• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.69-82
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• 2023

High-tech sensibility textile and fashion, in which consumers' emotions and various textile and fashion technologies are converged, is an important industrial group. It is important to develop the ability to apply in practice by gathering the creative by understanding other fields and exchanging ideas through interdisciplinary collaboration in the field of emotional engineering. Through interdisciplinary research and collaboration, talent must be nurtured of individuals who would lead the era of the 4^th Industrial Revolution with the ability to empathize with others as well as the creative convergence-type intellectual ability necessary for the rapidly changing society. To determine content-creation methods, basic research is conducted. Additionally, this study investigates on the current status and educational process of the emotional textile-fashion industry worldwide. To nurture talents in the textile and fashion sensibility science, the basic contents are created to manage the knowledge that delivers sensibility science and the ICT related to this field, as well as in the intensive, PB-style conceptual design based on sensibility. The process from derivation of consumer emotion analysis and product development can be experienced through smart kit practice. Moreover, various methods are developed to set up intellectual property rights generated while developing ICT convergence products as start-ups. The study also covers new knowledge rights to develop emotional textile fashion.

• The Plant Pathology Journal
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• v.36 no.4
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• pp.335-345
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• 2020

Tomato grey mould has been one of the destructive fungal diseases during tomato production. Ten mM of menadione sodium bisulfite (MSB) was applied to tomato plants for eco-friendly control of the grey mould. MSB-reduced tomato grey mould in the 3rd true leaves was prolonged at least 7 days prior to the fungal inoculation of two inoculum densities (2 × 10⁴ and 2 × 10⁵ conidia/ml) of Botrytis cinerea. Protection efficacy was significantly higher in the leaves inoculated with the lower disease pressure of conidial suspension compared to the higher one. MSB-pretreatment was not effective to arrest oxalic acid-triggered necrosis on tomato leaves. Plant cell death and hydrogen peroxide accumulation were restricted in necrotic lesions of the B. cinereainoculated leaves by the MSB-pretreatment. Decreased conidia number and germ-tube elongation of B. cinerea were found at 10 h, and mycelial growth was also impeded at 24 h on the MSB-pretreated leaves. MSB-mediated disease suppressions were found in cotyledons and different positions (1st to 5th) of true leaves inoculated with the lower conidial suspension, but only 1st to 3rd true leaves showed decreases in lesion sizes by the higher inoculum density. Increasing MSB-pretreatment times more efficiently decreased the lesion size by the higher disease pressure. MSB led to inducible expressions of defence-related genes SlPR1a, SlPR1b, SlPIN2, SlACO1, SlChi3, and SlChi9 in tomato leaves prior to B. cinerea infection. These results suggest that MSB pretreatment can be a promising alternative to chemical fungicides for environment-friendly management of tomato grey mould.

• Journal of IKEEE
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• v.24 no.2
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• pp.529-535
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• 2020

As the main technology of the 4th industrial revolution, immersive 360-degree video contents are drawing attention. The market size of immersive 360-degree video contents worldwide is projected to increase from $6.7 billion in 2018 to approximately $70 billion in 2020. However, most of the immersive 360-degree video contents are distributed through illegal distribution networks such as Webhard and Torrent, and the damage caused by illegal reproduction is increasing. Existing 2D video industry uses copyright filtering technology to prevent such illegal distribution. The technical difficulties dealing with immersive 360-degree videos arise in that they require ultra-high quality pictures and have the characteristics containing images captured by two or more cameras merged in one image, which results in the creation of distortion regions. There are also technical limitations such as an increase in the amount of feature point data due to the ultra-high definition and the processing speed requirement. These consideration makes it difficult to use the same 2D filtering technology for 360-degree videos. To solve this problem, this paper suggests a feature point extraction and identification technique that select object identification areas excluding regions with severe distortion, recognize objects using deep learning technology in the identification areas, extract feature points using the identified object information. Compared with the previously proposed method of extracting feature points using stitching area for immersive contents, the proposed technique shows excellent performance gain.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.175-186
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• 2021

The roles and functions of domestic public libraries are diversifying, but various problems have emerged due to internally biased book lending. In addition, due to the 4th Industrial Revolution, public libraries have introduced a book recommendation system focusing on popular books, but the variety of books that users can access is limited. Therefore, in this study, the public library unborrowed book recommendation system was implemented limiting its spatial scope to Duryu Library in Daegu City to enhance the satisfaction of public library users, by using the loan records data (213,093 cases), user information (35,561 people), etc. and utilizing methods like cluster analysis, topic modeling, content-based filtering recommendation algorithm, and conducted a survey on actual users' satisfaction to present the possibility and implications of the unborrowed book recommendation system. As a result of the analysis, the majority of users responded with high satisfaction, and was able to find the satisfaction was relatively high in the class classified by specific gender, age, occupation, and usual reading. Through the results of this study, it is expected that some problems such as biased book lending and reduced operational efficiency of public libraries can be improved, and limitations of the study was also presented.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.321-335
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• 2020

Given that with the development of the 4th industry, interest and desire for smart cities are gradually increasing and related technologies are developed as a way to strengthen urban competitiveness by utilizing big data, information and communication technology, IoT, M2M, and AI, the purpose of this study is to find out how to achieve this goal on the premise of the idea of smart well fair city. In other words, the purpose is to devise a smart well-fair city in the care area, such as health care, medical care, and welfare, and see if it is feasible. With this recognition, the paper aimed to review the concept and scope of smart city, the discussions that have been made so far and the issues or limitations on its connection to social security and social welfare, and based on it, come up with the concept of welfare city. As a method of realizing the smart welfare city, the paper reviewed characteristics and features of a social security platform as well as the applicability of smart city, especially care services. Furthermore, the paper developed discussions on the standardization of the city in terms of political and institutional improvements, utilization of personal information and public data as well as ways of institutional improvement centering on social security information system. This paper highlights the importance of implementing the digitally based community care and smart welfare city that our society is seeking to achieve. With regard to the social security platform based on behavioral design and the 7 principles(6W1H method), the present paper has the limitation of dealing only with smart cities in the fields of healthcare, medicine, and welfare. Therefore, further studies are needed to investigate the effects of smart cities in other fields and to consider the application and utilization of technologies in various aspects and the corresponding impact on our society. It is expected that this paper will suggest the future course and vision not only for smart cities but also for the social security and welfare system and thereby make some contribution to improving the quality of people's lives through the requisite adjustments made in each relevant field.

• Culinary science and hospitality research
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• v.18 no.3
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• pp.90-107
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• 2012

This research has been conducted to discover the consumer's behavior in the purchase and consumption of korean alcoholic beverages. The intent of these works are to contribute to the growth of the traditional alcoholic beverages markets by giving necessary data for the marketing strategies and the development of favorite beverage to meet the consumer's tastes. The surveys have been conducted against a group of people ranging from their 20's to 60's randomly picked from seoul. The duration of the surveys was from August 1st to September 30th, 2010. We also examined the relationship between the selection attributes of traditional liquor and purchase satisfaction by consumer's life-styles. SPSS 18.0 statistical package was used to process data. Frequency analysis, factor analysis, a reliability test, K-means cluster analysis, one-way ANOVA and multiple regression were executed. As a result, through factor analysis and cluster analysis, authors identified 6 factors in the selection attributes of traditional liquor(characteristics, taste & fragrance, popularity, design, harmony, interest), 4 consumer groups(expert, fan, beginner, indifference), 4 consuming lifestyles(social oriented consuming style, maniac consuming style, pursuit of knowledge consuming style, outsider consuming style). Among the selection attributes of traditional liquor, taste & fragrance and popularity had effects on purchase satisfaction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.276-279
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• 2022

The 4th industrial revolution refers to the transition to a knowledge society in which the production speed of knowledge is fast and the proportion of the knowledge industry is greatly increased. The reorganization of the industrial structure and the change of occupations and jobs due to new technologies are bringing about changes in education, and the development of digital technology has made education that is borderless, individual and dynamic, becoming the new standard of education. With these changes, interest in nano-degrees on new technologies or micro-degrees focused on core courses rather than regular course degrees is increasing. As a representative example, Udacity in the United States has opened and operated online nanodegree courses related to jobs, and collaborates with major companies to develop and educate core training courses necessary for companies, thereby efficiently supporting companies in securing talent. With the revitalization of online vocational and job training, an environment has been prepared in which individuals can set goals for vocational competency development and continue their portfolio-based sustainable learning. However, for effective vocational education, automated and personalized educational content design should be preceded. To this end, in this paper, we propose a personalized career and course map recommendation system in the era of online learning

• The Journal of Bigdata
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• v.6 no.1
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• pp.23-35
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• 2021

In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.

• Industry Promotion Research
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• v.8 no.4
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• pp.91-99
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• 2023

The purpose of this study was to confirm the determination of the career attitude of multicultural youth, which will be the growth engine of Korean society in the future, and to determine the effect of parental support for multicultural youth on career attitude determination. Multicultural adolescents experience more difficulties in parental support and career attitude determination than ordinary adolescents due to confusion over biculturalism exposed at birth. Therefore, this study confirmed the effect of parental support of multicultural adolescents on career attitude determination and verified the effect of bicultural acceptance attitude. To this end, data from the 8th year of the Multicultural Youth Panel (MAPS) conducted by the Korea Youth Policy Institute were used, and a total of 1,229 multicultural teenagers in the 2nd year of high school participated in the study. For data analysis, frequency analysis, descriptive statistical analysis, correlation analysis, path model suitability verification, path model coefficient, and mediating effect verification were conducted. Based on the results of these studies, it was intended to provide basic data for developing an integrated program that improves parental support and career attitude determination of multicultural adolescents.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.1-12
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• 2021

With the recent 4th Industrial Revolution, the growth and value of big data are continuously increasing, and the government is also actively making efforts to open and utilize public data. However, the situation still does not reach the level of demand for public data use by citizens, At this point, it is necessary to identify research trends in the public data field and seek directions for development. In this study, in order to understand the research trends related to public data, the analysis was performed using topic modeling, which is mainly used in text mining techniques. To this end, we collected papers containing keywords of 'Public data' among domestic and foreign research papers (1,437 domestically, 9,607 overseas) and performed topic modeling based on the LDA algorithm, and compared domestic and foreign public data research trends. After analysis, policy implications were presented. Looking at the time series by topic, research in the fields of 'personal information protection', 'public data management', and 'urban environment' has increased in Korea. Overseas, it was confirmed that research in the fields of 'urban policy', 'cell biology', 'deep learning', and 'cloud·security' is active.