scholarly journals Analysis Model of Risk Factors of Urban Bus Operation Based on FTA-CLR

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jianfeng Xi ◽  
Yunhe Zhao ◽  
Tongqiang Ding ◽  
Jian Tian ◽  
Lianjie Li
Keyword(s):  
Risk Factors ◽  
Goodness Of Fit ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Economic Loss ◽  
Analysis Model ◽  
Goodness Of Fit Test ◽  
High Risk Factors ◽  
Accident Data ◽  
Urban Bus

In order to comprehensively analyze the risk factors and accurately find the high risk factors related to accidents, an analysis model of risk factors of urban bus operation is proposed, in which the advantages of the structural analysis of the Fault Tree Analysis (FTA) and the correlation analysis of the Cumulative Logistic Regression (CLR) are combined. Firstly, based on the accident data in Northeast China, FTA is used to compile the urban bus operation fault tree. In the fault tree, 16 bus operation risk factors are classified, while the risk factors are sorted and compared from three aspects: structural importance, probability importance, and critical importance. And then, the 11 higher risk factors are selected according to the discriminant principle. Secondly, bus operation accidents are divided into fatal accidents, injury accidents, and major economic loss accidents. The CLR model is used to fit the much higher risk factors that lead to urban bus operation accidents from above 11 higher risk factors. Finally, the scientific rationality and applicability of the model are verified, through the goodness of fit test and the comparison test with the actual probability of occurrence.

scholarly journals Risk Analysis of Tunnel Water and Mud Inrush Using Interpretive Structural Modeling and Fault Tree

2022 ◽  
Author(s):  
Min Han ◽  
Teng Xia ◽  
Maoxin Su ◽  
Yiguo Xue
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Structural Modeling ◽  
Geological Structure ◽  
Geological Hazard ◽  
Analysis Model ◽  
Interpretive Structural Modeling ◽  
Water And Mud Inrush

Abstract Water and mud inrush is a common geological hazard in tunnel construction. Risk analysis of tunnel water and mud inrush has always been an important subject. In order to avoid the geological hazard, this paper presents a risk analysis model of tunnel water and mud inrush. The model combines the interpretive structural modeling method (ISM) and fault tree analysis (FTA). Relying on the Qinyu tunnel in the Weiwu expressway project, water and mud inrush risk factors are obtained by using ISM. Fundamental risk factors include formation lithology, attitude of stratum, strata combination, topography and geomorphology, geological structure and weather. ISM core risk factors are used as FTA basic events. Fuzzy importance of FTA basic events is obtained by using fuzzy interval calculation. The results show that geological structure is the primary risk factor causing Qinyu tunnel water and mud inrush. The model achieves qualitative and quantitative analysis of tunnel water and mud inrush. It accurately determines the main factors affecting the tunnel water and mud inrush, which is conducive to accident prevention.

scholarly journals Risk factors for peripheral venous catheter failure: A prospective cohort study of 5345 patients

2021 ◽  
pp. 112972982110150
Author(s):  
Ya-mei Chen ◽  
Xiao-wen Fan ◽  
Ming-hong Liu ◽  
Jie Wang ◽  
Yi-qun Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Cohort Study ◽  
Goodness Of Fit ◽  
Insertion Site ◽  
Healthcare Providers ◽  
Venous Catheter ◽  
Goodness Of Fit Test ◽  
Peripheral Venous Catheter ◽  
Independent Risk Factors

Purpose: The objective of this study was to determine the independent risk factors associated with peripheral venous catheter (PVC) failure and develop a model that can predict PVC failure. Methods: This prospective, multicenter cohort study was carried out in nine tertiary hospitals in Suzhou, China between December 2017 and February 2018. Adult patients undergoing first-time insertion of a PVC were observed from catheter insertion to removal. Logistic regression was used to identify the independent risk factors predicting PVC failure. Results: This study included 5345 patients. The PVC failure rate was 54.05% ( n = 2889/5345), and the most common causes of PVC failure were phlebitis (16.3%) and infiltration/extravasation (13.8%). On multivariate analysis, age (45–59 years: OR, 1.295; 95% CI, 1.074–1.561; 60–74 years: OR, 1.375; 95% CI, 1.143–1.654; ⩾75 years: OR, 1.676; 95% CI, 1.355–2.073); department (surgery OR, 1.229; 95% CI, 1.062–1.423; emergency internal/surgical ward OR, 1.451; 95% CI, 1.082–1.945); history of venous puncture in the last week (OR, 1.298, 95% CI 1.130–1.491); insertion site, number of puncture attempts, irritant fluid infusion, daily infusion time, daily infusion volume, and type of sealing liquid were independent predictors of PVC failure. Receiver operating characteristic curve analysis indicated that a logistic regression model constructed using these variables had moderate accuracy for the prediction of PVC failure (area under the curve, 0.781). The Hosmer-Lemeshow goodness of fit test demonstrated that the model was correctly specified (χ2 = 2.514, p = 0.961). Conclusion: This study should raise awareness among healthcare providers of the risk factors for PVC failure. We recommend that healthcare providers use vascular access device selection tools to select a clinically appropriate device and for the timely detection of complications, and have a list of drugs classified as irritants or vesicants so they can monitor patients receiving fluid infusions containing these drugs more frequently.

A fuzzy fault tree analysis based risk assessment approach for enterprise resource planning projects

2018 ◽  
Vol 35 (5) ◽  
pp. 1115-1141 ◽  
Author(s):  
Mina Moeinedini ◽  
Sadigh Raissi ◽  
Kaveh Khalili-Damghani
Keyword(s):  
Risk Factors ◽  
Enterprise Resource Planning ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Resource Planning ◽  
Successful Implementation ◽  
Tree Analysis ◽  
Content Type ◽  
Cause And Effect ◽  
Fuzzy Fault Tree Analysis

Purpose Enterprise resource planning (ERP) is assumed as a commonly used solution in order to provide an integrated view of core business processes, including product planning, manufacturing cost, delivery, marketing, sales, inventory management, shipping and payment. Selection and implementation of a suitable ERP solution are not assumed a trivial project because of the challenging nature of it, high costs, long-duration of installation and customization, as well as lack of successful benchmarking experiences. During the ERP projects, several risk factors threat the successful implementation of the project. These risk factors usually refer to different phases of the ERP projects including purchasing, pilot implementation, teaching, install, synchronizing, and movement from old systems toward new ones, initiation and utilization. These risk factors have dominant effects on each other. The purpose of this paper is to explore the hybrid reliability-based method is proposed to assess the risk factors of ERP solutions. Design/methodology/approach In this regard, the most important risk factors of ERP solutions are first determined. Then, the interactive relations of these factors are recognized using a graph based method, called interpretive structural modeling. The resultant network of relations between these factors initiates a new viewpoint toward the cause and effect relations among risk factors. Afterwards, a fuzzy fault tree analysis is proposed to calculate Failure Fuzzy Possibility (FFP) for the basic events of the fault tree leading to a quantitative evaluation of risk factors. Findings The whole proposed method is applied in a well-known Iranian foodservice distributor as a case study. The most impressive risk factors are identified, classified and prioritized. Moreover, the cause and effect diagram between the risk factors are identified. So, the ERP leader can plan a low-risk project and increase the chance of success. Originality/value According to the authors’ best knowledge, such approach was not reported before in the literature of ERP risk assessments.

Cybersecurity risk analysis model using fault tree analysis and fuzzy decision theory

2018 ◽  
Vol 43 ◽  
pp. 248-260 ◽  
Author(s):  
Ana Paula Henriques de Gusmão ◽  
Maisa Mendonça Silva ◽  
Thiago Poleto ◽  
Lúcio Camara e Silva ◽  
Ana Paula Cabral Seixas Costa
Keyword(s):  
Risk Analysis ◽  
Decision Theory ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Fuzzy Decision ◽  
Analysis Model ◽  
Tree Analysis

scholarly journals Development and Validation of a Risk Scoring System for Cephamycin-Associated Hemorrhagic Events

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Tong-Ling Chien ◽  
Fei-Yuan Hsiao ◽  
Li-Ju Chen ◽  
Yu-Wen Wen ◽  
Shu-Wen Lin
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Scoring System ◽  
Goodness Of Fit ◽  
Bleeding Tendency ◽  
Multivariate Logistic Regression ◽  
Goodness Of Fit Test ◽  
Hemorrhagic Events ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Cephamycin-associated hemorrhages have been reported since their launch. This research aimed to determine risk factors for cephamycin-associated hemorrhagic events and produce a risk scoring system using National Taiwan University Hospital (NTUH) database. Patients who were older than 20 years old and consecutively used study antibiotics for more than 48 hours (epidode) at NTUH between January 1st, 2009 and December 31st, 2015 were included. The population was divided into two cohorts for evaluation of risk factors and validation of the scoring system. Multivariate logistic regression was used for the assessment of the adjusted association between factors and the outcome of interest. Results of the multivariate logistic regression were treated as the foundation to develop the risk scoring system. There were 46402 and 22681 episodes identified in 2009–2013 and 2014–2015 cohorts with 356 and 204 hemorrhagic events among respective cohorts. Use of cephamycins was associated with a higher risk for hemorrhagic outcomes (aOR 2.03, 95% CI 1.60–2.58). Other risk factors included chronic hepatic disease, at least 65 years old, prominent bleeding tendency, and bleeding history. A nine-score risk scoring system (AUROC = 0.8035, 95% CI 0.7794–0.8275; Hosmer-Lemeshow goodness-of-fit test p = 0.1044) was developed based on the identified risk factors, with higher scores indicating higher risk for bleeding. Use of cephamycins was associated with more hemorrhagic events compared with commonly used penicillins and cephalosporins. The established scoring system, CHABB, may help pharmacists identify high-risk patients and provide recommendations according to the predictive risk, and eventually enhance the overall quality of care.

Research and Application of Evidence Synthesis FTA Model Based on Similarity Analysis

2014 ◽  
Vol 926-930 ◽  
pp. 2001-2005
Author(s):  
You Long Yuan ◽  
Bin Liu
Keyword(s):  
Evidence Synthesis ◽  
Fault Tree ◽  
Evidence Theory ◽  
Fault Tree Analysis ◽  
Similarity Analysis ◽  
Analysis Model ◽  
Tree Analysis ◽  
Model Based ◽  
Validity Measures ◽  
Multiple Experts

In order to integrate multiple experts' opinions effectively, a fault tree analysis model based on the similarity is presented in this paper. First, the concept of similarity used to fuse data is introduced to analyze the similarity among multiple experts' opinions, and to assign each expert's opinions credibility weights based on the analysis results. Then, experts' opinions is synthesized by evidence theory, the probability of accident is predicted, and the importance degrees of basic events which may lead to top event occur is judged. Finally, a quantitative FTA model for the gas poison is established to compute the probability of top event and identify the most dangerous path which may lead to the accident, the results of analysis provide references to the managers when they develop validity measures.

Abstract 3124: The Magnitude of Reclassification Indices for Individual Predictors of Global Cardiovascular Risk

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Nancy R Cook ◽  
Paul M Ridker
Keyword(s):  
Risk Factors ◽  
Cardiovascular Risk ◽  
Goodness Of Fit ◽  
Absolute Risk ◽  
Health Study ◽  
Intermediate Risk ◽  
Goodness Of Fit Test ◽  
Parental History ◽  
Net Reclassification Improvement ◽  
Predicted Risk

Methods based on risk stratification have recently been proposed to evaluate and compare predictive risk models, but their performance in clinically relevant populations has not been demonstrated, including for well-known cardiovascular risk predictors. We fit models including traditional risk factors as well as high-sensitivity C-reactive protein (hsCRP) and parental history of myocardial infarction in prospective data from 24,558 women in the Women’s Health Study who experienced 766 cardiovascular events over an average 10-year follow-up. Fit of models with and without each risk factor was evaluated using both traditional methods, including the C index and goodness-of-fit test, and newly proposed methods for reclassification, which compare predicted risk strata for two models. Reclassification calibration compares observed to predicted risk for each model within reclassified risk strata; the net reclassification improvement (NRI) estimates the net proportion of cases moving to higher vs. lower risk strata; the clinical NRI estimates the NRI among those at intermediate risk; and the integrated discrimination improvement (IDI) compares the mean difference in predicted probabilities between cases and controls for two models. For each model set, the reclassification calibration statistic showed a significant lack of fit in models excluding each of these predictors, indicating that the predicted risk did not fit that observed in reclassified strata. Values of the NRI were 20% for age, 8–11% for hemoglobin A1c in diabetics, smoking, and systolic blood pressure, and 3–5% for lipids, hsCRP, and parental history. The clinical NRI for those initially at intermediate risk was 46% for age and ranged from 9–29% for other risk factors. The IDI was less than 2% for all predictors, including age. These data demonstrate the magnitude of several newly proposed reclassification measures for well-known cardiovascular risk factors. These measures can demonstrate the potential of new models and markers to change risk strata and alter treatment decisions, and should be considered as another means to compare models and assess the accuracy of absolute risk estimates and risk strata.

scholarly journals Formal Safety Assessment of a Marine Seismic Survey Vessel Operation, Incorporating Risk Matrix and Fault Tree Analysis

2020 ◽  
Vol 19 (2) ◽  
pp. 155-172
Author(s):  
Gregory Asuelimen ◽  
Eduardo Blanco-Davis ◽  
Jin Wang ◽  
Zaili Yang ◽  
Dante Benjamin Matellini
Keyword(s):  
Risk Factors ◽  
Safety Assessment ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Seismic Survey ◽  
Risk Matrix ◽  
Tree Analysis ◽  
Formal Safety Assessment ◽  
Seismic Surveying ◽  
Marine Seismic

Abstract In maritime safety research, risk is assessed usually within the framework of formal safety assessment (FSA), which provides a formal and systematic methodology to improve the safety of lives, assets, and the environment. A bespoke application of FSA to mitigate accidents in marine seismic surveying is put forward in this paper, with the aim of improving the safety of seismic vessel operations, within the context of developing an economically viable strategy. The work herein takes a close look at the hazards in North Sea offshore seismic surveying, in order to identify critical risk factors, leading to marine seismic survey accidents. The risk factors leading to undesirable events are analysed both qualitatively and quantitatively. A risk matrix is introduced to screen the identified undesirable events. Further to the screening, Fault Tree Analysis (FTA) is presented to investigate and analyse the most critical risks of seismic survey operation, taking into account the lack of historical data. The obtained results show that man overboard (MOB) event is a major risk factor in marine seismic survey operation; lack of training on safe work practice, slippery deck as a result of rain, snow or water splash, sea state affecting human judgement, and poor communication are identified as the critical risk contributors to the MOB event. Consequently, the risk control options are focused on the critical risk contributors for decision-making. Lastly, suggestions for the introduction and development of the FSA methodology are highlighted for safer marine and offshore operations in general.

scholarly journals Instructional Software for Reliability Estimation and Fault Tree Analysis

2013 ◽  
Vol 1 (2) ◽  
pp. 83-109
Author(s):  
Rashpal Ahluwalia
Keyword(s):  
Goodness Of Fit ◽  
Engineering Students ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Software Tool ◽  
Reliability Estimation ◽  
Instructional Software ◽  
Tree Analysis ◽  
Failure Data ◽  
State Dependent

This paper describes a software tool to introduce fundamental concepts of reliability and fault tree analysis to engineering students.  Students can fit common failure distributions to failure data.  The data can be complete, singly censored, or multiply censored.  The software computes distribution and goodness-of-fit parameters.  The students can use the tool to validate hand calculations.  Failure distributions and reliability values for various components can be identified and stored in a database.  Various components and sub-systems can be used to build series- parallel or complex systems.  The components data can also be used to build fault trees.  The software tool can compute reliability of complex state independent and state dependent systems.  The tool can also be used to compute failure probability of the top node of a fault tree.  The software was implemented in Visual Basic with SQL as the database.  It operates on the Windows 7 platform.

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