bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling the clearing of intra-provincial power market considering the equivalent value of power supply from outside Guangdong Province under the environment of Southern Regional Market (SRM)
Authors: Wang Haohao , Huang Yuanming , Luo Jinqing , Shu Kangan , Sun Qian , Chen Qing 
Published: April 2024

Abstract
Focusing on the complex market environment of Guangdong Province, this research pioneers a model for assimilating external power sources into the intra-provincial power market, a critical move to support the region’s high demand for electricity driven by robust economic activities. Our study innovatively tackles the province’s fluctuating power supply and demand by employing a novel power supply equivalence and co-modulation technique, enhancing system modeling efficiency and computational effectiveness. Comparative evaluations demonstrate that our approach significantly reduces the power market’s purchase costs by 15% while safeguarding power supply stability and security. The proposed model presents a breakthrough in optimizing Guangdong’s power market’s economic and reliability aspects, offering a promising pathway for future market clearing practices.
Research on microbial data modeling and disease prediction by fusion and integration of deep learning
Authors: Wang Zidong 
Published: April 2024

Abstract
The dynamics of microbial communities are closely related to human health. Deep learning techniques have shown great potential in bioinformatics by demonstrating powerful data analysis capabilities in areas such as microbial data modeling and disease Prediction since recent years. Our paper explores new approaches combining deep learning techniques with microbial data to generate more precise predictive models for early diagnosis and treatment. This study is dedicated to developing a method for modeling microbial data and predicting diseases that incorporates deep learning. Multiple deep learning models combine data from microbial communities to improve prediction accuracy through an integrated learning strategy. Experiments were conducted on two primary disease datasets: Inflammatory Bowel Disease (IBD) and Colorectal Cancer (Colorectal). This research method’s AUC values were 0.897 and 0.876, which is an improvement compared to traditional machine learning methods. A new perspective on the study of disease mechanisms was provided by identifying highly correlated microbial markers through feature selection analysis. This study can effectively enhance the use of microbial data in disease prediction by integrating deep learning models, which provides powerful technical support for future clinical diagnosis and treatment.
Exploring the Dynamical System Modeling and Evolutionary Mechanisms for the Integration of AI and Civic Education Management in Colleges and Universities
Authors: Zhang Yue 
Published: April 2024

Abstract
With the help of the dynamics model of the integration of AI and the management of college civic education, this paper investigates the integration of artificial intelligence and civic education in three directions: application specification, application design, and application practice. Using differential equations to represent the non-linear dynamics equations of the system and by means of differential solutions, the evolution mechanism of AI education application and integration is projected in this paper. The integration of AI and college civic education is explored through empirical analysis and comparative analysis. The results show that the average value of the comprehensive score of the three directions in the sample colleges and universities is 77.5828, which is in the bare integration stage, and the integration degree in the “formulation” path is the best, which is 85.698, and is in the complete integration stage. The students in the experimental class of the sample universities scored better than the control class without AI integration in civic education. There were no students with scores below 60, and there were 32 more students than the control class in the 90–100 segment.
Construction of Cybersecurity and Risk Prediction Model for New Energy Power Plants under Machine Learning Algorithm
Authors: Sun Xiaofu , Wang Shengda , Liu Danni , Wang Lihong , Lin Ziqing 
Published: April 2024

Abstract
Addressing the complex equipment and network challenges in new energy power plant industrial control systems, this study introduces a Markov time-varying machine learning algorithm, leveraging classification-constrained Boltzmann machines for real-time network security risk prediction. By employing a hybrid training mode for innovative feature extraction and classification, the algorithm forecasts future security risk states through an up-to-date state transition probability matrix. Integrating with the Markov time-varying model enhances the efficiency over traditional Boltzmann machines, facilitating nuanced network state analyses. The proposed model demonstrates high effectiveness against various network attacks, with average precision, recall, and F1 scores of 0.96, 0.93, and 0.94, respectively, and maintains over 80% accuracy under noise levels up to 40 dB. This research provides a solid foundation for proactive security defense mechanisms in industrial control systems.
A Study on the Construction of a Smart Music Education Classroom and the Utility of Music Teaching Reforms
Authors: Hou Bowen , Chen Bo , Liu Weiwei , Qiu Xiaolan 
Published: April 2024

Abstract
This study explores the integration of information technology tools, such as audio signal visualization, score recommendation algorithms based on difficulty features, and sight-singing assessment algorithms, into the development of an intelligent music classroom. It evaluates the impact of these technologies on teaching quality and efficiency, emphasizing their role in enhancing music sight-singing and classroom visualization. Findings reveal that innovative music education significantly improves teaching outcomes. While over half of the students responded positively to the creative teaching approaches, a segment found the material presented through music visualization challenging. However, introducing an intelligent music education classroom markedly benefits students’ musical learning.
Structural Analysis and spatial impact of financial agglomeration effects on regional economic development
Authors: Zhong Ming , Hong Qingyu , Yu Jingjing 
Published: April 2024

Abstract
This study examines the impact of financial and industrial agglomeration on regional economic development through a descriptive analysis. By establishing an evaluation index system for financial agglomeration effects and constructing a spatial measurement model, we empirically investigate the dynamics between financial accumulation and economic growth. Our Analysis of 37 Chinese cities reveals that Moran’s I, indicating the spatial correlation of economic growth, varies between 0.300 and 0.410, suggesting a strengthening spatial correlation over time. These findings highlight the significance of financial agglomeration in regional economic development and suggest avenues for economic structure optimization.
Construction of Social Resilience Assessment System after Floods in the New Era
Authors: Yin Junyi 
Published: April 2024

Abstract
This paper constructs an assessment framework through theoretical research and literature study, determines the assessment indicators using the systematic review method, and forms a final assessment system of social resilience after flooding based on the correlation test. On this basis, the index weights were determined using the comprehensive assignment method, and the social resilience index was calculated using multi-criteria optimization and compromise solutions methods. The spatiotemporal evolution trend and spatial correlation characteristics of post-flood social resilience were explored by combining mathematical statistical methods, geographic information technology, and spatial measurement models. The temporal evolution characteristics of different dimensions of social resilience during the period 2012–2021 show that the social resilience index declined steeply in 2012, reached a maximum value of 0.316 in 2018, then gradually decreased to 0.305 in 2020, and recovered to 0.312 in 2021, with an overall increase of 5.05%. Assessing the social resilience of 17 cities under the jurisdiction of Henan Province, overall, the ability of the social system to cope with heavy rainfall and flooding disasters in 10 cities showed an increasing trend, and 7 towns showed a decreasing trend.The social resilience of Zhengzhou City under heavy rainfall and flooding disasters in 2017–2021 showed a trend of decreasing and increasing, with a composite index fit of 0.885, 0.893, 0.806, 0.893, 0.806, 0.824, 0.861.This paper constructs a social resilience assessment system after flooding to provide some reference for central cities to cope with extreme weather.
Research on the Transformation of Digital Intelligence of Accounting Profession Based on Big Data Technology
Authors: Zheng Su 
Published: April 2024

Abstract
Teaching RPA technology to accounting students can be better adapted to the changing market demand. Therefore, this paper proposes the RPA financial automation process model generated by the data flow classification algorithm using integrated learning, which combines the development and application of RPA into the daily teaching of accounting students and combines the data analysis and application with practical scenarios. The questionnaire survey reflects the students’ comprehensive evaluation of the course’s teaching quality, application effect, satisfaction, and maturity of the RPA model. In the survey results on the stereoscopic satisfaction of the cultivation of professional knowledge, skills and vocational ability, the average score of each item exceeds 2 points, and the satisfaction of RPA technology is high. In the evaluation of application, the scores of curriculum dimension and teaching method dimension are 80.37 and 82.06 respectively, which are at a better level, and the score of accounting process dimension is 77.83, which brings a positive impact. The learning dimension achieved a score of 73.66, which is a satisfactory level. According to 95.6% of the students, RPA is advantageous for their profession and future work. 99.7% of the students are willing to recommend studying to other students. However, the final score of RPA’s maturity level is 71.6, which is still in progress, and it still needs to continuously promote the transformation of digital intelligence.
Analysis of English Classroom Interaction in Colleges and Universities Based on Student Behavioral Data
Authors: Wang Ruiping 
Published: April 2024

Abstract
With the advancement of the information age, the traditional teacher-led English classroom interaction in colleges and universities has made it challenging to meet the individualized needs of different students. Therefore, this paper takes the current classroom behavior data of college students as the basis, uses the K-means clustering algorithm and I-divergence measure to categorize, analyze, and study the student behavior data, and digs out the correlation between students’ classroom behavior data and teaching interaction. This paper takes all the teachers and students of English majors in college M as the research samples. It conducts experimental research in terms of teachers’ and students’ classroom speech rates, teachers’ and students’ questioning rates, and teachers’ and students’ use of instructional technology, etc. The 10 classes of English majors in college M do not have more than 50% of the students’ speech rate, except for class 2. Class 2 has the highest speech rate (61.64%) among students, while class 5 has the lowest rate (7.5%). From the point of view of active questioning rate, 10 classes had very low SQ ≤ 0.02, and even in classes 1, 3, 4, 5, and 6, there was a situation where students’ active questioning rate was zero. After analyzing the student behavior data in some classes, it was found that the mean score of English test students in the experimental group before and after the test increased by 4.687, corresponding to a significance Sig value of 0.000<0.05, which reaches the level of significance. The analysis of classroom behavior data reveals that enhancing the ratio of teacher-student interaction activities can improve students’ English scores.
Research on objective evaluation methods of labor education teaching for college students in higher education
Authors: Wang Xin , Zhou Wenjie 
Published: April 2024

Abstract
Labor education in colleges and universities in the new era is the fundamental task of implementing the principle of establishing morality and educating people, as well as an essential hand in cultivating college students with all-round development of morality, intelligence, physicality, aesthetics, and labor. This paper focuses on the objective evaluation method of college students’ labor education to conduct research. Using the improved binary tree support vector machine multi-class classification algorithm, an evaluation model for college labor education based on a binary tree support vector machine has been constructed, and an evaluation system for labor education has been developed. The results show that the majors that have compulsory labor education courses, elective labor education courses, and have added labor education modules in their major courses are all art and sports, accounting for more than 50% on average. The percentages of liberal arts, science, economics and management, art and sports, medicine and science, and agriculture, which did not offer labor education-related courses, were 26.35%, 22.16%, 19.91%, 13.59%, 11.03%, and 13.19%, respectively. It is evident that labor education courses are not distributed equally in colleges and universities, and there are still some majors that do not offer labor education courses. In terms of labor education, most of the labor education through Civics and Political Science classes is provided to students. Managers are those who choose the most specialized courses. Students also tend to participate in bicultural education and social practice activities, accounting for 29.02% and 43.01%, respectively. It shows that the algorithm in this paper can objectively and effectively evaluate labor education in colleges and universities and identify the deficiencies in education.
Research on Accounting Quality Management of Enterprises under Financial Sharing Mode
Authors: Yu Donggen , Jia Dongxiao 
Published: April 2024

Abstract
With the deep integration of the global economy and the continuous individuality of technology, the complexity of enterprise operation and management is increasing, which makes the traditional accounting and accounting methods difficult to meet the needs of modern enterprises. This paper proposes an enterprise accounting accounting method applying information computing technology, which applies association rules to generate frequent item sets of data for the accounting data under the financial sharing mode and obtains the optimal rules through pruning. Based on the time series prediction of the enterprise’s financial data, changes are made. Taking the actual enterprise case study, the association rules involved in accounting are more accurate, the calculation results are basically the same as the actual value, and the final cost accounting value is only nearly 2 million yuan different from the actual value, the accounting error is only 0.02%. Furthermore, the association rule algorithm has a significant impact on improving the efficiency of accounting work. The service time of counter personnel can be reduced by 30% after Bank P applies the management rules to accounting management. The average execution time of the initial ticket examination operation has been accelerated from 10.53 seconds to 5.42 seconds. The association rule algorithm can effectively improve the precision of enterprise accounting and the efficiency of accounting personnel, while also identifying existing problems in the current management system.
Development Status, Comparison and Inspiration of Integrated Circuit Virtual Simulation Teaching at Home and Abroad
Authors: Hu Peipei 
Published: April 2024

Abstract
The cultivation of higher vocational integrated circuit technology professionals requires a complete practical training teaching system and practical training conditions, especially integrated circuit layout design, production process, packaging and testing and other process personnel training needs to be completed in a real work scenario, the virtual simulation training is just for the integrated circuit professional education and teaching to provide support. This paper takes CNKI, SCI and EI databases as the research data source. It uses word frequency analysis and co-word analysis in statistical analysis to quantitatively analyze the development status of virtual simulation teaching of integrated circuits at home and abroad. And combined with the clustering analysis algorithm to explore the integration results of the keywords of integrated circuit virtual simulation teaching at home and overseas, and give the path to improve the high-quality development of integrated circuit virtual simulation teaching. It has been found that the domestic research related to IC virtual simulation teaching has improved by 80 times during 2000–2022, but the foreign research is 1.642 times higher than the domestic one. In addition, domestic and foreign countries are mainly focused on virtual simulation and innovative practice, respectively, and their word frequencies have reached 465 and 596 times respectively. Higher vocational colleges and universities need to optimize the teaching mode of industry-teaching integration, use virtual simulation technology to help students understand the knowledge related to integrated circuits, and provide technical support for improving the quality of talent training.
Virtual Reality (VR) Innovative Communication Strategies for Chinese Traditional Arts in the Digital Age
Authors: Zheng Rongling 
Published: April 2024

Abstract
Chinese traditional art has shown an inevitable decline in dissemination in the digital era. This paper utilizes virtual reality technology to enhance the experience of conventional art and LOD technology to manage the specifics of the virtual interactive scene. To display complex virtual terrain accurately, the data is reorganized with the help of a quadtree. The reconstructed art scene creates a virtual hand shape based on the structural characteristics of the human hand and the data glove. The kernel correlation filtering algorithm is utilized to construct the real-time tracking of the virtual hand. The research object in Chinese traditional art is the stele forest in practice. The results of virtual reality experience show the total score of interaction experience 88.159∊(80,100). The VR technology-based calligraphy experience in the stele forest received high user ratings, and the audience recognized the narrative experience. An in-depth study found that the subtitle grouping in the virtual interaction scene significantly affected the immersion of the art experience (P=0.019<0.05, F=4.562). Virtual reality technology provides a communication channel for digitizing traditional Chinese art, and the study contributes to the proposal of communication strategies.
An ecological music education model based on deep learning: a blend of tradition and innovation
Authors: Zheng Weixin 
Published: April 2024

Abstract
With the improvement of the status of music education, the reform of music education mode is imminent. The intersection of tradition and innovation is achieved by combining ecological education and deep learning concepts to construct an environmental music education model based on the traditional music education model. The research mainly focuses on intelligent music generation and its auxiliary effects in ecological music education. The steps are to complete the intelligent generation of multi-track music through the HL-MTMG model by combining the blended learning module and reward feedback module after defining the problems of music rhythm and melody problems. In analyzing the efficacy of ecological music education based on deep learning, it was concluded that the satisfaction rate of the generated music samples ranged from 66% to 72%, and the average score of students’ satisfaction with the classroom teaching of the ecological music teaching model based on deep learning ranged from 3.313 to 4.253. The environmental music education model through deep learning can significantly enhance the impact of music education and encourage students’ interest in music learning.
On a New Generalization of Pell Hybrid Numbers
Authors: Bród Dorota , Szynal-Liana Anetta , Włoch Iwona 
Published: April 2024

Abstract
In this paper, we define and study a new one-parameter generalization of the Pell hybrid numbers. Based on the definition of r-Pell numbers, we define the r-Pell hybrid numbers. We give their properties: character, Binet formula, summation formula, and generating function. Moreover, we present Catalan, Cassini, d’Ocagne, and Vajda type identities for the r-Pell hybrid numbers.
The Development of Standard Designs of Primary School Buildings in Lithuania During the 1920s and 1930s
Authors: Vilkončius Evaldas 
Published: April 2024

Summary
This article analyses the development of standard designs of primary school buildings in Lithuania during the 1920s and 1930s. This process aimed to create simple and comfortable standard school buildings and provide them to the primary schools operating in the country. The article presents the development of standard designs that took place at that time, explaining the circumstances of their emergence, and comparing the main designs of such buildings developed at that time. To reveal this process as best as possible, the influence of the then Ministry of Education of Lithuania, local former Lithuanian county municipalities, and various architectural specialists in the standardisation of buildings for primary schools and the development of standard designs are presented and analysed. This aims to introduce the readers to the still little-known process that took place in the architecture of Lithuania during the 1920s and 1930s.
Romanian Art History During the 1950s as a Form of Social History of Art
Authors: Modreanu Roxana 
Published: April 2024

Summary
The Romanian Workers’ Party – the political party that led Romania from 1947 until 1965 – need for legitimisation led to the rewriting of history in a way that the history of Romania was presented as a linear progression finally leading to communism. In art history, art also became a linear phenomenon, progressively advancing towards Socialist Realism.
The tactics of constructing the new narrative in art history during the 1950s and the beginning of the 1960s can be read as a form of the social history of art. Although the methodology could have led to remarkable results, ethical boundaries were violated: only some historical episodes and moments from artists’ biographies were selected.
Within this context, this study investigates whether papers and monographs about Romanian painters active in the second half of the 19th century and the beginning of the 20th century can be read as a form of social history of art.