• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1563-1583
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• 2018

With the deregulation of electronic finance, FinTech has been revitalized. The discussion on artificial intelligence is active in the financial industry. However, there is a problem of increasing security threats behind new technologies. Security vulnerabilities have increased because we are more connected than before, and the channels and entities of the financial industry have diversified. Although there are technical and policy discussions on security, the essence of all discussions is human. Fundamentals of finance are trust and security, and attention to human factors is important. This study presents the role of human and artificial intelligence for financial security, respectively. Furthermore, this derives a collaborative model in which human and artificial intelligence complement each other's limitations. To support this, it first discusses the development of finance and IT, AI, human factors, and financial security threats. This study suggests that the security threats will intensify in the era of new technology, but it can overcome them by using machinery and technology.

• Journal of Korean Philosophical Society
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• v.147
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• pp.261-281
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• 2018

This paper will cover recent discussions on the risks of human being due to the development of artificial intelligence(AI). We will consider AI research as artificial narrow intelligence(ANI), artificial general intelligence(AGI), and artificial super intelligence(ASI). First, we examine the risks of ANI, or weak AI systems. To maximize efficiency, humans will use autonomous AI extensively. At this time, we can predict the risks that can arise by transferring a great deal of authority to autonomous AI and AI's judging and acting without human intervention. Even a sophisticated system, human-made artificial intelligence systems are incomplete, and virus infections or bugs can cause errors. So I think there should be a limit to what I entrust to artificial intelligence. Typically, we do not believe that lethal autonomous weapons systems should be allowed. Strong AI researchers are optimistic about the emergence of artificial general intelligence(AGI) and artificial superintelligence(ASI). Superintelligence is an AI system that surpasses human ability in all respects, so it may act against human interests or harm human beings. So the problem of controlling superintelligence, i.e. control problem is being seriously considered. In this paper, we have outlined how to control superintelligence based on the proposed control schemes. If superintelligence emerges, it is judged that there is no way for humans to completely control superintelligence at this time. But the emergence of superintelligence may be a fictitious assumption. Even in this case, research on control problems is of practical value in setting the direction of future AI research.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.354-368
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• 2022

The purpose of this study was to verify whether there were significant differences in the levels and relationships of emotional intelligence, school adaptation, self-resilience, positive human relationships, and depression between elementary school students who participated in after-school music activities and those who did not. The participants of this study were 379 fourth, fifth, and sixth grade elementary school students in the Capital Area and Gyeongnam Province participated in after-school music activities and 368 students who did not, totaling 747 students. For research analysis, t-test and multi-group analysis were performed, and the analyzed results are as follows. First, the level of emotional intelligence, self-resilience, positive human relationships, and school adaptation were higher in the participating group and the level of depression was lower than the group that did not participate. Second, as a result of multiple group analysis, the participating group had stronger influences on the paths of [emotional intelligence→self-resilience], [emotional intelligence→positive human relationship], [emotional intelligence→depression], [emotional intelligence→school adaptation], and [self-resilience→school adaptation] than those of non-participating group. Third, the participating group showed mediating effects from self-resilience, positive human relationships, and depression in the relationship between emotional intelligence and school adaptation. On the other hand, the non-participating group manifested significant mediating effects only from self-resilience and depression variables in the relationship between emotional intelligence and school adaptation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2334-2347
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• 2023

Metaverse services generate text data, data of ubiquitous computing, in real-time to analyze user emotions. Analysis of user emotions is an important task in metaverse services. This study aims to classify user sentiments using deep learning and pre-trained language models based on the transformer structure. Previous studies collected data from a single platform, whereas the current study incorporated the review data as "Metaverse" keyword from the YouTube and Google Play Store platforms for general utilization. As a result, the Bidirectional Encoder Representations from Transformers (BERT) and Robustly optimized BERT approach (RoBERTa) models using the soft voting mechanism achieved a highest accuracy of 88.57%. In addition, the area under the curve (AUC) score of the ensemble model comprising RoBERTa, BERT, and A Lite BERT (ALBERT) was 0.9458. The results demonstrate that the ensemble combined with the RoBERTa model exhibits good performance. Therefore, the RoBERTa model can be applied on platforms that provide metaverse services. The findings contribute to the advancement of natural language processing techniques in metaverse services, which are increasingly important in digital platforms and virtual environments. Overall, this study provides empirical evidence that sentiment analysis using deep learning and pre-trained language models is a promising approach to improving user experiences in metaverse services.

• Korean Journal of Human Ecology
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• v.14 no.3
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• pp.379-386
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• 2005

Bowlby has proposed that child-mother attachment is important in the child's representation of self. In this study, the child's emotional intelligence was examined in connection with child-mother attachment with a sample of 5-year-olds. The quality of attachment was assessed based on the child's behavior on reunion following a separation, using a SSP (Strange Situation Procedure) system devised by Main and Solomon. The emotional intelligence was assessed with Lee's Scale for young children. The results show significant connections between child-mother attachment and the emotional intelligence. Specific areas of emotional intelligence are related to particular patterns of attachment. Namely, securely attached children are assessed significantly higher than the unsecurely attached, not only in the ability to identify and control their own emotions, but also in the ability to control others' emotional state. Also, securely attached children perceive their social competence significantly higher.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1049-1058
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• 2022

HAR(Human Action Recognition) such as anomaly and object detection has become a trend in research field(s) that focus on utilizing Artificial Intelligence (AI) methods to analyze patterns of human action in crime-ridden area(s), media services, and industrial facilities. Especially, in real-time system(s) using video streaming data, HAR has become a more important AI-based research field in application development and many different research fields using HAR have currently been developed and improved. In this paper, we propose and analyze a deep-learning-based HAR that provides more efficient scheme(s) using an intelligent AI models, such system can be applied to media services using RGB video streaming data usage without feature extraction pre-processing. For the method, we adopt Slowfast based on the Deep Neural Network(DNN) model under an open dataset(HMDB-51 or UCF101) for improvement in prediction accuracy.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.2
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• pp.108-115
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• 2023

Alongside the rapid development of AI technology, which is stepping in to do tasks more quickly and less prone to error than humans can, the possibility for MI (multiple intelligence) development warrants equal attention and fervor. Recent theories of human intelligence point beyond standard cognitive capacity, IQ, and shine a light on the other unique potentials naturally endowed to humans. The applicability of MI to aviation is discussed, suggesting that it is important to consider ways to integrate MI development techniques into pilot education and training. Experiential starting points are discussed.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.1
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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.

• Korean Journal of Human Ecology
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• v.21 no.4
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• pp.649-664
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• 2012

The purpose of this study was to examine the impact of the emotional intelligence of preservice early childhood teachers on their self-concept and self-efficacy in an attempt to provide some information on the development of the emotional intelligence of preservice early childhood teachers. The subjects in this study were the freshmen, sophomores and juniors who were in the departments of early childhood education in private colleges and universities in Chungcheong, Kyonggi, Seoul, in Korea. After a survey was conducted, the following findings were given: First, the juniors had the best self-concept of the others, and the freshmen were ahead of the others in self-efficacy. The university students had a better self-concept than the college students. Second, emotional intelligence had a statistically significant positive correlation to self-concept and self-efficacy. Third, all the sub-factors of emotional intelligence exerted a statistically significant positive influence on self-concept. Among the sub-factors of emotional intelligence, emotional regulation and emotional utilization exerted a statistically significant positive influence on self-efficacy. The findings of the study illustrated that the preservice early childhood teachers had a better self-concept and a better self-efficacy when they were better at emotional intelligence.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.803-812
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• 2021

This study explored the concept of artificial intelligence and the problem-solving process that can be explained through literature research. Through this study, the educational meaning and application plan of artificial intelligence that can be explained were presented. XAI education is a human-centered artificial intelligence education that deals with human-related artificial intelligence problems, and students can cultivate problem-solving skills. In addition, through algorithmic education, it is possible to understand the principles of artificial intelligence, explain artificial intelligence models related to real-life problem situations, and expand to the field of application of artificial intelligence. In order for such XAI education to be applied in elementary schools, examples related to real world must be used, and it is recommended to utilize those that the algorithm itself has interpretability. In addition, various teaching and learning methods and tools should be used for understanding to move toward explanation. Ahead of the introduction of artificial intelligence in the revised curriculum in 2022, we hope that this study will be meaningfully used as the basis for actual classes.