• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.499-510
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• 2016

It is very important to select relevant variables in regression models for survival analysis. In this paper, we introduce a penalized variable-selection procedure in multi-level frailty models based on the "frailtyHL" R package (Ha et al., 2012). Here, the estimation procedure of models is based on the penalized hierarchical likelihood, and three penalty functions (LASSO, SCAD and HL) are considered. The proposed methods are illustrated with multi-country/multi-center bladder cancer survival data from the EORTC in Belgium. We compare the results of three variable-selection methods and discuss their advantages and disadvantages. In particular, the results of data analysis showed that the SCAD and HL methods select well important variables than in the LASSO method.

• Journal of Digital Convergence
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• v.13 no.6
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• pp.125-132
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• 2015

It is current situation that a number of issues are being raised how the weight is calculated from customer satisfaction survey. This study investigated how the weight of satisfaction for each quantile is different by comparing ordinary least square regression model to quantile regression model and carried out bootstrap verification to find the influence difference of regression coefficient for each quantile. As the analysis result of using R(Quantreg package) that is open software, it appeared that there was the influence size of satisfaction factor along study result and quantile and there was the significant difference statistically regarding regression coefficient for each quantile. So, to use quantile regression model that offers the influence of satisfaction factor for each customer group along satisfaction level would contribute to plan the quantitative convergence policy for customer satisfaction.

• Journal of Korean Library and Information Science Society
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• v.47 no.4
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• pp.1-18
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• 2016

The purpose of this study is to explore application of topic modeling for topic analysis of book report. Topic modeling can be understood as one method of topic analysis. This analysis was conducted with texts in 23 book reports using LDA function of the "topicmodels" package provided by R. According to the result of topic modeling, 16 topics were extracted. The topic network was constructed by the relation between the topics and keywords, and the book report network was constructed by the relation between book report cases and topics. Next, Centrality analysis was conducted targeting the topic network and book report network. The result of this study is following these. First, 16 topics are shown as network which has one component. In other words, 16 topics are interrelated. Second, book report was divided into 2 groups, book reports with high centrality and book reports with low centrality. The former group has similarities with others, the latter group has differences with others in aspect of the topics of book reports. The result of topic modeling is useful to identify book reports' topics combining with network analysis.

• Journal of Korean Academy of Nursing Administration
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• v.8 no.2
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• pp.249-259
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• 2002

Purpose: This study was to identify the relationship between transformational leadership of nurse managers and autonomy, empowerment of nurses. Method: The subjects were 468 nurses and 19 head nurses were working at the 3 general hospitals in seoul. The data were collected from July 6 to September 14, 2001 by the structured questionnaires. For data analysis, descriptive statistics, ANOVA, Pearson correlation coefficient, and stepwise multiple regression with SAS package were used. Result: 1) 'Autonomy' and 'Empowerment' were positively related to 'Total Transformational Leadership', 'Charisma', 'intellectual stimulation', 'individual consideration'($r=.18{\sim}24$, $r=.26{\sim}36$, p<.001). 2) 'Transformational leadership' showed a significant difference according to major field of practice(F=4.47, p<.001). 3) 'Autonomy' showed a significant difference according to age, education level, total numbers of years in nursing practice, and position in present(F=3.68, 3.27, 3.13, 4.34, p<.05). 4) 'Empowerment' showed a significant difference according to age, marital status, education level, major field of practice, total numbers of years in nursing practice, and position in present(F=16.02, t=9.04, F=6.97, 1.86, 15.71, 11.38, p<.05). 5) As a result of regression analysis, the key determinants of 'autonomy' were 'Charisma' and this explained 10.61% of the total variance of it. And the key determinants of 'empowerment' were 'intellectual stimulation' and this explained 16.01% of the total variance of it.

• Journal of Life Science
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• v.14 no.4
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• pp.593-607
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• 2004

The nucleotide sequence for a nuclear-encoded small subunit rDNA (SSU rDNA) was determined for 43 species of the class Dinophyceae, including harmful algae Cochlodinium polykrikoides and Gyrodinium aureolum. These sequences and data analyses were performed by parsimony, distances and maximum likelihood methods in PHYLIP (Phylogenetic Inference Package) version 3.573c. The species Noctiluca scintillans, Gonyaulax spinifern and Crypthecodinium cohnii occupied a basal position within the Dino- phyceae in our analyses. The genera Alexandrium and Symbiodinium were monophyletic (supported by a bootstrap value of >70%), whereas the genera Gymnedinium and Gyrodinium formed polyphyletic nodes, for which bootstrap support was strong (>70%) in the neighbor-joining and maximum likelihood methods except for the PHYLIP parsimony analysis (=59%). The sequence divergence between G. aureolum and G. dorsum/ G. galathenum was the largest at 7.4% (45 bp), whereas G. aureolum and G. mikimotoi showed an extremely low value of genetic divergence of 0.9% (5 bp). The genetic divergence between C. polykrikoides and G. aureolum was a low value of 5.2% (31 bp). In the phylogenetic analysis, the placement of G. aureolum and C. polykrikoides was closer to the genus Gymnodinium than to the genus Gyrodinium, which was supported by a moderate bootstrap value.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.26-31
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• 2000

It is said that the focus of managing venture business is currently moving from technology competition to management competition. By the way, the software venture business(SVB) has some weak points in its structural composition and itematization and no professional personnel in other several sections except technology development section. In addition, such basic functions as technology and R & D, finance and accounting, marketing required to the management of business are concentrated on only one man, its representative director. Therefore, this study aims to provide the basic data useful to the establishment of governmental policy in information and communication, to the rearing of the SVB by a local government related to the software, and to the administration of SVB by investigating the actual conditions. This study attempts to examine the literature on venture business and software industry, and its management with a questionnaire about the actual conditions of managing the SVB. The questionnaire is given to 527 local enterprises belonging to the Software Industry Association and to 171 enterprises in the Software Center. This study compromises the characteristics of the SVB, the actual conditions of its technology and R & D, finance and accounting, and marketing. The characteristics of the SVB are classified into categories such as the stage of its growth(the stage of its seed and start-up, the stage of tis development and growth, the stage of its stability and maturity) and the main business(the system integration, the software development for contract, the package software development service, the software-related service). Additionally, the study attempts to analyze positively the actual condition of its management after classified by the areas of business profile, its general management, its technology development, its finance and accounting, and its marketing The result of this study is found that the SVB has a lot of troubles in part of marketing and finance & accounting activity as well as general management. The SVB realizes the importance of the technology development rather than that of management activity including marketing activity. So we expect this study can assist the SVB to establish the business guidelines for own management plans.

• Journal of the Korean Institute of Gas
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• v.11 no.4
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• pp.47-53
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• 2007

The safe operation of high pressure pipe line systems is of significant importance. Leaks due to faulty operation from the pipelines can lead to considerable product losses and to exposure of community to dangerous gases. There are several leak detection methods, which have been recently suggested on pipeline network. The negative pressure wave detection technology, which has advantages of short time detection availability, accurate leaking location estimate capability and cost effective, is concentrated in this study. Theoretical analysis of the flow characteristics for leaking through a hole on the pipe wall has been performed by using CFD++, commercial CFD package. The results of 3-dimensional analysis near leaking hole confirm the occurrence of negative pressure wave and verify the characteristics of propagation of the wave which travels with speed equal to the speed of sound in the pipeline contents. For the application of long pipe line system. The method of 1-dimensional analysis has been suggested and verified with results of CFD++.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.213-219
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• 2020

In this paper, we propose a classification analysis method for diagnosing and predicting problematic smartphone use in order to provide policy data on problematic smartphone use, which is getting worse year after year. Attempts have been made to identify key variables that affect the study. For this purpose, the classification rates of Decision Tree, Random Forest, and Support Vector Machine among machine learning analysis methods, which are artificial intelligence methods, were compared. The data were from 25,465 people who responded to the '2018 Problematic Smartphone Use Survey' provided by the Korea Information Society Agency and analyzed using the R statistical package (ver. 3.6.2). As a result, the three classification techniques showed similar classification rates, and there was no problem of overfitting the model. The classification rate of the Support Vector Machine was the highest among the three classification methods, followed by Decision Tree and Random Forest. The top three variables affecting the classification rate among smartphone use types were Life Service type, Information Seeking type, and Leisure Activity Seeking type.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.53-59
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• 2017

This study was attempted to identify the domestic research related to depression and stress. The subjects of the analysis were 1,875 college degree theses thrown in the National Assembly Library searched by the depression and stress keyword as of November 30, 2016. The analysis method visualizes atypical data with Word Cloud, which is one of the text mining techniques. We also used the R'LDA package and LDA to classify treatment and subjects. As a result of the analysis, 233(12.4%) of the total papers with therapeutic keywords were found. Application of treatment methods was art therapy, music therapy, horticultural therapy, cognitive behavior therapy, clinical art therapy, cognitive therapy, psychological therapy, depression treatment, group therapy, laughter treatment sequence. The study subjects were adolescents, elderly, patient, mother, child, female, parents, and college students in order. The results of LDA topic analysis for adolescents were classified into four topics: self-support, treatment program, relationship effect, and variable study.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1431-1438
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• 2014

We analyzed the articles from "Kukje Shinmun" and "Busan Ilbo", which are two local newpapers of Busan Metropolitan City. The articles cover from January 1, 2013 to December 31, 2013. Meaningful pattern inherent in 2889 articles of which the title includes "Busan" and "Traffic" and related data was analyzed. Textmining method, which is a part of datamining, was used for the social network analysis (SNA). HDFS and MapReduce (from Hadoop ecosystem), which is open-source framework based on JAVA, were used with Linux environment (Uubntu-12.04LTS) for the construction of unstructured data and the storage, process and the analysis of big data. We implemented new algorithm that shows better visualization compared with the default one from R package, by providing the color and thickness based on the weight from each node and line connecting the nodes.