• Title/Summary/Keyword: Automated Hazard Analysis

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Development of Reliability-Based Optimum Design of High-Speed Railway Bridges Considering Structure-Rail Longitudinal Interaction and Structure-Vehicle Interaction Using Heuristic Decision Method (Heuristic Decision Method를 이용하여 구조물-궤도 종방향 상호작용 및 구조물-차량 상호작용을 고려한 고속철도 교량의 신뢰성 최적설계 기법 개발)

  • Ihm, Yeong-Rok
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.3
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    • pp.31-38
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    • 2010
  • In this study, it is suggested that it has to reliability-based design methodology with respect to bridge structure-rail longitudinal interaction and bridge structure-vehicle interaction. For the structural analysis, commercial package, ABAQUS, are used for a three-dimensional finite element analysis. The optimization process utilizes a well-known optimizer, ADS(Automated Design Synthesis). Optimization technique is utilized the ALM-BFGS method for global area search and Golden Section Method for 1-D search. In general, ALM-BFGS method don't need the 1-D search, and that algorithm converge a 0.1~0.2 of Push-Off factor. But in this study, value of Push-Off factor is used 90, therefore 1-D search should be needed for effective convergency. That algorithm contains the "heuristic decision method". As a result of optimum design of 2-main steel girder birdge with 5${\times}$(1@50m), design methodology suggested in this study was demonstrated more economic and efficient than existing design and LCC optimization not considering bridge-rail longitudinal interaction and bridge-vehicle interaction.

Prioritization of Potential Technology for Establishing a Safe Work Zone Environment (안전한 도로 공사구간 환경 구축에 필요한 기술의 우선순위 선정)

  • Kim, Jin Guk;Yang, Choong Heon;Yun, Duk Geun
    • International Journal of Highway Engineering
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    • v.17 no.6
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    • pp.117-126
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    • 2015
  • PURPOSES : This study prioritizes potential technology for establishing a safe work zone environment on roadways. We consider almost all conceivable technologies that enable mitigation of unexpected accidents for both road workers and drivers. METHODS : This study suggests a methodology to set the priority of potential technology for establishing a safe work zone environment by using the analytical hierarchy process (AHP). For this purpose, the AHP structure was first developed. Thereafter, a web-based survey was conducted to collect experts' opinions. Based on the survey results, weights associated with the relevant criteria of the developed structure were estimated. With the consistency index (CI) and consistency ratio (CR), we verified the estimated weights. In addition, a sensitivity analysis was performed to confirm whether the estimated weights were reliable. We finally proposed the priority for potential technology for establishing a safe work zone environment on roadways. RESULTS : In the first level, safety technology has the highest priority, and real-time information delivery for work zone, hazard warning for drivers, and temporal automated operation for traffic facilities were selected in the second level of hierarchy. CONCLUSIONS : The results imply that establishing the priority will be useful to establish a future road map for improving the work environment for road workers and drivers by employing appropriate protection facilities and developing safety systems.

A Study on the Risk Analysis and Fail-safe Verification of Autonomous Vehicles Using V2X Based on Intersection Scenarios (교차로 시나리오 기반 V2X를 활용한 자율주행차량의 위험성 분석 및 고장안전성 검증 연구)

  • Baek, Yunseok;Shin, Seong-Geun;Park, Jong-ki;Lee, Hyuck-Kee;Eom, Sung-wook;Cho, Seong-woo;Shin, Jae-kon
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.299-312
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    • 2021
  • Autonomous vehicles using V2X can drive safely information on areas outside the sensor coverage of autonomous vehicles conventional autonomous vehicles. As V2X technology has emerged as a key component of autonomous vehicles, research on V2X security is actively underway research on risk analysis due to failure of V2X communication is insufficient. In this paper, the service scenario and function of autonomous driving system V2X were derived by presenting the intersection scenario of the autonomous vehicle, the malfunction was defined by analyzing the hazard of V2X. he ISO26262 Part3 process was used to analyze the risk of malfunction of autonomous vehicle V2X. In addition, a fault injection scenario was presented to verify the fail-safe of the simulation-based intersection scenario.

The Implementation of Hierarchical Artificial Neural Network Classifier for Chromosome Karyotype Classification (염색체 핵형 분류를 위한 계층적 인공 신경회로망 분류기 구현)

  • Jeon, Gye-Rok;Choe, Uk-Hwan;Nam, Gi-Gon;Eom, Sang-Hui;Lee, Gwon-Sun;Jang, Yong-Hun
    • Journal of Biomedical Engineering Research
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    • v.18 no.3
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    • pp.233-241
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    • 1997
  • The research on chromosomes is very significant in cytogenetics since genes of the chromosomes control revelation of the inheritance plasma. The human chromosome analysis is widely used to study leukemia, malignancy, radiation hazard, and mutagen dosimetry as well as various congenital anomalies such as Down's, Klinefelter's, Edward's, and Patau's syndrome. The framing and analysis of the chromosome karyogram, which requires specific cytogenetic knowledge is most important in this field. Many researches on automated chromosome karyotype analysis methods have been carried out, some of which produced commercial systems. However, there still remains much room to improve the accuracy of chromosome classification and to reduce the processing time in real clinic environments. In this paper, we proposed a hierarchical artificial neural network(HANN) to classify the chromosome karyotype. We extracted three or four chromosome morphological feature parameters such as centromeric index, relative length ratio, relative area ratio, and chromosome length by preprocessing from ten human chromosome images. The feature parameters of five human chromosome images were used to learn HANN and the rest of them were used to classify the chromosome images. The experiment results show that the chromosome classification error is reduced much more than that of the other researchers using less feature parameters.

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Prognostic Implication of Volumetric Quantitative CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea

  • Byunggeon Park;Jongmin Park;Jae-Kwang Lim;Kyung Min Shin;Jaehee Lee;Hyewon Seo;Yong Hoon Lee;Jun Heo;Won Kee, Lee;Jin Young Kim;Ki Beom Kim;Sungjun Moon;Sooyoung, Choi
    • Korean Journal of Radiology
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    • v.21 no.11
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    • pp.1256-1264
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    • 2020
  • Objective: Lung segmentation using volumetric quantitative computed tomography (CT) analysis may help predict outcomes of patients with coronavirus disease (COVID-19). The aim of this study was to investigate the relationship between CT volumetric quantitative analysis and prognosis in patients with COVID-19. Materials and Methods: CT images from patients diagnosed with COVID-19 from February 18 to April 15, 2020 were retrospectively analyzed. CT with a negative finding, failure of quantitative analysis, or poor image quality was excluded. CT volumetric quantitative analysis was performed by automated volumetric methods. Patients were stratified into two risk groups according to CURB-65: mild (score of 0-1) and severe (2-5) pneumonia. Outcomes were evaluated according to the critical event-free survival (CEFS). The critical events were defined as mechanical ventilator care, ICU admission, or death. Multivariable Cox proportional hazards analyses were used to evaluate the relationship between the variables and prognosis. Results: Eighty-two patients (mean age, 63.1 ± 14.5 years; 42 females) were included. In the total cohort, male sex (hazard ratio [HR], 9.264; 95% confidence interval [CI], 2.021-42.457; p = 0.004), C-reactive protein (CRP) (HR, 1.080 per mg/dL; 95% CI, 1.010-1.156; p = 0.025), and COVID-affected lung proportion (CALP) (HR, 1.067 per percentage; 95% CI, 1.033-1.101; p < 0.001) were significantly associated with CEFS. CRP (HR, 1.164 per mg/dL; 95% CI, 1.006-1.347; p = 0.041) was independently associated with CEFS in the mild pneumonia group (n = 54). Normally aerated lung proportion (NALP) (HR, 0.872 per percentage; 95% CI, 0.794-0.957; p = 0.004) and NALP volume (NALPV) (HR, 1.002 per mL; 95% CI, 1.000-1.004; p = 0.019) were associated with a lower risk of critical events in the severe pneumonia group (n = 28). Conclusion: CRP in the mild pneumonia group; NALP and NALPV in the severe pneumonia group; and sex, CRP, and CALP in the total cohort were independently associated with CEFS in patients with COVID-19.

Model Integration of Systems Design and Safety Analysis Processes for Systematic Design of Safety-Critical Systems (안전중시 시스템의 체계적인 설계를 위한 시스템 설계 및 안전 분석 활동 모델의 통합)

  • Kim, Chang-Won;Lee, Jae-Chon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.8
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    • pp.363-368
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    • 2016
  • In safety-critical systems (SCS), failure may result in accidents with serious damage to human beings and property. As systems become more complex and automated, the goal of acquiring safety has attracted increasing attention lately in the defense industry, as well as the rail, automotive, and aerospace industries, among others. As such, the Department of Defense and international organizations have established appropriate standards and guidelines for systems safety and design. To this end, there has been research on the processes, methods, and associated tools for safety design. However, those results do not seem to sufficiently utilize system architectural information. The purpose of this paper is to provide a more systematic approach to SCS design. To better identify potential hazards, design information at each level of system hierarchy is exploited. Based on the results, an integrated process model was developed by combining the processes of system design and safety analysis. As a case study, the resultant integrated process model was applied to the safety design of an automobile system, which shows useful results for safety evaluation.