• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

• Convergence Security Journal
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• v.21 no.2
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• pp.67-79
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• 2021

Lessons Learned(LL) is a military term defined as all activities that promote future development by finding problems and need improvement in education and reality in the field of warfare development. In this paper, we focus on presenting actual examples and applying AI analysis inference techniques to solve revealed problems in promoting LL activities, such as long-term analysis, budget problems, and necessary expertise. AI legal advice services using cognitive computing-related technologies that have already been practical and in use, were judged to be the best examples to solve the problems of LL. This paper presents intelligent LL inference techniques, which utilize AI. To this end, we want to explore theoretical backgrounds such as LL analysis definitions and examples, evolution of AI into Machine Learning, cognitive computing, and apply it to new technologies in the defense sector using the newly proposed L²-OODA ensemble algorithm to contribute to implementing existing power improvement and optimization.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.299-308
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• 2021

This study aimed at identifying the significant effects and effectiveness of patients with mild dementia when using personalized reminiscence therapy digital services using AI voice technology. In the process of interpreting the results of stakeholder interviews, the design idea of personal customization using voice AI technology was derived, and prototypes were created and usability tests were conducted in the first and second rounds. The main results are as follows: Since reminiscence therapy itself is highly influenced by personal experience and can receive customized care guides based on treatment status and results through customized treatment programs, the concept of personalization can improve the quality of treatment than existing treatment methods. However, it is expected that the usability of the service will further increase if we study micro-interactions that can prevent errors and increase usability, as issues that may arise due to the forgetting cognitive characteristics of mild dementia patients are observed.

• Journal of Medicine and Life Science
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• v.20 no.2
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• pp.53-59
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• 2023

This study explores the potential use of artificial intelligence (AI)-based services, specifically ChatGPT-3.5, in medical education. The application of this technology is acknowledged as a valuable tool for simulating authentic clinical scenarios and enhancing learners' diagnostic and communication skills. To construct a case, students received ChatGPT training using a clinical ethics casebook titled "Clinical Ethics Cases and Commentaries for Medical Students and Physicians." Subsequently, a role-play script was generated based on this training. The initial draft of the script was reviewed by two medical professors and was further optimized using ChatGPT-3.5. Consequently, a comprehensive role-play script, accurately reflecting real-world clinical situations, was successfully developed. This study demonstrates the potential for effectively integrating AI technology into medical education and provides a solution to overcome limitations in developing role-play scripts within conventional educational settings. However, the study acknowledges that AI cannot always generate flawless role-play scripts and recognizes the necessity of addressing these limitations and ethical concerns. The research explores both the potential and limitations of employing AI in the early stages of medical education, suggesting that future studies should focus on overcoming these limitations while further investigating the potential applications of AI in this field.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.715-722
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• 2023

The purpose of this study is to revitalize rehabilitation treatment for people with physical disabilities by presenting a convergence plan between e-sports and rehabilitation exercises using AI-based metaverse. Metaverse-based e-sportscan be useful in providing sports experiences to people with physical disabilities who are unable to participate in society, and this also allows individuals with disabilities to experience sports that are difficult to actually experience. The use of metaverse will enable effective rehabilitation exercise links in vulnerable communities such as hospitals and farming and fishing villages, and provide integrated services of medical and rehabilitation movements that allow exercise data to be managed in an integrated manner. To this end, interdisciplinary experts should participate in the convergence development of e-sports and rehabilitation exercise.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.97-108
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• 2024

Ethical and technical problems are becoming serious as the industrialization of artificial intelligence robots becomes active, research on risk is insufficient. In this situation, the researcher developed 52 verified indicators that can measure the body, rights, property, and social risk of artificial intelligence robots. In order to develop measurement indicators for each type of risk of artificial intelligence robots, 11 experts were interviewed in-depth after IRB deliberation. IIn addition, 328 workers in various fields where artificial intelligence robots can be introduced were surveyed to verify their fieldwork, and statistical verification such as exploratory factor analysis, reliability analysis, correlation analysis, and multiple regression analysis was verifyed to measure validity and reliability. It is expected that the measurement indicators presented in this paper will be widely used in the development, certification, education, and policies of standardized artificial intelligence robots, and become the cornerstone of the industrialization of artificial intelligence robots that are socially sympathetic and safe.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.3
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• pp.145-156
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• 2024

This study explores the integration of cutting-edge technology with records management, aiming to create new value not only in work processes but also in record information services. The research focuses on the case of constructing an "AI-based cultural heritage research record learning data and search system," carried out by the National Research Institute of Cultural Heritage (NRICH) Archives, and analyzes user satisfaction results. "Discovering Cultural Heritage with ZOOM" is a system designed to proactively predict research data demand by constructing big data (learning data) from images (675,338 items) contained in 1,421 volumes of publications in the cultural heritage field, spanning from 1973 to the present, and simultaneously presenting 50 similar images. This initiative aims to foster change and development in the field of records management and cultural heritage in response to the Fourth Industrial Revolution's advanced technologies. It is expected to provide valuable information to researchers, practitioners, and the general public alike.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.206-223
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• 2023

The introduction of Smart technologies such as Artificial Intelligence(AI) systems are have a powerful impact in a variety of industry fields. Some experts predict that smart technology will completely change people's daily life and work styles, causing technological innovation, productivity improvement, and discovery and emergence of new fields. On the one hand, this vision cannot ignore negative views and concerns. Despite many social debates about employment, such as job loss and rising unemployment, there have not been many studies based on employee experience that provide a fundamental solution to the conflict between AI and employment. Therefore, this study finds out the effects and related factors of AI concierge robots for hotel employees, focusing on the hotel industry, and how employees' perceptions of AI concierge robots affect user resistance and turnover intention. This study, conducted a questionnaire survey of 322 hotel employees who had experience working with AI concierge robots in China, and used SPSS and SmartPLS statistical analysis programs to draw conclusions. We found that hotel employees' perceptions of AI concierge robots were significantly related to user resistance and turnover intention, and this association was related to employee self-efficacy, perceived organizational support, quality of AI services and new tasks. In addition, it was found that the quality of AI concierge robots directly or indirectly had the greatest influence on user resistance and turnover intention. The findings of this study provide theoretical implications for academia and practical implications for industry practitioners.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.79-90
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• 2024

This study focused on user trust in ChatGPT, a generative AI technology, and explored the factors that affect usage status and intention to continue using, and whether the influence of trust varies depending on the purpose. For this purpose, the survey was conducted targeting people in their 20s and 30s who use ChatGPT the most. The statistical analysis deploying IBM SPSS 27 and SmartPLS 4.0. A structural equation model was formulated on the foundation of Bhattacherjee's Expectation-Confirmation Model (ECM), employing path analysis and Multi-Group Analysis (MGA) for hypothesis validation. The main findings are as follows: Firstly, ChatGPT is mainly used for specific needs or objectives rather than as a daily tool. The majority of users are cognizant of its hallucination effects; however, this did not hinder its use. Secondly, the hypothesis testing indicated that independent variables such as expectation- confirmation, perceived usefulness, and user satisfaction all exert a positive influence on the dependent variable, the intention for continuance intention. Thirdly, the influence of trust varied depending on the user's purpose in utilizing ChatGPT. trust was significant when ChatGPT is used for information retrieval but not for creative purposes. This study will be used to solve reliability problems in the process of introducing generative AI in society and companies in the future and to establish policies and derive improvement measures for successful employment.

• Asia-Pacific Journal of Business
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• v.9 no.4
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• pp.13-27
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• 2018

This study aims to explore and identify factors of respondent's on the definition of 'smart community facilities', their usage and satisfaction in Malaysia. Study carried out in four sites which were Kota Belud, Kemaman, Lundu and Putrajaya. Data was collected through qualitative method where interviews was carried out with several smart community members in answering factors that drives the usage/participation, satisfaction and continuance intention from using the 'smart community facilities'. Interpretation from the qualitative approach reveals that community thinks infrastructure, content and digital services will help to generate and build up 'smart community'. This will give the benefit for the whole community as well as improve individual efficiency, lifestyles and well-being. Findings demonstrated that the advance of Internet will enhance people usage on being 'smart' and efficient and it should be further improved with better infrastructures, systematic development with sophisticated digital technology services, facilities and structured content, and also safety-security measures in place.