bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measurement of Leakage Current in Wet and Polluted Conditions Using Different Sensing Electrodes
Authors: Šárpataky Ľuboš , Dolník Bystrík 
Published: December 2023

Abstract
Insulators, as the main insulating element of transmission lines, are exposed to various stresses, which affect the operation and thus the reliability of electricity supply. To improve the reliability of insulators, it is necessary to monitor their condition. Thanks to the development of computer technology, it is possible to process a large amount of data, which popularizes the possibility of diagnostics online. Factors that affect reliability, failure rate, and losses the most, are pollution and humidity. Our research is focused on monitoring and evaluating the applicability of various sensing electrodes for measuring leakage current on glass insulators. Relative humidity and pollution levels changes can give us a clear view of the used measuring method and how different sensing electrodes can affect the value of leakage current.
Spark-Based Digital Factory Design
Authors: Pölöskei István 
Published: December 2023

Abstract
Big data processing often uses the paradigm of parallelism by computing directly on top of the distributed data storage. The existing big data workflows unify the data processing practices to utilize the cloud’s native computational potentials to offer advanced machine learning and BI capabilities. Spark is an open-source massively parallel in-memory data processing framework, the current state-of-the-art. The primary approach is to break down the job into granular-level executed tasks, enabling parallelization. In the discussed case study, through IoT – cloud solutions, the plant data can be converted into an analyzable form to let the farther machine learning modules produce added value. To maximize the efficiency of the processing and accumulation, cloud-based components are introduced. Based on the data insights, the appropriate operative actions can be taken. The cost and performance optimization methods were also discussed in the study. Through achieving higher degree of digitalization, the control over the production increased.
Hydraulic Turbine Modelling Including a Fuzzy Model of Efficiency
Authors: Perduková Daniela , Fedor Pavol , Fedor Marek 
Published: December 2023

AbstractThe hydraulic turbine is considered as a heart of the hydropower plant because of its important function in the whole process of electrical energy production. Turbine´s efficiency calculation is analytically demanding and dependent on parameters that are often obtained only by a theoretical estimation. Therefore, using its accurate model, which takes into account its efficiency, is necessary to achieve realistic and relevant results. The article briefly surveys current knowledge and methods of designing the hydraulic turbine model. The new idea consists in that a fuzzy system was used to create turbine´s efficiency model based on a measured operating data of the turbine flow rate and its mechanical speed without any need of knowing exactly the turbine parameters. Such a model can be used in the design and development process of an optimal energy control of a hydraulic turbine, as well as in the effective process of determination the actual turbine’s wear rate. The achieved results were obtained using the computational tools of the Fuzzy Toolbox in the MATLAB.
Initial Analysis of Multi Active Bridge Converter
Authors: Marcinek Adrián , Pástor Marek 
Published: December 2023

AbstractThis paper introduces a design of a modular multiport converter, employing active bridges. The design incorporates a modular structure, and the paper begins by conducting steady state analyses to evaluate the converter’s characteristics. Subsequently, a RMS current equation, average current equation and power distribution equation are derived. From these equations is derived equation for delay of specific port. Lastly, a multi active bridge described in this way is verified by simulation.
Strategies for Safeguarding Intangible Cultural Heritage of Yi Ethnic Groups in the Context of Informatization and Its Practice in Regional Culture
Authors: Zhang Dehua , Wuda Pan 
Published: December 2023

Abstract
The digitization of intangible cultural heritage provides the basis for its protection and inheritance. In this paper, we extracted the classes and interrelationships corresponding to each element for the content of Yi Intangible Cultural Heritage, constructed the data model and accomplished the relationship abstraction of different classes. Based on the structure of different data classes, the correlation between spatial change and non-heritage status is explored. The data model is proposed to cluster non-heritage data based on SWC-WMD distance, which improves the similarity calculation based on WMD distance. The association analysis of non-heritage item classes was performed using Yi folk dance as an example, and the overall non-heritage data was analyzed by clustering. In Yi folk dance, the association formed a network correlation graph with N2, N3, and N12 as the three main centers, in which the dance class items associated with N2, N3, and N12 were 9, 9, and 8, respectively. Mining out the relationships among NH items helps to better the overall NH protection.
Analysis of the Impact of Curriculum Civics on Students’ Quality Cultivation Based on Bayesian Networks
Authors: Zhang Lili 
Published: December 2023

Abstract
This paper first analyzes the Bayesian network model based on probabilistic reasoning to study and explore the random phenomenon law of curriculum thinking. Secondly, probability theory and graph theory are utilized to deal with uncertain information and reduce the meta-multiplicity of the analysis of uncertain knowledge. Then, the Bayesian network structure learning problem is analyzed, and a constraint-based structure learning method is proposed to score students’ qualities by a given scoring function, and using a search algorithm, the best scoring network structure is searched. Finally, in order to analyze the influence of the Civics curriculum on the quality of students in college A, we should analyze the impact of the curriculum. The results show that from the innovative quality of students, the distribution density of innovative habit and innovative ability scores in the interval of 70~75 is (0.02, 0.035), and the distribution density of innovative consciousness scores in the interval of 70~86.25 is (0.005, 0.07). The data show that curriculum Civics can effectively promote the cultivation of innovative talents and the construction of an innovative country by internalizing the quality of innovation in the heart and externalizing it in the form of cultivating students’ innovative habits, improving their innovative consciousness and enhancing their innovative ability.
Optimization of Smart Campus Cybersecurity and Student Privacy Protection Paths Based on Markov Models
Authors: Jianhua Du 
Published: December 2023

Abstract
This paper starts with the application of hyper-convergence technology, builds the framework of a university smart campus based on it, and gives the framework description of the smart campus. In order to analyze the network security for the smart campus, the Markov model is used as the basis combined with the reinforced Q learning algorithm for network node security detection, and a specific simulation analysis is given. The encryption performance and defense performance of the elliptic curve cryptosystem are analyzed through the elliptic curve cryptosystem to formulate the encryption scheme for students’ private data in the smart campus. The results indicate that the Markov model node detection combined with reinforcement Q-learning in this paper takes a maximum time of about 5.75s when the network node size reaches 150. When the number of nodes in the smart campus network is 30, under brute force attack, the whole network is captured only when the number of malicious nodes increases to more than 22, while under random attack, it takes as many as 30 malicious nodes to join before the network completely falls. This illustrates that the use of the Markov model can be realized to analyze the network security of the smart campus and that student privacy protection needs to further improve the awareness of student data privacy protection and develop the habit of assessing the privacy risk beforehand in their daily network behavior.
An Interactive Approach to an Immersive Multimedia-Based Online Course in Vocal Music
Authors: Guo Shanyu 
Published: December 2023

Abstract
Since the traditional vocal music course cannot meet the learning objectives of current music majors, this paper explores the reform of vocal music courses by combining modern multimedia technology. First, the teaching experience brought by immersive multimedia technology is explored, and based on the spatial and temporal features of the interactive behavior of the vocal music online course are extracted by the convolutional neural network, and multimodal fusion is carried out by combining linguistic features. Then, the GCN-LSTM network is used to model its spatial structure information and long temporal dependency, based on the joint learning of multimodal features, and then identify the interactive behavior. Finally, after constructing the teacher-student features, the extraction effect, recognition effect, and interactivity results of the behavioral features of the vocal online course are analyzed. The results show that the overall teacher-student behavioral feature extraction is above 0.7, except for “writing” with an accuracy of 0.76, “speaking”, and “listening”. The recognition effect of the overall teacher’s behaviors is more than 0.73, and in the range of 100s~250s, students “raise their hands” frequently and interact more. The students “raised their hands” frequently in the 100s~250s and interacted with each other more frequently.
A Practical Study of Basketball Teaching Reform in Colleges and Universities Based on Big Data
Authors: Sheng Chengjian , Lian Chenxin , Pang Haolin 
Published: December 2023

Abstract
In this paper, the human body posture estimation algorithm is used to locate the key points of the human body in the RGB screen, and two human body multi-objective algorithms are used to predict the posture trajectory, and they can overcome the influence of the errors contained in the information recorded by the sensors to a certain extent. Secondly, the spatio-temporal graph convolutional neural network is used to identify human behavior and extract behavioral action features, and through the analysis of the action features, we understand the basketball skill level of the students and put forward the reform strategy of college basketball teaching. Sixty students from the basketball minor class at University Q’s College of Physical Education were selected as research subjects for teaching practice. The results show that the average scores of the students in spot-up shooting, half-court folding dribbling and marching one-handed over-the-shoulder shooting after the reform are higher than those before the reform by 1.80, 1.08, and 1.85, which indicates that the reform of basketball teaching based on big data can improve the students’ interest in learning and their training scores, and enhance the students’ basketball skill level.
Research on the Innovation of Talent Cultivation Mode and Industry-Education Integration Mechanism of College Education in the Internet Era
Authors: Wang Yanling 
Published: December 2023

Abstract
In this paper, in order to obtain a better classification evaluation effect, a feedback connection model is added to the convolutional neural network to establish the evaluation model of the integration of industry and education in colleges and universities based on FCNN. Compare the MSE loss values of the traditional BP neural network model and the FCNN model. Indicator system construction, with the help of the accuracy of the convolutional neural network, to carry out the whole process of evaluation around the indicators, weights, and the quality of the implementation results. The data of students’ micro-expression concentration recognition test is used as the evaluation data of students’ project participation, comparing the recognition rate of the participation evaluation system proposed in this paper and the traditional participation evaluation system to complete the quality evaluation of the talent cultivation model of college education. Analyze the data on the graduation rates of college graduates to determine the effectiveness of the university’s integration of college education. The analysis shows that in 2022, the professional matching employment rate of graduates was 86.28%, which reflects the high efficiency of the university’s industry-teaching integration on the cultivation of professional and applied talents, and the mechanism of industry-teaching integration is well affiliated.
Digital Analysis of Logistics and Supply Chain Management Innovation of E-commerce Enterprises in Green Economy
Authors: Zhuang Xueyan 
Published: December 2023

Abstract
This paper centers on the logistics and supply chain management of e-commerce enterprises, studies the development mode of e-commerce logistics as well as the logistics process, and constructs a collaborative innovation model of e-commerce logistics integration based on supply chain management. Through the synergistic composite system in the role of management activities, the harmonious coexistence between the various components of the subsystem order parameter in order to achieve the overall effect of the system. The dynamic evolution process of consumers, e-commerce platforms and logistics enterprises is simulated and analyzed, and the optimal decision-making under the integrated collaborative innovation mode is studied. The results show that under the platform warehousing + distribution integration synergy (SP) mode, the double marginal effect is 0.865, and both e-commerce platform and logistics enterprises reach a steady state at 0.723. The purpose of this paper is to propose innovative supply chain management and logistics warehousing solutions that can achieve cross-border e-commerce logistics integration based on supply chain management.
Informatization Integration Strategy of Modern Popular Music Teaching and Traditional Music Culture in Colleges and Universities in the Era of Artificial Intelligence
Authors: Cai Jiandong 
Published: December 2023

Abstract
In this paper, a music teaching aid is constructed based on the automatic analysis technique of music elements. The auxiliary tool uses constant Q transform and note onset detection technology to process and recognize students’ input audio. The logical operation of music longitudinal structure and spectral structure and the logical conversion of beat and rhythmic time nodes are used to realize the integration of popular music and traditional music teaching informationization. Using two corpora of 22 kHz, the effect of teaching the fusion of musical elements of auxiliary tools was analyzed with the regular transformation of curves in the sound intensity envelope. The results showed that the peaks of the overlap between elements of popular music and traditional music appeared at 56.8 FPs, 148.9 FPs, and 343.7 FPs, respectively, corresponding to the peaks of 48.3 Hz, 59.4 Hz, and 51.6 Hz, respectively. The integration of traditional music culture into popular music teaching was successfully realized. This study effectively examined an effective method and strategy for integrating teaching, which has a positive impact on the promotion and development of traditional music culture.
Integration Development of Civic Education and Student Management in Colleges and Universities Based on Combining Data Fusion Model in the Context of Exquisite Parenting
Authors: Jing Yangjun 
Published: December 2023

Abstract
This paper focuses on the design of an educational early warning mechanism based on the fusion of ideological education and multi-featured data so as to manage the educational situation of students in colleges and universities efficiently and accurately. In this paper, the wavelet transform, discrete Fourier transform, and lag sequence analysis algorithms are used to effectively extract temporal features of students’ behaviors. PageRank and Hit’s algorithms are employed to extract features related to student concept maps. The emotional tendencies recognition interface provided by Tencent Cloud was used to obtain the emotional features of students’ speeches. Following this, a multi-feature fusion was performed to depict the students’ learning. A Hive-based data warehouse is used to integrate heterogeneous data from multiple sources. Finally, the education early warning model based on multi-feature data fusion is introduced, and the operation mechanism of early warning mechanism for ideological and political education in colleges and universities is established. To verify the effect of this paper’s model against other algorithms, this paper’s model achieves the optimal performance in the F1 score in negative samples, which is 0.91, followed by the TPA-LSTM algorithm, which is 0.88. Before the optimization of the early warning mechanism, the average per capita absenteeism of the students was 1.32 sessions, and the rate of disciplinary actions was 0.0291. At the end of the academic year, the average per capita absence rate decreases to 1.24 sessions, and the disciplinary action rate decreases to 0.0245.
Exploring the Role of Chinese Language and Literature in the Transmission of Traditional Culture by Combining the Method of Internet Text Analysis
Authors: Zhao Bi 
Published: December 2023

Abstract
This paper constructs a Bayesian network text recognition model based on the Bayesian network and explores the role of Chinese language literature in the dissemination of traditional culture by analyzing the embodiment of traditional culture in Chinese language literature network texts. The collection process of Chinese language and literature data in network text is analyzed from the perspective of textual data interaction. The information of node variables in a Bayesian network is used to determine the mutual relationship between Chinese language literature and traditional culture. The degree of interdependence between Chinese literature and traditional culture can be measured by combining mutual information. The results show that the correct rate of text recognition of the Bayesian text recognition model decreases slightly when the training samples are (100-300), but the correct rate always stays around 0.85, thus reflecting the effectiveness of the network recognition model in this paper. Chinese language literature has a certain role in the dissemination of traditional culture, which proves that Chinese language literature, as a carrier of traditional culture, can improve the dissemination speed of traditional culture. This study focuses on the integration of Chinese literature and traditional communication to improve a new vision.
The Construction of Chinese Language and Literature Resource Base in Colleges and Universities under the Construction of Cognitive Mapping
Authors: Zhao Bi 
Published: December 2023

Abstract
Keeping up with the development of the Internet era, it is imperative for colleges and universities to vigorously carry out the construction of a Chinese language and literature resource base to promote the healthy development of Chinese language and literature education. This paper starts with the construction of Chinese language literature resource base related technology, analyzes the basic model of the cognitive map and the construction of the cognitive map of Chinese language literature. The graph database technology is used to transform the data structure of the resource base and load data from the Chinese literature resource base. Based on the cognitive map and graph database, jointly constructed the Chinese language literature resource base and introduced the fuzzy C-mean integration algorithm to integrate the data resources for better access to Chinese language literature resources. To verify the effectiveness of the Chinese language and literature resource base constructed in this paper, it was tested and analyzed through practice. The results show that the overall average response time of the resource library in this paper is 718.50ms, which is 214.78ms lower than that of the online learning data platform, and the resource library developed in this paper can realize the loss in data sharing to be controlled to be less than 0.5MB. Utilizing the resource library to experiment with teaching Chinese language and literature, the average score of the experimental class increased from 88.96 to 95.23, which is an improvement of 6.27 points. The construction of the Chinese language and literature resource base under the cognitive mapping architecture can effectively enhance the common sharing of Chinese language and literature educational resources and prompt teachers to have richer teaching resources.
A Study on the Presentation and Communication Influence of Shaanxi Regional Culture in Public Service Advertisements from the Perspective of Social Network Analysis
Authors: Ma Ying 
Published: December 2023

Abstract
This paper describes the dynamic propagation process of the influence of public service advertisements (PSAs) using the information dissemination model and proposes a click probability function by modeling the click rate of advertisements, which is solved by a heuristic method. The EPR advertisement recommendation algorithm is selected to simulate the push process of the advertisement, and the experimental performance is analyzed. Analyze the presentation of Shaanxi regional culture and the network mobilization mechanism model of enterprise public service advertisement, predict and analyze the click rate of public service advertisement broadcasting, and emphasize the trust analysis of the audience. Variables such as the number of effective viewing of advertisements, the number of link clicks, the number of likes, and the amount of placement are selected to carry out descriptive analysis and correlation analysis of the effect of PSAs on Shaanxi regional culture. From the correlation coefficient matrix, it can be seen that the correlation coefficients between the explanatory variables take smaller values and are at the level below 0.11, and the number of likes has significant positive correlation coefficients with the indicators of advertisement effect at each stage. Thus it can be verified that the social attributes of advertisements play a positive role in the effect of advertisements.
Applying Time Series Analysis to Study the Development Trend and Influencing Factors of Ethnic Folk Dance
Authors: Ning Fen 
Published: December 2023

Abstract
In this paper, firstly, we propose to use time series analysis to observe the development and change process of social events, using the DF test and ADF test to eliminate the random autocorrelation in order to exclude the interference of white noise series. Secondly, the instantaneous frequency of non-smooth data is defined by analyzing the signal, and the constraints are modified from global constraints to local constraints. The Fourier-transformed eigenmode function is used to satisfy the four necessary conditions of completeness, orthogonality, localization, and adaptability. Finally, the development trend of ethnic folk dances and the change in communication dynamics are analyzed. The results show that the change of language on the spreading attitude of folk dance is 4.381, the change of custom on the spreading attitude is 5.943, the change of culture on the spreading attitude is 10.866, and the change of culture on the spreading attitude of folk dance is the largest, which shows that the development of folk dance away from the development of folk dance is not separated from the support of culture. The study will have a positive impact on passing on the distinctive art of ethnic folk dance and enriching Chinese traditional culture and art.