bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on the work-hardening behavior and tissue property analysis of high-strength magnesium alloy
Authors: Zhang Congzheng , Liang Chen , Mu Jinpeng , Chen Haodong , Zhang Wei , Li Wenhao 
Published: September 2023

Abstract
Magnesium alloys show great superiority for modern applications due to their good biocompatibility, degradability, and excellent mechanical properties. In this paper, the strengthening effects and mechanisms of composite precipitation phases, microalloying regulated recrystallization behavior, composite grain organization, and new strain aging methods in magnesium alloys are investigated in terms of five stages of work hardening, heat treatment, and strengthening properties. The use of rare earth elements can effectively enhance the aging strengthening properties of magnesium alloy through the use of gadolinium (Gd) and yttrium (Y) in rare earth elements for the development of high-strength magnesium alloy. The results show that the solubility of aluminum in magnesium reaches the maximum of 12.6mmass.% at the eutectic temperature of 436℃and then gradually decreases with the decrease of temperature, and when the temperature decreases to room temperature, the solubility decreases to 2mass.%. The elongation of alloy 0.5Al alloy 0.5Zr alloy on the basis of the aging state was 6.7% and 4.8%, respectively. This paper provides theoretical and experimental guidance for the development of high-strength magnesium alloys through an in-depth study of strengthening mechanisms such as composite precipitation strengthening, crystal strengthening and strain aging strengthening.
An innovative approach to teaching physical education integrating modern network technology
Authors: Guo Huijuan 
Published: September 2023

Abstract
This paper first investigates the modern web technology algorithm data preprocessing process and database creation methods, dealing with missing data values, attribute coding and performing data normalization, and converting feature coding to Boolean values for teaching data in order to create a database. Then the data are sparse and regularized so that the coefficients corresponding to the features with strong optimization effects on the model are not zero. The physical education data are then evaluated using modern web technology algorithms. Then the advantages and disadvantages of traditional and innovative teaching methods were compared to support them. Finally, the effect of innovative teaching methods was evaluated in terms of students’ physical fitness change and teaching satisfaction. In terms of changes in students’ physical fitness, the increase in lung capacity of students in both classes after applying the new method p=0.042, which was less than 0.05 and greater than 0.01, indicating that the increase in lung capacity of students in the experimental class was higher than that of students in the control class, proving the significant effect of the experiment on the increase in students’ lung capacity. In the feedback of experiencing the pleasure of exercise and the sense of success and joy of completing the movement, the index of the experimental class was 48, and the control class was 42. The effect of the innovative teaching method integrating modern network technology was superior to the traditional method.
Research on quality engineering management effectiveness improvement strategy of universities based on fuzzy clustering maximum tree algorithm
Authors: Zhang Lei , Dong Yin , Yao Na 
Published: September 2023

Abstract
The “quality project” is an objective need to promote the comprehensive and coordinated development of higher education and cultivate high-quality talents. Based on the fuzzy clustering maximum tree algorithm, this paper first generates the maximum tree for a similar matrix and then clusters the maximum tree to find the clustering results. Then the idea of fuzzy clustering maximum tree algorithm is introduced into the management of “quality engineering” in Heilongjiang province colleges and universities, and the necessity of project management in the management of “quality engineering” in colleges and universities is analyzed, so that the knowledge related to project management can be applied in the construction of “quality engineering” in colleges and universities. “The results show that project quality management has a lot of advantages and disadvantages. The results show that there are problems such as weak awareness of quality management among all staff, unclear construction objectives and quality construction standards, and a lack of effective project monitoring and evaluation mechanism in project quality management. During the experimental period, the groundwater level was 0.4~0.7m below the surface, and the global risk level decreased from 5 to 3 along with the deep excavation of the foundation pit, and the risk probability of the foundation pit project became larger with time and finally stabilized at 60%. The research of this paper is helpful to improve the project management level of “quality engineering” in universities and promote the transformation of “quality engineering” results, which has certain practicality and guidance.
Optimization analysis of transmission characteristics of wireless energy transmission system based on dynamic tuning algorithm
Authors: Du Ruijuan 
Published: September 2023

Abstract
This paper aims to optimize the transmission characteristics of the wireless energy transmission system by optimizing the design of the coupling coils in the system, the system multi-parameter matching and the coil offset problem so that the overall wireless energy transmission system works in the best condition. The mathematical model of the power and efficiency of the two-coil MCRWPT is derived through the optimal tuning theory, and the principle of the wireless energy transmission method is analyzed to determine the wireless energy transmission method of the equivalent capacitive regulation circuit. By comparing the effects of load on output power and transmission efficiency under different topologies, a plane with a two-coil structure applicable to the wireless charging transmission system is selected to improve the transmission efficiency of the system. In the experimental verification of the WPT transmission characteristics optimization and dynamic tuning, it is concluded that the efficacy of the system is improved simultaneously with the transmission efficiency up to 91% when the load is adjusted to 298 mΩ for the load value adjusted at the transmission distance of 0.075m.
Exploration of digital media art professional design talent class training based on K-mode algorithm
Authors: Huang Zongyan 
Published: September 2023

Abstract
This paper combines big data technology to analyze the training mode of digital media professionals in universities in various regions and explores the knowledge system, enrollment target, learning content, textbook construction, and employment direction of digital media professional training, respectively. The real data in the faculty management system is selected as the evaluation data, and the K-modes clustering algorithm is used to optimize the evaluation data in three problems, such as the number of clusters K, the initial clustering center, and the calculation of distance similarity. According to the research content, the evaluation index system of teachers’ teaching conditions in Y school was established, and the system was applied to evaluate the teaching operation of Y school comprehensively. The results showed that only 6.89% of the teachers were evaluated as “excellent”, 46.89% were evaluated as “good”, and 46.89% were evaluated as “medium”. The percentage of those who rated “medium” or below was 45.89%. This indicates that the university still needs to do a lot of work in improving teachers’ ability to meet the needs of college students in the new era. The application of the K-modes algorithm in the evaluation of digital media art professionals’ training is of great significance to the development of the digital media industry.
Exploring the application of virtual space in spatial design in the era of artificial intelligence
Authors: Ding Pei , Ai Hongjuan , Moon Hyoun-Sun 
Published: September 2023

Abstract
The development of the Internet era acts on every change brought by spatial design so that the application of virtual reality technology in spatial design solutions begins to emerge. In this paper, firstly, combining the general process of visualization and the characteristics of visual variables, seven visual variables are selected for preliminary 3D visual representation, and their applicability under virtual reality space is analyzed. The HSV color space is also used for visual coding. According to the intuitive nature of visual perception of spatial design, a multiple visual variables mapping model based on VR is proposed. Considering the sequential characteristics of spatial design, PCA-LSTM spatial design classification model is proposed, and virtual space is applied in spatial design by local changes of the top surface, ground surface, and vertical interface. The simulation experiments are conducted by selecting SVM, BP neural network, and LSTM network as the comparison algorithms, and the results show that the accuracy of both the training set and the test set is found to be improved based on the PCA-LSTM classification model for spatial design classification, which is 4.9% and 9.49% higher than the traditional LSTM algorithm, respectively, verifying the PCA-LSTM for spatial design The effectiveness of PCA-LSTM for spatial design classification is verified. This study cleverly uses the design technique of virtual space to better apply virtual space in spatial design.
An analysis of the innovation strategy of student management in universities based on big data
Authors: Wu Cuicui 
Published: September 2023

Abstract
This paper collates and fuses data from various aspects of university students and designs student evaluation indexes by combining the data. Based on the student behavior segmentation model of cluster analysis, the traditional k-means clustering algorithm is optimized, focusing on the optimization of content selection of initial cluster centers and distance optimization calculation to make a better clustering effect and classify students accurately. Then the K-nearest neighbor algorithm is proposed to solve the problem of timeliness and posteriority of student warning, by which the behavior of students can be predicted, and teachers can manage and help students in time. Finally, a student behavior characteristic category model is established to strengthen the prediction model of the K-nearest neighbor algorithm and improve the accuracy of predicting student behavior. The student data of a university were analyzed, in which the correlation pearson coefficient between the number of library admissions and grades ranged from 0.25-0.31, and the p-values were all much less than 1. It showed that the number of library admissions of students obviously affected students’ grades. In the analysis of the correlation between the early rising index and academic achievement, where the Pearson coefficient is 0.291 with a p-value of 5.61E-7. This indicator, which is not much associated with academic behavior, indicates that students’ early rising and timely breakfast can affect achievement to some extent. Therefore, the method of this paper can be refined using student data.
Analysis on the innovative education mode of the integration of information technology and traditional teaching in the era of big data
Authors: Lv Foguang , Wang Wei , Ren Jianhua 
Published: September 2023

Abstract
In order to develop students’ concentration in the classroom, this paper proposes to analyze students’ learning concentration from three dimensions, where the superiority of the random forest classification algorithm is found in the dimension of head posture estimation so that students’ attention ranges can be analyzed. For data acquisition, the OpenPose platform is used for real-time detection of body, foot, hand, and face key points. A comprehensive evaluation study of students’ concentration levels in the classroom was achieved through an effective algorithm. Finally, the multimodal information fusion algorithm was investigated, and it was concluded that the weights could be calculated by hierarchical analysis to achieve a comprehensive evaluation of students’ learning concentration. By analyzing the course data of 12 students, the distribution of SFR values, Yaw angle and Pitch angle distribution, PERCLOS value distribution, and correct/error rate distribution of answers were counted, and the final scores of respective learning engagement were obtained as 0.91, 0.62, 0.80, 0.36, 0.82, 0.73, 0.81, 0.63, 0.81, 0.81 The model scores were compared with the expert scores, and the accuracy rate reached 98.6%, which proved that the model proposed in this paper is effective and can correctly reflect the real state of students’ learning in the classroom.
Innovation and exploration of construction project management based on BIM platform of big data
Authors: Yin Hui 
Published: September 2023

Abstract
The study of BIM engineering management platforms based on big data is conducive to improving the status quo of traditional construction engineering and providing new ideas to realize the innovation of construction engineering project management. This paper takes construction engineering project management as the research object, based on the BIM platform of big data, and understands the current difficulties and key points of safety management by investigating and analyzing the status of construction engineering project management and BIM the application status of the platform. Secondly, we make full use of building information model data standards, including: IFC standards, IDM standards, and MVD standards, to analyze building information model data standards. Finally, the data establishment practice is carried out based on the foundation BIM construction model that satisfies the 300 LOD level for the model components. The results satisfy the consistency test, and the weight coefficients are considered to be reasonably assigned. According to the judgment matrix to calculate the weights, the matrix is normalized by column, and the weights of each index are obtained as 0.6377, 0.2580, 0.1034, 0.1790, 0.1130, respectively. This paper is based on big data BIM technology application and construction process safety management activities, which can realize the information management of the whole project construction, strengthen the benefits of construction project safety management, and provide collaboration of all parties to provide a favorable sharing platform.
Exploring Innovative Strategies for Teaching English to College Students Based on Data Mining Theory
Authors: Duan Xiaolian 
Published: September 2023

Abstract
This paper suggests a J2EE framework-based online intelligent diagnostic assessment scheme. The system has the capabilities of teaching, diagnosis, testing, and feedback as auxiliary teaching software through the automated alteration of subjective and objective questions and the individualized design of diagnostic results. Combined with the characteristics of English composition, the research focuses on the use of the shortest editing distance, cosine vector space, regular matching and other techniques to automate the composition correction and diagnosis, which not only realizes the final scoring of subjective questions but also the diagnostic report can provide students with personalized comments, precisely give the strengths and weaknesses in terms of knowledge points, as well as the analysis chart of knowledge points, scores and ability values of previous exams. In this paper, when evaluating the system with teacher ratings, the overall mistake rate for class essays was 9.0% when the similarity criterion S=0.2 was employed. For individuals and classes passing the test, the error was within 10%, and the score difference was within 2 points. Finally, the common errors of students in English writing were detected, with grammar errors accounting for 58.2%, vocabulary errors for 26.7%, and essay errors for 15.1%. Therefore, this system can make a good contribution to the teaching reform of English and achieve a real reduction of the burden for teachers and students.
A Study on the Influence of Ecological Translation Theory on University English Translation Teaching in the Context of Big Data Analysis
Authors: Zhou Haiyan 
Published: September 2023

Abstract
This paper aims to investigate the influence of ecological translation theory on university English translation teaching, constructs a regression prediction model prediction result evaluation index on the basis of a regression model, uses the regression prediction model to analyze the data of classroom percentage in the process of university English teaching, and combines the prediction result evaluation index to study the influence of ecological translation theory on university English translation teaching, by analyzing the English translation content and translation By analyzing the two factors of English translation content and translation standards, suggestions are made for the subsequent development of university English translation teaching. The result data showed that in the university English translation classroom, the teacher-led time accounted for 60 minutes, the students’ independent discussion time was only 20 minutes, and there were only 10 minutes to test everyone’s classroom results. In terms of classroom content, the highest percentages of vocabulary content and grammar content were 30%, 40%, and 35%, respectively, and the lowest percentages of translation content were 10%, 5%, and 5%, respectively. The research data in this paper provide an effective reference for university English translation teaching and promote the development and progress of university English translation teaching.
The Application and Exploration of Curriculum Ideology and Politics in the Innovation and Entrepreneurship Education of Medical College Students Based on Hierarchical Analysis Method
Authors: Qi Wenjuan , Liu Xiaohui , Niu Renxiu 
Published: September 2023

Abstract
Promoting “mass entrepreneurship and innovation” in the context of the new norm of the Internet era is the inescapable trend of the moment. In order to provide the atmosphere and circumstances for innovation and creation education in educational institutions, this study first investigates the application of curricular ideology and politics in innovation and creative education. This is primarily expressed in the leading of innovation and creation education ideals. The set of data on college students’ innovation and entrepreneurial is then pre-processed in accordance with the hierarchical analysis method to obtain the data judgment matrix, and when combined with the fuzzy detailed evaluation method, a science-based system of college students’ innovation and creation education quality assessment model system is created. The initial data set was obtained through a sample survey, and the specific analysis of the connotation traits and interaction between innovation and creation education and ideological and political education of colleges and universities was conducted by using hierarchical analysis. The results show that the reliability coefficient is 0.926 with good reliability, and the validity KMO is 0.946 and passes the signature verification. Ideologic and political theory courses, daily ideologic and political education and self-efficacy were significantly and positively correlated at the level of 0.01. This study is a joint effort to endorse the deepening of innovation and the creation of education reform in higher education. This has a significant historical impact on cultivating socialist architects and successors with thorough moral, intellectual, physical, and artistic development.
A Study on English Teachers’ Behavior and Teaching Effectiveness in Universities Based on Big Data Technology
Authors: Zhang Jiao 
Published: September 2023

Abstract
Based on the traditional Flanders interaction analysis method, this paper proposes a new method for analyzing English teachers’ behavior by combining long and short-term memory networks in deep learning techniques. Firstly, the Flanders coding system is optimized in the coding stage, and the English teacher behavior categories are refined to better reflect the integrity, richness, and diversity of the classroom teaching process so as to construct an English teacher behavior dataset. Then, we designed the research protocol, determined the research subjects and instruments, classified the time series representing English teacher behavior based on the LSTM English teacher behavior analysis model in the results and analysis phase, and analyzed and evaluated the correlation between teacher behavior of students’ English learning achievement based on the classification results. The results show that the probability of getting the English teacher behavior evaluation index categories 1 to 4 is 0.6111, 0.00049, 0.002, and 0.3882, respectively. There is a significant correlation between both student learning achievement and teacher behavior, and the correlation coefficient of both is (r =0.73). Teacher behavior affects the achievement of student learning effectiveness. This study helps teachers to reflect on their teaching behaviors so as to improve the quality of teaching in higher education.
Research on intelligent recommendation algorithm of literature based on knowledge graph technology
Authors: Yin Zhiqiang 
Published: September 2023

Abstract
To address the issue of cold start and data sparsity in recommendation algorithms, this paper introduces a knowledge graph to assist intelligent recommendation algorithms in exploring. Firstly, it is introduced that the introduction of knowledge graphs into recommendation algorithms can introduce more semantic relationships as well as mining higher-order connection relationships, thus improving the purpose and user satisfaction. Second, the three categories of extant recommendation techniques—embedding-based, path-based, and propagation-based—are compiled. We examine how the current methods extract data from entities and connections in the knowledge graph and contrast the benefits and drawbacks of the three different types of approaches. Furthermore, the AUC metrics on the three datasets improve by 2.9%, 1.6%, and 1.2% over the state-of-the-art baseline, respectively, showing the effectiveness of the KGAT-CI model in using collaborative and knowledge-aware information, according to experiments on intelligent algorithms in the literature. It may be determined that the addition of knowledge graphs can improve the present recommendation algorithms’ accuracy, variety, and interpretability.