Software evaluation using the 9241 evaluator

The environmental quality evaluation of seawater is a multicomponent and multi-factorial one, the water environment quality classification standards and the level of water pollution and so on are some vague concepts .Currently available evaluation models of water quality have more or less some shortage, Based on the variable fuzzy theory, the paper is to establish the variable fuzzy evaluation model of seawater quality and apply the approach to the comprehensive evaluation of Jiaozhou Bay seawater quality. The practice indicates that the model is simple, and can reasonably determine the sample's the relative membership degree and the relative membership functions to the different index standard ranges and be able to properly rate the sample by taking the stable result as the result of the comprehensive evaluation of seawater quality through changing the model and its parameters (a and p parameters change, change for four models, including a linear, three nonlinear) thereby providing a new approach and method for multi-objective comprehensive evaluation and decision-making in marine environmental field

BackgroundPerioperative chemotherapy combined with D2 radical gastrectomy has been proven to be the standard treatment for local advanced gastric cancer. However, tumor regression grading (TRG) is the only neoadjuvant chemotherapy (NACT) response evaluation criterion recommended by the NCCN guideline for gastric cancer (GC). Given TRG’s limitations, we aim to explore a better comprehensive response evaluation method in this study.MethodsClinical information of 96 GC patients who received NACT was collected prospectively. Clinicopathological variables predictive of the response to NACT were identified by comparing the pre- and post-NACT examination results. The correlations between the response mode and long-term survival rate were assessed.ResultsUnivariate Cox regression analysis showed that CT-based evaluation of the primary lesion thickness (CT-thickness) and tumor markers (TMs) were significantly associated with prognosis. The comprehensive evaluation method, including CT-thickness, TRG, and TMs, was constructed and proved to have a higher Harrell’s C index. Significant differences in overall survival (OS) and recurrence-free survival (RFS) were observed between responders and non-responders distinguished by the comprehensive evaluation method.ConclusionsThe combination of CT-thickness, TRG, and TMs could be used to construct a pragmatic NACT efficacy evaluation method with both high sensitivity and specificity, which could facilitate clinical decision-making, NACT-related clinical research conduction, and efficacy predictive biomarker exploration.

Cloud-based applications have become more and more popular. However, it remains a big challenge to comprehensive evaluate the reliability and performance of cloud providers and services due to the reason that Cloud is extremely dynamic and uncertain, resources distributed, virtualised, and freedom of entry and exit. The grey theory is adapted to handle the problems of blurring and uncertainty. Therefore, based on the grey relational analysis and grey comprehensive evaluation method, this paper proposes a novel trust comprehensive evaluation method for cloud services, also a comprehensive user satisfaction evaluation method for the better selection of suitable providers. In addition, it discuss in detail the construction and calculation of the evaluation model by case study.

The core goal of higher vocational education is to cultivate students with good professional quality. The employability of college students depends on their professional quality to a large extent. From the perspective of school education, all kinds of higher vocational colleges have entered a new level in practice, but the evaluation of comprehensive quality is still relatively weak. Therefore, in order to enhance the comprehensive ability of higher vocational students and cultivate their excellent comprehensive quality, this paper adopts the fuzzy comprehensive evaluation method and puts forward the evaluation method of the comprehensive evaluation system of higher vocational students, so as to provide reference for solving the problem of comprehensive quality evaluation. The specific process is as follows: in this paper, a two-level fuzzy mathematical model is established by using fuzzy mathematics theory and multimedia technology. First of all, according to the educational characteristics such as learning interest, psychological quality when encountering difficulties, and the ability to solve problems cooperatively, a set of secondary indicator system reflecting vocational college students is established. With this indicator, quantitative indicators are fuzzified by introducing membership functions, and a single factor evaluation matrix is established. Then, the specific steps are illustrated with examples to realize the qualitative analysis and quantitative evaluation of students’ comprehensive quality. The results show that the new comprehensive quality evaluation method established in this paper has strong practicality and innovation.

The aggregate gradation of asphalt mixture is one of the most important factors affecting the service life of asphalt pavement. In order to study the gradation of asphalt mixture with the best comprehensive performance, this study puts forward a new method of mineral aggregate gradation optimization based on the fuzzy analytic hierarchy process and comprehensive evaluation method, aiming at the multi-level and multi-index evaluation of the road performance of asphalt mixture. First, the orthogonal test design method is applied to design nine target gradations with coarse aggregate (>4.75 mm) and fine aggregate (<4.75 mm) of AC-20 (asphalt concrete) mixture serving as two factors and the upper, middle, and lower positions of the gradation curve as three levels, and then the road performance test research is carried out. Second, a comprehensive model for evaluation of road performance of mineral aggregate gradation is established. A fuzzy complementary judgment matrix is constructed, and the index weights of each level and the hierarchical total ranking weight are calculated. Then, the membership function is introduced into the comprehensive evaluation model for the road performance of mineral aggregate gradation, and the membership values of each index of asphalt mixture road performance are obtained. Finally, the fuzzy comprehensive evaluation method is used to find out the comprehensive evaluation value of the road performance of the nine graded asphalt mixtures, and the mineral aggregate gradation is optimized. The research results show that the 1# gradation of the asphalt mixture has the highest comprehensive road performance evaluation value, and the combination of the fuzzy hierarchical analysis process and comprehensive evaluation method can more objectively and comprehensively evaluate the comprehensive road performance of the asphalt mixture and provide a useful reference for the optimal selection of asphalt mixture mineral gradation.

In operation and control system of BeiDou Navigation Satellite System (BDS) and international GNSS Monitoring and Assessment System (iGMAS), the single-station evaluation method of navigation signal is susceptible to environmental of the site area, so the reliability is poor. And the traditional multi-objective/multi-attribute comprehensive evaluation method has strong subjective randomness and lacks quantitative analysis. Aimed at above problem, a multi-station combined evaluation method for navigation signal tracking accuracy based on optimization weight was proposed. In the proposed method, the optimal comprehensive evaluation equation was establishing, and the optimized weights were calculated by solving equation. And last, the comprehensive evaluation result was obtained by using the optimized weights. Experimental and simulation results show that the proposed method is more robust than the single-station evaluation method and multi-objective/multi-attribute comprehensive evaluation method. And the proposed method can provide more objective, reliable and accurate evaluation results. The proposed method can provide effective theoretical guidance for the evaluation of tracking precision of Beidou operation and control system and iGMAS.

Accurate and computationally efficient series-connected battery pack models (PMs) in new energy vehicles are extremely important for battery management. Based on a system of indexes of accuracy, adaptability, and computational complexity, this article presents a practical and comprehensive evaluation method for series-connected battery PMs, which is crucial for model selection and model-based algorithm development. Seventeen battery PMs, based on four series-connected battery pack structure models and three battery cell models, are introduced and discussed in detail. Experiments are designed and carried out to collect realistic battery test data for parameter identification and model comparisons. The estimation accuracy and computational complexity of different battery PMs are compared. Both the merits and demerits of each battery PM are thoroughly analyzed and discussed. The practical comprehensive evaluation results provide useful insights that will enable industry and academia to design more advanced battery management systems for battery packs.

The traditional logging evaluation of comprehensive sweet spots in shale oil reservoirs has problems such as complex explanatory parameters, incompatible quantitative characterization scales, and low-cost efficiency. A method based on the fractal characteristics of conventional logging curves is proposed to evaluate the comprehensive sweet spots of fractured horizontal wells in shale oil reservoirs. Firstly, the existing evaluation parameters and methods were reviewed, pointing out the limitations of traditional logging evaluation methods. Furthermore, we analyzed 63 fractured sections from three horizontal fractured wells in the Yingxiongling shale oil reservoir of the Qinghai Oilfield, using tracer monitoring data. By applying wavelet transform to reduce noise in high-frequency signals from conventional logging curves, we then used multifractal spectrum analysis and R/S analysis to extract the multifractal spectrum width (∆α) and fractal dimension (D) from four conventional logging attributes: natural gamma logging (GR), acoustic time difference logging (AC), density logging (DEN), and neutron logging (CNL). A multi-attribute comprehensive fractal evaluation index was developed by using the post-fracturing tracer monitoring profile as a constraint and applying the grey relational analysis method. This approach enabled a quantitative classification and evaluation of the key sweet spots in shale oil reservoirs after fracturing. The results show that the comprehensive fractal evaluation index of the high-yield well section after Class I layering is 0.75<∆ α‘<1, 0 < D‘<0.25; 0.35<∆ α‘<0.75, 0.25 < D‘<0.8 in the middle well section of Class II layer; Class III low production well Sect. 0<∆ α‘<0.35, 0.8<∆ α‘<1. Finally, a prediction model for physical property parameters characterized by fractals was introduced using machine learning algorithms, which is 31.9% more accurate than the conventional interpretation physical property parameter prediction model for the comprehensive sweet spot of fracturing. This evaluation method is a concise approach to comprehensively evaluate the sweet spot area based on the extraction of multifractal spectral characteristic parameters from conventional logging data. It is of great significance for characterizing the volume fracturing effect of shale oil and providing technical support for the effective development of shale on a large scale.

With increasing concerns about climate change and resource-environmental limitations, the green development of the mining industry has become mainstream and gained much support. Driven by the concept of sustainable and green development, China has made the advancement of green mine construction a crucial part of establishing an eco-society and has put forward the overall goal of green mines. An important future strategy is to evaluate a large number of mines. However, developing scientific, reliable, and comprehensive index systems and evaluation methods is extremely difficult because of the objective complexity of green mine evaluation and the fuzziness of some indicators. The kernel method and intuitionistic fuzzy set can effectively handle these problems. This study proposed a comprehensive evaluation index system and a hybrid evaluation method based on the kernel distance measure and intuitionistic fuzzy TOPSIS method. The index system contains 22 indicators considering six aspects: mining area environment, resource development mode, comprehensive utilization of resources, energy saving and emission reduction, technical innovation, and corporation management. The hybrid evaluation method was applied to the practical assessment of ten green mines in Panxi, China. Comparative analyses were carried out to demonstrate its applicability and sensitivity. The results verify that the hybrid method can fully depict the construction achievements of green mines in all aspects with strong reliability and stability. This approach is a valuable reference for evaluators and decision-makers in government departments.

People pay more attention to analyzing the sports problems with mathematical methods. The paper takes the technical statistical data and game performance of NBA basketball players in 2021-2022 season as the research object, selects indexes by literature review, questionnaire and mathematical statistics, and conducts research on the technical ability, tactical awareness, fitness level and game performance of NBA basketball players. Based on statistical mathematics and fuzzy mathematics, the paper introduces the concept of index contribution rate, and constructs comprehensive evaluation model of competitive ability of outstanding basketball players with improved order relation method and cloud model, making both quantifiable indexes and non-quantifiable factors involved in the evaluation process. First of all, it uses improved order relation method to determine index weight, and constructs the index weight evaluation model of basketball players’ comprehensive ability. Secondly, with NBA players’ data as sample data, it realizes the conversion between qualitative concept and quantitative concept based on cloud model algorithm, uses Matlab to conduct simulation analysis to derive the order relation weight table, compares and analyzes the evaluation cloud chart and standard cloud chart based on cloud model, and analyzes the weight and influence of each index in the players’ comprehensive ability evaluation to determine the preferred index. Finally, the author verifies the indexes selected by mathematical method and the indexes of 503 basketball players published on the NBA official website in 2022-2023 season, proving that it is effective and can achieve the unity of subjective and objective. This demonstrates that the basketball players’ comprehensive ability evaluation system built in this paper is reasonable and has reference significance for basketball players and coaches. Compared with other weight evaluation models, the comprehensive ability index system established by the evaluation method provides a systematic method for quantitative analysis and comprehensive evaluation of basketball players’ competitive ability, and has practical significance for improve basketball players’ competitive performance with mathematical model.

In the context of the advancing construction engineering field in China, there has been a significant increase in the adoption of building information modeling (BIM) technology within engineering–procurement–construction (EPC) projects. This emerging technology is expected to significantly influence the decision‐making practices of professionals in the construction and engineering domain. Consequently, there is an urgent need for comprehensive research focused on construction management specifically pertaining to the effectiveness of construction developer management. This study examines seven representative EPC projects where BIM technology was implemented and it considers various factors that have the potential to influence project decision‐making while taking into account time and cost considerations. A comprehensive multidimensional evaluation method that combines the analytic hierarchy process (AHP) and the fuzzy comprehensive evaluation method is introduced in this study. The results of this study emphasize that the efficiency enhancement strategies derived from the judgment indicator method demonstrate favorable practical outcomes. This research highlights the importance of a comprehensive evaluation method combining the AHP and the fuzzy comprehensive evaluation method to enhance decision‐making efficiency for construction developer management staff.

The two failure modes of shell structure, dynamic instability and intensive destruction, have no distinct boundary on their structural performance; they are fuzzy and are difficult to determine problems. By using the comprehensive evaluation method in fuzzy mathematics and taking the initial imperfection of the structure into consideration, this paper, taking Kiewitt spherical shell as an example, made parameter impact analysis to the structure, and investigated the influence of span ratios, the initial geometric imperfections and bar cross-section of the structure under earthquake failure mode. Ensuring the relations between a variety of response factors of the structure and fuzzy failure modes, the paper established a power failure mode shell structure of fuzzy comprehensive evaluation model and evaluation method, and described the application of the method in the discrimination of failure mode on Kiewitt monolayer Shell with initial defect; the consequences showed that this method can solve the problem of failure mode identification better with more realistic facts and possesses higher accuracy.

As a result of the importance of the usability approach in system development and the EC's ‘Directive concerning the minimum safety and health requirements for VDT workers’ (EWG 1990), there is an accepted need for practical evaluation methods for user interfaces. The usability approach and the EC Directive are not restricted to user interface design, as they include the design of appropriate hardware and software, as well as organization, job, and task design. Therefore system designers are faced with many, often conflicting, requirements and need to address the question, ‘How can usability requirements comprehensively be considered and evaluated in system development?’ Customers buying hardware and software and introducing them into their organization ask, (How can I select easy-to-use hardware and software?’ Both designers and customers need an evaluation procedure that covers all the organizational, user, hard- and software requirements. The evaluation method, EVADIS.II, we present in this pa...

With the objective of identifying superior Vernicia montana trees grounded in phenotypic and agronomic traits, this study sought to develop and implement a comprehensive evaluation method which would provide a practical foundation for future clonal breeding initiatives. Using the Vernicia montana propagated from seedling forests grown in the Suxian District of Chenzhou City in southern Hunan Province, we conducted pre-selection, primary selection, and re-selection of Vernicia montana forest stands and took the nine trait indices of single-plant fruiting quantity, single-plant fruit yield, disease and pest resistance, fruit ripening consistency, fruit aggregation, fresh fruit single-fruit weight, fresh fruit seed rate, dry seed kernel rate, and seed kernel oil content rate as the optimal evaluation indexes and carried out cluster analysis and a comprehensive evaluation in order to establish a comprehensive evaluation system for superior Vernicia montana trees. The results demonstrated that a three-stage selection process-consisting of pre-selection, primary selection, and re-selection-was conducted using a comprehensive analytical approach. The pre-selection phase relied primarily on sensory evaluation criteria, including fruit count per plant, tree size, tree morphology, and fruit clustering characteristics. Through this rigorous screening process, 60 elite plants were selected. The primary selection was based on phenotypic traits, including single-plant fruit yield, pest and disease resistance, and uniformity of fruit ripening. From this stage, 36 plants were selected. Twenty plants were then selected for re-selection based on key performance indicators, such as fresh fruit weight, fresh fruit seed yield, dry seed kernel yield, and oil content of the seed kernel. Then the re-selected optimal trees were clustered and analyzed into three classes, with 10 plants in class I, 7 plants in class II, and 3 plants in class III. In class I, the top three superior plants exhibited outstanding performance across key traits: their fresh fruit weight per fruit, fresh fruit seed yield, dry seed yield, and seed kernel oil content reached 41.61 g, 42.80%, 62.42%, and 57.72%, respectively. Compared with other groups, these figures showed significant advantages: 1.17, 1.09, 1.12, and 1.02 times the average values of the 20 reselected superior trees; 1.22, 1.19, 1.20, and 1.08 times those of the 36 primary-selected superior trees; and 1.24, 1.25, 1.26, and 1.19 times those of the 60 pre-selected trees. Fruits counts per plant and the number of fruits produced per plant of the best three plants in class I were 885 and 23.38 kg, respectively, which were 1.13 and 1.18 times higher than the average of 20 re-selected superior trees, 1.25 and 1.30 times higher than the average of 36 first-selected superior trees, and 1.51 and 1.58 times higher than the average of 60 pre-selected superior trees. Class I superior trees, especially the top three genotypes, are suitable for use as mother trees for scion collection in grafting. The findings of this study provide a crucial foundation for developing superior clonal varieties of Vernicia montana through selective breeding.

Effective and comprehensive evaluation of cold stress is critical for healthy dairy cow breeding in the winter. Previous studies on dairy cow cold stress have considered thermal environmental factors but not physiological factors or air quality. Therefore, this study aimed to propose a multilevel fuzzy comprehensive evaluation (FCE) method for cold stress in dairy cows based on the analytic hierarchy process (AHP) and a genetic algorithm (GA). First, the AHP was used to construct an evaluation index system for cold stress in dairy cows from 3 dimensions: thermal environment (temperature, relative humidity, wind speed, and illumination), physiological factors (respiratory rate, body surface temperature), and air quality [NH3, CO2, inhalable particulate matter (PM10)]. Second, the consistency test of the judgment matrix was transformed into a nonlinear constrained optimization problem and solved using the GA. Next, based on fuzzy set theory, the comment set and membership function were established to classify the degree of cold stress into 5 levels: none, mild, moderate, high, and extreme. Then, the degree of cold stress in cows was obtained using multilevel fuzzy comprehensive judgment. To investigate the effect of illumination indicators on cold stress in dairy cows, 24 prelactation cows from the south and north sides were selected for a 117-d comprehensive cold stress evaluation. The results showed that the mean mild cold stress durations were 605.3 h (25.22 d) and 725.5 h (30.23 d) and the moderate cold stress durations were 67.2 h (2.8 d) and 96 h (4.0 d) on the south and north sides, respectively. Simultaneously, generalized linear mixed model showed that there were significant correlations between the daily cold stress duration and milk yield, feeding time, lying time, and active steps in the cows on both sides. This method can reasonably indicate cow cold stress conditions and better guide cold protection practices in actual production.