23 ± 0.32 mg/g; coixol, 5.95 ± 0.04 mg/g). We also investigated the antioxidant activity of the extracts via 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS⁺) scavenging assays. The results indicated that extracts obtained from sprouts under reflux conditions had the strongest antioxidative effects (DPPH half maximal inhibitory concentration [IC₅₀], 68.9 ± 4.1 g/mL; and ABTS, IC₅₀, 34.9 ± 0.1 g/mL). These results can serve as baseline data for the simultaneous determination of the two reference marker compounds, riboflavin and coixol, and development of functional food materials using CL sprouts.