• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.265-275
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• 2023

The purpose of this paper is to devise an optimal route allocation algorithm for automated vehicle(AV) in monitoring quality of road infrastructure to support the road safety. The tasks of an AV in this paper include visiting node-links at least once during its operation and checking status of road infrastructure, and coming back to its depot.. In selecting optimal route, its priority goal is visiting the node-links with higher risks while reducing costs caused by operation. To deal with the problem, authors devised reward maximizing algorithm for AVs. To check its validity, the authors developed simple toy network that mimic node-link networks and assigned costs and rewards for each node-link. With the toy network, the reward maximizing algorithm worked well as it visited the node-link with higher risks earlier then chinese postman route algorithm (Eiselt, Gendreau, Laporte, 1995). For further research, the reward maximizing algorithm should be tested its validity in a more complex network that mimic the real-life.

• Convergence Security Journal
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• v.22 no.1
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• pp.99-111
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• 2022

With current battlefield environment relying heavily on Network Centric Warfare(NCW), existing weaponary systems are evolving into a new concept that converges IT technology. Majority of the weaponary systems are implemented with numerous embedded softwares which makes such softwares a key factor influencing the performance of such systems. Furthermore, due to the advancements in both IoT technoogies and embedded softwares cyber threats are targeting various embedded systems as their scope of application expands in the real world. Weaponary systems have been developed in various forms from single systems to interlocking networks. hence, system level cyber security is more favorable compared to application level cyber security. In this paper, a secure real-time operating system has been designed, implemented and measured to protect embedded softwares used in weaponary systems from unknown cyber threats at the operating system level.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.433-442
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• 2010

Recent decrease in the availability of experienced skilled labor and a corresponding lack of new entrants has required the need for automating many of the construction equipment used in the construction industry. In particular, excavators are widely used throughout earthwork operations and automating its tasks enables work to be performed with higher productivity and safety. This paper introduces an optimal path generation method which is one of the core technologies required to make "Intelligent" excavators a reality. The method divides a given earthwork area into unit cells, identifies networks created by linking these cells, and identifies the optimal path an excavator should follow to minimize its total transportation costs. In addition, the method also accounts for drainage direction and path continuity to ensure that the generated path considers site specific conditions.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.377-379
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• 2022

POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.877-885
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• 2022

Vision-based activity recognition has been widely attempted at construction sites to estimate productivity and enhance workers' health and safety. Previous studies have focused on extracting an individual worker's postural information from sequential image frames for activity recognition. However, various trades of workers perform different tasks with similar postural patterns, which degrades the performance of activity recognition based on postural information. To this end, this research exploited a concept of human-object interaction, the interaction between a worker and their surrounding objects, considering the fact that trade workers interact with a specific object (e.g., working tools or construction materials) relevant to their trades. This research developed an approach to understand the context from sequential image frames based on four features: posture, object, spatial features, and temporal feature. Both posture and object features were used to analyze the interaction between the worker and the target object, and the other two features were used to detect movements from the entire region of image frames in both temporal and spatial domains. The developed approach used convolutional neural networks (CNN) for feature extractors and activity classifiers and long short-term memory (LSTM) was also used as an activity classifier. The developed approach provided an average accuracy of 85.96% for classifying 12 target construction tasks performed by two trades of workers, which was higher than two benchmark models. This experimental result indicated that integrating a concept of the human-object interaction offers great benefits in activity recognition when various trade workers coexist in a scene.

• Industry Promotion Research
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• v.8 no.4
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• pp.241-250
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• 2023

In investigating missing persons cases, the focus is on strengthening the efficiency of detectives' work in investigating missing persons cases. Disappearance cases are seen as a problem that directly affects social safety and individual well-being. The research has the following structure. The introduction presents the necessity, scope, and methodology of the study. Next, we analyze the definition, causes, types and actual conditions of disappearance cases. In terms of problems in the process of handling missing persons cases, the initial response process, problems in the response of related agencies after reporting, problems due to the prolongation of the case, and problems due to legal restrictions are analyzed. In the plan to improve the work efficiency of detectives for disappearance cases, the revitalization of public interest investigation networks, strengthening of capacity related to disappearance case investigation, professional public interest detective certification system, and establishment of exception provisions for detective activities are discussed. In the conclusion, we present what is necessary for the activities of public interest detectives specializing in missing persons cases.

• Convergence Security Journal
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• v.23 no.3
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• pp.73-81
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• 2023

The progress in science and technology has widened the scope of the battlefield, leading to the emergence of cyber electronic warfare that exploits electromagnetic waves and networks. Drones have become more important due to advancements in battery technology and navigation systems. Nevertheless, tackling drone threats comes with its own set of difficulties. Radar plays a vital role in detecting drones, offering long-range capabilities and independence from weather conditions. However, the battlefield presents unique challenges like dealing with high levels of signal noise and ensuring the safety of the detection assets. This paper proposes various approaches to improve the operation of drone detection radar in cyber electronic warfare, with a focus on enhancing signal processing techniques, utilizing low probability of interception (LPI) radar, and implementing optimized deployment strategies.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.324-330
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• 2023

Aids to navigation, which provide information about a ship's position, direction, and the location of obstacles, are crucial for uninterrupted maritime services. This study aimed to analyze accidents involving aids to navigation that resulted in service disruptions and identify the key factors associated with these accidents. Aids to navigation accident data from 2000 to 2022 were utilized to achieve this. We categorized accidents by accident type, cause, region, season, and type of navigation aid and established a network through correlation analysis. Bayesian networks based on aids to navigation accidents were assigned prior probabilities, and the factors that increased the probability of accidents for different types of aids to navigation were identified. The findings can be used to infer the causes of unreported aids to navigation accidents and serve as foundational data for the prevention of such accidents.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.223-241
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• 2024

Evaluating the performance of Tunnel Boring Machines (TBMs) stands as a pivotal juncture in the domain of hard rock mechanized tunneling, essential for achieving both a dependable construction timeline and utilization rate. In this investigation, three advanced artificial neural networks namely, gated recurrent unit (GRU), back propagation neural network (BPNN), and simple recurrent neural network (SRNN) were crafted to prognosticate TBM-rate of penetration (ROP). Drawing from a dataset comprising 1125 data points amassed during the construction of the Alborze Service Tunnel, the study commenced. Initially, five geomechanical parameters were scrutinized for their impact on TBM-ROP efficiency. Subsequent statistical analyses narrowed down the effective parameters to three, including uniaxial compressive strength (UCS), peak slope index (PSI), and Brazilian tensile strength (BTS). Among the methodologies employed, GRU emerged as the most robust model, demonstrating exceptional predictive prowess for TBM-ROP with staggering accuracy metrics on the testing subset (R² = 0.87, NRMSE = 6.76E-04, MAD = 2.85E-05). The proposed models present viable solutions for analogous ground and TBM tunneling scenarios, particularly beneficial in routes predominantly composed of volcanic and sedimentary rock formations. Leveraging forecasted parameters holds the promise of enhancing both machine efficiency and construction safety within TBM tunneling endeavors.

• The Journal of Korean Society for School & Community Health Education
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• v.24 no.4
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• pp.13-26
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• 2023

Objectives: The purpose of this study was to explore the factors that influence aerobic physical activity among Korean adults, including sociodemographic characteristics, health behavior, health status, social relationships, community satisfaction, and to find ways to increase aerobic physical activity among adults. Methods: In 2019, 191,152 adults in the Community Health Survey were analyzed, and complex sample frequency analysis, Rao-Scott test and complex sample logistic regression analysis were conducted by dividing them into the presence or absence of aerobic physical activity practice. Results: The rate of aerobic physical activity among adults was 36.0%, and males were higher than females. Among individual factors, gender, age, income level, smoking, drinking, weight control attempt, frequency of breakfast, obesity, quality of life, and subjective health status were factors that had a significant effect. Among social relationship factors, leisure activities and contact with neighbors at least once a week were significant factors, and only overall safety level satisfaction was a factor that had a significant effect on physical activity practice in community satisfaction factors. Conclusion: Programs focused on personal factors, social relationships, and networks should be strategically developed to improve the participation rate of adult aerobic physical activities, indicating the importance of these factors over community infrastructure. To development of community-centered professional integrated health education will be necessary in the future.