• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.595-603
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• 2016

In the Republic of Korea, the LTE-based public safety (PS-LTE) network is being built for the 700 MHz frequency band. However, the same bands are also assigned to the LTE-based high-speed railway (LTE-R) network. Therefore, it is essential to utilize the co-channel interference management schemes for the coexistence of two LTE networks in order to increase the system throughput and to reduce the user outage probability. In this paper, we focus on the downlink (DL) system for the coexistence of PS-LTE and LTE-R networks by considering non radio access network (RAN) sharing and LTE-R RAN sharing by PS-LTE users (UEs) to analyze the UE throughput. Moreover, we also utilize the cooperative communications schemes, such as coordinated multipoint (CoMP) for the coexistence of PS-LTE and LTE-R networks in order to reduce the UE outage probability. We categorize the coexistence of PS-LTE and LTE-R networks into four different scenarios, and evaluate the performance of each scenario by the important performance indexes, such as UE average throughput and UE outage probability.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• Smart Structures and Systems
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• v.30 no.6
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• pp.557-569
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• 2022

Vibration-based structural health monitoring (SHM) is crucial for the dynamic maintenance of civil building structures to protect property security and the lives of the public. Analyzing these vibrations with modern artificial intelligence and deep learning (DL) methods is a new trend. This paper proposed an unsupervised deep learning method based on a convolutional autoencoder (CAE), which can overcome the limitations of conventional supervised deep learning. With the convolutional core applied to the DL network, the method can extract features self-adaptively and efficiently. The effectiveness of the method in detecting damage is then tested using a benchmark model. Thereafter, this method is used to detect damage and instant disaster events in a rubber bearing-isolated gymnasium structure. The results indicate that the method enables the CAE network to learn the intact vibrations, so as to distinguish between different damage states of the benchmark model, and the outcome meets the high-dimensional data distribution characteristics visualized by the t-SNE method. Besides, the CAE-based network trained with daily vibrations of the isolating layer in the gymnasium can precisely recover newly collected vibration and detect the occurrence of the ground motion. The proposed method is effective at identifying nonlinear variations in the dynamic responses and has the potential to be used for structural condition assessment and safety warning.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.82-95
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• 2022

Since military weapon accidents or breakdowns are directly linked to enormous damage, it is important to analyze the causes of weapons system accidents. Recently, in the defense sector, there have been cases in which budget has been saved through analysis of the causes of frequent breakdowns and improvement activities that have occurred in the process of operating weapon systems since 2015. But due to the nature of the defense sector, it is not easy to collect data and studies on weapons system accidents have been insufficient so far. Therefore, this study aims to investigate the causes and types of military weapon accidents by collecting military weapon accident data for military weapon systems and analyzing trends by weapon system classification through the analysis process. It analyzes statistically and visually through social network analysis, NodeXL. It is expected that this study will help improve the stability of the weapon system by reducing the number of military weapon accidents and failures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4573-4594
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• 2020

Announcement protocol in Internet of Vehicles (IoV) is an intelligent application to enhance public safety, alleviate traffic jams and improve transportation quality. It requires communication between vehicles, roadside units and pedestrian to disseminate safety-related messages. However, as vehicles connected to internet, it makes them accessible globally to a potential adversary. Safety-related application requires a message to be reliable, however it may intrude the privacy of a vehicle. Contrarily, if some misbehaviour emerges, the malicious vehicles must be able to traceable and revoke from the network. This is a contradiction between privacy and accountability since the privacy of a user should be preserved. For a secure communication among intelligent entities, we propose a novel announcement protocol in IoV using group signature. To the best of our knowledge, our work is the first comprehensive construction of an announcement protocol in IoV that deploys group signature. We show that our protocol efficiently solves these conflicting security requirements of message reliability, privacy and accountability using 5G communication channel. The performance analysis and simulation results signify our work achieves performance efficiency in IoV communication.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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• pp.217-223
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• 2023

With the rapid advancement of technologies, need for different research fields where this technology can be used is also increasing. One of the most researched topic in computer vision is object detection, which has widely been implemented in various fields which include healthcare, video surveillance and education. The main goal of object detection is to identify and categorize all the objects in a target environment. Specifically, methods of object detection consist of a variety of significant techniq ues, such as image processing and patterns recognition. Anomaly detection is a part of object detection, anomalies can be found various scenarios for example crowded places such as subway stations. An abnormal event can be assumed as a variation from the conventional scene. Since the abnormal event does not occur frequently, the distribution of normal and abnormal events is thoroughly imbalanced. In terms of public safety, abnormal events should be avoided and therefore immediate action need to be taken. When abnormal events occur in certain places, real time detection is required to prevent and protect the safety of the people. To solve the above problems, we propose a modified YOLOv5 object detection algorithm by implementing dilated convolutional layers which achieved 97% mAP50 compared to other five different models of YOLOv5. In addition to this, we also created a simple mobile application to avail the abnormal event detection on mobile phones.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.385-391
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• 2013

As a solution for environmental problems caused by increasing number of vehicles, it is encouraged to use a bicycle as an environment-friendly transportation method. To vitalize the bicycle usage, it is a necessary to construct bicycle roads that are safe and suitable for users. Based on the previous research results, we assume the main purposes of bicycle usages are mainly local leisure activity and school commuting. Thus, the proposed method finds the shortest link between the existing bicycle road network and bicycle usage facilities such as leisure activity places or schools over public road network. Then, we carry out the RTK DGPS survey for the candidate links, and analyze the slopes of them. When the slope of a found link is larger than a threshold, an alternative link is re-found for the safety and convenience of a bicycle user. The proposed method is applied to the real bicycle road network in Mokpo, Chunnam and the results are discussed.

• Safety and Health at Work
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• v.8 no.3
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• pp.231-236
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• 2017

Vital to the prevention of work-related ill-health (WRIH) is the availability of good quality data regarding WRIH burden and risks. Physician-based surveillance systems such as The Health and Occupation Research (THOR) network in the UK are often established in response to limitations of statutory, compensation-based systems for addressing certain epidemiological aspects of disease surveillance. However, to fulfil their purpose, THOR and others need to have methodologic rigor in capturing and ascertaining cases. This article describes how data collected by THOR and analogous systems can inform WRIH incidence, trends, and other determinants. An overview of the different strands of THOR research is provided, including methodologic advancements facilitated by increased data quantity/quality over time and the value of the research outputs for informing Government and other policy makers. In doing so, the utility of data collected by systems such as THOR to address a wide range of research questions, both in relation to WRIH and to wider issues of public and social health, is demonstrated.

• Journal of the Society of Disaster Information
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• v.9 no.3
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• pp.339-346
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• 2013

In this study, the summary and characteristics of WHO International Safe Community are examined and the activities for the establishment of safe city were analyzed targeting Samcheok City in Gangwon-do which prepares for the certification of the International Safe Community. And, based on the result, this study intends to present the direction of establishment and development of international safe city to improve the regional safety. First, for the establishment of safe city, measures and programs for vulnerable classes and accidential forms in the area must be developed and operated continuously. Second, continuous and systematic activities must be done by establishing combined network between regional government association and relative organ and resident association in the area. Third, public policies for establishing safe city so as to improve regional safety, such as enactment of relative si/do ordinance, etc, must be prepared so as to operate it systematically. Finally, through the various activities by establishing international network, education, publicity activities and various informations must be acquired.

• Safety and Health at Work
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• v.13 no.4
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• pp.421-428
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• 2022

Background: The exposure to solar ultraviolet radiation is a significant risk factor generally underestimated by outdoor workers and employers. Several studies have pointed out that occupational solar exposure increased eye and skin diseases with a considerable impact on the lives and productivity of affected workers. The main purpose of this study was to evaluate the effectiveness against ultraviolet radiation of some measures recently undertaken for the protection of lifeguards in a coastal area of Tuscany. Methods: Different shading structures (gazebos and beach umbrella) were tested during a sunny summer's day on a sandy beach by means of two radiometers; the UV protection offered by some T-shirts used by lifeguards was also tested in the laboratory with a spectrophotometer. Results: The analysed shading structures strongly reduced the ultraviolet radiation by up to 90%, however a not always negligible diffuse radiation is also present in the shade, requiring further protective measures (T-shirt, sunglasses, sunscreen, etc.); the tested T-shirts showed a very good-excellent protection according to the Australian/New Zealand standard. Conclusion: Results obtained in this study suggest how the adoption and dissemination of good practices, including those tested, could be particularly effective as a primary prevention for lifeguards who are subjected to very high levels of radiation for long periods.