Level Evaluation Method Research Articles

Research on the evaluation of the manual manipulation level of a student pilot in a typical scene

The traditional evaluation method of student pilots ' manual manipulation level relies too much on teachers' subjective judgment. A quantitative evaluation method based on flight data is proposed to compensate for the shortcoming of the traditional method. According to the theory of the core competence of a pilot, the evaluation index system of manual manipulation level of student pilots in a typical scene is constructed. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) categorizes pilot manipulation levels into four grades. The improved support vector machine (SVM) model with particle swarm optimization (PSO) is trained using index data and rank labels as inputs. The data is split into training and verification sets with the cross-validation method. The training data for Guanghan Airport are taken as an example to verify the model's reliability. The model's prediction accuracy is compared with that of K-nearest neighbor and random forest models. The results show that the PSO-SVM model has higher prediction accuracy. The research can provide a theoretical reference for quantitatively evaluating manual manipulation levels and improving flight training quality.

Creep-fatigue damage level evaluation based on the relationship between microstructural evolution and mechanical property degradation

Creep-fatigue interaction is identified as a primary failure mode for components operating under high temperatures. As operational durations extend, this interaction not only alters the material's microstructures but also initiates a gradual degradation in mechanical properties, significantly impacting its deformation and damage behaviors. In this work, the dynamic microstructural evolution of GH4169 superalloy during creep-fatigue was elucidated via qualitative characterization, and damage level evaluation method was subsequently developed by bridging microstructure degradation to mechanical property degradation. Creep-fatigue tests were performed at 650 °C with various tensile holding times and were interrupted at lifetime fractions of 10 %, 50 % and 80 % for further analysis and tensile evaluations. Results revealed that the prolonged exposure to holding times induced the coarsening of γ″ precipitates alongside an increase in low-angle grain boundaries, culminating a reduction in creep-fatigue strength. The development of voids and cracks exacerbated the degradation of elongation, leading to a hybrid fracture mode encompassing both intergranular and transgranular cracking paths. Synthesizing microstructural evolutions to qualitatively categorize diverse degradation levels imparted a robust physical basis for damage evaluation. A mapping model was established to correlate the average kernel average misorientation (micro-degradation indicator) with the tensile plastic strain energy density (macro-degradation indicator). The damage level evaluation method was endowed with quantitative metrics utilizing this model, and its generality was additionally validated in P92 steel. This work offers an insight into the quantitative damage evaluations of creep-fatigue-induced degradations in materials, thereby providing a theoretical basis for the development of operation management and inspection plans of components.

Ultimate water level and deformation failures of the artificial dam in the coal mine underground reservoir

Coal mine underground reservoirs provide a new choice for the protection and utilization of water resources. This paper takes the underground reservoir of Wulanmulun Mine as the background, and takes the MB-1# artificial dam in the goaf of 31104–31116 working face of 3–1 coal seam as the research object. The theoretical model of artificial dam is established by elastic–plastic two-way slab theory, and the theoretical mechanical analysis and calculation are carried out. A similitude physical model for the coal mine underground reservoir was built by using the self-developed nested dual-dynamic-pressure similitude simulation testing system. Later, the mechanical response and deformation failure features of the artificial dam under different water pressure values were analyzed and the ultimate water pressure was determined. In addition, FLAC3D was used to determine the stress-seepage field-coupling model for the artificial dam. Using this model, the influence of water pressure on the multi-load coupling effect of the artificial dam and coal pillar dam was characterized. The dam form is optimized and the safety water level evaluation method of the dam body is proposed. The research results are as follows: (1) Based on the theory of elastic–plastic two-way slab, the theoretical analysis model of artificial dam is established, the expression of the ultimate water level function of artificial dam is derived, and the theoretical ultimate water head is determined to be 18.2 m (2) The seepage law of underground reservoir under different water pressures is obtained, and the ultimate water pressure of the model is determined to be 11.43 kPa. (3) It is clarified that the failure modes of the artificial dam are seepage failure and mechanical failure, and it is revealed that the groove area is the weakest position where the dam is most vulnerable to failure. In view of the failure modes of the dam, the I-shaped structure artificial dam is proposed. (4) A safe water level assessment method is proposed for the constructed artificial dam. According to the analysis of on-site monitoring data of MB-1# dam, the actual water level in the reservoir is within the allowable water level range of the artificial dam, and the whole reservoir is in a stable and relatively safe state at present. The reliability of this assessment method has been verified.

A cognitive level evaluation method based on machine learning approach and Bloom of taxonomy for online assessments

Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners’ cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners’ cognitive levels during the online learning process. However, most of the currently used techniques for evaluating cognitive levels rely on labour-intensive and time-consuming manual coding. In this study, we explore the machine learning (ML) algorithms and taxonomy of Bloom’s cognitive levels to explore features that affect learner’s cognitive level in online assessments and the ability to automatically predict learner’s cognitive level and thus, come up with a recommendation or pedagogical intervention to improve learner’s acquisition. The analysis of 15,182 learners’ assessments of a specific learning concept affirms the effectiveness of our approach. We attain an accuracy of 82.21% using ML algorithms. These results are very encouraging and have implications for how automated cognitive-level analysis tools for online learning will be developed in the future.

Synergistic regional emission reductions in China: Network evolution, spatial and temporal characteristics, and driving factor

Synergistic regional emission reduction (SRER) is an important part of the strategy to achieve carbon neutrality. In this paper, a system efficiency value-added model is proposed to measure the strength of SRER network relationships for 40,186 sets of city pairs and the SRER levels of 284 cities in China from 2011 to 2021. Subsequently, the evolution characteristics of the SRER network, the spatial and temporal characteristics of urban SRER levels, and the driving factors of the SRER network evolution are further analyzed. The results are as follows: SRER network is shifting from a fan-shaped network pattern of “three-region clustering and sporadic coverage” to a shuttle-shaped nested network pattern of “east-west linkage and multi-region support”. Time series analysis found that urban SRER level in China showed fluctuating growth characteristics during the study period. Spatial analysis reveals that the spatial autocorrelation of urban SRER level is decreasing, and the spatial distribution range is expanding towards the southwest. Emission reduction comparative advantages (CAER), green innovation division of labor (GIDL) and urban economic linkages (LCEL) are driver factors of SRER network evolution. This study proposes an evaluation method for the urban SRER level from network relationships perspective. Subsequently, network evolution characterization, spatial and temporal characterization, and driving factor analysis were conducted. The results of the study provide important theoretical guidance and inspiration for grasping the current status and enhancement paths of China's urban SRER level.

Evaluation method of sustainable utilisation level of agricultural land resources based on double difference method

Evaluation method of sustainable utilisation level of agricultural land resources based on double difference method

Research on evaluation system and method of MES system for intelligent manufacturing

Abstract With the development of informatization and digitalization, the transformation of intelligent manufacturing has become the focus. This paper builds an evaluation system based on the scientific evaluation method of the development level of smart manufacturing and the real demand situation. It establishes an evaluation model of intelligent manufacturing MES systems by combining the GA-BP algorithm. Then, a SeqGAN generative adversarial network is used to expand the real samples. The evaluation model was trained and validated by constructing a training model through the BP neural network, taking the sample data of evaluation indexes as the network input and the seven labels from Industry 1.0 to Industry 4.0 as the network output. The results show that the classification accuracy of the model is above 98%, and all of them have achieved good results. In the actual case evaluation, it is judged that the intelligent manufacturing MES system of Company Z is in the range of industry 3.0 to 3.5, and this result is very close to the manual evaluation of the factory field survey. The synthesis shows that the model is reasonable and effective and has important guiding significance for the evaluation of enterprise intelligent manufacturing MES systems.

An evaluation method of sustainable development level of agricultural economy under the economic new normal

An evaluation method of sustainable development level of agricultural economy under the economic new normal

Solid-liquid multiphase flow and erosion in the energy storage pump using modified drag model and erosion model

In order to achieve the carbon neutrality, the wind and solar power have greatly developed in recent years, which leads to a challenge of unpredictability and intermittence for the power grid. A new concept of energy storage pump station is proposed, which uses the large pump to store water from the downstream reservoir to the upstream reservoir in cascade hydropower stations, and consumes the electricity from wind and solar power. However, due to the high sediment content of rivers in China, erosion is a critical issue that damages components and shortens the operational life of energy storage pumps. In this work, an improved calculation model based on modified drag model and modified erosion model is established to investigate the solid-liquid two-phase flow and erosion characteristics in an energy storage pump. In the calculation model, a modified drag model by considering the effect of turbulence intensity is proposed, and a modified erosion model by considering the effect of particle Stokes number is proposed. An erosion experiment on a 90° elbow pipe is used to validate the accuracy of the improved calculation model, and the maximum error of erosion rate between experiment and calculation is 1.86 %. Then, solid-liquid flow and erosion in a centrifugal pump with the specific speed of 102 are numerically calculated under particle sizes of 0.01 mm, 0.05 mm, 0.1 mm, 0.25 mm, 0.5 mm, 0.75 mm and 1 mm, respectively. Results show that particles tend to accumulate at the hub and blade pressure side as particle size increases, which results in a rise in non-uniformity of particle distribution in impeller. Meanwhile, the non-uniformity of erosion in impeller strengthens with particle size increase, and erosion in impeller under particle size of 1 mm is 1245 times more than that under particle size of 0.05 mm. A new evaluation method of effect level of parameter on erosion of a centrifugal pump by using Stp = 1 is proposed. When Stp < 1, particle impact velocity is the primary factor on erosion, and the average erosion rate decreases with particle size increase. When Stp > 1, the particle number impacting the wall is the primary factor on erosion, and the average erosion rate increases with particle size increase.

Evaluation of the Level of Farmland Infrastructure Based on High-Resolution Images of UAV

The evaluation of the level of farmland infrastructure is a necessary objective condition for the use of arable land and agricultural development. In order to investigate the evaluation index system and method of farmland infrastructure level, this article uses the Kenli District of the Yellow River Delta as the research region. In the study region, six typical observation sample areas are chosen. Each area receives high-resolution UAV photos, which are then used to extract information about the farmland infrastructure of the field. A farming infrastructure evaluation index system was built, consisting of 10 indexes for four aspects, including farmland roads, field plots, ditches, and forest belts, using the 100 m by 100 m grid method to divide the evaluation units. The comprehensive index technique was used to calculate the farmland infrastructure score of each unit and identify the degree of excellent, good, and poor farmland infrastructure. The weight of each indication was decided by the hierarchical analysis method. There were 20 excellent grades, 77 good grades, and 29 poor grades among the 126 evaluation units in the study area, with excellent and good grades accounting for 79.13% and area proportions of 14.29%, 64.84%, and 20.87%, respectively. Among the six sample areas, sample areas E and F had the highest percentages of excellent grades, sample area A had 82.62% of the good grades, and all sample areas except A and C had a percentage of poor grades that was higher than 20%. Regularity of the fields, average size of the fields, and the agricultural plot’s slope are the dominant indexes of farmland infrastructure in each observation sample area, and the indexes of the ratio of the perimeter of roads to the perimeter of fields, density of ditches, and the ratio of area of agricultural forest networks to area of fields need to be optimized and improved. The spatial distribution of each grade differs significantly. The evaluation results are consistent with the real situation in the study region and have positive reference meaning for the development and management of farming infrastructure, according to the study’s proposed evaluation system and methodology.

Novel cadmium (II) N2O2‐Schiff base compounds: X‐ray crystal structure, Hirshfeld surface study, thermal behavior, antimicrobial, DNA cleavage power, antioxidant, and cytotoxicity activity

A new N2O2‐tetradentate Schiff base ligand entitled as N,N′‐((ethane‐1,2‐diybis [oxy])bis (ethan‐2,1‐diyl))bis(3‐(4‐methoxyphenyl)prop‐2‐en‐1‐imine was prepared by direct reaction between 3‐(4‐methoxyphenyl)‐2‐propenal and 1,8‐diamino‐3,6‐dioxaoctane. After characterization of the ligand, some novel cadmium coordination compounds formulated as CdLX2 (X: Cl−, Br−, I−, N3−, SCN−and NO3−) were synthesized and characterized by physical and spectral techniques. Typically crystal structure of cadmium nitrate coordination compound was determined suggesting crystallization in monoclinic system (with space group of I2/a) and a coordination geometry of square anti‐prism around the Cd (II) ion. Moreover, CdLBr2 and CdLI2 compounds were prepared in nanostructured dimensions by sonochemical method confirmed by SEM, EDX, and XRD techniques. In continuation, thermal behavior investigation of the compounds including thermal stabilities, thermal decomposition steps, and thermo‐kinetic parameters was performed based on Coats‐Redfern equations from room temperature to 900 °C. Furthermore, all the compounds were subjected to bioassay against two Gram‐positive bacteria of Staphylococcus aureus and Bacillus subtilis, two Gram‐negative bacteria of Pseudomonas aeruginosa and Escherichia coli, and two fungal strains of Aspergillus oryzae and Candida albicans. The results showed that all the synthesized compounds act well as antimicrobial agents. DNA cleavage power of the materials was also evaluated using extracted DNA from E. coli bacterium. The cytotoxic activities of some compounds were investigated against the prostate cancer cell lines (PC3) and human umbilical vein endothelial cells (HUVEC) (as normal cells) by MTT assay and nitric oxide level evaluation method as compared with cis‐platin confirming anti‐cancer effects of them. Finally, the antioxidant properties of the N2O2‐ligand and its cadmium coordination compounds were examined by DPPH and FRAP methods suggesting all the compounds have good antioxidant activity as compared with standard samples.

A Neural Network Method for Systematic Evaluation of Informatization Development Level in Smart Court Construction

&lt;p&gt;The systematic evaluation of informatization development level (IDL) is an evaluation that follows the development trend of digitization, networking and intelligence, and focuses on the formation of business capabilities of informatization. Research on informatization evaluation methods has been extensively studied by both domestic and international academics over the years. However, traditional evaluation methods suffer from flaws like complex mechanism design, unreliable metric conversion, difficulty obtaining the relative importance of indexes, complex evaluation process, and high computational volume. This paper attempts to introduce the neural network method into the information system evaluation, and uses the Extreme Learning Machine (ELM) algorithm to establish the evaluation model. The evaluation of the smart court system is used as an example to simulate and test the model, and the results show that the neural network-based evaluation model of informatization system is more applicable to large-scale evaluation indexes, and by continuously increasing the learning samples, it objectively improves the accuracy of evaluation, effectively avoids human subjective factors, and has the advantageous features of advanced, accurate and convenient.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Determination of relationship between high-temperature low cycle fatigue damage and mechanical property degradation: Experimental and theoretical analyses

Mechanical properties of metallic materials gradually degrade under high-temperature low cycle fatigue (HTLCF) loading, which is a manifestation of fatigue damage accumulation. In this study, a mapping modeling is developed to determine the relationship between micro-scale HTLCF damage and macro-scale mechanical property degradation. Strain-controlled HTLCF tests in GH4169 superalloy are carried out at 650 °C and interrupted at various lifetime fractions for subsequent microscopic characterizations and high-temperature tensile tests. Quantitative analysis of electron backscatter diffraction indicates a three-stage increase in kernel average misorientation and geometrically necessary dislocation throughout the cyclic process, along with variations in the fraction of different grain boundaries. Simultaneously, the evolutions of shearing precipitate and de-twinning are characterized using transmission electron microscope. Furthermore, the mechanical properties of GH4169 superalloy, such as yield strength, ultimate tensile strength, elongation and work-hardening rate, demonstrate different degradation characteristics after exposure to HTLCF damage. Based on these results, the mechanism of HTLCF-induced mechanical property degradation is clarified and the mapping modeling is established using tensile plastic strain energy density and kernel average misorientation. Finally, a damage level evaluation method for engineering components is developed after the generality and flexibility of model is verified in different high-temperature materials.

A novel method for evaluating population accommodation level of adjustable products based on interval estimation

In designing adjustable products, their proper adjustable ranges need to be determined based on an accurate accommodation level evaluation method. Previous accommodation level evaluation methods have employed point estimation for representing an adjustable product's population accommodation level. However, a point estimate of population accommodation level is limited in that it lacks 1) information regarding the precision of an estimated accommodation level, and 2) the capability to conduct statistical comparisons of the differences between accommodation levels of multiple designs/products. Therefore, as a remedy for such limitations, this study developed a novel population accommodation level evaluation method that incorporates both point and interval estimation. The method evaluates an adjustable product's accommodation level on the basis of the adjustable range provided by the product and a set of fitting product configurations of multiple individuals. The method consists of three parts: 1) an accommodation level is evaluated for each individual for a given adjustable range, 2) a population accommodation level is determined based on the obtained individual accommodation levels, and 3) a confidence interval of the population accommodation level is generated. The descriptions of the developed method are provided, presented along with its advantages. Then, a case study is conducted to demonstrate how the method can be applied to practical design problems. Lastly, the practical implications of the developed method are discussed along with some possible future research directions.

Test Database for Corroded Prestressing Steel Strands Recovered from Aged Bridges

To evaluate the structural safety of corroded prestressed concrete structures, it is necessary to define the deteriorated mechanical behaviors of corroded prestressing steel strands. However, no standard provides a quantified relationship between the level of corrosion and the residual mechanical properties, and no consensus for such quantification has been reached. The aim of this study was to provide a test database for the residual mechanical properties of corroded prestressing steel strands. Strands recovered from aged bridges were naturally corroded, and an evaluation method for the corrosion level was suggested. In addition, corrosion assessment criteria were suggested based on characteristics of the corrosion appearance.

Evaluation method of sustainable utilisation level of agricultural land resources based on double difference method

Evaluation method of sustainable utilisation level of agricultural land resources based on double difference method

UAV imagery based potential safety hazard evaluation for high-speed railroad using Real-time instance segmentation

Potential safety hazards (PSHs) along the track needs to be inspected and evaluated regularly to ensure a safe environment for high-speed railroad operations. Other than track inspection, evaluating potential safety hazards in the nearby areas often requires inspectors to patrol along the track and visually identify potential threads to the train operation. The current visual inspection approach is very time-consuming and may raise safety concerns for the inspectors, especially in remote areas. Using the unmanned aerial vehicle (UAV) has great potential to complement the visual inspection by providing a better view from the top and ease the safety concerns in many cases. This study develops an automatic PSH detection framework named YOLARC (You Only Look at Railroad Coefficients) using UAV imagery for high-speed railroad monitoring. First, YOLARC is equipped with a new backbone having multiple available receptive fields to strengthen the multi-scale representation capability at a granular level and enrich the semantic information in the feature space. Then, the system integrates the abundant semantic features at different high-level layers by a light weighted feature pyramid network (FPN) with multi-scale pyramidal architecture and a Protonet with residual structure to precisely predict the track areas and PSHs. A hazard level evaluation (HLE) method, which calculates the distance between identified PSH and the track, is also developed and integrated for quantifying the hazard level. Experiments conducted on the UAV imagery of high-speed railroad dataset show the proposed system can quickly and effectively turn UAV images into useful information with a high detection rate and processing speed.

Evaluation of EV penetration level limit in distribution system applying charging and scheduling strategies

Traveling by electric vehicles (EVs) instead of conventional fuel cars is strongly supported by a lot of governments for the sustainable development of urban transportation. However, EVs increase the load in the distribution system which impacts the voltage stability in the distribution network. In this paper, a method for evaluation the largest EV number to be accommodated in the distribution system is proposed. First of all, a Monte Carlo charging model for electric vehicles is established. Then the EV charging schedule is determined with the TOU electricity price and the dispatch method to suppress the maximum peak load is presented. Ultimately, Considering the temporal and spatial features of EV charging, the maximum vehicle access capacity of the distribution network is calculated by the continuous power flow method. The developed method was tested in the PG&E 69-bus distribution system, and the results show that the EV penetration level evaluation method proposed is an efficient tool for the distribution system planning, as well as the voltage stability analysis with the fast increasing EVs in the distribution system.

Biological risk assessment in the clinical laboratory from the nurse's point of view

Introduction: The nurse as an active member of the health care team is key in risk management. Aim: To evaluate the level of biological risk in a primary health care clinical laboratory from the nurse's point of view. Methods: Descriptive study in a primary health care clinical laboratory, selected by non-probabilistic and intentional sampling. The Safety Level Evaluation Method, implemented in the ASeC software, was applied. Results: 34 % of negative aspects for safety were found, which is equivalent to an Unacceptable-Critical (I-C) level. Conclusions: the risk assessment developed made it possible to determine the biological risk profile of the laboratory under study, ranked by importance. The intervention of the nurse in the fulfillment of her investigative, assistance and administrative functions made it possible to identify and evaluate the risks in order to avoid work accidents, damage to the community and the environment

Comprehensive Evaluation of Runoff Forecast Level Based on Forecasting Difficulty

ABSTRACTThe current traditional forecasting level evaluation method only uses the forecast error value series for relevant analysis, such as dividing the number of qualified forecasts by the total number of forecasts to indicate the corresponding forecasting accuracy or level. This does not consider the different external environments during the forecast. When assessing the forecasting level of different forecasters, fairness cannot be reflected to a certain extent. So this paper puts forward the concept of forecasting difficulty and analyses the physical significance of forecasting difficulty. Based on the traditional concepts of forecasting accuracy and error, two methods calculating the forecasting difficulty are established to consider different forecasting situations, such as rainy, rainless, different foresight periods, and different inflow levels. Further, a new comprehensive forecasting level evaluation method of forecasters is proposed. Taking the Guandi reservoir as an example, the case study results show that compared with the traditional method, the proposed forecasting level evaluation method can effectively consider the difficulty factors of different forecasting situations. In addition, the methods can better reflect the contribution of difficult situations to the comprehensive forecasting level when considering the improvement of forecasting accuracy, which makes the obtained results more scientific and reasonable.