Comprehensive Benefit Evaluation Method of Mountain Flood Disaster Prevention and Control in Jiangxi Province Based on Matter-Element Extension Model

Taking the mountain flood disaster prevention and control project in Jiangxi province as the research object, the evaluation period is 2010-2015, and 29 evaluation indexes are selected from 7 aspects. In this paper, game theory is introduced to optimize the subjective and objective weights of the index, and the comprehensive weights are obtained by normalization. The results show that the eigenvalues of the grade variables of benefit evaluation decreased from 3.43 to 2.03, indicating that the project of mountain flood disaster prevention and control in Jiangxi province brings into play the benefits year by year, and the eigenvalues tend to decrease steadily after 2012, it is consistent with the changes of various engineering measures and non-engineering measures in the project.

Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.

E-government maturity model and its evaluation

In order to ensure e-government construction healthily,rapidly and orderly develop,an e-government maturity model（EGMM）is proposed based on a software capability maturity model （CMM）and a project management maturity model（PMMM）. Five levels of maturity in e-government development process are constructed,which include network infrastructure,information serving,information interactive,information sharing and comprehensive integrating.An index system of e-government maturity is put forward,and then an e-government maturity levels evaluation method is presented,which can provide clear,detailed and efficient decision information and investment directions of e-government for decision-makers.The EGMM and its maturity evaluation method are helpful for improving the construction of e-government.

Modeling and performance evaluation of QoS-aware job scheduling of computational grids

To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net （SHLPN） model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.

Similarity evaluation model for the internal defect detection of strip steel

An internal defect meter is an instrument to detect the internal inclusion defects of cold-rolled strip steel.The detection accuracy of the equipment can be evaluated based on the similarity of the multiple detection data obtained for the same steel coil.Based on the cosine similarity model and eigenvalue matrix model,a comprehensive evaluation method to calculate the weighted average of similarity is proposed.Results show that the new method is consistent with and can even replace artificial evaluation to realize the automatic evaluation of strip defect detection results.

Evaluation of the International Vehicle Emission (IVE) model with on-road remote sensing measurements

Intemational Vehicle Emissions （IVE） model funded by U.S. Environmental Protection Agency （USEPA） is designed to estimate emissions from motor vehicles in developing countries. In this study, the IVE model was evaluated by utilizing a dataset available from the remote sensing measurements on a large number of vehicles at five different sites in Hangzhou, China, in 2004 and 2005. Average fuel-based emission factors derived from the remote sensing measurements were compared with corresponding emission factors derived from IVE calculations for urban, hot stabilized condition. The results show a good agreement between the two methods for gasoline passenger cars＇ HC emission for all 1VE subsectors and technology classes. In the case of CO emissions, the modeled results were reasonably good, although systematically underestimate the emissions by almost 12%-50% for different technology classes. However, the model totally overestimated NOx emissions. The IVE NOx emission factors were 1.5-3.5 times of the remote sensing measured ones. The IVE model was also evaluated for light duty gasoline truck, heavy duty gasoline vehicles and motor cycles. A notable result was observed that the decrease in emissions from technology class State II to State I were overestimated by the IVE model compared to remote sensing measurements for all the three pollutants. Finally, in order to improve emission estimation, the adjusted base emission factors from local studies are strongly recommended to be used in the IVE model.

Application of Projection Pursuit Evaluation Model Based on Real-Coded Accelerating Genetic Algorithm in Evaluating Wetland Soil Quality Variations in the Sanjiang Plain, China

A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.

Can We Estimate the Impacts of Fixed Links Using Current Transport Models?Experiences from Concept Evaluations of Fixed Links on E39

Transport analysis and impact evaluations are important input for decisions about infrastructure projects.The impacts on transport from fjord crossing tunnels or bridges are the foundation for the cost benefit analysis,and also the basis for estimating the income from toll collection.Based on experiences from concept evaluations of several fixed link projects on E39,and an ongoing overall analysis,we question the results from transport analysis made by the official tools for such analysis:the RTM(regional transport model)which estimates the demand for trips below 10 km,the NTM(national transport model),for trips of 10 km or more,and the freight transport model.Both the NTM and the freight transport model are integrated in the RTM in the net assignment stage.We will demonstrate strengths and weaknesses in the transport models by showing contra intuitive or questionable results using the model as it is.The following questions arose as the initial results from the transport model were presented:Are the transport models able to capture immediate as well as long-term impacts?How would different assumptions about the monetary costs on these projects affect the forecasted demand and the cost benefit analysis?Are there other and wider ranges of impacts,if the analysis covers the total coastal highway as a whole,compared to evaluating impacts of each fixed link project individually?Do we have enough data to include transport effects of wider impacts of the fixed link projects?We had to deal with these questions in the concept evaluations carried out for the various fixed links project and in the current overall evaluation.We would like to suggest improvements in the analysis tools and emphasize requirements for knowledge about impacts of fixed links projects.

Study on the Construction and Evaluation System of Clinical Midwifery Teaching Faculty under the New Nursing Model

Objective:To explore the impact of the construction of a clinical midwifery teaching faculty and the development of an evaluation system under the new nursing model on the current teaching quality.Methods:From July 2022 to March 2023,10 clinical teaching teachers and 20 midwifery interns from Beijing Anzhen Hospital affiliated with Capital Medical University were selected as the subjects of this study.The clinical teaching teachers and midwifery interns were divided into an observation group and a control group,with each group including 5 clinical teaching teachers and 10 midwifery interns.The observation group received daily management and evaluation under the new nursing model,while the control group received management and evaluation under the traditional nursing model.The teaching quality evaluation of clinical midwifery teaching teachers by midwifery interns,the exit exam scores of midwifery interns,and the scores of clinical teaching teachers’internship lectures and teaching rounds were compared between the two groups.Results:In the observation group,the scores for teaching attitude,teaching skills,and teaching management in the teaching quality evaluation of clinical midwifery teaching teachers were higher than those in the control group.The professional theory scores(91.28±3.64)and overall nursing comprehensive scores(92.56±4.38)of midwifery interns in the observation group were higher than those of midwifery interns in the control group(81.58±2.27 and 80.29±3.33,respectively).The scores for internship lectures(89.32±4.15)and teaching rounds(90.64±5.52)in the observation group were also significantly higher than those in the control group(80.46±3.28 and 81.24±4.38,respectively),and the differences were statistically significant(P<0.05).Conclusion:The management of the clinical midwifery teaching faculty under the new nursing model effectively improved the quality of clinical teaching.It significantly enhanced the teaching effectiveness of clinical teaching teachers and the proficiency of midwifery interns in clinical operations,making it worthy of promotion and use.

High-resolution modeling and evaluation of ozone air quality of Osaka using MM5-CMAQ system

High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with complex terrain and land-use. This study uses Community Multiscale Air Quality （CMAQ） model coupled with MM5 mesoscale model for a comprehensive analysis to assess the suitability of such high-resolution modeling system in predicting ozone air quality in the complex terrains of Osaka, Japan. The 1-km and 3-kin grid domains were nested inside a 9-km domain and the domain with 1-km grid covered the Osaka region. High-resolution Grid Point Value-Mesoscale Model （GPV-MSM） data were used after suitable validation. The simulated ozone concentrations were validated and evaluated using statistical metrics using performance criteria set for ozone. Daily maxima of ozone were found better simulated by the 1-krn grid domain than the coarser 9-km and 3-km domains, with the maximum improvement in the mean absolute gross error about 3 ppbv. In addition, 1-km grid results fared better than other grids at most of the observation stations that showed noticeable differences in gross error as well as correlation. These results amply justify the use of the integrated high-resolution MM5-CMAQ modeling system in the highly urbanized region, such as the Osaka region, which has complex terrain and land-use.

Catastrophe theory-based risk evaluation model for water and mud inrush and its application in karst tunnels

This paper presents a risk evaluation model of water and mud inrush for tunnel excavation in karst areas.The factors affecting the probabilities of water and mud inrush in karst tunnels are investigated to define the dangerousness of this geological disaster.The losses that are caused by water and mud inrush are taken into consideration to account for its harmfulness.Then a risk evaluation model based on the dangerousness-harmfulness evaluation indicator system is constructed,which is more convincing in comparison with the traditional methods.The catastrophe theory is used to evaluate the risk level of water and mud inrush and it has great advantage in handling problems involving discontinuous catastrophe processes.To validate the proposed approach,the Qiyueshan tunnel of Yichang-Wanzhou Railway is taken as an example in which four target segments are evaluated using the risk evaluation model.Finally,the evaluation results are compared with the excavation data,which shows that the risk levels predicted by the proposed approach are in good agreements with that observed in engineering.In conclusion,the catastrophe theory-based risk evaluation model is an efficient and effective approach for water and mud inrush in karst tunnels.

Evaluation of NASA GISS Post-CMIP5 Single Column Model Simulated Clouds and Precipitation Using ARM Southern Great Plains Observations

The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies （GISS） Model E2 atmospheric general circulation model （GCM; post-CMIP5, hereafter P5）. In this study, single column model （SCM_P5） simulated cloud fractions （CFs）, cloud liquid water paths （LWPs） and precipitation were compared with Atmospheric Radiation Measurement （ARM） Southern Great Plains （SGP） groundbased observations made during the period 2002-08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM_P5-simulated CFs and LWPs showed a moderate increase （10%-20%） but precipitation increased significantly （56%）, which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.

Evaluation of Simulated CO_2 Concentrations from the CarbonTracker-Asia Model Using In-situ Observations over East Asia for 2009–2013

The CarbonTracker(CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO_2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO_2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO_2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO_2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model's performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO_2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within-0.3 and 1.3 ppm, except for inland stations(7.7 ppm).

Shale gas production evaluation framework based on data-driven models

Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system.Sharp decline of gas production has been widely observed in shale gas reservoirs.How to forecast shale gas production is still challenging due to complex fracture networks,dynamic fracture properties,frac hits,complicated multiphase flow,and multi-scale flow as well as data quality and uncertainty.This work develops an integrated framework for evaluating shale gas well production based on data-driven models.Firstly,a comprehensive dominated-factor system has been established,including geological,drilling,fracturing,and production factors.Data processing and visualization are required to ensure data quality and determine final data set.A shale gas production evaluation model is developed to evaluate shale gas production levels.Finally,the random forest algorithm is used to forecast shale gas production.The prediction accuracy of shale gas production level is higher than 95%based on the shale gas reservoirs in China.Forty-one wells are randomly selected to predict cumulative gas production using the optimal regression model.The proposed shale gas production evaluation frame-work overcomes too many assumptions of analytical or semi-analytical models and avoids huge computation cost and poor generalization for numerical modelling.

Hydrocarbon expulsion model and resource potential evaluation of high-maturity marine source rocks in deep basins:Example from the Ediacaran microbial dolomite in the Sichuan Basin,China

Hydrocarbon expulsion features and resource potential evaluation of source rocks are crucial for the petroleum exploration.High-maturity marine source rocks have not exhibited a hydrocarbon expulsion mode owing to the lack of low-maturity source rocks in deep petroliferous basins.We considered the Ediacaran microbial dolomite in the Sichuan Basin,the largest high-maturity marine gas layer in China,to exhibit a method that quantitatively characterizes the hydrocarbon expulsion of high-maturity marine source rocks.The experiment of fluid inclusion,rock pyrolysis,and vitrinite reflectance(Ro)of 119 microbial dolomite core samples obtained from the Dengying Formation were performed.A hydrocarbon expulsion model of high-maturity source rock was established,and its resource potential was evaluated.The results showed that the Ediacaran microbial dolomite in the Sichuan Basin is a good source rock showing vast resource potential.The hydrocarbon expulsion threshold is determined to be vitrinite reflectance at 0.92%.The hydrocarbon expulsion intensities in the geologic history is high with maximum of 1.6×10^(7)t/km^(2).The Ediacaran microbial dolomite expelled approximately 1.008×10^(12)t of hydrocarbons,and the recoverable resource was 1.5×10^(12)m^(3).The region can be categorized into areasⅠ,Ⅱ,Ⅲ,andⅣ,in decreasing order of hydrocarbon expulsion intensity.Areas with a higher hydrocarbon expulsion intensity have a lower drilling risk and should be prioritized for exploration in the orderⅠ>Ⅱ>Ⅲ>Ⅳ.Two areas,northern and central parts of Ediacaran in the Sichuan Basin,were selected as prospects which had the drilling priority in the future gas exploration.The production data of 55 drilled wells verified the high reliability of this method.This model in this study does not require low-maturity samples and can be used for evaluating high-maturity marine source rocks,which has broad applicability in deep basins worldwide.

Ecological Security Evaluation Algorithm for Resource-Exhausted Cities Based on the PSR Model

Today,resource depletion threatens a number of resource-based cities in China.The ecological security problem caused by the long-term exploitation of natural resources is a key issue to be solved in the development of resource-exhausted cities.Using 23 indicators,this study evaluated the ecological security status and development trends of 21 resource-exhausted cities in China from 2011 to 2017.The results showed that from 2011 to 2015,the overall ecological security of this type of city was low,with over 60%of the cities at an unsafe level.However,ecological security improved rapidly after 2016,and by 2017,all of the cities had reached the critical safety level.The top 10 indicators of ecological security included industrial sulfur dioxide emissions,water supply,agricultural fertilizer application,and forest coverage.These 10 indicators’cumulative contribution to ecological security was 48.3%;among them,reducing industrial sulfur dioxide emissions contributed the most at 5.7%.These findings can help governments better understand the ecological security status of resource-exhausted cities,and it can provide a reference for the allocation of funds and other resources to improve the ecological safety of these cities.

Redesigning the Model of Book Evaluation in the Polish Performance-based Research Funding System

Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we reconstruct the framework of the 2010 and 2018 models of book evaluation in Poland within the performance-based research funding system. Findings: For almost 20 years the book evaluation system in Poland has been based on the verification of various technical criteria(e.g. length of the book). The new 2018 model is based on the principle of prestige inheritance(a book is worth as much as its publisher is) and is inspired by the publisher list used in the Norwegian Model. In this paper, we argue that this solution may be a more balanced policy instrument than the previous 2010 model in which neither the quality of the publisher nor the quality of the book played any role in the evaluation.Research limitations: We work from the framework of the 2018 model of book evaluation specified in the law on higher education and science from 20 July 2018, as implementation acts are not available yet. Practical implications: This study may provide a valuable point of reference on how structural reforms in the research evaluation model were implemented on a country level. The results of this study may be interesting to policy makers, stakeholders and researchers focused on science policy. Originality/value: This is the very first study that presents the new framework of the Polish research evaluation model and policy instruments for scholarly book evaluation. We describe what motivated policy makers to change the book evaluation model, and what arguments were explicitly raised to argue for the new solution.

Comprehensive evaluation of 5G+smart distribution network based on combined weighting method-cloud model

With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.

Advantages of the latest Los Alamos Sea-Ice Model(CICE):evaluation of the simulated spatiotemporal variation of Arctic sea ice

The Los Alamos Sea-Ice Model(CICE)is one of the most popular sea-ice models.All versions of it have been the main sea-ice module coupled to climate system models.Therefore,evaluating their simulation capability is an important step in developing climate system models.Compared with observations and previous versions(CICE4.0 and CICE5.0),the advantages of CICE6.0(the latest version)are analyzed in this paper.It is found that CICE6.0 has the minimum interannual errors,and the seasonal cycle it simulates is the most consistent with observations.CICE4.0 overestimates winter sea-ice and underestimates summer sea-ice severely.Meanwhile,the errors of CICE5.0 in winter are larger than for the other versions.The main attention is paid to the perennial ice and the seasonal ice.The spatial distribution of root-mean-square errors indicates that the simulated errors are distributed in the Atlantic sector and the outer Arctic.Both CICE4.0 and CICE5.0 underestimate the concentration of the perennial ice and overestimate that of the seasonal ice in these areas.Meanwhile,CICE6.0 solves this problem commendably.Moreover,the decadal trends it simulates are comparatively the best,especially in the central Arctic sea.The other versions underestimate the decadal trend of the perennial ice and overestimate that of the seasonal ice.In addition,an index used to objectively describe the difference in the spatial distribution between the simulation and observation shows that CICE6.0 produces the best simulated spatial distribution.

Modeling and Experimental Analysis of Roughness Effect on Ultrasonic Nondestructive Evaluation of Micro-crack

A high-precision evaluation of ultrasonic detection sensitivity for a micro-crack can be restricted by a corroded rough surface when the surface microtopography is of the same order of magnitude as the crack depth.In this study,a back-surface micro-crack is considered as a research target.A roughness-modified ultrasonic testing model for micro-cracks is established based on a multi-Gaussian beam model and the principle of phase-screen approximation.The echo signals of micro-cracks and noises corresponding to different rough front surfaces and rough back surfaces are obtained based on a reference reflector signal acquired from a two-dimensional simulation model.Further compari-son between the analytical and numerical models shows that the responses of micro-cracks under the effects of dif-ferent corroded rough surfaces can be accurately predicted.The numerical and analytical results show that the echo signal amplitude of the micro-crack decreases significantly with an increase in roughness,whereas the noise ampli-tude slightly increases.Moreover,the effect of the rough front surface on the echo signal of the micro-crack is greater than that of the rough back surface.When the root-mean-square(RMS)height of the surface microtopography is less than 15μm,the two rough surfaces have less influence on the echo signals detected by a focused transducer with a frequency of 5 MHz and diameter of 6 mm.A method for predicting and evaluating the detection accuracy of micro-cracks under different rough surfaces is proposed by combining the theoretical model and a finite element simulation.Then,a series of rough surface samples containing different micro-cracks are fabricated to experimentally validate the evaluation method.