• 제목/요약/키워드: Risk simulation

검색결과 1,093건 처리시간 0.028초

2007 Price Risk Management & World Maize Outlook 세미나

  • 홍성수
    • 사료
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    • 통권27호
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    • pp.81-85
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    • 2007
  • 지난 5월 17,18일 양 일간에 걸쳐 한국사료협회(KFA)와 미국곡물협회(USGC)는 국내곡물 구매자들을 대상으로 급변하는 국제곡물시장에 능동적으로 대처하고자 미국CBOT, USGC, Cargil티 Consultant의 발표와 Simulation을 병행하는 "2007 Price Risk Management & World Maize Outlook 세 미나"를 개최하였다. 이 에 본지에서는 세미나 내용을 요약.게재 한다.

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네트워크 포트스캔의 위험에 대한 정량화 방법 (A Method for Quantifying the Risk of Network Port Scan)

  • 박성철;김준태
    • 한국시뮬레이션학회논문지
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    • 제21권4호
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    • pp.91-102
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    • 2012
  • 네트워크 포트스캔 공격은 내부 네트워크에 있는 시스템에서 열려 있는 포트를 알아내기 위한 방법이다. 기존 대부분의 침입탐지시스템(Intrusion Detection System; IDS)들은 단위 시간당 시스템 또는 네트워크에 몇 번의 패킷을 보냈는지의 횟수를 기록하여 전송한 패킷의 횟수가 임계치보다 높은 소스 인터넷 주소(source IP address)에 대해서 포트스캔 공격이 수행되었다고 간주하였다. 즉, 네트워크 포트스캔 공격을 수행한 소스 인터넷 주소에 대한 위험 정도는 IDS들이 기록한 포트스캔 공격횟수에 의존하였다. 그러나 단순히 포트스캔 공격 횟수에 기반을 둔 위험성의 측정은 느린 포트스캔 공격에 대해 거짓 부정(false negative)이 높아져 포트스캔 탐지율이 낮아진다는 문제가 있다. 본 연구에서는 네트워크 포트스캔 공격에 대해 좀 더 정확하고 포괄적인 구분을 하기 위해 4가지 형태의 정보를 요약한다. 포트스캔 공격에 대한 위험성을 집약적으로 나타내기 위하여 주성분분석(principal component analysis, PCA)에 의해 이러한 정보들을 정량화한 위험지수를 제안한다. 실험을 통해 제안한 위험지수를 이용한 탐지가 포트스캔 탐지율에 있어서 Snort보다 우수하다는 것을 보인다.

작업장에서의 n-부틸 글리시딜 에테르에 대한 건강 위험성 평가 (Human Health Risk Assessment of n-Butyl Glycidyl Ether from Occupational Workplaces)

  • 문형일;최현일;신새미;변상훈
    • 한국산업보건학회지
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    • 제23권1호
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    • pp.20-26
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    • 2013
  • Objectives: This study was conducted to evaluate the health risk of workers exposed to butyl glycidyl ether to prevent them from developing occupational diseases. Methods: The workplaces that coat floor with epoxy were selected and the samples were collected and analyzed with NIOSH 1616 Method. We calculate workplace reference concentration using with NOAEL estimated by the study of Anderson et al. in 1978. Risk was calculated by the ratio of exposure to workplace reference concentration. Monte-Carlo simulation was performed to derivate the median, cumulative 90%, and cumulative 95% value by using Crystal Ball. Results: Butyl glycidyl ether is a skin, eye irritator and can result in central nervous system depression, allergic reaction. NOAEL was 38 ppm and workplace reference concentration was calculated as 0.73 ppm corrected with uncertainty factors. Geometric mean was 1.152 ppm and geometric standard deviation was 1.522 by the workplace environment measurement. The median, cumulative 90%, and cumulative 95% value of risk were calculated as 1.617, 1.934, and 2.092, respectively. Conclusions: Not only cumulative 90% and cumulative 95% value but also the median of risk is higher than 1.0 by the risk characterization, so it can do a lot of harm to workers. Therefore, the process of derivating workplace reference concentration and the appropriacy of the uncertainty factors should be re-examined.

Uncertainty reduction of seismic fragility of intake tower using Bayesian Inference and Markov Chain Monte Carlo simulation

  • Alam, Jahangir;Kim, Dookie;Choi, Byounghan
    • Structural Engineering and Mechanics
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    • 제63권1호
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    • pp.47-53
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    • 2017
  • The fundamental goal of this study is to minimize the uncertainty of the median fragility curve and to assess the structural vulnerability under earthquake excitation. Bayesian Inference with Markov Chain Monte Carlo (MCMC) simulation has been presented for efficient collapse response assessment of the independent intake water tower. The intake tower is significantly used as a diversion type of the hydropower station for maintaining power plant, reservoir and spillway tunnel. Therefore, the seismic fragility assessment of the intake tower is a pivotal component for estimating total system risk of the reservoir. In this investigation, an asymmetrical independent slender reinforced concrete structure is considered. The Bayesian Inference method provides the flexibility to integrate the prior information of collapse response data with the numerical analysis results. The preliminary information of risk data can be obtained from various sources like experiments, existing studies, and simplified linear dynamic analysis or nonlinear static analysis. The conventional lognormal model is used for plotting the fragility curve using the data from time history simulation and nonlinear static pushover analysis respectively. The Bayesian Inference approach is applied for integrating the data from both analyses with the help of MCMC simulation. The method achieves meaningful improvement of uncertainty associated with the fragility curve, and provides significant statistical and computational efficiency.

An AI-Based Prevention Program to Protect Youth from Cybergrooming

  • 김기정;리푸 후앙;조진희
    • 인터넷정보학회논문지
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    • 제24권5호
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    • pp.67-73
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    • 2023
  • The Digital Age calls for improvement of information literacy particularly among children and youth who are vulnerable to cybergrooming. Taking an interdisciplinary approach by leveraging our team's expertise including child and adolescent development, data analytics, and cybersecurity, this study proposes an interactive artificial intelligence (AI)-based preventive simulation program that raises youth knowledge and awareness about the risk of cybergrooming as well as increases resilient self-efficacy in their cybersecurity-relevant skills. The primary purpose of this project is to evaluate the effectiveness of the simulation program on preventing cybergrooming. More specifically, this study is designed to examine developmental changes in self-efficacy of cybersecurity-relevant skills among youth participants as a function of the preventive simulation program. Further, this study will identify risk and protective factors that explain interindividual differences in the ability of children and youth either to fall victim to advances from a cyber predator or to recognize and deter such threats. The preliminary data will help improve the effectiveness of the preventive simulation program as well as the methods of implementation to large groups of youth. The findings from the proposed study will contribute to making specific recommendations to parents, educators, practitioners, and policy makers for the prevention of cybergrooming.

A General Semiparametric Additive Risk Model

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제19권2호
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    • pp.421-429
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    • 2008
  • We consider a general semiparametric additive risk model that consists of three components. They are parametric, purely and smoothly nonparametric components. In parametric component, time dependent term is known up to proportional constant. In purely nonparametric component, time dependent term is an unknown function, and time dependent term in smoothly nonparametric component is an unknown but smoothly function. As an estimation method of this model, we use the weighted least square estimation by Huffer and McKeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

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A Simple Estimation of Relative Risk

  • Park, Hyo-Il;Hong, Seung-Man
    • Communications for Statistical Applications and Methods
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    • 제14권2호
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    • pp.317-327
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    • 2007
  • In this paper, we propose a simple estimate of relative risk based on a functional equation. We derive the asymptotic normality with a restricted condition. Then we discuss some interesting features as concluding remarks. Finally we comment briefly about application of the estimate to the testing problems and compare our estimate with that of Begun through simulation study.

A Nonparametric Additive Risk Model Based on Splines

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제18권1호
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    • pp.97-105
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    • 2007
  • We consider a nonparametric additive risk model that is based on splines. This model consists of both purely and smoothly nonparametric components. As an estimation method of this model, we use the weighted least square estimation by Huller and Mckeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

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A Nonparametric Additive Risk Model Based On Splines

  • 박철용
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2006년도 추계 학술발표회 논문집
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    • pp.49-50
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    • 2006
  • We consider a nonparametric additive risk model that are based on splines. This model consists of both purely and smoothly nonparametric components. As an estimation method of this model, we use the weighted least square estimation by Huffer and McKeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

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