Effective Evaluation Method Research Articles

Theoretical and experimental study on a novel evaluation criteria of heat exchangers applied in aero engines

For the application of heat exchangers in the aeronautic field, an effective evaluation method is required to support the satisfaction of the multi-aspect design restrictions including the thermal and hydraulic performance, occupied volume, total weight, etc. To weigh the benefit and cost for both heat transfer units and heat exchangers, this study thus proposes three evaluation indexes Rp, RV, and Rm defined by the product of heat transfer coefficient and heat transfer area of unit windward area times pressure drop (hA/(AfrontΔp)), that of unit volume (hA/V) and that of unit weight (hA/m). Considering the factors h and A comprehensively and excluding the influence of mean differential temperature, the three indexes can reflect the low flow resistance, compactness, and lightness characteristics under fixed operating conditions and heat transfer duty requirement accordingly. A validation experiment is carried out and the deviation between the evaluation and experiment results is less than 10.88% for the three indexes. To show the applicability, a detailed evaluation of six different heat transfer units and five types of heat exchangers is conducted. A heat transfer unit selection method based on the new indexes is provided finally for heat exchanger design.

Blasting vibration effect and safety evaluation method of railway cross tunnels

The evolution characteristics of the peak particle velocity and frequency of an existing railway cross tunnel are systematically studied. The analysis results show that there is a difference in the blasting vibration response before and after the new tunnel face is built. In this paper, a set of blasting vibration response evaluation methods that can quantitatively consider the influence of frequency by means of dimensional analysis is introduced. In addition, relevant knowledge on topics such as wavelet packet analysis, signal processing, structural dynamics, and explosion mechanics is applied to research the influence of the frequency. The research results show that the influence of the frequency on the blasting vibration response can be quantitatively analyzed by quantifying the dynamic amplification factor. To resolve the insufficiency of field monitoring, the distribution of the blasting vibration response along the entire section of the existing tunnel is studied through numerical simulation. Based on the theory of distortion energy in material mechanics, a new idea for evaluating the blasting vibration response of a cross tunnel is proposed.

Research on effectiveness evaluation of corporate culture construction based on the neutrosophic cubic number multiple attribute decision making

Corporate culture has its own development laws and may play a significant role in a short period of time, but its development and improvement are a relatively long-term task. The construction of corporate culture is a systematic project that varies depending on the enterprise. For enterprises, the construction of corporate culture has very important practical significance for the re integration of the enterprise team and the enhancement of competitive strength. Culture is a productive force, and the role of corporate culture is more direct. Therefore, enterprises should focus on their own development goals, create their own unique corporate culture based on learning and reference, and meet market challenges with a new look and strong strength. The effectiveness evaluation of corporate culture construction is a classical multiple attribute decision making (MADM). Recently, the TODIM and VIKOR method has been used to cope with MADM issues. The neutrosophic cubic sets (NCSs) are used as a tool for characterizing uncertain information during the effectiveness evaluation of corporate culture construction. In this manuscript, the neutrosophic cubic number TODIM-VIKOR (NCN-TODIM-VIKOR) method is built to solve the MADM under NCSs. In the end, a numerical case study for effectiveness evaluation of corporate culture construction is given to validate the proposed method. The research aim of the paper is summarized: (1) the NCN-TODIM-VIKOR is proposed for MADM problem with NCSs; (2) The attributes weight information is obtained through information entropy; (3) the NCN-TODIM-VIKOR method is designed for effectiveness evaluation of corporate culture construction and were compared with some existing methods; (4) Through the comparison, it is found that NCN-TODIM-VIKOR method for effectiveness evaluation of corporate culture construction proposed are effective.

An Evaluation method of online education reform effect based on fuzzy weight

An Evaluation method of online education reform effect based on fuzzy weight

Research on the evaluation method of the cost deviation control effect for complex large-scale construction projects based on the matter-element extension theory

Research on the evaluation method of the cost deviation control effect for complex large-scale construction projects based on the matter-element extension theory

Evaluation method of ore grade estimation effectiveness.

This study proposes a new method to evaluate the effectiveness of orebody grade estimations, drawing upon the analysis of existing evaluation methods for grade estimation. This new approach addresses factors such as uneven sampling and asymmetric estimation range, which are challenging to overcome with existing evaluation techniques. The core principle of this method involves documenting how frequently individual samples are used during grade estimation and calculating the total distance weights for each sample. Subsequently, the usage frequency and total weight of the samples are standardized, and these standardized values are weighted based on the sample grades. A comparison is made between the weighted sample grades and the estimated grades, with the closeness between the two serving as a metric for assessing the effectiveness of the estimation. This study compares the new evaluation method to the direct comparison and cross-validation methods, examining the effectiveness of grade estimation using the inverse distance weighting (IDW) method. The findings revealed that: (1) The new evaluation method theoretically accounts for the systematic deviation between the statistical measures of estimated and sample grades resulting from uneven sample distribution, offering a fresh approach for enhancing the effectiveness of orebody grade estimation. (2) In the grade estimation of experimental Fe samples, the frequency of usage and the sum of distance weights were unequal. This inequality significantly contributes to the systematic deviation between the estimated and sample grades. (3) Comparing the new evaluation method to others confirms the stability and reliability of the new approach for evaluating the effectiveness of orebody grade estimation. This novel method demonstrates theoretical advantages and practical utility. (4) The deviation between the estimated grades and the statistical results of sample grades is influenced by the distribution pattern of sample grades, the spatial relationship between samples and estimation blocks, and the inherent systematic error associated with the IDW method. This systematic error cannot be overlooked.

Evaluation method of immersive situational interpretation teaching effect based on natural language processing

Evaluation method of immersive situational interpretation teaching effect based on natural language processing

Evaluation method of English flipped classroom teaching effect based on entropy weight method

Evaluation method of English flipped classroom teaching effect based on entropy weight method

An evaluation method of online education reform effect based on fuzzy weight

An evaluation method of online education reform effect based on fuzzy weight

Evaluation Method and Application of Hydraulic Fracturing Effect in Yingxiongling Shale Reservoir

Evaluation Method and Application of Hydraulic Fracturing Effect in Yingxiongling Shale Reservoir

An objective evaluation method of vocal singing effect based on artificial intelligence technology

Abstract The continuous progress of artificial intelligence technology has shown great potential for application in several fields, especially music. The research direction of Objective Evaluation of Vocal Singing Effectiveness uses advanced technologies to analyze and assess a singer’s performance across multiple dimensions, including pitch, rhythm, and timbre, and is highly valuable. Building an accurate and fair evaluation system faces many challenges, including how to accurately capture and analyze the subtle changes in the voice and synthesize the effects of different musical elements on the quality of the performance. This requires researchers to explore music theory, sound analysis techniques, and artificial intelligence algorithms, and develop a new methodology that can comprehensively evaluate the effectiveness of vocal singing. This paper constructs a complete set of vocal singing evaluation models by analyzing acoustic feature extraction, Hidden Markov Model, and Generalized Regression Radial Basis Function Network in detail. The study adopts a logarithmic Mel spectrum for acoustic feature extraction to effectively capture the essential attributes of the singing voice. Hidden Markov models and mixed Gaussian models are used to model the sound signal, improving phoneme recognition accuracy. Accurate singing effect was evaluated using a generalized regression radial basis function network. In this article, the accuracy of this evaluation method in terms of pitch, rhythm, and timbre reached 95%, 93%, and 89%, respectively, demonstrating high evaluation consistency and reliability. The research method provides a new objective evaluation tool for vocal singing effects, which is valuable for vocal teaching and self-practice.

Research on the evaluation method of cost deviation control effect for complex large-scale construction projects based on the matter-element extension theory

Research on the evaluation method of cost deviation control effect for complex large-scale construction projects based on the matter-element extension theory

Research on military targets camouflage effect rating based on background anomaly detection and deep transfer features learning

Manual evaluation of military target camouflage often fails to fully capture human visual characteristics. This paper introduces a method for intelligent camouflage feature extraction and effect evaluation using deep neural networks. Firstly, military target and background datasets are constructed, with annotation methods optimized through perceptual experiments. A GANomaly model for background anomaly detection and a transfer learning feature model are developed. These models evaluate data similarity to background and target features to categorize camouflage into three levels. PCA dimensionality reduction and RFE screening identify final features. Two logistic regression models are then combined to create a grading model. In experiments, the GANomaly model was trained and optimized, achieving 86.8% accuracy in distinguishing level 1 from non-level 1 camouflage using 28-dimensional features. Among three transfer models, the MobileNetV2 model identified 33-dimensional features with 85.1% accuracy in distinguishing level 3 from non-level 3 camouflage. Combined, the models reached an 84.3% grading accuracy on the test set, with Micro and Macro average AUC values of 0.939 and 0.945, respectively. This performance surpasses that of BP network models and linear models based on manual features, as well as metrics like SSIM, UIQI, MSE, and PSNR. The results indicate that the models effectively align with human annotations and can reliably assess military target camouflage levels.

Evaluation method of English flipped classroom teaching effect based on entropy weight method

Evaluation method of English flipped classroom teaching effect based on entropy weight method

Study on evaluation method of modern distance teaching effect under MOOC environment

Study on evaluation method of modern distance teaching effect under MOOC environment

Evaluation method of immersive situational interpretation teaching effect based on natural language processing

Evaluation method of immersive situational interpretation teaching effect based on natural language processing

Application of quantum dots in brain diseases and their neurotoxic mechanism.

The early-stage diagnosis and therapy of brain diseases pose a persistent challenge in the field of biomedicine. Quantum dots (QDs), nano-luminescent materials known for their small size and fluorescence imaging capabilities, present promising capabilities for diagnosing, monitoring, and treating brain diseases. Although some investigations about QDs have been conducted in clinical trials, the concerns about the toxicity of QDs have continued. In addition, the lack of effective toxicity evaluation methods and systems and the difference between in vivo and in vitro toxicity evaluation hinder QDs application. The primary objective of this paper is to introduce the neurotoxic effects and mechanisms attributable to QDs. First, we elucidate the utilization of QDs in brain disorders. Second, we sketch out three pathways through which QDs traverse into brain tissue. Ultimately, expound upon the adverse consequences of QDs on the brain and the mechanism of neurotoxicity in depth. Finally, we provide a comprehensive summary and outlook on the potential development of quantum dots in neurotoxicity and the difficulties to be overcome.

Exploration and Practice of Educational Teaching Evaluation Reform in Higher Vocational Colleges Based on Big Data Technology

Abstract This paper constructs an evaluation model of education and teaching in higher vocational colleges based on big data technology, which focuses on students’ individual development and adapts to the “double-high program” goal. The evaluation index system of education and teaching quality established by the study contains 5 first- and 22 second-level indicators. The empirical Analysis takes QH College in R province as an example and analyzes the educational teaching data from 2018-2023. During this period, the mean values of secondary indicators of education teaching quality evaluation in QH College ranged from 2.7083 to 3.2886. The highest mean value of the rating of teaching objectives A1 and the lowest mean value of teaching standards A2. The coefficient of variation of teaching scenario B3 was the highest at 0.4887, and the coefficient of variation of building teaching resources was the smallest at 0.2587. In terms of the comprehensive evaluation of the quality of teaching and learning in higher vocational colleges and universities, the evaluation index system of QH College was categorized as “strong”. In addition, the study also analyzed the vulnerability of the evaluation of education and teaching in higher vocational colleges. From 2010 to 2023, the mean values of the vulnerability index of teaching quality evaluation of five higher vocational colleges in R province were 0.9693, 1.0536, 1.0507, 0.9993, 1.0407, respectively, with a significant turnaround in 2013, when the risk was significantly reduced. Synthesizing these data, this study provides an effective teaching model and evaluation method for higher education institutions to achieve high quality educational development.

Design of Teaching Mode and Evaluation Method of Effect of Art Design Course from the Perspective of Big Data

Design of Teaching Mode and Evaluation Method of Effect of Art Design Course from the Perspective of Big Data

MOOC distance teaching effect evaluation method based on fuzzy entropy

MOOC distance teaching effect evaluation method based on fuzzy entropy