• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.136-141
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• 2023

Artificial intelligence is becoming a global hot topic and is being actively applied in various industrial fields. Not only is artificial intelligence being applied to industrial sites in an on-premises method, but cloud-based artificial intelligence platforms are expanding into "as a service" type. The purpose of this study is to develop and verify a measurement tool for an evaluation framework for the adoption of a cloud-based artificial intelligence platform and test the interrelationships of evaluation variables. To achieve this purpose, empirical testing was conducted to verify the hypothesis using an expanded technology acceptance model, and factors affecting the intention to adopt a cloud-based artificial intelligence platform were analyzed. The results of this study are intended to increase user awareness of cloud-based artificial intelligence platforms and help various industries adopt them through the evaluation framework.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1192-1200
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• 2019

Recently, artificial intelligence techniques have been widely used in the computer science field, such as the Internet of Things, big data, cloud computing, and mobile computing. In particular, resource management is of utmost importance for maintaining the quality of services, service-level agreements, and the availability of the system. In this paper, we review and analyze various ways to meet the requirements of cloud resource management based on artificial intelligence. We divide cloud resource management techniques based on artificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloud computing systems. The aim of the paper is to propose an intelligent resource management scheme that manages mobile resources by monitoring devices' statuses and predicting their future stability based on one of the artificial intelligence techniques. We explore how our proposed resource management scheme can be extended to various cloud-based systems.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.3
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• pp.234-246
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• 2023

Purpose: This study aimed to develop a case-based nursing education program using generative artificial intelligence and to assess its usability and applicability in nursing curriculums. Methods: The program was developed by following the five steps of the ADDIE model: analysis, design, development, implementation, and evaluation. A panel of five nursing professors served as experts to implement and evaluate the program. Results: Utilizing ChatGPT, six program modules were designed and developed based on experiential learning theory. The experts' evaluations confirmed that the program was suitable for case-based learning, highly usable, and applicable to nursing education. Conclusion: Generative artificial intelligence was identified as a valuable tool for enhancing the effectiveness of case-based learning. This study provides insights and future directions for integrating generative artificial intelligence into nursing education. Further research should be attempted to implement and evaluate this program with nursing students.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.153-172
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• 2023

We look into the theory of experiential learning, which allows learners to design and organize their own lives, as well as to develop the necessary competencies for students who will be living in intelligent information society. We also investigate the teaching and learning methods, as well as the educational contents of artificial intelligence education, and develop an approach to artificial intelligence education that will develop learners' capabilities. As a result, we have investigated the pedagogical needs for artificial intelligence education in elementary and secondary schools, critically reviewed the discussions on experiential learning-based education for artificial intelligence education in elementary and secondary schools, and proposed a plan. Experiential learning achieves comprehension and knowledge acquisition naturally, as well as subject connection and integration. When preparing for artificial intelligence education, practical methods and procedures for developing capabilities in artificial intelligence education, focusing on in-depth learning, inter-subject linkage and integration, life-related learning, and reflection on the learning process, should be considered unavoidable.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.521-531
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• 2021

The aim of this was to examine the mediating effect of resilience in the relatioinship of stress to emotional intelligence in nursing students experienced COVID-19. The participants in this study were 179 nursing students in 3rd and 4th grade and data were collected using self-reported questionnaires. Data were analyzed using the SPSS/WIN 25.0 program, with descriptive statistics x2-test, t-test, ANOVA, Pearson's correlation. There were significant correlations between college based stress and emotional intelligence(r=-.33, p<.001), clinical based stress and emotional intelligence(r=-.31, p<.001), resilience and emotional intelligence(r=62, p<.001). Resilience showed partial mediating effects in the relationship between college-based stress and emotional intelligence. Resilience showed full mediating effects in the relationship between clinical-based stress and emotional intelligence(Z=-3.07, p<.001). Based on the findings of this study, the enhancement of resilience may positively affect the emotional intelligence of the nursing students, even while they are stress. Therefore, it is necessary to develop effective strategies to enhance resilience for stress.

• Journal of Information Technology Applications and Management
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• v.28 no.2
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• pp.17-33
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• 2021

Korean society is changing into multicultural society with increasing international marriage and immigrant influx. The increasing number of immigrants in Korean society suggests the necessity of social and economic integration of people with diverse cultural backgrounds. We study the entrepreneurial intention of multicultural immigrant. Cultural intelligence is closely related with sustainable value and belief to their eagerness in surviving of the 2nd country. Cultural intelligence is the individual's capability to function or manage effectively in different cultural settings or in multicultural settings. It is assumed that the cultural intelligence of multicultural immigrant might affect the entrepreneurial intention. Based on the theory of planned behavior, we set up the research model. 243 usable responses of multicultural immigrants in Korea were analyzed. Our findings suggest that cultural intelligence positively affected entrepreneurial intention by affecting subjective norm and perceived behavior control. This study contributed the study of the entrepreneurial intention and multicultural immigrant.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1301-1306
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• 2018

Artificial intelligence is one of the key technologies of the Fourth Industrial Revolution. This paper introduces the diverse kinds of approaches to subjects that tackle diverse kinds of research fields such as model-based MS approach, deep neural network model, image edge detection approach, cross-layer optimization model, LSSVM approach, screen design approach, CPU-GPU hybrid approach and so on. The research on Superintelligence and superconnection for IoT and big data is also described such as 'superintelligence-based systems and infrastructures', 'superconnection-based IoT and big data systems', 'analysis of IoT-based data and big data', 'infrastructure design for IoT and big data', 'artificial intelligence applications', and 'superconnection-based IoT devices'.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.113-122
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• 2015

Collective intelligence can be an influential factor of decision-making based on collaboration and information exchange between individuals. Our study explores whether collective intelligence can mitigate the loss aversion effect, bias and error in human judgment, and collective intelligence in online communities can reduce the loss aversion effect. Our community settings display both individual-level and group-level loss aversion effect, investigate effective collective intelligence characteristics like investment commitment, participant experience. Using a multi-method approach our research comprises a web-based experiment with 100 participants investing 3 situations from a real-world community, data from a survey measuring loss aversion behavior of participants. The results suggest the loss aversion effect mitigates under the online-circumstance. Overall, our results suggest that, while collective intelligence mitigates the loss aversion effect, participants do not transfer these results to other settings.

• Journal of Korean Elementary Science Education
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• v.37 no.2
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• pp.126-146
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• 2018

The current study explores students' views about artificial intelligence (AI) through analyses of their drawings and perceptions. The data were gathered from a total of 177 elementary school students. The constant comparative analysis was used as the data analysis method. Based on the result, the current study found that students' views about artificial intelligence were constructed into two distinct dimensions: form and relationship. The form dimension, students' views about artificial intelligence were categorized into human, household goods, machine, smart computer, electronic chip/algorithm, or the hybridized form related to the game of go such as AlphaGo. On the relationship dimension, students' views about artificial intelligence were categorized into servants, friends or enemy. Given the combination of two dimensions, the current study found two noted patterns. The first, students who viewed artificial intelligence as human form perceived artificial intelligence as a friend or an enemy. However, those who viewed artificial intelligence as non-human form perceived artificial intelligence as a servant or an enemy. Based on these results, educational implications related to the preparation of artificial intelligence era for elementary science education are discussed.

• Proceedings of the Korean Society for the Gifted Conference
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• 2002.05a
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• pp.9-30
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• 2002

A 4-year joint research project (1999-2003), entitled "The Development of Multiple Talents (DMT)", has been designed and carrying out under the sponsorship of the National Science Council, R.O.C. (Taiwan). A 3-dimension construct is proposed for the DMT: form of talents (10 forms, mainly based on Gardner′s theory of multiple intelligences), function of talents (3 functions, based on Stemberg′s conception of successful intelligence), and developmental stage (4 stages, from pre-school to senior high). To take an example of its empirical studies, Wu and Chien (2000), based on a renovated conception of personal intelligence, developed the "Personal Intelligence Inventory" (PII). By means of the PII, it was found that there were some personal intelligence differences between gifted and regular pupils: however, gifted group was not as superior as on academic performance to the regular one (Wu '||'&'||' Chien, 2000). It was also found that there were significant relationships between pupils′personal intelligence and school adjustment in both groups (Tsai '||'&'||' Wu, 2000).