bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep learning-based fault diagnosis and localization method for fiber optic cables in communication networks
Authors: Zhang Lixia , Gao Wei , Yan Leifang
Published: September 2023

With the arrival of the big data era and the development of new network technology, how to use big data technology to diagnose and locate fiber optic cable faults in communication networks has become a hot topic of current concern. Firstly, a combined generative adversarial network and convolutional neural network algorithm is proposed based on a deep learning algorithm, then an improved fault diagnosis model combining generative adversarial network and convolutional neural network algorithm is built, and finally, the combined generative adversarial network and convolutional neural network model is used to verify and analyze the fiber optic cable fault diagnosis. The results show that the accuracy of the DCGAN-CNN algorithm for fiber optic cable fault diagnosis is 98.5%, and the research results verify the effectiveness of the combined generative adversarial network and convolutional neural network model for fiber optic cable fault diagnosis. This study can accurately and comprehensively solve the problem of fiber optic cable faults in communication networks and thus play a guiding reference value for developing fault diagnosis in Chinese communication networks.
A Study on Innovative Teaching Strategies of English in Universities Based on VAR Model
Authors: Lyu Ruifeng
Published: September 2023

English is one of the basic courses in college classroom education, but the current model of college English education gradually reveals some problems. For this reason, this paper researches and analyzes the strategies of English innovation education in colleges and universities based on the VAR model. Firstly, this paper constructs a VAR model, on which a TVP-VAR hybrid model is constructed, and four estimation methods of the TVP-VAR model are analyzed in detail. Secondly, we designed the English teaching method based on the TVP-VAR model and the “5C” model of innovative teaching. Based on these models and methods, this paper investigates English majors’ learning status and teachers’ teaching status in several universities in different regions. The analysis shows that the overall attitude of English majors toward learning English is very good, and those who like learning English account for 83.58% of the total number of students surveyed, but 93.6% of the students learn English to deal with exams go to higher education and going abroad, and only 6.4% really like English. Although multimedia in teachers’ teaching methods has exceeded 50% in all four grades, it is still far from matching the information age. Finally, based on the various problems analyzed in the survey, this paper proposes strategies for innovative teaching English in colleges and universities in China.
Analysis of the impact of ADDIE education model based on logistic regression model on teaching contemporary cultural and creative product design
Authors: Huang Yingying
Published: September 2023

Exploring the influence of the ADDIE education model on teaching cultural and creative product design to promote the improvement of the quality of teaching cultural and creative product design. Starting from the ADDIE education model, this paper analyzes the five components of the model and the specific functions of each component. The logistic regression algorithm that constitutes the analysis module of the ADDIE education model is introduced, and a sparse prior factor is introduced to optimize the logistic regression algorithm; then, a sparse logistic regression algorithm is constructed to solve the likelihood function of the weight vector. Finally, the ADDIE education model is used to analyze the indicators of cultural and creative product design teaching in two aspects: the teaching objectives and teaching principles of cultural and creative product design. From the teaching objectives, the influence of cognitive, skill, and emotional objectives accounted for 47.11%, 44.41% and 51.26%, respectively. From the teaching principles, the percentages of uniqueness, practicality, and attractiveness are 51.5%, 43.7%, and 40.3%, respectively. Based on the ADDIE education model can affect the emotional goals and uniqueness in the teaching of cultural and creative product design, and it is necessary to focus on the emotional teaching of product design as well as diversified and differentiated teaching in design teaching in order to enhance better the learners’ interest degree in cultural and creative product design.
Research on practical education model of mental health development of college students in higher education institutions in the context of big data
Authors: Luo Le
Published: September 2023

The advent of the big data era brings opportunities and challenges to the innovation of mental health education for college students in higher education institutions. In this paper, we monitor the mental health of college students in higher education institutions by collecting students’ consumption data, access control data, network data and historical achievement data, and use a convolutional neural network to extract features from behavioral data and then input the feature set into random forest model for training. The recognition effect of the RF algorithm is analyzed by comparing it with other algorithms, and the problems of college students’ mental health education are analyzed based on the correlation of features. The accuracy of identifying mental health problems of college students based on RF analysis of big data reached 0.72, the recall rate reached 0.58, and the F1-Measure was 0.67. For the correlation of different features, the most significant correlation effect was the time spent in the dormitory on rest days and the number of swiping access cards, with the correlation coefficients reaching 0.2719 and -0.2191, respectively. The analysis based on big data can accurately grasp the current situation and problems of mental health education of college students in higher education institutions and promote the comprehensive development of mental health education of college students.
Orientation and triage of preschool students’ interest development based on deep learning model
Authors: Hao Weiren , Kong Cuiwei
Published: September 2023

To study the direction of preschool students’ interest development, this paper proposes to mine and analyze preschool students’ interest development data using a deep learning model. This paper first introduces the basic algorithmic process of deep learning BP neural network model, then uses a genetic algorithm to optimize the traditional BP neural network to get the best performance. The deep learning model is then used to analyze the preschool students’ family income, family structure, interest cultivation direction, gender and age, and interest cultivation orientation and diversion. The lower the family income, the higher the percentage of children choosing interest classes, mostly concentrated in families with income between 2000-8000. In terms of gender, there are also differences in interest cultivation analysis, with boys favoring the cultivation of science and sports abilities such as logical thinking, technology, calculation, and sports, accounting for about 20% more than girls in general, while girls favoring the cultivation of art abilities such as dance, English, reading, and vocal music, with 15-20% more than boys. Deep learning model-based interest development for preschool students can follow the natural choices of young children and provide scientific guidance for interest triage of preschool children.
Assessment of tax-related risks in corporate betting agreements based on vector autoregressive model
Authors: Zhang Yang
Published: September 2023

This paper is based on the vector autoregressive (VAR) model, and the model optimization is completed by determining the lag order to eliminate the autocorrelation in the error term through model comparison. The variables in the tax-related risk of the betting agreement are formed into a vector form, the parameters are estimated by least squares or maximum likelihood estimation, and the interrelationship of the variables is analyzed by impulse response function. The vector autoregressive model was used to evaluate the tax-related risk of the betting agreement of Company M, and 12 factors were obtained. Among them, the factors that have more than 80% influence on tax-related risk are the lack of research on the betting agreement and the backwardness of the theoretical aspects of the handling of the betting agreement, with the influence of 87.89% and 84.98%, respectively. Therefore, the vector autoregressive model can effectively assess the tax-related risks in corporate betting agreements and provide a reference for companies diversifying into restructuring and mergers.
Exploring Innovative Strategies for Teaching English in Higher Education with the Support of Big Data
Authors: Ren Lilin
Published: September 2023

Under the background of the rapid development of big data technology, how to use big data technology to improve the quality and efficiency of English teaching in higher education is currently a hot topic of key concern in society and education circles. This paper is firstly based on the feedback data of English teaching from students and teachers in higher education institutions. The ranking model of fused similarity pre-processes the feedback data to get the data to feature values of English-level similarity. Then the personalized teaching system is constructed based on the data feature values, and the overall teaching framework and ideas of the MOOC personalized teaching system are proposed. The satisfaction of the MOOC personalized teaching system platform in the past five years, from 2018-2022, was analyzed employing a questionnaire, and the results showed that: on the teachers’ side, the overall satisfaction increased from the initial 53.46% to 73.64% year by year. Regarding parents, the overall satisfaction rate increased from 46.72% at the beginning to 65.76% year by year. In terms of students, the satisfaction rate increased from 75.37% at the beginning to 91.23% year by year. Overall, students showed better satisfaction with the English personalized instruction system platform than parents and teachers. This study can lead to pedagogical innovations based on the data feedback on students’ English performance, which can improve teachers’ teaching ability and pedagogical innovations.
Cultural and artistic dissemination of traditional Chinese silk patterns in the 17th-18th centuries in the context of big data
Authors: Wang Taidi , Feng Hui , Sun Ying
Published: September 2023

Silk has evolved a unique silk culture in its long history, and silk patterns have condensed the external aesthetics of silk culture and shown distinctive national characteristics. This paper firstly constructs the cultural communication network of the 17th-18th century Maritime Silk Road through big data technology and uses social network analysis to study the structural characteristics of the cultural and artistic communication network. The MPI multidimensional spatio-temporal communication evolution model is used to delineate the network’s layers further, and exploratory spatial data analysis is introduced to explore the spatio-temporal communication evolution pattern of the network. Finally, in the empirical analysis, 200 years of silk pattern data from 1600-1800 in China were selected to establish four dimensions and 11 indicators data for measurement. A comprehensive MPI multidimensional spatio-temporal propagation evolution model was derived by principal component analysis to derive the contribution of each indicator. The results show that the multidimensional cultural dissemination index of traditional silk pattern culture and art from 1600 to 1800 was 0.7461 and approximated to 0.8, and the dissemination influence was 0.2252, respectively, rising to 97%, indicating that the dissemination of silk pattern culture and art in the 17th-18th centuries was a flourishing trend. The MPI multidimensional spatial and temporal communication evolution model proposed in this paper effectively visualizes and analyzes the communication channels of silk pattern culture and art, which provides a guiding reference for the revival and communication of modern Chinese traditional culture.
Scale and efficiency of China’s radiation industry based on LightGBM model
Authors: Gong Yu , Qu Yunhuan , Xu Ying
Published: September 2023

In the digitalization of big data information, how to use big data and China’s radiation industry combined have become a key topic of social concern. This paper first constructs LightGBM model by gradient boosting tree and deep neural network. Gradient boosting tree optimizes the convergence and stability of LightGBM model, while the deep neural network improves the accuracy and efficiency of the LightGBM model by updating the weights on each edge. Then the radiation safety management method is proposed according to the danger of the radiation industry, the characteristic data of radiation industry scale and efficiency are obtained through research work, the research indexes are determined, and finally, the data analysis of China’s radiation industry scale and efficiency is conducted by using LightGBM model. Take the medical isotope industry as an example: from 2010 to 2020, the number of nuclear medicine industries increased from 857 to 1148, and the deviation rate of prediction was always maintained at 10%. In terms of radiation industry benefits: the annual growth rate of PET diagnostics, SPECT diagnostics and Nuclide Therapy benefit is 56%, 14% and 5.3%, respectively, the radiation industry has great market demand, and the benefit will continue to grow in the future. This study is a comprehensive and accurate analysis of the scale and benefits of China’s radiation industry and has a guiding reference value for the development and research of China’s radiation industry.
Research on the Development of Young Teachers’ Informatization Teaching Ability in Universities Based on Big Data Technology
Authors: Xu Qiongyan
Published: September 2023

This paper presents an incomplete multi categorization algorithm based on relative distance, which instead of simply using the Euclidean distance between class centers to measure the degree of dissimilarity between classes, uses the relative distance between classes to measure the dissimilarity of classes. The entire algorithm strictly follows the principle of splitting the most easily separable classes first, which decreases the accumulation of errors occurring in the binomial tree structure and improves the algorithm’s overall evaluation accuracy. Relevant tests are designed to measure the comprehensive performance of the algorithm. In terms of accuracy, the algorithm in this paper can be 4.14% higher than the best OVR algorithm and 1.63% higher than the best OVO. The experimental results prove that the algorithm is effective and that the overall time consumption in testing time is less than OVR and OVO. The analysis of young teachers’ informatization teaching ability obtained that the main influencing factors were the lack of theoretical guidance for teachers’ teaching, the lack of a common sharing platform for subject teaching resources and the lack of a sound service support system, which influenced the informatization teaching ability to 86%, 83.62% and 84.06%, respectively. Therefore, the results proved that the algorithm is effective, young teachers should focus on theoretical training in teaching informatization, and the school should build an informatization teaching platform to improve the service support system.
Design of energy big data and carbon emission monitoring system based on perceptron model in the context of carbon neutral and carbon peaking
Authors: Hu Yuanyuan , Xie Tianxiang , Chi Ning , Yang Yujie
Published: September 2023

The big energy data and carbon emission monitoring system is designed to collect carbon emission-related data for pollution gas management. This paper constructs a carbon emission monitoring system in the context of carbon neutrality and peaking. A multi-layer perceptron algorithm is introduced based on the principle of perception, and a BP-MLP neural network model is proposed by optimizing the perceptron weights using BP neural network. For the sensors in the carbon emission monitoring system, the node redundancy is processed, and the optimal sensor distribution is proved by using the correlation coefficient. Finally, the evaluation analysis of the carbon monitoring system was carried out in three aspects: relevance coefficient de-redundancy, number of iterations and daily emissions. The results show that when the correlation threshold is 0.8, the sensor distribution of the monitoring system can satisfy the monitoring under various wind conditions, and when the number of iterations is 600, the difference between the real value and the monitored value is only 3.63% and the daily emission peaks at 5.243 mg/m3 at 14:00 a.m. This shows that the carbon emission monitoring system constructed based on the BP-MLP model can effectively collect and analyze carbon emission data. Data collection and analysis, and provide corresponding data support for the management of gas pollution.
A model of online opinion dissemination based on vector autoregressive model of emotional information entropy
Authors: Yin Jingqi , Chang Rui
Published: September 2023

In the context of the digitalization of big data information, to solve the problems of timeliness and accuracy of traditional online opinion dissemination models. This paper firstly proposes a vector autoregressive model in the research problem of online opinion dissemination model and constructs a vector autoregressive model based on multivariate time series and unit root test. Then the emotional information entropy is determined based on the statistical characteristics of the emotional index, and the evaluation index is mainly composed of the current mainstream online public opinion dissemination modes. Finally, data analysis of online opinion dissemination modes based on the vector autoregressive model is conducted, and the dissemination efficiency of different modes is compared based on the analysis results. The results show that in the microblog dissemination mode, online public opinion’s dissemination efficiency remains in the range of 38.02% to 44.81%, and its average dissemination efficiency is 41.51%. In the online short video dissemination mode: the online public opinion dissemination efficiency remains between 32.15% to 35.74%, and its average dissemination efficiency is 33.97%. In the consultation mode, online public opinion’s dissemination efficiency remains within the range of 22.06% to 28.99%, and its average dissemination efficiency is 25.61%. In terms of the average dissemination efficiency, the microblog dissemination mode performs better than the other two. Through a comprehensive and objective study of online public opinion dissemination modes, this study has a guiding reference value for improving online public opinion dissemination to promote the development of online public opinion dissemination in China.
Multimodal construction of human movement dataset under the development of physical dance teaching in colleges and universities
Authors: Liu Feng
Published: September 2023

First, this paper proposes a multimodal fusion-based human motion recognition technique applied to college physical dance teaching, where feature-level or decision-level fusion maps human kinematic semantic information from datasets to classifiers under a single-level stage. Secondly, a multi-level multimodal fusion approach for human motion recognition is proposed to make it more adaptable to practical application scenarios. The depth data is converted into a depth motion projection map at the input side, and the inertial data is converted into a signal image. Finally, all the modalities are trained by a convolutional neural network for extracting features, and the extracted features are fused at the feature level by discriminant correlation analysis. The results show that the multi-level multimodal fusion framework achieves 99.8% and 99.9% recognition accuracy on the two datasets, respectively, with 100% accuracy in the Throw and Catch action recognition and the lowest recognition rate of 95.36% in the Clap action test, with an average recognition rate of 97.89%, which has a high recognition accuracy. The multi-level multimodal fusion model can obtain movement data close to the actual movement data after optimization in low-precision movement data, which provides data support for physical dance teaching and learning.
Reading promotion mode of university libraries in the context of information development
Authors: Liang Yuhua , Wang Jinying
Published: September 2023

This paper mainly proposes a technical route of user profiling based on multi-view clustering and constructs a multidimensional and multi-view reader feature system based on reader behavior data. According to the constructed reader feature system and the defects of the classical K-means algorithm in multi-view clustering, a multi-view dichotomous K-means algorithm based on Marxian distance is proposed. Using the proposed algorithm for multi-view clustering of readers, the user portrait features of readers can be obtained, and finally, a university library user portrait system is designed and implemented. By analyzing the behavior of college students through the user portrait technique, we get that the most preferred book genre of college students is literature accounting for 71.45%, followed by science and history with 57.64% and 51.37%, respectively. The most popular form of reading promotion among college students is classical film and television exhibitions, accounting for 63.73%, followed by lectures by celebrities and experts, accounting for 60.91%. The highest influence on college students going to the library is too many spare time activities, accounting for 64.38%, and not choosing books, accounting for 36.95%. These data can help libraries understand readers’ needs and provide help for reading accurate recommendations and services based on readers’ user profiles.
Design of online art education system based on 3D virtual simulation technology
Authors: He Shuijing
Published: September 2023

At present, the call for information reform in education teaching is increasing, and art education is also facing the demand for online. This paper analyzes the demand for online art education according to the characteristics of existing online education, proposes an online education system based on virtual simulation technology for the special needs of art education, and studies the structure distribution of learning resources, teaching organization and online teaching practice under 3D virtual simulation scenarios respectively. At the same time, a virtual simulation explanation robot is added using Unity3D technology to realize online learning interaction in art education. In the continuity test of the system, the system throughput per second accounted for 42.31% of the maximum throughput on average, with the lowest accounting for only 28.65% and the highest accounting for 56.98%, and the operating efficiency of the system met the teaching needs of art education. In the concurrency test, the success rate of system interface calls remained above 80% as the number of concurrent users increased. In practice, the overall satisfaction rate of students with the art online education system reached 88.3%. The system in this paper can enhance the interest in art teaching and provide a feasible new path for the development of art education in the information era.
Diversified Integration of Civics Teaching Resources in Universities Based on Discrete Regression Model
Authors: Gan Lu
Published: September 2023

Diversified integration, rationalized allocation and high-efficiency utilization of various practical teaching resources are the prerequisite and foundation for realizing the goal of monolithic education of Civic and Political Science teaching. This paper proposes a local two-way adaptive degree function of a complex network of Civic and Political Science teaching resources cluster and constructs a discrete regression-based resource diversification integration model based on the adaptive degree function by considering the characteristics of a complex network of Civic and Political Science teaching resources cluster with local worldliness (cluster structure), complexity, incomplete and asymmetric information obtained. The research results show that the discrete regression model Cronbach’s α coefficient value is 0.903, and the cumulative explained variance reaches 81.69%, which can effectively and highly fit the integration of diverse resources of Civics teaching. And compared with the traditional BA integration model, the discrete regression model increases the integration speed by 36.21% and the breadth by 41.39%. The discrete regression-based resource diversification integration model proposed in this paper effectively improves the level of practical teaching of Civics in colleges and universities and provides some reference and help for related researchers.
Teaching reform of university botany courses based on discrete regression algorithm
Authors: Li Zhuowei , Liu Junyuan , Lu Liuwanwan , Wang Yafang , Yan Xiaowei , Han Chunyang
Published: September 2023

Under the digitalization of big data information, the traditional way of teaching botany courses faces challenges and opportunities, and using big data technology to improve the quality of botany teaching becomes a key research problem. Firstly, based on the big data technology and the teaching objectives of botany in colleges and universities, the teaching system platform is proposed to be constructed by a discrete regression algorithm and Hadoop platform. Then the structure and functions of the teaching system are designed according to the needs of teachers and students and course objectives, and the teaching system is realized for practical application in botany courses. Finally, starting from students as learning subjects, biological engineering students of Guizhou University were identified as the research objects, and the teaching system platform based on the discrete regression algorithm was used to conduct weight analysis on the teaching of botany courses in colleges and universities. The results showed that the mean values of the botany course, bacteriology course, zoology course and microbiology weight were 25.64%, 25.32%, 24.57% and 24.47%, respectively, and the overall weight means performance showed that botany was better than the other three types of biology courses with the mean value of 25.64%. This study has helped improve botany teaching quality and curriculum reform by increasing the participation of students in classroom teaching.
The Innovation of GIS Service Mode Based on “Grid Integration” and “Elastic Cloud”
Authors: Wang Chenchun , Ma Shenglong , Hui Zi
Published: September 2023

This paper firstly investigates the theory and method of geospatial information services and grid integration model in the geographic information grid, intending to locate the parameter coordinates of the grid integration model into the GeoSOT-3D profiling framework. Secondly, the framework of the consumption structure between its services and cloud resources is established by the elastic cloud model based on the computation and storage capabilities provided by the shared grid infrastructure. And use the steady-state theoretical foundation for analysis to assess the service quality of each type of service and reflect the service quality of the GIS service model as a whole. Finally, a GIS service platform based on the grid integration model and elastic cloud model is constructed based on the existing open geographic information standards, service technology system, and grid technology. The research results show that the operation speed of the GIS service platform proposed in this paper is increased by 16.3%, the estimated cost has been reduced by 23.3%, and the service evaluation of the platform is improved by 43.6%. The GIS service platform based on the grid integration model and elastic cloud model has the advantages of global uniformity, multi-scale and spatial 2-3D consistency, which provides a new model with high economy and rapid response time for geographic information processing.
Distributed optical fiber sensing technology in operation status monitoring of GIL equipment
Authors: Du Wenjiao , Hu Zhong , Li Chenmeng , Chen Zihui , Chen Wenhong , Qiu Shiyan
Published: September 2023

This paper firstly proposes distributed fiber optic sensing technology based on big data technology and physics, distributed fiber optic sensing technology includes distributed fiber optic sensing technology based on interference type and distributed fiber optic sensing technology based on the scattering principle. Then investigated the demand for remote monitoring of distributed fiber optic sensing systems and the demand for large sensing networks in the Internet of Things and designed a long-distance distributed fiber optic sensing-based intelligent monitoring system. Finally, the vibration acceleration signal of the metal shell when partial discharge occurs is collected, and the high-frequency components in the vibration acceleration signal are used to diagnose and analyze the discharging faults caused by the metal particles of GIL. The results show that: when the rated current is loaded on the GIL, the main frequency distribution of the vibration acceleration signal on the surface of the metal shell is from 0 to 1 kHz, and the percentage of the signal energy in this frequency band is greater than 99% of the total energy in the range of 0 to 20 kHz. In the frequency range of 1 kHz to 20 kHz, the percentage of the signal energy in the total energy does not exceed 1%, and there is almost no high-frequency vibration acceleration signal. This study and the combination of these two technologies is a great contribution to the further development of each, but also more favorable for application in work and life.
Optimization of Innovative Teaching Model of College English Reading Based on Perceptual Machine Model
Authors: Wang Lang
Published: September 2023

Reading is an essential part of English learning and one of the basic elements of language proficiency. This paper proposes a joint analysis model based on multilayer perceptron, which uses an LSTM network model suitable for text processing. Using the BiLSTM network can obtain all the contexts before and after the current word and avoid the problems of gradient disappearance and gradient explosion that exist in ordinary recurrent neural networks. Two multilayer perceptrons are used, one for predicting lexical annotations and the other for predicting the relationship types of dependency arcs, and the model accuracy is further improved by continuously optimizing the parameters in the model. The English corpus is divided into a training set and a test set, and the prediction rate of the model in this paper reaches 96.02% in the English corpus. To test the effectiveness of this method for college English reading instruction, this model was implemented in the experimental class, while the traditional PWP teaching model was still used in the control class. The mean reading post-test score of the experimental class was 31.54, and the mean post-test score of the control class was 26.35. The mean reading post-test score of the experimental class was 7.7 points higher than the mean score of the pre-test. Therefore, the method in this paper is effective in teaching English reading and can improve college students’ reading performance.
Identification of Key Factors Influencing Consumer Purchase in Livestreaming Based on Principal Component Analysis and Combination Weighting
Authors: Zhu Xiaoping , Yang Li
Published: September 2023

Based on the livestreaming of the e-commerce platform Taobao, this paper studied the consumers’ online live streaming purchase decision behavior, taking causal snacks purchase as an example. In the paper, the principal component analysis (PCA) was applied to reduce dimension of the evaluation indicators of consumers purchase decision, and an evaluation index system for consumers’ purchase of casual snacks under livestreaming was established, which consists of 5 first-level indicators and 20 sub-level indicators. In view of the uncertainty of expert evaluation, Using Fuzzy-DEMATEL analysis the evaluation index’s logical relationships and influence relationships, and an Analytic Network Process (ANP) network based on the importance and relevance of consumer purchase influence was constructed. The weighted method of Fuzzy-DEMATEL and ANP combination is used to improve the objectivity of indexing importance. The experimental results showed that the amount of transaction guided by anchors, popularity of anchors, teamwork ability of livestreaming, brand awareness of snack and selection ability of livestreaming team were the key factors for consumers’ purchasing decisions of snack under livestreaming. This research could help livestreaming e-commerce platforms, businesses and livestreaming marketing teams understand the consumers behavior better, thus improve the purchase intention of consumers from the key factors affecting their decision-making, increase the sales volume and the amount of attention of the products, and increase the volume of guided transactions and the number of fans for the livestreaming marketing teams.
A hybrid physics-data-driven optimization model for grassland grazing management
Authors: Yu Bo , Li Yulong
Published: September 2023

This paper presents a hybrid physics-data-driven optimization model for grassland grazing management. It comprehensively assesses essential factors in the Abaga Banner grassland ecosystem, including soil moisture, vegetation biomass, desertification degree index, and soil compaction. Through a thorough analysis, the impacts of grazing patterns and intensity on the grassland’s physical characteristics and biomass are studied. Employing genetic algorithms, an optimal grazing model is formulated to minimize soil desertification throughout the year. The paper aims to contribute to grassland ecology restoration and ensure sustainable livelihoods for local herdsmen, offering a scientific foundation for promoting the sustainable growth of grassland husbandry.
China’s Image in German Media in Major Epidemic Prevention and Control Based on Mathematical Statistics
Authors: Jingjing Liu , Xiaoyan Zhang
Published: September 2023

National image is an important symbol of national cultural soft power. Adhering to ideas and methods of mathematical statistics, this paper focuses on the construction of China’s image in German media from the perspective of epidemic prevention and control. Taking Deutschlandfunk as the retrieval object, texts are analyzed by AntConc corpus analysis toolkit to construct China’s image and German media attitude tendency under the background. The study found that, the German media exoticised and politicised the event through a series of discursive devices, constructing a biased image of China, although giving positive comments on China’s anti-epidemic measures and foreign aid.
Research on the influence of key audit matters on the audit quality of commercial banks-Evidence from China
Authors: Wei Xiaoyan , Zhang Lifang , Li Jing , Zhou Xiyu Thomas
Published: September 2023

In this paper, multiple linear regression model is used to predict and test the effect of audit policy changes in the capital markets. In 2016, China issued a new reporting guideline which included the addition of key audit matters (KAMs) as the core focus. It was required that all A+H-share companies should implement these in their reporting in 2017, as well as all domestic listed companies in 2018. In order to study the impact of the KAMs standard on the audit quality of Chinese commercial banks, we analysed the KAMs as disclosed by commercial banks as well as any further change in audit quality at these banks before and after implementation of the new auditing reporting standards. The results show that the disclosure of KAMs significantly promotes the improvement of loan impairment provisions in commercial banks, thus inhibiting potential earnings manipulation by management and improving the quality of financial information. The level of loan impairment provision plays an intermediary role in the improvement of bank audit quality in the new reporting standards.
Does Work Engagement Effectively Predict Subjective Well-Being? : A Meta-Analysis Using R Statistical Software
Authors: Ding Hui , Si Shoujing
Published: September 2023

Does work engagement effectively predict subjective well-being? In this paper, we investigated the relationship between work engagement and subjective well-being by synthesizing 176 effects from 59 studies involving 21927 subjects. The results showed that work engagement were positively correlated with subjective well-being, while job burnout were negatively correlated with subjective well-being. Literature sources significantly adjusted the relationship among work engagement, job burnout and subjective well-being. The paper proved that work engagement and subjective well-being are closely related, and literature sources may play a moderating role.
Performance Evaluations of Audit Institutions That Purchase Social Audit Services
Authors: Wei Xiaoyan , Wang Hua
Published: September 2023

The technical characteristics of government audits make the purchase of social audit services different from the purchase of other public services. Carrying out performance evaluations of outsourced social audit services is important for ensuring effective social audit service outsourcing and for completing comprehensive high-quality audits. On the basis of constructing a conceptual framework for performance evaluations of social audit service purchases under the background of comprehensive audit coverage, the objectives, principles, processes, models, and steps of performance evaluations are clarified. From the perspective of performance evaluation theory, a performance evaluation model and an index system are constructed. On this basis, the evaluation framework is applied to performance evaluations of audit institutions that purchase social audit services. Although outsourcing social audit services solves the problem of coverage quantity relatively economically, there is still room for improvement in terms of efficiency and effectiveness. Audit institutions can continuously improve the performance of outsourced social audit services by building and continuously optimizing the pool of institutions and social audit personnel, constructing a real-time management system for outsourced social audit services, and improving the management incentive system for and performance of outsourced social audit services.
Forecasting Stock Market Volatility via Causal Reasoning
Authors: Yang Dan , Lu Di
Published: September 2023

Studies have shown that Internet financial news has become an important reference for investors in investment behavior. In order to simulate trading experiments that mimic the real stock market, this paper develops a stock volatility prediction model based on causal reasoning. It also gathers and cleans news and stock market data from the Internet, such as opening price, closing price, and change. The findings of the study indicate that the level of stock market volatility can be significantly influenced by online financial news. The proposed model can analyze the effects of news and stock market data in an explainable manner.
Difference-in-Differences Test for the Effect of Extreme Weather upon Enterprise Productivity
Authors: Li Guiping , Zhang Xiaohua , He Qian , Xiao Zheng
Published: September 2023

This paper establishes DID and PSM-DID models to examine the effect of extreme weather on enterprise productivity, using empirical evidence from natural experiments of torrential rainstorm in Zhengzhou of China. Based on analysis of empirical results, we find that extreme weather has a negative impact on enterprise productivity, psychological capital plays a regulatory role in this influence, and decrements of enterprise productivity with high psychological capital is smaller than enterprises with low psychological capital. The results of this study provide empirical data support to understand the negative effect of extreme weather upon enterprise productivity and the positive role of employee psychological capital.
The impact of industrial-university-research collaborations on innovation output in China’s petroleum and petrochemical industry
Authors: Zhu Zhihong , Zhang Shuang
Published: September 2023

To increase the capacity and production of the petroleum and petrochemical industries, it is helpful to investigate the features of industry-university-research collaborative innovation networks. Using the DEA model as a research object, listed companies in China’s petroleum and petrochemical industries are assessed for their innovation output, Moreover, we examined the structural holes in a Co-innovation network between industry and university. We have also assessed the network’s density, the strength of its connections, and the quality of its links. The strength of network relationships was negatively correlated with innovation output, but network density was positively correlated with structural holes. As a result of the research, relevant policy recommendations are made, including actively building industry-university-research collaborative innovation platforms, improving the depth and breadth of collaboration between innovation entities within the industry-university-research network, by connecting industry and universities to collaborate on innovative projects, petroleum and petrochemical companies can better compete.
Research on the influence of new media on ideological and political education in colleges
Authors: Liu Erting , Zhao Lanwei
Published: September 2023

This study aims to investigate the effectiveness of new media on ideological and political education in higher education institutions and utilizes data analysis methods to uncover the role and impact mechanism of new media in this context. To gather data and gain a deeper understanding, grounded theory and a questionnaire survey based on the Diffusion of Innovations Model were employed. The survey targeted university students and provided insights into the information dissemination and influence pathways of new media in ideological and political education at universities. The survey findings shed light on the positive role of new media in enhancing students’ learning outcomes in ideological and political theory and their willingness to participate in civic and political affairs. In addition to the survey, the study utilized literature visualization analysis using Citespace to identify research directions and approaches related to the influence of new media on ideological and political education in higher education institutions. The analysis results revealed research trends in this area. In conclusion, the study’s findings highlight the effectiveness of new media in ideological and political education in higher education institutions and contribute to a deeper understanding of its role and impact
The Role of Modern Techniques in Preservation of Archaeological Sites
Authors: Chabuk Mahmood , Al-Amiri Shatha
Published: September 2023

Archaeological sites have always suffered from loss and degradation due to many human and natural hazards. In recent decades, interest in preserving archaeological sites has increased dramatically. Many modern techniques have emerged from the different disciplines that can be used in preservation works, and a large number of the techniques and their capability made it difficult for decision-makers and specialists to determine the appropriate technique that gives the best results in preserving the archaeological site. The research aims to identify the project needed to preserve the archaeological site and then choose the appropriate technique for it, based on the opinions of experts using the analytic hierarchy process (AHP) method, which helps decision-makers and specialists to choose the most appropriate technology. The archaeological site of Babylon was chosen as a case study. As a result of applying the AHP method, the priority weights of preservation stages for the archaeological site of Babylon were determined as follows: (diagnosis and monitoring 30.8 %), (intervention 21.2 %), and (tourism and media 16.6 %), while the appropriate technique was determined as follows: (infrared thermography 29.4 %), (maintenance 49.3 %), and (augmented reality 38.7 %).
On absolute summability of infinite series and Fourier series
Authors: Özarslan Hikmet Seyhan
Published: September 2023

In the present paper, a theorem on θ −|T; δ|k summability method of an infinite series is proved, and also by using this method, a result on summability of a trigonometric Fourier series is obtained.
Virtual 3D Tour Assistance in Real Estate Management
Authors: Leimontaitė Lina , Naimavičienė Jurga
Published: September 2023

Over the past decades, more efficient real estate management opportunities have significantly expanded and improved. Complex methods, innovative techniques, and a constantly evolving spectrum of information technology have become readily available for common use. When managing real estate for short-term or medium-term rentals, planning, servicing, and ensuring accommodation quality are inseparable aspects, as is providing suitable housing. This process begins at the very first step when potential tenants request a viewing of the preferred property. The situation of the past few years demonstrated that the real estate business was one of the most affected economic sectors by the COVID-19 pandemic. Potential buyers or tenants could no longer physically visit and experience the space as before. Faced with this new reality, there was a need to find a tool to enhance the real estate management strategy by presenting the property. One such tool became the 360-degree photography and virtual tour. The aim of this study is to assess the practical applicability of 3D video tours and evaluate the advantages and drawbacks in short- and medium-term rental business.
The Dollar and Gold: Which is the Safest Haven? COVID-19 Evidence
Authors: Bousbia Salah Rahima , Beggat Hanane , Debbar Abdelkerim
Published: September 2023

This paper examines the dynamic correlation between the US dollar and gold prices during the coronavirus pandemic to determine which of the two assets is a safer haven from an investor’s perspective. The research utilises methods of analysis and synthesis of theoretical knowledge from published articles, literature, and official statistics websites. Data covering the period from January 1, 2020 to May 26, 2021, were primarily collected from the latest versions of these websites. The study includes a quantitative analysis of variables, including the Johansen cointegration test, the Granger causality test, and the error correction model. Our empirical analysis reveals a long-term equilibrium relationship between the US dollar and gold price. There is a oneway inverse causality relationship between the dollar and gold price. The results indicate that gold can be considered the safest haven from the investors’ perspective.