• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.749-753
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• 2008

Nowadays, first objectives of business activity is to develop competitive power by means of satisfying customer's needs. So, it is necessary to educate and train personnel in call-center in order to develop their job ability and latent ability. Especially departments of call-marketing or tele-marketing in domestic university have established for support of professionals had systematic and professional abilities In this paper, we analyze curricula in university for training call-center. Also, we analyze important subjects in similar departments of university and course descriptions based on educational objectives in college and university.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.51-56
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• 2008

With growing demand for zero defects, predicting reliability of software systems is gaining importance. Software reliability models are used to estimate the reliability or the number of latent defects in a software product. Most reliability models to estimate the reliability of software in the literature are based on the development lifecycle stages. However, in the maintenance phase, the software needs to be corrected for errors and to be enhanced for the requests from users. These decrease the reliability of software. Software Reliability Growth Models (SRGMs) have been applied successfully to model software reliability in development phase. The software reliability in maintenance phase exhibits many types of systematic or irregular behaviors. These may include cyclic behavior as well as long-term evolutionary trends. The cyclic behavior may involve multiple periodicities and may be asymmetric in nature. In this paper, SGRM has been adapted to develop a reliability prediction model for the software in maintenance phase. The model is established using maintenance data from a commercial shop floor control system. The model is accepted to be used for resource planning and assuring the quality of the maintenance work to the user.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.8
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• pp.641-651
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• 2003

In order to assess the reliability of a building energy simulation program (TRNSYS) from the standpoint of user, a set of verification experiment and calculation of cooling load for a test space is carried out. This work is a complement of the previous study that dealt with heating load for the same space. The test space is kept airtight to eliminate the source of uncertainties in modeling. A window-mounted, on/off controlled air-conditioner is used for cooling, whose performance has been established a priori. The calculation encompasses two models for evaluating cooling load in TRNSYS: energy rate control and temperature level control. Comparison of the total cooling loads obtained from different sets of experimental data enables to validate the measurements. The experimental result shows that the latent load is fairly large even in the absence of apparent air change in the space, which needs to be clarified. Each of hourly and daily accumulated sensible loads is compared between the experiment and two calculation models. Despite an inconsistency associated with solar irradiation, both of the models agree favorably with the experiment within a tolerance, illustrating their capability of properly predicting space thermal loads.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1583-1598
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• 2019

Recently, software has increased in complexity and been applied in various industrial fields. As a result, the presence of software bugs cannot be avoided. Various bug severity prediction methodologies have been proposed, but their performance needs to be further improved. In this study, we propose a novel technique for bug severity prediction in cross projects such as Eclipse, Mozilla, WireShark, and Xamarin by using topic modeling and similarity (i.e., KL-divergence). First, we construct topic models from bug repositories in cross projects using Latent Dirichlet Allocation (LDA). Then, we find topics in each project that contain the most numerous similar bug reports by using a new bug report. Next, we extract the bug reports belonging to the selected topics and input them to a Naïve Bayes Multinomial (NBM) algorithm. Finally, we predict the bug severity in the new bug report. In order to evaluate the performance of our approach and to verify the difference between cross projects and single project, we compare it with the Naïve Bayes Multinomial approach; the Lamkanfi methodology, which is a well-known bug severity prediction approach; and an emotional similarity-based bug severity prediction approach. Our approach exhibits a better performance than the compared methods.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.8
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• pp.157-167
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• 2022

The global laundry detergents market in 2021 was valued at nearly $121 billion, with consumers being reported as heightening their search for hygienic products capable of fighting viruses. Therefore, the researchers undertook a study to determine how product innovation (PI), product quality (PQ), and product attitude (PA) effects Thai consumers' satisfaction (CS) with their purchase of laundry detergent and fabric softener. After the questionnaire's validity and reliability confirmation, the authors used multi-stage random sampling by region and province in January and February 2022 to collect 520 questionnaires. LISREL 9.10 was used in the CFA and SEM analysis of the six hypotheses, which were determined to be supported. The results showed that all three causal variables positively influenced CS, with a total effect (TE) R² value = 87%. Also, latent variable total effect (TE) values showed that PI was strongest (0.93), then PQ (0.56), and finally, PA (0.54). Therefore, consumer satisfaction is essential in a firm's ongoing development and sustainability in a highly competitive, globalized world. Organizations must develop competitive strategies that adjust to consumer needs. Management must monitor online and social media sources where product reviews are given and adjust their strategies accordingly.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.9-16
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• 2020

The purpose of this study is to understand the public needs for AI education actively promoted and supported by the current government. In doing so, 11 metropolitan news articles and Twitter posts regarding AI education that have been posted from January 1, 2018 to December 31, 2019 were collected. Then, word frequency analysis using TF(Term Frequency) method and LDA(Latent Dirichlet Allocation) method of topic modeling analysis were conducted. The topics of the news articles turn out to be a macroscopic policy support such as 'training female manpower in the AI field' and 'curriculum reform of university and K-12', whereas the topics of twitter delineate more detailed social perception on future society, such as future competencies and pedagogical methods, including 'coexistence with intelligent robots', 'coding education', and 'humane education competence development'. The findings are expected to be used to suggest the implications for the composition and management of AI curriculum as well as the basic framework of human resources development in the future industry.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.23-30
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• 2006

A recommender system for E-commerce site receives information from customers about which products they are interested in, and recommends products that are likely to fit their needs. In this paper, we investigate several methods for large-scale product purchase data for the purpose of producing useful recommendations to customers. We apply the traditional data mining techniques of cluster analysis and collaborative filtering(CF), and CF with reduction of product-dimensionality by use of latent semantic indexing(LSI). If reduced product-dimensionality obtained from LSI shows a similar latent trend of customers for buying products to that based on original customer-product purchase data, we expect less computational effort for obtaining the nearest-neighbor for target customer may improve the efficiency of recommendation performance. From simulation experiments on synthetic customer-product purchase data, CF-based method with reduction of product-dimensionality presents a better performance than the traditional CF methods with respect to the recall, precision and F1 measure. In general, the recommendation quality increases as the size of the neighborhood increases. However, our simulation results shows that, after a certain point, the improvement gain diminish. Also we find, as a number of products of recommendation increases, the precision becomes worse, but the improvement gain of recall is relatively small after a certain point. We consider these informations may be useful in applying recommender system.

• Journal of Korea Water Resources Association
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• v.46 no.2
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• pp.111-122
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• 2013

The necessity of clear understanding of water and energy cycles has been attracted recently due to the climate change. The micrometeorological flux tower networks play a role of cornerstone of the hydrological and ecological analyses. Although the eddy covariance techniques used for flux tower have been proven to be applicable for estimation of latent heat flux, the raw data are often underestimated and needs to be corrected. Among several methods, the Bowen ratio is recognized as the most useful method in which the net radiation and other flux data (Ground heat flux, Sensible heat flux) are used and needed to be validated. In this study, in order to validate the net radiation from flux tower in Seolmacheon and Cheongmicheon watersheds, we compare it with two version of calculated net radiation: (1) FAO 56 Daily net radiation proposed by Allen et al. (1998). (2) Instantaneous net radiation proposed by Bastiaanssen (1995). The results showed that the net radiation from the flux data had similar tendency with those calculated based on physical theory. In addition, after it was applied to Bowen ratio method, the corrected latent heat flux was considerably improved with making the energy balance much more closed.

• 한국노년학
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• v.36 no.3
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• pp.541-562
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• 2016

The current study investigates the relationship and the mechanisms between bridge employment and change in marital satisfaction during midlife, using a three-wave panel dataset obtained from the Korean Baby Boomer Panel Study. A multivariate latent growth analysis reveals that the transition from career employment to bridge employment, compared to maintaining career employment, has an indirect negative effect on increase rate of marital satisfaction through the wage decrease. A steep decrease in wage following transition to bridge employment causes a lower increase in marital satisfaction. On the other hand, continuously engaging in bridge employment rather than career employment is associated with a higher increase in marital satisfaction via a higher increase in job commitment. This result implies that Baby Boomers adapt to bridge employment over time. Overall, the present study finds that the effect of bridge employment on the change in marital satisfaction during midlife varies with the duration of bridge employment. A future research needs to explore which factors can buffer the negative effect of decrease in wage during transition to the bridge employment on the change in marital satisfaction.

• Journal of Creative Information Culture
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• v.5 no.2
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• pp.117-134
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• 2019

The study is to compare the temperaments and characters of the gifted in invention with those of the genearl students, and also the characteristics of the subgroups of the gifted in invention through the LPA analysis. The results of the study are as follows: First, we compared the results of JTCI (Junior Temperament and Character Inventory) between the students entering Institute of Invention Science Education and the general students; through this comparison, we found out that the gifted in invention are more creative and willing to accept, generally feel more positive, and have the motivation to pursue meaningful goals and values above the personal needs than the non-gifted. Second, through the LPA analysis, the gifted in invention were divided into two subgroups; one group which showed far higher scores on pursuing stimulus, the subscale of temperaments, and slightly higher scores on autonomy, the subscale of characters, and the other group which showed the similar scores on pursuing stimulus and far higher scores on autonomy.