• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.214-220
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• 2024

Remote control is used for operating maritime autonomous surface ships. The operator controls the ship using control data generated by the remote control system. To ensure successful remote control, three principles must be followed: safety, reliability, and availability. To achieve this, the suitability of both the control data and operators for remote control must be established. Currently, there are no international regulations in place for evaluating remote control suitability through experiments on actual ships. Conducting such experiments is dangerous, costly, and time-consuming. The goal of this study is to develop a suitability evaluation method using the output values of control devices used in actual ship operation. The proposed method involves evaluating the suitability of data by analyzing the output values and evaluating the suitability of operators by examining their tracking of these output values. The experiment was conducted using a shore-based remote control system to operate the training ship 'Hannara' of Korea National Maritime and Ocean University. The experiment involved an iterative process of obtaining the operator's tracking value for the output value of the ship's control devices and transmitting and receiving tracking data between the ship and the shore. The evaluation results showed that the transmission and reception performance of control data was suitable for remote operation. However, the operator's tracking performance revealed a need for further education and training. Therefore, the proposed evaluation method can be applied to assess the suitability and analyze both the control data and the operator's compliance with the three principles of remote control.

• Smart Media Journal
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• v.13 no.6
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• pp.9-15
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• 2024

In recent trends, there has been an increase in 'Qshing' attacks, a hybrid form of phishing that exploits fake QR (Quick Response) codes impersonating government agencies to steal personal and financial information. Particularly, this attack method is characterized by its stealthiness, as victims can be redirected to phishing pages or led to download malicious software simply by scanning a QR code, making it difficult for them to realize they have been targeted. In this paper, we have developed a classification technique utilizing machine learning algorithms to identify the maliciousness of URLs embedded in QR codes, and we have explored ways to integrate this with existing QR code readers. To this end, we constructed a dataset from 128,587 malicious URLs and 428,102 benign URLs, extracting 35 different features such as protocol and parameters, and used AutoML to identify the optimal algorithm and hyperparameters, achieving an accuracy of approximately 87.37%. Following this, we designed the integration of the trained classification model with existing QR code readers to implement a service capable of countering Qshing attacks. In conclusion, our findings confirm that deriving an optimized algorithm for classifying malicious URLs in QR codes and integrating it with existing QR code readers presents a viable solution to combat Qshing attacks.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.6.1-6.15
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• 2023

Background: Polycyclic aromatic hydrocarbons (PAHs) are occupational and environmental pollutants generated by the incomplete combustion of organic matter. Exposure to PAHs can occur in various occupations. In this study, we compared PAH exposure levels among occupations based on 4 urinary PAH metabolites in a Korean adult population. Methods: The evaluation of occupational exposure to PAHs was conducted using Second Korean National Environmental Health Survey data. The occupational groups were classified based on skill types. Four urinary PAH metabolites were used to evaluate PAH exposure: 1-hydroxypyrene (1-OHP), 2-naphthol (2-NAP), 1-hydroxyphenanthrene (1-OHPHE), and 2-hydroxyfluorene (2-OHFLU). The fraction exceeding the third quartile of urinary concentration for each PAH metabolite was assessed for each occupational group. Adjusted odds ratios (ORs) for exceeding the third quartile of urinary PAH metabolite concentration were calculated for each occupational group compared to the "business, administrative, clerical, financial, and insurance" group using multiple logistic regression analyses. Results: The "guard and security" (OR: 2.949; 95% confidence interval [CI]: 1.300-6.691), "driving and transportation" (OR: 2.487; 95% CI: 1.418-4.364), "construction and mining" (OR: 2.683; 95% CI: 1.547-4.655), and "agriculture, forestry, and fisheries" (OR: 1.973; 95% CI: 1.220-3.191) groups had significantly higher ORs for 1-OHP compared to the reference group. No group showed significantly higher ORs than the reference group for 2-NAP. The groups with significantly higher ORs for 1-OHPHE than the reference group were "cooking and food service" (OR: 2.073; 95% CI: 1.208-3.556), "driving and transportation" (OR: 1.724; 95% CI: 1.059-2.808), and "printing, wood, and craft manufacturing" (OR: 2.255; 95% CI: 1.022-4.974). The OR for 2-OHFLU was significantly higher in the "printing, wood, and craft manufacturing" group (OR: 3.109; 95% CI: 1.335-7.241) than in the reference group. Conclusions: The types and levels of PAH exposure differed among occupational groups in a Korean adult population.

• Journal of the Korean Society for information Management
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• v.41 no.2
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• pp.245-268
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• 2024

As the recognition of data's value increases, the role of data repositories in managing, preserving, and utilizing data is becoming increasingly important. This study investigates ways to enhance the trustworthiness of data repositories through obtaining CoreTrustSeal (CTS) certification. Trust in data repositories is critical not only for data protection but also for building and maintaining trust between the repository and stakeholders, which in turn affects researchers' decisions on depositing and utilizing data. The study examines the CoreTrustSeal, an international certification for trustworthy data repositories, analyzing its impact on the trustworthiness and efficiency of repositories. Using the example of DataON, Korea's first CTS-certified repository operated by the Korea Institute of Science and Technology Information (KISTI), the study compares and analyzes four repositories that have obtained CTS certification. These include DataON, the Physical Oceanography Distributed Active Archive Center (PO.DAAC) from NASA, Yareta from the University of Geneva, and the DARIAH-DE repository from Germany. The research assesses how these repositories meet the mandatory requirements set by CTS and proposes strategies for improving the trustworthiness of data repositories. Key findings indicate that obtaining CTS certification involves rigorous evaluation of organizational infrastructure, digital object management, and technological aspects. The study highlights the importance of transparent data processes, robust data quality assurance, enhanced accessibility and usability, sustainability, security measures, and compliance with legal and ethical standards. By implementing these strategies, data repositories can enhance their reliability and efficiency, ultimately promoting wider data sharing and utilization in the scientific community.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.1-10
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• 2024

The purpose of this study is to explore the direction of elderly education in the age of science and technology. The research contents to achieve the research purpose are, first, to examine the current status of elderly education, and second, to suggest the direction of elderly education in the age of science and technology. Due to the current status of education for the elderly, education for the elderly continues to change and develop, and various programs and activities are provided to help the elderly enjoy a richer retirement life. According to the survey report on the elderly, 11.9% of all elderly people participate in learning activities. Senior welfare centers accounted for the largest number of institutions conducting learning activities for elderly education learning activities participants at 35.5%. First, in the direction of elderly education in the age of science and technology, education on the use of digital technology and information is necessary in the composition of elderly education contents. Second, in the case of elderly education methods, customized elderly education methods are needed. Third, in the case of operating elderly education institutions, specialized education centers for elderly education must be further strengthened and supported. The international community is already forming a consensus that the establishment of new social systems and financial investment due to the increase in the elderly population should be considered a new growth engine rather than a social crisis. Although there is a burden on the social security sector due to the increase in the elderly population, there is a shift in the direction of recognizing the potential capabilities and experiences of the elderly and returning them to social resources. Elderly education in the age of science and technology needs to change to a direction that can build a healthy and progressive society in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.23-29
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• 2024

In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.

• The Journal of Bigdata
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• v.9 no.1
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• pp.101-113
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• 2024

Federated learning has garnered attention as an efficient method for training machine learning models in a distributed environment while maintaining data privacy and security. This study proposes a novel FedRFBagging algorithm to optimize the performance of random forest models in such federated learning environments. By dynamically adjusting the trees of local random forest models based on client-specific data characteristics, the proposed approach reduces communication costs and achieves high prediction accuracy even in environments with numerous clients. This method adapts to various data conditions, significantly enhancing model stability and training speed. While random forest models consist of multiple decision trees, transmitting all trees to the server in a federated learning environment results in exponentially increasing communication overhead, making their use impractical. Additionally, differences in data distribution among clients can lead to quality imbalances in the trees. To address this, the FedRFBagging algorithm selects only the highest-performing trees from each client for transmission to the server, which then reselects trees based on impurity values to construct the optimal global model. This reduces communication overhead and maintains high prediction performance across diverse data distributions. Although the global model reflects data from various clients, the data characteristics of each client may differ. To compensate for this, clients further train additional trees on the global model to perform local optimizations tailored to their data. This improves the overall model's prediction accuracy and adapts to changing data distributions. Our study demonstrates that the FedRFBagging algorithm effectively addresses the communication cost and performance issues associated with random forest models in federated learning environments, suggesting its applicability in such settings.

• Journal of Radiation Industry
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• v.18 no.3
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• pp.183-193
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• 2024

As part of the social response to the radon bed incident in 2018, the Nuclear Safety and Security Commission took measures to collect and dispose of all radon beds. The Waste Management Act provides landfill disposal as one of the disposal methods for natural radioactive product waste, which is one of the NORM wastes. When NORM wastes are landfilled, workers and the public at the landfill site are exposed to radiation through various pathways, such as leaching of radionuclides through soil and groundwater, and multiple exposure factors are involved simultaneously. In order to improve the reliability of radiological impact assessment, the values of main exposure factors should be selected more accurately. Therefore, before developing the main exposure factors for site characteristics, it is necessary to prioritize main exposure factors reflecting domestic characteristics of NORM waste landfills. Therefore, in this study, the main exposure factors for NORM waste landfill were derived using NDD analysis. To derive the main exposure factors, the analysis tool was first selected as RESRAD-ONSITE computer code, and the exposure scenarios were mainly selected as a resident farmer and suburban resident scenario, recreation scenario, and industrial worker scenario. Then, the priority 1 and 2 factors were selected for sensitivity analysis, and a Korean standard model was established to reflect Korean characteristics. Finally, the sensitivity analysis was conducted through NDD, and the main exposure factors were derived based on this. In the resident farmer scenario, the contaminated zone distribution coefficients of ²²⁶Ra, ²¹⁰Pb, ²³²Th, ²²⁸Ra, ²³⁴U, and ²³⁸U, as well as precipitation and evapotranspiration factors, were derived as the main exposure factors. In the suburban resident scenario, the contaminated zone distribution coefficients of ²²⁶Ra, ²¹⁰Pb, ²³²Th, ²²⁸Ra, ²³⁴U, and ²³⁸U, as well as precipitation and evapotranspiration coefficients, were derived as the main exposure factors. In the recreation scenario, the contaminated zone distribution coefficient of ²³²Th was derived as the main exposure factor. For the industrial worker scenario, the erosion rate was derived as the main exposure factor. The main exposure factors for each scenario were analyzed to be different depending on the scenario characteristics. The results of this study can be utilized as a basis for radiological environmental impact assessment of NORM waste landfill in Korea.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.827-832
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• 2024

The AI program Sora is a video production model that can be used innovatively and is the starting point of a major paradigm shift in video planning and production in the future. In this paper, through consideration of the characteristics, application, and process of the AI video production program, the characteristics of the AI design video production method were understood, and the production algorithm was considered. The detailed consideration and characteristics of the work creation process for the video graphic AI video generation program that will be intensified every year were examined. Next, the method of generating a customized video with a text prompt and the process of innovative production results different from the previous production method were considered. In addition, the design direction through the generation of AI images was studied through the review of the strengths and weaknesses of the image details of the recently announced AI music video results. By considering the security of the AI generation video Sora and looking at the internal process of the actual AI process, it will be possible to present indicators for the future direction of AI video model production and education along with the direction of the design designer and education system. In the text and conclusion, we analyzed the strengths and weaknesses and future status of OpenAI Sora image, concluded how to apply the Sora model's capabilities, limitations, quality, and human creativity, and presented problems and alternatives through examples of the Sora model's capabilities and limitations to increase human creativity.