• Journal of Ginseng Research
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• v.43 no.4
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• pp.600-605
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• 2019

Background: The leaves and roots of Panax ginseng are rich in ginsenosides. However, the chemical compositions of the leaves and roots of P. ginseng differ, resulting in different medicinal functions. In recent years, the aerial parts of members of the Panax genus have received great attention from natural product chemists as producers of bioactive ginsenosides. The aim of this study was the isolation and structural elucidation of novel, minor ginsenosides in the leaves of P. ginseng and evaluation of their antiinflammatory activity in vitro. Methods: Various chromatographic techniques were applied to obtain pure individual compounds, and their structures were determined by nuclear magnetic resonance and high-resolution mass spectrometry, as well as chemical methods. The antiinflammatory effect of the new compounds was evaluated on lipopolysaccharide-stimulated RAW 264.7 cells. Results and conclusions: Two novel, minor triterpenoid saponins, ginsenoside $LS_1$ (1) and 5,6-didehydroginsenoside $Rg_3$ (2), were isolated from the leaves of P. ginseng. The isolated compounds 1 and 2 were assayed for their inhibitory effect on nitric oxide production in LPS-stimulated RAW 264.7 cells, and Compound 2 showed a significant inhibitory effect with $IC_{50}$ of $37.38{\mu}M$ compared with that of NG-monomethyl-L-arginine ($IC_{50}=90.76{\mu}M$). Moreover, Compound 2 significantly decreased secretion of cytokines such as prostaglandin $E_2$ and tumor necrosis factor-${\alpha}$. In addition, Compound 2 significantly suppressed protein expression of inducible nitric oxide synthase and cyclooxygenase-2. These results suggested that Compound 2 could be used as a valuable candidate for medicinal use or functional food, and the mechanism is warranted for further exploration.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.347-358
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• 2019

Lambertian cloud model (Lambertian Cloud Model) is the simplified cloud model which is used to effectively retrieve the vertical ozone distribution of the atmosphere where the clouds exist. By using the Lambertian cloud model, the optical characteristics of clouds required for radiative transfer simulation are parametrized by Optical Centroid Cloud Pressure (OCCP) and Effective Cloud Fraction (ECF), and the accuracy of each parameter greatly affects the radiation simulation accuracy. However, it is very difficult to generalize the vertical ozone error due to the OCCP error because it varies depending on the radiation environment and algorithm setting. In addition, it is also difficult to analyze the effect of OCCP error because it is mixed with other errors that occur in the vertical ozone calculation process. This study analyzed the ozone retrieval error due to OCCP error using two methods. First, we simulated the impact of OCCP error on ozone retrieval based on Optimal Estimation. Using LIDORT radiation model, the radiation error due to the OCCP error is calculated. In order to convert the radiation error to the ozone calculation error, the radiation error is assigned to the conversion equation of the optimal estimation method. The results show that when the OCCP error occurs by 100 hPa, the total ozone is overestimated by 2.7%. Second, a case analysis is carried out to find the ozone retrieval error due to OCCP error. For the case analysis, the ozone retrieval error is simulated assuming OCCP error and compared with the ozone error in the case of PROFOZ 2005-2006, an OMI ozone profile product. In order to define the ozone error in the case, we assumed an ideal assumption. Considering albedo, and the horizontal change of ozone for satisfying the assumption, the 49 cases are selected. As a result, 27 out of 49 cases(about 55%)showed a correlation of 0.5 or more. This result show that the error of OCCP has a significant influence on the accuracy of ozone profile calculation.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.235-241
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• 2019

An analytical method was developed for the determination of an antibiotic fungicide, kasugamycin, in agricultural products (hulled rice, potato, soybean, mandarin and green pepper) using liquid chromatographytandem mass spectrometry (LC-MS/MS). Samples were extracted with methanol adjusted to pH 13 using 1 N sodium hydroxide, and purified with a HLB (hydrophilic lipophilic balance) cartridge. Linearity of a matrix-matched calibration curve using seven concentration levels, from 0.001 to 0.1 mg/kg, was excellent with a correlation coefficient ($R^2$) of more than 0.9998. The limits of detection (LOD) and quantification (LOQ) of instrument were 0.0005 and $0.001{\mu}g/mL$, respectively, and the LOQ of analytical method calculated as 0.01 mg/kg. The average recoveries at three spiking levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n=5) were in the range of 71.2~95.4% with relative standard deviation of less than 12.1%. The developed method was simple and all optimized results was satisfied with the criteria ranges requested in the Codex guidelines and Food Safety Evaluation Department guidelines. The present study could be served as a reference for the establishment of maximum residue limits (MRL) of kasugamycin and be used as basic data for safety management relative to kasugamycin residues in imported and domestic agricultural products.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.242-250
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• 2019

An analytical method was developed for the determination of fenquinotrione, a triketone herbicide, in agricultural products. Fenquinotrione was metabolized to KIH-3653-M-2 in plants. Analyte extraction was conducted using 2% formic acid in acetonitrile and cleaned up using a hydrophillic-lipophillic balance (HLB) cartridge. The limits of detection (LOD) and quantification (LOQ) were 0.004 and 0.01 mg/kg, respectively. Matrix-matched calibration curves were linear over the calibration ranges ($0.001{\sim}0.1{\mu}g/mL$) into a blank extract with $r^2>0.99$. The recovery results for fenquinotrione and KIH-3653-M-2 ranged between 81.1 to 116.2% and 78.0 to 110.0% at different concentration levels (LOQ, $10{\times}LOQ$, $50{\times}LOQ$) with relative standard deviation (RSD) less than 4.6%. All values were corresponded with the criteria ranges requested in both the Codex (CAC/GL 40-1993, 2003) and MFDS guidelines (2016). Therefore, the proposed method can be used as an official analytical method for determination of fenquinotrione in the Republic of Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.65-73
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• 2019

The MODIS (Moderate Resolution Imaging Spectroradiometer) data in Hierarchical Data Format (HDF) have been processed using the Geospatial Data Abstraction Library (GDAL). Because of a relatively large data size, it would be preferable to build and install the data analysis tool with greater computing performance, which would differ by operating system and the form of distribution, e.g., source code or binary package. The objective of this study was to examine the performance of the GDAL for processing the HDF files, which would guide construction of a computer system for remote sensing data analysis. The differences in execution time were compared between environments under which the GDAL was installed. The wall clock time was measured after extracting data for each variable in the MODIS data file using a tool built lining against GDAL under a combination of operating systems (Ubuntu and openSUSE), compilers (GNU and Intel), and distribution forms. The MOD07 product, which contains atmosphere data, were processed for eight 2-D variables and two 3-D variables. The GDAL compiled with Intel compiler under Ubuntu had the shortest computation time. For openSUSE, the GDAL compiled using GNU and intel compilers had greater performance for 2-D and 3-D variables, respectively. It was found that the wall clock time was considerably long for the GDAL complied with "--with-hdf4=no" configuration option or RPM package manager under openSUSE. These results indicated that the choice of the environments under which the GDAL is installed, e.g., operation system or compiler, would have a considerable impact on the performance of a system for processing remote sensing data. Application of parallel computing approaches would improve the performance of the data processing for the HDF files, which merits further evaluation of these computational methods.

• Journal of the Korean Applied Science and Technology
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• v.36 no.1
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• pp.324-332
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• 2019

Most countries including Korea and Indonesia have strong policy for implementing biofuels like biodiesel. Shortage of the oil feedstock is the main barrier for increasing the supply of biodiesel fuel. In this study, in order to improve the stability of feedstock supply and lower the biodiesel production cost, the feasibility of biodiesel production using two types of Indonesian tropical crop oils, pressed at different harvesting times, were investigated. R. Trisperma oils, a high productive non-edible feedstocks, were investigated to produce biodiesel by esterification and transesterification because of it's high impurity and free fatty acid contents. the kindly provided oils from Indonesia were required to perform the filtering and water removal process to increase the efficiency of the esterificaton and transesterification reactions. The esterification used heterogeneous acid catalyst, Amberlyst-15. Before the reaction, the acid value of two types oil were 41, 17 mg KOH/g respectively. After the pre-esterification reaction, the acid value of oils were 3.7, 1.8 mg KOH/g respectively, the conversions were about 90%. Free fatty acid content was reduced to below 2%. Afterwards, the transesterification was performed using KOH as the base catalyst for transesterification. The prepared biodiesel showed about 93% of FAME content, and the total glycerol content was 0.43%. It did not meet the quality specification(FAME 96.5% and Total glycerol 0.24%) since the tested oils were identified to have a uncommon fatty acid, generally not found in vegetable oils, ${\alpha}$-eleostearic acid with much contents of 10.7~33.4%. So, it is required to perform the further research on reaction optimization and product purification to meet the fuel quality standards. So if the biodiesel production technology using un-utilized non-edible feedstock oils is successfully developed, stable supply of the feedstock for biodiesel production may be possible in the future.

• Management & Information Systems Review
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• v.38 no.1
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• pp.201-223
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• 2019

The purpose of this study is to verify empirically the causal relationship between service quality, ease of use, customer satisfaction, and repurchase intention of mobile shopping mall. And this study is to investigate the ease of use and customer satisfaction mediating effect of between service quality and repurchase intention. Therefore, 323 university students in Jeonnam area were surveyed and the structural equation model was derived based on previous research. Service quality of mobile shopping mall make a significant effect on using easiness, purchasing satisfaction and repurchase intention. However, among service quality of mobile shopping mall, service scape like mobile interface and site design made a positive effect on purchasing satisfaction, but did not any effect on repurchase intention. In other words, service quality factors that make positive effects on customer's pleasant using and repurchase intention make a positive effect on repurchase intention when providing and using the service customer wants faithfully rather than external part of the site and mutually influencing attitude or behavior well. The implications suggested by this study are as follows. First, service quality of mobile shopping mall makes a significant effect on repurchase intention, so it's necessary to improve CS service system so as to treat customers' inquiries or inconveniences actively during mobile shopping and return and refund of defective products quickly and conveniently. And, in addition to the finally used factors in analysis process, benefits using customers' grade by number of purchases, such as various events, coupons, reserve, etc. and active contents marketing strategies providing more various pleasures and values of shopping are necessary. Second, satisfaction of mobile shopping mall makes a positive effect on repurchase intention, so visiting of site and repurchasing of product are continuously done as customers' satisfaction on shopping mall is increasing. Therefore, shopping mall site requires differentiation of contents, exact plan and practice of service, marketing, etc. so that customers can feel more satisfaction. This study is significant as it systematically analyzed concepts of components that service quality of mobile shopping mall makes an effect on using easiness, purchasing satisfaction, and repurchase intention, verified the relations, systematized it by theoretical structure, and widened the understanding of effects making an effect on repurchase intention.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.296-302
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• 2019

Ganjang-gejang (soy sauce-marinated crab) is a ready-to-eat (RTE) seafood and is also one of the most popular traditional dishes in Korea. It is generally prepared by washing raw blue crabs and then preserving them in soy sauce. Since this process does not involve cooking or any treatment with heat, it is difficult to control the microbiological quality of the final product. Thus, the objectives of this study were to compare the efficacies of various sanitizers in eliminating microorganisms on raw blue crab during the washing step and to evaluate the effectiveness of chitosan on the inhibition of microbial growth in the ganjang-gejang during storage. The raw blue crabs were submerged in chlorinated water (50 mg/L), peracetic acid (40 mg/L), acetic acid (5%) and lactic acid (5%) for 10 min at $25^{\circ}C$, respectively. The blue crabs treated with 5% acetic acid were marinated with soy sauce containing 0.5 and 1% of soluble chitosan, followed by storing them at 4 and $12^{\circ}C$ for up to 30 days. Results show that 5% acetic acid reduced the microbial populations on the blue crabs by 1.5 log CFU/g, which was significantly higher than those of other treatments. Based on these results, 5% acetic acid was selected for the washing step. The microbial populations of all ganjang-gejang samples significantly increased to about 8.0 CFU/g at $12^{\circ}C$ for 7 days. At $4^{\circ}C$, the microbial populations of the products containing 1% chitosan increased by about 2.9 CFU/g for 20 days, which were significantly lower than those (4.2-4.5 log CFU/g) of the products without and with 0.5% chitosan. Thus, these results suggest that 5% acetic acid washing of raw blue crabs and the addition of 1% chitosan in ganjang-gejang could improve the microbiological quality of the final products under refrigerated condition.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.140-147
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• 2019

An analytical method was developed for the determination of quinoxyfen in agricultural products using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The samples were extracted with 1% acetic acid in acetonitrile and water was removed by liquid-liquid partitioning with $MgSO_4$ (anhydrous magnesium sulfate) and sodium acetate. Dispersive solid-phase extraction (d-SPE) cleanup was carried out using $MgSO_4$, PSA (primary secondary amine), $C_{18}$ (octadecyl) and GCB (graphitized carbon black). The analytes were quantified and confirmed by using LC-MS/MS in positive mode with MRM (multiple reaction monitoring). The matrix-matched calibration curves were constructed using six levels ($0.001-0.25{\mu}g/mL$) and the coefficient of determination ($R^2$) was above 0.99. Recovery results at three concentrations (LOQ, 10 LOQ, and 50 LOQ, n=5) were in the range of 73.5-86.7% with RSDs (relative standard deviations) of less than 8.9%. For inter-laboratory validation, the average recovery was 77.2-95.4% and the CV (coefficient of variation) was below 14.5%. All results were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for quinoxyfen determination in agricultural commodities. This study could be useful for the safe management of quinoxyfen residues in agricultural products.