Human Health Risk Assessment Model of Organic Pollution in Groundwater:Shijiazhuang Industrial Zone

In this study, a risk-based management model is developed and applied to an industrial zone. The models proposed by the United States Environmental Protection Agency and Han Bing have been improved by adding a residual ratio of volatile organic compounds （VOC） after boiling and deleting the related parameters in half-life. Using this improved model, an integrated process was used to assess human health risk level in the study area. Compared with water quality analysis, the results highlight the importance of applying an integrated approach for decision making on risk levels and water protection. The results of this study demonstrated that： （1） Compared with these permissible level standards in China （GB 3838-2002） and National Primary Drinking Water Regulations of the United States, the residents＇ daily life had not been affected by the groundwater in this area （except for relative bad water quality of HB3-4 and HB3-6）; （2） The typical detected organic contaminants of all groundwater samples were chloroform, carbon tetrachloride, trichloroethylene and tetrachloroethene, and the pollution sources were mainly industrial sources by preliminary investigations; （3） As for groundwater, the non-carcinogenic risk values of all samples do not exceed the permissible level of 1.0 and the carcinogenic risk values are relatively lower than the permissible level of 1.00E-06 to 1.00E-04; （4） Drinking water pathway of trichloroethylene and tetrachloroethylene mainly contribute to increasing the health risk of residents＇ in study areas; （5） In terms of non-carcinogenic risk and carcinogenic risk, the health risk order for drinking water pathway and dermal contact pathway was： drinking water pathway 〉 dermal contact pathway.

New Three-Dimensional Assessment Model and Optimization of Acoustic Positioning System

This paper addresses the problem of assessing and optimizing the acoustic positioning system for underwater target localization with range measurement.We present a new three-dimensional assessment model to evaluate the optimal geometric beacon formation whether meets user requirements.For mathematical tractability,it is assumed that the measurements of the range between the target and beacons are corrupted with white Gaussian noise with variance,which is distance-dependent.Then,the relationship between DOP parameters and positioning accuracy can be derived by adopting dilution of precision(DOP)parameters in the assessment model.In addition,the optimal geometric beacon formation yielding the best performance can be achieved via minimizing the values of geometric dilution of precision(GDOP)in the case where the target position is known and fixed.Next,in order to ensure that the estimated positioning accuracy on the region of interest satisfies the precision required by the user,geometric positioning accuracy(GPA),horizontal positioning accuracy(HPA)and vertical positioning accuracy(VPA)are utilized to assess the optimal geometric beacon formation.Simulation examples are designed to illustrate the exactness of the conclusion.Unlike other work that only uses GDOP to optimize the formation and cannot assess the performance of the specified size,this new three-dimensional assessment model can evaluate the optimal geometric beacon formation for each dimension of any point in three-dimensional space,which can provide guidance to optimize the performance of each specified dimension.

Smoke Hazard Assessment Model Based on Fire Dynamics Simulator and FED Model

Smoke is the main cause of fire death. In order to minimize the potential danger of smoke hazard, a rational VR based fire training simulator should fully consider all aspects of smoke hazard. In the simulator, the visualization of data based on FDS (Fire Dynamics Simulator) and FED fire dynamic data and volume rendering is further optimized, which can be effectively and quickly applied to virtual fire protection. In addition, a comprehensive smoke hazard assessment model based on FED and FED is established to assess the IHD value of different paths, which represents the safety of different paths, and can be used for evacuation or rescue in virtual training. Taking the case of campus fire drill as an experiment, the research shows the accuracy and effectiveness of smoke assessment based on FDS and FED model. The road force with the highest safety can be selected through the comprehensive model. So the assessment model is proved to be valuable.

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.

Recycling Strategy and Recyclability Assessment Model Based on the Artificial Neural Network

Now, a rapidly growing concern for the environmental protection and resource utilization has stimulated many new activities in the in dustrialized world for coping with urgent environmental problems created by the steadily increasing consumption of industrial products. Increasingly stringent r egulations and widely expressed public concern for the environment highlight the importance of disposing solid waste generated from industrial and consumable pr oducts. How to efficiently recycle and tackle this problem has been a very impo rtant issue over the world. Designing products for recyclability is driven by environmental and economic goals. To obtain good recyclability, two measures can be adopted. One is better recycling strategy and technology; the other is design for recycling (DFR). The recycling strategies of products generally inclu de: reuse, service, remanufacturing, recycling of production scraps during the p roduct usage, recycle (separation first) and disposal. Recyclability assessment is a very important content in DFR. This paper first discusses the content of D FR and strategies and types related to products recyclability, and points out th at easy or difficult recyclability depends on the design phase. Then method and procedure of recyclability assessment based on ANN is explored in detail. The pr ocess consists of selection of the ANN input and output parameters, control of t he sample quality and construction and training of the neural network. At la st, the case study shows this method is simple and operative.

Establishment of ocean dumping area capacity assessment model

Dumping area capacity is mainly affected by the hydrodynamic process （tidal sediment, storm surge and wave, etc.） as well as the size and depth of dumping area. Based on three-dimensional ocean circulation model known as FVCOM （Finite Volume Coast and Ocean Model） and the stochastic dynamic statistical analysis model, taking advantage of dumping ground topography evolution and dumping quantity, the author aims to discuss the influence of hydrodynamic processes and dumping activity so as to built a new model of ocean dumping area capacity. With the data of depth and dumped amount in the dumping area, the changes of bottom topographic which caused by tidal current under the natural condition based on the FVCOM hydrodynamic and sediment module, the author strive to analyze the statistical relation of the changes for dumping amount, tidal current and bottom topographic. Through real data to fit revision coefficient values, which will be regarded as topographic changes reference value affected by wave and storm surges. Thus taking this evaluation as the long-term changes in the dumping capacity. In the premise of setting up the threshold of bottom topographic changes, the dumping area capacity is calculated. Take Yangtze Estuary No. 1 dumping area as an example, As the water depth reduces by 0.5 m annually, the dumping area capacity is about 6.7 million m3/a, the model results are in reasonable agreement with the actual amount. Then the model is validated in Luoyuan Bay dumping area, Shengsishangchuan Mountain dumping area, Dongding dumping area, Dongshan dumping area, and Wenzhou Port dumoin~ area. it is turns out the results are similar to that of the actual observations.

Quantum Risk Assessment Model Based on Two Three-Qubit GHZ States

With the acceleration of the construction of quantum communication networks,scholars have proposed different quantum communication protocols for different application scenarios.However,few scholars pay attention to the risk assessment process before communication.In this paper,we propose a novel quantum risk assessment model based on quantum teleportation technology with two three-qubit GHZ states.Only by using Bell states measurements(BSMs)and two-qubit projective measurements(PJMs),the communicators can recovery any arbitrary two-qubit state.This protocol can transmit two-dimension risk assessment factors with better security performance.On the one hand,more sufficient evaluation factors allow the two communicating parties to more objectively evaluate the risk level of communication with the other party,and on the other hand,it also improves the qubit efficiency of the protocol.Moreover,we introduce the third party in this scheme can be semi-trusted,which must be full-trusted in our previous work.This change can reduce the dependence of the communication parties on the third-party organization and improve the privacy of communication.The security analysis shows that this scheme can resist internal and external attacks,and the quantum circuit diagrams also prove that our protocol is physically easier to implement.

Development and validation of a risk assessment model for prediabetes in China national diabetes survey

BACKGROUND Prediabetes risk assessment models derived from large sample sizes are scarce.AIM To establish a robust assessment model for prediabetes and to validate the model in different populations.METHODS The China National Diabetes and Metabolic Disorders Study(CNDMDS)collected information from 47325 participants aged at least 20 years across China from 2007 to 2008.The Thyroid Disorders,Iodine Status and Diabetes Epidemiological Survey(TIDE)study collected data from 66108 participants aged at least 18 years across China from 2015 to 2017.A logistic model with stepwise selection was performed to identify significant risk factors for prediabetes and was internally validated by bootstrapping in the CNDMDS.External validations were performed in diverse populations,including populations of Hispanic(Mexican American,other Hispanic)and non-Hispanic(White,Black and Asian)participants in the National Health and Nutrition Examination Survey(NHANES)in the United States and 66108 participants in the TIDE study in China.C statistics and calibration plots were adopted to evaluate the model’s discrimination and calibration performance.RESULTS A set of easily measured indicators(age,education,family history of diabetes,waist circumference,body mass index,and systolic blood pressure)were selected as significant risk factors.A risk assessment model was established for prediabetes with a C statistic of 0.6998(95%CI:0.6933 to 0.7063)and a calibration slope of 1.0002.When externally validated in the NHANES and TIDE studies,the model showed increased C statistics in Mexican American,other Hispanic,Non-Hispanic Black,Asian and Chinese populations but a slightly decreased C statistic in non-Hispanic White individuals.Applying the risk assessment model to the TIDE population,we obtained a C statistic of 0.7308(95%CI:0.7260 to 0.7357)and a calibration slope of 1.1137.A risk score was derived to assess prediabetes.Individuals with scores≥7 points were at high risk of prediabetes,with a sensitivity of 60.19%and specificity of 67.59%.CONCLUSION An easy-to-use assessment model for prediabetes was established and was internally and externally validated in different populations.The model had a satisfactory performance and could screen individuals with a high risk of prediabetes.

Comparative study of different machine learning models in landslide susceptibility assessment: A case study of Conghua District, Guangzhou, China

Machine learning is currently one of the research hotspots in the field of landslide prediction.To clarify and evaluate the differences in characteristics and prediction effects of different machine learning models,Conghua District,which is the most prone to landslide disasters in Guangzhou,was selected for landslide susceptibility evaluation.The evaluation factors were selected by using correlation analysis and variance expansion factor method.Applying four machine learning methods namely Logistic Regression(LR),Random Forest(RF),Support Vector Machines(SVM),and Extreme Gradient Boosting(XGB),landslide models were constructed.Comparative analysis and evaluation of the model were conducted through statistical indices and receiver operating characteristic(ROC)curves.The results showed that LR,RF,SVM,and XGB models have good predictive performance for landslide susceptibility,with the area under curve(AUC)values of 0.752,0.965,0.996,and 0.998,respectively.XGB model had the highest predictive ability,followed by RF model,SVM model,and LR model.The frequency ratio(FR)accuracy of LR,RF,SVM,and XGB models was 0.775,0.842,0.759,and 0.822,respectively.RF and XGB models were superior to LR and SVM models,indicating that the integrated algorithm has better predictive ability than a single classification algorithm in regional landslide classification problems.

Research on the Assessment System of Computational Mechanics Courses Based on the TOPSIS Entropy Weight Model

This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qualitative evaluation methods.The system not only pays attention to students’practical operation and theoretical knowledge mastery but also puts special emphasis on the cultivation of students’innovative abilities.In order to realize a comprehensive and objective evaluation,the assessment and evaluation method of the entropy weight model combining TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)multi-attribute decision analysis and entropy weight theory is adopted,and its validity and practicability are verified through example analysis.This method can not only comprehensively and objectively evaluate students’learning outcomes,but also provide a scientific decision-making basis for curriculum teaching reform.The implementation of this diversified course evaluation system can better reflect the comprehensive ability of students and promote the continuous improvement of teaching quality.

A risk assessment method considering risk attributes and work safety informational needs and its application

The technological revolution has spawned a new generation of industrial systems,but it has also put forward higher requirements for safety management accuracy,timeliness,and systematicness.Risk assessment needs to evolve to address the existing and future challenges by considering the new demands and advancements in safety management.The study aims to propose a systematic and comprehensive risk assessment method to meet the needs of process system safety management.The methodology first incorporates possibility,severity,and dynamicity(PSD)to structure the“51X”evaluation indicator system,including the inherent,management,and disturbance risk factors.Subsequently,the four-tier(risk point-unit-enterprise-region)risk assessment(RA)mathematical model has been established to consider supervision needs.And in conclusion,the application of the PSD-RA method in ammonia refrigeration workshop cases and safety risk monitoring systems is presented to illustrate the feasibility and effectiveness of the proposed PSD-RA method in safety management.The findings show that the PSD-RA method can be well integrated with the needs of safety work informatization,which is also helpful for implementing the enterprise's safety work responsibility and the government's safety supervision responsibility.

Regional Climate Damage Quantification and Its Impacts on Future Emission Pathways Using the RICE Model

This study quantified the regional damages resulting from temperature and sea level changes using the Regional Integrated of Climate and Economy(RICE)model,as well as the effects of enabling and disabling the climate impact module on future emission pathways.Results highlight varied damages depending on regional economic development and locations.Specifically,China and Africa could suffer the most serious comprehensive damages caused by temperature change and sea level rise,followed by India,other developing Asian countries(OthAsia),and other high-income countries(OHI).The comprehensive damage fractions for China and Africa are projected to be 15.1%and 12.5%of gross domestic product(GDP)in 2195,with corresponding cumulative damages of 124.0 trillion and 87.3 trillion United States dollars(USD)from 2005 to 2195,respectively.Meanwhile,the comprehensive damage fractions in Japan,Eurasia,and Russia are smaller and projected to be lower than 5.6%of GDP in 2195,with cumulative damages of 6.8 trillion,4.2 trillion,and 3.3 trillion USD,respectively.Additionally,coastal regions like Africa,the European Union(EU),and OHI show comparable damages for sea level rise and temperature change.In China,however,sea level-induced damages are projected to exceed those from temperature changes.Moreover,this study indicates that switching the damage modules on or off affects the regional and global emission trajectories,but the magnitude is relatively small.By 2195,global emissions under the experiments with all of the damage modules switched off,only the sea level damage module switched on,and only the temperature damage module switched on,were 3.5%,2.3%and 1.2%higher than those with all of the damage modules switched on,respectively.

Study of The Technical Index of Online Learning Behavior Analysis of Nursing Majors on The Superstar Platform Based on The Kirkpatrick Evaluation Model

Objective:To analyze the technical indexes of students’online learning behavior analysis based on Kirkman’s evaluation model,sort out the basic indexes of online learning behavior,and extract scientific and efficient evaluation indexes of online learning effect through statistical analysis.Methods:The online learning behavior data of Physiology of nursing students from 2021-2023 and the first semester of 22 nursing classes(3 and 4)were collected and analyzed.The preset learning behavior indexes were analyzed by multi-dimensional analysis and a correlation analysis was conducted between the indexes and the final examination scores to screen for the dominant important indexes for online learning effect evaluation.Results:The study found that the demand for online learning of nursing students from 2021-2023 increased and the effect was statistically significant.Compared with the stage assessment results,the online learning effect was statistically significant.Conclusion:The main indicators for evaluating and classifying online learning behaviors were summarized.These two indicators can help teachers predict which part of students need learning intervention,optimize the teaching process,and help students improve their learning behavior and academic performance.

Towards Automated Assessment of Learning Management Systems in Higher Education Institutions in Zambia

Zambia like any other country in most African regions is still grappling with the dynamics of harnessing technology for the betterment of Higher Education. The onset of the Covid 19 pandemic brought a test for the preparedness of the Zambian Higher Education Institutions (HEIs) in harnessing technology for pedagogical activities. As countries worldwide switched to electronic learning during the pandemic, the same could not be said for Zambian HEIs. Zambian HEIs struggled to conduct pedagogical activities on learning management platforms. This study investigated the factors affecting the implementation and assessment of learning Management systems in Zambia’s HEIs. With its focus on assessing: 1) system features, 2) compliance with regulatory standards, 3) quality of service and 4) technology acceptance as the four key assessment areas of an LMS, this article proposed a model for assessing learning management systems in Zambian HEIs. To test the proposed model, a software tool was also developed.

Strategic Assessment Model and Its Application:a Case Study

Accurate and effective assessment of strategic alternatives of an organization directly affects the decision-making and execution of its deve1opment strategy. In evaIuation of strategic alternatives , relevant elements from both interna1 and external environments of an organization must be considered. In this paper we use strategic assessment model to evaluate strategic alternatives of an air-conditioning company. Strategic objectives and alternatives of the company are developed through analysis of the competitive environment, key competitors and internal conditions. The environment factors are classified into internal, task, and general opportunities and threats. Ana1ytical hierarchy process, subjective probabilities, entropy concept, and utility theory are used to enhance decision-maker's ability in evaluating strategic alternatives. The evatuation results show that the most effective strategic alternative for the company is to reduce types of products, concentrate its effort on producing window-type and cupboard-type air-conditioners, enlarge the production scale, and pre-empt the market. The company has made great progress by implementing this alternative. We conc1ude that SAM is an appropriate tool for eva1uating strategic alternatives.

Financial risk assessment model based on big data

Conventional financial risk assessment is not accurate and its adaptive assessment ability is low.In order to solve this problem,a financial risk assessment model based on big data is proposed.In this method,the quantitative analysis method is adopted to analyze the explanatory variable model and the control variable model of financial risk assessment.The market-to-book ratio,asset–liability ratio,cash flow ratio and financing structure model are adopted as constraint parameters to construct a big data analysis model for financial risk assessment.On this basis,the adaptive fuzzy weighted control method is adopted for information fusion of financial risk assessment data and big data classification,and the asset income control and innovative evaluation model are adopted for linear planning and square fitting during financial risk assessment.Based on the intervention factors of financial market participants,quantitative regression analysis is performed,and according to the economic game theory,big data analysis and prediction of financial risk assessment are performed through the regression analysis method.Then the big data fusion and clustering algorithms are adopted for financial risk assessment.The simulation results show that this method can provide a relatively high accuracy in financial risk assessment,and has relatively strong adaptive evaluation capability to the risk coefficient,so it has a good application value in the prevention and control of risk factors in financial systems.

Decentralised energy and its performance assessment models

Energy development concerns not only the development of renewable energies but also the shift from centralised to clean,decentralised power generation.The development of decentralised energy(DE)is a core part of the energy and economic strategies being adopted around the world that drives the progress toward a highly sustainable future.This paper reviews the concepts,development status,trends,benefits and challenges of DE systems and analyses the existing models and methods for assessing the performance of these systems.A hierarchical decision model for evaluating the performance of DE systems is also constructed based on the framework of multiple criteria decision analysis,which considers the identification,definition and assessment grade of decision criteria.The evidential reasoning approach is applied to aggregate assessment information in a case study of the implementation of an intelligent decision system.Sensitivity and trade-off analyses are also conducted to show how the proposed model can be used to support decision making in DE systems.

Analysis of a Conceptual Model and Assessment of the e-Procurement System in Bangladesh

The public procurement system in Bangladesh has been running by traditional manual process under the flagship of Public Procurement Act (PPA 2006) and Public Procurement Rules (PPR 2008). Public procurement agencies have been facing challenges in this manual tendering system. To overcome this problem and to bring reality to the “Digital Bangladesh” slogan, the Government of Bangladesh introduced the e-Procurement system under the e-GP (Electronic Government Procurement) guideline 2011. After the inception of e-procurement, there is no e-procurement assessment model to improve the e-GP system. The purpose of this research is to develop a conceptual framework and to design an e-procurement assessment model. With this view, we have considered one of the biggest entity Roads and Highways Department (RHD) of the Government of Bangladesh, for field study. Mixed methods along with FGD (Focus Group Discussion), KII (Key Informant Interview), and survey questionnaires are used to collect data from RHD, and then Statistical Package for Social Science (SPSS) software is used for regression analysis and hypothesis testing to develop the e-Procurement assessment model. The novel contribution of the study lies in the test of the hypothesis that focuses on developing the conceptual model of the e-procurement assessment system in Bangladesh. Findings of the study are essential for all Procurement Entity (PE) and suppliers i.e. contractors of RHD who are engaged in the construction of the infrastructure project development project.