• 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.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.158-169
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• 2019

Ergot alkaloids are mycotoxin produced by fungi of the Claviceps genus, mainly by Claviceps purpurea in EU. Recently obtained informations indicates necessity for control the ergot in imported grains. Recent occurrence data of ergot alkaloids from EU countries indicate the necessities of management and control these toxins from the imported grains like rye, wheat, oat etc. The aim of this study is to optimize the liquid chromatography-tandem mass spectrometry method for determination of ergot alkaloids (ergometrine, ergosine, ergotamine, ergocornine, ergocryptine, ergocristine and their epimers (-inines) from grain and grain-based food. The test method was optimized by extracting the sample with acetonitrile containing 2 mM ammonium carbonate, purification with Mycosep cartridge, and instrumental analysis by LC-MS/MS using Syncronis C18 column. The standard calibration curves showed linearity with correlation coefficents; $R^2$ >0.99. Mean recoveries ranged from 72.0 to 111.3% at three different fortified levels (20, 50, and $100{\mu}g/kg$). The correlation coefficient expressed as precision was within the range of 1.9-12.9%. The limit or quantifications (LOQ) ranged from 0.012 to $0.058{\mu}g/kg$. The developed analytical method met the criteria of AOAC Int. and CAC validation parameters like accuracy and sensitivity. As a result, it was confirmed that the test method developed in this study is suitable for the simultaneous analysis of six species of ergot alkaloid from grains and grain products.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.115-123
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• 2019

An analytical method was developed for the determination of fenpropimorph, a morpholine fungicide, in hulled rice, potato, soybean, mandarin and green pepper using QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) sample preparation and LC-MS/MS (liquid chromatography-tandem mass spectrometry). The QuEChERS extraction was performed with acetonitrile followed by addition of anhydrous magnesium sulfate and sodium chloride. After centrifugation, d-SPE (dispersive solid phase extraction) cleanup was conducted using anhydrous magnesium sulfate, primary secondary amine sorbents and graphitized carbon black. The matrix-matched calibration curves were constructed using seven concentration levels, from 0.0025 to 0.25 mg/kg, and their correlation coefficient ($R^2$) of five agricultural products were higher than 0.9899. The limits of detection (LOD) and quantification (LOQ) were 0.001 and 0.0025 mg/kg, respectively, and the limits of quantification for the analytical method were 0.01 mg/kg. Average recoveries spiked at three levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n=5) and were in the range of 90.9~110.5% with associated relative standard deviation values less than 5.7%. As a result of the inter-laboratory validation, the average recoveries between the two laboratories were 88.6~101.4% and the coefficient of variation was also below 15%. All optimized results were satisfied the criteria ranges requested in the Codex guidelines and Food Safety Evaluation Department guidelines. This study could serve as a reference for safety management relative to fenpropimorph residues in imported and domestic agricultural products.

• Journal of Bio-Environment Control
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• v.28 no.2
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• pp.134-142
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• 2019

This study was conducted to evaluate the growth characteristics of lettuce (Lactuca sativa L.) as affected by artificial light sources and different growing media in a closed-type plant production system (CPPS). The lettuce seeds were sown in the 128-cell plug tray filled with 5 different growing media such as urethane sponge (US), rock-wool (RW), Q-plug (QP), TP-S2 (TP) and PU-7B (PU). The germination rate of lettuce seeds was examined during 12 days after sowing. On the 13 days after sowing, the lettuce seedlings were transplanted in a CPPS with temperature $25{\pm}1^{\circ}C$ and nutrient solution (EC $2.0dS{\cdot}m^{-1}$, pH 6.5) using recirculating deep floating technique system. The light sources were set with FL (fluorescent lamps) and combined RB LEDs (red : blue = 7 : 3) with $150{\pm}10{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ PPFD and a photoperiod of 14/10 hours (light/dark). The initial germination rate of lettuce was the highest in TP. The final germination and mean daily germination were the significantly highest in RW, QP and TP. The plant height, leaf length, leaf width, leaf area, and fresh and dry weights of shoot were the greatest in QP irradiated with RB LED. The number of leaves, fresh and dry weights of root and SPAD were the greatest in QP and TP irradiated with RB LED. The root length was the longest in TP irradiated with RB LED. Therefore, these results indicate that RB LED was effective for the growth of lettuce and it was also found that the QP and TP were effective for the germination and growth of lettuce in a CPPS. In addition, we confirmed the applicability of the newly developed growing medium TP for the lettuce production in a CPPS.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.292-299
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• 2018

In a survey in which farmers were asked about their levels of satisfaction with agricultural machines, Japanese products scored higher than local products by 1.2, 1.3, and 1.4 times for tractors, combine harvesters, and rice transplanter, respectively. Japanese products corresponded to generally high satisfaction levels in terms of operating performance, operability, frequency of breakdowns, and durability, excluding sales price and after-sales services. Effective countermeasures through quality improvement are therefore necessary for Korean products. Furthermore, a survey of dealers showed that the components and consumables for core agricultural machines had high frequencies of breakdowns and repairs. Four major components of tractors represented 85.3% of all breakdowns and repairs, five components of combine harvesters represented 89.6%, and three components of rice transplanters represented 80.5%. Moreover, a comparison of the technological levels between local and imported machines showed that the local machines' levels were at 60-100% for tractors, 70-100% for combine harvesters, and 70-95% for rice transplanters. Small and mid-sized tractors, 4 interrow combine harvesters, and 6 interrow rice transplanters showed similar levels of technology. The results of the analysis suggest that action is urgently needed at a policy level to establish an agricultural machinery component research center for the development, production, and supply of commonly-used components, with the participation of manufacturers of agricultural machines and components, in order to enhance the competitiveness of local manufacturers and to revitalize the agricultural machine market.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.5
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• pp.15-29
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• 2021

This study is based on ERIS model for start-up performance, and aims to derive the main reason for start-up sustainability centered on organizational resilience. To this end, systematic literature examination and modified Delphi method were used to investigate start-up sustainability factors based on ERIS Model focused on organizational resilience. The results showed that ERIS model-based entrepreneurial continuity factors were divided into four categories: entrepreneur, resource, industrial environment, strategy, subdivision 8 and detailed factors 54. In addition, the ERIS model-based continuity factors were structured around organizational resilience, and the continuity factors were structured according to ERIS model under five categories: leadership, culture, people, system and environment. The results of this study are as follows. First of all, the results of existing research and analysis show that the concept of successful start-up and sustainability of start-up are used in various fields. Second, it is confirmed that there are common factors of influence on start-up performance and start-up sustainability based on ERIS model. Third, Delphi method's results showed that the general characteristics of entrepreneurs, such as academic background, education level, gender, age, and business experience did not affect the sustainability of entrepreneurship. This study is significant in that it is based on ERIS model focused on organization resilience, and ERIS-R, which integrates Strategy into System and Organization resilience into R in the field of gradually expanding start-up development and support. It is expected that the results of this study will improve the sustainability of start-up that can predict, prevent, and overcome various crises at any time.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.39 no.3
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• pp.42-55
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• 2021

This study investigated the memories of the natives and the migrants who had been living with the 760-year-old Zelkova serrata located in the Keangnam Apartment Complex in Dogok 1-dong. Place memory is a newly illuminated concept since the 1980s, and is also used as a new research methodology for studying and recording multi-layered memories left in a place based on feelings and traces of vivid memories. The urban development of Gangnam, which began in the 1970s, quickly changed rural to apartment complexes. The natives of Yeokmal were scattered throughout the country, and new migrants moved in. In the process, zelkova serrata was managed in different ways from time to time, and residents also establish relationship in different ways. Natives used to take a rest in the tree or swing at Dan-o, and recognized it as a place to receive the god during the village ritual. In other words, they shared the entire process of life and death and were given various roles depending on the lives of the residents. It is also a direct experience that was experienced in detail and a place where collective memories of residents are melted. On the other hand, with the construction of Keangnam Apartment, the management of zelkova tree has become stricter, making it impossible for migrants to access. Migrants have come to enjoy zelkova serrata visually, and the annual Yeokmal Traditional Festival makes common memories in the city. In addition, many people personified trees and received mental comfort. In addition, the nature of the old big tree was highlighted in the background of the city, and the symbol of "uniqueness and speciality" was newly formed, which led to the formation of pride and attachment. Through the memories of the two subjects' zelkova tree, we were able to examine the memories of the tree value, and management of protected tree in the city.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.5-5
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• 2019

The objectives of this paper are (i) to analyze past trends and future directions of rice production, consumption and trade across the world and (ii) to discuss emerging challenges and future directions in the global rice industry. Rice is a staple food of over half of the world's 7.7 billion people. It is an important economic, social, political, and cultural commodity in most Asian countries. Rice is the $1^{st}$ most widely consumed, $2^{nd}$ largely produced, and $3^{rd}$ most widely grown food crop in the world. It was cultivated by 144 million farms in over 100 countries with harvested area of over 163 million ha producing about 745 million tons paddy in 2018. About 90% of the total rice is produced in Asia. China and India, the biggest rice producers, account for over half of the world's rice production. Between 1960 and 2018, world rice production increased over threefold from 221 to 745 million tons (2.1% per year) due to area expansion from 120 to 163 million ha (0.5% per year) and paddy yield increase from 1.8 to 4.6 t/ha (1.6% per year). The Green Revolution led massive increase in rice production prevented famines, provided food for millions of people, reduced poverty and hunger, and improved livelihoods of millions of Asians. The future increase in rice production must come from yield increase as the scope for area expansion is limited. Rice is the most widely consumed food crop. The world's average per capita milled rice consumption is 64 kilograms providing 19% of daily calories. Asia accounted for 84% of global consumption followed by Africa (7%), South America (3%), and the Middle East (2%). Asia's per capita rice consumption is 100 kilograms per year providing 28% of daily calories. The global and Asian per capita consumption increased from the 1960s to the 1990s but stable afterward. The per capita rice consumption is expected to decline in Asia but increase outside Asia especially in Africa in the future. The total milled rice consumption was about 490 million tons in 2018 and projected to reach 550 million tons by 2030 and 590 million tons by 2040. Rice is thinly traded in international market because it is a highly protected commodity. Only about 9% of the total production is traded in global rice market. However, the volume of global rice trade has increased over six-fold from 7.5 to 46.5 million tons between the 1960s and 2018. A relatively small number of exporting countries interact with a large number of importing countries. The top five rice exporting countries are India, Thailand, Vietnam, Pakistan, and China accounting for 74% of the global rice export. The top five rice importing countries are China, Philippines, Nigeria, European Union and Saudi Arabia accounting for 26% of the global rice import. Within rice varieties, Japonica rice accounts for the highest share of the global rice trade (about 12%) followed by Basmati rice (about 10%). The high concentration of exports to a few countries makes international rice market vulnerable to supply disruptions in exporting countries, leading to higher world prices of rice. The export price of Thai 5% broken rice increased from 198 US$/ton in 2000 to 421 US$/ton in 2018. The volumes of trade and rice prices in the global market are expected to increase in the future. The major future challenges of the rice industry are increasing demand due to population growth, rising demand in Africa, economic growth and diet diversification, competition for natural resources (land and water), labor scarcity, climate change and natural hazards, poverty and inequality, hunger and malnutrition, urbanization, low income in rice farming, yield saturation, aging of farmers, feminization of agriculture, health and environmental concerns, improving value chains, and shifting donor priorities away from agriculture. At the same time, new opportunities are available due to access to new technologies, increased investment by the private sector, and increased global partnership. More investment in rice research and development is needed to develop and disseminate innovative technologies and practices to overcome problems and ensure food and nutrition security of the future population.

• Korean Journal of Psychosomatic Medicine
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• v.28 no.2
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• pp.185-193
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• 2020

Objectives : The aim of this study was to develop and to verify the Korean version of the Eating Disorder Diagnosis Scale DSM-5 (K-EDDS) as a web-based diagnostic system, which enables rapid diagnosis of patients for early intervention. Methods : A total of 119 persons participated in the study, including patients with eating disorders (n=38) and college students (n=81). Along with the paper-and-pencil SCOFF, all participants completed the web-based K-EDDS, the Eating Disorder Examination-Questionaire (EDE-Q), and the Clinical Impairment Assessment Questionnaire (CIA). The semi-structured interview using the Eating Disorder Examination Interview (EDE) was conducted for participants with two or more SCOFF scores. Within two weeks, the web-based K-EDDS, the EDE-Q, and the CIA were re-tested. Results : In the exploratory factor analysis, four factors were extracted : body dissatisfaction, binge behaviors, binge frequency and compensatory behaviors. The four subscales of the web-based K-EDDS had significant correlation with each of the four subscales of the EDE-Q. The internal consistency of the web-based K-EDDS was highly satisfactory (Cronbach's alpha=0.93). The diagnostic agreement between the web-based K-EDDS and the EDE was excellent (96.83%), and the web-based K-EDDS's test-retest diagnostic agreement was fairly good (92.86%). The web-based K-EDDS and the CIA also showed significant differences between patients and general population, supporting discriminant validity. Conclusions : This study suggested that the web-based K-EDDS is a valid tool for assisting diagnosis of eating disorders based on DSM-5 in clinical and research fields.