• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.174-181
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• 2017

Colors that stimulate human emotions in everyday life are one of the important factors in animation production. The research on color has been actively carried out in relation to the importance and nature mainly for animation production. However, researches that investigated different views for specific color by geographic characteristics are rare. Therefore, information was collected through questionnaire survey and empirical analysis was conducted using SPSS statistical package to analyze preference of Korean and Chinese people for the Chinese traditional colors. The analysis results showed that both Korean and Chinese groups preferred red color among Chinese traditional colors. This preference for red was statistically significant in both groups, indicating that the intensity of preference for red was different even though Korean and Chinese equally preferred red. Furthermore, among 10 red colors, the preferred red was different between Chinese and Korean. Based on these results, it is suggested that the color should be selected considering the characteristics of the intended market for Chinese animation production and the personality of the viewers who watch the animation products.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1282-1287
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• 1999

통신 프로그램은 고도의 신뢰성과 기능성, 확장성, 그리고 유지 보수성이 필요하다. 프로그램 테스트의 결과와 McCabe의 Complexity를 측정한 데이타를 가지고 회귀모델을 만들고 그 신뢰성을 분석함으로서 프로그램의 결함과 복잡도의 관련성을 평가한다.본 연구에서 사용한 통신 프로그램은 500개 블록이 59가지 기능을 수행하는 교환 기능 중에서 복잡도가 너무 많아서 통계 처리의 bias가 될 블록을 제외하고 394 블록을 선정하여 SAS에 의해서 통계 분석을 하고 회귀 분석 모델을 설계하였다. t 분포에 의하여 방정식의 유의성 수준을 검증하고 프로그램의 결함수에 가장 큰 영향을 주고 있는 복잡도가 McCabe의 복잡도와 설계 복잡도 임을 밝혀냈다. 이 연구 결과에 의해서 설계 정보 및 유지 보수 정보를 얻을 수 있다. Abstract Switching software requires high reliability, functionality, extendability and maintainability. For doing, software quality model based on MaCabe's complexity measure is investigated. It is experimentally shown using regression analysis the program fault density depends on the complexity and size of the function unit. The software should be verified and tested if it satisfies its requirements with automated analysis tools. In this paper we propose the regression model with the test data.The sample program for the regression model consists of more than 500 blocks, where each block compose of 10 files, which has 59 functions of switching activity.Among them we choose 394 blocks and analyzed for 59 functions by testing tools and SAS package. We developed Regression Analysis Model and evaluated significant of the equation based on McCabe's cyclomatic complexity, block design complexity, design complexity, and integration complexity.The results of our experimental study are that number of fault are under the influence of McCabe's complexity number and design complexity.

• Women's Health Nursing
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• v.17 no.5
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• pp.439-446
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• 2011

Purpose: Early diagnosis is the primary method aimed at controlling breast cancer. The purpose of this study was to analyze some factors affecting the performance of mammography screening among women with a family history of breast cancer in Korea. Methods: This study applied a descriptive design method through structured self-report questionnaires. The Care Seeking Behavior Theory provided a theoretical framework for the study. Factors measured in this study represent demographic, clinical, and psychosocial variables including anxiety, barriers, utility, habits, perception, and facilitators. A total of 212 participants, of at least 20 years old, were sampled from April 8, 2010 to March 31, 2011. The data was analyzed by logistic regression method using the Statistical Package for the Social Science 18.0 software. Results: Of the 212 participants, 122 women (57.5%) went through mammography screening. The results of the analysis showed that (a) age (Odds Ratio [OR] =1.10, p<.001), (b) facilitating influences (OR=1.83, p=.008), (c) perception of mammography importance (OR=1.92, p=.011), (d) barriers to mammography (OR=0.60, p=.031), and (e) utility of mammography (OR=2.01, p=.050) significantly affect mammography screening. Conclusion: The results underscore the impact that psychosocial variables in obtaining mammography have on adherence to screening. Women with a family history of breast cancer should be given accurate information and recommendation about mammography by healthcare provider and a regular source of healthcare.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.129-140
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• 2021

Recently, interest in AI tutors is rising as a way to bridge the educational gap in school settings. However, research confirming the effectiveness of AI tutors is lacking. The purpose of this study is to explore how effective learner characteristics and recommended item learning activities are in predicting learner's academic performance in an adaptive online learning environment. This study proposed the hypothesis that learner characteristics (prior knowledge, midterm evaluation) and recommended item learning activities (learning time, correct answer check, incorrect answer correction, satisfaction, correct answer rate) predict academic achievement. In order to verify the hypothesis, the data of 362 learners were analyzed by collecting data from the learning management system (LMS) from the perspective of learning analytics. For data analysis, regression analysis was performed using the regsubset function provided by the leaps package of the R program. The results of analyses showed that prior knowledge, midterm evaluation, correct answer confirmation, incorrect answer correction, and satisfaction had a positive effect on academic performance, but learning time had a negative effect on academic performance. On the other hand, the percentage of correct answers did not have a significant effect on academic performance. The results of this study suggest that recommended item learning activities, which mean behavioral indicators of interaction with AI tutors, are important in the learning process stage to increase academic performance in an adaptive online learning environment.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.322-331
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• 2021

This study attempted to identify the multi-cultural acceptance level of freshmen in nursing colleges and to analyze the factors influencing it. For the research method, data were collected from 410 first-year nursing students at K University in W City through a questionnaire from March 1 to 28, 2021, and frequency, reliability analysis, t-test, ANOVA, correlation, and multiple regression were conducted using the open-source statistical package R. As a result of the study, the multi-cultural acceptance level of freshman in nursing colleges averaged 77.36 points, indicating that they have a slightly higher multi-cultural acceptance capacity, and as a result of analyzing the influence of multi-cultural acceptance related factors, Korean recognition requirements(𝛽=0.34, p<.001), perceived threat recognition for migrants (𝛽=0.29, p<.001), Experience in multi-cultural education(𝛽=0.14, p<.001), Recognition of the appropriate age for multi-cultural education (𝛽=0.20, p<.001) was statistically significant. According to results, it is necessary to develop and actively utilize regular curriculum and programs related to multi-culturalism for nursing students.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.253-263
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• 2021

This study aims to present effective teaching and learning methods for improving class satisfaction and improving the quality of university education by empirically analyzing changes in class satisfaction according to teaching methods such as face-to-face(FTF) classes, non-face-to-face(NFTF) classes, and blended classes of theories and practical subjects before and after COVID-19, targeting beauty major students who have a relatively higher proportion of practical classes than theoretical classes. For data analysis, SPSS 18.0 statistical package was used, and in the analysis of the difference in satisfaction with teaching methods for theoretical subjects before and after COVID-19, 10 items out of 20 items showed statistically significant differences, and 8 items out of 20 items in the practical subjects showed statistically significant differences. It is expected that the quality of university education will be improved by applying efficient and practical teaching methods considering the items affecting the class satisfaction according to the teaching and learning methods of these theories and practical subjects.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.63 no.4
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• pp.338-359
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• 2018

Soybean (Glycine max L.), a major part of Asian diet, is consumed primarily for its nutritional value. However, poor storage stability often leads to loss of nutritional value or deterioration in quality. This study focused on the storage stability of soy flour obtained from raw and roasted "Saedanbaek" soybeans packed in polyethylene (PE) and polypropylene (PPE) film bags that were stored at $4^{\circ}C$, $20^{\circ}C$ and $45^{\circ}C$ for 48 weeks. The early acid values (diene and p-anisidine) of raw soybean flour (RSF) at high temperature (HT) were higher than those at refrigerated temperature (RFT) and room temperature (RT) during 48 and 12 to 36 weeks, respectively. In the case of roasted soybean flour (ROSF), which was stored at RFT and RT, the acid and conjugated diene values gradually increased after 24 weeks. In RSF, the peroxide value increased since the beginning of the $24^{th}$ week. The p-anisidine value also increased during 12 to 36 weeks but was much lower than the values obtained from HT storage. As the peroxide values decreased, the p-anisidine values increased, indicating an inverse relationship. Lipoxygenase activity of ROSF at all storage conditions was lower than RSF. Several differences were observed between the packing materials used. This study could, therefore, provide useful information for the industrial use of soybean flour (SF).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.151-160
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• 2019

EPC companies to continue operating overseas, it is increasingly becoming apparent that risk is no longer something to be avoided but a subject to be managed. During the bidding stage, the requirements, specifications and project line items within the bid package must be studied in details to analyze the various risk factors in order to avoid cost overruns. However, reviewing vast quantities of bidding documents is time consuming and labor intensive and is not an easy task and this is where automated information technology can help. For this study, I have constructed an ITB analysis model based on Watson AI that can analyze and apply vast amount of documents more effectively in a short time. Configuration of the Watson Explorer AI architecture for AI-based ITB risk management model research, the selection of learning procedures and analysis subjects, and the performance evaluation criteria were defined, and a test bed was constructed to conduct a pilot research. Consequently, I verified the effectiveness of the analytical time reduction and the quality of its results and VOC operations by professionals.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.4
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• pp.467-476
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• 2019

Objective: This research was conducted to study the genetic diversity in several Indonesian cattle breeds using microsatellite markers to classify the Indonesian cattle breeds. Methods: A total of 229 DNA samples from of 10 cattle breeds were used in this study. The polymerase chain reaction process was conducted using 12 labeled primers. The size of allele was generated using the multiplex DNA fragment analysis. The POPGEN and CERVUS programs were used to obtain the observed number of alleles, effective number of alleles, observed heterozygosity value, expected heterozygosity value, allele frequency, genetic differentiation, the global heterozygote deficit among breeds, and the heterozygote deficit within the breed, gene flow, Hardy-Weinberg equilibrium, and polymorphism information content values. The MEGA program was used to generate a dendrogram that illustrates the relationship among cattle population. Bayesian clustering assignments were analyzed using STRUCTURE program. The GENETIX program was used to perform the correspondence factorial analysis (CFA). The GENALEX program was used to perform the principal coordinates analysis (PCoA) and analysis of molecular variance. The principal component analysis (PCA) was performed using adegenet package of R program. Results: A total of 862 alleles were detected in this study. The INRA23 allele 205 is a specific allele candidate for the Sumba Ongole cattle, while the allele 219 is a specific allele candidate for Ongole Grade. This study revealed a very close genetic relationship between the Ongole Grade and Sumba Ongole cattle and between the Madura and Pasundan cattle. The results from the CFA, PCoA, and PCA analysis in this study provide scientific evidence regarding the genetic relationship between Banteng and Bali cattle. According to the genetic relationship, the Pesisir cattle were classified as Bos indicus cattle. Conclusion: All identified alleles in this study were able to classify the cattle population into three clusters i.e. Bos taurus cluster (Simmental Purebred, Simmental Crossbred, and Holstein Friesian cattle); Bos indicus cluster (Sumba Ongole, Ongole Grade, Madura, Pasundan, and Pesisir cattle); and Bos javanicus cluster (Banteng and Bali cattle).

• Journal of Information Technology Applications and Management
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• v.26 no.2
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• pp.13-26
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• 2019

The purpose of this study is to examine the effect of each of the two technology acceptance factors(employees' attitude toward smart factory technology, and ease of smart factory technology use) on the introduction level of each of the three smart factory technologies (manufacturing big data technology, automation technology, and supply chain integration technology), and in turn, the effect of each of the three smart factory technologies on manufacturing performance. This study employed PLS statistics software package to empirically validate a structural equation model with survey data from 100 domestic small-and medium-sized manufacturing firms (SMMFs). The analysis results revealed the followings. First, it is founded that employees' attitude toward smart factory technology influenced all of the three smart factory technology introduction levels in a positive manner. In particular, SMMFs of which employees had more favorable attitude toward smart factory technology tended to increase introduction levels of both automation technology and supply chain integration technology more than in the case of manufacturing big data technology. Second, ease of smart factory technology use also had a positive impact on each of the three smart factory technology introduction levels, respectively. A noteworthy finding is this : SMMFs which perceived smart factory technology as easier to use would like to elevate the introduction level of manufacturing big data technology more than in the cases of either automation technology or supply chain integration technology. Third, smart factory technologies such as automation technology and supply chain integration technology had affirmative impacts on manufacturing performance of SMMFs. These results shed some valuable insights on the introduction of smart factory technology : The success of smart factory heavily depends on organization-and people-related factors such as employees' attitude toward smart factory technology and employees' perceived ease of smart factory technology use.