• Title/Summary/Keyword: 안전리스크

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A Case Study of the Risk Identification in Construction Project (건설사업의 리스크 식별에 관한 사례연구)

  • Ahn, Sanghyun
    • Korean Journal of Construction Engineering and Management
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    • v.16 no.1
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    • pp.15-23
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    • 2015
  • In the construction industry, risk management has gained constant attention as the factor not only to evaluate global competitiveness of the country but also to secure competitiveness of public institutions and private companies. For effective construction risk management, the specific work process improvement that can be employed in the field in terms of risk management of the entire corporation such as financial, insurance and safety management is necessary. To manage construction risks, what is important is the step to identifying inherent risks in the construction project. The identification of risks will be followed by the step to seeking ways to establish and manage strategies responding to the risks. This study suggests ways and processes to make a checkslit to identify risks through case studies. To that end, the focus will be placed on working process improvement of risk identification among stages to manage construction risks such as risk identification and analyses, planning to respond to risks, risk monitoring and management. The case study checklists show that setting up the system to classify risks by stage is helpful to figure out causes of risks to reduce or eliminate risk factors. The checklist making process that considers features of the project is expected to contribute to successful completion of the project by enabling effective risk identification and systematic risk management.

Establishment of Risk Database and Development of Risk Classification System for NATM Tunnel (NATM 터널 공정리스크 데이터베이스 구축 및 리스크 분류체계 개발)

  • Kim, Hyunbee;Karunarathne, Batagalle Vinuri;Kim, ByungSoo
    • Korean Journal of Construction Engineering and Management
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    • v.25 no.1
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    • pp.32-41
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    • 2024
  • In the construction industry, not only safety accidents, but also various complex risks such as construction delays, cost increases, and environmental pollution occur, and management technologies are needed to solve them. Among them, process risk management, which directly affects the project, lacks related information compared to its importance. This study tried to develop a MATM tunnel process risk classification system to solve the difficulty of risk information retrieval due to the use of different classification systems for each project. Risk collection used existing literature review and experience mining techniques, and DB construction utilized the concept of natural language processing. For the structure of the classification system, the existing WBS structure was adopted in consideration of compatibility of data, and an RBS linked to the work species of the WBS was established. As a result of the research, a risk classification system was completed that easily identifies risks by work type and intuitively reveals risk characteristics and risk factors linked to risks. As a result of verifying the usability of the established classification system, it was found that the classification system was effective as risks and risk factors for each work type were easily identified by user input of keywords. Through this study, it is expected to contribute to preventing an increase in cost and construction period by identifying risks according to work types in advance when planning and designing NATM tunnels and establishing countermeasures suitable for those factors.

Construction of Financial Networks based on Virtual Private Networks (가상사설통신망 기반 금융전산망 구축 방안)

  • Seo, Moon-Seog
    • The Journal of the Korea Contents Association
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    • v.9 no.8
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    • pp.41-48
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    • 2009
  • As enactment and enforcement of capital markets integration law, investment banks are going to be appeared in our financial market and be able to provide payment services. To provide these kinds of services, investment banks need to be participated in the financial network. As the financial network enormously affect the economy, the operation of the network will require a variety of risk managements. In this paper we define operational risk management criteria for the financial network such as security, in-time response, economical efficiency and stability to be required for the healthy economy and propose the configuration of the financial network system based on virtual private networks for investment banks to provide payment services. Finally we analyze that the proposed VPN configuration for financial networks has high security and in-time response with the cost and operation effective.

A Study on Cybersecurity Risk Assessment in Maritime Sector (해상분야 사이버보안 위험도 분석)

  • Yoo, Yun-Ja;Park, Han-Seon;Park, Hye-Ri;Park, Sang-Won
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2019.11a
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    • pp.134-136
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    • 2019
  • The International Maritime Organization (IMO) issued 2017 Guidelines on maritime cyber risk management. In accordance with IMO's maritime cyber risk management guidelines, each flag State is required to comply with the Safety Management System (SMS) of the International Safety Management Code (ISM) that the cyber risks should be integrated and managed before the first annual audit following January 1, 2021. In this paper, to identify cyber security management targets and risk factors in the maritime sector and to conduct vulnerability analysis, we catagorized the cyber security sector in management, technical and physical sector in maritime sector based on the industry guidelines and international standards proposed by IMO. In addition, the Risk Matrix was used to conduct a qualitative risk assessment according to risk factors by cyber security sector.

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AutoML and CNN-based Soft-voting Ensemble Classification Model For Road Traffic Emerging Risk Detection (도로교통 이머징 리스크 탐지를 위한 AutoML과 CNN 기반 소프트 보팅 앙상블 분류 모델)

  • Jeon, Byeong-Uk;Kang, Ji-Soo;Chung, Kyungyong
    • Journal of Convergence for Information Technology
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    • v.11 no.7
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    • pp.14-20
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    • 2021
  • Most accidents caused by road icing in winter lead to major accidents. Because it is difficult for the driver to detect the road icing in advance. In this work, we study how to accurately detect road traffic emerging risk using AutoML and CNN's ensemble model that use both structured and unstructured data. We train CNN-based road traffic emerging risk classification model using images that are unstructured data and AutoML-based road traffic emerging risk classification model using weather data that is structured data, respectively. After that the ensemble model is designed to complement the CNN-based classification model by inputting probability values derived from of each models. Through this, improves road traffic emerging risk classification performance and alerts drivers more accurately and quickly to enable safe driving.