bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on energy efficiency improvement strategy of photovoltaic-hybrid energy storage DC microgrid considering green energy saving concepts
Authors: Zhang Zhi , Han Yonglu , Zhu Huan , Wu Bo 
Published: February 2024

Abstract
In this paper, the development of microgrid technology is discussed in close connection with the growing energy demand and the real needs of energy structure adjustment in the context of the times. Guided by green energy saving, the research focuses on constructing a hybrid energy storage DC microgrid model, especially the integrated photovoltaic power generation model and the related control strategy and power characteristics. The article further adopts a fuzzy PID control strategy to optimize the energy efficiency configuration of hybrid energy storage devices in DC microgrids. By carefully analyzing and optimizing the energy storage system in the DC microgrid, remarkable results are obtained: the optimized capacitive charge states range from 0.1 to 0.9, indicating a significant fluctuation of capacitive charge states, but at the same time avoiding the phenomenon of light abandonment and ensuring the reliability of power supply. More notably, during the increase of SOC (state of the energy storage system) from 0.40 to 0.70, the system can perform mode transitions under continuous load changes. This point shows the effectiveness of the optimization method in improving the energy storage efficiency and enhancing the system performance of the DC microgrid. Overall, the optimization method proposed in this paper provides a practical energy storage optimization scheme for developing microgrids, which is of great practical significance in promoting the research and application of microgrid technology. This not only helps to improve the efficiency of energy use, but also is a crucial step to realize sustainable energy development.
Design and Planning of Tourism Path Based on Social Media Sharing Data Mining
Authors: Huang Meizhong , Pan Jiang , Yan Cheng 
Published: February 2024

Abstract
In recent years, along with the rapid development of artificial intelligence, big data and social media, informatization in the tourism industry also shows an explosive trend. This paper constructs a tourism path planning system based on data mining technology and the selection method of the optimal path. The GS algorithm is used to optimize the SVM algorithm to form the GS-SVM fusion algorithm, which makes the tourism path planning and predicts the optimal path according to the specific conditions of the journey, the characteristics of the scenic spot itself, and the tourists’ needs. After testing, this system has a good prediction performance on the traffic accessibility, attraction congestion and crowd change of scenic tour path. It is found that the transportation accessibility of scenic tour paths is positively correlated with tourists’ experience. In addition, in the experiment on the advantages and disadvantages of tourism paths, the passage time of paths 14, 15 and 16 is more than 3 minutes. Still, the actual length of these three paths is not more than 350m, which indicates that there are things for tourists to visit and experience on the passage paths, thus lengthening the passage time. This shows that the system provides real-time and reference paths for tourists by mining social media sharing data.
Research on the evaluation method of rock brittleness characteristics based on stress-strain curve
Authors: Tang Xuan , He Yi 
Published: February 2024

Abstract
In this study, not only the variability of the internal texture of rocks is considered in the in-depth investigation of the brittle fracture properties of rocks, but also the effects of different stress states and temperature factors on the fragility of rocks are focused on. Through experimental studies and data analysis of various types of rocks under different stress conditions and temperature environments, this study found that the plasticity of marble is positively related to stress. Under other stress states of 5, 15, 25, and 35 MPa, the stress-strain curves become flatter with increasing stress. Under uniaxial stress condition, the fragile strengths of different rocks are sandstone, red sandstone, granite, marble, chert, and cement mortar in that order. Whereas, under triaxial stress condition, the fragility of the rock samples was in the order of fine-grained granite, coarse-grained granite, sandstone, tuff, and marble. It was further found that the rock specimens after different high-temperature water-cooling treatments exhibited four different stages of brittle fracture, and the peak of the first stage of the rock was higher as the temperature decreased. The inclination of the peak was inversely proportional to the temperature. This study provides an essential scientific basis for the in-depth understanding of the brittle fracture characteristics of rocks and their engineering applications.
Classification and Value Assessment of Sports Intangible Cultural Heritage Resources Combined with Digital Technology
Authors: Zhang Yongjiang , Ala Tengcang 
Published: February 2024

Abstract
This paper is dedicated to designing and constructing a knowledge ontology framework for sports intangible cultural heritage (ICH) resources, aiming to support their preservation and inheritance by integrating and mining sports ICH resources. The study includes the collection of multiple data of sports ICH from various data sources, and constructing ICH knowledge ontology using CIDOC CRM metadata reference model and seven-step method. To enrich the content of the ontology, the TextRank algorithm is used to extract textual critical information and design a domain-specific NER model for sports NRL. In addition, the study adopts the VSM vector space model for text representation and uses an improved hierarchical classification model for text categorization to improve classification accuracy. The study also explores the similarity calculation of concepts in the sports NRM ontology and proposes a semantic similarity calculation formula based on the ontology concepts. Respondents’ willingness to pay was investigated through the conditional value method (CVM) to assess the value of sports NRM tourism resources. Finally, the influencing factors of respondents’ willingness to pay were analyzed using statistical analysis and Logistic regression model, and it was found that they were mainly influenced by the degree of understanding of sports non-heritage resources and the level of education. The results of this study not only provide theoretical and methodological support for the effective integration and excavation of sports non-heritage resources and a new perspective for their protection, inheritance and sustainable development.
A Comparative Analysis of Japanese Learners’ Translation Bias Using Neurosemantic Analysis
Authors: Cao Zheng 
Published: February 2024

Abstract
In today’s increasingly frequent cultural exchanges between China and Japan, accurate and error-free Japanese translation has become an inevitable choice for cross-cultural communication. In this paper, based on twin neural network and attention mechanism, BiLSTM model is combined with sentence semantic similarity matching algorithm to construct a Japanese translation bias sentence semantic similarity model. The Japanese corpus data were collected and preprocessed by Python technology, and the Japanese translation corpus database was searched and counted using Wordsmith and AntConc tools. For the Japanese learners’ translation bias in the Japanese translation process, a comparative analysis was carried out in several aspects, such as end-of-sentence modal expressions, consecutive translations, and word frequency effects. The study results show that the difference in the frequency distribution of Japanese learners’ modal expressions is only 4.66% compared with that of native speakers of Japanese. Still, the difference between the two is significant at the 1% level, and the difference in the frequency of Japanese learners’ use of the modal expression “yes” is 56 sentences per 10,000 sentences. The frequency of Japanese learners’ use of successive expressions was 30.1 percentage points higher than that of native speakers. The neural semantic analysis method combined with the Japanese translation corpus can clarify the translation bias of Japanese learners in the process of Japanese translation, which can provide a reference for enhancing the translation quality of Japanese learning.
The Path of Cultivating Music Appreciation Ability in Piano Education in Colleges and Universities in the Internet Era
Authors: Dai Xiaoqin 
Published: February 2024

Abstract
With the Internet and AI technology development, piano education in colleges and universities faces innovative challenges. This study explores the effectiveness of the Internet-based teaching mode in enhancing students’ music appreciation ability. The study adopts a teaching model based on the Internet and AI technology, combining automatic composition, arranging and piano concerto repertoire sessions, and AI+professional teachers’ collaborative evaluation. By implementing a creative thinking teaching module, including pre-course preparation, classroom training and presentation, and post-course communication, the study aimed to improve students’ music appreciation and creative thinking skills. The study results showed that students demonstrated significant improvement in music appreciation skills. The data showed that students who participated in the new teaching model showed an average of 25% improvement in music appreciation skills assessment. In addition, students’ creative thinking skills were also enhanced, with 85% of them demonstrating a high level of innovative music composition. The college piano education model integrating Internet and AI technologies significantly improves students’ music appreciation ability and creative thinking. This model enhances the interactivity and fun of teaching, provides students with a broader platform for musical understanding and practice, and offers new perspectives and methods for music education in colleges and universities.
Analyzing the Development History of Chinese Ceramic Packaging Containers and Their Modern Design Innovation Based on Multivariate Statistics
Authors: Wu Yuzhou , Tao Tao 
Published: February 2024

Abstract
This paper explores the development history and modern design innovation of Chinese ceramic packaging containers through multivariate statistical analysis, revealing their essential role in the market and cultural heritage. The development history and contemporary design innovation of Chinese ceramic packaging containers are studied in depth. The study finds that ceramic packaging containers have evolved from prehistoric hand-kneaded small pieces to the present, constantly incorporating new crafts and cultural elements. Regarding formal aesthetics, the use of rhythm and rhyme in ceramic packaging containers grew at 81.13% between 2015 and 2020, suggesting that designs tend to be more dynamic and expressive. Data analysis shows that the key factors influencing the design of ceramic packaging containers include process technology, trade development, cultural concepts and religious beliefs. Regression analysis indicates that these factors significantly positively impact the design quality of ceramic packaging containers, with a model fit of 63.52%, revealing that these factors jointly promote the improvement of design quality. Innovative combination of traditional elements and modern technology is the key to fostering innovation of ceramic packaging container design and cultural heritage. The market competitiveness and cultural value of ceramic packaging containers can be effectively promoted by emphasizing the development of craft technology and the integration of cultural elements.
Supervision and guarantee of constitutional normativity in a legal system aimed at legal regulation
Authors: Xu Juan 
Published: February 2024

Abstract
This study focuses on the monitoring and safeguarding constitutional normativity in the legal system, explores its empirical Analysis in environmental protection law and patent law, and emphasizes the importance of the legal named entity identification model and legal instrument element extraction. The study adopts the implicit Markov-based legal named entity identification model and the Bleem model oriented to extracting legal instrument elements. In environmental protection law, we explored the correlation between the content and manner of law enforcement through a quantitative analysis model. We found that the correlation between pollution prevention and source prevention was 0.575, showing a strong correlation. We analyzed the R&D investment data of 23 provincial-level administrative division units in patent law from 2009 to 2023. We found that in-house R&D expenditures increased from 65% to 78.5%, proving the significant incentive effect of the patent law reforms on enterprise R&D investment. Adequate supervision and guarantee of constitutional normativity play an essential role in the improvement and practical implementation of the legal system, especially in the fields of environmental protection and intellectual property rights.
Study on the Innovative Application of Civil and Commercial Law in the Context of E-Commerce in the Internet Era
Authors: Wang Xuefang 
Published: February 2024

Abstract
This paper focuses on the innovative application of civil and commercial law in the context of e-commerce in the Internet era, and explores how e-commerce affects the application and innovation of civil and commercial law, aiming to provide theoretical support and practical guidance for the legal environment in the era of e-commerce. A combination of theoretical Analysis and Poisson regression model is used to analyse the impact of e-commerce on civil and commercial law, and a robust regression model based on mean drift penalty is constructed for quantitative Analysis. It is found that the development of e-commerce positively impacts the effectiveness of civil and commercial law. The data show that for every unit increase in the level of e-commerce development, the efficacy of civil and commercial law increases by 0.318 points (p<0.01). In addition, regional analyses show that e-commerce has the most significant impact on civil and commercial law in the central region, followed by the west and the east, and the impact is not substantial in the northeast. The time-lag effect analysis shows a weak lag effect on the impact of e-commerce development on the effectiveness of civil and commercial law. The conclusion indicates that in the context of the rapid growth of e-commerce, it is necessary to innovate the application of civil and commercial law to adapt to the new business environment, protect the legitimate rights and interests of both parties to the transaction, and promote the healthy development of e-commerce.
The Inheritance and Development of Ethnic Folk Dance in Dance Teaching under the Background of Informatization
Authors: Xiong Yan 
Published: February 2024

Abstract
With the arrival of the informationization era, the inheritance and development of ethnic folk dance in dance teaching faces new challenges and opportunities. This paper discusses effectively inheriting and developing ethnic folk dance under informationization. The research methodology includes the Analysis of folk dance movement characteristics, movement capture and feature extraction based on Kinect acquisition technology. The results show that the dancer’s movement data can be accurately recorded by Kinect capture technology, and the error of capture coordinates can be minimized up to 1.115. The study also finds that the dance movement features can be effectively extracted using Gaussian Mixture Model Background Subtraction and Median Filtering preprocessing techniques. In addition, the “Trinity Teaching Assistive Technology” proposed in this study can improve teaching quality. The application of information technology not only promotes the scientific and standardized teaching of folk dance, but also helps improve students’ skills and creativity.
Research on the digital construction mode of college music teaching curriculum based on knowledge mapping
Authors: Yang Yaokun 
Published: February 2024

Abstract
The study uses the MKR (Multi-task Knowledge-aware Recommendation) model, which integrates knowledge graphs and multilayer perceptron networks, and focuses on mining users’ high-level music preferences from music information and user behaviors. The study first introduces the three core parts of the MKR model: the recommendation task module, the knowledge learning module, and the cross-compression unit. Then, by optimizing the MKR model, the A-MKR (Attention-based MKR) model is proposed, which introduces the attention mechanism to further improve the model performance. In the application of music teaching, the study explores the keyword analysis of music education, digital teaching methods and their effect evaluation. The experimental results show that compared with traditional teaching, the digital teaching model performs better in both field assessment and ability growth, and the error rate is significantly reduced. For example, the digital group scored 1.3 and 9 points higher than the traditional group in field assessment and ability growth, respectively, and the error rate was reduced by 5.8%. This study proves the effectiveness and practical value of knowledge mapping based on the MKR model in the digital transformation of music teaching in colleges and universities. It provides new perspectives and methods for future music teaching.
Research on the reform of the modularized curriculum of “Cultivation Technology of Northern Taoist Medicinal Herbs” in the context of the new version of GAP
Authors: Sun Liang 
Published: February 2024

Abstract
This study explores the reform of the modularized course “Cultivation Technology of Northern Daoji Medicinal Herbs” in the context of the new version of the “Good Agricultural Practice for the Production of Chinese Medicinal Herbs” (GAP). The research methods include skill mapping and knowledge structure analysis, formal context theory, ensemble and analytic models, and learning path planning algorithms based on KL dispersion and matrix eigenvector similarity. These methods aim to construct course knowledge structures, clarify teaching and learning priorities, and generate personalized learning paths. RESULTS SURFACE: The established course knowledge network reveals the relationship between knowledge points through skill mapping and knowledge structure analysis. The network density is 0.0624, indicating fewer connections between knowledge points. The course contains 68 knowledge and skill points, among which the Degree of centrality of the skill node “Dewhead Cultivation” is the largest. Based on the analyzed knowledge networks and learning paths, the course was divided into several modules, each tailored to specific teaching objectives and students’ learning needs. Through the effective integration of skill mapping and knowledge structure, the modularized curriculum reform of “Cultivation Technology of Northern Medicinal Herbs” in the context of the new GAP not only improves the quality of teaching, but also meets the personalized learning needs of the students, and provides a new direction for future education.
Characterization of Business English Translation Styles Based on Semantic Contrastive Analysis
Authors: Ji Xiangyan 
Published: February 2024

Abstract
Language genre is a form of language expression formed by certain people from specific purposes in a particular context, and no form of language expression can exist independently of genre characteristics. The study adopts the space vector model to digitally represent the potential semantics of business English translation. By constructing a translation-word matrix and applying the TF-IDF method to calculate the weights of the elements in the matrix, the study proceeded to perform a singular value decomposition of the matrix. This process helps to extract the features of corpora similarity in business English translation, which in turn completes the construction of a language model for business English translation. The study selected a business English translation corpus for instance analysis. The data results show that in the interaction and information feature analysis, the mean values of ECQ (interaction feature quantitative value) features are higher than TCQ (information feature quantitative value) in three different periods, with the differences of 0.0992, 0.0534 and 0.043 respectively. Regarding the standardized scores of the stylistic features, 24 stylistic feature indexes meet the standardization requirements, accounting for 75% of the total indexes. This finding provides an essential basis for understanding the differences between Business English and other stylistic features. The research in this paper has significant application value for professionals in business English translation.
Synergistic Coupling Mechanism of Digital Media Art and Vocal Talent Cultivation
Authors: Wang Henghua , Li Xue 
Published: February 2024

Abstract
In the field of higher education in today’s era, cultivating vocal talents is crucial. This paper focuses on an innovative mechanism in vocal talent cultivation, i.e., enhancing vocal education by constructing a music recognition model based on Fourier algorithm. The Model is further applied to design a teaching aid system incorporating reinforcement learning to realize the synergistic development of digital media art and vocal talent cultivation. After rigorous testing, we found that the music recognition model has an accuracy rate of over 90% and is highly resistant to noise. In addition, by analyzing the practices of several colleges and universities’ music schools, it is observed that there are significant differences among different institutions in the four comparative items, with standard deviations exceeding 0.6. In particular, the average scores using this study’s teaching system for vocal talent cultivation are 4.312, 4.335, 4.267, and 4.354, respectively, generally higher than those of the other colleges. The mean values of these four different vocal music majors were all above 4 points. Therefore, the teaching system for vocal talent training proposed in this paper effectively improves the quality of vocal talent training and provides a new path for the practical reform and optimization of said education.
Correlation Analysis and Teaching Optimization of University English Lecture Mode Preferences
Authors: Wang Zhenzhen 
Published: February 2024

Abstract
The article first discusses the categorization and difficulty of learning resources and proposes a method to quantify the difficulty of teaching resources. Then, the article recommends appropriate learning resources through similarity matching and student knowledge level diagnosis. This includes analyzing students’ test answers and modeling students’ knowledge level based on this. Data analysis and model building were employed to propose four key indicators: knowledge point density, knowledge point depth, evaluation index and correctness rate. In addition, cosine distance was employed to measure the similarity between resources and Hidden Markov Models were used to predict students’ knowledge point mastery. Four key indicators were effectively applied to construct a vector of resource difficulty indicators in quantifying learning resource difficulty. A vector representation of students’ knowledge mastery was successfully built in diagnosing students’ knowledge level. In addition, the article discusses the construction of a personalized learner preference model and a personalized English teaching model based on collaborative filtering algorithms. The effect of college English teaching can be effectively improved through the detailed Analysis of learning resources and the application of personalized recommendation model.