• Journal of Life Science
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• v.22 no.7
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• pp.871-879
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• 2012

Polyploids are a potentially important germplasm source in seedless citrus breeding program. Seedlessness is one of the most promising traits of commercial mandarin breeds that mandarin triploid hybrids possess permanently. The formation of new constant triploid hybrids can be recovered through diploid species hybridization from the fusion of divalent gametes at low frequencyor intra-and inter-ploidy crosses. However, extensive breeding work based on small $F_1$ hybrid seeds developed is impossible without a very effective aseptic methodology and ploidy event. In this study, in vitro embryo culture was employed to recover natural hybrids from monoembryonic diploid, open-pollinated mandarin. Flow cytometry was used to determine ploidy level. A total of 10,289 seeds were extracted from 792 fruits having approximately 13 seeds per fruit. Average frequency of small seeds developed was 7.1%, while the average frequency of small seeds per fruit were: 8.9% for 'Clementine' 10.2% for 'Harehime' 2.6% for 'Kamja' 3.1% for 'Pyunkyool' 2.8% for 'Sadookam' and 7.0% for 'Wilking' mandarin. Average size of a perfect seed was $49.52{\pm}0.07mm^2$ ('Clementine') while the small seed measured $7.95{\pm}0.04mm^2$ ('Clementine'), which was about 1/6 smaller than the perfect seed. In total, 731 small seeds were obtained and all of them contained only one embryo per seed. The efficiency of 'Clementine' was 14 times higher than 'Wilking' and more than 109 times higher than 'Pyunkyool'. The basic information on spontaneous polyploidy provides for the hybridization of constant triploids and increases the efficiency of conventional cross.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.415-417
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• 2008

The meteorological data comes out pouring every moment. This paper deals with the neural network for weather forecast. Finally, we compare neural network with decision tree. As a result, it is suitable that Fog Forecasting Method, and I could get conclusion that the correctness rate and efficiency of Fog Forecasting Method that use this are very high.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.1-10
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• 2007

In this paper, we focus on churn analysis for the first successful candidates in the entrance examination on 2006 year using Clementine, data mining tool. The goal of this study is to apply decision tree including C5.0 and CART algorithms, neural network and logistic regression techniques to predict a successful candidate churn. And we analyze the churning and nochurning successful candidates and why the successful candidates churn and which successful candidates are most likely to churn in the future using data from entrance examination data of K university on 2006 year.

• Journal of Korean Academy of Nursing
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• v.40 no.3
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• pp.378-388
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• 2010

Purpose: This study was designed to build a theoretical frame to provide practical help to prevent and manage adolescent internet game addiction by developing a prediction model through a comprehensive analysis of related factors. Methods: The participants were 1,318 students studying in elementary, middle, and high schools in Seoul and Gyeonggi Province, Korea. Collected data were analyzed using the SPSS program. Decision Tree Analysis using the Clementine program was applied to build an optimum and significant prediction model to predict internet game addiction related to various factors, especially parent related factors. Results: From the data analyses, the prediction model for factors related to internet game addiction presented with 5 pathways. Causative factors included gender, type of school, siblings, economic status, religion, time spent alone, gaming place, payment to Internet cafe$\acute{e}$, frequency, duration, parent's ability to use internet, occupation (mother), trust (father), expectations regarding adolescent's study (mother), supervising (both parents), rearing attitude (both parents). Conclusion: The results suggest preventive and managerial nursing programs for specific groups by path. Use of this predictive model can expand the role of school nurses, not only in counseling addicted adolescents but also, in developing and carrying out programs with parents and approaching adolescents individually through databases and computer programming.

• Journal of Korean Academy of Nursing
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• v.43 no.1
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• pp.1-10
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• 2013

Purpose: The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. Methods: A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. Results: The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. Conclusion: The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3400-3411
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• 2013

The data mining is a new approach to extract useful information through effective analysis of huge data in numerous fields. This study was analyzed by decision making tree model using Clementine C&RT(Classification & Regression Tree, CART) as data mining technique. We utilized this data mining technique to analyze medical record of 1,500 people. Whole data were assorted by length of stay in PACU and divided into 3 groups. The result extracted by C5.0 decision tree method showed that important related factors for lengh of stay in PACU are type of operation, preoperative EKG abnormality, anesthetics, operative duration, age.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.3973-3982
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• 2012

The purpose of this study was to identify cognitive impairment and it's related factors of the elderly in long term care facilities. The participants of this study were 229 residents of five nursing homes. Data were analyzed using two sample t-test, ${\chi}^2$-test, and logistic regression. The results revealed eight factors related to cognitive impairment: gender(OR=2.41, p=.035), age(75-84: OR=3.26, p=.002, Over 85: OR=4.46, p<.001), living with family before admission(OR=2.17, p=.015), hearing(OR=8.88, p=.004), family history of dementia(OR=4.39, p=.009), ADL(OR=0.82, p<.001), hypertension(OR=4.07, p<.001), and diabetes(OR=3.42, p=.001). Based on the findings of this study, continuous nursing intervention focused on adjustable factors would be helpful in order to improve nursing home elderly people's quality of life.

• Journal of Plant Biotechnology
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• v.42 no.4
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• pp.326-335
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• 2015

Citrus is an economically important fruit tree with the largest amount of fruit production in the world. It provides important nutrition such as vitamin C and other health-promoting compounds including its unique flavonoids for human health. However, it is classified into the most difficult crops to develop new cultivars through conventional breeding approaches due to its long juvenility and some unique reproductive biological features such as gamete sterility, nucellar embryony, and high level of heterozygosity. Due to global warming and changes in consumer trends, establishing a systematic and efficient breeding programs is highly required for sustainable production of high quality fruits and diversification of cultivars. Recently, reference genome sequences of sweet orange and clementine mandarin have been released. Based on the reference whole-genome sequences, comparative genomics, reference-guided resequencing, and genotyping-by-sequencing for various citrus cultivars and crosses could be performed for the advance of functional genomics and development of traits-related molecular markers. In addition, a full understanding of gene function and gene co-expression networks can be provided through combined analysis of various transcriptome data. Analytic information on whole-genome and transcriptome will provide massive data on polymorphic molecular markers such as SNP, INDEL, and SSR, suggesting that it is possible to construct integrated maps and high-density genetic maps as well as physical maps. In the near future, integrated maps will be useful for map-based precise cloning of genes that are specific to citrus with major agronomic traits to facilitate rapid and efficient marker-assisted selection.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.851-858
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• 2009

Mobbing is not restricted to problem of young people but the bigger recent problem occurs in workspaces. According to reports of ILO and domestic case mobbing in the workplace is increasing more and more numerically from 9.1%('03) to 30.7%('08). These mobbing brings personal and social losses. The proposed algorithm makes it possible to grasp not only current mobbing victims but also potential mobbing victims through user profile and contribute to efficient personnel management. This paper extracts user profile related to mobbing, in a way of selecting seven factors and fifty attributes that are related to this matter. Next, expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and through this summation Mobbing-Value(MV) can be calculated . Finally by mapping MV of online social network users to G2 mobbing propensity classification model(4 Groups; Ideal Group of the online social network, Bullies, Aggressive victims, Victims) which is designed in this paper, can grasp mobbing propensity of users, which will contribute to efficient personnel management.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.1-12
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• 2009

Mobbing is going the rounds through a society rapidly and Military is not exception. Because mobbing of military is expressed not only psychology exclusion that is mobbing pattern of adult society but also sometimes psychologic and physical mobbing, is possible to join serious military discipline like a suicide and outrageous behavior. Specially military try to protect occurrence of victims that is public service through various rules and management plan but victims is going on happen. It means importance of grasp not only current mobbing victims but also potential mobbing victims better than preparation of various rules and management plans. Therefore this paper extracts seven factors and fifty attributes that are related to this matter mobbing. Next, by using Gunwoo's Social Network Service that is made for oneself and expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function(Dice's coefficient) to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and propose Mobbing Value(MV) Algorithm through this total summation. Finally through this algorithm which will contribute to efficient personnel management, we can grasp mobbing victims and tentative mobbing victims.