bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the intelligent teaching model of integrated English reading and writing classrooms in colleges and universities based on big data technology
Authors: Xu Hui 
Published: September 2023

Abstract
Because of the current relatively lagging writing ability and the current situation of English teaching that separates reading and writing, input and output, this paper proposes the reading and writing integration model to improve English teaching. This paper first introduces the definition of mutual information and interaction information, explains the information theory feature selection method of big data relationship mining technology, and uses the feature selection method to select the features related to the target variable, further derives the hidden structural information between the features, mines the correlation between the target variable and the features, and derives their causal relationship through correlation. Then the specific measures of reading and writing integration are elaborated, including developing students’ sense of language through reading and imitating writing. Finally, the effectiveness of this method is evaluated in terms of learning confidence, achievement and writing level. In terms of English achievement, the mean score after the experiment was 95.44, which was higher than the previous mean score of 82.78. In terms of writing ability, 76.5% of the students said that reading improved the quality of writing, and 65.4% said that the integrated teaching of reading and writing made their writing faster. The integrated teaching mode of reading and writing has improved students’ English proficiency and interest in learning.
Corporate performance management model based on CPS evaluation system
Authors: Wu Ji 
Published: September 2023

Abstract
This paper proposes an enterprise performance management model based on the CPS evaluation system to improve the efficiency and efficiency of enterprises. First, this paper explains the connotation of the CPS evaluation system and constructs an enterprise performance evaluation model. The index data is normalized, and the index weights are calculated using Delphi and entropy methodsthod so that the indexes are scored comprehensively. Then the enterprise performance management system was established, and the assessment criteria for each department of the enterprise, including the finance and production departments, were established. Finally, the management effect of this performance management model was analyzed in terms of enterprise profit and return rate. In terms of enterprise profit, the enterprise’s net profit was between 700,000 and 800,000 in the five months before the adoption of this method, while the profit of the enterprise was basically above 800,000 and increased month by month after the adoption of this system. In terms of payback rate, the payback rate fluctuated around 60% before the adoption of the evaluation system, but after the adoption, the payback rate of the enterprise was above 70% and showed an increasing trend. The enterprise performance management mode based on the CPS evaluation system can improve the efficiency of the enterprise, which proves the reliability of the method of this paper.
Comparative strategies of domestic and foreign ideological and political education in universities in the context of big data
Authors: Zhang Rongyun 
Published: September 2023

Abstract
The comparison and study of ideological and political education methods in Chinese and American universities can enable us to improve ideological and political education methods further. In this paper, we use the global optimization performance of the genetic algorithm to overcome the disadvantage that the K-means algorithm is sensitive to initial values and tends to converge only to local optimum points and propose an improved K-means algorithm based on the genetic algorithm. Meanwhile, the combination with the simulated annealing algorithm eliminates the problem that the K-means algorithm is sensitive to isolated points, makes the algorithm less susceptible to extreme data, and improves the analysis ability of the algorithm. In analyzing the content of ideological and political education in China and the United States, the main contents of ideological and political education in American colleges and universities include civic education, patriotic education and religious education. The first content of ideological and political education in Chinese schools is “mental health education”, accounting for 94.44%, and the second is “moral quality education”, accounting for 75.97%. The second is “ideal and belief education” and “education on life and values”, accounting for 73.23% and 72.70%, respectively. Therefore, American colleges and universities cultivate responsible citizens with the American spirit, while Chinese Civic Education cultivates socialist builders who serve the people.
Research on the innovation of ideological and political education for college students based on the Civic and Political Science Cloud Education Platform
Authors: Luo Siyi , Alia Noryati Binti 
Published: September 2023

Abstract
Innovative ideological and political education for college students is to help better students improve their ideological quality and political literacy. In this paper, under the background of big data, the Civic and Political Cloud Education Platform is constructed using big data technology, which is mainly composed of four main parts: model layer, view layer, control layer, and basic services. Student behavior data is collected and analyzed through a collaborative filtering recommendation algorithm under big data collection and analysis technology, and performance simulation analysis is conducted for the Civic and Political Science Cloud Education Platform. From the performance analysis, when the number of concurrent users of the Civic Education Cloud Platform is 80-120, the average transaction processing per second is stable at 10.5 s. From the practicality, the Civic Education Cloud Platform built by big data can effectively explore the value of Civic Education teaching resources. This shows that the Civic and Political Science cloud education platform is an effective way to innovate and develop the ideological and political education of college students, and through this platform, the ideological quality and political literacy of college students can be effectively improved.
Improving online ideological and political precision education in universities based on knowledge mapping
Authors: Liu Ning 
Published: September 2023

Abstract
Empowering precision innovation through big data to improve the effectiveness of ideological and political education in colleges and universities can effectively promote cultivating the new generation of the times. Based on learners’ learning behaviors and quantified learning behavior indicators, this paper proposes a three-branch division model based on a cognitive level to reduce the “Matthew effect” of collaborative filtering algorithms in path recommendation and improve the cognitive level of online learners. Based on the three-branch decision theory, we select the decision with the highest expected utility as the final decision and recommend the learning content suitable for the learners’ development. The analysis of the functional requirements of the personalized learning recommendation system based on knowledge mapping, the overall structure diagram of the system, and the construction process of each component module are proposed. By analyzing the influence of ideological and political education on college students, about 80% of college students generally think that ideological and political education has improved political character, strengthened ideals and beliefs, enhanced national sentiment, standardized speech and behavior, improved comprehensive literacy, and enriched after-school knowledge. More than 80% of students, teachers, and leaders are satisfied with the personalized recommendation model proposed in this paper, and less than 10% are dissatisfied. Therefore, big data technology can help improve students’ Civics learning effect and has strong applicability.
A multi-objective optimization algorithm based on the identification of risk spillover intensity measurement in Chinese financial markets
Authors: Mao Rui , Liang Fuxiang , Wang Jingjing 
Published: September 2023

Abstract
Identifying the intensity of risk spillover in China’s financial market can provide an important empirical basis and information reference for monitoring and preventing financial risks. This paper uses a multi-objective application of particle swarm optimization algorithm under a multi-objective optimization algorithm to induce the MOPSO algorithm. The algorithm identifies and measures the intensity of risk spillover in China’s financial market in two aspects, including the risk spillover from policy instability to the stock market and the two-way risk spillover between the financial industry and the real estate industry. Regarding policy instability, the risk spillover intensities of downside fiscal policy, monetary policy, trade policy, and foreign exchange policy are 14.83%, 53.88%, 7.54%, and 31.06%, respectively. Regarding the two-way risk spillover intensity, the average risk spillover intensity of real estate to finance is 70.28%, which is 5.57 percentage points higher than that of finance. This indicates that the multi-objective optimization algorithm can identify and measure the risk spillover intensity of China’s financial market, providing data support and information reference for preventing financial risks.
A Study on the Multidimensional Expression Form of Ancient Chinese Teaching in Universities Based on Multidimensional Analysis Model
Authors: Yu Lu 
Published: September 2023

Abstract
With the continuous development of computer technology, the teaching of ancient Chinese has realized a quantitative and statistical research path for a large-scale corpus. In this paper, based on a multidimensional analysis model, six disciplines in the humanities domain (Chinese literature, history, philosophy) and social sciences domain (economics, sociology, law) of ancient Chinese were selected as dimensions, and 111 linguistic features of ancient Chinese in the corpus were factor analyzed. Multivariate ANOVA and post hoc tests were conducted on the discourse dimension scores of different disciplinary domains, and qualitative analyses were conducted in conjunction with the linguistic features in the specific corpus to further verify the linguistic domain coefficient of variation of ancient Chinese. The results of the study show that the results of the Levenes test for homogeneity of variance in the teaching of ancient Chinese in a single dimension are all p < 0.0001, while there are highly significant differences between the historical and philosophical domain features in the humanities (p = 0.001 ≤ 0.01), and extremely significant differences with the other four disciplines. The results of the multidimensional expression form of ancient Chinese teaching based on the multidimensional analysis method proposed in this paper effectively advance the advancement of ancient Chinese teaching and enable students to learn Chinese culture from other dimensions while learning ancient Chinese.
Exploring the Multiple Meanings of Ice and Snow Sports Culture Construction in Chinese Universities Based on Fuzzy Algorithm
Authors: Wang Zhen 
Published: September 2023

Abstract
In the Internet era, sports have been given a good opportunity for development, and the increase in sports activities has also led to the continuous improvement of national physical quality. This paper uses a fuzzy algorithm to decompose test cases’ reusability into functionality and portability. Then, we use hierarchical analysis to stratify the required reusability metrics into sub-characteristics and different attributes under sub-characteristics to obtain the weight ratio of each layer of reusability attributes. Then the sub-characteristic metrics are reasonably quantified by numbers to realize the quantitative evaluation of test case functionality and portability and turn the abstract concepts into intuitive numbers to provide users with reference. Finally, with the core of promoting the development of ice and snow sports programs in Chinese colleges and universities, the construction of ice and snow sports on campuses is strengthened according to the advantageous conditions in the region to improve the physical and mental quality of youth and the simultaneous development of science and culture. Using the fuzzy algorithm to analyze the importance of ice and snow sports by school leaders, it is concluded that 68.8% of the base schools do not have relevant management methods, and 56.3% do not have relevant rules and regulations. This study further promotes the reform and development of ice and snow sports in colleges and universities nationwide and also provides a theoretical basis for strengthening the training of ice and snow sports talents nationwide.
The construction of hotel information management mode under the trend of low carbon tourism
Authors: Tong Jun , Liu Zaiying 
Published: September 2023

Abstract
The management of hotels in the context of low-carbon tourism tends to be more and more information-based, and there is an urgent need to build a management model in line with information technology. In this paper, a hotel informatization management system considering customer satisfaction is established, the system objectives are designed based on the demand analysis of travelers, and the functions of subsystems are designed based on the information management activities of the system. For the analysis module of customer satisfaction, the satisfaction index system of hotel travelers is constructed based on the ACSI model, and the satisfaction index is analyzed using the PLSR method. For the database structure of the system, the system tables were divided into several interrelated information tables. In the system test, this system’s read/write rate improved by 8.26% compared with the Green Cloud system and 7.53% compared with the Golden Swan system. Regarding the fit of satisfaction analysis, this system improved by 5.53%, 18.90%, 12.29%, and 1.33% over the quadratic graph method, the Carnot model, the CCSI model, and the ECSI model, respectively. Regarding the optimization rate of services, this system improves by 8.03% compared to the Opera system. The information-based management system helps improve the hotel’s service quality and management level and also provides a solution for operators to develop users in the hotel industry.
Research on energy consumption analysis of air conditioning and refrigeration equipment based on perceptron model
Authors: Zhang Youtong 
Published: September 2023

Abstract
This paper mainly studies the energy consumption of air conditioning and refrigeration system from the perspective of the dynamic operation of air conditioning systems and selects the energy consumption of a chiller system, cooling tower system, chilled water pump system and fan coil system, which affect the energy consumption of air conditioning system, as model variables. An integrated learning method based on a multilayer perceptron is proposed to integrate spatial features with temporal features, and a spatio-temporal prediction model for air conditioning energy consumption analysis is established under the Seq2Seq framework, and then the input curves of the four variables with load change under the optimal operation of the air conditioning system under dynamic load are derived. The results show that the deviation between the simulated value and the measured, calculated value of the energy consumption analysis model of air conditioning and refrigeration equipment based on the multilayer perceptron is within 5%, which can effectively and accurately predict and reduce air conditioning energy consumption by 15% to 20%. The maximum energy-saving efficiency can reach 30% when the air conditioning system is in optimal operation under dynamic load, and the energy-saving effect of the chiller, chilled water pump and cooling water pump is relatively significant. The research results of this paper have a certain reference value for reducing the energy consumption of air conditioning systems in practice.
Research on the design of interactive intelligent toy art experience based on multimodal sensory
Authors: Luo Cong 
Published: September 2023

Abstract
Although many kinds of intelligent toys, interactive toys that can mobilize children’s sensory experience in many aspects and cultivate their creative thinking are still scarce. In this paper, interactive experience elements are built based on virtual reality technology, image recognition technology, human-computer interaction theory, and ergonomics theory. A brain interaction network based on multimodal sensory modulation is constructed to allow intelligent toys to perceive their surroundings effectively. And the dynamic causal model (DCM) is proposed to infer the connection strength and direction of neural activities among pre-defined cortical regions of the brain. The results showed that the classification accuracy of noisy audiovisual (AVd) modality in the BA18 region was 87.87% significantly higher than that of the STS region (81.41%). The average classification accuracy of the mono-visual noise-added (Vd) modality in the BA18 ROI was 79.40%, which was also significantly higher than that of the STS ROI at 65.12%. It indicates that the interactive design based on multimodal senses can effectively stimulate children’s brain interest areas, which makes children experience better and communicate more interactions. The research results of this paper provide new perspectives and have important implications for the application of interactive intelligence to toy art.
ECOC-based integrated learning method for fault diagnosis in nuclear power plants
Authors: Sheng Guimin , Mu Yu , Zhang Boyang 
Published: September 2023

Abstract
The fault diagnosis system of nuclear power plants plays an important role in ensuring the safety and economy of nuclear power plant operations. This paper first analyzes typical faults of nuclear power plants and their phenomena, and fault samples are obtained. A comprehensive study of the structure of the nuclear power plant system, its working mode and the association between each subsystem is carried out to analyze the monitoring parameters and fault characteristics and establish the fault data set. Secondly, an IFWA (Improved Fireworks Algorithm - Integrated Learning) algorithm is proposed to assess the severity of faults in the first circuit of a nuclear power plant. Finally, the fault diagnosis module is divided into three units according to the functional logic, i.e., condition monitoring unit, fault identification unit, and fault severity assessment unit. The results show that the diagnostic accuracy of the IFWA algorithm is 94.25% for SGTR in the single-fault diagnosis experiment and 96.25% for SGTR-LOCA in the multiple-fault diagnosis experiment. It shows that the IFWA algorithm proposed in this paper has the optimal performance capability when applied to nuclear power plant fault diagnosis and effectively assists managers in diagnosing faults and giving maintenance recommendations.
Self-efficacy-based change in educational administration style and public management model
Authors: Li Qiao , Zhang Dawei 
Published: September 2023

Abstract
At present, the public management model is relatively backward, and the way of education administration needs urgent change. This paper explores the characteristics of the higher education administrative body operation mode in different periods and analyzes and summarizes the problems of the current educational administrative style. In response to these problems, an educational administrative management style based on self-efficacy is proposed, and the mathematical expression of three characteristic dimensions of self-efficacy is established through the modeling study of the factors influencing self-efficacy. The impact of characteristic self-efficacy dimensions on the efficiency and fairness of educational administration was analyzed as a strategy to propose management model changes. The impact factors of self-efficacy magnitude on input-output efficiency reached 0.43, self-efficacy breadth on problem-solving efficiency reached 0.40, and self-efficacy intensity on planning goal completion efficiency reached 0.27. The impact factors of the three characteristic dimensions of self-efficacy on educational equity reached 0.31, 0.35, and 0.34. This study provides an effective reference path for educational administration. This study provides an effective reference path for optimizing educational administration and helps promote the scientific construction of the public management model.
A Study on the Impact of Cloud Computing Performance Efficiency on Task Resource Scheduling
Authors: Lin Jianling 
Published: September 2023

Abstract
In this paper, the inertia weighting strategy of the particle swarm is improved by using the properties of periodicity and fixed upper and lower bounds of sinusoidal function to model the task scheduling problem in cloud computing as a mathematical problem, and the improved particle swarm algorithm is discretized, and the improved discrete particle swarm algorithm is applied to task scheduling by corresponding encoding method. The task scheduling algorithm (PSOACO) that fuses the fast convergence and small computational power of the particle swarm algorithm with the global exploration capability of the ant colony algorithm for scheduling tasks is proposed. Two test cases, PageRank and wordcount, are selected to measure the performance of the PSO-ACO algorithm. In the performance comparison running the PageRank test case, the PSO-ACO algorithm obtains a performance speedup ratio of 3.8 times that of the native Domino when 50,000 pages are added. In the execution time comparison for the wordcount test case with an additional data set, the PSO-ACO algorithm is nearly 2.8 times faster than the native Domino when adding 1GB of data. Thus, the fusion algorithm reduces the task completion time and achieves a balance between the algorithm’s computational effort and the scheduling’s convergence performance.
The construction of an intelligent English grading teaching model based on partial least squares method
Authors: Qi Yuanyuan 
Published: September 2023

Abstract
Building an intelligent English grading teaching model helps to improve English teaching and students’ English performance in colleges and universities. In this paper, the PLS-ELM model is constructed from partial least squares as the base algorithm, the concept of an extreme learning machine is introduced, and the principal component score of the PLS algorithm is used to the number of neuron nodes of ELM, and then the adjustment of weights is realized. The principal components of PLS were used to analyze the selection of independent variables for the English-graded teaching model. The effectiveness of the English-graded teaching model was verified by comparing students’ satisfaction with teaching evaluation and performance after teaching implementation. Regarding student satisfaction, the percentages of those evaluated as very satisfied, generally satisfied, and dissatisfied were 53.71%, 32.86%, and 13.43%, respectively. Regarding students’ performance, the average score of students in the experimental group was 88.6, 14.62% higher than the English performance of the control group. This shows that the English grading teaching mode can improve students’ English learning performance, enhancing students’ own quality and professional ability, improving university English teaching, and cultivating students’ English application ability.