• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2550-2572
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• 2023

Epidemiological survey is an important means for the prevention and control of infectious diseases. Due to the particularity of the epidemic survey, 1) epidemiological survey in epidemic prevention and control has a wide range of people involved, a large number of data collected, strong requirements for information disclosure and high timeliness of data processing; 2) the epidemiological survey data need to be disclosed at different institutions and the use of data has different permission requirements. As a result, it easily causes personal privacy disclosure. Therefore, traditional access control technologies are unsuitable for the privacy protection of epidemiological survey data. In view of these situations, we propose a black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data. Firstly, a black box-assisted multi-attribute authority management mechanism without a trusted center is established to avoid authority deception. Meanwhile, the establishment of a master key-free system not only reduces the storage load but also prevents the risk of master key disclosure. Secondly, a sensitivity classification method is proposed according to the confidentiality degree of the institution to which the data belong and the importance of the data properties to set fine-grained access permission. Thirdly, a hierarchical authorization algorithm combined with data sensitivity and hierarchical attribute-based encryption (ABE) technology is proposed to achieve hierarchical access control of epidemiological survey data. Efficiency analysis and experiments show that the scheme meets the security requirements of privacy protection and key management in epidemiological survey.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.41-50
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• 2024

Korea is facing a significant problem with historically low fertility rates, which is becoming a major social issue affecting the economy, labor force, and national security. This study analyzes the factors contributing to the regional gap in fertility rates and derives policy implications. The government and local authorities are implementing a range of policies to address the issue of low fertility. To establish an effective strategy, it is essential to identify the primary factors that contribute to regional disparities. This study identifies these factors and explores policy implications through machine learning and explainable artificial intelligence. The study also examines the influence of media and public opinion on childbirth in Korea by incorporating news and online community sentiment, as well as sentiment fear indices, as independent variables. To establish the relationship between regional fertility rates and factors, the study employs four machine learning models: multiple linear regression, XGBoost, Random Forest, and Support Vector Regression. Support Vector Regression, XGBoost, and Random Forest significantly outperform linear regression, highlighting the importance of machine learning models in explaining non-linear relationships with numerous variables. A factor analysis using SHAP is then conducted. The unemployment rate, Regional Gross Domestic Product per Capita, Women's Participation in Economic Activities, Number of Crimes Committed, Average Age of First Marriage, and Private Education Expenses significantly impact regional fertility rates. However, the degree of impact of the factors affecting fertility may vary by region, suggesting the need for policies tailored to the characteristics of each region, not just an overall ranking of factors.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.551-562
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• 2024

This study relates to a method and device for extracting and tracking moving objects. In particular, objects are extracted using different images between adjacent images, and the location information of the extracted object is continuously transmitted to provide accurate location information of at least one moving object. It relates to a method and device for extracting and tracking moving objects based on tracking moving objects. People tracking, which started as an expression of the interaction between people and computers, is used in many application fields such as robot learning, object counting, and surveillance systems. In particular, in the field of security systems, cameras are used to recognize and track people to automatically detect illegal activities. The importance of developing a surveillance system, that can detect, is increasing day by day.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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• pp.25-32
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• 2024

Purpose: This study utilizes big data from the 8th (2021) National Health and Nutrition Examination Survey to determine first, the relationship between chewing discomfort in the elderly and some systemic diseases and second, whether oral diseases and oral health problems are related to systemic diseases. Since this may have an impact, we aim to provide basic data to facilitate the expansion and emphasize the importance of integrated health management education. Methods: Original data from the 8th (2021) National Health and Nutrition Survey, conducted by the Korea Centers for Disease Control and Prevention, were analyzed using SPSS Version 21.0 (IBM). A complex sample frequency analysis was conducted to confirm the general and health-related characteristics of the study subjects, and a complex sample cross-analysis was conducted to determine chewing discomfort according to both general and health-related characteristics. Complex sample multiple logistic regression analysis was conducted to determine the effect on chewing discomfort. Results: In order to analyze the factors that affect chewing discomfort, the general characteristics that showed significant differences in chewing discomfort were adjusted for age, personal income, education level, basic livelihood security, high blood pressure, subjective health status, and subjective oral health. It was found that the condition had a statistically significant effect on chewing discomfort. Conclusion: The findings of this study demonstrate that high blood pressure, subjective health status, and subjective oral health status affect chewing discomfort; hence, measures such as developing and operating programs to improve national oral health are needed. We hope that our study will be used as basic data for research into chewing discomfort and systemic diseases in the elderly.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.41-49
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• 2024

This paper discusses the modeling and implementation of a worker location system at a shipbuilding site. The importance of worker location in an industrial environment is highlighted as a critical element in the prevention of industrial accidents. The paper presents a worker tracking system that integrates power line and beacon communication to accurately track worker position. Through experiments, the paper demonstrates how to monitor the changes in worker location based on different scenarios and how to access the status of worker location using the manager's web service. The paper can be used for the design of a system that will provide real-time location information to safety managers for the improvement of worker safety management.

• Journal of Platform Technology
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• v.12 no.3
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• pp.55-61
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• 2024

As the digital environment becomes more complex and cyber attacks become more sophisticated, the importance of data protection is emerging. As various security threats such as data leakage, system intrusion, and authentication bypass increase, secure key management is emerging. Key Management System (KMS) manages the entire encryption key life cycle procedure and is used in various industries. There is a need for a key management system that considers requirements suitable for the environment of various industries including public and finance. The purpose of this paper is to derive the characteristics of the key management system for each industry by comparing and analyzing key management systems used in representative industries. As for the research method, information was collected through literature and technical document analysis and case analysis, and comparative analysis was conducted by industry sector. The results of this paper will be able to provide a practical guide when introducing or developing a key management system suitable for the industrial environment. The limitations are that the analyzed industrial field was insufficient and experimental verification was insufficient. Therefore, in future studies, we intend to conduct specific performance tests through experiments, including key management systems in various fields.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.201-208
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• 2024

This study aims to analyze the causes and characteristics of conflicts arising from the relocation of national defense facilities, focusing on the Jeonju Aviation School relocation project, and to explore effective conflict management strategies. As urbanization progresses, military facilities initially located on the outskirts of cities have been integrated into urban areas, increasing the need for relocation. This process frequently results in conflicts among the government, the military, and local residents due to differing interests. This study employs a combination of literature review and surveys to examine perceptions of conflict causes and resolution strategies. The findings reveal that the primary conflict factors include inadequate information provision and consultation, noise and property value decline, and unilateral decision-making processes. Participatory decision-making was found to be effective in resolving conflicts. Based on these findings, the study proposes policy recommendations such as institutional improvements, enhanced information disclosure and communication, comprehensive compensation systems, and strengthened expertise in conflict management. This research is significant in empirically confirming the importance of participatory decision-making in national defense facility relocation projects and providing specific policy suggestions for conflict management.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3501-3511
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• 2024

Titanium alloys play a vital role in optimizing the effectiveness and security of nuclear reactors, strengthening structural durability, and facilitating the effective handling of nuclear waste. The aim of this study is to investigate the gamma-ray, neutron, and transmission properties of four common titanium alloys through the examination of the deposited energy amount in the liquid sodium coolant material, in relation to the mechanical properties of these alloys. MCNP (version 6.3) is utilized for designing the titanium pipes. Next, the pipes were re-designed considering the elemental mass fractions and densities of the investigated titanium alloys. Grade 26 sample is reported with the highest values of mass attenuation coefficients and the lowest HVL values among those investigated alloys. Grade 26 is reported to have the lowest TF value, whereas Grade 12 demonstrated the highest TF value. The highest Effective Removal Cross Section (Σ_R, 1/cm) value against fast neutrons is reported for Grade 26. The utilization of Grade 26 sample as pipe material resulted in the lowest deposited energy amount (MeV/g) and subsequent lowest contamination in the coolant material. Out of the alloys that were chosen for analysis, it has been determined that Grade 26 exhibits the highest level of strength. It can be concluded that the Grade 26 alloy exhibits desirable characteristics for applications in nuclear technologies that require superior gamma-ray and neutron absorption properties, as well as exceptional mechanical properties. Nevertheless, it is essential to emphasize the importance for ongoing studies to enhance the existing material properties of Grade 26, with the aim of achieving improved safety and efficacy in nuclear applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.5
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• pp.147-157
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• 2024

This study empirically analyzed the impact of technological innovation on corporate performance and the moderating effect of technology commercialization capability in this relationship. The purpose was to identify the impact of technological innovation activities, divided into process innovation and product innovation, on financial and non-financial performance, and to clarify the role of technology commercialization capability. An online survey was conducted with 300 companies from April to May 2024, and the results were analyzed using SPSS 29.0 and Process macro. The results showed that technological innovation had a positive effect on both non-financial and financial performance of the company. In addition, it was confirmed that the higher the technology commercialization capability, the stronger the impact of technological innovation on non-financial performance. However, technology commercialization capability did not significantly moderate the relationship between technological innovation and financial performance. This study empirically demonstrated the importance of technology commercialization capability in the relationship between technological innovation and corporate performance, and is expected to provide useful implications for establishing corporate technology innovation strategies and developing policies in the future.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.455-462
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• 2024

In the construction industry, known for its dynamic and hazardous environments, there exists a crucial demand for effective safety incident prevention. Traditional approaches to monitoring on-site safety, despite their importance, suffer from being laborious and heavily reliant on subjective, paper-based reports, which results in inefficiencies and fragmented data. Additionally, the incorporation of computer vision technologies for automated safety monitoring encounters a significant obstacle due to the lack of suitable training datasets. This challenge is due to the rare availability of safety accident images or videos and concerns over security and privacy violations. Consequently, this paper explores an innovative method to address the shortage of safety-related datasets in the construction sector by employing generative artificial intelligence (AI), specifically focusing on the Stable Diffusion model. Utilizing real-world construction accident scenarios, this method aims to generate photorealistic images to enrich training datasets for safety surveillance applications using computer vision. By systematically generating accident prompts, employing static prompts in empirical experiments, and compiling datasets with Stable Diffusion, this research bypasses the constraints of conventional data collection techniques in construction safety. The diversity and realism of the produced images hold considerable promise for tasks such as object detection and action recognition, thus improving safety measures. This study proposes future avenues for broadening scenario coverage, refining the prompt generation process, and merging artificial datasets with machine learning models for superior safety monitoring.