Quantitative Risk Assessment for Aerospace Facility According to Windrose

Wind direction and speed are the most important factors that determine the degree of damage caused by a jet fire. In this study, the metal hose used to extract/supply fuel was identified as the component with the highest risk for a jet fire occurring at an aerospace facility. A risk assessment was performed to evaluate the individual risk of a jet fire from the metal hose according to the wind direction and speed. HSE failure data was applied for calculating the jet fire probability including metal hose failure, ignition frequency, and jet fire frequency. Which was 3.0 × 10−4. The individual risk of different fatality probabilities was calculated according to the wind rose data for the aerospace facility. The individual risk from jet fire in the aerospace facility was calculated with a maximum risk of 3.35 × 10−5 and a minimum risk of 1.49 × 10−6. The individual risk satisfied HSE ALARP criteria. In addition, firewalls, extinguishing systems, and an emergency shut off system were enhanced, and it was thought that the risk from jet fire could satisfy acceptable criteria.

The risk-based strategy model technical maintenance of the unique technological structures

The article considers an approach to the development of a risk-based strategy model for the technical maintenance of a unique technological structure. It is proposed to use the minimum risk of the structure failure as a criterion for optimizing the technical maintenance of the structure. It is shown that this approach allows to decrease considerably and by limited means the risk of the elements failure especially those influencing the structure safety. The task of determining the strategy parameters of technical maintenance of the construction object under consideration is formulated as a Boolean mathematical programming task. The theoretical conclusions are confirmed by the calculation example. The solution showed the advantage concerning the risk of use of the proposed strategy in comparison with the current one.

Colorectal anastomosis in rectal cancer surgery: methods of anastomotic leakage prevention

One of the most serious complications after low anterior resection is the failure of sutures of colorectal anastomosis, which is the most common surgical complication that results in patient’s death. Promptly diagnosed anastomotic leakage in postoperative period is challenging. Nevertheless, elimination of risk factors in preoperative period can significantly reduce complication rates.The purpose of this review article is to analyze possible risk factors and methods for preventing colorectal anastomosis leakage.An important area of prevention and optimization of treatment options for anastomotic leakage is the development of prognostic measures to eliminate risk factors. We see the prospects for this direction in the introduction of a nomogram, which allows the surgeon to assess the possible outcomes of the operation, to choose the optimal tactics with a minimum risk of complications, as well as the introduction of methods to avoid or prevent the development of complications of colorectal anastomosis.

Study on Assessment of Risk factors of Constipation among Patients Undergoing Abdominal Surgery

Objective: Aim of the study to assess the risk of constipation among patients undergoing abdominal surgery. Constipation is a gastrointestinal tract condition which can lead to abnormal stools, uncomfortable storage and passing with pain and stiffness. Constipation is one of the gastrointestinal system's functional impairments. Various symptoms also include bloating, pushing, abdominal and rectal pain, a feeling of fullness in the rectum or extreme defecation, a lack of full discharge, and stool infrequency (usually less than three times a week). Constipation problem is a condition that is prevalent in abdominal surgery patients in the preoperative and postoperative period due to physiological and psychological factors. While constipation does not endanger life. Bowel frequency is affected by many variables, including dietary factors, emotional state, immobility, prior history of bowel elimination problem, and psychological morbidity after abdominal surgery. Constipation is a common issue that many individuals face. Materials and Methods: The cross sectional research study conducted in AVBR hospital Sawangi Meghe, Wardha district with quantitative research approach. Sample size was 85. Sample was undergoing abdominal surgery patients. Tool was structured questionnaire including Patients characteristics & constipation risk assessment scale. Results: 48.24% of patients undergoing abdominal surgery had no risk of developing constipation, 29.41% had low risk of constipation, 14.12% had moderate and 8.23% of the patients undergoing abdominal surgery had severe risk of constipation. Minimum risk of constipation was 0 and maximum was 17. Mean risk of constipation was 5.14±5.71. Conclusion: This study can help to assess the risk of constipation among undergoing abdominal surgery patients and make them aware about risk of constipation.

Comparative study of the behavior of the effective boundary of minimal risk portfolio in the conditions of hybrid uncertainty, depending on the restrictions on the profitability of the portfolio

В работе проведены исследования эффективной границы портфеля минимального риска в условиях гибридной неопределенности. Для случая двумерного портфеля при ограничении на ожидаемую доходность портфеля и ограничении по возможности/необходимости и вероятности на доходность портфеля в зависимости от уровня вероятности построены квазиэффективные границы портфеля. Результаты численных экспериментов согласуются с ранее полученными авторами теоретическими результатами. The paper studies the effective boundary of the minimum risk portfolio in the conditions of hybrid uncertainty. For the case of a two-dimensional portfolio, with a restriction on the expected return of the portfolio and a restriction on possibility/necessity and probability on the return of the portfolio, quasi-effective portfolio boundaries are constructed depending on the probability level. The results of numerical experiments are consistent with the theoretical results previously obtained by the authors.

Takeover Safety Analysis with Driver Monitoring Systems and Driver-Vehicle Interfaces in Highly Automated Vehicles

According to SAE J3016, autonomous driving can be divided into six levels, and partially automated driving is possible from level three up. A partially or highly automated vehicle can encounter situations involving total system failure. Here, we studied a strategy for safe takeover in such situations. A human-in-the-loop simulator, driver-vehicle interface, and driver monitoring system were developed, and takeover experiments were performed using various driving scenarios and realistic autonomous driving situations. The experiments allowed us to draw the following conclusions. The visual–auditory–haptic complex alarm effectively delivered warnings and had a clear correlation with the user’s subjective preferences. There were scenario types in which the system had to immediately enter minimum risk maneuvers or emergency maneuvers without requesting takeover. Lastly, the risk of accidents can be reduced by the driver monitoring system that prevents the driver from being completely immersed in non-driving-related tasks. We proposed a safe takeover strategy from these results, which provides meaningful guidance for the development of autonomous vehicles. Considering the subjective questionnaire evaluations of users, it is expected to improve the acceptance of autonomous vehicles and increase the adoption of autonomous vehicles.

Development of a New Risk Assessment Methodology for Light Goods Vehicles on Two-Lane Road Sections

Increasing mobility directly affects traffic frequency and thus increases the possible risk of traffic accident occurrences. Taking this into account, it is necessary to create models for determining risk and to act preventively based on these models; this is of great importance both to society and science. In this paper, six measuring sections of a road network are considered on the basis of eight geometric-exploitation road parameters, taking into account the data for light goods vehicles. An original methodology is proposed for identifying risk levels of road sections through their evaluation. For identifying risk levels, the Dombi Logarithmic Methodology of Additive Weights (D’LMAW) was used, which was combined with the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) method. Statistical indicators were processed using a hybrid methodology based on the application of rough numbers and Dombi–Bonferroni functions. The performance of the presented methodology was verified on a real-world example, processing the statistical parameters of six two-lane road sections, with the sixth measuring section showing the best performance, since it had the minimum risk. Research has shown that measuring sections with increasing longitudinal gradients are safer. The analysis of measuring sections from fall to rise reduces the deviation of speeds from the speed limit on the roads. The effectiveness, rationality, and robustness of the solution of the proposed methodology was confirmed through a sensitivity analysis.

Multiagent Minimum Risk Path Intrusion Strategy with Computational Geometry

In wireless sensor networks (WSNs), inefficient coverage does affect the quality of service (QoS), which the minimum exposure path (MEP) is traditionally used to handle. But intelligent mobile devices are generally of limited computation capability, local storage, and energy. Present methods cannot meet the demand of multiple target intrusion, lacking the consideration of energy consumption. Based on the Voronoi diagram in computational geometry, this paper proposed an invasion strategy of minimum risk path (MRP) to such a question. MRP is the path considered both the exposure of the moving target and energy consumption. Federated learning is introduced to figure out how to find the MRP, expressed as C t i , t j = f E , e . The value of C t i , t j can measure the success of an invasion. At the time when a single smart mobile device invades, horizontal federated learning is taken to partition the path feature, and a single target feature federated (SPF) algorithm is for calculating the MRP. Moreover, for multi smart mobile device invasion, it has imported the time variable. Vertical federated learning can partition the feature of multipath data, and the multi-target feature federated (MFF) algorithm is for solving the multipath MRP dynamically. The experimental results show that the SPF and MFF have the dominant advantage over traditional computational performance and time. It primarily applies the complex conditions of a massive amount of sensor nodes.