• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.118-119
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• 2019

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.309-316
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• 2018

The main purpose of this study is to understand how cognitive factors influence the way people interact with information/information systems, by conducting comprehensive and in-depth literature reviews and a theoretical synthesis of related research. Adaptive systems have been built around an individual user's characteristics, such as interests, preferences, knowledge and goals. Individual differences in the ability to use new information and communication technology have been an important issue in all fields. Performance differences in utilizing new information and communication technology are sufficiently predictable that we can begin to coordinate them. Therefore, it is necessary to understand cognitive mechanisms to explain differences between individuals as well as the levels of performance. The theoretical synthesis from this study can be applied to design intelligent (i.e., human friendly) systems in our everyday lives. Further research should explore optimization design for user, by integrating user's individual traits (such as emotion and intent) and system modules to improve the interactions of human-system in data-driven environments.

• Journal of Smart Tourism
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• v.2 no.1
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• pp.33-39
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• 2022

This research explores the public's perceptions of the appropriateness of the use of robots in museums and galleries. Using data from an international survey of 1589 participants, the data show that the perceived appropriateness of robot implementation in museums and galleries is driven largely by perceptions of the usefulness and emotional skills of robotic technologies, and their perceived advantages compared to human employees. Additionally, the findings suggest that the general attitudes towards service robots in tourism shape the attitudes towards robots in museums and galleries in particular. Furthermore, the findings reveal that the demographic characteristics of visitors are not related to their perceptions of robots in museums and galleries.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.1
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• pp.17-21
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• 2023

The primary objective of this research is to utilize machine learning models to analyze factors tailored to each dataset for predicting mental health conditions. The study aims to develop appropriate models based on specific datasets, with the goal of accurately predicting mental health states through the analysis of distinct factors present in each dataset. This approach seeks to design more effective strategies for the prevention and intervention of depression, enhancing the quality of mental health services by providing personalized services tailored to individual circumstances. Overall, the research endeavors to advance the development of personalized mental health prediction models through data-driven factor analysis, contributing to the improvement of mental health services on an individualized basis.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.307-313
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• 2024

This study explores the integration of Explainable Artificial Intelligence (XAI) and network science in healthcare, focusing on enhancing healthcare data interpretation and improving diagnostic and treatment methods. Key methodologies like Graph Neural Networks, Community Detection, Overlapping Network Models, and Time-Series Network Analysis are examined in depth for their potential in patient health management. The research highlights the transformative role of XAI in making complex AI models transparent and interpretable, essential for accurate, data-driven decision-making in healthcare. Case studies demonstrate the practical application of these methodologies in predicting diseases, understanding drug interactions, and tracking patient health over time. The study concludes with the immense promise of these advancements in healthcare, despite existing challenges, and underscores the need for ongoing research to fully realize the potential of AI in this field.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.79-83
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• 2024

Digital Twin technology is rapidly transforming various industries by providing comprehensive virtual models that replicate physical objects or processes. In the context of agriculture, digital twin can be a game-changer. This technology can help in creating precise simulations of farming scenarios, thereby enabling farmers to make data-driven decisions and optimize farm operations. The potential benefits include improved crop yields, resource efficiency, and environmental sustainability. However, the implementation of digital twin technology in agriculture poses challenges, such as data management issues and the need for robust IoT infrastructure. Despite these hurdles, the future of digital twin in agriculture looks promising, with ongoing research and developments aimed at overcoming these obstacles.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.555-562
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• 2023

The Railway Safety Act of 2014 strengthened the 'Railway Safety Management System' to establish autonomous safety management for railway operators and railway facility managers. Accordingly, it is required to establish and implement risk assessment and safety measures for risk management. However, the current risk assessment system is carried out at the fragmented safety management level within individual fields, which has caused difficulties in establishing and implementing risk assessment and safety measures. In addition, the technical standards of the safety management system stipulate that risk assessment of railway operators is mandatory, so standardized standards for risk assessment of railway facilities and railway vehicle maintenance are needed. Therefore, in this paper, we first verified railway risks by analyzing railway accident data for the last 10 years, and proposed a standardized framework to effectively assess and manage risks through a case study of a condition-based smart maintenance system developed based on railway vehicle maintenance data.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.515-530
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• 2023

Purpose : This research aims to develop a data-driven inspection policy for radio stations utilizing the KS Q ISO 2859-1 sampling method, addressing potential regulatory relaxations and impending management challenges. Methods : Using radio station inspection big data from the past six years, we established a simulation model to evaluate the current policy. A new inspection sampling policy framework was designed based on the KS Q ISO 2859-1 method. The study compares the performance of the current and proposed inspection systems, offering insights for an improved inspection strategy. Results : This study introduced a simulation model for inspection system based on the KS Q ISO 2859-1 sampling method. Through various experimental designs, key performance indicators such as non-detection rate and sample proportion were derived, providing foundational data for the new inspection policy. Conclusion : Using big data from radio station inspections, we evaluated current inspection systems and quantitatively compared a new system across diverse scenarios. Our simulation model effectively verified the feasibility and efficiency of the proposed framework. For practical implementation, essential factors such as lot size, inspection cycle, and AQL standards need precise definition and consideration. Enhancing radio station inspections requires a policy-driven approach that factors in socio-economic impacts and solicits feedback from industry participants. Future study should also explore various perspectives related to legislative, institutional, and operational aspects of inspection organizations.

• Asian Journal of Business Environment
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• v.7 no.1
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• pp.5-12
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• 2017

Purpose - In order to achieve the organizational objectives, the behavior of the employees and their collaboration with management should be taken into account. It has been shown that strategic behavior depends on a number of different factors. The aim of this article was determining the relationship between factors related to the strategic behavior. Research design, data, and methodology - Accordingly, a conceptual model was developed and tested in the form of a survey. Participants of the study were the employees working in the social Insurance company of Tehran. Data was collected using a questionnaire conducted among managers and the staff. A correlation model was used for data analysis by employing the SPSS software. Results - The findings showed there was a relationship between employees' engagement and the strategic behavior. Conclusions - Our research has demonstrated the effect of employees' engagement on the strategic-driven behavior, emphasizing the role of employees' engagement in health-care service firms. Although previous service research has focused on the factors that drive employees' performance, it seems that most of this research has been inspired by the idea of the service profit chain, focusing on the effect of employees' satisfaction on performance.

• Asia-Pacific Journal of Business
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• v.8 no.2
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• pp.41-55
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• 2017

This exploratory research compares two particular features of coffee culture, namely the reason why a particular coffee shop is frequented and the reason for going to the chosen coffee shop in Italy and South Korea. A survey was carried out targeted at current undergraduate university students in both countries with data being collected in the late spring and early summer of 2017. The main impetus for this research was to investigate the aforementioned areas given the fact that Italy has such a long standing coffee culture that dates back centuries and is still an industry dominated by independent coffee houses while the Korean coffee industry started developing in the early 1980s and taking off after the 1988 Olympic Games. The Korean coffee industry, in contrast, is driven by the franchise coffee shops such as Starbucks, $Caf{\acute{e}}$ Benne, and The Coffee Bean among others. While both countries have well developed coffee cultures, they developed along very different lines. Data collected from respondents are tabulated and presented followed by an analysis and interpretation of the data. Finally, some suggestions on how to conduct further research in order to better understanding the underpinnings and contributing factors in understanding consumer choice and coffee culture in both Italian and Korea are suggested.