bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integration of Computer-Assisted Teaching Technology in English Online Education Platforms
Authors: Wang Hongjuan 
Published: August 2024

Abstract
This study proposes an English online education platform centered on the English teaching resource management module and the teaching resources personalized recommendation module on how to closely integrate computer-aided technology into English teaching. In the English teaching resource management module, the fuzzy comprehensive evaluation method is utilized to evaluate teaching resources. An improved placement algorithm, ERRPA, based on the rating of educational resources, is proposed to improve the insufficiency of HDFS files and achieve allocation node modeling. In the English teaching resources personalized recommendation module, then a collaborative filtering algorithm for user clusters is proposed to filter some noisy users using the UCC algorithm, and mix the predicted ratings with the actual ratings through the rating mapping to obtain good recommendation prediction results. In the teaching application of the English online teaching platform, the passing rate of the subject students was improved by 13.79%, the average learning tasks were completed by 59.1% in the online learning behaviors, and the average learning video viewing time reached 89.2 minutes. Learning interest, learning attitude, and sense of independent learning in learning status were improved by 3.2, 4.38, and 4.28, respectively, compared with the pre-experiment, showing highly significant differences (P<0.01).
Application of nonlinear signal analysis in millimeter-wave radar blood flow rate monitoring
Authors: Zhang Lina 
Published: August 2024

Abstract
Due to the advantages of millimeter-wave radar, such as its relatively simple structure, small size, high sensitivity, etc., it is used to obtain the human pulse signal and blood flow signal. Using the methods of mean cancellation, phase differencing, and smoothing, static clutter removal and heartbeat signal enhancement can be achieved, which can effectively eliminate interference information. Based on the collected information, the three-dimensional Navier-Stokes equations and boundary conditions are determined, and the theoretical knowledge related to fluid mechanics and bioengineering is used to construct the model of the multidimensional blood monitoring system, and the nonlinear signal analysis method is used to analyze the application of the constructed model. Based on the data, there is only a 0.1% difference between the waveform of the blood vessel diameter measured by the multidimensional blood monitoring system and that of the blood vessel diameter tested by commercial ultrasound equipment. The waveform trend is also consistent. In addition, the blood flow velocity at point 5 was much greater than that at point 2, when the vessel stenosis exceeded 50%. This study can accurately and efficiently monitor blood flow velocity for single and multiple individuals, which is critical for the healthcare field's development and innovation.
Intelligent Generation System for Personalized Physical Training Programs and the Effect of Practical Application
Authors: Meng Qingbo 
Published: August 2024

Abstract
With the comprehensive construction of quality education, physical training is an important way to cultivate students’ physical quality, and its related construction is gradually receiving comprehensive attention and support. This paper discusses the intelligent generation scheme of sports training plans, which aims to meet the individual needs of students through algorithms while developing the best training plan for them. This paper first introduces the overall architecture of the sports training program generation system. Secondly, the association rule method is utilized to mine the sports training data, and after elaborating the concept of association rules, the FP-growth algorithm is proposed to carry out the data mining work with the FP tree at the very beginning as the core. Then, a decision tree model based on the ID3 algorithm is constructed to correctly classify the training program based on the attributes selected at each level of nodes in order to obtain the attributes with maximum information gain. An empirical analysis of students from all grades in a school showed that there is a correlation between the various sports training programs of male and female students. After using the sports training program generation system designed on this basis, the boys’ 50-meter run performance (P<0.01), boys’ standing long jump performance (P<0.05), and girls’ 50-meter run performance (P<0.05) were significantly improved.
Strategies for Cultivating Oral Proficiency in English Teaching and the Construction of Evaluation System
Authors: Wang Qi 
Published: August 2024

Abstract
Today’s society promotes and improves teaching in various ways. However the teaching of spoken English still lacks the guidance of scientific method. The importance of oral teaching is becoming more and more prominent in English teaching. Therefore, this paper proposes specific oral teaching training strategies to explore effective methods of oral evaluation after applying the DTW construction strategy. The cultivation strategy of spoken English has been improved from the perspective of teachers. The speech evaluation system is designed and implemented to normalize the speech signal and then add windows to it in frames. SMFCC, volume intensity, and fundamental trajectory were chosen as the feature parameters of the system comparison. Parameters were extracted from the amplitude spectrum, and after feature extraction, parameter distance calculation was carried out on the feature parameters so as to get the results of English-speaking level scoring. According to the study, the teaching model that incorporates the English-speaking development strategy significantly improves the students’ speaking ability compared to the control class. Moreover, the evaluation system’s performance in terms of exact agreement rate and neighbor agreement rate is consistently above 90%, which indicates that the system can objectively evaluate the students’ oral proficiency.
Construction and Optimization of Deep Learning-based Innovative Experimental Platform for Mathematical Intelligence in Electricity Major
Authors: Wang Qiuyan , Xiong Yuejia 
Published: August 2024

Abstract
Due to the lack of management capability of the model development process on traditional experiment platforms, they cannot meet the continuous experimentation, reproducibility, and traceability needs of university researchers in the model development process. For this reason, the authors propose research on the design and optimization of a platform for digital intelligence innovation experimentation that is combined with deep learning. Through a theoretical analysis of the key technologies used in the deep learning development platform, the authors summarise the design structure of the deep learning innovation experiment platform. The algorithm management module, training management module, and model deployment module primarily construct this structure. Aiming at the problem of the slow computation speed of the platform in large data sets and high-dimensional space, a gradient descent algorithm is used to optimise the platform. The platform is validated and analyzed in terms of performance testing and application effects. The results show that the experimental platform optimized by the gradient descent algorithm has a higher throughput than the traditional experimental platform, and the difference is 0.1~1.5. Also, class A’s total score on experimental reflection ability (2.58±0.877) was significantly higher than class B’s (1.48±0.377) after the experiment, and the p-value was less than 0.05, which showed that the new experimental platform was more likely to improve students’ experimental reflection ability than the old way of teaching.
A Study on the Construction of Hakka Sports Culture Data Model and Its Innovative Effect in the Modernization Process
Authors: Cui Shengli , Wang Shuiquan 
Published: August 2024

Abstract
By analyzing the theory of the origin of Hakka sports culture, the characteristics of Hakka sports culture are summarized. Based on the principle of evaluation index system construction, the evaluation indexes of Hakka sports culture are initially formulated, and the coefficient of variation is used for screening to finalize the evaluation index system of Hakka sports culture, which consists of 4 first-level indexes and 13 second-level indexes. Based on the scale table, the indicators are compared two by two, the corresponding judgment matrix is constructed, and the judgment matrix is normalized by using the fuzzy hierarchical analysis algorithm to get the evaluation indicator weight values, and the consistency test is conducted on its weight values. According to the steps of the fuzzy comprehensive evaluation, a set of evaluation phrases is formulated to verify and analyze the evaluation model of Hakka sports culture. The results show that the sports behavior culture (0.3461) > sports material culture (0.2456) > sports institutional culture (0.2285) > sports spiritual culture (0.1798), while the comprehensive evaluation analysis result of Hakka sports culture is 3.3707, and the comprehensive evaluation grade of Hakka sports culture in the region is in the range of average to good, and summarizes the innovation effect of Hakka sports culture. The development of Hakka sports culture is promoted by this study, as well as the value and influence of China’s excellent national traditional culture.
Optimization of Informatization Communication Pathway of Chinese Traditional Culture Based on Multi-objective Optimization Algorithm
Authors: Yang Shuai , Ju Jingyi 
Published: August 2024

Abstract
With the development of Internet technology, social networks have gradually become the main medium for interpersonal information exchange and a broad platform for information dissemination. The dissemination process of traditional Chinese cultural information in social networks is characterized by fast dissemination speed and low dissemination costs. Based on the perspective of multi-objective optimization, this paper constructs a multi-objective optimization model to maximize the influence of Chinese traditional culture information dissemination, taking into account factors such as structural influence, user interest, and dissemination cost. The classical influence maximization algorithm is used to obtain influential nodes as candidate seed sets, and the structural influence, interest of the affected users, and dissemination cost of the seed sets are calculated. And use the evolutionary multi-objective optimization algorithm to obtain the undominated solution set for multi-objective influence maximization. Finally, validation experiments of the proposed solution scheme are conducted on citation networks based on real social network data. The user participation of mass culture information in social network communication ranges from 0.721 to 0.785, while niche culture information ranges from 0.201 to 0.332, and there is a difference in the informational communication effect between the two, which suggests that the proposed method can provide more flexible decision-making suggestions for Chinese traditional culture communicators.
Methods and Practices of Dynamic Programming Algorithms to Promote the Fluency of Japanese Literary Metaphor Translation
Authors: Su Wei 
Published: August 2024

Abstract
This paper uses a dynamic programming algorithm to achieve automatic sentence alignment for Japanese-Chinese metaphor translation, based on a bilingual dictionary. The dynamic programming algorithm is utilized to find out the sentence pair path from the beginning to the end of the text paragraph with the largest total evaluation value, and the sentence pairs on the path are output in reverse, which are the aligned sentence pairs of the paragraph. Using the translation dictionary and dynamic programming algorithm to align the algorithm for obtaining Japanese-Chinese translations, the correctness rate of the final extracted translation units is 85.19%, and the recall rate is about 62.2% by sampling test, and compared with the traditional alignment algorithms, the fluency of the dynamic programming alignment algorithm is about 15%–23% higher. The algorithm not only inherits the advantages of the dictionary word-based alignment algorithm but also enhances its shortcomings, thereby improving both the correctness and fluency of the alignment. According to the statistics on sentence length relationships between Chinese and Japanese metaphorical translation, the more stable the relationship is, the longer the text length. A significant difference can be seen in the Sig values of fluency between manual translation and the dynamic planning alignment algorithm, which are less than 0.01.
Quantitative analysis of landscape changes in geoparks combined with GIS
Authors: Chen Meijun , Zheng Jie , Si Ruijie 
Published: August 2024

Abstract
Geoparks are both the concentration of valuable geological remains and an important carrier of tourism activities. Relying on a geographic information system (GIS), this project takes the landscape change of a geopark from 2005 to 2020 as an example, and after processing the remote sensing images, quantitative analysis is carried out by using the landscape pattern index method, which reveals the landscape change characteristics of the sample geopark. The data related to natural and human factors was collected, and the driving factors of landscape changes in geoparks were analyzed by combining probes. The main landscape types of the sample geoparks are cropland, woodland, and rocky desertification land, and the study period presents landscape changes of decreasing cropland area (22.96%), fluctuating woodland area, and increasing desertification area (37.40%), and the development of the park landscape changes presents irregularity and complexity. The main drivers of landscape change in geoparks are geological conditions, topography and geomorphology, vegetation, economic development capacity, and ecological environment quality (q value = 0.438~0.521), of which economic development capacity and ecological environment quality play a dominant role in the interaction of factors (0.86).
A study of preschool integration of deep learning to optimize the content of personalized education for young children
Authors: Ding Yanyun , Li Yongxia 
Published: August 2024

Abstract
With the reform and development of modern education curriculum, the focus of preschool education has changed from focusing on the “learning results” to the “learning process” of young children, and deep learning, as a hot trend of education reform, is an important way to implement education reform in pre-school education, which is based on problem-solving, emphasizing on the application of migration, and focusing on the reflective construction. Deep learning, a trend of educational reform that is based on problem-solving, emphasizes transfer and application, and focuses on reflection and construction, is an important way to implement educational reform in preschool education. This study first explores the connection between preschool education and deep learning, collects the problems of deep learning in preschool education through a questionnaire survey, and builds a personalized preschool education model based on deep learning in combination with DELC theory. The teaching effect of the deep learning preschool education model is explored through educational comparison experiments in this paper. The mean value of the preschool education model of this paper compared with the traditional preschool education in the four dimensions of learning motivation, learning input, learning strategy, and learning outcome were increased by 2.00~4.00 points, respectively, and the Sig values were all less than 0.05. Meanwhile, the average grade of this paper’s teaching model was 65.124 points, which was increased by 3.112 points compared with the average grade of the traditional cumulative preschool education model, proving that this paper’s effect of the application of deep learning personalized preschool education mode, which has a significant advantage in the degree of deep learning and learning achievement. In addition, this study provides suggestions for the development of deep learning in preschool education from the levels of teachers, teaching materials, teaching curricula, and external support so as to promote the process of deep learning in preschool education.
Application of Intelligent Remote Control Combined with Machine Vision in Coal Mine Electromechanical Equipment
Authors: Du Yujing 
Published: August 2024

Abstract
In this paper, the machine vision integration method is first investigated to design the coal mine working environment monitoring system for electromechanical equipment. Then, the PID control algorithm is used to remote control various electromechanical equipment in coal mines. Finally, we analyze the effect of the intelligent remote control function combined with machine vision on the coal mine electromechanical monitoring and environmental monitoring, analyze the effect of machine vision device with deviation detection and coal pile detection effect, as well as compare the optimization results and fault separation correct rate of different machine vision fault diagnosis methods for electric power equipment. According to the results, the fault diagnosis adaptability of the optimization results of power equipment fault diagnosis using this paper’s method is approximately 95, and the fault separation accuracy rate is between 92% and 96%.
GPT Modeling for English Learning Assistance Functions in Non-Native Language Environments
Authors: Lu Shuting 
Published: August 2024

Abstract
In this paper, we design an English multi-round dialogue model based on the pre-trained model GPT-2 and use Top-p and Top-k sampling instead of greedy search and cluster search sampling to optimize the decoding strategy. After that, a dialog history keyword replication mechanism is introduced to improve context consistency. Based on the GPT-2 English Multi-Round Dialogue Model, a conversational teaching model for teaching English in a non-native language environment has been constructed. The impact of this teaching model on students’ theoretical learning and teaching skills was examined. The results show that the BLEU1 index value of the GPT-2DH model after pre-training in the chatterbot corpus is 0.356, which is almost twice as much as that of seq2seq. As a result, the model in this paper is superior. Compared with traditional teaching methods, the GPT dialogic learning model significantly improved students’ theoretical learning performance, English listening and speaking skills, learning attitude (P=0.029<0.05), and extrinsic learning motivation (P=0.046<0.05) but had no significant effect on their instructional design skills and intrinsic learning motivation.
A Study on the Role of Textual Data Analysis of Ancient Poetry in Decision Making on Urban Cultural Construction
Authors: Wang Zhongjun 
Published: August 2024

Abstract
Cultural construction is an essential and increasingly important part of urban construction. Today’s urban document construction is heavily influenced by ancient poetry, which is one of the best parts of Chinese culture. Based on the realistic value of ancient poetry in urban culture construction, the study constructs an ancient poetry text mining model using the Word2Vec model, keyword word extraction algorithm, and text classification algorithm. Taking Hangzhou as an example, the study conducts text mining and data analysis on ancient poems related to Hangzhou, extracts the elements that are useful for urban culture construction to construct an evaluation index system for urban culture construction, and finally puts forward the corresponding development suggestions based on the results of urban culture construction evaluation. The majority of the landscape words in ancient poems related to Hangzhou are natural, with 7591 natural landscape words appearing and 4516 humanistic landscape words appearing. Excluding the indicator of ecological greening facilities, the indicator of Hangzhou’s urban culture construction with the highest score is natural landscape, with a score of 0.858184, and the lowest score is humanistic landscape, with a score of 0.643769. This shows that Hangzhou’s humanistic landscape construction in urban culture construction is still insufficient, and there is still room for improvement, it is necessary to focus on the enhancement of the humanistic landscape to improve the overall level of urban culture construction. There is still room for improvement.
An Empirical Study on the Reversal Effect of English Teaching in Colleges and Universities in the Internet Era
Authors: Ren Lei , Xia Ying , Lv Meiqin 
Published: August 2024

Abstract
This paper begins with the innovation of English teaching in colleges and universities during the Internet era. It then presents innovative application strategies, exemplified by the online learning platform and online teaching quality evaluation. Finally, it conducts empirical research on the reversal effect of English teaching in colleges and universities during the Internet era, using application analysis. Text information extraction is accomplished by mutual information technology; teaching resource transmission and scheduling are realized by the Markov chain; collaborative filtering of teaching resources is carried out; and an online learning platform is constructed. Create an online assessment ensemble for teaching quality, set assessment constraints for optimization, generate an affiliation function for English teaching quality assessment and construct an algorithm for English teaching quality online assessment. Conduct teaching practice at the University of Rochester to empirically demonstrate the effects of counterbalancing on English teaching in colleges and universities. After the practice, the speaking, reading, and writing test scores of the subject students increased by 2, 2.41, and 1.46, respectively, compared to their pre-practice scores, and their learning anxiety decreased. During the practice period, English class attendance was stable at more than 90% since the 5th week, and the dimensions of English learning ability were higher than 3.5. The subject students also had high satisfaction attitudes toward the overall quality of English teaching.
A study on the morphological evolution of college students’ employment concepts in response to the digitalization context
Authors: Zhang Hainan , Feng Pengyu 
Published: August 2024

Abstract
In recent years, the government has attempted to address the issue of college student employment in relation to national harmony and stability. Against the backdrop of the current era, the study investigates the employment concepts of students at a comprehensive university, analyzing the evolution of these concepts based on survey data on college students’ employment and entrepreneurship status in recent years. Afterward, the study identifies the variables associated with the employment concept and direction, employs the multinomial logit model for regression analysis and average marginal effect analysis to investigate the factors influencing the employment concept, and subsequently develops effective countermeasures to foster the correct employment concept among college students. The main employment destinations of college students are graduate school (27.9%~37.7%), enterprise employment (26.5%~31.2%), public examination (8.5%~10.4%), and flexible employment (9.6%~18.6%). It reveals that the most valued employment factors among college students have shifted from career prospects to welfare treatment, with pragmatism and diversification emerging as key development trends in their employment concepts. Colleges and universities should accelerate the pace of vocationalization reform, strengthen students’ quality education, guide college students to correct their employment attitudes, and promote the formation of correct employment concepts among college students.