• Korean Chemical Engineering Research
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• v.44 no.2
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• pp.166-171
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• 2006

In this study, in using a piezoelectric material of $Pb(Mg_{1/3}Nb_{2/3})O_3-PbTiO_3$ (PMN-PT), which has a high electromechanical coupling coefficient, we have tried to study about this material can be practically available as a new biosensor to detect protein by using surface acoustic wave (SAW). As the results, the filtering of the center frequency of the PMN-PT substrate is a superior result to that of the $LiTaO_3$ (LT) substrate, but the result was not completely satisfactory. Also this study attempts to develop a sensing method to detect mismatched DNA in order to diagnose cancer. We could directly immobilize the MutS to the NTA using the EDC solution. But, we immobilized MutS using nickel and it is judged that is more effective method to detect mismatched DNA.

• Journal of the Korea Organic Resources Recycling Association
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• v.9 no.1
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• pp.56-64
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• 2001

Composting of livestock feces is economic and safe process to decrease the possibility of direct leakage of organic pollutants to ecosystem from commercial and environmental point of view. This study was conducted with three different experiments related to composting of livestock feces. The purpose of experiment 1 was to investigate changes of characteristic of compost pile during composting period by low temperature in cold season. To compare composting effect of experimental compost pile and control pile exposed in cold air, experimental compost piles were warmed up by hot air until their temperatures were reached at $35^{\circ}C$. Sawdust, Ricehull and Ricestraw were mixed with livestock feces as bulking agent. The highest temperatures of compost pile during composting period were in sawdust, rice hull, rice straw, and control were $75^{\circ}C$, $76^{\circ}C$, $68^{\circ}C$, $45^{\circ}C$ respectively. Moisture content, pH, C/N and volume of compost were decreased during composting period. Experiment 2 was carried out to study utilization effect of compost by plant. A corn was cultivated for 3 years on fertilized land with compost and chemical fertilizer. The amount of harvest and nutrition value of corn were analyzed. In first year of trial, the amount of harvest of corn on land treated with compost was lower by 20% than that of land treated with chemical fertilizer. In second year, there was no difference in yield of com between compost and chemical fertilizer. In third year, the yield of com on land fertilized with compost was much more than that of land fertilized with chemical fertilizer. The purpose of experiment 3 was to estimate the decrease of malodorous gas originating from livestock feces by bio-filter. Four types of bio-filters filled with saw dust, night soil, fermented compost and leaf mold were manufactured and tested. Each bio-filter achieved 87-95% $NH_3$ removal efficiency. This performance was maintained for 10 days. The highest $NH_3$ removal efficiency was achieved by leaf mold on the first day of operation period. It reduced the concentration of $NH_3$ by about 95%. Night soil and fermented compost showed nearly equal performance of 93 to 94% for 10 days from the beginning of operation. The concentration of hydrogen sulfide and methyl mercaptan originating for compost were equal to or less than $3mg/{\ell}$ and $2mg/{\ell}$, respectively. After passing throughout the bio-filter, hydrogen sulfide and methyl mercaptan were not detected.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.20 no.2
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• pp.89-94
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• 1987

The fluctuations of sea surface temperatures (SST) and their anomalies in the Tsushima Current region are studied by means of empirical orthogonal function (EOF) analysis of the monthly SST data for 30 years (1941-1970) at 8 coastal stations. The overall features of the seasonal variation of SST are described by the first EOF mode, which explains $97.2\%$ of the total variance. Annual ranges of seasonal variation of SST and root-mean-square amplitudes of SST anomalies in the downstream of the Tsushima Current are larger than those in the upstream. The SST anomalies in the Tsushima Current region consist of simultaneous fluctuations, which explain $40.9\%$ of the total variance, and 'see-saw' fluctuations of which rise and fall in the upstream are opposite to those in the downstream. The latter second EOF mode explains $19.3\%$ of the total variance. We generated the low-pass (periods longer than 24 months), band-pass (periods between 6 and 24 months) and high-pass (periods shorter than 6 months) SST anomaly series and analyzed them by EOF method. The spatial distributions of the first and second EOF modes of all filtered SST anomalies are similar to each other.

• 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.