bluuebunny/crossref_metadata_2025 huggingface dataset:
PEDAGOGICAL CONDITIONS OF PREPARING STUDENTS FOR DIAGNOSTIC ACTIVITIES IN INSTITUTIONS OF HIGHER EDUCATION
Authors: Chuvasov Mykhailo
Published: November 2024

The training of highly qualified pedagogical staff is particularly relevant, as well as the process of diagnostic activity in the system of professional training and the identification of means of objective assessment of the quality of preparedness of future teachers for creativity and pedagogical mastery in the field of pedagogical work. The purpose of the research: to identify a set of pedagogical conditions and to theoretically substantiate their importance in the increased productivity of forming the readiness of future teachers for diagnostic activities. Research methods: analysis, synthesis and systematization of philosophical psychological-pedagogical and methodological studies devoted to the formation of the readiness of future teachers for diagnostic activity, the formation of readiness for diagnostic activity in the process of professional training at the university, for studying the state of the problem and theoretical justification of the need for it; comparative analysis, generalizations, which make it possible to distinguish the pedagogical conditions of the productivity of training future teachers for diagnostic activities in the system of university education. The positive result in the formation of readiness of future teachers for diagnostic activity in the educational process is due to a set of conditions: the creation of a psychological climate and a communication-emotional educational environment for the development of professional potential in the educational institution; the development of the innovative potential of an individual, the creative saturation of the diagnostic activity content; personal active position of the diagnostic process subjects; methodological literacy in the diagnostic activities organization and implementation.
SOCIAL AND PSYCHOLOGICAL SUPPORT IN VETERAN DEVELOPMENT CENTERS: PRACTICAL EXPERIENCE
Authors: Kravchenko Oksana , Baldyniuk Olena , Kvashuk Vitalii
Published: November 2024

Institutions of higher education actively participate in the implementation of the state veteran policy. The article characterizes the practical experience of the Center for Veteran Development in providing first-level psychological assistance. Research methods applied: analysis of the activities of the Center for Veteran Development of Pavlo Tychyna Uman State Pedagogical University, generalization of the main forms of social and psychological support for veterans and their family members; study of the official website of the institution of higher education. The main form of socio-psychological support for veterans and veterans is Veteran Development Centers. The article`s purpose is to characterize the practical experience of the Center for Veteran Development in providing first-level psychological assistance. Research methods: analysis of the activities of the Center for Veteran Development of Pavlo Tychyna Uman State Pedagogical University, generalization of the main forms of social and psychological support for veterans and their family members; study of the official website of the institution of higher education. Since 2023, such a center has been created based on Pavlo Tychyna Uman State Pedagogical University. The university staff is working on creating a barrier-free space and accessible services. Among the forms of work of the center: individual psychological counseling is provided; group therapeutic classes, psychoeducation, and information sessions are practiced; rehabilitation programs are being developed; measures to support families are in demand; relaxation techniques and therapies are effective; individual work on social and psychological adaptation is carried out; training work is popular. Volunteer activities are systematically carried out by specialists and volunteers of the Center. It is possible to study for veterans at the university, as well as to study a foreign language.
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.
Weed Community Changes Due To Herbicide Treatment In Mature Oil Palm Plantations
Authors: Apriansa Azharudin , Yakup Yakup , Susilawati Susilawati
Published: November 2024

Stenochlaena palustris, commonly known as pakisan weed, poses significant challenges in oil palm plantations due to its highly invasive nature, which can lead to reduced agricultural productivity. Management of this weed is critical, as effective control measures can inhibit its dominance and promote the proliferation of alternative weed species, thereby enhancing biodiversity within the ecosystem. This study aimed to 1) assess the effectiveness of the herbicide ammonium glufosinate, in combination with an adjuvant, for controlling S. palustris in oil palm plantations, and 2) investigate the subsequent alterations in the weed community structure following herbicide application. We employed a randomised group design (RAK), incorporating the herbicide with added adjuvants. Results showed a clear change from S. palustris to Asystasia sp. as the dominant species. Treatments K and H had the most Asystasia sp., while treatment L had the least. Furthermore, we clearly compared treatments L, K, and S to the control treatment, emphasizing the emergence of diverse species within the treatment plots. However, low levels of diversity and evenness suggest a stressed weed community, indicating that the herbicide application can disrupt existing ecological balances. This study emphasizes the importance of assessing herbicide impacts not only on targeted weed species but also on broader community dynamics, revealing a significant research gap in understanding the long-term ecological consequences of herbicide use in oil palm plantations.
Jak bezpiecznie prowadzić terapię marihuaną leczniczą?
Authors: Sapilak Bartosz J.
Published: November 2024

Niniejsza praca stanowi przybliżenie kanadyjskiego opracowania, które ukazało się 3 lata temu na łamach „European Journal of Internal Medicine”. Omówiono w nim zasady prowadzenia i monitorowania terapii marihuaną medyczną. Przedstawiono informacje o działaniach niepożądanych, metodach dawkowania, doborze substancji czynnych i modyfikowaniu leczenia.
The role of the stakeholders in sustainable ecotourism management at Malela Waterfall of Indonesia’s West Bandung
Authors: Anwar Rully Khairul , Saepudin Encang , Rukmana Evi Nursanti
Published: November 2024

The purpose of this study is to address the issue of low local participation in ecotourism management in Indonesia, specifically at the Malela Waterfall ecotourism site in Cicadas Village, Rongga District, West Bandung Regency, West Java, Indonesia. The research method is action research, which includes observation data gathering, in-depth interviews, and Focus Group Discussions. The findings of the study show that by carrying out the process of developing social infrastructure, namely development that prioritizes strengthening human resources in carrying out social service functions in ecotourism activities such as skill training of residents in the field of ecotourism, massive ecotourism outreach, and strengthening social communities—Non-Governmental Organizations (NGOs) and youth organizations as ecotourism actors. This type of development serves to raise awareness and participation among local inhabitants in Malela Waterfall ecotourism in West Bandung Regency. This promotes harmony and mutually beneficial partnerships among all Malela Waterfall ecotourism stakeholders. Furthermore, increasing community participation benefits the well-being of residents in the tourist region.
Comparative assessment of ESG ratings methodology and results based on XBRL
Authors: Lukács Bence , Molnár Péter , Rickards Robert C.
Published: November 2024

This study provides a comparative analysis of Environmental, Social, and Governance (ESG) ratings methodologies and explores the potential of eXtensible Business Reporting Language (XBRL) to enhance transparency and comparability in ESG reporting. Evaluating ratings from different agencies, the research identifies significant methodological inconsistencies that lead to conflicting information for investors and stakeholders. Statistical tests and adjusted rating scales confirm substantial divergence in ESG scores, primarily due to differing data categories and indicators used by rating firms. Using a sample of 265 European companies, the study demonstrates that individual ESG agencies report markedly different ratings for the same firms, which can mislead stakeholders. It proposes that XBRL based reporting can mitigate these inconsistencies by providing a standardized framework for data collection and reporting. XBRL enables accurate and efficient data collection, reducing human error and enhancing the transparency of ESG reports. The findings advocate for integrating XBRL in ESG reporting to achieve higher levels of comparability and reliability. The study calls for greater regulatory oversight and the adoption of standardized taxonomies in ESG reporting to ensure consistent and comparable data across sectors and jurisdictions. Despite challenges like the lack of a standardized taxonomy and inconsistent adoption, the research contends that XBRL can significantly improve the reliability of ESG ratings. In conclusion, this study suggests that standardizing ESG data through XBRL could provide a viable solution to the unreliability of current ESG rating scales, supporting sustainable business practices and informed decision making by investors.
Integrating LLMs and software-defined resources for enhanced demonstrative cloud computing education in university curricula
Authors: Pan Wuming , Yang Ying , Yin Hao
Published: November 2024

This paper explores the integration of Large Language Models (LLMs) and Software-Defined Resources (SDR) as innovative tools for enhancing cloud computing education in university curricula. The study emphasizes the importance of practical knowledge in cloud technologies such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), DevOps, and cloud-native environments. It introduces Lean principles to optimize the teaching framework, promoting efficiency and effectiveness in learning. By examining a comprehensive educational reform project, the research demonstrates that incorporating SDR and LLMs can significantly enhance student engagement and learning outcomes, while also providing essential hands-on skills required in today’s dynamic cloud computing landscape. A key innovation of this study is the development and application of the Entropy-Based Diversity Efficiency Analysis (EDEA) framework, a novel method to measure and optimize the diversity and efficiency of educational content. The EDEA analysis yielded surprising results, showing that applying SDR (i.e., using cloud technologies) and LLMs can each improve a course’s Diversity Efficiency Index (DEI) by approximately one-fifth. The integrated approach presented in this paper provides a structured tool for continuous improvement in education and demonstrates the potential for modernizing educational strategies to better align with the evolving needs of the cloud computing industry.
Strategies for Improving Accuracy and Fluency of Cultural Tourism Translations with the Help of Emerging Technologies
Authors: Meng Bei
Published: November 2024

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

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

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

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

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

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

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

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

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

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

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

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.
Exploring Random Forest Modeling of Accounting Disclosure Quality and ESG Performance in the Face of Big Data Era
Authors: Zhang Rongkun , Yang Zi , Liu Xinxin
Published: November 2024

This paper combines the theoretical knowledge of the current research on accounting information disclosure and ESG performance, selects seven first-level indicators, which are truthfulness, completeness, materiality, relevance, timeliness, comparability, and comprehensibility, and then subdivides these seven first-level indicators to obtain 22 second-level indicators, thus forming the evaluation index system of accounting information disclosure quality. Based on the high flexibility and robustness of the Random Forest (RF) model, it is proposed to use the Random Forest (RF) model to calculate the weights of the evaluation indicators. The evaluation index system’s comprehensive evaluation results are calculated using the TOPSIS method immediately. The comprehensive evaluation results of accounting information disclosure quality are taken as the explanatory variables of the fixed-effects model, and the data of the explanatory variables and control variables originated from a certain data system, and the fixed-effects model is chosen to clarify the relationship between the quality of accounting information disclosure and ESG performance. The regression coefficient for accounting disclosure quality is 0.0349, and there is a significant positive correlation between accounting disclosure quality and ESG performance at the 1% level. When the quantitative value of corporate accounting disclosure increases by 1 unit, the quantitative value of ESG performance improves by 0.0349 units.
Research on Efficient Data Warehouse Construction Methods for Big Data Applications
Authors: Zhao Chenggang , Du Junwei , Wang Furong , Li Haojie
Published: November 2024

In computing application scenarios with large volumes of data, time-efficient data warehouses are the primary choice for most businesses. The metadata module will be designed with MySQL as an intermediate node for information exchange among modules in an efficient data warehouse in this paper. The first and second-layer data scheduling algorithms are utilized to monitor the progress of queries and updates in the data warehouse system in real-time, and to realize the intelligent setting of dynamic priorities for data processing tasks. Subsequently, the data scheduling and execution module is built based on the scheduling algorithm, and the efficient data warehouse system is constructed using the Hadoop open-source computing framework. The results show that each module of the efficient data warehouse system passes the functionality test, and the data processing time in real and synthetic datasets can fully satisfy the actual time requirements of big data processing and data analysis. In addition, the performance of this paper’s data warehouse system is better than the comparison data warehouse system, and the query time of this paper’s system can be reduced by 87.74% compared with the comparison system in the 1-dimensional data dimension of the SD2 dataset. The efficient data warehouse system designed in this paper is able to achieve high throughput and low latency optimization, which improves the efficiency of data processing and provides a reference for related research in the field of big data processing.
Impact of media attention, corporate announcements on stock market returns based on big data
Authors: Xue Ziyu , Zhu Sha
Published: November 2024

The rapid development of big data technology has led to a profound impact on the stock market from media reports, corporate announcements, and other public opinion data. To address this issue, after collecting relevant data, a panel regression model is used to analyze the specific mechanism of media attention on stock returns. Multiple regression models are also used to analyze the effect of corporate clarification announcements on their response to stock market returns. The value of Hauseman’s statistic for the panel data on stock returns and media attention is 0.964, and the probability is 0.67. The correlation between media attention and stock returns is positive. While media attention is significant at a 1% confidence level, every 1% increase in the stock attention index increases the stock return by 0.002%, keeping other variables constant. The overall significance of the regression results for the quality of clarification announcements and their effect is evident, with a R-square value ranging from 11% to 21%. This suggests a good fit between the regression equation and the credibility of the multiple regression results. The regression results show that the time lag, level of detail, and defense attitude of corporate clarification announcements influence their clarity effect, thereby significantly impacting stock market returns. The findings of this paper are significant in promoting the stable development of stock and capital markets.
Natural language processing in language learning: personalized and adaptive English language teaching using artificial intelligence
Authors: Li Deyi , Wang Hongbin
Published: November 2024

In recent years, artificial intelligence technology has begun to be widely used in the field of language teaching in colleges and universities. As an important branch of artificial intelligence, the study introduces natural language processing technology into English teaching in colleges and universities, utilizes it to extract rich semantic features in English teaching resources, combines LSTM and attention mechanism, and designs an English teaching resource recommendation model based on student’s interests. Based on the recommendation model, an adaptive platform for English teaching is constructed. A small-scale trial is conducted to discuss students’ feedback after the trial and explore the application effect of the platform. The results of each index of the English teaching resources recommendation model are optimal, and the recall (88.65%), accuracy (90.29%) and NGDD (0.3725) are higher than those of other models, which proves the model’s effectiveness in resource recommendation. The positive feedback from students on the adaptive effect, applicability, and recognition of the adaptive platform for English teaching is basically above 50%. The analysis reveals that the AI-based resource recommendation model and adaptive English teaching can aid English teaching in colleges and universities and enhance the quality of English teaching.
Artificial Intelligence-Assisted Simulation Research on Intelligent Behavior of Film and Television 3D Animation Characters
Authors: Lin Yesheng
Published: November 2024

With the continuous development of artificial intelligence technology, the continuous improvement of three-dimensional animation design technology has become an inevitable trend. This paper conducts a simulation study on the intelligent behavior of three-dimensional animation characters in film and television, using finite state machines as the basis. First, we look at the basic parts of the character behavior diagram design and behavior modeling. Then, we use the decision state of the finite state machine to define the intelligent behavior of a three-dimensional animation character. Finally, we combine the character behavior operation principle with the character action generator to finish building the character intelligent behavior model. Under the technical support of the film and television animation character behavior model of the finite state machine, Anima Studio is used to realize the construction of the film and television animation character simulation platform, and the platform of this paper is used to explore the simulation of intelligent behavior of animation characters. Upon exploration, we discover that the animated character, utilizing the finite state machine model, operates efficiently and consistently, thereby demonstrating the simulation effect of the film and television animation character simulation platform in a vivid and realistic manner.
Research on the Application of Montage Technique in the Integration of Construction Technique and Design of Cultural Elements of Patchwork Clothing
Authors: Wang Haitao
Published: November 2024

In modern clothing design, quilting as a means of emphasizing pattern decoration and enriching fabric texture form, its application has presented a diversified and diversified trend. This paper utilizes the montage technique in the process of designing patchwork clothing. The cultural elements of quilted clothing are being innovated through the use of the unique creative art technique of montage. Patchwork clothing design and montage techniques are cross-analyzed to explore the commonality of the two in creative techniques and artistic expression. In order to objectively measure the design effect, AHP is used to determine the weights of the indicators, and then TOPSIS is used for the comprehensive evaluation, which is constructed into a comprehensive evaluation model of quilted apparel design integrating the montage technique. The design evaluation results were achieved by combining the consistency test of the model and the hierarchical total ranking. According to the hierarchical analysis method, the weights of the secondary indicators are calculated, and practicality (25.46%), comfort (20.96%), and functionality (15.37%) rank in the top three, which have a greater impact on the effect of quilting garment design incorporating the montage technique. When the two techniques are applied to apparel design, the understanding and application of practicality, comfort, and functionality should be deepened.
Intelligent optimization of process parameters and regulation mechanism for the preparation of water-based ink for polyethylene-polyvinyl acetate films
Authors: Yao Xiaoping
Published: November 2024

Ink is the printing industry’s most basic raw material, mainly composed of resin and organic solvents. However, these organic solvents not only harm the industry’s staff but also have a great potential for environmental pollution. In recent years, with the continuous modification of resin, the structure of new products in the ink category has also changed greatly. This paper first analyzes the basic principle of polyvinyl acetate to form water-based ink, based on the synthesis method of ink, water-based ink prepared through experiments, and put forward the corresponding ink performance testing and analysis methods. Subsequently, according to the proposed test method, the prepared water-based ink was analyzed in terms of performance and water absorption. Orthogonal tests were designed to optimize the ratio of poly (vinyl acetate) copolymerization raw materials. Then, the experimental data were processed to derive the optimization formula of the process parameters for the preparation of PVAs slow-release film, and finally, the mechanism of regulating the morphology and structure of PVAs core-shell ink was obtained. The ink water resistance test showed an increase in ink surface tension from 54.154 mN/m to 60.545 mN/m due to an increase in R. The average particle size of ink particles of different core layers was around 178 nm, which was less affected by the change of core layer, and the ink particle size of different shell layers ranged from 120-290 nm and increased gradually with the increase of shell layer.
Research on Data-Driven Visual Element Positioning and Brand Impact Analysis Methodology
Authors: Huang Xuan
Published: November 2024

Visual element positioning is the main soul of a brand, which can directly give the public the brand identity from the appearance impression and can play an icing on the cake for the enhancement of brand influence. In this paper, we collect consumers’ online review data and preprocess the data, extract the keywords of visual element positioning and brand influence using the TF-IDF algorithm, and then analyze consumers’ sentiment scores for each dimension using the sentiment value calculation method. Finally, a multiple-step regression model is constructed based on correlation analysis and data-driven analysis to analyze the relationship between visual element positioning and brand influence. The results show that there is a significant positive correlation between the visual element positioning of the sign and each dimension of brand influence (r>0, P<0.05). And the logo design (P=0.010<0.05) and auxiliary graphic design (P=0.000<0.05) in visual element positioning can have a significant positive impact on brand purchase tendency and brand identity. This paper shows that visual element positioning can promote the development of brand products, provide a reference for good and accurate image positioning of the brand, help improve the brand value and uniqueness, and then improve the brand influence.