• Title/Summary/Keyword: Operational Resilience

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Research on the educational management model for the interplay of structural damage in buildings and tunnels based on numerical solutions

  • Xiuzhi Wei;Zhen Ma;Jingtao Man;Seyyed Rohollah Taghaodi;H. Xiang
    • Geomechanics and Engineering
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    • v.37 no.1
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    • pp.21-29
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    • 2024
  • The effective management of damage in tunnels is crucial for ensuring their safety, longevity, and operational efficiency. In this paper, we propose an educational management model tailored specifically for addressing damage in tunnels, utilizing numerical solution techniques. By leveraging advanced computational methods, we aim to develop a comprehensive understanding of the factors contributing to tunnel damage and to establish proactive measures for mitigation and repair. The proposed model integrates principles of tunnel engineering, structural mechanics, and numerical analysis to facilitate a systematic approach to damage assessment, diagnosis, and management. Through the application of numerical solution techniques, such as finite element analysis, we demonstrate the efficacy of the proposed model in simulating various damage scenarios and predicting their impact on tunnel performance. Additionally, the educational component of the model provides valuable insights and training opportunities for tunnel management personnel, empowering them to make informed decisions and implement effective strategies for ensuring the structural integrity and safety of tunnel infrastructure. Overall, the proposed educational management model represents a significant advancement in tunnel management practices, offering a proactive and knowledge-driven approach to addressing damage and enhancing the resilience of tunnel systems.

An Analysis on Climate Change and Military Response Strategies (기후변화와 군 대응전략에 관한 연구)

  • Park Chan-Young;Kim Chang-Jun
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.2
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    • pp.171-179
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    • 2023
  • Due to man-made climate change, global abnormal weather phenomena have occurred, increasing disasters. Major developed countries(military) are preparing for disasters caused by extreme weather appearances. However, currently, disaster prevention plans and facilities have been implemented based on the frequency and intensity method based on statistical data, it is not enough to prepare for disasters caused by frequent extreme weather based on probability basis. The U.S. and British forces have been the fastest to take research and policy approaches related to climate change and the threat of disaster change, and are considering both climate change mitigation and adaptation. The South Korean military regards the perception of disasters to be storm and flood damage, and there is a lack of discussion on extreme weather and disasters due to climate change. In this study, the process of establishing disaster management systems in developed countries(the United States and the United Kingdom) was examined, and the response policies of each country(military) were analyzed using literature analysis techniques. In order to maintain tight security, our military should establish a response policy focusing on sustainability and resilience, and the following three policy approaches are needed. First, it is necessary to analyze the future operational environment of the Korean Peninsula in preparation for the environment that will change due to climate change. Second, it is necessary to discuss climate change 'adaptation policy' for sustainability. Third, it is necessary to prepare for future disasters that may occur due to climate change.

Using AHP to Develop a Rehabilitation Room Management Model for Fire Officers at Disaster Sites (재난현장 소방공무원의 회복실 운영모델 개발)

  • Yim, Dong-Kyun;Chae, Jin
    • Fire Science and Engineering
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    • v.34 no.4
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    • pp.115-124
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    • 2020
  • The purpose of this study was to provide an operational model of the rehabilitation room for fire officers at disaster sites to improve the safety and resilience of fire officers. Therefore, we analyzed the operation related elements of the rehabilitation room-such as overseas rehabilitation room operation cases and previous studies- and managed different factors including, but not limited to, management and human resources, equipment and facility, and accessibility and convenience factors; afterward, the relative importance and importance of sub-layers in each field were measured. The priority of items for the operation of the rehabilitation room for fire officers at disaster sites was elucidated; after expert analysis, it was found that human resources were the most crucial factor. Finally, it was found that, in descending order, accessibility and convenience, administrative, equipment, and facility factors were also essential. Based on this, we proposed a rehabilitation room operation guideline for disaster sites.

Lessons from constructing and operating the national ecological observatory network

  • Christopher McKay
    • Journal of Ecology and Environment
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    • v.47 no.4
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    • pp.187-192
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    • 2023
  • The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.

The Necessity and Development Direction of the ROK's Maritime Security Strategy White Paper (한국의 해양안보전략서의 필요성과 발전방향)

  • Kim, Kang-nyeong
    • Strategy21
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    • s.45
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    • pp.148-187
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    • 2019
  • This paper is to analyse the necessity and development direction of the ROK's maritime security strategy white paper. To this end the paper is composed of 5 chapters titled introduction; the necessity of the ROK's maritime security strategy white paper; the ROK's actual situation in relation to maritime security strategy and cases of major advanced oceanic countries; the vision, goals, strategic tasks, and implementation system of the ROK's 'national maritime security strategy'; and conclusion. The achievement of the national marine strategic vision, such as the 'Ocean G5,' is of course possible when Korea can maintain and strengthen the maritime safety and maritime security of the people. The Sewol Ferry incident reminds us that we need a 'national maritime security strategy white paper' like the advanced marine countries. In order for the national maritime security strategy to be carried our efficiently, as in advanced oceanic countries, mere should be a dedicated department with sufficient authority and status to mobilize the cooperation of related organizations including naval-coastal cooperation. It would be good to set up a tentatively named Maritime Security Council, an organization of minister-level officials involved under the National Security Council, and an executive body composed of working-level officials from related ministries. In order to successfully carry out the national maritime security strategy for the maritime safety and maritime security of the people like the United States and the United Kingdom, we need to further strengthen our domestic cooperation and cooperation system, international cooperation, and maritime security. We have to promote the establishment and promotion of maritime security strategies by the Navy; strengthening the operational link between the Navy and the Coast Guard; strengthening the maritime surveillance capability at the national level, and promoting sharing with the private sector, etc.

Applicability Evaluation of Deep Learning-Based Object Detection for Coastal Debris Monitoring: A Comparative Study of YOLOv8 and RT-DETR (해안쓰레기 탐지 및 모니터링에 대한 딥러닝 기반 객체 탐지 기술의 적용성 평가: YOLOv8과 RT-DETR을 중심으로)

  • Suho Bak;Heung-Min Kim;Youngmin Kim;Inji Lee;Miso Park;Seungyeol Oh;Tak-Young Kim;Seon Woong Jang
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1195-1210
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    • 2023
  • Coastal debris has emerged as a salient issue due to its adverse effects on coastal aesthetics, ecological systems, and human health. In pursuit of effective countermeasures, the present study delineated the construction of a specialized image dataset for coastal debris detection and embarked on a comparative analysis between two paramount real-time object detection algorithms, YOLOv8 and RT-DETR. Rigorous assessments of robustness under multifarious conditions were instituted, subjecting the models to assorted distortion paradigms. YOLOv8 manifested a detection accuracy with a mean Average Precision (mAP) value ranging from 0.927 to 0.945 and an operational speed between 65 and 135 Frames Per Second (FPS). Conversely, RT-DETR yielded an mAP value bracket of 0.917 to 0.918 with a detection velocity spanning 40 to 53 FPS. While RT-DETR exhibited enhanced robustness against color distortions, YOLOv8 surpassed resilience under other evaluative criteria. The implications derived from this investigation are poised to furnish pivotal directives for algorithmic selection in the practical deployment of marine debris monitoring systems.

GEase-K: Linear and Nonlinear Autoencoder-based Recommender System with Side Information (GEase-K: 부가 정보를 활용한 선형 및 비선형 오토인코더 기반의 추천시스템)

  • Taebeom Lee;Seung-hak Lee;Min-jeong Ma;Yoonho Cho
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.167-183
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    • 2023
  • In the recent field of recommendation systems, various studies have been conducted to model sparse data effectively. Among these, GLocal-K(Global and Local Kernels for Recommender Systems) is a research endeavor combining global and local kernels to provide personalized recommendations by considering global data patterns and individual user characteristics. However, due to its utilization of kernel tricks, GLocal-K exhibits diminished performance on highly sparse data and struggles to offer recommendations for new users or items due to the absence of side information. In this paper, to address these limitations of GLocal-K, we propose the GEase-K (Global and EASE kernels for Recommender Systems) model, incorporating the EASE(Embarrassingly Shallow Autoencoders for Sparse Data) model and leveraging side information. Initially, we substitute EASE for the local kernel in GLocal-K to enhance recommendation performance on highly sparse data. EASE, functioning as a simple linear operational structure, is an autoencoder that performs highly on extremely sparse data through regularization and learning item similarity. Additionally, we utilize side information to alleviate the cold-start problem. We enhance the understanding of user-item similarities by employing a conditional autoencoder structure during the training process to incorporate side information. In conclusion, GEase-K demonstrates resilience in highly sparse data and cold-start situations by combining linear and nonlinear structures and utilizing side information. Experimental results show that GEase-K outperforms GLocal-K based on the RMSE and MAE metrics on the highly sparse GoodReads and ModCloth datasets. Furthermore, in cold-start experiments divided into four groups using the GoodReads and ModCloth datasets, GEase-K denotes superior performance compared to GLocal-K.