• Journal of Preventive Medicine and Public Health
• /
• v.54 no.1
• /
• pp.8-16
• /
• 2021

This article aims to introduce the inception and operation of the COVID-19 International Collaborative Research Project, the world's first coronavirus disease 2019 (COVID-19) open data project for research, along with its dataset and research method, and to discuss relevant considerations for collaborative research using nationwide real-world data (RWD). COVID-19 has spread across the world since early 2020, becoming a serious global health threat to life, safety, and social and economic activities. However, insufficient RWD from patients was available to help clinicians efficiently diagnose and treat patients with COVID-19, or to provide necessary information to the government for policy-making. Countries that saw a rapid surge of infections had to focus on leveraging medical professionals to treat patients, and the circumstances made it even more difficult to promptly use COVID-19 RWD. Against this backdrop, the Health Insurance Review and Assessment Service (HIRA) of Korea decided to open its COVID-19 RWD collected through Korea's universal health insurance program, under the title of the COVID-19 International Collaborative Research Project. The dataset, consisting of 476 508 claim statements from 234 427 patients (7590 confirmed cases) and 18 691 318 claim statements of the same patients for the previous 3 years, was established and hosted on HIRA's in-house server. Researchers who applied to participate in the project uploaded analysis code on the platform prepared by HIRA, and HIRA conducted the analysis and provided outcome values. As of November 2020, analyses have been completed for 129 research projects, which have been published or are in the process of being published in prestigious journals.

• Smart Structures and Systems
• /
• v.31 no.4
• /
• pp.311-323
• /
• 2023

Ever since ancient times, earthquakes have been a major threat to the civil infrastructures and the safety of human beings. The majority of casualties in earthquake disasters are caused by the damaged civil infrastructures but not by the earthquake itself. Therefore, the efficient and accurate post-earthquake assessment of the conditions of structural damage has been an urgent need for human society. Traditional ways for post-earthquake structural assessment rely heavily on field investigation by experienced experts, yet, it is inevitably subjective and inefficient. Structural response data are also applied to assess the damage; however, it requires mounted sensor networks in advance and it is not intuitional. As many types of damaged states of structures are visible, computer vision-based post-earthquake structural assessment has attracted great attention among the engineers and scholars. With the development of image acquisition sensors, computing resources and deep learning algorithms, deep learning-based post-earthquake structural assessment has gradually shown potential in dealing with image acquisition and processing tasks. This paper comprehensively reviews the state-of-the-art studies of deep learning-based post-earthquake structural assessment in recent years. The conventional way of image processing and machine learning-based structural assessment are presented briefly. The workflow of the methodology for computer vision and deep learning-based post-earthquake structural assessment was introduced. Then, applications of assessment for multiple civil infrastructures are presented in detail. Finally, the challenges of current studies are summarized for reference in future works to improve the efficiency, robustness and accuracy in this field.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.14 no.4
• /
• pp.293-300
• /
• 2011

Many countries of the world, including IMO, has noticed that foreign marine hazardous organisms, which were introduced by ballast water, have disturbed the marine ecosystem of its own nation, and posed a serious threat to human health and the value of environment and economy. Therefore, IMO has tried to manage the introduced species by assessing the risk of ballast water, and suggested three risk assessment methods, such as environmental matching risk assessment, speciesbiogeographical risk assessment, and species-specific risk assessment. In this thesis, species-specific risk assessment method was considered, and a risk assessment program established by applying it was described.

• Journal of Information Processing Systems
• /
• v.12 no.2
• /
• pp.226-233
• /
• 2016

Cloud computing is a distributed computing model that has lot of drawbacks and faces difficulties. Many new innovative and emerging techniques take advantage of its features. In this paper, we explore the security threats to and Risk Assessments for cloud computing, attack mitigation frameworks, and the risk-based dynamic access control for cloud computing. Common security threats to cloud computing have been explored and these threats are addressed through acceptable measures via governance and effective risk management using a tailored Security Risk Approach. Most existing Threat and Risk Assessment (TRA) schemes for cloud services use a converse thinking approach to develop theoretical solutions for minimizing the risk of security breaches at a minimal cost. In our study, we propose an improved Attack-Defense Tree mechanism designated as iADTree, for solving the TRA problem in cloud computing environments.

• Journal of Environmental Impact Assessment
• /
• v.17 no.2
• /
• pp.105-112
• /
• 2008

Human activity has been the major threat to wetlands. Agriculture, industrial development, and urban and suburban sprawl have caused the greatest losses of coastal wetlands. In fact, riceland agriculture, because of the flooding that goes with it, provides some additional wetland habitat not otherwise available. The biggest current source of loss for freshwater coastal wetlands is from urban sprawl. In this study, spatial analysis method such as landscape index were applied to Sihwa area in Ansan city. The SMA (Spectral Mixture Analysis) method using Landsat image showed the change distribution of wetland vegetation from 1996 to 2004. The southern part of Sihwa wetland have been changed with Suda japonica of 24% and reed vegetation of 34% on coastal wetland which were covered with tidal flat.

• Journal of Korean Institute of Industrial Engineers
• /
• v.28 no.1
• /
• pp.44-56
• /
• 2002

For the risk analysis and risk assessment techniques to be effectively applied to the field of information technology (IT) security, it is necessary that the required activities and specific techniques to be applied and their order of applications are to be determined through a proper risk management model. If the adopted risk management model does not match with the characteristics of host organization, an inefficient management of security would be resulted. In this paper, a risk management model which can be well adapted to Korean domestic IT environments is proposed for an efficient security management of IT. The structure and flow of the existing IT-related risk management models are compared and analysed, and their common and/or strong characteristics are extracted and incorporated in the proposed model in the light of typical threat types observed in Korean IT environments.

• Proceedings of the KSME Conference
• /
• 2008.11b
• /
• pp.2001-2006
• /
• 2008

The most concerning issue of these days is the energy crisis by increasing threat of dependency on foreign oil and its volatility itself. In the situations, the PHEV is drawing attention for the next generation's car which could give a chance to decrease the dependency on foreign oil. As well as, the Korean electric power infrastructure is a strategic national asset that is under utilized most of the time. With the proper changes in the operational paradigm, it could generate and deliver necessary energy to charge the PHEVs which could penetrate the market within few years. In doing so, it would reduce greenhouse gas emissions, improve the economics of the electricity industry, and reduce the energy dependency. This paper investigate the technical potential and impacts of using the existing idle capacity of the electric infrastructure in conjunction with the emerging PHEVs technology to meet the majority of daily energy needs of the Korean LDV fleet.

• Proceedings of the KSR Conference
• /
• 2008.11b
• /
• pp.2116-2120
• /
• 2008

Recently, in the national railway industry there has been interested in the methodology of hazard analysis and risk assessment. The need of safety management system based on the technology of hazard analysis and risk assessment is being extended to identify in advance the weakness and threat factors causing the accident and cope with the accident actively. It is important to manage the risk of railway casualty accidents having a majority of railway accident. Especially, a hazard event of people struck takes the highest proportion of the railway casualty accidents. This paper describes the result of analysis for environment properties such as an age of casualty, time happened, day, month and weather conditions being concerned in the hazard event of people struck.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.13 no.5
• /
• pp.69-79
• /
• 2003

We analyze key business process by using IDEF method in the perspective of business continuity, identify key information assets by using Skandia model, and use Nessus Version 1.4.2 to assess vulnerability about the sever of library information system according to OCTAVE(The Operationally Critical Threat, Asset, and Vulnerability Evaluation) approach. We suggest the vulnerability assessment case for introducing improved OCTAVE method including IDEF method and Skandia model.

• Health Policy and Management
• /
• v.19 no.3
• /
• pp.109-124
• /
• 2009

Background: This study aimed to examine whether cases of punishing false claimants threat general physicians to check their medical cost claims with care to avoid being suspected, and identify empirically general deterrence effects of the on-site investigation system in the Korean National Health Insurance. Methods: 800 clinics were selected among a total of 15,443 clinics that had no experience of on-site investigation until June 2007 using a stratified proportional systematic sampling method. We conducted logistic multiple regression to examine the association between factors related to provider's perception of on-site investigation and high level of perceived deterrence referring to fear of punishment after adjusting provider's service experiences and general characteristics. Results: The probability of high perceived deterrence was higher 1.7 times (CI: 1.13-2.56), 2.73 times (CI: 1.68-4.45) each among clinics exchanging the information once or more per year or once or more for 2-3 months than among clinics no exchanging the information about on-site investigation. Also, the probability of high perceived deterrence was higher 2.27 times (CI: 1.28-4.45) among clinics that knows more than 3 health care institutions having experienced an on-site investigation than among clinics knowing no case. Conclusion: A clinic knowing more punishment cases by onsite investigation and exchanging more frequently information about on-site investigation is likely to present high perceived deterrence. This result will provide important information to enlarge preventive effects of on-site investigation on fraud and abuse claims.