bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Textual Logical Analysis of the Evolution of Marx’s Urban Critical Thought
Authors: Li Conglai 
Published: May 2024

Abstract
Focusing on elucidating Marx’s urban critical thought is of positive significance for understanding China’s urbanization path and shaping the socialist urban development model with Chinese characteristics in the new era. The main point of Marx’s urban critical thought is the starting point of this paper, and it examines the manifestation and evolution logic of Marx’s urban critical thought. For the textual logic of Marx’s urban critical thought, the Word2vec model is utilized to extract textual features. Then, the BERT model is introduced for text word vector construction, and a multiclassification model of Marx’s urban critical thought text is established based on the fusion of multiple semantic information features. After completing the construction of the method, relevant texts about Marx’s urban critical thought were collected to construct a dataset, and the classification effect was analyzed to explore the evolutionary development trend of Marx’s urban critical thought. The results show that the text classification model can achieve the optimal classification accuracy of 93.15% by applying the 15th layer. The optimal performance is obtained when the local text word length is 100, and the sustainability growth of Marx’s urban critical thought between 1950 and 2020 reaches 102.34%. An in-depth analysis of Marx’s urban critical thought evolutionary logic can provide theoretical guidance for the modernization of Chinese cities.
Deep Learning Based Algorithm for Detecting Errors in Mandarin Read-Aloud Backreading Omission Incremental Reading
Authors: Li Huixu , Yang Zhaozhao 
Published: May 2024

Abstract
With the continuous development of computer technology and the deepening of the popularization of Mandarin, the role of computer technology in language-assisted language learning and recognition has become more and more significant. In this study, the acoustic model and speech model based on the Hidden Markov Model are constructed for the error detection of reading aloud in Mandarin. Then the feature extraction of the acoustics of speech signals is carried out to build the error detection model of reading aloud in Mandarin based on pronunciation features. On this basis, a DNNHMM hybrid model is built by combining deep neural networks and Hidden Markov Models for detecting Mandarin read aloud keyword errors. Through the empirical analysis of Mandarin reading error detection, it can be seen that the average accuracy of the Mandarin reading error detection model constructed in this paper is 92.37%. Compared with the other models, the average accuracy improvement ranges from 4.69% to 8.19%, and the average accuracy of the vowel and consonant pronunciation features is 85.04% and 81.69%, respectively. In the detection of errors in Mandarin reading aloud, the F-score of misreading, back-reading, adding, changing, omitting, and other six error types is above 80%, and the accuracy rate is above 83%. It shows that the deep learning-based model for reading aloud in Mandarin performs well and provides an effective method for error detection in reading aloud in Mandarin.
Feature Extraction and Musical Personality Analysis of Piano Artistic Performances
Authors: Liu Shuai 
Published: May 2024

Abstract
Starting from the basic process of piano music recognition, this paper focuses on the feature extraction process of piano art performance. In the feature extraction of piano art performance, the fundamental frequency characteristics of piano music signals were analyzed by using short-time Fourier transform theory, focusing on the feature extraction of musical pitch, time value, and tonality, and the spectrum analysis of piano music signals and the reconstruction of piano timbre were completed. The piano performance work, “Autumn Moon on the Peaceful Lake,” is used as an example to analyze the musical characteristics and personality. The overall structure of “Autumn Moon on the Peaceful Lake” is a typical three-part structure: the key is the bD palace seven-tone mode, the key is single, and the marking range of performance strength is ppp-pp-p-mf-mf-f-ff. In the three versions played by Yin Chengzong, Lang Lang, and Chen Jie, the average tempo of the performance was 31.5 beats, 26.5 beats, and 26.8 beats, respectively. The performance process of different pianists is a “slow-fast-slow” layout, and other passages are added to the individual free processing to further enhance the charm of the work.
Cycle life and influencing factors of cathode materials for lithium-ion batteries--a case study of lithium-cobalt oxides
Authors: Shou Haofang , Cui Xiajing 
Published: May 2024

Abstract
Lithium-cobalt oxide has become a new generation of highly promising anode materials for lithium-ion batteries due to its low price, environmental friendliness, high platform voltage, and high theoretical capacity. In this paper, the working characteristics and related parameters of lithium-ion batteries are sorted out, and the influence factors of the decline mechanism of lithium-ion batteries are investigated from the perspective of chemical composition. Regarding the cycle life of lithium-ion battery cathode materials, this paper establishes a cycle life prediction model for lithium-ion batteries based on the LSTM model. It optimizes the hyperparameters of the model using the PSO algorithm. In addition, this paper also prepared lithium cobalt oxide cathode materials and carried out a validation analysis of the factors affecting their electrochemical performance. It is found that the cycle life prediction of lithium-ion battery based on LSTM has an RMSE of 3.27%, and the capacity of lithium cobalt oxide soft pack full battery decays from 249.81mAh to 137.04mAh at 26°C. The cycle life of its lithium cobalt oxide lithium-ion battery is around 250 cycles, and the average decay is 0.445mAh during one charge/discharge. Different charge/discharge cycles and diversity will have a significant effect on the cycle life of lithium-ion battery cathode materials, and it is necessary to pay attention to the parameter changes in the preparation of lithium cobalt oxide cathode materials in order to increase the cycle life of lithium-ion batteries.
Construction and Application of English teaching in vocational colleges Model under Output Orientation
Authors: Huang Yanhong 
Published: May 2024

Abstract
The basic idea of teaching reform and practice is the teaching mode. This research, which is based on POA, examines how higher vocational English is taught under the direction of a new teaching model and assesses the viability and application of using POA to teach English in vocational institutions. This paper establishes an English teaching in vocational colleges model under POA, which consists of three parts: “driving,” “facilitating,” and “evaluating.”Through the improvement of the BP neural network, this research develops the English teaching in vocational colleges quality assessment model under POA, thereby verifying the efficacy of the model. The changes in students’ English achievement are explored through teaching experiments and the two-sided sigmoid curve. A value of 0.007<0.05 in the paired-sample t-test of the experimental class proves that compared with the traditional English teaching in vocational colleges model, the English teaching in vocational colleges model under POA has a more obvious promotion effect on English achievement. The improved BP neural network model produced quantitative assessments of teaching quality that are mostly in line with actual findings. The model is used to evaluate the quality of English instruction in vocational colleges under POA.
Exploration and Reflection on the Development of Internationalized Industry-Education Integration of Vocational Education in the Context of Big Data
Authors: Kong Ming , Kuang Yan , Zhang Zhichao 
Published: May 2024

Abstract
The integration of industry and education serves as a potent mechanism to enhance the educational quality of higher vocational colleges and universities while simultaneously fostering the innovative vitality of enterprises. This study delineates a framework for internationalized industry-education integration in vocational education, grounded in the tripartite relationship among government, enterprises, and educational institutions. Building on this framework, the research initially constructs a performance evaluation index system for internationalized industry-education integration, which encompasses three dimensions: the input, process, and outcomes of industry-education integration. Subsequently, the weights of these indices are determined through hierarchical analysis, and the integration performance of four sample institutions is assessed using fuzzy analysis. The findings reveal that all sampled institutions surpass a ‘good’ performance level, with Institution X1 achieving the highest comprehensive evaluation score of 86.3593. Further, the study conducts an empirical analysis comparing the implementation effects of two models of industry-education integration: the ‘group-run school’ model and the ‘industrial park’ model. The study indicates that the ‘industrial park’ model is marginally superior by 0.13 points in its evaluation compared to the ‘group-run school’ model; however, this difference is statistically insignificant (P>0.05), suggesting that both models exhibit distinct characteristics yet achieve comparable outcomes in integrating industry and education. The research offers actionable insights and practical guidance to advance the development of internationalized industry-education integration within vocational education contexts.
Research on the application of multi-feature fusion in ceramic art design
Authors: Li Hua , Fang Xiao 
Published: May 2024

Abstract
In this paper, median filtering and linear stretching are used to preprocess the classified ceramic images, respectively, and the LoG operator is utilized to detect the edges of ceramic photos. Combining the Hough transform and TMOAA algorithm to measure the edge length, thickness, and diagonal dimension of ceramics to obtain the basic elements of ceramic art design. The FAST algorithm is used to make up for the shortcomings of the SIFT algorithm in real-time, to extract the features of the overall image of ceramics and the vessel image, and then combined with the thinking framework of ceramic art design to generate the best conceptual model of ceramic art design. Extract and detect the ceramic vessel image and carry out similarity rate calculation, quantify the enamel color characteristics to generate a color design scheme, calculate the color difference value, and evaluate the aesthetic value of ceramic art design works from the perspective of ceramic art design aesthetics. Porcelain enamel color difference ΔE = 2.0369, ΔE ≤ 5.00~6.00, in line with the color quality standards, indicating that the color design scheme generated based on the color semantic elements has a certain applicability. Evaluating the best conceptual model of ceramic art design by aesthetic standards, the works generated based on the seven ceramic patterns have different aesthetic values and different forms, which meet the various demands for ceramic artworks nowadays.
Research on the Application of Gray Prediction and BP Neural Network in English-Chinese Translation Quality Assessment
Authors: Wu Yitao 
Published: May 2024

Abstract
Gray prediction model and BP neural network are increasingly used in many fields as important prediction and analysis tools. The article first elaborates on the related algorithm of the gray prediction method. It constructs the gray prediction model, then constructs the BP neural network, and builds the gray BP neural network translation quality assessment model through the modeling of the simulation of the artificial neural network, and finally takes eight postgraduate students of translation majors of Beijing Foreign Studies University as the subjects, and the eight students translate two articles with similar word counts and difficulties, and score the translation quality of the subjects, and reasonably evaluate and scientifically predict these translations in order to validate the grey translation quality of subjects. The quality of translation is scored, and these translations are reasonably evaluated and scientifically predicted to verify the role and effect of the gray BP neural network in the quality of English-Chinese translation. The study concludes that the results based on the gray prediction model are that the prediction results are in the error range of 0%–7% compared with the original data, and the overall error is small. The prediction results of the compensatory fuzzy neural network prediction model for all 8 subjects before and after translation were more accurate than those predicted by the traditional fuzzy neural network method, with a good fit to the actual monitoring data and a small relative error. Only one subject out of the 8 spent more time on Chapter B than on Chapter A. Chapter B was more time-consuming than Chapter A. The time spent on Chapter A was more than the time spent on Chapter A. Chapter B was more time-consuming than Chapter A. Chapter B was more time-consuming than Chapter A. One subject spent equal time on both articles. The remaining 6 subjects did not spend as much time on chapter B as they did on chapter A.
Research on the Application of Data Mining Techniques in Early Warning Models for Financial Management
Authors: Su Wei 
Published: May 2024

Abstract
In the process of accelerating enterprise development in China, enterprises are prone to financial management crises while grasping development opportunities. This paper is oriented towards enterprise financial management data and proposes an adaptive neuro-fuzzy inference system to reason about risky data. The ANFIS model is integrated into K-mean clustering to provide early warning of enterprise risk by dividing different financial management risk indicators. The validation method uses both the comparison of similar algorithms and the practical test of A enterprise. Compared to other analysis models, the accuracy of the early warning model constructed by the K-Means algorithm is as high as 99.64%, which is suitable for enterprise financial management early warning. Using the model built in this paper to cluster the types of enterprise financial risk, the second cluster centers clusters of enterprises in financial difficulties, a number of indicators show negative results, and the net sales interest rate is as low as −94.23. This indicator is applied to the financial crisis of Company A’s financial situation analysis and found to be consistent with the characteristics of the second cluster center. This verifies the accuracy of the financial early warning model constructed in this paper.
Exploring the Path of Innovative College Dance Teaching Models with Motion Capture Technology
Authors: Sun Zhenyi , Cui Yunlong 
Published: May 2024

Abstract
The continuous development of artificial intelligence has brought new exploration paths and ideas for the teaching field, however, the current application and research of motion capture technology in college dance teaching mode is less. In this study, the human body and the appearance model are modeled in three dimensions: the simulated annealing particle swarm algorithm is used to optimize the human body modeling posture. Then, the feature vector matching algorithm is used to capture the human body’s movement posture, construct the college dance teaching mode, and carry out practical application. According to the study, the capture effect of the five movements in the dance teaching classroom video clip is between 0.865 and 0.945, and each movement is recognized with an accuracy of above 95%. After using this model, it was concluded by analyzing the effect of dance teaching that the number of excellent grades in the experimental group was 2 more than that in the control group, and the number of good grades was 2 more than that in the control group. This study provides a new development path for dance teaching in colleges and universities.
Optimization of Urban Science and Technology Innovation Performance Assessment Model - Based on VAR Methodology Perspective
Authors: Zhang Huimin 
Published: May 2024

Abstract
Conventional science and technology performance assessment methods and indicators can no longer meet the current needs of urban science and technology innovation performance assessment, and innovative research is urgently needed. In this study, the four elements of innovation input, innovation process, innovation output, and innovation guarantee are taken as the first-level indicators of the urban science and technology innovation performance assessment index system. The G1 entropy value correction method is used to assign weights to the urban science and technology innovation performance assessment index system to reduce subjective arbitrariness. Finally, the specific situation of innovation elements and innovation performance in S city was selected, and the influence relationship between innovation elements and innovation performance assessment was analyzed using a vector autoregressive model. The results show that the method of assessing the city’s science and technology innovation performance based on the VAR model is simple and easy to operate, the confidence coefficient of the assessment model is more than 0.7, and the mean value of the validity CVR is 0.703. The assessment results have a high degree of credibility and validity and effectively promote the region’s scientific and technological self-reliance and self-improvement.
Construction of Comprehensive Evaluation Model for Financial Risk Management in Colleges and Universities Based on Fuzzy Logic
Authors: Zhao Linglin 
Published: May 2024

Abstract
Among the many risks faced by colleges and universities, financial risk is one of the most important risks and has a large complexity. This paper evaluates the financial risk management level of colleges and universities using the fuzzy logic method based on the four dimensions of financial risk. The affiliation function is used to quantitatively describe fuzzy logic, and weighted summation is used to ensure the accuracy of fuzzy propositions. After selecting the evaluation indexes, the weights of the evaluation index system are determined, and a comprehensive evaluation system for financial risk management of colleges and universities is constructed. Taking Q colleges and universities in G city as the research object, the comprehensive evaluation coefficient of financial risk management of the subject colleges and universities is calculated, and the average value of the extensive risk coefficient of the subject colleges and universities in 2015–2017 is between 0 and 0.4, which belongs to the level of significant risk. The test university ranked second among 7 universities, but the comprehensive score index coefficient is 0.4898. However, there is still a large financial risk possibility. We need to formulate a corresponding risk management policy slightly.
A Study on the Integration and Practice of Integrated Transfer Learning Strategies in Japanese Language Teaching and Learning
Authors: Su Xiaoming 
Published: May 2024

Abstract
Addressing the prevalent issue of inefficiency in Japanese language learning, this study focuses on innovating classroom teaching methodologies for the Japanese language. Initially, the research employs a stochastic gradient descent algorithm to enhance the performance of a transfer learning algorithm, aiming to accurately identify student behaviors within the Japanese language classroom. Subsequently, these behaviors are quantified into integration weights using a predefined integration strategy. Behaviors demonstrating significant similarities are consolidated and analyzed to yield the results of the student behavior identification process. Furthermore, this behavior recognition approach is seamlessly incorporated into Japanese language pedagogy to develop a refined model for teaching, thereby potentially increasing the efficacy of language acquisition. Using this paper’s algorithm to identify students’ classroom behaviors and correlate them with their grades, it is found that when the number of positive behaviors in the classroom is higher, the student’s academic performance is also higher (r=0.9986, p=0.001<0.05). The average percentage of students’ attentive listening behaviors could reach 52.24% after the intervention, as determined by behavioral recognition results in the Japanese language teaching classroom. The behavior recognition algorithm in this paper provides an effective method for analyzing and intervening in students’ behavior in the classroom, and the teaching model constructed based on the algorithm offers a reference way to improve the effectiveness of Japanese language teaching.
Expansion of Innovative Diffusion and Communication Strategies of Chinese Opera Culture Based on ADDIE Modeling
Authors: Wang Youjing , Hou Yongguang 
Published: May 2024

Abstract
Based on the ADDIE model, this paper designs an innovative dissemination and communication strategy for Chinese opera culture and utilizes a questionnaire to explore the effects of opera culture dissemination and communication after the application of this strategy. The questionnaire is designed from the basic information of the audience, the cognition, attitude, and behavioral level of the opera culture communication, and the reliability and validity of the questionnaire are examined by using Cronbach’s Alpha reliability coefficient method and KMO test and Bartlett’s sphericity test, respectively. The survey results showed that only 16 people were exposed to opera culture for pure entertainment. The mean score of “I learned a lot of knowledge about opera” at the cognitive level is 3.48. In contrast, the mean scores of the audience’s attitude and behavior towards the dissemination of opera culture reach 3.79 and 4.03, respectively, which fully proves the positive application of this paper’s strategy. The innovative dissemination and communication strategy of opera culture constructed in this paper provides an effective path to improve the dissemination effect of opera culture. Also, it provides a reference basis for the inheritance and dissemination of other traditional Chinese cultures.
Virtual Reality-based Meta-Cosmic Perspective on Curriculum Integration Innovations in Art and Technology Programs
Authors: Wen Ling 
Published: May 2024

Abstract
At the end of the 20th century, the development of science and technology has made remarkable achievements, and some artists have begun to try to integrate science and technology into art creation. In this paper, based on DEM art space analysis, Unity technology is added to build a three-dimensional scene for teaching art and technology professional courses. At the same time, HoloLens2-based sensory interaction technology is introduced to enhance the integration of art and technology in the virtual classroom. Based on this basis, a teaching framework for VR art and technology fusion courses centered on students’ learning and interaction experience is designed and applied to actual teaching. In the sample correlation analysis, the experience of the relevant courses in the early stage had a significant impact on both the shadow students’ artistic self-perception (t=0.7854, p<0.01) and their learning behaviors in the later stage (t=0.6452, p<0.01). After the integration of art and technology teaching, the student’s interest in art learning and technology learning were both enhanced, with the mean values of 0.07398 and 0.0.20255, respectively, and the integration of art and technology professional course curriculum based on virtual reality technology effectively improved the students’ learning interest.