• The Journal of Information Systems
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• v.30 no.3
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• pp.177-199
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• 2021

Purpose This study explores the development direction of the artificial intelligence curriculum as a universal education that enhances the ability of college students to flexibly use artificial intelligence these days, where artificial intelligence education is spreading, and the educational components based on this are subdivided according to the characteristics of each major. Design/methodology/approach In order to develop the educational purpose of the subject and the detailed educational curriculum suitable for the subject of education, we first analyzed domestic and foreign prior research related to artificial intelligence liberal arts education. As the main components derived by experts, the basic concept of artificial intelligence converges to literacy to read and write for everyday problem solving, as well as problem-solving ability to manipulate real data and software. Findings The results showed that In the artificial intelligence literacy module, trends and prospects of artificial intelligence and necessary competencies were checked, and cases applied to major fields were examined. In the AI utilization and application part, basic data analysis items and content composition were composed through creative thinking, logical thinking, and intelligence. In order to design the curriculum, a software development language suitable for each major area was first selected, and AI education content areas, elements, and packages were defined and designed for each major area to meet the objectives of the subject.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.55-63
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• 2022

Although research on the leader's or speaker's voice has been continuously conducted, existing research has a single point of view. Sound analysis of voice characteristics has been studied from engineering perspectives, and leadership trait theory has been studied from a business perspective. Convergence studies on leader voice and member cognition are being attempted today. Convergence research on voice has a positive effect on refinement of voice analysis, diversification of voice use, and establishment of voice utilization strategy. This study explains the current flow of research on convergence between speaker's voice and listener's perception, and suggests a direction for the future development of voice fusion research. Furthermore, in connection with AI in the 4th industrial age, new attempts for voice research are sought. First, advances in AI focus on strategically generating the voices needed for individual situations. Second, the voice corrected in real time will support the leader and speaker to utilize the desired voice type. Third, voices through AI based on big data will affect the cognition, attitude and behavior of individual listeners who members, customers, and students in more diverse situations. The purpose and significance of this study is to suggest the way to research the leader's voice recognized by members, and to suggest a method that can be applied in various situations.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.760-761
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• 2019

Smart manufacturing is a process of integrating computer-related technologies in production and by doing so, achieving more efficient production management. The recent development of supercomputers has led to the broad utilization of artificial intelligence (AI) and machine learning techniques useful in predicting specific patterns. Despite the usefulness of AI and machine learning techniques in smart manufacturing processes, there are many fundamental issues with the direct deployment of these technologies related to data management. In this paper, we focus on solving the outlier detection issue in smart manufacturing applications. More specifically, we apply a state-of-the-art outlier detection technique, called Elliptic Envelope, to detect anomalies in simulation-based collected data.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.108-111
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• 2024

클라우드 사용이 보편화 되고 확대됨에 따라, 서비스를 유연하게 확장 및 축소하여 신속하게 시장의 수요에 대응할 수 있는 PaaS(Platform-as-a-Service) 형태의 서비스가 많은 기업에서 각광받고 있다. 그리고 이러한 PaaS 형 서비스의 핵심이 되는 기술인 컨테이너(Container)와 컨테이너 관리를 효율화 해주는 쿠버네티스(Kubernetes)가 실질적인 표준으로 사용되고 있다. 이때 쿠버네티스 기반의 환경에서 서비스 어플리케이션은 다양한 구성사례가 존재하나, DB 는 아직 안정성 및 데이터 정합성 등을 이유로 베어메탈(Baremetal)이나 VM(Virtual Machine)을 기반으로 구성하고 있는 상황이다. 그러나, 인프라 구성 및 운영에 있어서도 파드(Pod) 형태의 DB 구성은 베어메탈 및 VM 대비 장점이 존재한다고 생각하여 본 실험을 수행하였다. 본 논문에서는 서비스 응답시간 및 자원 사용의 효율성 측면에서 VM 기반의 DB 와 쿠버네티스 파드 기반의 DB 에 각각 트래픽을 발생시켜서 비교한 결과와 시사점을 제시한다.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.4
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• pp.333-351
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• 2023

This study investigates user behavior in library spaces through the lens of AI camera analytics. By leveraging the face recognition and tracking capabilities of AI cameras, we accurately identified the gender and age of visitors and meticulously collected video data to track their movements. Our findings revealed that female users slightly outnumbered male users and the dominant age group was individuals in their 30s. User visits peaked between Tuesday to Friday, with the highest footfall recorded between 14:00 and 15:00 pm, while visits decreased over the weekend. Most visitors utilized one or two specific spaces, frequently consulting the information desk for inquiries, checking out/returning items, or using the rest area for relaxation. The library stacks were used approximately twice as much as they were avoided. The most frequented subject areas were Philosophy(100), Religion(200), Social Sciences(300), Science(400), Technology(500), and Literature(800), with Literature(800) and Religion(200) displaying the most intersections with other areas. By categorizing users into five clusters based on space utilization patterns, we discerned varying objectives and subject interests, providing insights for future library service enhancements. Moreover, the study underscores the need to address the associated costs and privacy concerns when considering the broader application of AI camera analytics in library settings.

• Convergence Security Journal
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• v.24 no.3
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• pp.117-129
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• 2024

With the announcement of Transformer, a new type of architecture, in 2017, there have been many changes in language models. In particular, the development of LLM (Large language model) has enabled generative AI services such as search and chatbot to be utilized in various business areas. However, security issues such as personal information leakage and reliability issues such as hallucination, which generates false information, have raised concerns about the effectiveness of these services. In this study, we aimed to analyze the factors that are increasing the frequency of using generative AI in the workplace despite these concerns. To this end, we derived eight factors that affect the quality of LLM-based generative AI response data and empirically analyzed the impact of these factors on job satisfaction using a valid sample of 195 respondents. The results showed that expertise, accessibility, diversity, and convenience had a significant impact on intention to continue using, security, stability, and reliability had a partially significant impact, and completeness had a negative impact. The purpose of this study is to academically investigate how customer perception of response data quality affects business utilization satisfaction and to provide meaningful practical implications for customer-centered services.

• Knowledge Management Research
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• v.25 no.3
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• pp.145-171
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• 2024

Literacy initially referred to the ability to read and understand written documents and processed information. With the advancement of digital technology, the scope of literacy expanded to include the access and use of digital information, evolving into the concept of digital literacy. The application and purpose of digital literacy vary across different fields, leading to the use of various terminologies. This study focuses on generative artificial intelligence (AI), which is gaining increasing importance in the AI era, to assess users' literacy levels. The research aimed to extend the concept of literacy proposed in previous studies and develop a tool suitable for Korean users. Through exploratory factor analysis, we identified that generative AI literacy consists of four factors: AI utilization ability, critical evaluation, ethical use, and creative application. Subsequently, confirmatory factor analysis validated the statistical appropriateness of the model structure composed of these four factors. Additionally, correlation analyses between the newly developed literacy tool and existing AI literacy scales and AI service evaluation tools revealed significant relationships, confirming the validity of the tool. Finally, the implications, limitations, and directions for future research are discussed.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1789-1803
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• 2022

With the increase of data and the development of AI technology, the strategies and policies related to integrated data are being actively established to increase the usability of data all over the world. Recently, in the research field, infrastructure projects and management systems are being prepared to utilize research data at the initiative of the government. Also, in Korea, platforms for searching and sharing research data are being actively developed. The National Disaster Management Research Institute (NDMI) has been conducting extensive research on disaster & safety as a national institute, but data-oriented management and utilization are insufficient. Because it still lacks consistent data management systems, metadata for outcomes of research, experts on data and policies for utilization of data to research. In order to move to the data-based research paradigm, we defined the master plans and verified a target model for the integrated management and utilization of disaster & safety research data. In this study, we found out the need to establish differentiated data governance, such as data standardization and unification of the data management system, and dedicated organization for managing data, based on the necessity and actual demands of NDMI. In order to verify the effectiveness of the target model reflecting the derived implications, we intend to establish a pilot mode. In the future, major improvement measures to establish a disaster & safety research data management system will be implement.

• Communications of Mathematical Education
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• v.38 no.2
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• pp.263-286
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• 2024

With the introduction of AI digital textbooks, interest in the use of technology tools in mathematics education is increasing. Technology tools have the advantage of visualizing mathematical concepts and discovering mathematical principles through experimentation and inquiry. The 2015 revised mathematics curriculum in Korea already mentions the use of technology tools, and accordingly, various teaching and learning activities using technology tools are presented in mathematics textbooks. However, there is still a lack of systematic analysis on the types and utilization methods of technology tools presented in textbooks. Therefore, this study analyzed the current status of the use of technology tools presented in high school mathematics textbooks based on the 2015 revised curriculum. To this end, the types of technology tools presented in mathematics textbooks were categorized, and the utilization ratio of each category was investigated. In addition, the utilization patterns of technology tools were analyzed by subject and content area, and the utilization ratio of technology tools according to the type of teaching and learning activities was examined. The results showed that technology tools were used in various types and ratios according to the subject and content area. In particular, technology tools in the symbol-manipulation graphing software category accounted for 58% of the total usage cases, showing the highest proportion. By subject, the use of symbol-manipulation graphing software was prominent in subjects dealing with the analysis area, while the use of dynamic geometry software was relatively high in the geometry area. In terms of teaching and learning activity types, the utilization ratio of auxiliary tool type (49%) and intended inquiry induction type (37%) was high. The results of this study show that technology tools play various roles in mathematics textbooks and provide useful implications for improving mathematics teaching and learning methods using technology tools in the future. Furthermore, it can contribute to the establishment of educational policies related to AI digital textbooks and the development of teacher training programs.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.237-253
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• 2018

In a rapidly changing environment, dynamic resources have become important factors for companies, the use of Big Data come into focus new core value of business but researches on the major resources and capabilities of companies are insufficient. In this study, the effect of dynamic capability and entrepreneurial orientation in the SMEs on the intention of Big Data utilization are explored. For the purpose of empirical analysis, the survey condusted of 364 domestic SMEs to analyze the effect of dynamic capability on the intention of Big Data utilization through entrepreneurial orientation, performed a parallel multi-parameter analysis of using SPSS Win Ver.22.0 and PROCESS macro v3.0. The results of hypothesis testing showing that dynamic resources and entrepreneurial orientation had positive influence intention of big data utilization. For the determinants of Big Data utilization related to AI it provide suggestions thereby improving the understanding of dynamic capabilities and entrepreneurial orientation and helping to improve the management of SMEs.