Risk Analysis Tools Research Articles

Diagnosing atrial fibrillation early: the power of radiomics analysis on non-contrast cardiac CT

Abstract Background Often silent and asymptomatic, atrial fibrillation (AF) contributes significantly to morbidity and mortality. Early detection of AF could prevent and treat AF complications. Epicardial adipose tissue (EAT) is a unique fat tissue located on the surface of the myocardium that can be demonstrated on gated non-contrast cardiac CT (CCT). Radiomics, a method that translates medical images into quantitative data, can yield biological information and enable radiologic phenotypic profiling. Purpose This study aimed to identify radiomic features of both EAT and left atrium (LA)-EAT in patients with AF, based on non-contrast CCT, and utilize these features to construct a prediction model for the presence of AF. Methods We conducted a retrospective case control study of 180 patients who underwent cardiac CTA (CCTA) for clinical indications between 2018-2022 in Shaare Zedek Medical Center Jerusalem. The AF group contained 90 patients with known AF referred to CCTA prior to pulmonary vein isolation. The control group included 90 patients referred to CCTA for other indications, without a definite or suspected AF diagnosis. In all patients, the cardiac CT protocol included initial non-contrast CCT, which we used for radiomic analysis. The study dataset was trained on 60 patients from each group, with evaluation performed on a validation dataset of 30 patients each. Detection of the cardiac EAT was performed fully automatically using the cardiac risk analysis tool, SyngoVia, Research Frontier, Siemens Healthineers. Additional specific segmentation of the LA- EAT was performed semi-automatically using fixed anatomical landmarks. Radiomic analysis was performed via Radiomic tool, SyngoVia, Research Frontier, Siemens Healthineers. Results Both groups included in this research, study and control, had matching clinical characteristics such as age (average 63.2) , sex (female 50%), history of dyslipidemia, hypertension, diabetes, and smoking. A univariant statistical analysis for detection of AF of 1691 radiomic features in LA-EAT found an AUC of 0.866, p<<0.001 and 0.804, p<<0.001 for morphological and texture features, respectively. In a multivariate regression analysis, combining the top two radiomic features increased the AUC to 0.89, p = 0.004. Evaluation of linear regression and random forest model applications on a new validation cohort of 60 patients verified the results with AUC curves of 0.88 and 0.87 respectively. Compared to LA-EAT, applying total EAT prediction model on a new validation cohort produced inferior results, with AUC curves of 0.79 and 0.8 for linear regression and random forest model applications, respectively. Conclusion This proof-of-concept study demonstrated that radiomic features of LA-EAT are associated with and predictive of AF. Models based on radiomic features from gated non-contrast CCT of LA-EAT identified the presence of AF with excellent diagnostic performance. Models based on total EAT produced inferior results.Figure 1Heatmap of radiomic featuresFigure 2ROC curves

Failure mode and effects analysis using an improved pignistic probability transformation function and grey relational projection method

Failure mode and effects analysis (FMEA) is an important risk analysis tool that has been widely used in diverse areas to manage risk factors. However, how to manage the uncertainty in FMEA assessments is still an open issue. In this paper, a novel FMEA model based on the improved pignistic probability transformation function in Dempster–Shafer evidence theory (DST) and grey relational projection method (GRPM) is proposed to improve the accuracy and reliability in risk analysis with FMEA. The basic probability assignment (BPA) function in DST is used to model the assessments of experts with respect to each risk factor. Dempster’s rule of combination is adopted for fusion of assessment information from different experts. The improved pignistic probability function is proposed and used to transform the fusion result of BPA into probability function for getting more accurate decision-making result in risk analysis with FMEA. GRPM is adopted to determine the risk priority order of all the failure modes to overcome the shortcoming in traditional risk priority number in FMEA. Applications in aircraft turbine rotor blades and steel production process are presented to show the rationality and generality of the proposed method.

Risk in transit: a case study of the introduction of a new risk definition for risk management in the Norwegian petroleum industry

In 2015, a new risk definition was presented by the Norwegian Petroleum Safety Authority (PSA-N) as a petroleum regulation update and ‘rolled out’ in the PSA-N organisation and the oil and gas industry as a regulatory guideline, changing the definition of risk from ‘the combination of probabilities and consequences’ to ‘the consequences of an activity, with associated uncertainties’. This article reports on research that explores the industrial effects of this change. We have conducted qualitative interviews with both operator employees and consultants, and we have undertaken a qualitative cross-sectional analysis, where we explored how the implementation of the new risk definition is experienced by different actors in the industry. The analysis draws on translation perspectives from institutional theory and focuses on the developments of theory and practice influenced by the interaction between the industry and consultancies, academia and the regulator. We find that the new risk definition has had some practical influence on risk management, particularly exemplified through a generally raised awareness about uncertainty, in addition to some direct effects on risk analysis tools. The study also demonstrates pros et cons with a functional regulatory regime. On one hand it gives the companies significant leeway for them to tailor their treatment and evaluation of uncertainty to the context. On the other hand, with different understandings of uncertainty among the companies, it is more challenging for the regulator to perform audits in a structured manner. Furthermore, the study sheds light on different power aspects that are at play, influencing the interplay between standardised definitions, legislative instruments, practice, experience, and expertise.

Enhanced EPIRISK tool for rapid epidemic risk analysis

ObjectivesThis study aims to create an enhanced EPIRISK tool in order to correctly predict COVID-19 severity in various countries. The original EPIRISK tool was developed in 2018 to predict the epidemic risk and prioritise response. The tool was validated against nine historical outbreaks prior to 2020. However, it rated many high-income countries that had poor performance during the COVID-19 pandemic as having lower epidemic risk. Study designThis study was designed to modify EPIRISK by reparameterizing risk factors and validate the enhanced tool against different outbreaks, including COVID-19. MethodsWe identified three factors that could be indicators of poor performance witnessed in some high-income countries: leadership, culture and universal health coverage. By adding these parameters to EPIRISK, we created a series of models for the calibration and validation. These were tested against non-COVID outbreaks in nine countries and COVID-19 outbreaks in seven countries to identify the best-fit model. The COVID-19 severity was determined by the global incidence and mortality, which were equally divided into four levels. ResultsThe enhanced EPIRISK tool has 17 parameters, including seven disease-related and 10 country-related factors, with an algorithm developed for risk level classification. It correctly predicted the risk levels of COVID-19 for all seven countries and all nine historical outbreaks. ConclusionsThe enhanced EPIRSIK is a multifactorial tool that can be widely used in global infectious disease outbreaks for rapid epidemic risk analysis, assisting first responders, government and public health professionals with early epidemic preparedness and prioritising response to infectious disease outbreaks.

Risk analysis in conformity assessment of positive displacement flowmeter

Volume measurement of manufactured liquids and liquid raw materials carried out by road tankers (RT) is usual and has economic relevance, justifying the need to ensure metrological reliability. It requires some actions, including choosing suitable standards. In this scenario and considering the practice for type evaluation of measuring instruments, the article proposes a case study, analyzing performance data from a positive displacement meter, a measurement principle widely used as a standard in RT verifications. Current criteria of legal metrology were used: for the 0.3 accuracy class, the maximum permissible error (MPE) is 0.2%. The meter was tested with three different fluids (with different viscosities), and measurement errors were contrasted with the MPE specification, being considered compliant in all situations. On the other hand, risk analysis tools for conformity assessment were incorporated (JCGM 106) based on the different consumer risks, the formulated decision rule, and the measurement uncertainty. Even though, when including the risk analysis, the flowmeter was considered non-compliant, showing the need for a better basis decision using measurement uncertainty in legal metrology actions.

Remote sensing as a tool for natural disaster risk analysis: a bibliometric review

Introduction: remote sensing as a tool is a fundamental resource that helps to develop various applications for disaster risk management.Objective: to conduct a bibliometric analysis of remote sensing as a tool for natural disaster risk analysis in Scopus between 2003 and 2023.Methods: this was a bibliometric analysis that defined the metrics of scientific production. The indicators were obtained from 409 documents chosen from the Scopus database using keywords in English (Remote sensing, natural disaster).Results: the data revealed a significant increase in the number of papers published on the topic (59,9 %) between 2019 and 2023. In addition, China (22,5 %; n=133) recorded the highest rate of scientific output, with the Chinese Academy of Sciences publishing the most (n=36). The journal Remote Sensing published 30 papers, while Natural Hazards received 720 citations, the most referenced author being Pradhan, B. (n=11 papers; 1587 citations).Conclusions: studies on this topic have increased in number, subject variation and author cooperation, as remote sensing allows data to be collected from inaccessible or hazardous regions, enabling real-time monitoring and tracking of natural phenomena.

Probabilistic-based seismic fragility assessment of earthquake-induced site liquefaction

As a very complex and uncertain problem, seismic liquefaction is affected by many factors, such as earthquake intensity, site conditions, soil properties, etc. During the past half a century, the state-of-the-art in analysis and evaluation of earthquake-induced soil liquefaction and its consequences as well as the state-of-the-practice in improving seismic stability to resist liquefaction have been made much progress. However, the fragility analysis and assessment for seismic liquefaction of sites have not been paid enough attention to. In this paper, the concept of seismic liquefaction fragility for building sites is proposed. The soil resistance to liquefaction and liquefaction possibility are expressed as a fragility function of ground motion intensity, which can be used to describe minor, moderate and severe liquefaction potential under different ground motion intensity. Combined with the existing research results of seismic liquefaction evaluation, the analysis method of liquefaction fragility is given. Taking a specific site as an example for liquefaction fragility analysis, it is found that taking the calculated exceedance probability of different liquefaction levels as the observation value, the liquefaction fragility function follows both lognormal distribution and log-logistic distribution. With the increase of liquefaction level, the median value of liquefaction fragility function increases, while the site liquefaction fragility curve moves to the right, which shows that the ability of the site to resist more severe liquefaction is increasing. When convolved with the analysis results of liquefaction triggering and hazard, the liquefaction fragility function can be a much efficient tool for seismic liquefaction risk analysis of specific sites.

Development of hamming and hausdorff distance metrics for cubic intuitionistic fuzzy hypersoft set in cement storage quality control: Development and evaluation.

Quality control is paramount in product manufacturing as it ensures consistent production to meet customer expectations, regulatory requirements and maintain a company's reputation and profitability. Distance measures within fuzzy sets serve as powerful tools for quality control, allowing for data comparison and identification of potential defects or outliers within a system. This study aims to develop a hybrid concept by combining a Cubic Intuitionistic Fuzzy Set (CIFS) with Soft Set (SS) and extending it to Cubic Intuitionistic Fuzzy Hypersoft Set (CIFHSS). CIFHSS enables handling multiple distinct attributes at the sub-attribute level within a cubic set environment. The concept includes operations like internal, partial internal, external, complement, direct sum, and product. Additionally, six distance metrics are defined within CIFHSS and applied to establish a quality control management system for industrial applications. The versatility of CIFHSS in quality control management stems from its ability to capture and model uncertainty, vagueness, and imprecision in data. This makes it an effective tool for decision-making, risk analysis, and process optimization across a wide range of industrial applications.

Application of quantitative risk analysis to fireproofing

AbstractOne of the core elements of fire protection for petrochemical processing plants is the consideration of passive fire protection (PFP). This general category, often referred to as fireproofing, is addressed in the American Petroleum Institute (API)‐recommended practice (RP) 2218. This RP provides guidelines for the selection and application of fireproofing with what is mostly a qualitative risk assessment approach. The logic focuses on predicting pool fires based on rough characterizations of system properties combined with equipment layout. Although pool fire impacts are often localized, jet fires can affect larger areas. API RP 2218 addresses jet fires in an appendix because of their unpredictable nature, leaving pool fire exposures as the default basis for structural fireproofing. To properly account for both fire types, fire exposure can be evaluated with quantitative risk analysis (QRA) tools that incorporate both jet and pool fire impacts for a wide variety of accident scenarios, weather conditions, and release orientations. By evaluating the thermal radiation impacts of fires in relation to the vulnerability of steel structural elements, a QRA‐based approach to placement of PFP can be achieved. This approach has the benefit of applying PFP where it is needed the most, to best protect a company's infrastructure.

Risk Assessment of Industrial Waste: Case of an Algerian Company

More than 300,000 tons of industrial hazardous wastes are produced every year in Algeria. Industrial waste can cause harm to people or the environment. The study highlights the problem of a very important step of the industrial waste management which is the storage. The Algerian regulation does not specify the storage mode of the different industrial wastes. This can cause very dangerous accidents such as fires and explosions. The main research technique is modeling according to a risk analysis tool. Using our assessment method (Preliminary Hazard Analysis), various risk factors can be classified according to their contribution to environmental and human health risks. The goal of this study was to study the risks associated with storing industrial waste and to assist businesses in improving their waste management practices for the purpose of sustainable development. The initial analysis of dangers and the Risk Assessment Matrix show that hazardous wastes like used batteries, used oils, and Askarel transformers can cause serious harm to the environment and humans if not handled safely. They can make the air, water, and soil dirty, and they can also contaminate the fauna and flora.

Methodology for Analyzing Coupling Mechanisms in RFI Problems Based on PEEC

In this article, a method for analyzing coupling mechanisms in radio frequency interference (RFI) problems is proposed. The partial element equivalent circuit (PEEC) method is first used to derive the retarded inductances and capacitances between different mesh cells. With the introduction of a novel partitioning algorithm, the capacitive coupling and inductive coupling between arbitrary layout parts can be quantified based on the magnitude of the displacement current and induced voltage drop. The accuracy of the PEEC models is validated by comparison with different commercial tools. The proposed coupling mechanism analysis flow provides a useful prelayout tool for RFI risk analysis.

An operational risk awareness tool for small fishing vessels operating in harsh environment

Probabilistic safety assessment using the Bayesian network (BN) has emerged as a popular method for developing risk analysis tools. The method allows for risk-influencing factors from several areas to be captured probabilistically, enabling an easy-to-use safety assessment tool to be developed. Meanwhile, because the resulting tool is a BN model, the use of subject-matter experts in eliciting probabilities for the conditional probability tables (CPT) makes the method subjective. The subjectivity makes the tool's output result less reliable since different experts rarely produce the same probabilities for CPTs. Therefore, the present study proposed a probability-scoring scale that uses pre-determined scores to assign probabilities to CPTs. Using the scale ensures that different experts working on a common CPT produce identical probabilities. That way, the variability among experts’ results is minimised while the reliability of a BN's output result increases. The scale was applied to a BN-based risk-awareness (RAw) tool developed for monitoring safety aboard small fishing vessels (SFV). Advanced safety monitoring equipment is lacking aboard many SFVs, especially those in developing countries. Hence, the RAw tool developed in the present study demonstrates how the probabilistic safety assessment method could be leveraged to equip SFVs with safety monitoring tools. The study will benefit SFV owners and operators, the commercial fishing industry, and maritime administrations in charge of ensuring safety aboard SFVs.

A New Clinical Tool for Scoliosis Risk Analysis: Scoliosis Tele-Screening Test.

Methodological, observational clinical study. This study aimed to develop a virtual screening test to detect scoliosis risk initially by parents without the need for medical visit during the coronavirus disease 2019 pandemic. The scoliosis screening program has been implemented to early detect scoliosis. Unfortunately, access to health professionals was limited during the pandemic. However, during this time, interest in telemedicine has increased remarkably. Recently, mobile applications related to postural analysis were developed, but none permits evaluation by parents. Researchers developed the Scoliosis Tele-Screening Test (STS-Test), which included drawing-based images of body asymmetries, to assess the scoliosis-associated risk factors. The STS-Test was shared on social networks, allowing the parents to evaluate their children. After test completion, the risk score was generated automatically, and children with medium and high risks were then advised for medical consultation for further evaluation. The test accuracy and consistency between the clinician and parents were also analyzed. Of the 865 tested children, 358 (41.4%) consulted clinicians to confirm their STS-Test results. Scoliosis was then confirmed in 91 children (25.4%). The parents were able to detect asymmetry in 50% of the lumbar/thoracolumbar curvatures and 82% of the thoracic curvatures. In addition, the forward bend test revealed favorable agreement between parents and clinicians (r =0.809, p<0.0005). Internal consistency of the esthetic deformities domain in the STS-Test was also excellent (α=0.901). This tool was 94.97% accurate, 83.51% sensitive, and 98.87% specific. The STS-Test is a new parent-friendly, virtual, cost-effective, result-oriented, and reliable tool for scoliosis screening. It allows parents to actively participate in the early detection of scoliosis by screening their children for the risk of scoliosis periodically without the need to visit the health institution.

Use of Risk Analysis Tools in Investment Construction Project Cost Management

The paper examines the possibilities of improving the accuracy of estimating the value of an investment and construction project based on various analysis and evaluation tools. Accurate estimates can be achieved using the Project Value Model at all stages of the project lifecycle. The stages of estimating the cost of an investment and construction project are considered, including costing, i.e. determining the costs of individual works depending on the calculation of the volume of work and pricing — determining the total cost of the project taking into account cost, profit and contingency provisions. The work carried out a comparative analysis of the methods of estimating the cost of the project: methods of high-level assessment, analog and method of parametric estimates, detailed assessment of the project costs, the use of which should be carried out iteratively. It is noted that risk management tools should be considered in combination with the project cost assessment due to the dependence of the goal in identifying and assessing risks with maximum performance and lowest cost. The article studied various approaches to assessment, in particular: estimating the cost of the project at the pre-investment stage in the form of a rough (approximate) value; estimate the project cost at the business planning stage as the estimated value of the cost justification Project Cost Estimation in the Process of Costing by Activity Type — Budget Cost Assessment Estimate the final planned project cost to be included in the project budget — accurately estimate the project cost. The article proposes the use of various tools and methods of risk analysis at the stages of the life cycle of an investment and construction project.

Development of a seismic loss prediction model for residential buildings using machine learning – Ōtautahi / Christchurch, New Zealand

Abstract. This paper presents a new framework for the seismic loss prediction of residential buildings in Ōtautahi / Christchurch, New Zealand. It employs data science techniques, geospatial tools, and machine learning (ML) trained on insurance claims data from the Earthquake Commission (EQC) collected following the 2010–2011 Canterbury earthquake sequence (CES). The seismic loss prediction obtained from the ML model is shown to outperform the output from existing risk analysis tools for New Zealand for each of the main earthquakes of the CES. In addition to the prediction capabilities, the ML model delivered useful insights into the most important features contributing to losses during the CES. ML correctly highlighted that liquefaction significantly influenced building losses for the 22 February 2011 earthquake. The results are consistent with observations, engineering knowledge, and previous studies, confirming the potential of data science and ML in the analysis of insurance claims data and the development of seismic loss prediction models using empirical loss data.

A conflict elimination-based model for failure mode and effect analysis: A case application in medical waste management system

As a recognized and powerful risk analysis tool, failure mode and effects analysis (FMEA) has proven its effectiveness in medical waste management, which has profound significance to human health and ecological environment. However, existing FMEA studies pay little attention to the heterogeneity of team members (TMs) and their trust relationship, potentially leading to inappropriate results. Therefore, this paper constructs a FMEA model with internal and external TMs for medical waste management system, which focuses on the conflict elimination under social network to circumvent TMs’ negative behaviors and improve team harmony, thereby enhancing the reliability of FMEA. Firstly, to increase the flexibility and accuracy of information expression and synthesis, probabilistic linguistic term sets (PLTSs) and Dempster-Shafer evidence theory (D-S theory) are employed to provide and process evaluations of failure modes (FMs). Secondly, an objective trust prediction method based on bounded confidence is proposed for building a credible social network. Thirdly, a conflict elimination mechanism is devised to improve team cohesion, in which TM weights are dynamically determined. Afterwards, an integrated DEMATEL-TODIM decision framework is proposed to prioritize FMs. An application and related analysis prove that the proposed model can effectively improve the social relationship of TMs and obtain a reliable ranking of FMs on the basis of discriminating FMs’ causality while considering TMs’ bounded rationality.

Application of fuzzy DEMATEL approach in maritime transportation: A risk analysis of anchor loss

Vessels are exposed to various operational risks throughout their service life. Anchor loss, which is one of the operational risks, may lead to grounding, collision and even total loss of vessel afterwards. Accidents due to loss of anchor may lead to serious consequences such as pollution, injury, loss of life and property. Therefore, it is very important to minimize the risk of anchor loss. In this study, a comprehensive literature review including accident and incident reports, technical reports and expert views was conducted to determine the factors that may cause anchor loss of ships. In order to analyze and define the cause-effect relationship between the determined factors, combination of the fuzzy logic and the DEMATEL (Decision Making Trial and Evaluation Laboratory) method was used. The aim of this study is to mitigate the risk of anchor loss by developing an alternative risk analysis tool. Environmental factors at anchorage area, training and competency of crew, the number of shackles paid out, anchoring method and selection of anchor are identified as the most critical factors for anchor loss. According to the results, a risk analysis model based on cause-effect relationship between the factors has been presented for the shareholders in maritime industry.

A qualitative approach for a situation analysis of AMR risks in the food animal production sector.

In response to the need to manage Antimicrobial Resistance (AMR), countries have produced National Action Plans (NAPs), which require detailed information of the AMR situation in all sectors. Considering the limited information that is publicly available for an analysis of the AMR situation in animal production, the FAO Regional Office for Latin America and the Caribbean (FAO RLC) developed the "FAO tool for a situation analysis of AMR risks in the food and agriculture sectors." The objective of this paper is to present the methodology developed for a qualitative evaluation of the risk factors of AMR toward animal and human health, based on terrestrial and aquatic production systems and their associated national public and private mitigation measures. The tool was developed reflecting the AMR epidemiological model and the guidelines to conduct a risk analysis of AMR from the Codex Alimentarius and WOAH. Applied in four stages of progressive development, the objective of the tool is to provide a qualitative and systematic assessment of the risks of AMR from animal production systems, to animal and human health, and to identify gaps in cross cutting factors in AMR management. The tool consists of three instruments: (i) a survey to collect data for a situation analysis of AMR risks; (ii) a methodological procedure for the analysis of the information obtained; (iii) instructions for the preparation of a national roadmap for the containment of AMR at a national level. Based on the results from the information analysis, a roadmap is prepared by guiding and prioritizing the needs and sectoral actions for the containment of AMR under an intersectoral, multidisciplinary and collaborative approach, and according to country priorities and resources. The tool helps to determine, visualize and prioritize the risk factors and challenges that contribute to AMR from the animal production sector and that need to be addressed to manage AMR.

Risk Matrix as a Tool for Risk Analysis for Work-Related Hazard in Offshore Installation in the Oil and Gas Industry

This study aims to investigate the likelihood of hazard occurrence, the frequency level, the level of severity, and the consequences of work-related hazards in Offshore Installations. This study was a cross-sectional design assessment and the instrument used for this study was a well-structured questionnaire on Analysis of Work-related Accidents which was sent to e-mails of oil and gas workers. The reliability of the instrument was assessed using Cronbach's alpha. Data analyses were carried out using descriptive statistics, Risk Matrix, and Fault tree analysis. The 4 by 4 risk assessment matrix for the likelihood and consequences showed that 12 of the hazard were categorized as having high risk and Wind/Strong current was classified as extreme risk, However, 5 of the identified hazards, H5, H6, H7, H8 &amp; H10 are risks that can be easily controlled to prevent an incident from occurring. All the offshore risks identified were either rated as high or extreme, which indicated that offshore hazards have severe consequences for the People, Environment, Asset and Reputation of the company. Therefore, high safety measures must be put in place to control these risks.

Risk-Averse Stochastic Programming for Planning Hybrid Electrical Energy Systems: A Brazilian Case

This work presents a risk-averse stochastic programming model for the optimal planning of hybrid electrical energy systems (HEES), considering the regulatory policy applied to distribution systems in Brazil. Uncertainties associated with variables related to photovoltaic (PV) generation, load demand, fuel price for diesel generation and electricity tariff are considered, through the definition of scenarios. The conditional value-at-risk (CVaR) metric is used in the optimization problem to consider the consumer’s risk propensity. The model determines the number and type of PV panels, diesel generation, and battery storage capacities, in which the objective is to minimize investment and operating costs over the planning horizon. Case studies involving a large commercial consumer are carried out to evaluate the proposed model. Results showed that under normal conditions only the PV system is viable. The PV/diesel system tends to be viable in adverse hydrological conditions for risk-averse consumers. Under this condition, the PV/battery system is viable for a reduction of 87% in the battery investment cost. An important conclusion is that the risk analysis tool is essential to assist consumers in the decision-making process of investing in HEES.