bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Application of PDCA Cycle Theory Combined with Subjective and Objective Empowerment Method in Teaching Quality Assessment System of Higher Vocational Colleges and Universities
Authors: Xiao Zhiyong , Li Hongfeng , Yuan Xianyu , Zou Linfeng , Liu Yan , Jiang Biao , Qiu Tiegang , Yin Jieqin 
Published: June 2024

Abstract
As the expansion of higher vocational education hastens the massification of higher education, issues concerning the quality of teaching at higher vocational institutions have become increasingly apparent. This study addresses these concerns by integrating the PDCA (Plan-Do-Check-Act) cycle theory to develop a robust assessment system for evaluating teaching quality in higher vocational colleges. Utilizing a combination of hierarchical analysis and entropy weighting methods, the assessment system is enhanced both subjectively and objectively. By employing higher vocational colleges and universities labeled M1 to M6 as illustrative examples, we apply linear weighted summation to derive comprehensive evaluation scores from the tested teaching quality evaluation index system. The empirical results indicate that the cumulative variance contribution rate of the assessment indices reached 91.765%. In the quality assessment, M4 scored the highest with a composite score of 4.60, while M6 scored the lowest at 3.49. Comparative analysis across dimensions shows that the index scores for M6 were notably lower than those of other institutions, ranging between 3.20 and 3.80. Implementing the proposed teaching quality assurance system resulted in a substantial increase of 0.77 points in its comprehensive score. Thus, the assessment and assurance system developed in this study proves to be practically valuable, offering an effective means to enhance teaching quality and elevate the educational standards in higher vocational colleges.
Application of Virtual Reality Technology in Historical and Cultural Landscape Reproduction
Authors: Xu Yi , Xie Meiling , Xiong Shuhui 
Published: June 2024

Abstract
Virtual reality panoramic technology transcends the constraints of time and space, offering audiences immersive visual and auditory experiences that diminish the costs associated with exploring historical and cultural landscapes and enhance communication effectiveness. This study employs fisheye cameras to capture panoramic images of such landscapes. The collected images undergo correction via spherical projection and reflective planar unfolding mapping. Subsequently, an enhanced method for optimal stitching line selection is applied to ensure seamless transitions between spliced images. The process is completed by integrating image interpolation and projection algorithms to virtually recreate historical landscapes. Analytical assessment of the model’s reproduction effects focuses on point error and accuracy. A practical application involving a real historical and cultural landscape is examined, revealing a maximum control point deviation from the optical scan of 0.02m and a minimum of 0.0014m, which negligibly affects the landscape’s virtual representation. Reproducing an actual landscape image yielded a maximum measurement error of 0.02m, a minimum of 0.01m, and an average of 0.0175m, affirming the capability for precise replication. This paper introduces innovative approaches and methodologies for leveraging virtual reality technology in the accurate reproduction of historical and cultural landscapes, illustrating its practical utility and effectiveness.
Study on the Role of Public Sector Human Resource Management in Educational Management Reforms
Authors: Xu Lei 
Published: June 2024

Abstract
The principles and methods of human resource management have been introduced into the field of education for some time, but the analysis of the current state of research, specifically on educational management, is still insufficient. The first part of this paper analyzes the measures that are related to human resource management in education management reform in each sector and further investigates the factor analysis method in the public sector human resource management system. By constructing the factor analysis model and factor calculation method, we can provide an algorithmic basis for studying the role of public sector human resource management in education management reform. The article utilizes the factor analysis method to conduct an empirical study by using the educational resources of different schools in 11 cities of Province A as test objects. According to the study, the first principal component has seven-factor loadings that are higher than 0.72, which indicates that all seven factors have a positive impact on the allocation efficiency of higher vocational education. The second principal component has four-factor loadings greater than 0.80, suggesting that all four factors have a positive effect on the allocation efficiency output of higher vocational education. From the sample data of the school education resource allocation status of each city, it can be obtained that the school education resource allocation status of city A is the most favorable, with the highest overall score of 43,153.1, followed by city B and city D, with 25,431.9 and 12,136.4, respectively. This indicates that the education resource allocation effect of these three cities is better and belongs to the upstream level in province Z.
Innovative Applications of Intelligent Assistive Systems in Interior Design
Authors: Yang Zhen 
Published: June 2024

Abstract
With the development of smart homes, virtual reality, and other technologies, people’s demand for digital modeling and visualization of interior space is increasing. How to quickly and accurately estimate the layout of the interior space has become a matter of great concern. This paper develops a 3D virtual visual interior design platform structure based on this. By studying the indoor multi-sensor fusion localization system, the localization module in the navigation process was designed based on this fusion result. The visual localization algorithm, WiFi localization, PDR localization, and AMCL fusion localization algorithms are introduced, respectively. The extended Kalman filter algorithm is used to fuse the algorithm with the highest state value for localization, which is used for scene recognition according to the algorithm localization effect. To achieve the 3D virtual visual impact, a 3D virtual visual interior design platform is created based on 3D virtual vision. Experiments are conducted on the localization system in the platform, and the error of all the localization points of the localization method combining vision and AMCL is no more than 1.1m, with the maximum error of 1.071m and the average error of 0.481m, which is the lowest error among all the algorithms. The localization sensor constructed by the localization algorithm using vision and AMCL with extended Kalman filtering has an average error of 10.33cm, which allows for good scene recognition. The data analyzes designers’ satisfaction with the use of the platform, and the independent variable in the regression equation that contributes most significantly to total satisfaction is the platform’s time-saving, with a coefficient of 0.324. The platform’s focus should be on enhancing time efficiency.
Comparison of Grouping Paths for Improving Technological Innovation Efficiency in Financial Enterprises in the Context of Digital Economy
Authors: Yue Dazhi , Gao Shuanping 
Published: June 2024

Abstract
Technological innovation efficiency is an important index to measure the development level of financial enterprises, and scientific and reasonable assessment of technological innovation efficiency is of great significance to play the role of financial enterprises in economic development. The article takes the upstream and downstream financial enterprises in province A as the research object. It proposes the super-efficiency DEA model on the basis of the data envelopment analysis method to measure the technological innovation efficiency of the sample enterprises. On this basis, the fuzzy set qualitative comparative analysis method is utilized to compare group paths in five aspects: digital economy, government subsidies, enterprise scale, profitability, and operational capacity. The results of the study show that the overall consistency of the conditional grouping scheme (H1: 0PER*GOV*DEC*PROF, scheme H2: DEC*SIZE*0PER*GOV, scheme H3: DEC*0PER*GOV) that promotes the technological innovation efficiency of the upstream manufacturing enterprises reaches 0.78, and the total coverage rate reaches 0.51. The conditional grouping scheme (scheme H2: DEC*SIZE*0PER*GOV, scheme H3: DEC*0PER*GOV) that promotes the technological innovation efficiency of the downstream manufacturing enterprises reaches 0.51. The overall consistency of the conditional configuration scheme (Scheme L1: DEC*~SIZE*0PER, Scheme L2: ~SIZE*PROF*~GOV, Scheme L3: DEC*PROF) reaches 0.91, and the total coverage rate reaches 0.45. The research results reveal the differences between the current upstream and downstream technological innovation efficiency and driving paths in the financial industry and have some guiding significance for the choice of paths of the financial industry innovation drive. It has a certain relevance that is guiding.
A Study of Vocabulary Teaching Strategies in ESP Instruction and Their Effects on Students’ English Vocabulary Learning Using the Subsumption Sorting Algorithm
Authors: Zhang Jun , Liu Zhenqian 
Published: June 2024

Abstract
To facilitate the application of the subsumption sorting algorithm within vocabulary instruction, this study develops a novel Learning Management System (LMS). This system adopts the ESP vocabulary teaching model as its primary instructional framework delves into the requisites of English vocabulary acquisition, the system’s architecture, and its instructional content. It employs an enhanced DTW pattern-matching algorithm to dynamically refine English vocabulary resources. Furthermore, it integrates the merging and sorting algorithm to augment the efficiency of the LMS operations, enabling precise management of student learning progression and vocabulary retention. Comparative analyses of various sorting algorithms were conducted alongside assessments of the impacts of the LMS and ESP vocabulary teaching models on vocabulary learning outcomes. The findings from a semester-long study of vocabulary instruction indicate significant improvements within the experimental group: increases of 6.3, 5.32, and 9.33 points in word form, meaning, and usage accuracy, respectively. Notably, the usage of vocabulary saw the most substantial enhancement. The ESP model-based English vocabulary LMS effectively ameliorates students’ vocabulary usage errors and enhances accuracy in vocabulary application.
Student Management Perspectives on the Moderating Effects of Biological Clock Interventions on Mental Health
Authors: Zhao Chuang 
Published: June 2024

Abstract
In today’s fast-paced life and learning rhythm leads to the generalization of mental health problems in the student population, the biological clock, as one of the links that regulate the functioning of the human body, has been increasingly emphasized in the regulation of mental health. The study selected 545 students in School Z for the experiment on biological clock intervention in students’ mental health. It randomly divided them into an experimental group and a control group for comparison. The SDL-90 scale and SDS scale were used as the basis of the questionnaire design, and independent t-tests and pre-and post-test analyses were conducted on the collected data on students’ mental health to investigate the intervention effect of the biological clock on students’ mental health. The results showed that before the experiment, the mental health level of the experimental group (2.395±0.375) was slightly inferior to that of the control group (2.253±0.342). After the experiment, the mental health level of the experimental group was significantly improved; the total mean score on the SDL-90 scale was reduced from 2.395 to 1.932, and the total mean score of SDS was reduced from 52.242 to 36.769. The intervention of the biological clock had a significant positive effect on reducing the students’ depression and improving the students’ mental health levels.
Design of automatic style classification system of visual art works based on image processing
Authors: Dan Jin 
Published: June 2024

Abstract
The emergence of a vast array of visual artworks meets the growing public demand for cultural literacy while simultaneously presenting challenges in the understanding and selection of appropriate artistic styles. Leveraging advancements in image processing technology, this study successfully automates the classification of 158,652 visual art images by categorizing them into distinct artistic styles. A novel approach combining the Scale-Invariant Feature Transform (SIFT) feature extraction algorithm with the spatial pyramid matching technique is introduced. This paper details the development and evaluation of a classification system tailored for the automatic categorization of visual artworks. Comparative testing results demonstrate that this innovative combination surpasses the traditional SIFT algorithm in both execution speed and classification accuracy. Specifically, the Support Vector Machine (SVM) based classification system, utilizing the enhanced SIFT method, achieves an accuracy rate exceeding 90% in identifying five distinct styles, including PHPS, NOS, IS, TF, and AAS. The implementation of this automatic classification system proves to be a practical tool in aiding individuals to select the visual artwork style that best suits their preferences.
Landscape ecological network construction method supported by high-precision GIS data
Authors: Chen Lulu 
Published: June 2024

Abstract
With the acceleration of urbanization, the regional landscape pattern has undergone profound changes. This study combines green space ecology and explores the construction method of landscape ecological networks using the support of GIS data platform. After completing the extraction of landscape environmental information, it is fused and processed using principal component transformation, tasseled cap transformation, and vegetation index extraction. Different landscape pattern indices are utilized to construct a landscape analysis pathway based on the relevant data from high-precision GIS. Meanwhile, an ecological sensitivity evaluation method that includes soil erosion and rocky desertification was proposed. By comparing and analyzing the landscape pattern indices, it was concluded that the Shannon diversity index increased by 0.2927 and the Shannon evenness index increased by 0.0352, indicating that the landscape types of the study area gradually tend to be even in quantity and spatial distribution. In the evaluation of ecological sensitivity, the proportion of moderate and lower sensitivity reaches 69.28%, indicating that the ecological environment is relatively calm despite external disturbances.
Intelligent Analysis and Predictive Modeling of Tennis Match Data
Authors: Dong Yansong 
Published: June 2024

Abstract
In today’s sports environment, prediction has a significant effect on athletes to achieve good performance and improve training efficiency. This study explores the construction of a prediction model for tennis match data based on an intelligent analyzing system in combination with tennis match results. The probabilistic algorithm for predicting tennis tournament performance has been designed and implemented, and the Glicko ranking system has been optimized using the improved Apriori algorithm. After cleaning, integrating, and dimensional standardizing the data from previous tournaments, the player’s match ranking is predicted based on the Glicko ranking system. Players’ eigenvalues, technical averages, and tactical decisions are used to verify the accuracy of the model prediction. All 10 selected features have a certain degree of influence on the match results, as evidenced by the results, suggesting that the model has a certain reference value. According to the ranking prediction based on athletes’ technical averages, the prediction correct rate of both the Australian and French Open reaches no less than 80%, which proves that the model in this paper is able to effectively predict the performance of tennis tournaments.
The application of carbon footprint assessment under intelligent computing in green consumption decision-making
Authors: Du Yu , Zhou Qingna , Li Zhiwei , Zhang Ziying 
Published: June 2024

Abstract
Reducing carbon emissions is a basic policy long insisted on by the Chinese government, and the calculation of carbon footprint is of great application significance for reducing carbon emissions and realizing green consumption. Based on the multi-objective planning model this paper establishes a carbon footprint assessment model based on multi-objective planning from the economic, environmental, and social benefits of carbon footprint. It optimizes the particle swarm algorithm to solve the objective function of the carbon footprint multi-objective assessment model. The designed model is utilized in green consumption decision-making to forecast the carbon footprint and structure of green energy consumption in the future. The comparison shows that after the optimization of the carbon footprint assessment model based on multi-objective planning designed in this paper, the proportion of coal and oil consumption in the carbon footprint of energy consumption decreases by 1.2% and 0.5%, respectively, and the energy intensity can be optimized. The per capita carbon footprint of energy consumption of residents in eastern, central, and western China grows by 11.3%, 15.2%, and 2.7%, respectively, from 2024 to 2026. The carbon footprint of per capita energy consumption in the three regions is quite different. The results of the two projections show that the carbon footprint assessment model based on multi-objective planning designed in this paper is important for improving the energy consumption structure in different regions and realizing green consumption decisions.
The Design of Online Interactive Teaching Model of College English Combined with ICD Modeling
Authors: Duan Ting , Chen Mingming 
Published: June 2024

Abstract
Amidst the swift advancement and integration of science and technology in educational frameworks, the traditional pedagogical approaches to college English necessitate significant transformation and enhancement. This study introduces an online interactive teaching mode for college English, devised through the utilization of the Integrated Curriculum Design (ICD) model. This innovative model synergistically incorporates neural networks with backtracking search optimization to foster a dynamic educational environment. The preliminary establishment of the online interactive teaching mode, grounded in the ICD model, was thoroughly analyzed and researched. Subsequently, the strategic integration of the BP neural network with the backtracking search optimization algorithm furnishes robust technical support, thereby laying a solid foundation for extensive analytical undertakings. Empirical analysis reveals that students, teachers, and parents from varied geographical and socio-economic backgrounds demonstrate disparate performances across several metrics. Nonetheless, there remains a uniformly high level of satisfaction with the online interactive teaching modality, indicative of its effectiveness and acceptance. Notably, when juxtaposed with conventional offline teaching methodologies, the newly designed online mode evidences an enhancement in students’ auditory comprehension efficiency by approximately 28.74%. The advent of this online interactive teaching mode for college English, predicated on the ICD model, plays a pivotal role in catalyzing the burgeoning “Internet + education” paradigm, underscoring its potential to revolutionize traditional educational ecosystems.
The Role of Cloud Computing Platform in Improving Resource Allocation Efficiency of Training for Male Badminton Players
Authors: Gao Fei , Wang Ziya 
Published: June 2024

Abstract
In recent years, the deployment of computer vision technology across various applications for recognizing human posture and behavior has significantly advanced the field of sports training research and development. This study introduces the application of the OpenPose algorithm to estimate badminton training postures and identify critical points on the human skeleton. Following the identification of these points, we construct a human posture estimation model, which involves preprocessing the data through steps such as detecting key human points, removing redundant points, establishing a two-dimensional coordinate system, and substituting missing key points. The implementation of this algorithm is hosted on a cloud computing platform. Subsequently, we collect relevant data and execute feature extraction using the coordinate normalization technique. This paper analyzes the training postures and suggests an optimization strategy for the allocation of training resources aimed at enhancing the efficacy of training plans. The application of these optimized training schemes resulted in significant improvements in the players’ badminton skills, particularly in forehand high ball hits and serves. Notably, in the experimental tests of forehand high ball hits and serves, the skill levels were recorded at 16.56 and 15.29, respectively—outperforming the control group’s scores of 14.98 and 13.65.
A biomechanics-based study of stroke technique in student tennis players
Authors: Kang Wanchun , Liu Yang 
Published: June 2024

Abstract
Studying the hitting technique of student tennis players is of great significance in improving the technical and tactical level of student tennis and promoting the popularization and scientificization of tennis. Since the performance of tennis hitting action recognition depends on the representation of the action, this study utilizes the Gaussian mixture distribution as a statistical distribution of human action data to provide a more accurate description of tennis hitting action. This paper presents the LM skeletal point coordinate fitting method to enhance the structure of the Gaussian mixture distribution-based Hidden Markov Model to capture the act of hitting the ball. In the end, the biomechanical properties of the tennis hitting technique were examined by analyzing the motion images of forehand and backhand hitting techniques of college tennis players. The mean values of the angle between the racket surface and the ground during the forehand stroke and the topspin stroke were 82.96° and 35.95°, respectively, and the speed of the grip point and wrist joint was faster than that of the flat stroke during the topspin stroke. The angles and velocities of the knee, hip, and ankle joints of the lower limbs were faster than those of the open backhand stroke in the closed backhand stroke. The angle and speed are smaller than that of the open backhand stroke, while the angle of the shoulder and elbow joints is larger than that of the open backhand stroke. The tennis action recognition model and algorithm designed in this paper can effectively acquire and analyze the technical characteristics of tennis hitting.