• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• Clinical and Experimental Reproductive Medicine
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• v.31 no.3
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• pp.183-190
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• 2004

Objectives: Methylenetetrahydrofolate reductase (MTHFR) mutation are commonly associated with hyperhomocysteinemia, and through their defects in homocysteine metabolism, they have been implicated as a risk factor for recurrent spontaneous abortion. Recent report describe that 28-bp tandem repeat polymorphism in thymidylate synthase enhancer region (TSER) that influence enzyme activity would affect plasma homocysteine level. We have investigated the relationship between TSER genotype and plasma homocysteine level in 54 patients with recurrent spontaneous abortion. Methods: Plasma homocysteine level was measured by fluorescent polarizing immunoassay. MTHFR mutation (C677T and A1298C) was identified by PCR-restriction fragment length polymorphism assay and TSER mutation was analyzed by PCR method. The data were analyzed using the program SAS 8.2 for Windows. Results: Total homocysteine level was significantly higher in MTHFR 677TT genotype ($9.80{\pm}3.87{\mu}mol/L$) than MTHFR 677CC genotype ($8.14{\pm}1.74{\mu}mol/L$) in Korean patients with unexplained recurrent spontaneous abortion (p=0.0143). However, the plasma homocysteine level was not significantly different in the MTHFR 1298AA ($8.42{\pm}2.65{\mu}mol/L$) and 1298CC ($6.09{\pm}0.32{\mu}mol/L$; p=0.2058) and, TSER 2R2R ($8.61{\pm}1.68{\mu}mol/L$) and 3R3R ($8.05{\pm}2.81{\mu}mol/L$; p=0.9319) mutant genotypes, respectively. In this study, we found the combination effects of TSER and MTHFR C677T genotypes. Plasma homocysteine levels were the highest ($11.47{\pm}4.66{\mu}mol/L$) in individuals with TSER 3R3R ($8.05{\pm}2.81{\mu}mol/L$) and MTHFR 677TT ($9.80{\pm}3.87{\mu}mol/L$) genotypes. Individuals with a combination of both TSER 2R2R/2R3R and MTHFR 677CC/CT genotypes ($7.69{\pm}1.77{\mu}mol/L$) had lower plasma homocysteine levels than TSER 2R2R ($8.61{\pm}1.68{\mu}mol/L$) and MTHR 677CC ($8.14{\pm}1.74{\mu}mol/L$) genotypes, respectively. The effect of MTHFR polymorphism in the homocysteine metabolism appears to be stronger than that of TSER polymorphism. Conclusion: Although statistically not significant, we found the elevated level of plasma homocysteine in combined genotypes with TSER and MTHFR (C677T and A1298C) in Korean patients with unexplained habitual abortion. In this study, we reported the possibility that TSER polymorphism is a genetic determinant of plasma homocysteine levels in the Korean patients as well as MTHFR C677T polymorphism. A large prospective study is needed to verify our findings.

• The Korean Journal of Mycology
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• v.48 no.3
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• pp.355-367
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• 2020

One hundred representative species of fungi in Korea were selected and their Korean names were proposed to increase interest in fungi among Korean people. This task was performed under the supervision of the Committee of Mycological Terms, under the Korean Society of Mycology. First, the committee established the criteria for selecting 100 representative species of fungi in Korea and then selected the candidate fungal species accordingly. To ensure the uniformity and stability of Korean fungal names, the principle of naming fungi in Korean was established, and the candidate Korean fungal names were presented accordingly. Finally, the candidate Korean fungal names were posted online to collect opinions of the members of the Korean Society of Mycology. The candidate Korean names of the plant pathogenic fungi and mushrooms were reviewed by the Korean Society of Plant Pathology and the Korean Society of Mushroom Science, respectively. After their opinions were considered, the Korean names for 100 representative fungi in Korea were finally determined. The 100 fungi comprised 41 common molds and yeasts, 28 plant pathogenic fungi, and 31 mushrooms.

• Journal of Life Science
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• v.26 no.8
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• pp.904-910
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• 2016

Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.157-172
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• 2023

Controlled pollination (CP) is an important method in tree breeding programs because CP quickly generates desirable genotypes and rapidly maximizes genetic gains. However, few studies have evaluated the efficiency and success rate of CP in the breeding program of Pinus densiflora. To evaluate CP and the management of control pollinated progenies, we used 159 individuals in CB2 × KW40 or KW40 × CB2 populations that were established in 2015. After genotyping microsatellite loci, we estimated whether the number of primers was sufficient or not. Then, we performed pedigree analysis. The result showed that the number of primers was sufficient. By pedigree analysis, we found out that 60 of 159 individuals had been generated by the mating between CB2 and KW40. In the maternity analysis, there was evidence to indicate the possibility of management problems. Therefore, we excluded 54 individuals and repeated the pedigree analysis. In the second analysis, 47 of 105 individuals were generated by the mating between CB2 and KW40. To increase the efficiency of CP in tree breeding programs, several precautions are required. It is necessary to identify the exact clone names of the mother and father trees. In addition, CP processes should be performed properly, including deciding on the schedule of CP and the isolation of female strobili or flowers. Finally, the monitoring of hybrid progenies management after mating is important. Molecular markers should be used to identify the clone names of the mother and father trees and for monitoring post hoc management. This study provides a reference for tree breeding programs for the future control pollination of pine species.