• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2867-2881
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• 2022

This study investigates fashion Artificial Intelligence (AI) curation services to expand sustainable consumption. We analyzed the factors that affect the AI fashion curation service experience of women in their 20s and 30s using their clothes. An online survey was conducted from March 29, 2021, to June 4, 2021, for women of the previously mentioned age groups residing in the metropolitan area. Before answering the questionnaire, they installed the "Style Bot" application on their phone, took five or more photos of their clothes according to the manual provided by the application, stored them in a virtual wardrobe on the application, and then responded to the questionnaire using the AI recommended coordinating function. The effect of the properties of fashion AI curation service application on the use of clothes was investigated. Among the attributes of the fashion AI curation service application, convenience, speed, and usefulness were found to have a positive effect on the use of clothes, and promptness had no effect. Second, regarding the impact of clothing utilization on environmental sustainability, clothing utilization was found to have a positive effect on environmental sustainability. Third, environmental sustainability was found to have a positive effect on satisfaction. Fourth, clothing utilization had a positive effect on satisfaction. Thus, fashion AI curation service would help promote service development so that clothes could be used actively through an in-depth understanding of the properties of these services. Finally, the results of this study would contribute to promoting environmental sustainability.

• Clinical and Experimental Pediatrics
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• 제63권6호
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• pp.219-225
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• 2020

Background: There is increasing concern that moderate preterm (32-33 weeks' gestation) and late preterm (34-36 weeks' gestation) birth may be associated with minor neurodevelopmental problems affecting poor school performance. Purpose: We explored the cognitive function, cognitive visual function, executive function, and behavioral problems at school age in moderate to late preterm infants. Methods: Children aged 7-10 years who were born at 32⁺⁰ to 36⁺⁶ weeks of gestation and admitted to the neonatal intensive care unit from August 2006 to July 2011 at the National Health Insurance Service Ilsan Hospital were included. We excluded children with severe neurologic impairments, congenital malformations, or chromosomal abnormalities. Neuropsychological assessments consisted of 5 neuropsychological tests and 3 questionnaires. Results: A total of 37 children (mean age, 9.1±1.2 years) participated. The mean gestational age at birth was 34.6±7.5 weeks, while the mean birth weight was 2,229.2±472.8 g. The mean full-scale intelligence quotient was 92.89±11.90; 24.3% scored between 70 and 85 (borderline intelligence functioning). An abnormal score was noted for at least one of the variables on the attention deficit hyperactivity disorder diagnostic system for 65% of the children. Scores below borderline function for executive quotient and memory quotient were 32.4% and 24.3%, respectively. Borderline or clinically relevant internalizing problems were noted in 13.5% on the Child Behavior Check List. There were no significant associations between perinatal factors or socioeconomic status and cognitive, visual perception, executive function, or behavior outcomes. Conclusion: Moderate to late preterm infants are at risk of developing borderline intelligence functioning and attention problems at early school age. Cognitive and executive functions that are important for academic performance must be carefully monitored and continuously followed up in moderate to late preterm infants.

• 정보교육학회논문지
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• 제25권3호
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• pp.491-499
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• 2021

세계의 주요 국가들은 높은 수준의 인공지능 교육 환경을 구축하고자 국가 차원에서 전략을 수립하고 막대한 자본을 투입하여 실행에 옮기고 있다. 국내의 관계 부처들도 이러한 시대적 흐름에 맞추어 '인공지능 국가전략'을 수립하고 인공지능 교육의 전문성을 향상하여 선도국과의 격차를 해소하기 위한 노력을 기울이고 있다. 본 논문에서는 예비 및 현직 초등교사들을 대상으로 교육현장에서 현재 활용되고 있는 인공지능 수업 콘텐츠를 설명하고, 수업에 참여하였던 학생들이 특별히 선호하는 수업의 내용과 초등교육 현장에 학생들이 직접 적용하고자 계획하는 수업 아이디어를 분류하였다. 그 결과, 예비 및 현직 초등교사들은 인공지능의 기저 이론에 대한 깊이 있는 내용보다는 초등교육에 즉시 적용이 가능한 인공지능 교육 도구 중심의 실습을 더욱 선호하는 경향이 있음을 알게 되었다. 그러나 인공지능의 이론에 대한 충분한 이해를 토대로 인공지능의 활용 역량도 배양될 수 있으므로, 이론 교육에 대한 학습 효과를 향상하기 위한 방안이 향후 연구로써 필요함을 본 연구를 통해 알 수 있었다.

• 한국컴퓨터정보학회논문지
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• 제26권1호
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• pp.275-281
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• 2021

본 연구의 목적은 인공지능예술작품 구매할 때 소비자들이 어떤 감지가 있는지, 그리고 구매의 향과 어떤 관계가 있는지 살펴보는데 있다. 본 연구에서 고객감지가치가 제품감지가치, 서비스감지가치 그리고 사회감지가치 총 3가지를 제시하였다. 이를 바탕으로 고객감지가치와 구매의향 간의 모델을 구축하였다. 연구를 위해 데이터 수집은 온라인 설문 조사를 실시하였다. SPSS24.0와 AMOS24.0을 통해 수집한 데이터의 신뢰성, 타당성 및 구조 방정식 분석을 통해 가설 검증을 하였다. 검정결과를 보면 제품인지가치와 서비스인지가치는 소비자의 온라인 구매의향에 긍정적인 영향을 미친다. 그러나 사회인지가치가 소비자의 구매의향에 영향을 주지 않는 결과가 나타났다.

• 한국안전학회지
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• 제39권2호
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• pp.65-74
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• 2024

We analyzed the relationship between the normal measurement of the seismic accelerometer (SA) and the error rate of the output voltage linear ratio to propose an evaluation method to determine whether the SA in use is measuring normally. Utilizing a test bed, the regular operation of SA in use was evaluated using acceleration data measured through impact tests since there are no regulations regarding performance testing of SA in use. For the used SA, the error rate of the output voltage linear ratio, which is a major performance criterion, was evaluated. We analyzed common characteristics of the SA that satisfied the impact test and the performance criteria of the output voltage linear ratio error rate. The results indicated that we must consider the decreasing trend and convergence of the error rate as the measurement angle increases, ensuring that the average value of the output voltage linear ratio error rate is within 1%.

• 한국응급구조학회지
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• 제21권3호
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• pp.49-58
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• 2017

Purpose: The purpose of this study was to validate the Moral Intelligence Checklist(MIC) of Borba (2001) modified by Kim et al. (2010) for college students majoring in health. Methods: The MIC survey was performed with 348 college students in Gongju, Chungnam. Initial MIC modified by Kim et al. (2010) consists of 7 factors (empathy, self-control, conscience, kindness, fairness, respect and tolerance) and 42 items. Data were analyzed using confirmatory factor analysis. Results: We finally analyzed with 37 items, because 5 items with estimates level below 0.5 were deleted. The Cronbach's ${\alpha}$ of 7 factors were ranged from .780 to .851. Finally, the model fit of GFI(.805), CFI(.864), RMSEA(.033) was satisfied with confirmatory factor analysis using structural equation model. Conclusion: This MIC model is suggested to be used in development of moral intelligence educational programs.

• 한국조리학회지
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• 제23권8호
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• pp.145-152
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• 2017

This study was performed to verify the importance of emotional aspect for hotel employees to derive the organizational commitment and customer orientation. Present study estimated the emotional intelligence as four factors: self emotion, other emotion, emotional utilization, and emotional regulation. Online survey method was used and distributed the questionnaires to hotel employees who are working for restaurants. A total of 300 questionnaires were distributed and 257 participants were employed for statistical analysis using SPSS 21.0 and AMOS 21.0 for Windows. As results, two factors(emotional utilization and emotional regulation) were significant antecedents of organizational commitment, and three factors(self emotion, other emotion, and emotional utilization) were critical predictors of customer orientation. In addition, organizational commitment has significantly influenced the customer orientation. According to the results of this study, hotel restaurant managers or hotel company need to understand the importance of the emotional intelligence for providing better service to their customers as well as improving the organizational commitment. These results will contribute to develop advanced marketing strategics for hotel restaurants employees who have many connections with customers in a hotel.

• 보건의료산업학회지
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• 제9권4호
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• pp.51-62
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• 2015

Objectives : Identify the factors that affect organizational citizenship behavior of hospital nurses, and to provide a basis for developing an effective nursing workforce management system. Methods : Participants of this study were 214 nurses serving at general hospitals located in B Metropolitan City. Data collection was performed from Oct.15th to 25th, 2014. The methods of analyzing data were ANOVA, Scheffe's-Test, Pearson's Correlation Coefficient Analysis and the Stepwise Multiple Regression Analysis according to the SPSS WIN 18.0 Program. Results : Emotional intelligence explained 42.1% of the subjects' organizational citizenship behaviors. This figure increased to 48.7, 51.3 and 52.3%, respectively when other three factors of job satisfaction, age and educational background were added on a one-by-one basis. Conclusions : Considering that emotional intelligence is a critical factor in organizational citizenship behaviors, general hospitals should develop and implement education and training programs that can raise their nurses' emotional intelligence and job satisfaction and, concomitantly, promote their organizational citizenship behaviors provided that feedbacks is provided later.

• 한국인공지능학회지
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• 제12권1호
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• pp.7-16
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• 2024

This study aims to explore driving factors of Artificial Intelligence application for city marketing strategy with perspectives of millennials and generation Z. This study proposed the following research questions: i) how perceived place branding factor, public service factor, affective factor, immersive experience factor, cognitive factor, cost benefit factor, social networking factor, and promotional value factor affect attitude toward AI application for city marketing; and ii) how attitude affect satisfaction and prospect toward AI application for city marketing? This study conducted an online survey with the assistance of a well-known research agency and applied factor and regression analysis to test hypotheses. The results found that effects of place branding, cognitive, social networking, and promotional value affect attitude significantly in the case of millennials, while effects of public service, affective, cost benefit, social networking, and promotional value affect attitude significantly in the case of generation Z. The results found that effects of attitude on satisfaction and prospect of AI showed significance. The results provide implications and different aspects for AI application of city marketing strategy with perspectives by generations, while millennials and generation Z perceived effects of promotional value as the most significant factor for AI application of city marketing strategy.

• 한국의류학회지
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• 제42권1호
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• pp.148-158
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• 2018

This study analyzes recent trends in fashion retailing instigated by the fourth industrial revolution and approaches the trends in terms of the convergence of big data and artificial intelligence. The findings are as below. First, companies like 'Edited' and 'Stylumia' offer solutions that support the strategic decisions of fashion brands and fashion retailers by analyzing big data using artificial intelligence. Second, the convergence of big data and artificial intelligence scales personalized service on the web as examples of 'Coded Couture', 'StitchFix', and 'Thread'. Third, the insights gained from artificial intelligence and big data help create new fashion retailing platforms such as 'Botshop' and 'Lyst'. Last, artificial intelligence and big data assist with design. 'Ivyrevel' designs digital fashion, assisted by a macroscopic perspective on fashion trends, market and consumers through the analysis of big data. The Fourth Industrial Revolution brings changes across all industries that will likely accelerate. The fashion industry is also undergoing many changes with advancements in scientific technology. The convergence of big data and artificial intelligence will play a key role in the future of fast-moving industry like fashion, where fickle tastes of consumers are the main drivers.