• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.129-135
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• 2015

This study was the content and flow of the present study Karate match. 2011, second elimination rounds national developmen, 7th Korea Open International Championships and National development in first elimination rounds, 2012 is a World Cup game against Karate1 in Busan. Man Of The match in the final three games by 5 grade were selected to match match 15, 30 people. I was about to score the study Karate and attack techniques. The conclusion is as follows: 1) In this study, there was a significant difference in use between the class score and the frequency of use of attack technology. The frequency of use of the technology of attack of each class per 60kg or less, 67kg or less, 75kg or less, was the order of 84kg and more than 84kg or less. Frequency of use disonchigi, apsonchigi, apdollyeochagi, geolgi aphurigi. It was followed by scores of attack technology of class per 84kg or more, 60kg or less, 67kg or less, 75kg or less, the following 84kg. 2) Winner has a lot of attack skills than the loser. The game was a draw and the loser disonchigi, apdollyeochagi, apsonchigi. The winner is aphurigi, apdollyeochagi, apsonchigi in the order of many uses.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.126-132
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• 2019

Creative thinking appears even before it is expressed in language, and its existence is revealed through emotion, intuition, image and body feeling before logic or linguistics rules work. In this study, Lego is intended to present experimental child interactive content that is applied with a computer vision based on image processing techniques. In the case of infants, the main purpose of this content is the development of hand muscles and the ability to implement imagination. The purpose of the analysis algorithm of the OpenCV library and the image processing using the 'VVVV' that is implemented as a 'Node' in the midst of perceptual changes in image processing technology that are representative of object recognition, and the objective is to use a webcam to film, recognize, derive results that match the analysis and produce interactive content that is completed by the user participating. Research shows what Lego children have made, and children can create things themselves and develop creativity. Furthermore, we expect to be able to infer a diverse and individualistic person's thinking based on more data.

• Journal of Industrial Convergence
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• v.22 no.4
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• pp.21-29
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• 2024

This study analyzed the difficulty of scoring in different match situations in relation to which competitor scored first. The study analyzed the data from the 2022 Guadalajara World Taekwondo Championships. The analysis was performed for two separate weight classes: lightweight and heavyweight. Four game content variables were used: whether the athlete scored first, attack type, attack area, and game situation. Descriptive statistics, the Rasch model, and discrimination function questions were applied for data processing. SPSS and Winsteps were used for the statistical analysis, and the statistical significance level was set at 0.05. Consequently, in the lightweight class, the scoring frequency of the first scorer was high for all the game variables. In the heavyweight class, the scoring frequency for the first scorer was high for the attack type and attack area. By contrast, those who did not score first were more frequently found to be in a loss situation. By analyzing the scoring difficulties in different match situations based on whether the competitor scored first, the athletes who scored first in attack type most easily scored first. In losing situations, the athletes who scored first in attack area scored most easily, whereas those who did not score first scored most easily in body and match situations. For the heavyweight class, those who scored first in terms of attack type, counter-attack, and attack area scored the most easily while winning in body and match situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1689-1705
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• 2023

To deal with the potential XSS vulnerabilities in the source code of the power communication network, an XSS vulnerability detection method combining the static analysis method with the dynamic testing method is proposed. The static analysis method aims to analyze the structure and content of the source code. We construct a set of feature expressions to match malignant content and set a "variable conversion" method to analyze the data flow of the code that implements interactive functions. The static analysis method explores the vulnerabilities existing in the source code structure and code content. Dynamic testing aims to simulate network attacks to reflect whether there are vulnerabilities in web pages. We construct many attack vectors and implemented the test in the Selenium tool. Due to the combination of the two analysis methods, XSS vulnerability discovery research could be conducted from two aspects: "white-box testing" and "black-box testing". Tests show that this method can effectively detect XSS vulnerabilities in the source code of the power communication network.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.390-402
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• 2014

This study, based upon the Sturges' crisis stages, examines the crisis response communication strategies of Korea Professional Football League(KPFL) for the K-league match-fixing case as well as the frequency of related news articles and the source of information. To explore the crisis response communication strategies the Korea Professional Football League used, a total of 118 news articles were analyzed using the content analysis and frequency analysis. The unit of analysis for crisis response communication strategies is sentence. The frequency of news articles based upon the crisis stages shows highest rate at the acute crisis stage. The source of information for news reports shows that KPFL was one of the major sources of the news reports. KPFL's crisis response communication strategy throughout all stages of the crisis stage shows that corrective action strategy was used highest ratio. In particular, the crisis response communication strategy between team, player and KPFL was shown lack of consistency throughout all crisis stages. Implication and future research direction for the results are discussed.

• Food Science of Animal Resources
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• v.34 no.4
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• pp.543-551
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• 2014

The aim of this study was to evaluate the effect of proteolytic (Serratia liquefaciens, match %: 99.39) or lipolytic (Acinetobacter genomospecies 10, match %: 99.90) psychrotrophic bacteria (bacterial counts, analysis of free fatty acids (FFA) and analysis of free amino acids) on the microbial and chemical properties (yogurt composition), and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) of yogurt during storage. Yogurts were prepared with raw milk preinoculated with each psychrotrophic bacteria. The total solid, fat, and protein content were not affected by preinoculation, but the pH of yogurt preinoculated with psychrotrophic bacteria was higher than in control. There was a dramatic increase in short chain free fatty acids among FFA in yogurt with Acinetobacter genomospecies 10. For 14 d of cold storage condition, SCFFA was 25.3 mg/kg to 34.4 mg/kg (1.36 times increased), MCFFA was 20.4 mg/kg to 25.7 mg/kg (1.26 times increased), and LCFFA was 240.2 mg/kg to 322.8 mg/kg (1.34 times increased). Serratia liquefaciens (match %: 99.39) in yogurt caused a greater accumulation of free amino acids (FAA), especially bitter peptides such as leucine, valine, arginine, and tyrosine, but SDS-PAGE showed that the inoculation of Serratia liquefaciens did not affect the degree of casein degradation during storage. Taken together, the excessive peptides and FFA in yogurt generated from psychrotrophic bacteria could develop off-flavors that degrade the quality of commercial yogurt products.

• Journal of Korea Technology Innovation Society
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• v.19 no.1
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• pp.80-104
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• 2016

Existing methodologies of technology planning about promising new technology focused on target technology itself, so it is true that socio-environmental context which the relevant technology has influence on is not well understood. In this respect, this study is aimed to questingly examine that news content analysis methodologies widely available in the field of science communication can be applied as a complementary methodology for contextual understanding of socio-environment in terms of technology planning about promising new technology. In the co-evolutionary environment of technology-society, promising new technology shows hype phenomenon regarding the relation with the society. Based on this, this study performed news content analysis and examined if the consequences of analysis would match hype cycle. It tried to explore substantive content understanding by socio-environment factors according to specific news frame content. To do this, new content analysis was performed targeting cloud computing as a representative promising new technology. The result of news content analysis targeting general newspapers, business news, IT special newspapers revealed that the tendency of news reporting matched the trend of hype cycle. Particularly, it was verified that reporting attitude and news frame analysis provided useful information to understand contextual content depending on social, economic, and cultural environment factors about promising new technology. The results of this study implied that news content analysis could overcome the limitation of technology information analysis focusing on academic journal patent usually applied for technology planning and could be used as a complementary methodology for understanding the context depending on macro-environment factors. In conclusion, application of news content analysis on the phase of macro-environment analysis of technology planning could contribute to the securement of mutually balanced view in the co-evolutionary perspective of technology-society.

• Korea Science and Art Forum
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• v.37 no.3
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• pp.125-134
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• 2019

This study was conducted to organize a program to classify and analyze the characteristics of images for the automation of background music selection in the video content production process. The results and contents of the study are as follows: video characteristics are selected as subject category, emotion, pixel motion speed, color, and character material. Subject categories and feelings were extracted using Microsoft's Azure Video Indexer, Pixel Movement Speed was an Optional flow, Color was an Image Histogram for Image, and character materials was CNN(Convolutional Neural Network). The results of this study are significant in that video analysis was conducted to match background music in the recent content production process of 'Internet One-person Broadcasting Creators'.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.263-283
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• 2024

Users' comments after online shopping are critical to product reputation and business improvement. These comments, sometimes known as e-commerce reviews, influence other customers' purchasing decisions. To confront large amounts of e-commerce reviews, automatic analysis based on machine learning and deep learning draws more and more attention. A core task therein is sentiment analysis. However, the e-commerce reviews exhibit the following characteristics: (1) inconsistency between comment content and the star rating; (2) a large number of unlabeled data, i.e., comments without a star rating, and (3) the data imbalance caused by the sparse negative comments. This paper employs Bidirectional Encoder Representation from Transformers (BERT), one of the best natural language processing models, as the base model. According to the above data characteristics, we propose the F_MixBERT framework, to more effectively use inconsistently low-quality and unlabeled data and resolve the problem of data imbalance. In the framework, the proposed MixBERT incorporates the MixMatch approach into BERT's high-dimensional vectors to train the unlabeled and low-quality data with generated pseudo labels. Meanwhile, data imbalance is resolved by Focal loss, which penalizes the contribution of large-scale data and easily-identifiable data to total loss. Comparative experiments demonstrate that the proposed framework outperforms BERT and MixBERT for sentiment analysis of e-commerce comments.

• The Research Journal of the Costume Culture
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• v.26 no.2
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• pp.203-216
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• 2018

This study explores sustainability education in textile and apparel (T&A) programs in U.S. higher education institutions. Specifically, the researchers study whether more courses with sustainability focus are offered in higher-ranked institutions and explore whether sustainability is taught more in specific T&A related subject fields. Content analysis was conducted for 3,200 courses found in online course catalogs or the course information sites of 69 institutions. Institutions were selected from the 2015 rankings of the top 50 fashion design and top 50 fashion merchandising schools in the US on www.fashion-schools.org. All cases were coded by two coders with a Cohen's Kappa score of 97.5%, indicating good interrater reliability. Coded data were analyzed through descriptive statistics, correlation analysis, and t-tests. The findings show that sustainability is being integrated into the curricula and across courses of T&A programs in the U.S. Over half of the institution surveyed offered at least one sustainability embedded course. Higher ranked institutions provided more sustainability-related courses than power-ranked institutions. A natural match between the subject field and specific sustainability theme was observed (e.g., cultural diversity in history/culture and social psychology/education; recycle/reuse in textile science; sustainability in fashion design; social responsibility and ethics in industry/consumer). The need to introduce sustainability in courses holistically is discussed, whereby sustainability within the industry supply chain is examined in a connected way.