Observation of the Effect of Video Assessment Method on the Operation Skills of Individual Nurses

Objective:To explore the application effect of video assessment method in clinical nurses’nursing operation skills.Method:To select 58 nurses who participated in the individual soldier standard in the children’s hospital in 2019 and 2020 as the research objects,among which the nurses who participated in the individual soldier standard in 2019 were the nurses who participated in the individual soldier standard in 2019 and 2020.A total of 29 people in the first batch were set as the control group,using traditional assessment methods.In 2020,the second batch of 29 nurses who participated in the individual soldier standard reached the experimental group.Using the video assessment method,there was no significant difference in general information between the two groups(P>0.05).After the assessment,the scores,coping with work pressure,and proactiveness of the two groups of research subjects were compared.Results:The experimental group’s nursing operation assessment scores,coping with work pressure,and proactiveness were significantly better than those of the control group,the difference was statistically significant(P<0.05).Conclusion:The application of the video assessment method improves the passing rate of nurses’operational skills examination,enhances nurses’initiative in learning,reduces examination pressure,and can be accurately,timely,and safely applied to clinical nursing work,which is worthy of study and promotion.

Risk Assessment Framework and Algorithm of Power Systems Based on the Partitioned Multi-objective Risk Method

针对平均风险指标无法区分高损失-低概率事件及低损失-高概率事件的缺点,提出了电力系统的分割多目标风险分析框架。该框架将电力系统的风险状态细分为低损失、中等损失和高损失3个风险范围,并提出3个损失范围条件风险函数和条件风险概率的概念。采用经典的容量停运表模型,建立了这些条件期望指标的计算方法。对IEEE-RTS及TH-RTS2000系统进行了分割多目标风险评估,研究不同负荷水平下系统风险在3个损失范围的分布及转移情况,并分析损失分割点对系统风险的影响。通过分割多目标风险分析,风险分析者和决策者可以权衡系统的平均风险以及高、中、低损失范围的条件期望风险,从而对系统的风险状况有一个全面和深入的了解。

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.

A novel refined dynamic model of high-speed maglev train-bridge coupled system for random vibration and running safety assessment

Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.

Seismic safety assessment with non-Gaussian random processes for train-bridge coupled systems

Extensive high-speed railway(HSR)network resembled the intricate vascular system of the human body,crisscrossing mainlands.Seismic events,known for their unpredictability,pose a significant threat to both trains and bridges,given the HSR’s extended operational duration.Therefore,ensuring the running safety of train-bridge coupled(TBC)system,primarily composed of simply supported beam bridges,is paramount.Traditional methods like the Monte Carlo method fall short in analyzing this intricate system efficiently.Instead,efficient algorithm like the new point estimate method combined with moment expansion approximation(NPEM-MEA)is applied to study random responses of numerical simulation TBC systems.Validation of the NPEM-MEA’s feasibility is conducted using the Monte Carlo method.Comparative analysis confirms the accuracy and efficiency of the method,with a recommended truncation order of four to six for the NPEM-MEA.Additionally,the influences of seismic magnitude and epicentral distance are discussed based on the random dynamic responses in the TBC system.This methodology not only facilitates seismic safety assessments for TBC systems but also contributes to standard-setting for these systems under earthquake conditions.

Research on the Reform of Assessment under the Blended Teaching Mode:Taking the Teaching Practice of English Stylistics in Guangdong Technology College as an Example

English Stylistics is provided as an elective course by the Business English major at Guangdong Technology College,whose evaluation mechanism significantly impacts how well students learn the language.A novel assessment model is put forth in this study with the intention of transforming from a single summative assessment to a combination of formative and summative assessment in light of the shortcomings of the current assessment methodology in the course.In order to take advantage of blended teaching and integrate the online and offline learning resources of English Stylistics,all-round reforms have been carried out at multiple levels,including teaching content,teaching methods,and assessment approaches.Therefore,a more reasonable and diversified assessment method has been adopted to more comprehensively reflect students’learning objectives and proficiency in foreign languages.

Comparative Analysis of Pythagorean MCDM Methods for the Risk Assessment of Childhood Cancer

According to the World Health Organization(WHO),cancer is the leading cause of death for children in low and middle-income countries.Around 400,000 kids get diagnosed with this illness each year,and their survival rate depends on the country in which they live.In this article,we present a Pythagorean fuzzy model that may help doctors identify the most likely type of cancer in children at an early stage by taking into account the symptoms of different types of cancer.The Pythagorean fuzzy decision-making techniques that we utilize are Pythagorean Fuzzy TOPSIS,Pythagorean Fuzzy Entropy(PF-Entropy),and Pythagorean Fuzzy PowerWeighted Geometric(PFPWG).Ourmodel is fed with nineteen symptoms and it diagnoses the risk of eight types of cancers in children.We develop an algorithm for each method and calculate its complexity.Additionally,we consider an example to make a clear understanding of our model.We also compare the final results of various tests that prove the authenticity of this study.

Solving Multi-Objective Linear Programming Problem by Statistical Averaging Method with the Help of Fuzzy Programming Method

A multi-objective linear programming problem is made from fuzzy linear programming problem. It is due the fact that it is used fuzzy programming method during the solution. The Multi objective linear programming problem can be converted into the single objective function by various methods as Chandra Sen’s method, weighted sum method, ranking function method, statistical averaging method. In this paper, Chandra Sen’s method and statistical averaging method both are used here for making single objective function from multi-objective function. Two multi-objective programming problems are solved to verify the result. One is numerical example and the other is real life example. Then the problems are solved by ordinary simplex method and fuzzy programming method. It can be seen that fuzzy programming method gives better optimal values than the ordinary simplex method.

Risk Assessment of Diary Cattle Brucellosis Based on Systematic Multilevel Grey Relation Entropy Method

[Objective] The study was to explore the major factors affecting diary cattle brucellosis risk assessment,as well as their strong-to-weak sequence,so as to provide theoretical basis for assessing diary cattle brucellosis risk level in different regions.[Method] From 4 dimensions of feeding and importing,breeding,housing and polyculture situation,an evaluation index system was set up,and diary cattle brucellosis risk survey was conducted in 3 typical regions.Finally,systematic multilevel grey relation entropy method was applied to perform data analysis.[Result] The strong-to-weak sequence of Level 1 impact factor of diary cattle brucellosis was as follows：feeding and importinghousingpolyculture situationbreeding;the sequence of Level 2 impact factor was U32〉U12〉U11〉U31〉U21〉U42〉U43〉U23〉U22〉U41;the risk level sequence of 3 typical regions was Province A（County A1,A2,A3）Province B（County B1,B2,B3）Province C（County C1,C2,C3）.[Conclusion] According to the weight of Level 1 index strata,administrative departments at all levels and dairy cattle farmers should lay emphasis on the aspects of feeding,importing and housing;viewed from the perspective of Level 2 index strata,dairy cattle farmers should value the siting of cattle field,the brucellosis surveillance before importing and milking modes most.According to the diary cattle brucellosis risk level of 3 typical regions,if administrative departments at all levels strengthen peoples＇ awareness of their personal health and increase investment in this area,with new healthy cultured atmosphere built,the risk level of diary cattle brucellosis will surly decline.

Multi-Objective Image Optimization of Product Appearance Based on Improved NSGA-II

A second-generation fast Non-dominated Sorting Genetic Algorithm product shape multi-objective imagery optimization model based on degradation(DNSGA-II)strategy is proposed to make the product appearance optimization scheme meet the complex emotional needs of users for the product.First,the semantic differential method and K-Means cluster analysis are applied to extract the multi-objective imagery of users;then,the product multidimensional scale analysis is applied to classify the research objects,and again the reference samples are screened by the semantic differentialmethod,and the samples are parametrized in two dimensions by using elliptic Fourier analysis;finally,the fuzzy dynamic evaluation function is used as the objective function of the algorithm,and the coordinates of key points of product contours Finally,with the fuzzy dynamic evaluation function as the objective function of the algorithm and the coordinates of key points of the product profile as the decision variables,the optimal product profile solution set is solved by DNSGA-II.The validity of the model is verified by taking the optimization of the shape scheme of the hospital connection site as an example.For comparison with DNSGA-II,other multi-objective optimization algorithms are also presented.To evaluate the performance of each algorithm,the performance evaluation index values of the five multi-objective optimization algorithms are calculated in this paper.The results show that DNSGA-II is superior in improving individual diversity and has better overall performance.

Urban flood risk assessment under rapid urbanization in Zhengzhou City,China

With accelerated urbanization and climate change,urban flooding is becoming more and more serious.Flood risk assessment is an important task for flood management,so it is crucial to map the spatial and temporal distribution of flood risk.This paper proposed an urban flood risk assessment method that takes into account the influences of hazard,vulnerability,and exposure,by constructing a multi-index urban flood risk assessment framework based on Geographic Information System(GIS).To determine the weight values of urban flood risk index factors,we used the analytic hierarchy process(AHP).Also,we plotted the temporal and spatial distribution maps of flood risk in Zhengzhou City in 2000,2005,2010,2015,and 2020.The analysis results showed that,the proportion of very high and high flood risk zone in Zhengzhou City was 1.362%,5.270%,4.936%,12.151%,and 24.236%in 2000,2005,2010,2015,and 2020,respectively.It is observed that the area of high flood risk zones in Zhengzhou City showed a trend of increasing and expanding,of which Dengfeng City,Xinzheng City,Xinmi City,and Zhongmu County had the fastest growth rate and the most obvious increase.The flood risk of Zhengzhou City has been expanding with the development of urbanization.The method is adapted to Zhengzhou City and will have good adaptability in other research areas,and its risk assessment results can provide a scientific reference for urban flood management personnel.In the future,the accuracy of flood risk assessment can be further improved by promoting the accuracy of basic data and reasonably determining the weight values of index factors.The risk zoning map can better reflect the risk distribution and provide a scientific basis for early warning of flood prevention and drainage.

Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects.Additionally,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry.However,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks.To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making approach.First,a credit risk assessment index for Chinese real estate enterprises is established.Then,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods.This approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation information.Finally,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility.This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

A Comparative Analysis of Environmental Quality Assessment Methods for Heavy Metal-Contaminated Soils

Four assessment methods （two pollution indexes and two fuzzy mathematical models） were employed to investigate the environmental quality of four soils around a ferroalloy plant in Nanjing City. Environmental quality was assessed as class Ⅳ （moderately polluted） for each soil with single-factor index method, and was identified to be classes Ⅳ, Ⅲ （slightly polluted）, Ⅲ, and Ⅲ for soils A, B, C, and D, respectively, with the comprehensive index model. In comparison with the single-factor index method, the comprehensive index model concerned both dominant parameter and average contribution of all factors to the integrated environmental quality. Using the two fuzzy mathematical methods （single-factor deciding and weighted average models）, the environmental risks were determined to be classes Ⅳ, Ⅲ, Ⅱ （clean）, and Ⅱ for soils A, B, C, and D, respectively. However, divergence of the membership degree to each pollution class still occurred between the two methods. In fuzzy mathematical methods, membership functions were used to describe the limits between different pollution degrees, and different weights were allocated for the factors according to pollution contribution. Introduction of membership degree and weight of each factor to fuzzy mathematical models made the methods more reasonable in the field of environmental risk assessment.

Dynamic assessment method of air target threat based on improved GIFSS

As the air combat environment becomes more complicated and changeable, accurate threat assessment of air target has a significant impact on air defense operations. This paper proposes an improved generalized intuitionistic fuzzy soft set (GIFSS) method for dynamic assessment of air target threat. Firstly, the threat assessment index is reasonably determined by analyzing the typical characteristics of air targets. Secondly, after the GIFSS at different time is obtained, the index weight is determined by the intuitionistic fuzzy set entropy and the relative entropy theory. Then, the inverse Poisson distribution method is used to determine the weight of time series, and then the time-weighted GIFSS is obtained. Finally, threat assessment of five air targets is carried out by using the improved GIFSS (I-GIFSS) and comparison methods. The validity and superiority of the proposed method are verified by calculation and comparison.

STUDY ON METHOD OF QUANTITATIVE ASSESSMENT OF FRAGILE ENVIRONMENT

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Seismic assessment of unanchored steel storage tanks by endurance time method

Liquid storage tanks are essential structures that are often located in residential and industrial areas; thus an assessment of their seismic performance is an important engineering issue. In this paper, the seismic response ofunanchored steel liquid storage tanks is investigated using the endurance time （ET） dynamic analysis procedure and compared to responses obtained for anchored tanks under actual ground motions and intensifying ET records. In most cases, the results from ground motions are properly obtained with negligible differences using ET records. It is observed that uplifting of the tank base, which is closely related to the tank aspect ratio, has the greatest significance in the responses of the tank and can be predicted with reasonable accuracy by using currently available ET records.

Research Progress in Occupational Health Risk Assessment Methods in China

Traditional occupational disease control and prevention has remained prevalent in China over recent decades. There are appropriately 30,000 new case reports of occupational diseases annually. Although China has already established a series of occupational disease prevention programs, occupational health risk assessment （OHRA） strategies continue to be a limitation.

A RISK ASSESSMENT METHOD OF THE WIRELESS NETWORK SECURITY

The core of network security is the risk assessment. In this letter,a risk assessment method is introduced to estimate the wireless network security. The method,which combines Analytic Hier-archy Process (AHP) method and fuzzy logical method,is applied to the risk assessment. Fuzzy logical method is applied to judge the important degree of each factor in the aspects of the probability,the influence and the uncontrollability,not to directly judge the important degree itself. The risk as-sessment is carved up 3 layers applying AHP method,the sort weight of the third layer is calculated by fuzzy logical method. Finally,the important degree is calculated by AHP method. By comparing the important degree of each factor,the risk which can be controlled by taking measures is known. The study of the case shows that the method can be easily used to the risk assessment of the wireless network security and its results conform to the actual situation.

Application of a Bayesian method to data-poor stock assessment by using Indian Ocean albacore (Thunnus alalunga) stock assessment as an example

It is widely recognized that assessments of the status of data-poor fish stocks are challenging and that Bayesian analysis is one of the methods which can be used to improve the reliability of stock assessments in data-poor situations through borrowing strength from prior information deduced from species with good-quality data or other known information. Because there is considerable uncertainty remaining in the stock assessment of albacore tuna（Thunnus alalunga） in the Indian Ocean due to the limited and low-quality data, we investigate the advantages of a Bayesian method in data-poor stock assessment by using Indian Ocean albacore stock assessment as an example. Eight Bayesian biomass dynamics models with different prior assumptions and catch data series were developed to assess the stock. The results show（1） the rationality of choice of catch data series and assumption of parameters could be enhanced by analyzing the posterior distribution of the parameters;（2） the reliability of the stock assessment could be improved by using demographic methods to construct a prior for the intrinsic rate of increase（r）. Because we can make use of more information to improve the rationality of parameter estimation and the reliability of the stock assessment compared with traditional statistical methods by incorporating any available knowledge into the informative priors and analyzing the posterior distribution based on Bayesian framework in data-poor situations, we suggest that the Bayesian method should be an alternative method to be applied in data-poor species stock assessment, such as Indian Ocean albacore.

Multi-objective optimization strategies using adjoint method and game theory in aerodynamics

There are currently three different game strategies originated in economics： （1） Cooperative games （Pareto front）, （2） Competitive games （Nash game） and （3） Hierarchical games （Stackelberg game）. Each game achieves different equilibria with different performance, and their players play different roles in the games. Here, we introduced game concept into aerodynamic design, and combined it with adjoint method to solve multi- criteria aerodynamic optimization problems. The performance distinction of the equilibria of these three game strategies was investigated by numerical experiments. We computed Pareto front, Nash and Stackelberg equilibria of the same optimization problem with two conflicting and hierarchical targets under different parameterizations by using the deterministic optimization method. The numerical results show clearly that all the equilibria solutions are inferior to the Pareto front. Non-dominated Pareto front solutions are obtained, however the CPU cost to capture a set of solutions makes the Pareto front an expensive tool to the designer.