bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction of English Numerical Intelligence Text Translation Data Corpus in Colleges and Universities
Authors: Zhai Xiang 
Published: May 2024

Abstract
Given the specialized nature of English text translation in academic settings and the frequent absence of reliable reference materials, translation processes often lack verifiable evidence, impacting both efficiency and quality. This paper addresses these challenges by first developing a basic syntactic error correction model that leverages the structural features of recurrent neural networks (RNNs) and gated recurrent unit (GRU) networks to establish a Seq2Seq syntactic error correction framework. To enhance this model, we incorporate an Attention mechanism into the Seq2Seq-based English grammar error correction model. This innovation enables the model to swiftly focus on segments most pertinent to the current context, thereby boosting operational efficiency. Subsequently, we create a college English text translation data corpus using Numerical Intelligence techniques to maintain grammatical accuracy within the corpus. Comparative analysis of the model training reveals that the Seq2Seq model with the Attention mechanism achieves an accuracy rate of 41.7%, which represents a 9.19% improvement over the basic model, underscoring its significant advantage. Furthermore, the average accuracy rate for grammatical error correction stands at 72.87%. A practical application analysis shows a minimal difference of only 0.05 points between the model’s grammar correction scores and those of human teachers. The corpus developed using this enhanced grammar error correction model scored 86 overall, outperforming other corpora. Therefore, the augmented Seq2Seq model with the Attention mechanism proves highly effective for developing English text translation corpora in collegiate environments.
Evolutionary Model of Piano Performance Teaching in Higher Education - Based on Knowledge Graph Analysis
Authors: Fan Xiaohuan 
Published: May 2024

Abstract
The progressive reforms in music education present new prospects and challenges for piano performance teaching in higher education institutions, necessitating the exploration of teaching models that align with contemporary developments through knowledge mapping. This study develops an evolutionary model for college piano teaching that integrates knowledge mapping, graph representation learning, and link prediction techniques. College piano majors were selected for pedagogical experiments to evaluate this model. The efficacy of the proposed piano performance teaching model in colleges was assessed by comparing student satisfaction and piano performance scores before and after the implementation of the model. The findings indicate a significant increase in student satisfaction with the piano teaching approach, with most reporting satisfaction levels above 60%. Furthermore, there was a substantial improvement in piano performance scores, with an average increase of 25.2 points, while students who initially scored high demonstrated stable improvements. This college piano teaching model offers valuable insights and serves as a significant reference for enhancing piano education practices in academic settings.
Network Security Threat Intelligence Prediction in Network Traffic Analysis Based on Machine Learning
Authors: Guan Yankui 
Published: May 2024

Abstract
With the increasingly complex network architecture under the development of information technology, it is more and more difficult to recognize various network traffic. Based on the direction of machine learning for network traffic anomaly detection, this paper proposes a three-stage CNN-LSTM attention mechanism model for feature extraction of original traffic and a PCA-based improvement for spatial feature learning of CNN to construct its anomaly traffic detection model. Meanwhile, based on the abnormal traffic detection, with discriminative network and generative network as the main parts, we propose the cyber security threat intelligence prediction model based on the use of a domain adaptive model to realize the shared representation of source and target domains. In the experiment of the abnormal traffic detection model, the accuracy rate of this paper’s detection model is 93.56%, the check-all rate is 99.2%, the F1 value is 84.9%, and the Kappa value is 80.66%. The detection level in the face of DOS attacks is the highest, with 98.28% and 99.63% checking full rate and checking accuracy, respectively. In the experiments of the network security threat intelligence prediction model, the prediction model of this paper reduces the time consumed by about 72% on average compared to rule file matching in dealing with large-scale network traffic. In high-risk cybersecurity threat attack types, it has an average prediction accuracy of 88.83% and a recall rate of over 90%.
High-quality Construction and Development Path of College of Finance and Economics Industry in Higher Vocational Colleges under the Perspective of Industry-Teaching Integration
Authors: Han Meng 
Published: May 2024

Abstract
Under the wave of digital technology, the integration of industry and education is increasingly becoming the direction of teaching construction in higher vocational colleges and universities. As the foundation of cultivating skilled talents, the construction of a financial industry college in higher vocational colleges is particularly important. Under the perspective of industry-teaching integration, the study combines the triple helix theory to carry out the high-quality construction of finance and economics colleges in higher vocational colleges, analyzes the influencing factors of the high-quality construction of finance and economics colleges in higher vocational colleges by using the DEMATEL algorithm and ISM algorithm, and explores the high-quality construction and development paths of finance and economics colleges by using the Fuzzy Set Qualitative Comparative Analysis (fsQCA) method. The results show that the top 6 influencing factors of high-quality construction of financial and industrial colleges in higher vocational institutions are infrastructure, public services, campus supervision, campus governance, safeguards, and teaching management, and their cause degrees are all greater than 0.5. The overall coverage of innovative development paths of financial and industrial colleges in higher vocational institutions is 0.692. The overall consistency is 0.925, and a total of 3 model paths have been explored, i.e., There are supply-based paths (H1, H3), environment-based paths (H2, H5), and supply-environment synergy paths (H4).
Agricultural Pest Detection Methods and Control Measures Combining Deep Learning Algorithms
Authors: Hu Pengyu , Fang Wei , Li Jiahui 
Published: May 2024

Abstract
Agricultural pests and diseases critically impact the quality and yield of crops, thereby underscoring the practical importance of their automatic monitoring, identification, and timely management in agricultural production. This study develops a targeted detection model using a deep learning approach, specifically by enhancing the Faster R-CNN algorithm. Modifications were implemented in three key areas of the basic Faster R-CNN: First, the DIOU-NMS technique was employed to optimize the ancillary network during the feature extraction phase. Secondly, an attention mechanism along with an SE module was integrated within the DIOU-NMS to augment the network’s capability. During the training phase, optimization was facilitated through stochastic gradient descent. The efficacy of the refined Faster RCNN model was established via ablation studies, and its performance was benchmarked against existing methodologies for small and general target detection. Results indicate that the enhanced Faster R-CNN framework surpasses conventional small target and generic detection models in accuracy, achieving a 6.4% higher detection rate for various pest categories compared to its predecessor. The findings affirm the potential of the advanced Faster R-CNN in effective agricultural pest detection. Furthermore, this paper advocates a tripartite strategy for pest management, encompassing phytosanitary measures, agricultural interventions, and chemical controls.
Application of Adaptive Algorithms in Smart Building Design Optimisation
Authors: Li Qiang , Zhu JingJing , Li Han 
Published: May 2024

Abstract
How to realize the unity of safety, comfort, and economy of building structures has been a hot spot of concern in the field of construction engineering. This paper searches for optimal particles using a hybrid optimization strategy and optimizes the weights of each index in the fitness function into the same interval. Then dynamic inertia weights are used to improve the performance of the algorithm, and an enhanced adaptive particle swarm algorithm is obtained. After selecting the optimization variables for the building design, the objective function and constraints are designed, and the improved particle swarm algorithm is used to solve the optimal design of the intelligent building. The total weight of the target building structure was reduced after optimization, and 47.04% of the building materials were saved. The outer diameter of the steel pipe concrete at the lowest level of the building increases from 1.73m to 2.06m after optimization, which fulfills the law of column change in building design. It has also been found that the wind resistance of the optimized building structure has improved. This paper provides a reliable basis for the application of adaptive algorithms in building design optimization, and the proposed method also provides an effective reference for the field of construction engineering.
Application and Challenges of Virtual Reality (VR) in Art Exhibition Planning
Authors: Chen Jiahui 
Published: May 2024

Abstract
The combination of VR technology and art exhibition promotes a new form of art exhibition and enriches the multi-sensory experience of visitors. After analyzing the development form of VR art exhibition and the design process of VR art exhibition, this paper puts forward the solution countermeasures of using the sparse 3D map to optimize the presentation of virtual reality visualization scene, refining the 3D scene model and improving the presentation of the surface scene based on the Possion reconstruction for the lack of development of interactive experience in VR art exhibition. As well as based on the dimensions of interactive experiences, Kinect somatosensory interaction technology is used to update the interactive experience design in VR art exhibition planning. Explore the optimization effect of VR art exhibition planning, analyze the visitors’ interactive experience task completion time, participation, and interactive experience degree, and put forward effective countermeasures for the future development of VR art exhibitions. The mean value of scores of VR exhibitions and offline exhibitions are 5.887 and 5.657, respectively, with a difference of 0.23 and a total score difference of 2.07, which indicates that the art exhibition constructed on the basis of VR has a better sense of experience.
Stylistic Conversion and Linguistic Beauty Reproduction in English Translation-Based on Neurosemantic Analysis
Authors: Gong Han 
Published: May 2024

Abstract
The core of translation is language conversion, but it should be more of an aesthetic experience, a transformation of different ways of thinking. This paper proposes a neural semantic analysis method for English translation based on text similarity calculation. The technique uses a large-scale corpus to train the vector space model of words, establishes a concept-context matrix through the term-document matrix, and determines each value of the concept vector with a weight according to the literary translation in the knowledge base. The information extraction and evaluation of the English-translated text through semantic similarity calculation provides a theoretical basis for the subsequent analysis of style conversion and linguistic, and aesthetic reproduction of the English-translated text. The study will take the Lin Yutang translation and the Ricardian translation of The Analects of Confucius as an example to develop the analysis of style transformation and reproduction of linguistic beauty of the English-translated text from both lexical and syntactic levels. The results show that the lexical density of Lin Yutang’s translation is 0.5866, while that of Rie Jacob’s translation is 0.5334, with the former significantly larger than the latter. It shows that Lin Yutang’s translation of The Analects of Confucius adopts a naturalization strategy, i.e., To disseminate Chinese culture in a way that is authentic, familiar to English readers, and easy to understand, so as to make his linguistic expression more emotional.
Practical Exploration of Smart Classroom in Piano Teaching
Authors: Huang Xiaodong 
Published: May 2024

Abstract
In this paper, texture mapping technology is utilized to enhance the virtual reality piano teaching situation, and the piano classroom teaching data is integrated through big data statistical analysis methods. A deep neural network based on BERT+BiLSTM+CRF is used to train a named entity recognition model and complete the construction of a knowledge graph for piano subject data. Then, deep learning methods are used to extract the piano subject data and construct a visualized knowledge graph for the piano subject. Analyze the use of the Piano Smart Classroom teaching platform and the development of a blended teaching mode. The design requirements of the piano intelligent teaching platform are planned from two aspects: platform user roles and platform use cases, and the overall design of the piano intelligent teaching platform is carried out. The use of piano teaching video samples is a tool for calculating the teaching language ratio, analyzing the teaching interactions between teachers and students, and comparing the number of interactions between traditional teaching and smart classroom teaching. Analyze the effectiveness of piano-smart classroom teaching in three dimensions: cognition, emotion, and skill. The mean value of the specific content score of piano intelligent classroom teaching is 3.82, which is the single item with the highest mean value, and the piano teaching classroom supported by smart technology can show the piano teaching content more comprehensively.
Identification and Correction of Improved GLR Algorithm in English Translation Teaching
Authors: Li Tao 
Published: May 2024

Abstract
In this paper, after clarifying the common types of errors in English translation teaching, in order to achieve the improvement of English translation teaching, combined with the GLR algorithm for English phrase recognition and analysis, PCFG English syntactic analysis model and HDSM lexicalization model are introduced for the optimization of GLR algorithm, which constitutes the PCFG-HDSM model. Analyze the process of English translation error recognition and correction with an improved GLR algorithm and realize the improvement of the GLR algorithm. Compare the performance of the English translation grammar analysis generator and determine the ratio of pure grammar analysis time to total analysis time. Examine the English translation accuracy of the improved GLR algorithm by combining the training corpus and evaluating it using LP and LR metrics. Analyze practical teaching applications by classifying the structure of English translation topics and using the improved GLR algorithm. The improved GLR algorithm is able to achieve more than 80% of English translation recognition and correction rates, which enhances students’ scores on English translation topics and promotes the development of English translation teaching.
Correlation Analysis of Higher Education Music Teaching Quality and Students’ Artistic Literacy - Based on Regression Analysis Model
Authors: Lin Yushi 
Published: May 2024

Abstract
Music core literacy encompasses the essential skills students must acquire to form accurate concepts through music course learning. The enhancement of students’ artistic literacy within music education has emerged as a focal area of research. This study targets music majors at colleges and universities in H city, employing a questionnaire designed from dual perspectives: the quality of music teaching and the level of students’ artistic literacy. We applied open coding to the collected data, grounded in rooting theory, to formulate relevant research hypotheses. Subsequently, we assessed the reliability and validity of the questionnaire through factor analysis and conducted a preliminary analysis of the correlations using the Pearson correlation method. Furthermore, we developed a multiple regression model, positioning students’ artistic literacy as the dependent variable and music teaching quality as the independent variable, to explore and verify the interrelationships and hypotheses. The findings indicate that the equation can predict students’ artistic literacy: 0.882 + 0.255 × teaching ideology + 0.112 × teaching process + 0.176 × teaching ability + 0.225 × teaching effect. The results confirm that the quality of music teaching in colleges and universities significantly influences students’ artistic literacy levels. This research provides valuable insights for higher education institutions aiming to innovate music teaching methodologies and enhance the holistic literacy of their students.
Research on Digital Media Content Production and Dissemination Mode Based on Artificial Intelligence
Authors: Ma Shiming 
Published: May 2024

Abstract
In order to study the effect of digital media content production and dissemination supported by artificial intelligence technology, we aim to improve the dissemination and influence of digital media in short video platforms. This paper takes digital media as the research object and launches research on digital media content production and dissemination mode. Based on the research method of inquiry description, the core process of digital media intelligent transformation was deeply analyzed, and the overall logical framework of digital media intelligent transformation was designed. The digital media content production flow model is built by combining data integration and aggregation mining from a digital media content perspective. A graph-convolution matrix decomposition recommendation model for digital media broadcasting was developed by analyzing the performance of algorithmic recommendation in digital media applications. The results are presented: in terms of the order of influence degree size, the degree of influence on the number of likes is greater for political news (Beta = 0.2026, p < 0.01) than for military science and technology (Beta = 0.1637, p < 0.01) than for social news (Beta = 0.1225, p < 0.05), i.e.It indicates that the content theme is shifting from traditional social news to political news, which makes it easier to increase the heat of content dissemination. This study helps us think about the impact of media content production and dissemination strategies in the age of mobile Internet and provides new inspiration for communication theory research.
Research on Intelligent Optimisation Strategies for Interior Space Layout Design with the Aid of 3DsMax+AI
Authors: Liu Songlin 
Published: May 2024

Abstract
Indoor intelligent assistive technology has been widely used in space layout design optimization. This paper proposes a heuristic scene space layout generation method based on the smart evolution of scene space AI with WFC and deep network, joint wave function collapse algorithm, as well as two deep neural networks to generate the layout wireframe diagram while strangling reasonable boundaries and predicting functional semantic labels for the layout subspace. Applying the method of this paper to the office space layout optimization design, the results show that 95.68% of the area of the office and conference room has a lighting coefficient greater than 2%, and 85.78% of the area of the design room has a lighting coefficient greater than 3%. Ordinary white glass can be utilized in the design room to enhance the lighting quality, with a lighting coefficient of 2.87 and a compliance rate of 100%. The inset atrium space has a greater percentage of indoor thermal comfort area and a faster air flow rate. In this paper, 3DsMax+AI intelligent assistance and other technologies are used to simulate the layout design of the office space and realize the optimization of its layout design.
Academic Mobility in the Conditions of Forced Migration in Wartime (experience of Ukraine)
Authors: Boichenko Mykhailo 
Published: May 2024

Abstract
Forced migration during the war led to significant changes in academic mobility in Ukraine. This challenge received a worthy response thanks to the support of Ukraine from the European Union, the USA and other countries of Western democracy: many Ukrainian students and professors received greater opportunities to study and work in European and Western universities in general. This article aims to identify the main threats to inclusivity and new opportunities to provide additional resources and educational space for the development of inclusivity, which is directly related to forced migration as one of the challenges to higher education in Ukraine during this war. The methodology of this article is a philosophical approach based on the use of interrelated concepts of challenge and response. The case study of challenges for academic mobility in Ukraine is used as well. Obstacles and limitations of academic mobility during the war appear to be partially overcome, thanks to distance education. The new opportunities that have opened up for the Ukrainian higher education system provide broad and strategic prospects for the deep integration of the Ukrainian higher education system into the European and world educational space.
Specifics and Perspectives of the Third Mission of the Medical University: a Survey
Authors: Rodinkova Victoria , Kharkovenko Ruslana , Drachuk Olga , Horbenko Nataliia 
Published: May 2024

Abstract
Abstract:
Universities are an integral part of the communities in which they are located and linked by the practices of implementing various activities. Medical universities, whose mission is to contribute to public health, have especially tight connections with society. This paper discusses the specifics and perspectives of the third mission of the medical university in peacetime and during war using a specially designed survey.
It was determined that the social image of the medical university is provided by various socially oriented policies, primarily by providing medical aid to the population and conducting educational activities. The medical university is also a place for the continuous professional development of doctors and provides expert evaluation at the request of local authorities. Such a system of interaction has been established for years, and the process of collecting actual requests from the community needs to be adjusted and improved. Prospects for cooperation between the medical university and the community include the need to provide aid to the population that suffered as a result of russia’s armed aggression. Therefore, medical educational institutions, providing their main activity, will most likely become important centers for the rehabilitation of the wounded and providing them with psychological help. Thus, although the medical university has a lot of experience in cooperation with the community, this process could be improved by establishing a more constructive cooperation with society through the use of mechanisms developed and based on the appropriate regulatory framework that should meet the challenges of the time.