• ETRI Journal
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• v.31 no.2
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• pp.140-150
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• 2009

Although mutation testing is potentially powerful, it is a computationally expensive testing method. To investigate how we can reduce the cost of object-oriented mutation testing, we have conducted empirical studies on class mutation operators. We applied class mutation operators to 866 classes contained in six open-source programs. An analysis of the number and the distribution of class mutants generated and preliminary data on the effectiveness of some operators are provided. Our study shows that the overall number of class mutants is smaller than for traditional mutants, which offers the possibility that class mutation can be made practically affordable.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.1-8
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• 2014

This paper proposes an emotion classifier from EEG signals based on Bayes' theorem and a machine learning using a perceptron convergence algorithm. The emotions are represented on the valence and arousal dimensions. The fast Fourier transform spectrum analysis is used to extract features from the EEG signals. To verify the proposed method, we use an open database for emotion analysis using physiological signal (DEAP) and compare it with C-SVC which is one of the support vector machines. An emotion is defined as two-level class and three-level class in both valence and arousal dimensions. For the two-level class case, the accuracy of the valence and arousal estimation is 67% and 66%, respectively. For the three-level class case, the accuracy is 53% and 51%, respectively. Compared with the best case of the C-SVC, the proposed classifier gave 4% and 8% more accurate estimations of valence and arousal for the two-level class. In estimation of three-level class, the proposed method showed a similar performance to the best case of the C-SVC.

• Journal of The Korean Association For Science Education
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• v.23 no.5
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• pp.561-573
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• 2003

The teacher plays important role at students' achievement. This study analyses science class by pre-service science teacher. An survey tool for analysis of science class was composed of the lesson, student behavior, teacher behavior and questioning techniques. Pre-service science teacher analyzed the science class of 100 science teacher. The results of this study showed that pre-service science teacher analysis that current science class did not focused on inquiry-oriented. The score of science class did not statistically significantly difference by science teacher's characteristics as gender and age. Also, they analyses that science teacher use concept-oriented and teacher-oriented method.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.512-523
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• 2014

The purpose of this study is to provide useful information for improving interaction between teacher and student by analysing gifted class in mathematics with the Flanders Category System. Research questions are as follow. In gifted class in mathematics, How is the result of analysis regarding interactions between the teacher and students, according to 1) Flanders' Coding system? 2) Flanders' language pattern? 3) Flanders' Index system? For this, 3 gifted classes in mathematics were recorded by video camera and analyzed by Advanced Flanders(AF) analysis program version 3.54. Results are as follow. 1) Code Category Analysis mostly consists of lecture, voluntary speaking and chaos, silence work. 2) Most class patterns are not in accordance with effective class pattern models. So teacher needs to accept student's opinion actively and give appropriate feedback. 3) In Indices Results, revised I/d ratio, teacher's question ratio, student's speaking ratio, Student question and wide answer ratio are higher than analysis standard, indirect ratio is lower than analysis standard.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.15-35
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• 2020

In research on behavioral studies, significant attention has been paid to the stage-sequential process for multiple latent class variables. We now explore the stage-sequential process of multiple latent class variables using the multivariate latent class profile analysis (MLCPA). A latent profile variable, representing the stage-sequential process in MLCPA, is formed by a set of repeatedly measured categorical response variables. This paper proposes the extended MLCPA in order to explain an association between the latent profile variable and the latent group variable as a form of a two-dimensional contingency table. We applied the extended MLCPA to the National Longitudinal Survey on Youth 1997 (NLSY97) data to investigate the association between of developmental progression of depression and substance use behaviors among adolescents who experienced Authoritarian parental styles in their youth.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.4
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• pp.161-184
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• 2011

As movie demands become more and more diversified, it is necessary for movie related firms to segment a whole heterogeneous market into a number of small homogeneous markets in order to identify the specific needs of consumer groups. Relevant market segmentation helps them to develop valuable offer to target segments through effective marketing planning. In this article, we introduce various segmentation methods and compare their advantages and disadvantages. In particular, we analyze "2009~2010 consumer survey data of Korean Film Industry" by using Latent Class Analysis(LCA), a statistical segmentation method which identifies exclusive set of latent classes based on consumers' responses to an observed categorical and numerical variables. It is applied PROC LCA, a new SAS procedure for conducting LCA and finally get the result of 11 distinctive clusters showing unique characteristics on their buying behaviors.

• Journal of the Korea Safety Management & Science
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• v.14 no.2
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• pp.237-243
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• 2012

The more the satisfied customers increases in customer satisfaction survey, the more the company has difficultly in improving the customer satisfaction. In addition, the effectiveness of practical application of customer satisfaction survey decreases due to its constitution limitation on its data analysis. To overcome these problems, it is necessary to develop a new method to identify the strategy meanings and find the dissatisfied factors of satisfied customers using the satisfied customers reclassification. This study focuses on the satisfied customer segmentation using Latent Class Analysis. The case study shows that the satisfied customers are divided into three subgroups using Latent Class Analysis and we draw meaning results such as satisfaction and dissatisfaction factors through analyzing each group. This study is expected to play the role as the groundwork for the revitalization of customer satisfaction survey.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.241-254
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• 2020

This study proposes generalized models of joint latent class analysis (JLCA) for longitudinal data in two approaches, a JLCA with latent profile (JLCPA) and a JLCA with latent transition (JLTA). Our models reflect cross-sectional as well as longitudinal dependence among multiple latent classes and track multiple class-sequences over time. For the identifiability and meaningful inference, EM algorithm produces maximum-likelihood estimates under local independence assumptions. As an empirical analysis, we apply our models to track the joint patterns of adolescent depression and anxiety among US adolescents and show that both JLCPA and JLTA identify three adolescent emotional well-being subgroups. In addition, JLCPA classifies two representative profiles for these emotional well-being subgroups across time, and these profiles have different tendencies according to the parent-adolescent-relationship subgroups.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.256-263
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• 2014

This research aims is to confirm the influence of a teacher's teaching style and teaching career on instructional analysis. Through this, the differences in the relevant elements' view points on a class and those in teachers' analysis view points on class criticism and instructional analysis at the education field can be investigated. For this study, the teaching styles of 198 elementary school teachers were categorized, their teaching careers were checked as teaching career and set them as covariate, and the differences in the view points on the analysis of the class climates were verified depending on each teaching style. As the research result, meaningful differences were found in four areas of the elements of class climates analysis, that is, creativity, vitality, precision, and gentleness. In the analysis of the class climates, the teachers with a professional style among the teaching styles gave the highest grades to creativity in the same class, those with a facilitating style to vitality, those with a role model style to precision, and those with a facilitating and role model style to gentleness. On the other hand, those with an authoritative and a delegating style were proved to give the lowest grades in general class climates. It means that teachers with different teaching styles have different viewpoints when analyzing a class, and those with a professional, a role model and a facilitating style have a relatively stronger intention to analyze a class through reflective introspection and permissive recognition.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.257-263
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• 2021

This study analyzed the factors affecting online class satisfaction and tried to use it as basic data for more effective class management. The survey was collected on 208 students majoring in dental laboratory technology in Jeonbuk and Chungbuk. The data were analyzed by reliability analysis, descriptive stastistics, compare means(t-test, one-way ANOVA), Pearson's correlation coefficient and stepwies multiple regression analysis(SPSS program). The analysis results showed that expected benefit of time was 3.87, expected benefit of learning was 3.30, technology familiarity was 3.40, and class satisfaction was 3.21. The most influential factor in class satisfaction was technology familiarity. In order to increase the online class satisfaction, it is necessary to build a learning environment to improve the ability to learning tools used in classes and technology familiarity with the online class system.