• 제목/요약/키워드: effective damage model

검색결과 409건 처리시간 0.021초

Decision-Making Model Research for the Calculation of the National Disaster Management System's Standard Disaster Prevention Workforce Quota : Based on Local Authorities

  • Lee, Sung-Su;Lee, Young-Jai
    • Journal of Information Technology Applications and Management
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    • 제17권3호
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    • pp.163-189
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    • 2010
  • The purpose of this research is to develop a decision-making model for the calculation of the National Disaster Management System's standard prevention workforce quota. The final purpose of such model is to support in arranging a rationally sized prevention workforce for local authorities by providing information about its calculation in order to support an effective and efficient disaster management administration. In other words, it is to establish and develop a model that calculates the standard disaster prevention workforce quota for basic local governments in order to arrange realistically required prevention workforce. In calculating Korea's prevention workforce, it was found that the prevention investment expenses, number of prevention facilities, frequency of flood damage, number of disaster victims, prevention density, and national disaster recovery costs have positive influence on the dependent variable when the standard prevention workforce was set as the dependent variable. The model based on the regression analysis-which consists of dependent and independent variables-was classified into inland mountainous region, East coast region, Southwest coastal plain region to reflect regional characteristics for the calculation of the prevention workforce. We anticipate that the decision-making model for the standard prevention workforce quota will aid in arranging an objective and essential prevention workforce for Korea's basic local authorities.

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Long term structural health monitoring for old deteriorated bridges: a copula-ARMA approach

  • Zhang, Yi;Kim, Chul-Woo;Zhang, Lian;Bai, Yongtao;Yang, Hao;Xu, Xiangyang;Zhang, Zhenhao
    • Smart Structures and Systems
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    • 제25권3호
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    • pp.285-299
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    • 2020
  • Long term structural health monitoring has gained wide attention among civil engineers in recent years due to the scale and severity of infrastructure deterioration. Establishing effective damage indicators and proposing enhanced monitoring methods are of great interests to the engineering practices. In the case of bridge health monitoring, long term structural vibration measurement has been acknowledged to be quite useful and utilized in the planning of maintenance works. Previous researches are majorly concentrated on linear time series models for the measurement, whereas nonlinear dependences among the measurement are not carefully considered. In this paper, a new bridge health monitoring method is proposed based on the use of long term vibration measurement. A combination of the fundamental ARMA model and copula theory is investigated for the first time in detecting bridge structural damages. The concept is applied to a real engineering practice in Japan. The efficiency and accuracy of the copula based damage indicator is analyzed and compared in different window sizes. The performance of the copula based indicator is discussed based on the damage detection rate between the intact structural condition and the damaged structural condition.

Ginsenoside compound K reduces the progression of Huntington's disease via the inhibition of oxidative stress and overactivation of the ATM/AMPK pathway

  • Hua, Kuo-Feng;Chao, A-Ching;Lin, Ting-Yu;Chen, Wan-Tze;Lee, Yu-Chieh;Hsu, Wan-Han;Lee, Sheau-Long;Wang, Hsin-Min;Yang, Ding-I.;Ju, Tz-Chuen
    • Journal of Ginseng Research
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    • 제46권4호
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    • pp.572-584
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    • 2022
  • Background: Huntington's disease (HD) is a neurodegenerative disorder caused by the expansion of trinucleotide CAG repeat in the Huntingtin (Htt) gene. The major pathogenic pathways underlying HD involve the impairment of cellular energy homeostasis and DNA damage in the brain. The protein kinase ataxia-telangiectasia mutated (ATM) is an important regulator of the DNA damage response. ATM is involved in the phosphorylation of AMP-activated protein kinase (AMPK), suggesting that AMPK plays a critical role in response to DNA damage. Herein, we demonstrated that expression of polyQ-expanded mutant Htt (mHtt) enhanced the phosphorylation of ATM. Ginsenoside is the main and most effective component of Panax ginseng. However, the protective effect of a ginsenoside (compound K, CK) in HD remains unclear and warrants further investigation. Methods: This study used the R6/2 transgenic mouse model of HD and performed behavioral tests, survival rate, histological analyses, and immunoblot assays. Results: The systematic administration of CK into R6/2 mice suppressed the activation of ATM/AMPK and reduced neuronal toxicity and mHTT aggregation. Most importantly, CK increased neuronal density and lifespan and improved motor dysfunction in R6/2 mice. Conversely, CK enhanced the expression of Bcl2 protected striatal cells from the toxicity induced by the overactivation of mHtt and AMPK. Conclusions: Thus, the oral administration of CK reduced the disease progression and markedly enhanced lifespan in the transgenic mouse model (R6/2) of HD.

Theoretical Conception of Synergistic Interactions

  • Kim, Jin-Kyu;Vladislav G. Petin
    • 환경생물
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    • 제20권4호
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    • pp.277-286
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    • 2002
  • An increase in the overall biological effect under the combined action of ionizing radiation with another inactivating agent can be explained in two ways. One is the supposition that synergism may attribute to a reduced cellular capacity of damn-ge repair after the combined action. The other is the hypothesis that synergism may be related to an additional lethal or potentially lethal damage that arises from the interaction of sublesions induced by both agents. These sublesions ave considered to be in-effective when each agent is applied separately. Based on this hypothesis, a simple mathematical model was established. The model can predict the greatest value of the synergistic effect, and the dependence of synergy on the intensity of agents applied, as well. This paper deals with the model validation and the peculiarity of simultaneous action of various factors with radiation on biological systems such as bacteriophage, bacterial spores, yeast and mammalian cells. The common rules of the synergism aye as follows. (1) For any constant rate of exposure, the synergy can be observed only within a certain temperature range. The temperature range which synergistically increases the effects of radiation is shifted to the lower temperature fer thermosensitive objects. Inside this range, there is a specific temperature that maximizes the synergistic effect. (2) A decrease in the exposure rate results in a decrease of this specific temperature to achieve the greatest synergy and vice versa. For a constant temperature at which the irradiation occurs, synergy can be observed within a certain dose rate range. Inside this range an optimal intensity of the physical agent may be indicated, which maximizes the synergy. As the exposure temperature reduces, the optimal intensity decreases and vice versa. (3) The recovery rate after combined action is decelerated due to an increased number of irreversible damages. The probability of recovery is independent of the exposure temperature for yeast cells irradiated with ionizing or UV radiation. Chemical inhibitors of cell recovery act through the formation of irreversible damage but not via damaging the recovery process itself.

객체 인식 모델을 활용한 적재 불량 화물차 탐지 시스템 (An Overloaded Vehicle Identifying System based on Object Detection Model)

  • 정우진;박진욱;박용주
    • 한국정보통신학회논문지
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    • 제26권12호
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    • pp.1794-1799
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    • 2022
  • 최근 증가하고 있는 도로 위 적재 불량 화물차는 비정상적인 무게 중심으로 인해 물체 낙하, 도로 파손, 연쇄 추돌 등 교통안전에 위해가 되고 한번 사고가 발생하면 큰 피해가 유발할 수 있다. 하지만 이러한 비정상적인 무게 중심은 적재 불량 차량 인식을 위한 주행 중 축중 시스템으로는 검출이 불가능하다는 한계점이 있다. 본 논문에서는 이러한 사회 문제를 야기하는 적재 불량 차량을 관리하기 위한 객체 인식 기반 AI 모델을 구축하고자 한다. 또한 AI-Hub에 공개된 약 40만 장의 데이터셋을 비교 분석하여 전처리를 통해 적재 불량 차량 검지 AI 모델의 성능을 향상시키는 방법을 제시한다. 또한 객체 추적을 통해 실시간 검지를 수행하는 방법을 제안한다. 이를 통해, 원시 데이터를 활용한 학습 성능 대비 약 23% 향상된 적재 불량 차량의 검출 성능을 나타냄을 보였다. 본 연구 결과를 통해 공개 빅데이터를 보다 효율적으로 활용하여, 객체 인식 기반 적재 불량 차량 탐지 모델 개발에 적용할 수 있을 것으로 기대된다.

취약성 평가 기반 함정 임무수행능력 측정 방법: 해군 교전급 분석모델을 중심으로 (A Mission Capability Measuring Methodology of Warship based on Vulnerability Assessment: Focused on Naval Engagement Level Analysis Model)

  • 양정관;김봉석;최봉완;김종수
    • 산업경영시스템학회지
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    • 제46권4호
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    • pp.218-228
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    • 2023
  • Maintaining sea superiority through successful mission accomplishments of warships is being proved to be an important factor of winning a war, as in the Ukraine-Russia war. in order to ensure the ability of a warship to perform its duties, the survivability of the warship must be strengthened. In particular, among the survivability factors, vulnerability is closely related to a damage assessment, and these vulnerability data are used as basic data to measure the mission capability. The warship's mission capability is usually measured using a wargame model, but only the operational effects of a macroscopic view are measured with a theater level resolution. In order to analyze the effectiveness and efficiency of a weapon system in the context of advanced weapon systems and equipments, a warship's mission capability must be measured at the engagement level resolution. To this end, not the relationship between the displacement tonnage and the weight of warheads applied in the theater level model, but an engagement level resolution vulnerability assessment method that can specify physical and functional damage at the hit position should be applied. This study proposes a method of measuring a warship's mission capability by applying the warship vulnerability assessment method to the naval engagement level analysis model. The result can be used as basic data in developing engagement algorithms for effective and efficient operation tactics to be implemented from a single unit weapon system to multiple warships.

Gradual Bilinear Method를 이용한 사장교의 케이블 손상응답 해석 (Abnormal Response Analysis of a Cable-Stayed Bridge using Gradual Bilinear Method)

  • 김병철;박기태;김태헌;황지현
    • 한국구조물진단유지관리공학회 논문집
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    • 제18권6호
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    • pp.60-71
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    • 2014
  • 대표적인 장대교량 형식인 사장교는 공용 중에 케이블 손상이 발생하는 경우 전체 구조계의 손상을 유발할 수 있으므로 신속한 유지관리가 필요하다. 손상발생 이후 대응시간을 가능한 단축하기 위해서 손상신호로부터 직접 이상거동을 판단할 수 있는 알고리즘에 대한 많은 연구가 진행되고 있다. 이상거동 감지 알고리즘의 정확도를 향상시키기 위해서는 구조물의 다양한 손상에 대한 충분한 양의 계측결과가 필요하다. 그러나 공용중인 교량에 손상을 주어 이상거동을 계측할 수 없으므로 수치적인 방법으로 이상거동을 모사하는 것이 효율적인 대안이 될 수 있다. 사장교 케이블의 손상을 모사하는 지금까지의 연구는 케이블의 강성변화를 단순한 장력변화로만 모사하여 해석하는 방법이 주를 이루었다. 이러한 해석방법은 설계목적의 정밀도는 확보할 수 있지만 케이블의 손상에 의한 구조물의 정확한 응답을 재현하지 못한다. 본 연구는 사장교의 손상을 모사하기 위해 강성 및 질량의 변화를 고려하는 직접적분법 Gradual Bilinear Method (GBM)을 제안하고 해석프로그램을 개발하였다. 개발된 해석방법을 단순모델을 이용하여 검증하고 실제 사장교모델을 이용하여 손상시각 및 손상지연시간에 따른 응답의 변화를 관찰하였다. 수행된 연구결과는 향후 건축/대형구조물의 안전관리를 위한 고정밀도 이상거동 감지알고리즘을 개발하고 검증하는데 활용될 수 있다.

Minimum life-cycle cost design of ice-resistant offshore platforms

  • Li, Gang;Zhang, Da-Yong;Yue, Qian-Jin
    • Structural Engineering and Mechanics
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    • 제31권1호
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    • pp.11-24
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    • 2009
  • In China, the oil and natural gas resources of Bohai Bay are mainly marginal oil fields. It is necessary to build both ice-resistant and economical offshore platforms. However, risk is involved in the design, construction, utilization, maintenance of offshore platforms as uncertain events may occur within the life-cycle of a platform under the extreme ice load. In this study, the optimum design model of the expected life-cycle cost for ice-resistant platforms based on cost-effectiveness criterion is proposed. Multiple performance demands of the structure, facilities and crew members, associated with the failure assessment criteria and evaluation functions of costs of construction, consequences of structural failure modes including damage, revenue loss, death and injury as well as discounting cost over time are considered. An efficient approximate method of the global reliability analysis for the offshore platforms is provided, which converts the implicit nonlinear performance function in the conventional reliability analysis to linear explicit one. The proposed life-cycle optimum design formula are applied to a typical ice-resistant platform in Bohai Bay, and the results demonstrate that the life-cycle cost-effective optimum design model is more rational compared to the conventional design.

Estimation of the soil liquefaction potential through the Krill Herd algorithm

  • Yetis Bulent Sonmezer;Ersin Korkmaz
    • Geomechanics and Engineering
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    • 제33권5호
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    • pp.487-506
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    • 2023
  • Looking from the past to the present, the earthquakes can be said to be type of disaster with most casualties among natural disasters. Soil liquefaction, which occurs under repeated loads such as earthquakes, plays a major role in these casualties. In this study, analytical equation models were developed to predict the probability of occurrence of soil liquefaction. In this context, the parameters effective in liquefaction were determined out of 170 data sets taken from the real field conditions of past earthquakes, using WEKA decision tree. Linear, Exponential, Power and Quadratic models have been developed based on the identified earthquake and ground parameters using Krill Herd algorithm. The Exponential model, among the models including the magnitude of the earthquake, fine grain ratio, effective stress, standard penetration test impact number and maximum ground acceleration parameters, gave the most successful results in predicting the fields with and without the occurrence of liquefaction. This proposed model enables the researchers to predict the liquefaction potential of the soil in advance according to different earthquake scenarios. In this context, measures can be realized in regions with the high potential of liquefaction and these measures can significantly reduce the casualties in the event of a new earthquake.

빅데이터 분석을 활용한 초기 정보 기반 화재현장 위험도 예측 모델 개발 연구 (A Study on the Development of a Fire Site Risk Prediction Model based on Initial Information using Big Data Analysis)

  • 김도형;조병완
    • 한국재난정보학회 논문집
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    • 제17권2호
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    • pp.245-253
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    • 2021
  • 연구목적: 본 연구는 화재발생 건축물 정보, 신고자 취득 정보 등 초기 정보를 활용하여 화재현장의 위험도를 예측하여, 재난 발생 초기에 효과적인 소방자원 동원 및 적절한 대응을 위한 피해최소화 전략 수립을 지원하는 위험도 예측 모델을 개발하고자 한다. 연구방법: 화재 통계 데이터 상에서 화재의 피해규모와 관련된 변수 규명을 위해 머신러닝 알고리즘을 이용한 변수간 상관성 분석을 실시하여 예측 가능성을 검토하고, 데이터 표준화 및 이산화 등의 전처리를 통해 학습 데이터 셋을 구축하였다. 이를 활용하여 예측 정확도가 높은 것으로 평가 받고 있는 복수의 머신러닝 알고리즘을 테스트하여 가장 정확도가 높은 알고리즘을 적용한 위험도 예측 모델을 개발하였다. 연구결과: 머신러닝 알고리즘 성능 테스트 결과 랜덤포레스트 알고리즘의 정확도가 가장 높게 나왔으며, 위험도 등급에 대해서는 중간치에 대한 정확성이 상대적으로 높은 것으로 확인되었다. 결론: 화재 통계 상 피해규모 데이터의 편향성에 의해 예측모델 정확도가 제한적으로 나타났으며, 예측 모델 성능 개선을 위해 데이터 정합성 및 결손치 보완 등을 통한 데이터 정제가 필요하다.