Risk Evaluation Method Research Articles

Mortality risk evaluation methods for total dissolved gas supersaturation to fish based on a mitigation measure of utilizing activated carbon

The proper water chemical composition of aquaculture water is very important for fish farming in reservoirs or fish multiplication stations. Gas bubble disease (GBD) is mainly caused by total dissolved gas supersaturation (TDGS) in water and is a common problem that affects the healthy growth of fish. Extensive measures have been taken to mitigate TDGS levels in water where fish live, while methods for quantitatively evaluating the mitigation effect of the proposed measures on fish exposed to TDGS are still lacking. In this paper, an activated carbon (AC) adsorption experiment for supersaturated total dissolved gas (TDG) dissipation was conducted, and the experimental results indicated that AC addition could effectively accelerate supersaturated TDG dissipation. Based on fish tolerance experiments conducted by Huang (2010), two models, including a mortality risk degree evaluation model and a mortality rate calculation model, were developed to quantitatively evaluate the mortality risk mitigation effect of AC addiction on fish exposed to unsteady TDGS levels. Application of the results of the mortality risk degree evaluation model has shown that AC addition can help alleviate the mortality risk of fish suffering from TDGS. Application of the results of the mortality rate calculation model has also demonstrated that the final mortality rate of the fish group in the case with AC addition was lower than that of the case without added AC, and the final mortality rate decreased as the specific surface area and dosage of AC increased. Furthermore, an equation that related the required AC mass and a given harvested fish mass was established. This paper provides a reference for evaluating the effects of various mitigation measures to alleviate the risk posed to fish by TDGS.

Risk Priority Evaluation for Power Transformer Parts Based on Intuitionistic Fuzzy Preference Selection Index Method

The risk assessment of power transformer equipment can not only improve the safety and management level of transformer operation, but also reduce the operation and maintenance costs of the equipment on the basis of ensuring the overall reliable operation of the power system. As a result, it can enhance the rewards of assets investment. The quantitative analysis of power equipment risk often contains qualitative indicators that are difficult to quantify. These indicators have the characteristics of fuzziness. In order to improve the accuracy and reliability of risk assessment results, this paper proposed a new risk evaluation method based on intuitionistic fuzzy set. Firstly, language variables are transformed into corresponding intuitionistic fuzzy numbers. Secondly, a novel entropy of intuitionistic fuzzy set is established. Thirdly, a weighting method for determining each expert’s importance is proposed based on the new propose entropy. Furthermore, an extended preference selection index is put forward under intuitionistic fuzzy environment. Finally, an example of the risk assessment of power transformer components is discussed to illustrate the effectiveness of the new risk evaluation method.

Study on Multi-Indicator Quantitative Risk Evaluation Methods for Different Periods of Coal Spontaneous Combustion in Coal Mines

ABSTRACT For the current coal spontaneous combustion fire risk evaluation method has the problems of single evaluation dimension, incomplete evaluation index and unreliable evaluation results. However, the coal spontaneous combustion fire risk evaluation can effectively guide coal mine fire prevention and control. Therefore, a multi-indicator quantitative risk evaluation method combining analytic hierarchy process (AHP) and linear interpolation for different periods of coal spontaneous combustion is proposed as a way to improve the rationality of coal spontaneous combustion fire risk evaluation. The continuous segmental evaluation model was established based on the factors that influence the three periods of coal spontaneous combustion (Latent Period, Self-heating Period and Combustion Period). The latent period evaluation model was established based on the fire-prone nature of coal, coal seam occurrence, mining technology, and fire prevention measures. The self-heating period evaluation model was established based on the degree of self-heating of coal, absolute CO generation, and Graham index. The combustion period, there was already a spontaneous combustion fire, directly set the fire risk score to 0. The score could fully reflect the level of coal spontaneous combustion fire risk. The higher the score, the relatively smaller the risk of coal spontaneous combustion, and vice versa, the relatively larger. According to this risk evaluation model, the risk of coal spontaneous combustion in the 2−2 coal seam of a coal mine in Shaanxi Province was evaluated. The result shows that the level of coal spontaneous combustion risk of 2−2 coal seam in this coal mine is in a safer state, and this result is consistent with the actual situation. The multi-indicator quantitative evaluation of different periods of coal spontaneous combustion effectively improves the accuracy of fire risk evaluation. Therefore, the evaluation model has certain theoretical guidance for the control of coal spontaneous combustion risk in coal mines.

Applying risk matrices for assessing the risk of psychosocial hazards at work.

Although wide-ranging amendments in health and safety regulations at the European and national level oblige employers to conduct psychosocial risk assessment, it is still under debate how psychosocial hazards can be properly evaluated. For psychosocial hazards, an epidemiological, risk-oriented understanding similar to physical hazards is still missing, why most existing approaches for hazard evaluation insufficiently conceive psychosocial risk as a combination of the probability of a hazard and the severity of its consequences (harm), as found in traditional risk matrix approaches (RMA). We aim to contribute to a methodological advancement in psychosocial risk assessment by adapting the RMA from physical onto psychosocial hazards. First, we compare and rate already existing procedures of psychosocial risk evaluation regarding their ability to reliably assess and prioritize risk. Second, we construct a theoretical framework that allows the risk matrix for assessing psychosocial risk. This is done by developing different categories of harm based on psychological theories of healthy work design and classifying hazards through statistical procedures. Taking methodological and theoretical considerations into account, we propose a 3 × 3 risk matrix that scales probability and severity for psychosocial risk assessment. Odds ratios between hazards and harm can be used to statistically assess psychosocial risks. This allows for both risk evaluation and prioritizing to further conduct risk-mitigation. Our contribution advances the RMA as a framework that allows for assessing the relation between psychosocial hazards and harm disregarding which theory of work stress is applied or which tool is used for hazard identification. By this, we also contribute to further possible developments in empirical research regarding how to assess the risk of workplace stress. The risk matrix can help to understand how psychosocial hazards can be evaluated and organizations can use the approach as a guidance to establish a suitable method for psychosocial risk evaluation.

Risk evaluation of energy investment projects along the Belt and Road based on cloud model and evidence theory

China's major energy projects along the Belt and Road are characterized by large-scale capital investment, long construction cycles, and complex investment environments, making it more difficult to assess project investment risks. Based on the PESTEL theory, a risk evaluation index system is constructed for energy enterprises' investment projects along the Belt and Road. In view of the uncertainty of energy investment projects, a risk evaluation method combining a cloud model and an evidence theory is proposed. To examine the developed index system and risk evaluation method, an overseas hydropower investment project is chosen and the risk factors are analyzed. The results suggest that the risk level of the enterprise's project is highest, the political and environmental risks are both high, the economic and project risks are both at average level, and the energy risk is relatively low, which verifies the effectiveness of this information fusion method. The method can be used to solve the problem of linguistic ambiguity and uncertainty in multi-attribute decision problems and is applicable to similar investment projects, thus providing a new technical path to assess the investment risks of energy enterprises along the Belt and Road.

Protection challenges in seat positions with large rearward adjustment in frontal collisions: An approach using stochastic human body model simulations

Novel seat positions enabled by self-driving cars have been investigated in various studies in recent years. However, there is little research on the effect of increased rearward seat adjustments. To predict challenges associated with the possibility to move the seat further backwards in the car than currently possible as driver, appropriate methods have to be defined. A detailed human body model, a THUMS v4.1 in particular, tissue-based injury risk evaluation methods, a generic vehicle interior and a Latin hypercube design of experiments taking the variability of real-world crashes into account was established. In a first step, 200 simulations at current representative seat positions and a driving occupant posture were performed. The results were then compared to field data from an accident database to evaluate the accuracy of the method. The predictions exceeded the injury risks for the abdomen, head, and upper extremities, while underestimating the risk for thoracic and lower extremity injuries. A good match was observed for injuries of the neck and spine. In a second step, the 200 simulations were run again, but with the seat adjusted rearwards significantly. In this seat configuration, with the exception of the head and the upper extremities, increased injury risks were predicted for all body regions. The highest increases affected the lower extremities (+28%)—predominantly pelvic fractures—and the neck (+9%). In addition, (partial) submarining occurred in almost 50% of cases with the rearward adjusted seat—as opposed to none in the conventional seat position. The established method could be used in future studies to design safety measures addressing these identified potential safety risks.

The probabilistic linguistic term sets based ORESTE method for risk evaluation in Fine-Kinney model with interactive risk factors

The Fine-Kinney model is a quantitative and effective method to identify and evaluate potential risks. The Fine-Kinney method has been widely used in practice, while the traditional Fine-Kinney method is difficult to access risk parameters precisely in practice. Besides, the current Fine-Kinney method fails to take into account the fact that decision makers are interrelated in practice. Further, the detailed relationships among the potential hazards cannot be reflected in the conventional Fine-Kinney method during the risk priority process, especially in the case of uncertain information. To compensate these deficiencies, this paper proposes an extended Fine-Kinney framework by integrating ORESTE (organísation, rangement et Syn-thèse de données relarionnelles) (in French), Choquet integral, and Probabilistic Linguistic Term Sets (PLTSs). Firstly, the PLTSs are utilized to express the decision makers’ complex risk preference information. Then, the Choquet integral is used to integrate risk evaluation information, which can simulate the potential interaction relationships among individual risk evaluation of decision-makers. Next, an extended ORESTE based on the PLTSs method is used to obtain the priorities of potential hazards, in which distance measure of PLTSs is applied to replace Besson’s ranks. Moreover, the PIR (preference, indifference, and incomparability) structure is constructed to describe the detailed relationships between potential hazards. Finally, an illustrative example is described to illustrate the proposed risk evaluation method. After that, the rationality and efficiency of the proposed method are tested through the comparison with other similar methods.

Juvenile Offenders in Community Corrections: A Systemic Look at Risk Evaluation Methods to Implement UN Resolutions under the Chinese Legal System

Juvenile Offenders in Community Corrections: A Systemic Look at Risk Evaluation Methods to Implement UN Resolutions under the Chinese Legal System

Financial risk evaluation method of blockchain digital currency based on CART algorithm

In order to overcome the problems existing in traditional financial risk evaluation methods, such as high generalization error and fitting degree with actual value, this paper designs a financial risk evaluation method of blockchain digital currency based on CART algorithm. After screening and ranking the financial risk indicators of blockchain digital currency, the financial risk level of blockchain digital currency is determined by combining CART algorithm. Finally, by calculating the covariance matrix of the financial risk decision matrix, the positive ideal solution and the negative ideal solution of the financial risk are found, and then the final evaluation result is obtained by combining the progress of the financial risk. Experimental results show that the minimum generalization error of this method is only 0.021, the fitting degree of the obtained results and the actual risk can reach 98.0%, and the maximum risk accuracy can reach 0.978.

Study on Intelligently Designed Business Innovation Service Models Driven by Big Data

Although conventional business models have been increasingly affected in front of the big data technology application, it has also brought new opportunities and challenges for enterprise development. In order to create a higher value, enterprises should keep pace with the times and actively develop business innovation service models. The greatest value brought by data is to help enterprises find potential business value. It can provide a broader user market and channels, avoid homogeneous competition, and realize the integration of upstream and downstream value chains. In addition, it abandons the extensive development under the traditional model and allows enterprises to return to real value services, which is also an irresistible trend of business model transformation. This paper studies and analyzes business innovation service models. First, the business model as required is presented, and the management system and risk evaluation method are introduced. Then, the construction of the business service model is discussed, and the typical big data technologies are reviewed. Next, according to the evaluation theory of business model, the index system of business innovation service model is explored, which can examine the development of business model objectively and comprehensively. Last, the operations of the business model under the big data are analyzed. The research on the business model in this paper can be provided with universality and has a certain practical value for the development of business innovation service.

A Risk Evaluation Method of Coastal Oil Depots for Heavy Rainfall Vulnerability Assessment

Oil depots in the coastal areas of China are prone to disasters caused by heavy rain due to the monsoon climate. Studies focusing on heavy rainfall vulnerability in coastal oil depots are limited. Therefore, we evaluated the safety of oil depots based on four factors in this study: personnel, equipment and facility, environment, and resilience. Complex networks, analytic hierarchy processes, and information entropy theory were used to establish an evaluation index system including four first-level indicators, nine second-level indicators, and 40 third-level indicators. Scores of 40 evaluation indicators were taken as the input, a vulnerability level of oil depots affected by heavy rain was gained as the output, and results were presented visually (different warning levels distinguished by color) to help oil depot enterprises improve their safety performance under extreme weather conditions.

A New Method for Piping Risk Evaluation on Unconfined Aquifers under Dewatering of Deep Foundation Pits

This paper presents a new method to evaluate the piping risk of unconfined sandy cobble aquifers during the dewatering of deep foundation pits. Firstly, the possibility of piping is judged according to the particle size distribution and pore diameter of the sandy cobble stratum. Secondly, the critical hydraulic gradients of particles with different sizes are calculated according to the pipe flow model. Thirdly, the hydraulic gradient around the foundation pit during the dewatering process is calculated by numerical method. Then, combined with the distribution of hydraulic gradient around the foundation pit and the critical hydraulic gradients of particles with different sizes, the range of moveable particles with different sizes in the surrounding stratum is evaluated. Finally, according to the sandy cobble aquifers conditions and the influence of particle movement on the stratum, the level of piping risk is determined. This method was successfully applied to evaluate the piping risk of Tawan Station in Luoyang Metro Line No.1, and according to the risk evaluation the pensile curtain was recommended for the retaining structure in this case. From the satisfied applications, this method is a reference for the evaluation of piping risk and selection of retaining structure when considering the impact of the dewatering in deep foundation pit with unconfined aquifers on the surrounding stratum.

Risk Assessment Methods of Low Back Pain among Masonry Apprentice

Work-related musculoskeletal disorders (WMSDs) are primary cause of non-fatal injuries in construction. They involve instant or persistent stress on a worker's body (muscles, tendons, ligaments, bones) that may affect a worker's ability to perform his work or even cause chronic disability. This review helps the construction sectors in better understanding the intensity of WMSDs and the risks associated with them. This paper provides a layout for research community with a comprehensive overview of existing technique, their drawbacks, and the need for more study in order to achieve automated evaluations on construction sites. Despite the fact that assessing vulnerability to WMsSD risk factors has proven to be possible in order to reduce the rate of this injury, the area remains undeveloped due to a lack of awareness among professionals about the facilitating techniques, as well as their efficiency and limitations. This paper examines the current WMSD risk evaluation methods and outlines their convenience and disadvantages. This study helps the construction sector in better understanding the extremity of WMSDs and the risks associated with them. This review imparts the researchers with an integrated view of available methods, their drawbacks, and the need for study in order to achieve automated evaluations on construction sites.

A novel ship collision risk evaluation algorithm based on the maximum interval of two ship domains and the violation degree of two ship domains

In the research of ship collision avoidance, the evaluation of ship collision risk is an important part to determine whether there is a potential collision risk. In the field of ship collision avoidance, using an appropriate method to calculate the ship collision risk has always been a hot topic. To address the issues that only qualitative evaluation using the ship domain and the distance to the closest point of approach (DCPA) does not reflect the true distance between the two ships when the closest point of approach (CPA) parameters are used, a novel ship collision risk evaluation model is proposed. (1) A fuzzy quaternion ship domain (FQSD) model is established for the own ship (OS) and the target ship (TS) at the same time. (2) The two parameters the maximum interval of two ship domains (MISD) and the violation degree of two ship domains (VDSD) are introduced, which are solved based on Support Vector Machine for Classification (SVC) and geometric methods, respectively, and the ship collision probability model is established based on these two parameters. (3) Based on the momentum conservation theorem, considering the mass ratio of two ships, ship type, collision velocity and the location of the collision damage, the consequences of ship collision are calculated. (4) Based on the ship collision probability and ship collision consequences, a ship collision risk evaluation model is proposed. The simulation verification is performed under the three encounter situations of head-on, crossing, and overtaking, based on Maneuvering Model Group using the basic ship parameters of Dalian Maritime University's teaching-training ships “YUKUN” and “YUUPENG” to establish the model proposed in this paper. Simultaneously, it is compared to the ship collision risk evaluation method based on ship domain, CPA parameters, and spatial collision risk model. The simulation results demonstrate the superiority and efficacy of the ship collision risk evaluation algorithm proposed in this paper, which is an effective method for assessing ship collision risk.

Unsupervised anomaly detection based method of risk evaluation for road traffic accident

Unsupervised anomaly detection based method of risk evaluation for road traffic accident

Evaluation of failure risk for prestressed anchor cables based on the AHP-ideal point method: An engineering application

This research is focused on the evaluation method of failure risk of prestressed anchor cable, and an accurate evaluation method with a simple operation is proposed. The analytic hierarchy process are used to determine the weight of each evaluation element, the closeness degree of each indicator is determined based on ideal point method. The results show the following: (1) the evaluation method better integrates the effects of multiple factors on the failure risk of the prestressed anchor cable, and the evaluation results are accurate and consistent with the actual situation of the project; (2) the evaluation result is intuitive, and the correlation degree obtained can not only reflect the failure risk grade of prestressed anchor cable, but also the possibility of deterioration of the failure risk of the evaluated anchor cable to a higher level could be obtained; and (3) the rationality and practicability is verified by comparison with field situation and other several methods. In addition, this method has good applicability in solving the other uncertain problems.

QT interval extracted from 30-minute short resting Holter ECG recordings predicts mortality in heart failure

BackgroundProlonged repolarization duration is a significant total mortality (TM) predictor in post-myocardial infarction patients. AimWe examined the clinical significance of QT interval that was extracted from a Short Resting Holter ECG (SRH ECG – 30-min duration) as a TM predictor in heart failure (HF) patients. MethodsOne hundred forty-five HF patients (male = 84%, mean age = 64 ± 12 years, mean LVEF = 33 ± 10%) underwent an SRH ECG recording for 30 min. These high-resolution ECG signals were analyzed and the QT interval was calculated and corrected according to the Fridericia formula. After 42.1 months, 26 patients died. ResultsUnivariate analysis for Deceased and Living groups: QTc:455 ± 33 ms vs 441 ± 32 ms (p = 0.04), LVEF:32 ± 10% vs 34 ± 9% (p < 0.5), Mean Heart Rate: 73 ± 11 bpm vs 69 ± 12 bpm (p = 0.2), SDNN/HRV: 45 ± 42 ms vs 41 ± 29 ms (p = 0.4), QRS: 123 ± 26 ms vs 119 ± 29 ms (p = 0.5). Multivariate Cox regression analysis with model adjusted for QTc, Mean Heart Rate, LVEF, QRS, revealed that QTc-Fridericia interval was an independent TM predictor (H.R.:1.017, 95% C.I.: 1.003–1.030, p = 0.01). The cut-off point of 490 ms (90th percentile) in the same model presented HR: 2.9 for TM (95%C.I.: 1.066–7.882, p = 0.03). Kaplan Meier curves depicted a clear difference in survival between the two patients' groups (QTc Group≥490 ms vs QTc Group <490 ms). The curve diverge was important (log-rank, p = 0.02). ConclusionA fast risk stratification approach with SRH ECG recording is an efficient method for flash evaluation of mortality risk in HF patients.

Integrated risk assessment in sago preparation process using fuzzy petri net model

AbstractTapioca starch is one among the staple foods for human, especially in Tamil Nadu, India. The sago pearls can be produced from tapioca starch through a preparation process (PP). During PP failure may occur in the processing unit, and it may affect the quality of sago pearls, which is a major issue in sago industries. Hence, in our study, a risk assessment method based on fuzzy petri net (FPN) is proposed for the assessment of sago PP. FPN is a graphical mathematical modeling, which provides the basis for modeling the systems with uncertain and inadequate information. Evaluation of weights for places and transitions is a major concern in FPN models, to overcome this limitation, this study proposes a fuzzy analytic hierarchy process to evaluate the weights of the places and transitions in FPN. A FPN model for sago processing unit is defined and by using a matrix‐based reasoning algorithm, risk values for various levels and for the entire system is evaluated. Our method is the one of the reliable methods in risk evaluation of the sago mills and production factories.Practical ApplicationsA specific case study on sago manufacturing process in a factory at Namakkal district, Tamil Nadu is adopted to project the significance of the proposed FPN model with FAHP. For evaluation process, risk factors and token value of the risk factors for FPN model are acquired from the experts in the industry. From the evaluated results of the study attained from the proposed models, it is observed that the results are more consistent with the actual condition. Although the results obtained from the proposed are too reliable with the actual condition of the factory, the proposed FPN‐based risk evaluation methodology for the sago manufacturing process offers reasonable support to the Fault diagnosing unit to avoid the failure in the industry.

Evaluation of airborne transmission risk in university towns based on IEQ surveys

This study aims to evaluate airborne transmission risk in university towns during the COVID-19 pandemic based on surveys of indoor environmental quality (IEQ). Both on-site measurements and questionnaire surveys were carried out in public buildings in university towns in Changsha, China. Air temperature, relative humidity, and CO2 concentration in one library, ten classrooms, eight canteens, seven restaurants, and sixteen malls were measured. 2220 valid questionnaires concerning occupants’ sensation on thermal environment, air movement, and indoor air quality were collected. A 3-level evaluation method of airborne transmission risk that is dependent on building type and indoor CO2 concentration was developed. Excessive CO2 concentration is found in library (1045 ppm), classrooms (1151 ppm), restaurants (1242 ppm), and malls (1057 ppm). The percentage time of “high risk” accounts for 18–100% in these buildings. The results reveal a serious problem: numerous public buildings in China and probably other resource limited countries are not basically prepared and equipped to cope with airborne transmission. This fact should be taken into account when developing guidelines and formulating mitigation measures. Real-time monitoring and displaying IEQ and thus the transmission risk level should be an important way to be widely implemented in public buildings.

Occupational Risk Assessment of Wind Turbines in Bangladesh

Wind energy is among the foremost vital renewable energy sources in the world. With the increase in its popularity and use, the requirement for safety measures regarding this type of energy is becoming more prevalent. The development and operation requirements that come with installing and running wind turbines have many risks that need managing and mitigation. This study implemented a risk evaluation method for the transportation, construction, operation, and maintenance of wind turbines, employing the fuzzy method. Fuzzy Analytical Hierarchy Process (FAHP), a multi-criteria higher cognitive process technique, was used to determine the weights of the risk parameters evaluated with the Fine–Kinney method. After that, the Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS) was employed for ranking the hazard’s source. Using Occupational Health and Safety (OHS) consultants, this study was conducted in Bangladesh regarding its onshore turbines. Findings have revealed that the most prevalent hazards during transportation, construction, operation, and maintenance, respectively, are “Driving vehicles at night in dark weather conditions”, “Work in hot and humid conditions”, “Inclement weather”, and “Entering of unauthorized persons”. The results of this study can help the OHS department to track these risks and to control and minimize them.