bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of Teaching Path of Artificial Intelligence Programming Course in the Context of New Engineering Construction
Authors: Wang Hongmei 
Published: September 2023

Abstract
Under the background of new engineering construction and the requirements of new curriculum reform, the problem of using big data technology to combine with the teaching of the “Artificial Intelligence Programming” course has caused many educational researchers to focus on the problem. In this paper, we propose data mining based on a clustering algorithm to build a teaching management system to optimize the teaching path of the Artificial Intelligence Programming course and build a web-based teaching management system based on clustering analysis and clustering validity index. Then the system structure and database are designed through the teaching system requirements, and the course teaching evaluation index system is built based on the teaching objectives of Artificial Intelligence Programming. Finally, the course’s teaching efficiency is analyzed using the teaching system with 20 weeks of teaching Artificial Intelligence Programming in one semester. The results show the clustering algorithm: the average course teaching efficiency is 39.95%, and the BP neural algorithm: the average course teaching efficiency is 34.71%. Genetic algorithm: the average course teaching efficiency is 33.96%. Based on the clustering algorithm teaching system improves the course teaching efficiency by 39.95% compared with the other two better performances, which is conducive to improving the quality of course teaching and teaching reform. This study provides better information technology support for new engineering construction and engineering teaching optimization and has reference guiding value for course teaching research.
Research on the current situation and development countermeasures of Chinese sports industry companies in the context of big data
Authors: Wu Xiaoyan , Wang Zhaoling 
Published: September 2023

Abstract
To solve various problems in the development of the sports industry and enhance the pulling effect of the sports industry on the national economy. This paper first analyzes the development scale, the number of institutions and the number of people in China’s sports industry at present through sports industry-related indicators. It further constructs an index system to evaluate the comprehensive strength of the regional sports industry. Secondly, the factors affecting the spatial differences in the comprehensive strength of the sports industry are studied, and the spatial effect test and industrial network centrality analysis are conducted. A geographically weighted regression (GWR) power-driven model was further established for empirical analysis. Finally, the estimated parameters of the model were spatially visualized, and the influence of each influencing factor on the comprehensive strength of the local sports industry was analyzed in depth. The results show that the adjusted goodness-of-fit of the GWR model proposed in this paper is 0.8929, which is closer to 1 than 0.8073 of the OLS regression model, indicating that the GWR model has a better fit. Meanwhile, the AICc value of the GWR model is 5.4177, which is also smaller than that of the OLS regression model. The GWR model has a significant positive contribution to the development of the sports industry in each region in terms of the explanatory variables proposed government input, scientific and technological innovation and talent pool, which are all important to enhance the economic benefits of the sports industry in each region.
Exploring the teaching practice of visual communication design in colleges and universities under the background of big data
Authors: Yuan Dezun , Wang Xinpeng 
Published: September 2023

Abstract
Under the digitalization of big data information, how to use big data technology to combine with visual communication design teaching has become a key topic of concern in the current education sector. Firstly, this paper proposes using a deep learning model based on big data technology for teaching practice research of visual communication design majors in colleges and universities and constructs a deep learning model by combining perceptron and bp neural algorithm for data mining property and accurate prediction. Secondly, the deep learning model is optimized by using the activation function and knowledge distillation function in response to the limitation problem of the deep learning model. Then the teaching evaluation data of visual communication design majors in colleges and universities are obtained through questionnaire survey work, and evaluation indexes are determined according to the evaluation data. Finally, students of visual design majors at Guizhou Vocational and Technical College were selected as research samples, and the practice performance of communication design majors was analyzed based on the deep learning model. The results showed that the deep learning model: from week 1 to week 20, the score improved from 52 to 88, which improved the score by 69.23%. The traditional method: from week 1 to week 20, the score improved from 52 to 80, improving the score by 53.84%. This study is conducive to promoting the healthy development of the visual communication profession and cultivating design talents that meet the needs of the information age and is of great significance to the development of the visual communication profession in China.
Big data-based output-oriented teaching competency development for mathematics teacher trainees
Authors: Pan Jian 
Published: September 2023

Abstract
The purpose of exploring output-oriented ways to develop the teaching ability of teacher-training students in mathematics is to help better them improve their teaching ability. Starting from big data analysis technology, this paper first introduces the principle of support vector machines and explains that many types of support vector machines are classified by solving the optimal objective function through the Lagrange multiplier method. Then, the principle of the particle swarm optimization algorithm is introduced, the steps and process of the PSO algorithm are given, and the PSO-SVM classification model is constructed by using the PSO algorithm to optimize the parameters of support vectors. Finally, the PSO-SVM model is used to construct and analyze the evaluation index system with the example of teacher-training students majoring in mathematics at YL University. From the indicators of professional foundation and instructional design, 40%, 39.32%, 14.31%, and 6.35% were evaluated at A, B, C, and D levels, respectively. From the indicators of teaching evaluation and reflective development, the four levels of A, B, C and D evaluations accounted for 40.84%, 24.77%, 15.98% and 18.41%, respectively. This indicates that in addition to theoretical and practical techniques, it is also necessary to train teacher trainees in teaching evaluation and reflective development to improve their teaching ability under the output-oriented approach.
An Experiment on University English Translation Teaching Model Based on Big Data-Driven Learning
Authors: He Guanghui 
Published: September 2023

Abstract
Exploring the teaching mode of English translation in college to stimulate students’ learning initiative better and improve their English translation ability. In this paper, the basic principles of the plain Bayesian classification algorithm are introduced under big data technology-driven learning, and the conditional independence of plain Bayesian is illustrated. The algorithm and process of probabilistic classification of samples to be judged using great likelihood estimation are introduced, and the advantages and disadvantages of the algorithm are illustrated. Based on the disadvantages of this algorithm, the INB-MI classification algorithm is induced by adjusting the conditional probability after the number of smoothing using mutual information, and the validity is verified for this algorithm. For the university, English translation teaching was analyzed, a task-based English translation teaching model based on a blended environment was proposed, and the model was quantitatively analyzed with the INB-MI classification algorithm for the relevant data. In terms of cognitive types, the overall learning rate of this teaching model was 43.11%, 41.21%, 40.46%, and 38.3% for factual knowledge, conceptual knowledge, procedural knowledge, and metacognitive knowledge types, respectively. Regarding instructional evaluation, the percentage of those who agreed was 84.26%. Thus, the task-based English translation teaching model under big data-driven learning can help students integrate their existing knowledge and enhance their learning initiatives.
Design of IPR evaluation system based on linear regression model
Authors: Zhang Qihang , Jiang Jie , Feng Bo , Feng Junwen 
Published: September 2023

Abstract
This paper first defines the conceptual scope of intellectual property, and the intellectual property evaluation system analyzes the special characteristics of enterprise intellectual property evaluation and compares the differences between several intellectual property management models. Secondly, an open adaptive enterprise IPR evaluation system is constructed based on a linear regression model, and the system structure and the relationship between subsystems are analyzed in depth. Finally, based on the theory of adaptive evaluation management, the adaptive IPR evaluation system is constructed. The adaptive enterprise IPR evaluation model based on linear regression was constructed mainly from three dimensions, and the method to determine the development coordination index and early warning degree of the three dimensions was deduced. The results show that the average efficiency of the typical enterprise IPR evaluation system calculated based on the linear regression model is 0.86, which is 21.3% more efficient than the traditional model. Four of the decision units’ DEA is effective, 63% of the inputs are effective, and 37% of the input resources are wasted, which aligns with the actual enterprise. The adaptive IPR evaluation system based on the linear regression model proposed in this paper has theoretical innovation value and practical significance for enterprises to realize the transformation of IPR achievements.
China’s Stock Market Trend Prediction Model based on Adversarial Learning
Authors: Yang Dan , Zhang Yaomin 
Published: September 2023

Abstract
There are numerous stock market theories as a result of the gradual usage of mathematical models by researchers to forecast equities during the past few decades. By quantifying the rise and fall range, the prediction problem can be changed into a multi-classification problem based on the related data. This paper describes an Adversarial Learning-based stock forecast model by building a three-tier LSTM training network using the Adversarial Learning concept, selecting 300 stocks to represent the overall performance of the Chinese stock market, increasing the proportion of large to small training datasets, and strengthening the model’s ability to obtain detailed information from a small amount of data.
Seroprevalence of brucellosis infection in sheep in China during 2003-2022: A systematic review and meta-analysis
Authors: Wang Rulin , Bai Yunli , Li Yinfei , Zhou Weiguang 
Published: September 2023

Abstract
Brucellosis is an important zoonotic chronic infectious disease caused by Brucella. The disease mainly infects animals, such as sheep, cattle, pigs, and dogs, it can also infect humans, and sheep are the most seriously infected animals in China. The incidence of brucellosis has been rising annually in recent years, which has resulted in significant financial losses for the sheep business. Therefore, this systematic review and meta-analysis aimed to assess the seroprevalence of brucellosis infection in sheep in China from 2003 to October 2022. A sum of 92 relevant articles were retrieved from three Chinese databases and three English databases, and they were analyzed by RStudio software using a random-effects model. In accordance with the conclusions, the pooled incidence of brucellosis infection in sheep was 1.09% in China. Regarding the time distribution, sheep’s brucellosis seroprevalence was the highest from 2012 to 2016 (1.83%, 95% confidence interval (CI): 0.94-3.01) and the seroprevalence was the lowest during 2016-2022 (0.81%, 95% CI: 0.43-1.31). The regional distribution revealed that Northeast China has the highest seroprevalence (2.94%, 95% CI: 0.07-9.81), while that was the lowest in the East China (0.23%, 95%CI: 0.05-0.52). Among different provinces, Hebei Province had the highest incidence (17.41%, 95% CI: 17.41-21.77), and it was the lowest in Guangdong Province (0.08%, 95% CI: 0.02-0.18). Meta-analysis revealed that brucellosis infection was widely spread in sheep in China, thus, In order to lessen the financial losses and risks to human health brought on by brucellosis infection, it is vital to increase the control of the disease in animals.
Investigation into the Coincidence between Specialty Setting in Higher Vocational Colleges and Industrial Structure Utilizing a Coupling Coordination Evaluation Framework
Authors: Lu Zhengqiu , Zhou Chunliang , Zhoudan  
Published: September 2023

Abstract
The coincidence between specialty setting and industrial structure within higher vocational colleges epitomizes the tangible foundation for the amalgamation of industry and education in advanced vocational training, serving as an essential element in Ningbo’s regional economic evolution. Through an examination of Ningbo’s prevailing industrial composition and the regional specialty setting of higher vocational colleges, this study evaluates the congruity between specialty setting and industrial structure by fashioning a deviation degree model. Concurrently, it calculates the comprehensive development level of specialty setting and regional industry through entropy weight method, and then probes the coupling coordination magnitude between specialty setting and regional industry through the construction of a coupling assessment coordination framework on this basis. The findings reveal that the specialty setting and industrial structure of higher vocational colleges in Ningbo exist in a state of significant coupling, and the interconnection degree between the two is commendable. Nevertheless, the overall deviation is notably substantial, indicating that the coupling coordination demands further refinement. Hence, it becomes imperative to augment the synchronized advancement between specialty setting in higher vocational colleges and regional industries within Ningbo, focusing on three vital dimensions: the optimal utilization of the government’s comprehensive planning capability, the predominant role of higher vocational colleges, and the synergistic collaboration with enterprises within the context of higher vocational education.
Influence of Fatigue on Flight Safety: A Structural Equation Modeling Analysis
Authors: Zhu Shouxi , Chen Jian 
Published: September 2023

Abstract
Currently, pilot fatigue is considered to be a significant factor that affects aviation safety. In order to investigate the impact of fatigue on flight safety, we design a questionnaire to conduct a survey on the pilots of Shandong Airline, process and analyze the data through the SPSSAU data analysis platform, and construct a structural equation between fatigue and pilot unsafe behaviors. The study findings indicate that there is a significant relationship between situational awareness, safety awareness, crew atmosphere, work pressure and pilot fatigue, and the higher the pilot fatigue level, the lower situational awareness and safety awareness, the worse crew atmosphere and the higher work pressure. Compared to physical fatigue, mental fatigue was more vulnerable to the above four factors, and at the same time, it was also more likely to lead to the pilot’s unsafe behaviors, thus threatening flight safety. Therefore, in order to guarantee flight safety, airlines and aviation administration should pay more attention to pilot’s mental fatigue problems.
The moderating effect of creativity on entrepreneurial intention of Chinese vocational college students
Authors: Wang Chengming , Zhang Yanhua , Ding Hui , Zhang Li 
Published: September 2023

Abstract
At present, Chinese colleges and universities pursue “innovative talents” more strongly than ever. The status quo of creativity is closely related to the relatively low success rate of Chinese college students’ entrepreneurship. This paper combs the research results on the impact of creativity on college students’ entrepreneurial intention, and conducts a confirmatory analysis on the regulatory effect of creativity on entrepreneurial intention of Chinese vocational college students. This paper takes creativity as the independent variable, takes entrepreneurial intention as the dependent variable, makes an empirical analysis on the final sample data of 508 vocational college students, taking Chinese vocational college students as the survey objects. We find that creativity has a positive and distinctive impact on entrepreneurial intention of Chinese vocational college students. At the same time, we can see that there are obvious differences between entrepreneurial cultures of different countries and creativity of college students. It is suggested that the Chinese government should guide college students to cultivate entrepreneurial thinking, bring innovative thinking and adventurous spirit into their study and life, and actively advocate the establishment of a diversified and sustainable entrepreneurial ecology.
Some new existence results for fractional partial random nonlocal differential equations with delay
Authors: Heris Amel , Salim Abdelkrim , Benchohra Mouffak 
Published: September 2023

Abstract
The present paper deals with some existence results for the Darboux problem of partial fractional random differential equations with finite delay. The arguments are based on a random fixed point theorem with stochastic domain combined with the measure of noncompactness. An illustration is given to show the applicability of our results.
Modelling and predicting coastal zone depth profile evolution: a survey
Authors: Baramiya Denis , Lavrentiev Mikhail , Spigler Renato 
Published: September 2023

Abstract
We survey results concerning the problem of identifying depth profiles at coastal zone, which evolve in time due to natural as well as anthropic activities. This issue is relevant to control the modifications of the environment occurring near sea coastlines, but also in river's estuaries and harbors. One of the main goals is to predict the time evolution of the depth profile in the long-term (i.e., over years or decades, say), and to do this on the basis of real observed and measured data, available in several databases. Most mathematical models are formulated in terms of partial differential equations of the diffusive type, in one or two space dimensions. Consequently, from the mathematical standpoint, the aforementioned identification problem takes on the form of an inverse problem for some given parabolic equation associated with suitable initial and boundary conditions.
Correlation between the size of pheochromocytoma and the level of metanephrines
Authors: Rezkallah Emad , Elsaify Andrew , Hanna Ragai , Elsaify Wael 
Published: September 2023

Abstract

Objective. Pheochromocytomas (PHEO) and paraganglioma (PGLs) are rare neuroendocrine catecholamine-producing tumors that arise from the chromaffin cells of either the adrenal medulla or extra-adrenal paraganglionic tissues. Despite the recent advances in imaging technologies, biochemical evidence of excessive catecholamine production by the tumor is considered the most important test for the diagnosis of these tumors. The aim of the present study is to investigate the role of the catecholamine metabolites (normetanephrine and metanephrine) levels in the diagnosis of PHEO/PGLs and to evaluate if their levels correlate with the size of these tumors.

Patients and Methods. Twenty-five patients were included in the study during the time period of 10 years. Their data were compared with another set of 25 patients to obtain the sensitivity and specificity of metanephrine and normetanephrine in the diagnosis of PHEO/PGLs. The tumor size was reviewed in every patient to obtain the correlation coefficient between the tumor sizes and the plasma/24-hour urinary metanephrine levels.

Results. The sensitivity and specificity rates for plasma metanephrine were 80–92% and 92–96%, respectively; while for 24-hour urinary metanephrine were 80–90% and 95–100%, respectively. We found a strong positive relationship between the tumor size and the plasma levels of normetanephrine (r=0.518, p<0.01), and metanephrine (r=0.577, p<0.01). While the relation with the 24-hour urinary concentrations of normetanephrine (r=0.384, p=0.01) and 24-h urinary meta-nephrine (r=0.138, p<0.01) was low.

Conclusion. The determination of plasma and 24-hour urinary levels of metanephrines is a reliable test for the diagnosis of PHEO, as they are continuously produced by the tumor cells in contrast to catecholamines.
Customer Experience Management: Analysis of Customer Retention in Restaurants in Anambra State, Nigeria
Authors: Nwankwo Cosmas Anayochukwu , Kanyangale MacDonald Isaac 
Published: September 2023

Abstract
This study examined the effect of customer experience management (CEM) on customer retention in restaurants in Anambra State, Nigeria. Specifically, the study sought to investigate the influence of affective customer experience, cognitive customer experience, physical customer experience and social-identity customer experience on customer retention in restaurants in Anambra State, Nigeria. The study adopted a survey research method. The study found that affective customer experience, cognitive customer experience, physical customer experience and social-identity customer experiences have a significant effect on customer retention in restaurants in Anambra State, Nigeria. Based on the foregoing, the study concluded that CEM had a significant effect on customer retention in restaurants in Anambra State, Nigeria. The study recommended, amongst others, that management of restaurants should deliberately focus on humanic clues in terms of providing a conducive environment, especially one that is always clean for its customers.
The Dynamism of the Environment — The Impact on Service Company Competitive Advantage from a CRM Dynamic Capabilities Perspective
Authors: Pukas Anetta 
Published: September 2023

Abstract

Objective
To explore the dynamism of the environment and the impact on service company competitive advantage from a customer relationship management (CRM) dynamic capabilities (DCs) perspective. This work also aims to develop a multidimensional conceptualisation of the dynamic environment and propose a theoretical model for analysing the impact of the environment's dynamism on the relationship between dynamic CRM capabilities and competitive advantage.

Research Design and Methods
Based on the resource-based view (RBV) and dynamic capabilities view (DCV), the method of critical literature analysis was used. Literature sources written in the last two decades were analysed.

Findings
The result of the literature research became the development of a new conceptualisation of the dynamic environment and its three relevant dimensions, as well as the proposal of constructs in the theoretical model, where the dynamism of the environment plays a moderating role in the relationship between dynamic CRM capabilities and competitive advantage.

Implications/Recommendations
As implications for further research, empirical verification of the created model and checking the relationship between the constructs should be indicated.

Contribution
The findings extend the application of RBV and DCV in marketing knowledge. In addition, the model and this study's conclusions direct service firms to develop CRM capabilities that can enhance the company, thereby enabling the building of competitive advantage in a dynamic environment.