bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the Evaluation of Higher Vocational Students’ Occupational Literacy in the Context of Big Data
Authors: Zhou Yanli 
Published: April 2024

Abstract
The current education and evaluation systems for vocational literacy in higher vocational institutions are inadequate, hindering high-quality talent development. This study utilizes the hierarchical-gray correlation method to construct an evaluative framework for assessing vocational literacy, identifying key indices through a judgment matrix scaling method. We further refine our analysis using the Analytic Network Process (ANP) method to calculate the influence between indices, culminating in a comprehensive student vocational literacy evaluation model. Notably, our approach disregards dimensions in index evaluation, computing a final comprehensive score. The quality of our empirical investigation was assured through extreme value and homogeneity tests, revealing a Consistency Ratio (CR) between −26 and −20 (absolute value > 3) and a correlation coefficient (r) between 0.601 and 0.893 (absolute value < 0.4), with a significance level (P value) of 0.000, indicating high survey quality. Analysis of 21 tertiary components yielded an average score of 3.5260, with 42.86% of indices surpassing this average, suggesting generally good vocational literacy among students.
Research on the Construction of Translation Path of College English Teaching Based on Deep Learning Strategy
Authors: Liu Jiying , Li Zheng , Huang Qiuheng 
Published: April 2024

Abstract
Based on deep learning, this study explores a teaching model to promote college students’ English translation ability with the support of information technology. It mainly adopts the neural machine translation algorithm to make the training samples constitute data nodes with semantic feature-carrying properties through the profound training of semantic feature quantity. It then gets the best English translation utterance that recognizes the translated information. Using a combination of quantitative and qualitative methods, we explored the impact of deep learning strategies on English translation teaching in colleges and universities, as well as the evaluation of practical effects. The results of the study show that under the deep learning teaching mode, the English translation scores of college students are improved by 9.085 points, which is a significant difference (P=0.018) compared to the traditional teaching mode, indicating the excellent performance of the strategy in English translation teaching.
A Study on Role Orientation and Professional Development of Early Childhood Teachers in Preschool Education in the Context of Big Data
Authors: Wang Nini 
Published: April 2024

Abstract
This research delves into how early childhood teachers’ understanding of their roles impacts their professional advancement, essential for developing and nurturing children. We gathered data from six kindergartens in G city, employing a multiple linear regression model to scrutinize factors influencing this relationship. Our approach involved separate hypothesis formulation and model building, complemented by validity checks via endogeneity and robustness tests using advanced statistical methods. The analysis highlighted the importance of teachers’ emotional connection to their work, with a notable regression coefficient of 0.403. It demonstrated that enhancing core literacy by 1% leads to a 0.154% increase in professional development levels. The findings advocate focusing on emotional engagement and core skills to foster excellence in early childhood education.
Reform and Practice of Civic Teaching in Design Curriculum by Integrating Local Excellent Culture
Authors: Liang Guanbo 
Published: April 2024

Abstract
To scientifically constitute the reform of Civics teaching in design course, the support structure of Civics network resources in design course is subdivided into Civics theory and network technology. This paper mainly utilizes fuzzy set-based knowledge fusion algorithm and semantic similarity algorithm to realize the knowledge fusion of local cultural resources course ideology and politics, updates local artistic resources by combining the results of fusion of knowledge elements, establishes implicit connection between different knowledge elements, and realizes the knowledge fusion of local cultural resources and design studies course ideology and politics. Taking the design majors of six universities in Guangxi as an example, the information access channels of local excellent cultural resources are discussed in depth, in which the proportion of search engine and social network channels respectively reaches more than 70%, presenting a “strong” dependence level. Based on the data of practical teaching reform, the construction of local excellent culture courses of design majors in Guangxi colleges and universities needs to be further improved to deepen students’ understanding of local excellent culture and encourage them to actively participate in relevant practical activities.
Innovation of Talent Training Mode of Higher Vocational Education in the Information Age with Industry-Teaching Integration
Authors: Li Jiangwei , Wu Yang 
Published: April 2024

Abstract
The optimization of talent training structures and the promotion of scientific and technical accomplishments transformation may be achieved via the merger of industry and education with higher vocational education, particularly in the information technology era. This paper uses the fuzzy intuition stacked analysis method to compute the weights of the industry-education integration evaluation indexes and the binary semantics-based comprehensive evaluation method to convert the voice evaluation of experts into binary semantic information. According to the study’s findings, there will be 1,594 faculty members overall in 2021—114 more than there were in 2016. In 2021, there will be 1,012 full-time faculty members, representing 63.32% of the overall faculty members. Of the full-time professors on campus, 65.86% of them held a master’s degree in 2016. This represents the percentage of faculty degrees. 72.14% of all full-time professors on campus obtained their master’s degree in 2020, which is equivalent to 720 full-time faculty members. Furthermore, there is a general downward tendency in Institution B’s title faculty profiles from 2016 to 2020. Senior positions will be earned by 315 full-time faculty members, which is 31.56% of the total number of full-time professors on campus in 2020. In 2016 and 2020, the percentage of mid-level degrees was 48.38% and 45.19%, respectively. Assessing the degree of development of industry-taught integration can help modernize the governance structure and diversify the core integration. These developments will help enhance higher vocational education, enhance the development plan, and advance talent cultivation reform.
Reform of Innovation and Entrepreneurship Ability Cultivation System for Undergraduates in the Context of Economic Transformation and New Engineering Disciplines
Authors: Li Shangke 
Published: April 2024

Abstract
Science and technology and new industries are constantly changing, providing a more precise direction for innovation and entrepreneurship education in colleges and universities. To reform the cultivation system of college students’ innovation and entrepreneurship ability, this paper proposes the cluster core academic competence model (KAI) to analyze the learning process and the degree of knowledge absorption of college students engaged in bi-innovation education. The Group Learning Generation Network (GLGN) is constructed, and the GCN is used to update the GLGN, which can clearly show the practice and degree of difficulty of knowledge implementation, and focus on cultivating college students’ innovation and entrepreneurship ability. After the experimental research in this paper, the national innovation and entrepreneurship policy and innovation and entrepreneurship courses significantly correlate with the cultivation of innovation and entrepreneurship ability of college students. The Pearson correlation coefficient is 0.233 and 0.183 respectively, and the significance P-value is less than 0.01. From the aspect of the results of the innovation and entrepreneurship ability cultivation, the score of the college students’ participation in innovation and entrepreneurship competitions has risen to 0.098 after the reform, which shows that the reformed training system pays more attention to the education of innovation and entrepreneurship practice of college students.
Analysis of Artistic Instruction and Emotional Expression Pathways in College Piano Performance in the Internet Era
Authors: Liu Sha , Mao Dandan 
Published: April 2024

Abstract
As computer science advances, it intersects intriguingly with the realm of music acoustics, particularly in enhancing piano performance through technological means. This paper delves into an innovative approach to piano learning and creation, focusing on emotional expression’s nuances. We have devised a system capable of precise musical tone recognition and sound quality evaluation by adopting Mel Frequency Cepstral Coefficients (MFCC) for the nuanced extraction of piano sounds and integrating dynamic fuzzy neural networks. Our findings show an impressive accuracy rate, with musical tone misidentification below 2.58% and sound quality assessment errors within a 5% margin. This work not only sets a new benchmark in piano performance analysis but also paves the way for revolutionary teaching methods in music education, with profound implications for artistic instruction and emotional expression.
Reform of the Evaluation Index System of Civics Teaching in Higher Vocational Colleges and Universities Curriculum Oriented to the Demands of Vocational Positions in the Context of Deep Learning
Authors: Ma Xiaobing 
Published: April 2024

Abstract
Vocational and technical education professional courses have significant occupational relevance, and the teaching and evaluation design ideas of its course Civics should be drawn by the job tenure demand. In this paper, through the matching comparison between the characteristics of graduates of higher vocational colleges and the vector space of job demand characteristics, the residual optimal algorithm is used to construct the matching model of college students’ supply and demand so as to achieve the maximization of the total matching value between supply and demand. On the basis of the CIPP evaluation model and the teaching characteristics of courses in higher vocational colleges and universities, a fit analysis is carried out to construct the evaluation index system for the teaching of Civics and Politics in courses in higher vocational colleges and universities. The study shows that the weights of the four first-level indicators, namely, teaching background, teaching input, teaching process, and teaching effect, are 0.2042, 0.2592, 0.3754, and 0.1612, respectively, of which the teaching process has the most significant proportion of weight. Practical value can be gained from the teaching evaluation system.
Constructing Early Strategies for Cultivating Innovative Talents Based on Cognitive Behavioral Characteristics
Authors: Qiu Zhenzhong 
Published: April 2024

Abstract
The quest for innovative talent is more than an academic pursuit; it’s a strategic imperative for nations aiming to enhance their core competitiveness. Central to this quest is the early development of students’ scientific literacy, a focus grounded in cognitive behavior theory and enriched by the concept of ternary reciprocity. Our study introduces a novel approach to understanding and cultivating innovative talents, integrating a cognitive behavior system model to identify key influencing factors. Employing a fuzzy comprehensive evaluation method, we developed and tested an innovative talent cultivation strategy, yielding significant results: strategy effectiveness scores range from 2.1 to 2.3 for primary indicators and 1.8 to 2.3 for secondary indicators, with all indices showing statistically significant improvements (p < 0.05) when our strategies are applied. This research not only evidences the potency of our approach but also contributes actionable insights and methodologies for future innovative talent development.
Exploring the Path of Informatization Construction of Civic Education in Colleges and Universities in the Era of Melting Media
Authors: Shi Si 
Published: April 2024

Abstract
The development of informatization has increasingly become the transformation direction of the Civic Education in colleges and universities in the new media era. This paper outlines the path of civic and political information technology, in conjunction with campus networks in general, and presents a series of support mechanisms for information technology. Taking S university as a research case, firstly, Fractal Brownian motion is used to scientifically characterize the traffic of campus network users. The network group characteristics are estimated through the determination of the Hurst coefficient. Secondly, the Apriori algorithm is used to extract the association rules of online behaviors hidden in these traffic features to explore the relationship between online behaviors in time series. Finally, by combining the above features and association rules, we developed subspace clustering techniques for college students’ campus Internet usage behavior. We proposed a path for ideological education based on the clustering results. The results show that the online behavior of different students on campus shows significant differences. Class A students like to stay up late on weekends, and the number of such students online fluctuates slightly from 14:30 to 23:30. Class B students generally prefer to go online during the daytime. Class C students also have some students who stay up late, but the average duration is not long, with a maximum of 766 seconds. Class D students all stay up all night, and the peak of the mean value of the online duration occurs at 4:30. Class D students all stay up all night, and the peak of the mean value of the online duration occurs at 4:30. Category D students need to be given more attention in the management of political education.
Research on the Application Mode of Construction Engineering Safety Management Combined with BIM Technology
Authors: Wang Dongmei , Liu Shuqing , Jiang Weifeng 
Published: April 2024

Abstract
The advent of Building Information Modeling (BIM) technology heralds a new era in construction safety management. This research integrates BIM to forge a safety management system that proactively identifies construction risks and counteracts worker safety hazards in real-time. It also constructs a comprehensive BIM-based safety evaluation index, applying advanced multi-level fuzzy comprehensive assessment techniques and refined hierarchical analysis to calculate index importance. The study dissects safety management on multiple fronts through a detailed analysis of the construction safety practices at the new campus of People’s Hospital in Province A. The findings denote a basic level of success in collaborative safety efforts and an overall disappointing safety management score of 2.463, spotlighting an urgent need for systematic safety improvements within the project.
Exploration on the practice process of modernization of vocational education governance system based on big data
Authors: Yu Zhonghua , Feng Jian 
Published: April 2024

Abstract
In the era of big data, the integration of teaching and information technology has become a new trend in the development of modernized vocational education. Taking the big data majors of vocational college M as an example, this study explores the modernization of vocational education governance system, establishes a vocational education resource recommendation model based on K-Means clustering and FunkSVD algorithm, applies the model to analyze the students’ vocational abilities in terms of user profiles, and verifies the performance stability of the resource recommendation model through continuous iterative training of the model. Comparing the changes in students’ vocational abilities before and after using the resource recommendation model, the effects of the vocational education resource recommendation model are explored. It is finally concluded that the vocational skills of the selected students can be categorized into three types: the first type of students has the most muscular comprehensive strength and the highest proportion, 62.15%. The RMSE value of the resource recommendation model gradually decreases with the increase of data volume and iteration number. The RMSE value decreases by 0.06 when the data volume increases 10 times. The vocational ability of the selected students increases by about 0.05~0.15 after the resource recommendation, which verifies the recommendation effect of the model. The study can be used to improve students’ vocational competence and provide intelligent new ideas for the governance system of vocational education.
Construction of Intelligent Financial Supervision Mechanism for Colleges and Universities Based on RPA Technology
Authors: Zhao Huan 
Published: April 2024

Abstract
The RPA financial monitoring mechanism utilizes a predictive model to capture and store university data in preprocessing, and adopts a decision tree algorithm to construct a specific predictive model with good classification ability, and its logical structure is very similar to the decision-making ideas of human beings in the natural environment. CNN-LSTM financial risk assessment model is also utilized to carry out scientific risk assessment, the output of CNN is used as the input of LSTM, combining the advantages of the two to improve the learning ability of the financial fraud risk assessment model, and dynamic early warning can be accomplished beforehand for potential risk points. By analyzing the accuracy and coverage of the financial violation prediction model, 10.28% of violations were found with 96.7% accuracy. The accuracy is lower when the proportion of financial violations is higher. Risk assessment of fundraising activities and working capital of universities can be found that Z private universities have a relatively single source of income, tuition income is dominant, and in 2019, 2020 and 2022, the proportion of constructive expenditures of Z private universities reaches more than 20%, while the expenses of scientific research costs are less, however, the university’s comprehensive early warning status is relatively good. The financial risk is not significant and is in a safer range. In the university research fund violation supervision, the weight of researchers still have balance funds after two years after the completion of the project is 0.073, which indicates that the research project fund management supervision is not in place.
A study on the guiding role of educational management informatization in integrated physical education teaching and sports training
Authors: Zhou Yanhong 
Published: April 2024

Abstract
Employing the OpenPose model, this research advances the prediction and analysis of human skeletal points in videos, paving the way for refined action differentiation and posture analysis. By isolating unique posture features and developing a DTW-based algorithm for posture matching, we identify deviations in movements for corrective action in sports training. This methodology promotes the digitization of physical education, enabling personalized coaching and a detailed understanding of student performance. Our findings reveal a marked improvement in the experimental group’s movement evaluation scores, surpassing the control group by 82.86 points, with a P value of 0.000, and demonstrating significant skill test advancements (t=3.129, P<0.01). These results validate the approach’s potential to revolutionize physical education management and sports training with data-driven insights.
The Role of Mining and Detection of Big Data Processing Techniques in Cybersecurity
Authors: Wu Yubao 
Published: April 2024

Abstract
The need for advanced detection methods has become more critical in light of the increasing prevalence of network security incidents. This study proposes a novel approach to network security detection using a fuzzy data mining algorithm, addressing the rising challenges in big data processing and network security. The paper outlines the evolution of big data analytics by exploring the integration of network security detection, data mining, and structural feature analysis. Data for this research was collected using a sniffer device and underwent extensive preprocessing to ensure diversity and applicability. To overcome the limitations of traditional data mining, such as the issue of sharp boundaries, this method combines fuzzy logic with data mining techniques, enhancing conventional network security protocols. Simulation experiments demonstrate the efficacy of this fuzzy mining-based approach, with results showing 987,238 predicted positive cases, 93,951 of which were accurate. The method achieves an impressive 93.65% accuracy and 92.55% recall rate, proving its capability to promptly identify and mitigate suspicious network activities.
Line loss localization diagnosis and management measures of station area combined with data mining
Authors: Cheng Hui , Shen Jun , Wu Fangzhou , Gao Qian , Wei Yang 
Published: April 2024

Abstract
This study explores an advanced method for improving line loss in station areas, a vital issue in the energy sector. By analyzing line loss data from the X-area station using data mining and a novel convolutional neural network (CNN) model optimized with particle swarm optimization, we aimed to pinpoint and diagnose line loss issues effectively. Our model, which integrates specific line loss predictive parameters, underwent rigorous training and testing with collected data. The results were promising: the model's predictions closely matched actual data, with most errors under 0.1. It outperformed existing models in iteration speed, convergence time, and accuracy, evidenced by lower mean square error (0.0112), root mean square error (0.1023), and average absolute error (3.2514%). This research presents a potent tool for distribution network analysis, offering practical insights for line loss localization and diagnosis.
Application and Benefits of Building Information Modeling (BIM) in Intelligent Engineering Construction
Authors: Liu Hao 
Published: April 2024

Abstract
Currently, in China, intelligent construction research predominantly targets engineering projects, with limited focus on the benefits of Building Information Modeling (BIM) technology. This paper advocates for integrating BIM with cutting-edge engineering construction techniques, adhering to four intelligent construction level assessment principles. We introduce a benefit evaluation model for innovative construction, combining the two-dimensional cloud model with the Analytic Network Process (ANP) hierarchy method. Our findings highlight the significant role of BIM in enhancing operation and maintenance efficiency and in the deepening of design, evidenced by average scores of 4.0868 and 4.0691, respectively. Early stages of innovative construction projects benefit from BIM’s effective material usage control, reducing initial material consumption below planned levels. Furthermore, our analysis reveals BIM’s capacity to simultaneously optimize quality cost provision and additive cost, with Project 1 showcasing optimization indexes of 7.91% and 73.38%, respectively. These results underscore BIM’s substantial impact on improving the economic benefits of intelligent construction.