• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.849-854
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• 2018

Radio base stations, which are widely distributed across large areas, have many difficulties in managing them. Unmanned radio base stations in remote mountains are having a hard time accessing them in case of emergencies. Major telephone service providers only remotely control incoming and outgoing information and local small business partners responsible for maintaining actual facilities do not possess such technologies, so they are each checked during field visits. In this study, in order to process the sensor raw data and smoothing, we apply the particle filters and confirmed that the performance of sensor data accuracy is increased. Integrated system using temperature, humidity, fire condition, and power operation at a wide range of radio base stations under the real-time monitoring status is operated well. It show that all of the status of base station are monitored at the remote office using the cloud server through internet networking.

• The Journal of Bigdata
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• v.5 no.1
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• pp.139-145
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• 2020

In the era of the 4th Industrial Revolution, the use of information based on AI APIs has a great influence on industry and life. In particular, the use of artificial intelligence data in the medical field will have many changes and effects on society. This paper is to study the necessary components to implement the "Cognitive Health Advisor model (CHA model)" and to implement the "CHA model using chatbot" based on this. It uses the open Cognitive chatbot to analyze and analyze the health status of users changing in their daily lives. The user's health information analyzed by the biometric sensor and chatbot consultation delivers the information to the user through the chatbot. And it implements a cognitive health advisor model that provides educational information for users' health promotion. Through this implementation, it intends to confirm the possibility of future use and to suggest research directions.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.177-188
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• 2020

In the digital world, creative industries such as music, movies, and drama have been the most impacted by digital transformation. As these contents were converted to a digital format of 0s and 1s, the business model changed and so did the rules of competition in the market. Apple, Spotify, and Netflix were quick to ride the digital transformation wave to become market leaders in the creative industry. This study reviews case studies in the creative industry to grasp the important factors necessary for market restructuring using digital technology. It was found that companies that set visions, platform, and open innovation as business strategies were able to achieve critical mass and become market leaders. These three elements are commonly found in the contents industry. On the other hand, companies that did not embrace digital innovation have become victims of digital darwinism. By analysing the experience of digital product innovation through case studies in the creative industry, we can derive implications for digital transformation in the 4th industrial revolution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.20-29
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• 2021

In the Industry 4.0 era, artificial intelligence has attracted considerable interest for learning mass data to improve the accuracy of forecasting and classification. On the other hand, the current method of detecting anomalies relies on traditional statistical methods for a limited amount of data, making it difficult to detect accurate anomalies. Therefore, this paper proposes an artificial intelligence-based anomaly detection methodology to improve the prediction accuracy and identify new data patterns. In particular, data were collected and analyzed from the point of view that sensor data collected at vehicle idle could be used to detect abnormalities. To this end, a sensor was designed to determine the appropriate time length of the data entered into the forecast model, compare the results of idling data with the overall driving data utilization, and make optimal predictions through a combination of various sensor data. In addition, the predictive accuracy of artificial intelligence techniques was presented by comparing Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) as the predictive methodologies. According to the analysis, using idle data, using 1.5 times of the data for the idling periods, and using CNN over LSTM showed better prediction results.

• Information Systems Review
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• v.22 no.3
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• pp.15-30
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• 2020

In the real estate industry, the latest changes in the Fourth Industrial Revolution, such as big data analytics, machine learning, and VR (virtual reality), combine to bring about industry change. Proptech is a new term combining properties and technology. This study aims to derive and analyze from a comprehensive perspective the quality factors (systems, services, interfaces, information) for mobile real estate brokerage services that are well known and used in the domestic market. The surveys in this study were conducted online and offline and a total of 161 samples were used for statistical analysis. As a result, all hypotheses were approved to except system quality and service quality. The results show that the domestic proptech companies who are mostly focused on real estate brokerage services, peer-to-peer lending, advertising platforms and apartments need to grow in various fields of proptech business of other countries including Europe, USA and China.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.149-156
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• 2020

In the Fourth Industrial Revolution, successful cases using big data in various industries are reported. This paper examines cases that successfully use big data in the medical industry to develop the service and draws implications in value that big data create. The related work introduces big data technology in the medical field and cases of eight innovative service in the big data service are explained. In the introduction, the overall structure of the study is mentioned by describing the background and direction of this study. In the literature study, we explain the definition and concept of big data, and the use of big data in the medical industry. Next, this study describes the several cases, such as technologies using national health information and personal genetic information for the study of diseases, personal health services using personal biometric information, use of medical data for efficiency of business processes, and medical big data for the development of new medicines. In the conclusion, we intend to provide direction for the academic and business implications of this study, as well as how the results of the study can help the domestic medical industry.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.453-454
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• 2023

4차산업 혁명의 대표 영역인 인공지능은 과학기술뿐 아니라 사회, 경제, 문화 등 우리 사회의 전 분야에 적용되어가고 있다. 이것은 교육기관에서 인공지능 관련 컴퓨터 전공자만이 아닌 여러 전공 각 분야의 전공자 또한 인공지능 교육을 받아야 함을 의미하는 것이다. 이에 따라 전 분야에 걸친 A·I융합 인재의 양성이 관심사항이 되고 있다. 본 논문에서는 항공정비사 양성을 위한 국토교통부 전문교육기관 지정기준에 제시된 교육과목 및 내용에 소프트웨어 교육을 위해 시스템 제어에 관한 이론/실습교육의 추가를 제안하였다. 제안한 교육내용은 항공정비 분야에서의 A·I융합 인재양성에 한 방안이 될 것이라 기대한다.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.133-145
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• 2022

As a result of the study, the poorest keywords were information, big data, management, policy, government, law, and smart. In addition, as a result of network analysis, related research was being conducted on topics such as data industry policy, data governance performance, defense, governance, and data public. The four topics derived through topic modeling were "DG policy," "DG platform," "DG in laws," and "DG implementation," of which research related to "DG platform" showed an increasing trend, and "DG implementation" tended to shrink. This study comprehensively summarized data governance-related studies. Data governance needs to expand research areas from various perspectives and related fields such as data management and data integration policies at the organizational level, and related technologies. In the future, we can expand the analysis targets for overseas data governance and expect follow-up studies on research directions and policy directions in industries that require data-based future industries such as Industry 4.0, artificial intelligence, and Metaverse.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.441-453
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• 2021

Recently, the untact healthcare industry due to COVID-19 has been attracting attention, and the telemedicine industry based on medical information has become a field of the healthcare industry receiving attention. However, in Korea, due to obstacles in the legal system, telemedicine is still illegal between doctors and patients. In the case of neighboring China, the reality is the opposite of the recent rapid growth of the telemedicine industry under the leadership of the government. This study looks at this from the perspective of the industrial innovation system on the grounds that telemedicine is an industry and innovative technology needs to be changed to clarify the difference between domestic and Chinese telemedicine industries. As a result of analyzing China's telemedicine industry on the seven sub-divisions of demand conditions, innovators, networks et al., Such as seizing appropriate opportunities for demand driving effects and appropriate communication between economic actors were identified as major success factors. This researcher proposes the following suggestions. first, it conforms to the current digital New Deal policy flow, and conducts a demand survey on the change in demand for medical services in the 4th Industrial Revolution and the Untact Era. For the introduction, a plan to conduct a demand survey for the public and second, second, a plan to grow and intensively foster digital high-tech medical care as a new industry was suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.188-198
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• 2021

The purpose of this study is to verify the mediating effect from acceptance of the latest 4th Industrial Revolution technologies on the relationships between interest in the latest technologies, resistance to the latest technologies, and anxiety in workers at welfare institutions for the disabled. In order to achieve this goal, data were collected from July to August 2018 from workers at disability welfare centers in P Metropolitan City, and we analyzed data from 187 persons. Multiple regression analysis was applied to test the causal relationships between variables; the step-by-step analysis model of Baron and Kenny (1986) was used to verify mediating effects, and the Sobel test was performed to verify their significance. The analyses verified that the degree of interest in the latest technologies affects the degree of resistance to, and anxiety over, the latest technologies through acceptance of the latest technologies. At the same time, we verified that the degree of interest had a complete mediation effect because it did not directly affect the acceptance. In addition, the Sobel test result showed that the mediating effect was statistically significant. In other words, it was found that the degree of interest in the latest 4th Industrial Revolution technologies from workers at welfare institutions for the disabled increases the possibility of adaptation to future society by lowering resistance and anxiety through acceptance of the latest technologies. Based on these results, a plan to reduce resistance to, and anxiety over, the latest technologies was sought, and related measures to increase interest in the latest technologies and their acceptance are suggested.