bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nonlinear mathematical modeling in the model of village cultural industry
Authors: Zhang Xiaodong , Peng Changrong , Song Nan 
Published: August 2023

Abstract
To solve the problem that the current forecasting methods cannot describe the long-term correlation of traffic, which leads to low prediction accuracy, the author proposes a mathematical modeling, forecasting and analysis method for village nonlinear traffic. The original nonlinear traffic data collected from the village comes from each base station, the information contained is uneven, pre-processing the collected data, eliminating abnormal values and duplicate data, and supplementing the missing data. Nonlinear traffic contains limited information, so a random forest algorithm is used to extract traffic characteristics and reduce data processing dimensions. The nonlinear traffic characteristics of the village are convolved, and the cross entropy function is used as the loss function, the feature vector of the input prediction model is deeply learned, and the communication traffic prediction results are obtained. Taking the traffic data of the communication operation enterprise’s base station as the test data, the experiment results show that, in the test with 1 million pieces of data, the decision coefficient of the mathematical modeling, prediction and analysis method of village nonlinear flow designed by the author is 0.9599, which is 0.1267 and 0.1431 higher than the prediction and analysis method based on genetic algorithm and fuzzy clustering algorithm respectively. In the modeling and prediction of nonlinear flow, the determination coefficient of the method proposed by the author is closer to 1, the fitting degree of this method is better than that of the contrast method, and it is adaptive in the real scene with a large amount of data. It is proved that the mathematical modeling and prediction analysis method designed in this design can reduce NRMSE and MAPE, improve the determination coefficient of prediction results, and provide the basis for village analysis.
Application of Computer Big Data Modeling Based on Lagrangian Mathematical Equation in the Village Cultural Industry Model
Authors: Zhang Xiaodong , Peng Changrong , Liu Qian , Ma Yichu 
Published: August 2023

Abstract
To understand the Lagrangian mathematical equation, the author proposes an application study of big data modeling in the village cultural industry model. The author takes 20 traditional villages in Beijing as the object, and through crawling relevant Internet cultural and tourism big data, using the theory of tourism consumer behavior, from the aspects of consumer motivation behavior, food, housing, shopping, and other experience behavior, consumer evaluation behavior, and consumer space-time behavior, carry out targeted content analysis, aggregation analysis, etc, fully reveal the behavioral portrait of tourists in Beijing’s traditional villages. The results show that the overall tourism experience of Beijing’s traditional villages is good, but the development level is quite different, the cultural and tourism supply pattern of “some have boutiques, some have highlights, and the overall influence is weak” is presented to improve the overall level. At the same time, the computer big data based on tourists’ feedback can reasonably reveal the inherent characteristics and problems of traditional village tourism, which is innovative in the current situation where village tourism data is difficult to obtain.
Analysis of Macro Environment and Development Countermeasures of the Education Industry Based on the PEST Model
Authors: Wang Lihui , Hou Chen 
Published: August 2023

Abstract
To understand the macro environment of the education industry and analyze the development countermeasures, the author proposes a PEST model. The author takes the macro environment analysis of vocational education development in Sichuan Province as the research object. In recent years, the economic development of Sichuan Province has accelerated, and the GDP growth rate has been higher than the national GDP growth rate for many consecutive years. At the same time, the industrial structure has also been continuously optimized and adjusted, which has brought opportunities for the development of vocational education in Sichuan Province, but it also brings many challenges. The author uses the PEST model to analyze the development of vocational education in Sichuan Province, grasp the macro environment faced by the development of vocational education in Sichuan Province, and propose corresponding development strategies.
Characteristic Analysis of Cheerleading Self-selected Action Arrangement Elements Based on BP Neural Network
Authors: Wang Caohui , An Chenwei 
Published: August 2023

Abstract
BP neural network is a typical algorithm in artificial intelligence networks, and it has strong nonlinear mapping ability, solving some nonlinear problems and pattern recognition is its most prominent part. The network topology of the BP neural network is simple, it has high error precision, it is easy to program, and also has strong operability, it is one of the most important algorithms in the field of data mining. Cheerleading is one of the dance cheerleading events, because of its sunshine, fashion and vitality, it has become a new sports event on campus, although cheerleading has developed rapidly in China, its promotion on campus is still at the initial stage, with the increasing number of public contestants, the competition among the participating teams has become increasingly fierce, excellent choreography is the key to victory, by using the methods of literature, video analysis and mathematical statistics, the author made an in-depth analysis of the top eight teams, including 24 teams, who achieved the best in the collective flower ball optional complete set of actions in the three open national cheerleading championships from 2019 to 2021, grasp the current situation and trend of the arrangement of free flower ball movements in the open children’s group, and summarize its rules, it provides a theoretical basis for the arrangement of the set of collective flower ball optional movements of the open university group, improve the overall level of the flower ball cheerleading program of the open university group, and play a role in consolidating the basic learning of flower ball cheerleading.
Application of Deep Learning in Vocal Music Teaching
Authors: Zheng Lili , Cui Lina 
Published: August 2023

Abstract
This paper builds a cloud-oriented speech teaching system based on deep learning mode. A synthetic algorithm for decision-making based on depth and hierarchy knowledge is presented. This algorithm calculates the weight matrix of the user and marks to achieve personalized speech recommendations. The whole process of cloud music teaching has been realized. The identification performance of the recorded database is compared with that of the Berlin database. It is proved that the identification ability of this algorithm is greatly improved.
Design of English pronunciation quality evaluation system based on the deep learning model
Authors: Zhang Fangfang , Zhou Zhihong 
Published: August 2023

Abstract
To explore the design of the English pronunciation quality evaluation system, a design of the English pronunciation quality evaluation system based on a deep learning model is proposed. This method explores the research of English pronunciation quality evaluation by recommending key technical problems and solutions based on information represented by the deep learning model. The research shows that the efficiency of the English pronunciation quality evaluation system based on a deep learning model is about 30% higher than that of traditional methods. Through the experimental verification, the English pronunciation quality evaluation model method is reasonable and reliable. It can give learners timely, accurate, and objective evaluation and feedback guidance, help learners find out the difference between their pronunciation and standard pronunciation, correct pronunciation errors, and improve the efficiency of English spoken language learning.
Curriculum Construction Practice of Ideological and Political Education Based on the IPO Model
Authors: Song Lili 
Published: August 2023

Abstract
This paper establishes the teaching quality evaluation model and index system of ideological and political education with quality products as the core. This method was used to investigate 1140 college students in 10 universities. The results show that college students ignore intrinsic motivation and goals and lack ideal thinking in learning quality. In terms of course quality, there are some problems: the overall level of students’ investment in the course is not high, and their satisfaction with the course teaching is not high. The results of empirical analysis show that the multiple linear regression estimation based on the IPO method can better resist outliers and get a better prediction effect.
Construction of computer-assisted English writing teaching model from the perspective of the Internet of Things
Authors: Liu Fang 
Published: August 2023

Abstract
To solve the problems of the traditional embedded software development teaching platform, such as the heavy load on the server side, resulting in the slow response speed and poor experience of users, this paper proposes a computer-aided English writing teaching model from the perspective of the Internet of things. Based on the cloud platform, the system manages the resources of computers scattered on the server and client, to improve the efficiency of resource retrieval. In addition, based on the fuzzy logic model, the system can evaluate and evaluate students’ knowledge and learning achievements according to students’ preferences for cognition and knowledge acquisition. The experimental results show that motivation (μmot), attitude (μatt), extroversion (μext) and self-esteem (µsel) are positively correlated with students’ performance, and the data are 0.608, 0.533, 0.595 and 0.477 respectively, while introversion (µint) and anxiety (µanx) are negatively correlated with students’ performance, and the data are −0.464, −0.618. Conclusion: from the perspective of the Internet of Things, the computer-assisted English writing teaching model has good performance and can play a positive role in improving students’ grades.
A study on the cognitive model of student management in colleges and universities under the perspective of big data technology
Authors: Wang Enfu 
Published: August 2023

Abstract
The development of big data concepts and technology can not only effectively improve management efficiency but also promote the realization of personalized management. Based on the concept of big data and the management concepts advocated by scientific management theory, goal management theory, and human-oriented management theory, the survey materials were analyzed and organized to understand the current situation of student management in higher education institutions in terms of study management, internship management, merit management, life management, mental health management, and employment management. Combined with the background of big data, we found that there are problems in student management in higher education institutions, such as incomplete information collection, subjective decision-making, low efficiency of resource utilization, delayed management feedback, and lack of personalized management. Therefore, using the concept of big data to promote the optimization of student management in higher education institutions will be the future development trend.
Study on the application of deep learning technology and BIM model in the quality management of bridge design and construction stage
Authors: Huang Rui , Zheng Huan , Lei Jun 
Published: August 2023

Abstract
The development of the transportation industry can effectively accelerate the speed of economic development, in which bridges occupy an important position in transportation. The safety of the bridge design and construction process is a key part of bridge construction, and relying on human resources to investigate safety hazards greatly affects efficiency. In this paper, we combine deep learning technology and the BIM model to explore the synergistic effect of both on the quality management of the bridge construction phase and analyze the measured data. The results show that the application of the BIM model can improve efficiency by 35% compared with the traditional 2D CAD drawings, and the accuracy of data analysis can be improved by 12.51% and 14.26% for DNN and DBN models based on deep learning, respectively. The addition of the GSO algorithm leads to a further 19.19% improvement in the training accuracy of the coupled model. Finally, the optimization model was used to analyze the load factors and force majeure factors that affect the safety of the bridge, and to find the structural factors that affect the safety of the bridge design, which guides to ensure the quality of the bridge during the construction process.
A trajectory prediction method based on graph attention mechanism
Authors: Zhou Hejun , Zhao Ting , Fang Yang , liu Qilie 
Published: August 2023

Abstract
Vehicle trajectory prediction is one of the key technologies to realize autonomous driving, which provides an important guarantee for the safety of vehicles in the process of autonomous driving. In this paper, with this as the starting point, a graph convolutional neural network is introduced through a graph attention mechanism to obtain scene features by modeling the temporal Transformer model of surrounding information. Based on the temporal convolutional model to obtain scene features, new feature vectors are calculated by aggregating the weights for the features of nodes and neighboring nodes. Then the input feature dimensions are transformed into the weight matrix of the output feature dimensions, and the output feature vector corresponding to the attention coefficients is calculated by using weighted summation. Then the effect of multiple training of the model is evaluated by taking the mean value and defining its structural relationship. The experimental results show that the prediction error of the proposed method is significantly smaller than that of the comparison method in scenarios with speeds less than or equal to 5m/s and greater than 5m/s. The prediction error based on target detection is reduced by 58.95%, indicating that the proposed method is more consistent with the operation scenarios of autonomous driving.
Teacher evaluations of open educational resources designed to support dialogic cultural literacy learning in schools
Authors: Zimmermann Maria , Mayweg-Paus Elisabeth , Ruwe Theresa , Maine Fiona 
Published: August 2023

Abstract
For teaching practice to be useful, educational materials must be thoroughly evaluated prior to use. In this study, teachers evaluated open educational resources (OER) created for a European Commission Horizon 2020 project called DIALLS (‘DIalogue and Argumentation for cultural Literacy Learning in Schools’). Considering research on how OER are evaluated, we were interested in learning (1) how teachers perceive their application, content, design, value and sustainability and (2) what other aspects teachers find important when evaluating OER. After analysing quantitative and qualitative data, we found that aspects facilitating self-regulated use were rated most highly and mentioned most often. Teachers additionally valued adaptable materials offering opportunities to reflect their teaching practices. Future research may benefit from evaluating OER based on ‘affordance’ aspects — aspects that allow teachers to adapt the materials in a self-regulated way and reflect on their teaching.
Metamorphic dolomitic marble-hosted talc from the Mulvoj area in the Western Pamir Mountains, Tajikistan
Authors: Moazzen Mohssen , Silmonov Intizor , Elnazarov Sangin 
Published: August 2023

Abstract
Talc is crystallized in the metamorphic dolomitic rocks of the southwest Pamir mountains in the Mulvoj area, Tajikistan. Field studies show that talc is restricted to metamorphic dolomitic marble layers in the garnet-mica schist and gneiss. The layers are parallel to the original sedimentary bedding and schistosity of the metamorphic rocks. Petrography and whole rock geochemistry reveal calcite, tremolite, quartz and dolomite as the main mineral phases in the talc-bearing metamorphosed dolomitic rocks, while calcite is absent in the samples without talc. XRD studies show that talc samples are almost pure, and geochemistry indicates very low Fe and Cr and very high Mg contents. Geochemical features along with field observations clearly shows that Mulvoj talc is not originated from peridotite. Based on phase relations studies in the CaO-MgO-SiO2-H2O-CO2 system, the reaction between dolomite, quartz, and water at pressure greater than 2 kbar and temperature up to ~460°C and XCO2 up to 0.6 was the main talc forming reaction. Talc and calcite consuming reaction produced tremolite, dolomite and binary (CO2-H2O) fluid.
Productive Organisational Energy and Performance in Estonian Football Organisations
Authors: Aidla Anne , Iliushchenkov Georgii 
Published: August 2023

Abstract
Sports governance is a broad domain in which many ambitious goals are expected to be considered by top management. Attending to productive organisational energy may be the key to consolidating and amplifying efforts by members of sports organisations at individual, group and organisational levels in order to achieve those wide-ranging goals. The aim of the article is to discover whether Estonian football organisations with higher results for the dimensions of productive organisational energy also show higher performance. Overall, we reached about 14% of the population of players, coaching staff and management from football organisations in Estonia. Productive organisational energy was measured using affective, cognitive and behavioural dimensions (Cole et al., 2012). Rankings in the league tables for 2020, 2021 and 2022 reflected the performance of the football clubs. The results demonstrated that football clubs that had higher levels of productive organisational energy were mostly placed in the top half of the league table. All three dimensions of productive organisational energy were similarly relevant in regard to performance. The connection between productive organisational energy and performance has so far been analysed only in business organisations and in one health service organisation. We brought the topic to the sports context and distinguished three dimensions of productive organisational energy while comparing the performance of organisations, which has not been done before. We also conducted the first empirical study that considers whether dimensions of productive organisational energy are balanced in better performing clubs.
Effect of Global Oil Price Volatility and Exchange Rate Policy on Foreign Exchange Reserves in Iraq
Authors: Khudhair Layla Bdaiwi , Ghadeer Yousif Hakim 
Published: August 2023

Purpose: This paper offers simulations and forecasts of the ideal currency reserve measure in light of future shocks to the Iraqi economy due to the downturn in the international price of oil and the global economic shutdown triggered by the Corona pandemic.

Theoretical framework: The Iraqi foreign exchange reserves have entered a cycle of sustained and accelerated degradation in recent years and hit alarming amounts in 2020, affecting Iraq's financial stability compared to other foreign currency reserves. According to figures from the Iraqi Parliament's Financial Commission, the Iraqi fund in the Central Bank of Iraq decreased, following removing the government's second loan by the end of 2020, to $35 billion. The Fitch Ratings Agency, on the other hand, has found that Iraq's plan to slash public sector wages and pension costs will delay the reduction of currency reserves as part of the attempt to lower financial imbalances and relieve financial pressures. However, it will be difficult to enforce and risk exacerbating social disorders. According to Fitch, by the end of August (15% of projected GDP for 2020), cash funding from the Central Bank of Iraq grew to 28.5 billion Iraqi dinars from 14.1 billion Iraqi dinars at the end of May.

Design/methodology/approach: The study uses an analytical approach to show the fluctuations in oil prices and their impact on the fluctuation of oil revenues and the currency-selling window that the Central Bank of Iraq applies to its foreign reserves.

Findings: The systemic problem of worldwide petroleum price drops that provide longer-term estimates to estimate the decrease in petroleum prices on global oil markets explains the quick fall in Iraqi exchange reserve magnitude. Iraq's foreign reserves, mostly from oil exports, fulfill international standards. Iraq's exchange rate policy depends on the Central Bank's direct foreign currency sales. This approach reduces foreign money diversion from Iraq, preventing the central bank from maintaining exchange rate stability.

Research, Practical & Social implications: The impact of foreign reserves on national financial stability is becoming more obvious as their function evolves from supplying fundamental transaction needs to fulfilling financial security criteria.

Originality/value: The Iraqi dinar's value must be protected at all costs, hence the Central Bank of Iraq's foreign reserves are crucial. These reserves are affected by oil revenues, the main financier for it, and the window for selling the currency, which is the outlet for leakage from it.
https://www.cijds.calebuniversity.edu.ng/
Authors:   Bursary Department, Michael and Cecilia Ibru University,  Ughelli, Delta State, Nigeria, Akenroye Christopher Taiwo , Adegbie Folajimi Festus ,   Department of Accounting, Babcock University, Ilishan-Remo, Ogun State, Nigeria, Owolabi Sunday  Ajao ,   Department of Accounting, Babcock University, Ilishan-Remo, Ogun State, Nigeria, Ajibade Ayodeji ,   Department of Accounting, Babcock University, Ilishan-Remo, Ogun State, Nigeria, Adelegan Michael Oluyomi ,   Faculty of Management Sciences, University of Benin, Benin, Edo State, Nigeria, Otubor Christopher Osega ,   Department of Banking and Finance, Faculty of Management Sciences, University of Jos, Nigeria
Published: August 2023

In today’s dynamic and competitive business environment, solvency is a critical success factor that strategically enables a firm to structure their resources in meeting their financial obligations on the short, medium and long-term bases. However, the inability of a firm to maintain acceptable level of financial stability threatens its future growth. A company’s inability to sustain robust solvency portends the firm’s sick state that impairs its organic growth rate. Firms’ improper utilization of their unique characteristics as their corporate strategic drivers has given rise to illiquidity causing existential threat among listed firms in Nigeria. This study examines the effect of firms’ characteristics on solvency of selected listed companies in Nigeria. The study adopted ex-post facto research design. The population of the study was 161 listed companies in Nigeria as at 31st December 2020 with a chosen sample size of 111 purposively determined. Secondary data extracted from the published audited financial statements covering a 10-year period (2011–2020) were used for the study. Descriptive and inferential (multiple regression) statistics were employed to analyze the data. Findings revealed that corporate strategic drivers had joint significant effects on short-term solvency and long-term solvency. The study concludes that corporate strategic drivers exert significant influence on solvency of listed firms in Nigeria. The study recommends that firms should continue to utilize their corporate strategic characteristics to drive their short-term and long-term solvency statuses. Keywords:	Corporate Strategic Drivers, Financial strategy, Firms’ Characteristics, Long-term solvency, Short-term solvency