• Journal of Korean Library and Information Science Society
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• v.48 no.1
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• pp.161-189
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• 2017

The purpose of this study is to describe the experience of visually impaired academic researchers' use of scholarly contents and to explore intrinsic nature of the experience. In-depth interview was conducted with a total number of twelve visually impaired academic researchers and the data were analyzed using Colaizzi's phenomenological research method. A total of 107 significant statements were extracted, divided into 44 themes and 12 theme clusters. The statements were then classified into four categories. The 'scholarly contents acquisition and use' category has to do with difficulties that these experience when negotiating with internet sites with poor web accessibility and full-text availability. The 'changes in perception and emotions' category deals with transitions in perception and mood experienced by visually impaired academic researchers' over time. The 'relationships with support personnel' category includes issues related with the difficulty of securing support person, support person's inadequate level of competence, and establishing/sustaining personal relationships. Finally, the 'improvement requirements' category includes issues that these researchers want resolved with regard to contents acquisition and use.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.965-974
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• 2007

In this paper, we proposed the feature selection algorithm for multi-class genre classification. In our proposed algorithm, we developed GMM separation score based on Gaussian mixture model for measuring separability between two genres. Additionally, we improved feature subset selection algorithm based on sequential forward selection for multi-class genre classification. Instead of setting criterion as entire genre separability measures, we set criterion as worst genre separability measure for each sequential selection step. In order to assess the performance proposed algorithm, we extracted various features which represent characteristics such as timbre, rhythm, pitch and so on. Then, we investigate classification performance by GMM classifier and k-NN classifier for selected features using conventional algorithm and proposed algorithm. Proposed algorithm showed improved performance in classification accuracy up to 10 percent for classification experiments of low dimension feature vector especially.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.33-43
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• 2002

Various kinds of estimation methods have been developed for imputation of categorical missing data. They include category method, logistic regression, and association rule. In this study, we propose two fusions algorithms based on both neural network and voting scheme that combine the results of individual imputation methods. A Mont-Carlo simulation is used to compare the performance of these methods. Five factors used to simulate the missing data pattern are (1) input-output function, (2) data size, (3) noise of input-output function (4) proportion of missing data, and (5) pattern of missing data. Experimental study results indicate the following: when the data size is small and missing data proportion is large, modal category method, association rule, and neural network based fusion have better performances than the other methods. However, when the data size is small and correlation between input and missing output is strong, logistic regression and neural network barred fusion algorithm appear better than the others. When data size is large with low missing data proportion, a large noise, and strong correlation between input and missing output, neural networks based fusion algorithm turns out to be the best choice.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.615-632
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• 2017

Unlike randomized trial, statistical strategies for inferring the unbiased causal relationship are required in the observational studies. The matching with the propensity score is one of the most popular methods to control the confounders in order to evaluate the effect of the treatment on the outcome variable. Recently, new methods for the causal inference in latent class analysis (LCA) have been proposed to estimate the average causal effect (ACE) of the treatment on the latent discrete variable. They have focused on the application study for the real dataset to estimate the ACE in LCA. In practice, however, the true values of the ACE are not known, and it is difficult to evaluate the performance of the estimated the ACE. In this study, we propose a method to generate a synthetic data using the propensity score in the framework of LCA, where treatment and outcome variables are latent. We then propose a new method for estimating the ACE in LCA and evaluate its performance via simulation studies. Furthermore we present an empirical analysis based on data form the 'National Longitudinal Study of Adolescents Health,' where puberty as a latent treatment and substance use as a latent outcome variable.

• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.45-54
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• 2009

Categorization in a vital means for dealing with the multitudes of entities in the world surrounding people. Among others, the perceptual and the evaluative similarities factors strongly affect categorization. The conventional SD-type procedure are insufficient in this regard, since it requires an individual subject to make isolated judgments about each stimulus to identify categorization in terms of a group tendency. It disregards the individual categorization in which the similarities are of great importance. Thus in this study the phased emotional evaluation method is suggested based on the intuitive categorization of stimuli and on the similarity judgement of representative/ non-representative case in each category. To verify the effectiveness of the suggested evaluation method the scanned jewelry images are selected as test stimuli for emotional evaluation experiment. As a result of the evaluation experiment, the conventional SD-type procedure is complemented by the emotional evaluation method in phases of the task of intuitive categorization, the selection of the representative images and the setup of the evaluation score of the representative images to internally supplied anchors of evaluating non-representative images.

• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.693-704
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• 2016

The aim of this study was to investigate the conditions and strategies of interaction for the school adjustment for the early entrance students of science academy for the gifted. To know their concerns and process of school adjustment, we interviewed six early entrance gifted students of the science academy and two gifted students preparing for their early entrance with a semi-structured questions. Using the grounded theory, a paradigm model was organized and a core category was abstracted through the open, axial, and selective coding. Based on the open coding analysis, 75 concepts, 21 sub-categories, and 10 categories were derived. In the axial coding, the paradigm model was organized by the link between 10 categories derived from open coding. Through the selective coding, this study discovered the core category about early entrance student's school adjustment was overcoming difficulties by using academic, social, and emotional strategy for school adjustment. Through this, we understand the school adjustment process of the students of early entrance to science academy for the gifted.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.497-502
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• 2016

The survey is designed to provide fundamental data for assessing effects of calligraphy therapy program. An opened questionnaire asking psychological and physical experiences (3 advantages and 3 disadvantages) was given to 150 persons practicing calligraphy. Collected data were categorized into 10 psychological advantages (435 items), 6 psychological disadvantages (129 items), 9 physical advantages (302 items), and 7 physical disadvantages (150 items). Those subjective experiences were multidisciplinarily interpreted in terms of the mental and physical health and the humanistic education. A new structured assessing tool which will be developed based on the findings from the study may contribute in activating the calligraphy therapy program.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.589-594
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• 2012

In the initial stage, domestic games based online concentrated on game development focusing on income for some genres. However, various contents focusing on smart environment and social network are expanded at present and game materials are developed for more various objects. So, this study intends to examine new category, positive game, from the aspect of game designer for game approach based on various objects. And, game approaching process in the category based on pleasure was organized from the standpoint of designer, for the designer approach in the precedent stage of positive game development. From the aspect of designer, systemicity of game category and design approach are necessary to expand wire-wireless environment and new environment based on the convergence media to interactive contents focusing on games.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.183-188
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• 2013

A variety of cluster analysis techniques prerequisite to cluster objects having similar characteristics in data mining. But the clustering of those algorithms have lots of difficulties in dealing with categorical data within the databases. The imprecise handling of uncertainty within categorical data in the clustering process stems from the only algebraic logic of rough set, resulting in the degradation of stability and effectiveness. This paper proposes a information-theoretic rough entropy(RE) by taking into account the dependency of attributes and proposes a technique called min-mean-mean roughness(MMMR) for selecting clustering attribute. We analyze and compare the performance of the proposed technique with K-means, fuzzy techniques and other standard deviation roughness methods based on ZOO dataset. The results verify the better performance of the proposed approach.

• Journal of Korean Society of Archives and Records Management
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• v.20 no.1
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• pp.27-46
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• 2020

The need for changes in archival studies curriculum has been steadily raised because of the wide variation of the curriculum in each graduate school. In this study, the foreign archival studies guidelines and certification standards were compared and analyzed to derive key categories and elements for developing the Korean guidelines for a graduate program in archival studies. The five key categories and elements of the guideline include introduction, mission and goal, knowledge categories, administrative factors, and conclusion. On the other hand, the 10 knowledge categories to be learned by archivists include ① The Nature of Records and Archives, ② Selection, Appraisal, and Acquisition, ③ Arrangement and Description, ④ Preservation, ⑤ Reference and Access, ⑥ Outreach, Instruction, and Advocacy, ⑦ Management and Administration, ⑧ Social and Cultural Systems, ⑨ Legal and Financial Systems, and ⑩ Information Technology. In the future, knowledge categories need to be actively reflected by the opinions of the academic community and archivists to improve the graduate curriculum.