• Journal of Korean Society of Coastal and Ocean Engineers
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• v.14 no.2
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• pp.136-150
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• 2002

To improve the water quality of the recently constructed Siwhaho, sluice gates were operated to allow free exchange of water with the sea. This estuarine lake connected to the outer sea through narrow gates is affected mainly by flushing by gate operation and river flows and wind forcing sometimes. As a predicting tool far the water qualities, a three-dimensional finite volume model CE-QUAL-ICM is incorporated into a finite element hydrodynamic model, TIDE3D. In coupling these two different modules, a new error minimization technique is applied by considering conservation of mass. Model tests for one year after calibration and validation using field observation show that eutrophication and other biological changes reach quasi-steady state after initial 60 days of simulation, thus it would be necessary to consider moderate ramp up option to remove initial uncertainties due to cold start option. Sediment-water interaction might not be a concern in the long-term simulation, since its effect is negligible. Simulated results show the newly applied scheme can be applied with satisfaction not only fur lessening of eutrophic processes in an estuarine lake but also looking for some active circulation to improve water quality.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.4
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• pp.333-339
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• 2016

The objective of this study was to optimize analytical methods for ochratoxin A (OTA) and zearalenone (ZEA) in rice straw silage and winter forage crops using ultra-high performance liquid chromatography (UHPLC). Samples free of mycotoxins were spiked with $50{\mu}g/kg$, $250{\mu}g/kg$, or $500{\mu}g/kg$ of OTA and $300{\mu}g/kg$, $1500{\mu}g/kg$, or $3000{\mu}g/kg$ of ZEA. OTA and ZEA were extracted by acetonitrile and cleaned-up using an immunoaffinity column. They were then subjected to analysis with UHPLC equipped with a fluorescence detector. The correlation coefficients of calibration curves showed high linearity ($R^2{\geq_-}0.9999$ for OTA and $R^2{\geq_-}0.9995$ for ZEA). The limit of detection and quantification were $0.1{\mu}g/kg$ and $0.3{\mu}g/kg$, respectively, for OTA and $5{\mu}g/kg$ and $16.7{\mu}g/kg$, respectively, for ZEA. The recovery and relative standard deviation (RSD) of OTA were as follows: rice straw = 84.23~95.33%, 2.59~4.77%; Italian ryegrass = 79.02~95%, 0.86~5.83%; barley = 74.93~97%, 0.85~9.19%; rye = 77.99~96.67%, 0.33~6.26%. The recovery and RSD of ZEA were: rice straw = 109.6~114.22%, 0.67~7.15%; Italian ryegrass = 98.01~109.44%, 1.65~4.81%; barley = 98~113.53%, 0.25~5.85%; rye = 90.44~108.56%, 2.5~4.66%. They both satisfied the standards of European Commission criteria (EC 401-2006) for quantitative analysis. These results showed that the optimized methods could be used for mycotoxin analysis of forages.

• The Korean Journal of Pesticide Science
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• v.18 no.4
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• pp.269-277
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• 2014

The multiclass pesticide multiresidue method for the simultaneous determination of diflubenzuron in agricultural products was conducted by using HPLC-UVD. The method was validated through the guidelines of linearity, specificity, limit of detection (LOD), limit of quantification (LOQ), accuracy and precision with pesticide-free spinach, Korean cabbage, eggplant, squash, sweet pepper, cucumber, Korean melon. The calibration curve of diflubenzuron was linear over the concentration range of 0.05-5 mg/kg with correlation coefficient of above 0.99999. The limit of detection and quantification was 0.008 and 0.02 mg/kg. Mean recoveries of diflubenzuron for each sample were 77.5-105.6%. Relative standard deviation (RSD) in recoveries were all less than 20%. The intra-day and inter-day precision (RSD) were 0.4-1.9% and 0.7-1.9%, respectively. The result of validation indicated that this method was accurate and rapid assay.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.283-289
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• 2019

This study was performed to monitor the residual pesticides in agricultural products used in school foodservice in the Gwangju metropolitan area. Risk assessment was also carried out based on the amount of agricultural products consumed. A total of 320 agricultural products supplied to schools in Gwangju were analyzed from 2015 to 2017. The pre-treatment and residual pesticide analysis of these products was conducted in accordance with the second method for multi-residue analysis of pesticides in the Korean food code. The hazard index was calculated by dividing the estimated daily intake (EDI) of pesticides by the acceptable daily intake (ADI). The linearity correlation coefficient for the calibration curve was 0.9923 to 1.0000, LOD 0.004 to 0.019 mg/kg, LOQ 0.012 to 0.057 mg/kg, and recovery was 79.1 to 100.2%. Residual pesticides were detected in 18 (5.6%) of 320 agricultural products used for school foodservice, and one sample of sweet potato stem (0.3%) exceeded the maximum residual limit (MRL). The detection frequency for chili peppers and bell peppers was higher than that for other agricultural products. The frequently-detected pesticides were boscalid and acetamiprid. These results showed that residual pesticide management is needed for chili pepper, bell pepper and sweet potato stem among agricultural products supplied to schools. The hazard index of bifenthrin in sweet potato stem showed the highest (64.18%), and the other pesticides were 0.03-8.23%. These results indicated that agricultural products supplied to schools in Gwangju were safe for consumption. To minimize the intake of residual pesticides, it is necessary to not only thoroughly wash agricultural products but to also ensure the expanded supply of products that are pesticide-free.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.