bluuebunny/crossref_metadata_2025_split huggingface dataset:
AUDIOVISUAL METHOD IN LEARNING FOREIGN LANGUAGES
Authors: Leshchuk Halyna , Stefanchuk Bohdana 
Published: November 2024

The article reveals the essence of the audiovisual method of teaching foreign languages. The main methods of learning foreign languages are characterized (grammatical translation, audio-lingual, communicative, immersive, direct, suggestive, neurolinguistic methods). The history of the emergence of the audiovisual method is traced and the contribution of various scientists to its development is analyzed (P. Rivan, R. Lado, R. Riсher). It is noted that the audiovisual method of learning foreign languages is a teaching method based on a combination of auditory (audio) and visual (video) stimuli, i.e. the defining feature of the method is the simultaneous use of sound and image. The importance of the method in the context of further development of multimedia resources is emphasized. The main characteristics of the method are presented: combination of images and sounds, contextual learning, emphasis on listening comprehension and pronunciation, lack of translation, repeated practice. Determined components of the method: listening, watching videos, repetition, perception of context. Advantages and disadvantages of the method are outlined. The advantages of the audiovisual method include: improving perception and memorization, immersive learning, getting closer to the natural language environment, active use of the context, and gradual mastery of the language. The limitations of the audiovisual method are: less emphasis on writing, the need for technical resources, which can make it difficult to use the method in schools or at home. Prospects for further research of the audiovisual method and its potential are indicated, especially in the context of technology development and individualization of education. It was concluded that the audiovisual method is a powerful tool for the initial stage of language learning, but it needs to be supplemented with other methods for comprehensive language acquisition.
THE STRUCTURE AND CONTENT OF THE COURSE "INNOVATIONS IN SOCIAL WORK" (FROM THE TEACHING EXPERIENCE)
Authors: Popovych Anna 
Published: November 2024

The topic relevance is determined by the requirements for the training of social work specialists for innovative activities in conditions of modern challenges. The article aims to characterize the structure and content of the course "Innovations in Social Work" for the 2nd (master's) level of higher education, specialty 231 "Social Work" (from teaching experience). Scientific methods applied: generalization, abstraction, explanation, systematization, system-structural, and descriptive analysis. The author notes the importance of a systematic approach to the development of the general concept of the training course. It is justified by taking into account not only theoretical and practical aspects of innovative activity, but also regulatory and legal ones. The structure of content modules tested in the teaching process is proposed: 1) theory of innovative activity; 2) regulatory and legal support of innovations; 3) innovation as a factor in overcoming social problems of our time. A brief overview of the lectures and recommendations for seminars are provided. Considering the absence of thematic sections on innovations in the field of social protection of the population in cross-sectoral normative documents, special attention is paid to the Plan for the implementation of the Ukraine Facility 2024-2027. The reforms for the next 4 years are presented in this document. It is emphasized that some of them are considered in the module No.3 ("Social work in multidisciplinary rehabilitation teams", "Implementation of the veteran's assistant institute", "Evolution of the deinstitutionalization reform in Ukraine") with logical transition to module No.3. The proposed structure and content of the course "Innovations in Social Work" can contribute to the formation of program learning outcomes defined by the educational standard., Special emphasis is placed on the challenges of teaching innovative activities: taking into account the requirements of the standard of higher education and the professional standard, the interdisciplinary nature of knowledge, the incompleteness of legal support for innovative activities in the field of social work. Both the theoretical and legal and educational issues of teaching the course "Innovations in social work" are among the directions of further scientific research.
Strategies for Improving Accuracy and Fluency of Cultural Tourism Translations with the Help of Emerging Technologies
Authors: Meng Bei 
Published: November 2024

Abstract
This paper proposes the preliminary architecture of the cultural tourism corpus in accordance with the requirements of cultural tourism translation accuracy and fluency and further optimizes the structure of the architecture by combining it with the cultural tourism translation quality evaluation standards. Using the simple Bayesian classifier and machine learning technology, respectively, the cultural tourism corpus data and text information are collected, inputted, organized, and classified sequentially. Using natural language processing technology, an encoder-decoder framework is constructed to semantically analyze the preprocessed corpus data information, and proposed algorithm performance evaluation criteria are proposed. Simulation experiments are set up to evaluate the model’s translation quality in conjunction with practical applications. The proposed model in this paper is superior to other models in terms of translation fluency, and the TER index of the model in this paper reaches 72.589%. The model proposed in this paper has a translation accuracy of above 90% after six practical application tests. To understand the cultural background, 52.1% of tourists are interested in using the model proposed in this paper.
Innovative Practice and Subjective Expression of People’s Literature and Art in the New Era
Authors: Li Xue 
Published: November 2024

Abstract
People’s literary creation in the new era has ushered in new opportunities and challenges. The focus of this topic is on the innovative practice and subjective expression of people’s literature and art. The evaluation index system for the communication influence of literary and artistic creations of people is constructed, and evaluation indexes are assigned. Three representative works of people’s literary creations are selected, and the fuzzy comprehensive evaluation method is improved in terms of fuzzy arithmetic and comprehensive evaluation to assess the communication influence of the sample people’s literary creation works. Then, the innovative practice and subjective expression of people’s literature and art are taken as antecedent factors to construct the PLS-SEM model of people’s literature and art creation and dissemination and explore the generating mechanism of people’s literature and art creation and dissemination through the correlation analysis of the variables and the model test. The study finds that there is still much room for improvement in the dissemination influence of people’s literary and artistic creations, and the evaluation results of the sample literary and artistic works are all around 70 points, with an average level of dissemination influence. The innovative practice and subjective expression of people’s literary and artistic creations have a positive effect on perception factors and satisfaction and further have a positive and significant impact on the dissemination of literary and artistic works.
Data Security Storage and Verification Mechanism Based on Distributed Ledger Technology
Authors: Chen Lin , Shangguan Jun 
Published: November 2024

Abstract
Blockchain, as a secure distributed ledger technology, has received extensive attention from academia and industry for its decentralization, comparability and traceability. This paper proposes a method for verifying data security on blockchain, and a cryptographic uploading and retrieval scheme is combined with IOTA blockchain technology. In this way, an IoT data storage and sharing model is designed to combine blockchain with IPFS. In this paper, it is found that there is a certain delay in operating on Fabric and IOTA compared to the scenarios that do not use blockchain. But Fabric has better performance in upload and download performance than IOTA. In the proposed scheme in this paper, the uploading time is stabilized between 0.8 and 1.2, and the retrieval time is stabilized between 0.43s and 0.76s, which has superior data uploading and retrieval performance than Scheme 1. Furthermore, the time to generate a key for a 50MB file is only around 1800ms, and for a 50MB file split into 6KB blocks, the time to generate a secret key is only around 36s. In this paper, when the file size reaches 5MB, the computational overhead of encryption and decryption is about 1315ms and 1283ms, respectively, and the time overhead of data consistency validation is only about 1095ms when the data block is cut into 6KB for a file of 5MB, indicating that this paper’s scheme has a lower time overhead in the generation of the secret key, encryption and decryption, and the data consistency validation. In summary, the above experiments verify the security and applicability of this paper’s scheme in data storage and verification.
Synergistic Development Strategy and Effectiveness Assessment of Agricultural Industry Chain Driven by Digital Economy
Authors: Chen Yinan 
Published: November 2024

Abstract
The in-depth development of the digital economy can promote the optimization and upgrading of the agricultural industrial structure and provide a new impetus for the resilience enhancement and digital transformation of the agricultural industry chain. The article selects the panel data of 30 provinces in China from 2014 to 2023 and applies the entropy value method to measure the level of digital economy development, the level of agricultural industrial structure optimization and the level of agricultural industry chain toughness to test the influence effect of digital economy on the toughness of the agricultural industry chain. At the same time, the optimization of agricultural and industrial structures is included in the mediation effect model to analyze its role in the process of enhancing toughness of the digital economy-driven agricultural industry chain. The results show that the impact coefficient of the development level of digital economy on the toughness of the agricultural industry chain is 0.435, and the impact coefficient after adding control variables is 0.327, both of which are significantly positive, indicating that the improvement of the development level of digital economy can promote the improvement of the toughness level of the agricultural industry chain. The results of the heterogeneity test show that the promotion effect of the digital economy on the toughness of the agricultural industry chain is more evident in regions with large agricultural provinces.
Research on the Analysis of English Learners’ Behavior and Optimization of Teaching Strategies in Big Data Environment
Authors: Ding Lei 
Published: November 2024

Abstract
This paper constructs a road network model after analyzing the structure of the English learning road network under the background of big data. After that, we analyze the characteristics of students’ learning behaviors by extracting them from their daily behavioral data and generalizing them using a large amount of data. The correlation between students’ campus behavior and academic performance is examined using the learning behavior road network model algorithm. Predicting students’ learning styles through the predictive assessment of their behavior and performance using a road network model. Through the clustering of students’ learning behavior portraits, we get the students’ portrait style, optimize the teaching implementation process in a targeted way, and realize the purpose of analyzing the behavior of English learners and optimizing the teaching strategy under the big data environment. The percentage of students who borrowed books 15-20 times (19%), 20-25 times (11%) and >25 times (3%) decreased significantly in the last two months. Most of the students visited the library 60-80 times, and most of them spent 150-200 hours studying in the library. There is a strong correlation between borrowing specialized books and students’ study hours and exam results. In addition, according to the characteristics of students’ study behaviors, this paper classifies them into five categories: “active (38.46%), self-disciplined (21.87%), risky (3.37%), routine (27.31%) and supervised (8.99%)”. Since different student portrait styles have their differences in behavioral characteristics, different teaching strategies should be adopted for students with different learning styles.
Research on Intelligent Assessment Technology for Marine Ecosystem Health Status
Authors: Gao Quanhe 
Published: November 2024

Abstract
With the development of science and technology, the ocean is providing a strong material and economic guarantee for the development of human society. The issue of assessing the health of the marine ecosystem and providing data support for the healthy development of the marine system has become a hot topic for many scholars. This study mainly establishes a marine ecosystem health assessment system, analyzes the health degree of marine ecosystems using information entropy, and then adopts the gray correlation method and the DPSIR model to predict the health level of marine ecosystems, discusses the sustainability of the marine generating system, and provides a development direction for the healthy development of marine ecology. The entropy of the “supportive input” criterion layer is the highest, accounting for 42.25%. From the analysis of the comprehensive health index from 2020 to 2023, the IHI ranges from 0.6 to 1.5, and the state of the ocean can reach a healthy level in the future period, which shows that the development of the economy and science and technology influences the healthy development of marine ecology.
The Role of Intelligent Technology in the Upgrading of the Industrial Chain and Its Promotion of the Regional Economy
Authors: Huang Guiying 
Published: November 2024

Abstract
This paper selects research variables and compares and analyzes the different performances, influence effects and realization paths of industrial intelligence and economic high-quality development in the East, Central and West regions and within the regions. The panel data regression model is used to study the role and path of the manufacturing industry’s upgrading by intelligent technology. The results show that industrial intelligence has a significant positive effect on the high-quality development of the economy in the eastern, central and western regions (P<0.01). In the east (0.198), there is a stronger promotion effect than in the center (0.168), and the weakest effect is in the west (0.142). Intelligent technology can promote the upgrading of the manufacturing industry chain structure by clarifying market demand, improving human capital levels, and optimizing factor allocation.
Practice and Exploration of Ideological and Political Education in Colleges and Universities in the Context of Big Data
Authors: Jia Xiaoxia 
Published: November 2024

Abstract
Big data is not only a technological innovation but also provides a new value and methodology, which provides new ideas and methods to enhance and improve the effect of education and makes the realization of personalization of ideological and political education possible. In this paper, based on the disciplinary knowledge model, we draw a knowledge structure map, organize the learning resource base, prepare disciplinary quizzes, and obtain effective student assessment data. By analyzing student assessment data, we construct a learner interest model to accurately locate the learners’ ideological and political learning needs. Modeling student behavior during video learning of ideological and political courses on the online course platform of universities. Quantify the quality of online learning from the perspective of learning participation time. Then, a learning behavior sequence is defined to describe ideological and political online learning behavior. Finally, two ideological and political education courses in the online learning platform of a university are analyzed for students’ learning behavior, and optimization suggestions for ideological and political education in colleges and universities are proposed based on the analysis results. The geometric means of play completion of the two ideological and political courses are 0.6391 and 0.7907, and the coefficients of variation of the courses are 0.1738 and 0.2136, which indicate that students’ play completion in the two ideological and political courses deviates from the mean value. The results have strong practical application value and provide a new perspective for carrying out personalized education of ideology and politics in colleges and universities in a digital environment.
A Study on the Practical Application of Computational Modeling in Culturally Adaptive Teaching in the Reform of Translation Teaching in Colleges and Universities
Authors: Liang Zheng 
Published: November 2024

Abstract
Language is the bridge of communication between people. Different countries or regions have different social backgrounds, languages, and so on, so cultural differences must be paid attention to in the translation process. This paper focuses on exploring ways to improve students’ culturally adaptive translation ability during translation teaching. The particle swarm algorithm is employed to enhance the calculation model and create the analysis model for students’ culturally adaptive translation ability. The model is trained in Matlab software, and the correlation between the expected value and the measured value is measured by regression analysis to test the model’s performance. Subsequently, the model of this paper was applied to teaching practice, an experimental class was set up, a parallel control class was selected for reference, and a comparative analysis of the students’ culturally adaptive translation ability was conducted before and after the experiment in order to verify the effect of the application of the model of this paper on the improvement of the students’ culturally adaptive translation ability. The average score of students in the experimental class increased by 34.78% before and after the experiment, and the average score of students in the experimental class increased by 19.23% compared with that of students in the control class after the experiment. Compared to the pre-experiment, the increase in the scores of the students in the two classes for the culturally adaptive translation of long and difficult sentences was 116.67% and 47.62%, respectively.
A Study of Improvement Strategies for Semantic Analysis Techniques in Natural Language Processing
Authors: Wang Pingping , Ma Zeliang 
Published: November 2024

Abstract
Semantic analysis, a crucial aspect of natural language processing, encounters numerous practical challenges due to the limitations of its current technology. Therefore, this paper enhances the traditional semantic analysis technology by developing a frame recognition model that integrates syntactic and semantic roles, a text semantic feature extraction model, and an audio/video information extraction model with a multimodal inter-modal cross-attention mechanism. These models are then integrated to jointly construct an improved model for semantic analysis, which is based on deep neural networks. The paper examines the model’s improvement effect in semantic role labeling, text classification, and information extraction. The F1 values of this paper’s model on the Wall Street Journal and Brown test sets are 90.4% and 81.4%, respectively, which are the highest semantic role recognition annotation accuracy rates. The HL, P, R, and F1 values of this paper’s model on the three datasets, on the other hand, are the best results among all models, and it has the best text categorization effect. This paper’s model has a 95.3% accuracy rate in detecting theme subtitles. The recognition accuracy of simple and complex backgrounds is 95.7% and 94.1%, respectively. After the information extraction method of this paper’s model underwent error correction, the accuracy of ASR recognition increased by 18.55%.
Research on Feature Extraction and Optimization Measures of University English Translation for Machine Learning
Authors: Xu Xinxin 
Published: November 2024

Abstract
In the background of increasing translation content, it is no longer possible to rely solely on human translation to solve the problem of cross-language communication, and thus machine translation technology has gradually become an important means to solve the language barrier. In this paper, the semantic content features are extracted from university English using a semantic model based on fuzzy semantic mapping relations. Optimize the model feature extraction based on concept set context matching, introduce Super-Concept and Sub-Concept, calculate the concept semantic translation similarity, and add them into the translation decoding to get the translation optimization results. In this way, the university’s English machine translation system is constructed and evaluated. The maximum values of data recall and context matching rate of the system in this paper are 71.1% and 99.6%, respectively, and the BLEU values of this paper’s model are higher than those of the CNN model and the Transformer machine translation model in the tests of different slicing granularity. The system has high data recall, context matching rate, and translation accuracy, which is feasible and practical in university English translation, and lays a research foundation for further optimization of university English machine translation.
Research on the Application of Intelligent Technology in Promoting Digital Finance and High-Quality Economic Development
Authors: Yang Fuwei , Chen Jingjing 
Published: November 2024

Abstract
Artificial intelligence, blockchain, and other intelligent technologies serve as the primary technical support for the financial industry, enabling it to achieve digital transformation and enhance the quality of development. This paper utilizes the banking industry as a representative of the financial sector, showcasing the benefits of applying artificial intelligence and blockchain technology to the digital transformation of commercial banks through case studies. This approach indirectly underscores the importance of intelligent technology for the robust growth of digital finance. Taking “profitability” and “risk management level” of commercial banks as specific indicators, the relationship between the application of intelligent technology and the profitability and risk management level of banks is explored through multiple linear regression, thus reflecting the role of intelligent technology on the economy and the development of high quality. This paper further analyzes the relationship between banks’ application of intelligent technology and profitability and risk management levels through multiple linear regression. This paper also analyzes the influencing factors of banks’ intelligence levels to provide a reference for achieving high-quality development in digital finance and the economy. According to the regression results, the quadratic term of the intelligence index is 0.00282, which indicates that banks have effectively improved their profitability in the later stages of applying intelligent technology. Before and after the introduction of control variables, the coefficients of the degree of intelligence are 0.41997 and 0.47969, respectively, indicating that the application of intelligent technology is conducive to banks’ ability to improve risk management. It has also been found that factors such as fintech innovation ability, financial regulation, and asset size have a positive impact on the application of intelligent technology in commercial banks.