• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.43-53
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• 2023

In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.295-303
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• 2023

As the cloud computing market grows, a variety of cloud services are now reliably delivered. Administrative agencies and public institutions of South Korea are transferring all their information systems to cloud systems. It is essential to develop security solutions in advance in order to safely operate cloud services, as protecting cloud services from misuse and malicious access by insiders and outsiders over the Internet is challenging. In this paper, we propose a zero trust model for cloud storage services that store sensitive data. We then verify the effectiveness of the proposed model by operating a cloud storage service. Memory, web, and network forensics are also performed to track access and usage of cloud users depending on the adoption of the zero trust model. As a cloud storage service, we use Amazon S3(Simple Storage Service) and deploy zero trust techniques such as access control lists and key management systems. In order to consider the different types of access to S3, furthermore, we generate service requests inside and outside AWS(Amazon Web Services) and then analyze the results of the zero trust techniques depending on the location of the service request.

• Knowledge Management Research
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• v.24 no.1
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• pp.31-49
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• 2023

TikTok, as a leading short video platform, has attracted many users, and the resulting attention generates immense business value as a platform to diffuse knowledge. As a qualitative and explorative approach, this study reviews the knowledge payment industry and discusses the influential factors of users' payment decisions regarding knowledge products on TikTok. By conducting in-depth interviews with ten participants and observing 95 knowledge providers' videos, we find that TikTok has significant business potential in the knowledge payment industry. By using the ATLAS. ti software to code the data collected from these interviews, this study finds that demander characteristics (personal needs), product characteristics (product quality), provider characteristics (the key opinion leader effect), and platform characteristics (platform management) are the four core categories that influence users' payment decisions regarding knowledge products on TikTok. A theoretical model consisting of the ten variables of emotional needs, professional needs, quality, price, helpfulness, value, charisma, user trust, service guarantee, and scarcity is proposed based on the grounded theory. The theoretical and practical implications of the study findings are also discussed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.87-96
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• 2023

Recently, research on predicting the treatment results of diseases using deep learning technology is also active in the medical community. However, small patient data and specific deep learning algorithms were selected and utilized, and research was conducted to show meaningful results under specific conditions. In this study, in order to generalize the research results, patients were further expanded and subdivided to derive the results of a study predicting mortality after lung cancer diagnosis for men and women in their 80s, 90s, and 100s. Using AutoML, which provides large-scale medical information and various deep learning algorithms from the Health Insurance Review and Assessment Service, five algorithms such as Decision Tree, Random Forest, Gradient Boosting, XGBoost, and Logistic Registration were created to predict mortality rates for 84 months after lung cancer diagnosis. As a result of the study, men in their 80s and 90s had a higher mortality prediction rate than women, and women in their 100s had a higher mortality prediction rate than men. And the factor that has the greatest influence on the mortality rate was analyzed as the treatment period.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.33-39
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• 2022

This study aims to investigate the online class preference depending on students' gender and school level. To achieve this aim, the study conducted a survey on 4,803 elementary, middle, and high school students in 17 regions nationwide. The valid data of 4,524 were then analyzed using the Apriori algorithm to discern the associated patterns of the online class preference corresponding to their gender and school level. As a result, a total of 16 rules, including 7 from elementary school students, 4 from middle school students, and 5 from high school students were derived. To be specific, elementary school male students preferred software-based classes whereas elementary female students preferred maker-based classes. In the case of middle school, both male and female students preferred virtual experience-based classes. On the other hand, high school students had a higher preference for subject-specific lecture-based classes. The study findings can serve as empirical evidence for explaining the needs of online classes perceived by K-12 students. In addition, this study can be used as basic research to present and suggest areas of improvement for diversifying online classes. Future studies can further conduct in-depth analysis on the development of various online class activities and models, the design of online class platforms, and the female students' career motivation in the field of science and technology.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.925-932
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• 2017

In this study, the analysis of plate under torsion was carried out according to stacking angle at the unidirectional carbon fiber reinforced plastic(UD CFRP) among composite materials. In case of UD CFRP, the material property due to stacking angle becomes different. Also, the stacking angles were designated to 15°, 30°, 45°, 60°, 75° and 90° at the study models. The notch hole was applied at the center part by supposing that rivet or hole was used. The analysis method was used by applying the experimental method at ISO 15310. Two jigs were fixed at the lower part and two jigs were descending at the upper part. As seen by the analysis result values at this study, the shear stress happening at the fracture part was seen with the lowest value in case of the stacking angle of 45°. It is known that the case of the stacking angle of 45°has the structural safety and durability higher than those of the other stacking angles when the torsion applies. It is thought that this result can be applied to the data of basis which can be devoted to the durability when the torsion is applied at CFRP plate.

• Korea Trade Review
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• v.41 no.1
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• pp.91-116
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• 2016

This study proposes a research model to investigate the effect of ICT on national culture and values. Why should we research the relationship between ICT and culture? We do this to shed light on the cultural framework and find areas for further research. This research has found that the development of Information Communication Technology(ICT) has proved to have a positive effect on the quality of individualism (B0.603), there is a decrease in power distance index(B-0.331)and a correlation between individualism and wealth. Also, the development of Information Communication Technology(ICT) has proved to have a positive effect on the quality of Long Term Orientation. As for adoption and use of ICT, the role of culture is important for many reasons. First of all, we can recognize the importance of national culture and organizational culture in establishing the ability of the overall culture to adapt, efficiently merging with different cultures and overcoming potential obstacles of these tasks. This is the evidence supporting the current theory. Our research shows that development of technology highly influences deep human values. Furthermore, the data points used in this research are from World Economic Forum, World Development Indicator and International Telecommunication Union. In order to understand and develop social evolution and progress, we tried to use data that is fair and verifiable.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.458-460
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• 2021

The provision and application of public safety network in Korea is still insufficient for security response to the mobile app of public safety network in the stages of development, initial construction, demonstration, and initial service. The available terminals on the Disaster Safety Network (PS-LTE) are open, Android-based, dedicated terminals that potentially have vulnerabilities that can be used for a variety of mobile malware, requiring preemptive responses similar to FirstNet Certified in U.S and Google's Google Play Protect. In this paper, before listing the application service app on the public safety network mobile app store, we construct a data set for malicious and normal apps, extract features, select the most effective AI model, perform static and dynamic analysis, and analyze Based on the result, if it is not a malicious app, it is suggested to list it in the App Store. As it becomes essential to provide a service that blocks malicious behavior app listing in advance, it is essential to provide authorized authentication to minimize the security blind spot of the public safety network, and to provide certified apps for disaster safety and application service support. The safety of the public safety network can be secured.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.137-144
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• 2023

Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.