Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost

Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk.

Multi-objective optimization and evaluation of supercritical CO_(2) Brayton cycle for nuclear power generation

The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.

Improved Fuzzification Method for Multi-Objective Decision-Making and Its Application in Evaluation of Highway Planning

A new fuzzification method for multi-objective decision-making and selective sorting is proposed on the basis of the fuzzy consistent relation, and the specific algorithm is presented. The method is applied to the evaluation of highway planning of Zhanjiang city. To decrease the subjectivity in the process of decision-making, the LOWA operator is introduced, and a discussion on how to select appropriate weights involved in multi-objective sorting is made. It is concluded that it is feasible to apply the fuzzy consistent relation to multi-objective decision-making analysis, and the improved fuzzication method is workable.

Hesitant Fuzzy-Sets Based Decision-Making Model for Security Risk Assessment

Security is an important component in the process of developing healthcare web applications.We need to ensure security maintenance;therefore the analysis of healthcare web application’s security risk is of utmost importance.Properties must be considered to minimise the security risk.Additionally,security risk management activities are revised,prepared,implemented,tracked,and regularly set up efficiently to design the security of healthcare web applications.Managing the security risk of a healthcare web application must be considered as the key component.Security is,in specific,seen as an add-on during the development process of healthcare web applications,but not as the key problem.Researchers must ensure that security is taken into account right from the earlier developmental stages of the healthcare web application.In this row,the authors of this study have used the hesitant fuzzy-based AHP-TOPSIS technique to estimate the risks of various healthcare web applications for improving security-durability.This approach would help to design and incorporate security features in healthcare web applications that would be able to battle threats on their own,and not depend solely on the external security of healthcare web applications.Furthermore,in terms of healthcare web application’s security-durability,the security risk variable is measured,and vice versa.Hence,the findings of our study will also be useful in improving the durability of several web applications in healthcare.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi-time points and multi-indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the Electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi time points and multi indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the Multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

Method for Risky Multiobjective Group Decision-Making and Its Application

The multiobjective group decision-making problem under risk is common in reality. This paper focuses on the study about risky multiobjective group decision-making problem where the index value is not certain. We give indexes classifying method and index normalizing formula of this type problem. By building objective function that minimizes general weighted distance from every alternative to the relatively best and worst alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, and by building another objective function that minimizes general weighted distance from the optimal membership degree of every decision-maker to every alternative to the group optimal alternative and the group inferior alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, which are both based on probability theory and fuzzy theory. Aftermost a model is established which collects group preferences. This method provides a new idea and approach for solving multiobjective decision-making problem among uncertain system, which is applicable for practical problem. Finally a case study shows a satisfactory result.

GIS Application in Urban Flood Risk Analysis: Midar as a Case Study

The significance of this study lies in its exploration of the advanced applications of Geographic Information Systems (GIS) in assessing urban flood risks, with a specific focus on Midar, Morocco. This research is pivotal as it showcases that GIS technology is not just a tool for mapping, but a critical component in urban planning and emergency management strategies. By meticulously identifying and mapping flood-prone areas in Midar, the study provides invaluable insights into the potential vulnerabilities of urban landscapes to flooding. Moreover, this research demonstrates the practical utility of GIS in mitigating material losses, a significant concern in flood-prone urban areas. The proactive approach proposed in this study, centered around the use of GIS, aims to safeguard Midar’s population and infrastructure from the devastating impacts of floods. This approach serves as a model for other urban areas facing similar challenges, highlighting the indispensable role of GIS in disaster preparedness and response. Overall, the study underscores the transformative potential of GIS in enhancing urban resilience, making it a crucial tool in the fight against natural disasters like floods.

Optimal Decision-Making of Trans-Provincial Electricity Market Subjects with Risks under Renewable Portfolio Standards

The randomness and uncertainty of renewable energy generation are expected to significantly change the optimal decision-making of trans-provincial electricity market subjects.Therefore,it is beneficial to optimize the interests of each of these subjects,considering the unpredictable risks of renewable energy under the renewable portfolio standards(RPS)and researching their effects on the optimal decision-making of transprovincial electricity market multi-subjects.First,we develop a trans-provincial trading market mechanism for renewable energy and clarify the electricity supply and demand relation and the green certificates supply and demand relation of trans-provincial electricitymarketmulti-subjects.Then,under the RPS,we construct a multi-subject game model of the power supply chain that recognizes the risks,and adopt the reverse induction method to discuss the optimum risk-taking judgment of each subject in the trans-provincial electricity market.Finally,we useMATLAB to verify the viability and efficacy of the proposed gamemodel,and obtain a certain reference value for the optimal decision-making of trans-provincial electricity market subjects.In summary,we consider the uncertainty risks of renewable energy under RPS,study the effects of the green certificate price and risk aversion coefficient in the RPS mechanism on the optimal decisionmaking of trans-provincial electricity market subjects,and obtain the changing trends of two different power products and those of different electricity market subjects under the influence of the green certificate price and risk aversion coefficient,which have a certain reference value for studying the factors affecting the optimal decision-making of trans-provincial electricity market subjects.

Probabilistic Lane-Change Decision-Making and Planning for Autonomous Heavy Vehicles

To improve the safety and driving stability of the autonomous heavy truck, it is necessary to consider the differences of driving behavior and drivable trajectories between the heavy trucks and passenger cars. This study proposes a probabilistic decision-making and trajectory planning framework for the autonomous heavy trucks. Firstly, the driving decision process is divided into intention generation and feasibility evaluations, which are realized using the utility theory and risk assessment, respectively. Subsequently the driving decision is made and sent to the trajectory planning module. In order to reflect the greater risks of the truck to other surrounding vehicles, the aggressiveness index(AI) is proposed and quantified to infer the asymmetrical risk level of lane-change maneuver. In the planning stage, the lateral and roll dynamics stability domains are developed as the constraints to exclude the candidate trajectories that would cause vehicle instability. Finally, the simulation results are compared between the proposed model and the artificial potential filed model in the scenarios extracted from the naturalistic driving data. It is shown that the proposed framework can provide the human-like lane-change decisions and truck-friendly trajectories, and performs well in dynamic driving environments.

Application of Grey Situation Decision-Making Theory in Site Selection of a Waste Sanitary Landfill

An application of an unequal-weighted multi-objective decision making method in site selection of a waste sanitary landfill is discussed. The eight factors, which affected possible options, were: size and capacity of the landfill, permeability of the stratum, the average difference in elevation between the groundwater level and the bottom of the landfill pit, quality and source of clay, the quality grade of the landfill site, the effect of landfill engineering on nearby residents, distance to the water supply and the water source as well as the cost of construction and waste transport. These are determined, given the conditions of the geological environment, the need for environmental protection and landfill site construction and transportation related to the design and operation of a sanitary landfill. The weights of the eight factors were further investigated based on the difference in their relevance. Combined with practical experience from Xuzhou city (Jiangsu province, China), the objectives, effects and weights of grey decision-making were deter- mined and the process and outcome of the landfill site selection are stated in detail. The decision-making results have been proven to be acceptable and correct. As we show, unequal-weighted multi-objective grey situation decision-mak- ing is characterized by easy calculations and good maneuverability when used in landfill site selection. The number of factors (objectives) affecting the outcome and the quantitative method of qualitative indices can be adjusted on the basis of concrete conditions in landfill site selection. Therefore, unequal-weighted multi-objective grey situation decision making is a feasible method in selecting landfill sites which offers a reference method for landfill site selection else- where. It is a useful, rational and scientific exploration in the choice of`a landfill site.

The effect of risk perception and COVID‑19 anxiety in pregnancy on decision‑making via the Internet and prenatal care quality:A cross‑sectional multivariate analysis

Background:Risk perception and COVID‑19 anxiety in pregnant women restrict access to health services,cause pregnant women to resort to alternative channels such as the Internet,and affect prenatal care quality(PCQ)negatively.Purpose:The purpose of this study was to examine the effect of risk perception and COVID‑19 anxiety in pregnancy on decision‑making via the Internet(DMI)and PCQ with multivariate analysis.Materials and Methods:This cross‑sectional study was conducted with 406 pregnant women selected using the convenience sampling method in a training and research hospital,in Turkey.The data were collected using the information form,the perception of pregnancy risk questionnaire,the Coronavirus Anxiety Scale,the DMI Scale,and the PCQ Scale.The data obtained were subject to descriptive analysis and the multivariate analysis of variance.Results:Approximately 24.9%of the pregnant women were found to have a high perception of risk and 18%had symptoms of COVID‑19 anxiety.Pregnant women with high COVID‑19 anxiety and a higher perception of risk perceived the Internet as less influential for decision‑making(P<0.05).Pregnant women with a high‑risk perception had lower PCQ(P<0.05).Conclusion:The findings can be used to enhance mental health and resilience in pregnant women and to formulate appropriate intervention strategies.

Sustainability of Bridges:Risk Mitigation for Natural Hazards

Bridges serve as essential parts of transportation infrastructure,facilitating the movement of people and goods across rivers,valleys,and other obstacles.However,they are also susceptible to a wide range of natural hazards,including floods,earthquakes,and landslides,which can damage or even collapse these structures,leading to severe economic and human losses.A risk index has been developed to address this issue,which quantifies the likelihood and severity of natural hazards occurring in a specific location.The application of risk indices for natural hazards in bridge management involves a data collection process and mathematical modelling.The data collection process gathers information on bridges’location,condition,and vulnerability,while mathematical modelling uses the data to assess the risk of natural hazards.Overall,risk indices provide a quantitative measure of the vulnerability of bridges to natural hazards and help to prioritize maintenance and repair activities.Mitigation measures are then evaluated and implemented based on the risk assessment results.By using this tool,the UBMS research group has developed an algorithm for risk assessment which will be essential in the decision-making process,specifically focused on enhancing Fund Optimization,Deterioration Modelling,and Risk Analysis.These developments effectively fulfill the primary objectives associated with addressing and mitigating hazards.This development also helps bridge managers understand the potential threats posed by natural hazards and allocate resources more efficiently to ensure the safety and longevity of critical transportation infrastructure.

Decision-making method for high-speed rail early warning system in complex earthquake situations

To address the shortcomings in decision-making methods for ground motion threshold warning models in high-speed rail earthquake early warning systems(HSREEWs),we propose a dual judgement method and corresponding early warning process for earthquake early warning decisions based on joint peak ground acceleration(PGA)and complex earthquake environmental risk evaluation(ERE)values.First,we analyse the characteristics of four complex earthquake environments based on the characteristics of high-speed rail(HSR)operating environments.Second,we establish an earthquake environmental risk evaluation index system and propose an adversarial interpretive structure modelling method-based complex earthquake situation evaluation model(AISM-based ESEM).The AISM method firstly evaluates the proximity by the TOPSIS(technique for order preference by similarity to an ideal solution)method,then effectively rank targets with fuzzy attributes through opposite hierarchical extraction rules without sacrificing system functionality.Since PGA can reflect the current size of earthquake energy,combining PGA thresholds with ESEM-derived values of ERE can effectively determine the risk status of each train and make decisions on the most appropriate alarm form and control measures for that status.Finally,case analysis results under the background of Wenchuan Earthquake show that the new early warning decisionmaking method accurately assesses environmental risks in affected areas and provides corresponding warning levels as a supplement to existing HSREEWs warning models.

Risk assessment:method and case study for traffic projects

A comprehensive project evaluation and decision-making method considering multiple objectives,stakeholders,and attributes of proposed traffic treatments is inherently complicated.Although individual techniques in evaluating operations,safety,economic,and stakeholder objectives are available,a practical method that integrates all these risk factors and their uncertainties into a multiattribute decision-making tool is absent.A three-level project decision-making process was developed to model and assess multiple-attribute risk in a proposed traffic treatment from the perspective of multiple stakeholders.The direct benefits from reducing delay and safety risk(basic objectives of traffic treatments) are computed in Level 1 with established methods.Feasibility and performance analysis in Level 2 examine site-specific constraints and conduct detailed performance analysis using advanced analysis tools.In Level 3,this paper introduces an innovative and integrated multiple attributes evaluation process under fuzziness and uncertainty(MAFU) process for evaluation and decision-making.The MAFU is a comprehensive and systematic assessment and decision-making procedure that can assess the magnitudes of project performance and to integrate conflicting interests and tradeoffs among stakeholders.A case study illustrates theapplication of MAFU for the selection of a traffic alternative involving several evaluation attributes and stakeholders.Results show that the MAFU produced the smallest variance for each alternative.With traditional cost–benefit evaluation methods,the uncertainty associated with performance of a traffic project in terms of operation,safety,environmental impacts,etc.,is unrestricted and cumulative.Therefore,a reliable multi-attribute evaluation of complex traffic projects should not be made with conventional cost–benefit analysis alone but with a process like MAFU.

Managing Security-Risks for Improving Security-Durability of Institutional Web-Applications: Design Perspective

The advanced technological need,exacerbated by the flexible time constraints,leads to several more design level unexplored vulnerabilities.Security is an extremely vital component in software development;we must take charge of security and therefore analysis of software security risk assumes utmost significance.In order to handle the cyber-security risk of the web application and protect individuals,information and properties effectively,one must consider what needs to be secured,what are the perceived threats and the protection of assets.Security preparation plans,implements,tracks,updates and consistently develops safety risk management activities.Risk management must be interpreted as the major component for tackling security efficiently.In particular,during application development,security is considered as an add-on but not the main issue.It is important for the researchers to stress on the consideration of protection right from the earlier developmental stages of the software.This approach will help in designing software which can itself combat threats and does not depend on external security programs.Therefore,it is essential to evaluate the impact of security risks during software design.In this paper the researchers have used the hybrid Fuzzy AHPTOPSIS method to evaluate the risks for improving security durability of different Institutional Web Applications.In addition,the e-component of security risk is measured on software durability,and vice versa.The paper’s findings will prove to be valuable for enhancing the security durability of different web applications.

Development Strategy of Infrastructure Risk Assessment Based Disaster Response and Management System

Major infrastructures such as levee, dam, bridge, road, etc. have a significant meaning in that they are the means to support ordinary social and industrial activities and also protect human and physical assets at the occurrence of disaster. Especially, integrated risk management of SOC facilities provides the policy maker in charge of SOC facility safety and related disaster prevention with a reasonable means of decision making and ultimately contributes to improving the safety of the applicable SOC facility. Furthermore, a variety of issues raised in the Sewol ferry disaster that occurred recently in Korea, such as, a proper response method and the relevant Golden time decision making at the occurrence of disaster, rapid grasping and reporting the situation on disaster sites, management and mobilization of resources for rescue and recover, loss of integrated control tower function, etc., might occur as well in facility disaster management. As the method of solving such issues adequately, this study suggests a strategy of new disaster response and management system. The analyses of Hazus-MH (FEMA) and DIMSuS (Purdue University) were comprehensively conducted, and based on the results required functions of new disaster response system of major infrastructure and its development directions were suggested.

Modelling Agronomically-Suitable Sowing Date in Relation to the Risk of Frost Damage and Heat Stress of Wheat in Southern New South Wales, Australia

Sowing time of wheat in south eastern Australia varies from autumn to early winter, depending on the seasonal ＇break＇. Wheat yields are often reduced by frost damage at flowering time and by heat-and/or water-stress during grain filling. Selecting suitable varieties for specific sowing times is a complex decision farmers make because these varietal phenology and climate risks have to be assessed together. In order to help farmers make decisions, they need tools that simulate and analyse agronomically-suitable sowing dates （ASSD） for a given variety of wheat. The hypothesis underlining this study is the integration of a wheat phenology model with historical climate data is an effective approach to modelling the ASSD of current varieties used in the wheat growing areas of Southern NSW. The parameters of the wheat phenology model were based on data from five years of field experimentation across 15 sites. Data from four sites were used to examine varietal suitability in relation to sowing time and its associated risks of frost and heat damage. The optimum ASSD for any variety at 72 locations across Southern NSW was investigated. The results showed that there were substantial spatial variations in the ASSD across the target region. ASSD for a late maturing wheat genotype （EGA Gregory） can range from early March to late April, while the earliest acceptable sowing date for an early maturing spring wheat genotype （H46） can range from early to late May. The wide range of spatial variation in the earliest and latest sowing dates, as well as the varied length of sowing opportunities, highlighted the importance of being able to apply a modelling approach which can integrate information on crop phenology with climate risk for a given location. This approach would allow better decision-making on suitable varieties and sowing dates in order to minimise the risk of frost and heat damage affecting crop yield.

A novel framework of ecological risk management for urban development in ecologically fragile regions: A case study of Turpan City, China

Assessing and managing ecological risks in ecologically fragile areas remain challenging at present.To get to know the ecological risk situation in Turpan City,China,this study constructed an ecological risk evaluation system to obtain the ecological risk level(ERL)and ecological risk index(ERI)based on the multi-objective linear programming-patch generation land use simulation(MOP-PLUS)model,analyzed the changes in land use and ecological risk in Turpan City from 2000 to 2020,and predicted the land use and ecological risk in 2030 under four different scenarios(business as usual(BAU),rapid economic development(RED),ecological protection priority(EPP),and eco-economic equilibrium,(EEB)).The results showed that the conversion of land use from 2000 to 2030 was mainly between unused land and the other land use types.The ERL of unused land was the highest among all the land use types.The ecological risk increased sharply from 2000 to 2010 and then decreased from 2010 to 2020.According to the value of ERI,we divided the ecological risk into seven levels by natural breakpoint method;the higher the level,the higher the ecological risk.For the four scenarios in 2030,under the EPP scenario,the area at VII level was zero,while the area at VII level reached the largest under the RED scenario.Comparing with 2020,the areas at I and II levels increased under the BAU,EPP,and EEB scenarios,while decreased under the RED scenario.The spatial distributions of ecological risk of BAU and EEB scenarios were similar,but the areas at I and II levels were larger and the areas at V and VI levels were smaller under the EEB scenario than under the BAU scenario.Therefore,the EEB scenario was the optimal development route for Turpan City.In addition,the results of spatial autocorrelation showed that the large area of unused land was the main reason affecting the spatial pattern of ecological risk under different scenarios.According to Geodetector,the dominant driving factors of ecological risk were gross domestic product rating(GDPR),soil type,population,temperature,and distance from riverbed(DFRD).The interaction between driving factor pairs amplified their influence on ecological risk.This research would help explore the low ecological risk development path for urban construction in the future.

Multi-objective optimization for deepwater dynamic umbilical installation analysis

We suggest a method of multi-objective optimization based on approximation model for dynamic umbilical installation. The optimization aims to find out the most cost effective size, quantity and location of buoyancy modules for umbilical installation while maintaining structural safety. The approximation model is constructed by the design of experiment (DOE) sampling and is utilized to solve the problem of time-consuming analyses. The non-linear dynamic analyses considering environmental loadings are executed on these sample points from DOE. Non-dominated Sorting Genetic Algorithm (NSGA-II) is employed to obtain the Pareto solution set through an evolutionary optimization process. Intuitionist fuzzy set theory is applied for selecting the best compromise solution from Pareto set. The optimization results indicate this optimization strategy with approximation model and multiple attribute decision-making method is valid, and provide the optimal deployment method for deepwater dynamic umbilical buoyancy modules.