• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.255-256
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• 2021

The performance measurement of construction projects has traditionally been evaluated as a prerequisite for successful project completion. Considering this importance, the UK and the US are operating quantitative performance measurement systems for construction projects. However, in the case of Korea, there is a limit to the use of existing methods due to the limitation of data collection. Recently, in consideration of the domestic situation, research is being conducted to measure the quantitative performance of a project by using big data including progress and project attribute information. Therefore, this study aims to present the design direction of a performance monitoring system using Quality Function Deployment.

• The Korean Journal of Franchise Management
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• v.6 no.2
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• pp.17-30
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• 2015

Companies display the product information to the consumers in their online presences. As importance of online marketing activities are growing, most of the franchisers also uses the product images on their online sites to provide the vivid visual information of their merchandises. But the previous researches do not provide the rigorous understanding on the nature of how the consumers process the visual information. In this study, we explore the theoretical backgrounds of the visual information processing and set up the research proposition on the orders and directions of the online visitors' attentions. The visit data from experimental online shop for 81 days was analysed with repeated measure ANOVA. We found that the nature of visual information processing in the online environment is different from that of the ordinary text process. At the end of this study, implication and the limitations of the research were discussed.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.217-218
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• 2023

In modern architecture, tiles are used as a decorative material to enhance the appearance of buildings. However, defects occurring during tile installation affect not only the appearance of the building, but also its maintenance. This study aims to investigate stable tile installation by producing tile modules using the floating mortar method and conducting freeze-thaw tests to measure their adhesion strength. Test results showed that the adhesion strength increased as the mesh size decreased, except for S3 mesh. This study highlights the importance of research on tile installation to solve problems related to building appearance and maintenance.

• Educational Technology International
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• v.24 no.2
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• pp.143-168
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• 2023

This study aims to analyze the perceptions and educational needs of pre-service teachers for the use of Artificial Intelligence (AI) in education. To this end, we collected survey data from 25 undergraduate students who were enrolled in a teacher education college in Seoul. The purpose of the survey was to measure the importance and current performance for instructional AI use based on the technological, pedagogical, and content knowledge (TPACK) framework, and to explore the priority of educational needs using Borich's needs analysis and the Locus for Focus model. The results of the study confirmed that Ethics and TPK competencies are prioritized. Additionally, the results indicated a high demand for practical knowledge that can be implemented in the practice of education. Based on the results, it is necessary to develop a teacher education program that focuses on ethical aspects and teaching strategy competencies in AI-based education.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.170-178
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• 2024

Through the growth of the fifth-generation networks and artificial intelligence technologies, new threats and challenges have appeared to wireless communication system, especially in cybersecurity. And IoT networks are gradually attractive stages for introduction of DDoS attacks due to integral frailer security and resource-constrained nature of IoT devices. This paper emphases on detecting DDoS attack in wireless networks by categorizing inward network packets on the transport layer as either "abnormal" or "normal" using the integration of machine learning algorithms knowledge-based system. In this paper, deep learning algorithms and CNN were autonomously trained for mitigating DDoS attacks. This paper lays importance on misuse based DDOS attacks which comprise TCP SYN-Flood and ICMP flood. The researcher uses CICIDS2017 and NSL-KDD dataset in training and testing the algorithms (model) while the experimentation phase. accuracy score is used to measure the classification performance of the four algorithms. the results display that the 99.93 performance is recorded.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.44-47
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• 2024

With the advancement of Internet technology, online sales and purchases of products have become active. Along with this, the importance of user reviews is also being highlighted. Although user reviews are actively utilized for product sales and purchases, it is difficult to quickly and easily obtain useful information due to the abundance of user reviews. Therefore, prioritizing user reviews is a necessary service for customers that requires careful consideration. Metadata, which contains important information, can be effectively used to prioritize user reviews. However, it is crucial to select and use metadata appropriately according to the purpose. Lean Startup proposes a strategy of repeatedly correcting the problems of ideas or making early transitions to continue trying different approaches. In this paper, we propose a three-step method applying the Lean Startup process to analyze ways to prioritize user reviews using metadata: Build Priority, Measure Priority, Learn Priority.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.355-361
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• 2024

The purpose of the study was to examine the effects of early childhood teachers' professional development and Grit on their teacher-child interactions. The subjects were 363 early childhood teachers working at kindergartens or childcare centers of South Korea. We used self-reporting survey questionnaires to measure the major variables and utilized the SPSS 28.0 Program to analyze the collected data. Cronbach's alphas were calculated and the descriptive statistical analyses were conducted. To investigate the research questions, Pearson's correlation analysis and multiple regression analysis were done. As results, the higher early childhood teachers' professional development and Grit were, the higher their teacher-child interactions were. Early childhood teachers' professional development and Grit were found to have positive effects on their teacher-child interactions, which showed that professional development and Grit would predict the quality of interactions between teacher and young children. Based on these results, we suggest the importance of early childhood teachers' professional development and Grit so that they practice excellent interactions with young children in order to support development and learning through play.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.331-340
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• 2008

Feature Selection is one of methods to improve the classification accuracy of data in the field of machine learning. Many feature selection algorithms have been proposed and discussed for years. However, the problem of finding the optimal feature subset from full data still remains to be a difficult problem. Bio-inspired algorithms are well-known evolutionary algorithms based on the principles of behavior of organisms, and very useful methods to find the optimal solution in optimization problems. Bio-inspired algorithms are also used in the field of feature selection problems. So in this paper we proposed new improved bio-inspired algorithms for feature selection. We used well-known bio-inspired algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), to find the optimal subset of features that shows the best performance in classification accuracy. In addition, we modified the bio-inspired algorithms considering the prior importance (prior relevance) of each feature. We chose the mRMR method, which can measure the goodness of single feature, to set the prior importance of each feature. We modified the evolution operators of GA and PSO by using the prior importance of each feature. We verified the performance of the proposed methods by experiment with datasets. Feature selection methods using GA and PSO produced better performances in terms of the classification accuracy. The modified method with the prior importance demonstrated improved performances in terms of the evolution speed and the classification accuracy.

• Journal of The Korean Association of Information Education
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• v.20 no.5
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• pp.475-486
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• 2016

As software transforms the structure of industry, it becomes a key measure in determining market competitiveness. Therefore, various educational efforts have been attempted in Korea to cultivate software professionals to secure software competitiveness. While previous studies had focused mainly on the cognitive effectiveness of software education, the authors tried to focus on affective perspectives. The authors, therefore, aimed to analyze the predictive power of the recognition of software importance and learning flow on affective outcomes, such as efficacy of computational thinking skills, and attitude toward, and satisfaction with, software education. The data were collected from 103 sixth grade students who participated in a software education. Results show that software importance and learning flow had significant predictive power on affective outcomes; Learning flow mediated the relationship between software importance and affective outcomes. This study provides practical implications for improving affective outcomes in the design and implementation of software education.

• Journal of the Korean Home Economics Association
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• v.28 no.4
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• pp.177-189
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• 1990

The purpose of this study were to measure the body cathexis and the characteristics of middle-aged women groups segmented by their fashion orientation. Self-administered questionaire method was used. Seven demographic variables, 9 self-images, body cathexis were included as independent variables. Fashion orientation developed by Gutman and Mills was used. Data was collected from 369 Middle-aged women in Chonbuk Province. Frequencies, Percentages, means, standard deviation were caculated. ANOVA, cluster analysis, and discriminant analysis were used for data analysis. The results were as follows: 1. The body cathexis of the subjects were lower than capital city and increased according to age. 2. The self-image of the subjects were down-to-earth, modern, conventional, playing it safe, confident, stable, reserved and blending out into a crowd. The subjects with the self-image of being more sophisticated, confident, creative, stood out in a crowd, or complicated life style had higher body cathexis. 3. When the subjects were divided into segmentations according to their fashion orientation by cluster analysis, the best suitable number of groups was seven. The characteristics of seven groups were: *Fashion negatives showed low levels of fashion leadership and fashion interest, and medium level of importance of being well-dressed, and high level of antifashion attitudes. *Fashion neutrals showed medium levels of fashion leadership, fashion interest, and importnace of being-well dressed, and low level of antifashion attitudes. *Fashion uninvolveds showed low levels of fashion leadership, fashion interest, and antifashion attitudes. *Fashion followers showed high levels of fashion interest and importance of being well dressed, but low levels of fashion leadership and antifashion attitudes. *Fashion independents showed a littel bit high levels of fashion leadership, fashion interest, and importance fo being well-dressed, but low level of antifashion attitudes. *Fashion rejectors showed low levels of fashion leadership, fashion interest, and importance of being well-dressed, but high level of antifashion attitudes. 4. The seven groups segemented by their fashion orientation showed significant differences according to the educational levels, employment status, and total monthly income. Fashion leaders and fashion independents had higher educational level and monthly income, and involved more women with jobs. 5. Fashion leaders had self-image of being most sophisticated modern, diffenrent, creative, sociable, stood out in a crowd, and complicated life style. Fashion rejectors had self-image of being most down-to-earth, traditional, conventional, stable, reserved, blend into a crowd, and simplified life style. 6. The most effective variables among body cathexis, demographic variabls and self-images in discirminating fashion oreintation group differences were different-conventional, creativestable, and employment status. The discriminating power of above variables were high in very low in discriminating fashion negatives, fashion neutrals, and fashion independents, and the total discriminating power of these variables was 32.25%.