bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on phosphorite photoelectric sorting process based on fuzzy algorithm
Authors: Luo Kunyi , Zhang Bin , Li Ruolan , Peng Liqun , Ou Zhibing 
Published: May 2024

Abstract
In this paper, we synthesize the differences in grayscale and texture information of phosphorite X-ray images and extract a total of six feature quantities under their grayscale and texture features, respectively. After feature fusion, a fuzzy support vector machine classifier with a normal plane-type affiliation function is used to optimize the binary classification method of traditional support vector machines, which improves the accuracy of classification. To improve the sorting model’s division of the optimal classification hyperplane, the centroid position of the two types of samples is considered comprehensively. In order to give full play to the classification performance of the sorting model, the particle swarm algorithm is further used to optimize the core parameters of the fuzzy support vector machine, the penalty factor, and the kernel parameters to complete the construction of the classifier model. In the face of the mixed colloidal phosphorite that can not be exploited, based on the PSO-NP-FSVM photoelectric sorting operation, the concentrate yield rate, operation recovery rate, and optical sorting waste rate are 56.52%, 20.87%, and 71.17%, respectively. After photoelectric sorting, the grade of concentrate P2 O5 can be increased to 20.98%, which can meet the requirements for the grade of the processing plant. Therefore, the photoelectric sorting process combined with a fuzzy algorithm is capable of meeting the actual production requirements.
Constructing a Theoretical Methodological System for Vocal Music Education in Colleges and Universities in the Context of Deep Learning Algorithms
Authors: Zhang Weifang 
Published: May 2024

Abstract
In recent years, artificial intelligence technology has been deeply integrated into college education to comply with the call for teaching reform. The research first uses endpoint detection and Mel frequency cepstrum coefficients to realize the recognition and extraction of vocal music feature signals. Then it uses a deep convolutional neural network to output the extracted signals to complete the recognition and error correction of different vocal music. Finally, different vocal audio is used as a sample to deeply analyze the recognition of various styles of vocal music, as well as the recognition and error correction of music. The model in this paper has a more satisfactory effect on vocal music recognition and music style classification. The recognition rate of vocal music under different signal-to-noise ratios is above 90%. It can also well realize the error correction of vocal music and accurately judge the time value (95%) and pitch (93.57%) of the playing, which reflects a high application value in vocal music teaching. The use of deep learning in vocal music recognition and error correction in college vocal music education can assist vocal music learners and decrease the work intensity of vocal music educators.
Research on Data Acquisition and Regulation Methods of Basement Flashing Pressure Relief System Based on Digital Technology
Authors: Zhao Shixiao , Shi Wei , Zhang Lei , Zhang Yan , Zhang Hailiang 
Published: May 2024

Abstract
This study utilizes digital technology to monitor water pressure changes within basement flashings, facilitating targeted drainage operations. By implementing an active water discharge method, drainage holes are strategically placed around or beneath basements to decompress and reduce water levels, thereby alleviating hydrostatic pressure on underground structures. This approach helps prevent basement uplift. The paper addresses challenges such as high energy consumption and ample data storage in long-term monitoring, introducing an acceleration trigger module and a data correction algorithm based on an enhanced BP neural network. A WOA-BP neural network model was developed using historical data to monitor water pressure efficiently. Our findings indicate that at 0.076MPa, flashing connections begin to fail, progressing to shear damage at 0.085MPa. Consequently, to preserve basement integrity, it is crucial to activate complete drainage when monitored pressure exceeds 0.045MPa to maintain pressures below the critical threshold of 0.076MPa.
Analyzing the Effectiveness of Corporate Management Decision Making Using Information Entropy and Information Gain Ratio
Authors: Huang Qixin , Zhang Yajing 
Published: May 2024

Abstract
The information industry has increasingly become the dominant modern economy, and the introduction of informationization into enterprise management has become one of the necessary means for enterprises in various countries to improve their competitiveness and enhance their vitality. This paper is dedicated to studying the impact of information entropy and information gain ratio on enterprise management decision-making, which further confirms the necessity of modern enterprise management to implement informationization. This paper defines the relationship between information entropy and information gain ratio in enterprise management and establishes a comprehensive evaluation model that matches the two. The objective of indicator assignment improvement is improved by using weight determination based on information entropy to solve the issue of weighting between different indicators of two layers. According to the advantage that the information gain ratio can reflect the information orientation, the expert’s primary viewpoint assignment in the traditional enterprise management decision-making is replaced by the ratio of the information gain ratio of the sorted neighboring indicators to obtain the weights of each evaluation indicator. Taking enterprise Y as the research object to carry out empirical analysis, the entropy weight value of “consistency with the planned target” is 0.8599, which is an essential factor affecting the enterprise management decision. It can fully reflect the information orientation of the data itself and the subjective will of the experts or decision makers, which not only overcomes the shortcomings of the existing assignment methods that cannot objectively reflect the information orientation of the number or the subjective will of the experts or decision makers but also avoids the drawbacks of the existing combination assignment methods that cannot reasonably allocate the combination coefficients.
Research on the decision-making model of power purchase in electricity spot market oriented to market force suppression
Authors: Song Mingshu , Su Changsheng , Wu Maoqian , Song Wei , He Kai 
Published: May 2024

Abstract
In this study, for the electricity spot market under the market power suppression scenario, the market power suppression effect of contractual decomposed electricity is quantitatively evaluated by first reconstructing different electricity consumption loads using the combined MLR method and then combining the market power assessment model with the Lerner index. In addition, a contract for difference based on surveillance price is designed to inhibit market members from utilizing market power by adjusting the space of competitive electricity and the space of contracted electricity to avoid the market risk of rising electricity prices. Finally, a dynamic power purchase optimization decision model is constructed with CVaR as the risk metric and the profit of the power selling company and customer satisfaction as the objectives, and the MOSADE algorithm is used to solve the model and explore the optimal power purchase scheme. The analysis results show that the risk of the spot market can be avoided by bilateral contracts, option contracts, and unit power generation, and the price of electricity sales can be reduced. The expected returns of the four combinations are 21.37M$, 20.43M$, 19.24M$, 18.88M$, and 17.49M$ under the five risk coefficients, respectively. The CVaR values are −23.14, 2.84, 8.83, 10.75, 12.58. Higher than all the other cases, and their selling price for electricity is lower than all the different cases.
Application of Balanced Scorecard in Performance Evaluation of Educational Management
Authors: Wu Linfan , Li Ming 
Published: May 2024

Abstract
Good or lousy school education management is closely related to students’ growth, so research on the improvement of education management performance has become a hot topic. Taking School H as an example, this study utilizes the balanced scorecard to construct a system for evaluating school education performance at four levels: financial, customer satisfaction, internal operation processes, and learning and growth. Based on this basis, the weights of the educational management performance evaluation indicators at all levels are calculated by combining the entropy method and hierarchical analysis method, and the comprehensive evaluation scores of all indicators are derived. In addition, the multiple concurrent causal relationships and realization paths of the high-level development of educational management are also explored using the qualitative comparative analysis model. The results show that the evaluation score of educational management quality is 4.108, and the scores of each dimension of the secondary indexes are 4.102, 4.05, 4.13, and 4.15, respectively, which are above 4, indicating that the quality of educational management in the sample universities is good. This study provides the implementation steps of balanced scorecard performance evaluation for colleges and universities and, at the same time, provides a reference for other colleges and universities’ performance evaluations.
Analysis on the Design and Timeliness of English Teaching Models in Colleges and Universities under the Background of Informatization
Authors: Nong Siqi 
Published: May 2024

Abstract
The informationization era has accelerated people’s learning changed their thinking and cognitive styles, and the English teaching mode is also evolving and innovating. The purpose of this paper is to develop an English learning behavior analysis model, select an improved K-means algorithm for clustering learners, and examine the association rules between learning behaviors and learning effects. In addition, based on the sequence of learners’ behaviors, the article also combines the EduHawkes prediction model with multi-type features to quantify the learning effect in terms of learning engagement and predict the learning effect of students. The blended English teaching model is designed by combining learning behavior analysis and learning effect prediction models. In the experimental study of the timeliness of the English teaching model, the dimensions of students’ English literacy in terms of thinking quality, learning ability, and language ability showed significant differences before and after the experiment (P<0.05). In the evaluation of teaching methods, the dimensions of teaching materials, teaching tools, evaluation of learning outcomes assessment methods, and evaluation of teaching level showed significant differences (P<0.05). The English teaching model proposed in this paper is timely.
Exploring the Diversified Development of Vocal Music Teaching Methods in Colleges and Universities Combined with Multi-Priority Dynamic Threshold Algorithm
Authors: Shang Xiaoan 
Published: May 2024

Abstract
Enhancing the integration of modern information technology with educational practices, particularly in the vocal classroom, is crucial for improving academic quality. This paper presents an optimization method aimed at addressing the limitations of the existing multi-priority dynamic threshold algorithm. The specific performance is as follows: first, on the original basis of the PDT-RED algorithm, the expected cache utilization is set to ensure the utilization of the buffer. The optimized OPDT-RED algorithm should be used to ensure that the data frame is received with a high probability. Then, according to the channel environment, the dynamic fullness threshold was adjusted, which improved the performance of the highest priority queue with a high transmission success rate. Lastly, the measurements of vocal characteristic parameters like pitch, rhythm, beat, melody, and others. The goal was to create a complete evaluation network model for vocal teaching, which was applied to actual cases. The model’s performance and its effectiveness were evaluated. After testing, the subjects’ vocal rhythmic tempo was below 60, while the range of the sample repertoire was between 60 and 90, presenting two different forms of expression. The model proposed in this paper has the optimal effect on the enhancement of expressive movements while singing; 15.33% of the students improved by two notches, and the vocal teaching model designed in this paper has a very good effect on vocal enhancement.
Research on the framework of sports event management system of colleges and universities based on big data
Authors: Xie Yi , Guo Shuqing , Wang Shuling 
Published: May 2024

Abstract
With the continuous expansion of the scale of colleges and universities and the rapid development of network technology, the management of college sports events is facing more and more challenges. This study first constructs a collaborative management model for college sports events based on the SFIC model. It selects teachers and students from M school as the research object and presents relevant hypotheses. Factor analysis is used to verify the effectiveness of college sports event management, and multiple regression analysis is employed to analyze the factors. The results show that the four public factors extracted have been able to cumulatively summarize 71.408% of the original indicators of information starting conditions, catalytic leadership, institutional design, and synergistic process that can explain the management effect. Furthermore, the correlation coefficients between the variables and management effects are greater than 0.96, indicating a significant correlation. According to the study, there is potential for optimizing the management system of university sports events in terms of management power, management capacity, administrative duties, system improvement, management cooperation, transparency, and openness.
Aerobics Arm Movement Trajectory Recognition with Motion Computer Assistance
Authors: Xiong Chunzi 
Published: May 2024

Abstract
Aerobics is an internationally famous fitness and sports competition program. This paper aims to design an aerobics arm movement trajectory recognition method with the assistance of a sports computer to detect aerobics movements in real-time. The study first introduces the Gaussian kernel function based on the Kalman filter pose solution method to construct the aerobics arm GP-SUKF pose solution model. The acceleration data are then coordinate transformed to remove the gravity component of each axis, and the features of the aerobics action trajectory are extracted by combining the time-frequency domain integration method and eliminating the cumulative error. Finally, a support vector machine algorithm based on particle swarm optimization is constructed to classify and identify the features extracted from the trajectory of the extracted aerobics arm. In the simulation experiments, the algorithm in this paper provides more motion trajectory points for the aerobics arm movements. It is closer to the actual value of the wrist movements offered by the OptiTrack system, with the error ranging from 0.02m to 0.04m, and a better tracking effect can be obtained in the case of fast movements. This study can accurately track the trajectory of aerobics arm movements and provide more accurate posture and movement assistance for professional athletes and bodybuilders.
Research on the Integration Development Strategy of E-commerce and Cross-border Logistics Supply Chain in the Internet Era
Authors: Yang Lixia , Gong Jingjing , Feng Yujun 
Published: May 2024

Abstract
Based on industrial integration theory and system theory, this paper combines the development characteristics of e-commerce and cross-border logistics, utilizes the entropy weight method to assign weights to the indicators, and constructs a comprehensive evaluation model of e-commerce and cross-border logistics. Measure the coupling degree and integration degree of e-commerce and cross-border logistics. Using the multiple regression method to comprehensively study the technique of variable correlation and the important measures of the link between each variable, thus put forward optimization strategies for the logistics supply chain model, enterprise scale, and other aspects. The results of the analysis show that the proportion of cross-border e-commerce import transaction scale reached 22.7% in 2023, which increased 1.29 times compared with 2019, and the proportion of cross-border e-commerce import transactions continued to increase. In the analysis of the factors of the industrial integration of e-commerce and cross-border logistics, the influence of information network technology (0.108), the influence of platform resources, and the degree of influence of manufacturing technology occupy the top 3 places, which are the elements to focus on. Enterprise performance is significantly impacted by the economic level of the host province through regression analysis, with a coefficient of 0.1847 and significant at the 10% level. The evaluation value of the logistics alliance model is the best (comprehensive evaluation of 0.384), and it is most in line with the current development needs of cross-border e-commerce companies.
Research on the Monitoring and Evaluation System for the Growth of Innovation and Entrepreneurship Ability of College Students Based on Markov Model
Authors: Cao Changfang , Wang Hanmin , Guo Zhipeng 
Published: May 2024

Abstract
Human resources equipped with innovative entrepreneurial abilities are a vital catalyst in advancing enterprise development and the socio-economic landscape, as well as in transforming old and new kinetic energies. This study explores methods for fostering innovation and entrepreneurship among college students within the sphere of scientific and technological advancement. We developed an index system to measure these abilities and designed a questionnaire to assess the factors influencing student entrepreneurship. Our analysis, utilizing the Markov model and multiple regression, examines the skills of students from Universities A and B and identifies key factors that influence their entrepreneurial capabilities. The general proficiency of students at Universities A and B is moderate, with overall scores of 75.24 and 76.28, respectively. The data indicates that student capabilities increase alongside their academic progression. Influential factors contributing to innovation include curriculum teaching (0.054), campus atmosphere (0.041), and research conditions (0.047), with curriculum teaching playing a significant role. Higher education institutions must enhance students’ holistic abilities. By creating a diverse innovation-driven curriculum, these institutions can effectively boost the innovation and entrepreneurship skills of engineering students.
An Analysis of the Innovation of English Teaching Strategies and Their Impact on Learning Effectiveness in the Age of Big Data
Authors: Gao Haiyang , Zhang Qingping 
Published: May 2024

Abstract
In recent years, a wealth of research on English language teaching practice has emerged in the academic community at home and abroad, mainly focusing on the use of teachers’ strategies in the English language teaching classroom and less on whether the use of strategies can enhance students’ English language learning effectiveness. In this paper, we look for the factors affecting the effectiveness of English learning from the two subjects of teachers and students respectively, identify the main variables of the study, and put forward the relevant research hypotheses. By using partial least squares regression to construct a model of research impact on learning effectiveness, a regression test is proposed that utilizes Person’s correlation analysis as a benchmark. The research data were collected by means of an online survey, and in the descriptive statistics of the variables, the content mastery measure of the sense of learning goal effectiveness scored the highest at 4.253, and the learning content explanation of the English teaching innovation was adequate. The R2 of English learning strategies and goal effectiveness sense is 0.289 and adjusted is 0.265, the F value is 378.621, and the P value is less than 0.001, which is positive and significant. The more frequently English teaching innovation strategies are used in this study, the higher the sense of goal efficacy, which can significantly improve the effectiveness of learning.
A Study on the Effect of Color Preference on Purchase Intention of Picture Books for 3-7 Year Old Children in China and South Korea
Authors: Lei Qingyun , Zhong Guilin 
Published: May 2024

Abstract
This paper adopts a linear regression model to study the relationship between picture book color and purchase intention. The research object is selected, the research data are obtained by distributing questionnaires, the correlation coefficient formula of the linear regression model is used to get the correlation of the research independent variables, and then the least squares method is used to conduct regression analysis of picture book color preference and purchase intention. The research data show that the R² of model 1 (control variable) is 0.015. The R² of model 2 (independent variable) is 0.625, which increases the degree of explanation by 61.00% compared with model 1. The regression coefficients of the independent variables are 0.214, 0.122, and 0.126, respectively. All of them reach a significant level, which indicates that there is a significant positive effect of the color preference of picture books of Chinese and Korean children between the ages of 3-7 on the willingness to purchase. The color preference of Chinese and Korean children’s picture books aged 3-7 has a significant positive effect on purchase intention, as indicated by this. The cross-border children’s book market can benefit from this study as a good sales strategy and suggestion to better promote children’s picture books.
Simulation of bridge steel structure construction process based on BIM technology
Authors: Pan Wenming 
Published: May 2024

Abstract
With the rapid development of computer technology and information technology, bridge engineering is gradually transformed into information technology, and bridge BIM design technology is increasingly concern by the industry. This paper uses BIM technology to simulate the construction process of bridge steel structures. In order to solve the problem that the first model of BIM is too complicated, this paper utilizes the edge folding algorithm and quadratic error metric to refold the model and establish the new vertex coordinates, and at the same time, introduces the folding cost function to maintain the model characteristics. In the simulation experiments of the bridge structure construction, stress changes of the main girder of the bridge body are analyzed in various merging states. When the fitting error is +15mm, +25mm, and +35mm, the stress on the upper edge of the main girder near the top of the pier increases by 0.24MPa, 0.52MPa, and 0.78MPa, respectively, for the selection of materials and the prediction of construction and assembly parameters, in which the length of the steel girder N1 is accurate to the millimeters, which is 39940mm, and the single piece weighs 9,532.5kg. To prevent collision and interference with the bridge pier, the crane should be raised at a height of not less than 6.6m during the lifting stage. It can be seen that BIM technology can not only simulate and predict non-geometric factors such as the materials used but also simulate the margin of error and the bridge stresses as a way to help bridge projects on the ground.