• Journal of Digital Convergence
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• v.16 no.5
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• pp.221-229
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• 2018

Machine learning and artificial intelligence are core technologies for the 4th industrial revolution. However, it is difficult for the general public to get familiar with those technologies because most people lack programming ability. Thus, we developed a Graphic User Interface(GUI) to overcome this obstacle. We adopted TensorFlow and used .Net of Microsoft for the develop. With this new GUI, users can manage data, apply algorithms, and run machine learning without coding ability. We hope that this development will be used as a basis for developing artificial intelligence in various fields.

• Health Policy and Management
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• v.34 no.2
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• pp.103-105
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• 2024

Artificial intelligence (AI) technology is rapidly spreading across various industries. Accordingly, interest in ethical issues arising from the use of AI is also increasing. This is particularly true in the healthcare sector, where AI-related ethical issues are a significant topic due to its focus on health and life. Hence, this issue aims to examine the ethical concerns when using AI tools during research and publication processes. One of the key concerns is the potential for unintended plagiarism when researchers use AI tools for tasks such as translation, citation, and editing. Currently, as AI is not given authorship, the researcher is held accountable for any ethical problems arising from using AI tools. Researchers are advised to specify which AI tools were used and how they were employed in their research papers. As more cases of ethical issues related to AI tools accumulate, it is expected that various guidelines will be developed. Therefore, researchers should stay informed about global consensus and guidelines regarding the use of AI tools in the research and publication process.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.29-38
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• 2023

The purpose of this study is to explore how citizens perceive application of the metaverse platforms for city marketing and investigate factors that affect overall attitude for citizen relationship management in the public sector. In particular, this study investigates the following: i) how factors including perceived city brand value, public service, emotional value, experience, personalization, economic value, social value, and cultural value on overall attitude and ii) how overall attitude affects intention to use of metaverse for the public sector and citizen satisfaction. This study conducted an online survey with the assistance of a well-known research firm. This study applied factor, ANOVA, and regression analysis to test hypotheses. The results found that effects of perceived city brand value, emotional value, information, economic value, social value, and cultural value on overall attitude toward metaverse application for the public sector showed significance. The results provide managerial and policy implications for the public sector on how to apply metaverse to provide public services and enhance engagement with citizens. The results also provide implications which aspects should be considered to enhance citizen relationship management and to build the better city brand value by applying metaverse.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.231-232
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• 2023

It is important to utilize an efficient quality management platform because the management of deadlines at construction sites requires rapid and accurate processing of numerous defect data in a short time. In this study, 30 domestic patents for defect management and image analysis were analyzed to examine the development status of quality management platforms using mobile devices. As a result of the analysis, research on automatically detecting defects using artificial intelligence has been actively underway in recent years, and advanced IT technologies have been converging in various ways into linked services.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.187-195
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• 2018

Recently, the 4th industrial revolution has emerged as the core for enhancing national competitiveness, the development of a technology roadmap to efficiently develop related technologies to realize super intelligence as a main feature of the 4th Industrial Revolution is a major task has been highlighted. The objective of this study is to analyze the domestic and foreign technology level in the artificial intelligence field which is the core technology of the 4th Industrial Revolution era and to present the direction of development based on this. The keyword network analysis and the blank technical analysis based on the IPC classification were performed on the data derived from the keyword search of 'AI (Artificial Intelligence)' among domestic and foreign patent data. As a result, the number of domestic artificial intelligence related technology development was 1.2% compared with developed countries such as USA and Europe. In the major development fields, data recognition technology and digital information transmission technology were relatively insufficient. Through this study, we obtained the blank technology as a result of comparative analysis of domestic artificial intelligence related technologies compared to advanced countries and suggested the direction of domestic artificial intelligence technology development in future.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.531-540
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• 2021

As cyber attacks and crimes increase exponentially and hacking attacks become more intelligent and advanced, hacking attack methods and routes are evolving unpredictably and in real time. In order to reinforce the enemy's responsiveness, this study aims to propose a method for developing an artificial intelligence-based security control platform by building a next-generation security system using artificial intelligence to respond by self-learning, monitoring abnormal signs and blocking attacks.The artificial intelligence-based security control platform should be developed as the basis for data collection, data analysis, next-generation security system operation, and security system management. Big data base and control system, data collection step through external threat information, data analysis step of pre-processing and formalizing the collected data to perform positive/false detection and abnormal behavior analysis through deep learning-based algorithm, and analyzed data Through the operation of a security system of prevention, control, response, analysis, and organic circulation structure, the next generation security system to increase the scope and speed of handling new threats and to reinforce the identification of normal and abnormal behaviors, and management of the security threat response system, Harmful IP management, detection policy management, security business legal system management. Through this, we are trying to find a way to comprehensively analyze vast amounts of data and to respond preemptively in a short time.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.233-242
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• 2019

Numerous space perception studies have shown that Euclidean 3-D structure cannot be recovered from binocular stereopsis, motion, combination of stereopsis and motion, or even with combined multiple sources of optical information. Humans, however, have no difficulties to perform the task-specific action despite of poor shape perception. We have applied humans skill and capabilities to artificial intelligence and computer vision but those machines are still far behind from humans abilities. Thus, we need to understand how we perceive depth in space and what information we use to perceive 3-D structure accurately to perform. The purpose of this paper was to review space perception literatures to apply humans abilities to artificial intelligence robots more advanced in future.

• Korean Journal of Artificial Intelligence
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• v.9 no.1
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• pp.15-20
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• 2021

This paper was conducted to prevent and respond to crimes by predicting crimes based on artificial intelligence. While the quality of life is improving with the recent development of science and technology, various problems such as poverty, unemployment, and crime occur. Among them, in the case of crime problems, the importance of crime prediction increases as they become more intelligent, advanced, and diversified. For all crimes, it is more critical to predict and prevent crimes in advance than to deal with them well after they occur. Therefore, in this paper, we predicted crime types and crime tools using the Multiclass Logistic Regression algorithm and Multiclass Neural Network algorithm of machine learning. Multiclass Logistic Regression algorithm showed higher accuracy, precision, and recall for analysis and prediction than Multiclass Neural Network algorithm. Through these analysis results, it is expected to contribute to a more pleasant and safe life by implementing a crime prediction system that predicts and prevents various crimes. Through further research, this researcher plans to create a model that predicts the probability of a criminal committing a crime again according to the type of offense and deploy it to a web service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.303-304
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• 2021

In the 21st century, as we enter the Fourth Industrial Revolution, research in various fields utilizing big data is being conducted, and innovative and useful technologies are constantly emerging in the world. Among several technologies recently in the big data era, among various fields utilizing some algorithms of artificial intelligence, it shines in the field of finance and is used for pin tech, financial fraud detection and risk management, etc., and recently Even in the booming stock market, it is used for investment prediction and investment factor analysis using artificial intelligence algorithm models. In this paper, we plan to investigate various research cases and investigate trends in how they are used in the stock market through artificial intelligence that utilizes big data.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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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.