bluuebunny/crossref_metadata_2025_split huggingface dataset:
From Rate Regulation to Financial Control: Accounting and Public Policy at the Interstate Commerce Commission, 1887–1933
Authors: Miranti, Jr. Paul J. , Collier Deirdre M. , Palmon Dan 
Published: September 2023

ABSTRACT
This paper focuses on the Interstate Commerce Commission’s (ICC’s) application of accounting to achieve public policy goals for the U.S. railroad industry. The ICC began in 1887 with a mandate to ensure competition in the transportation industry, with rate oversight as one tool. During the Progressive Era, from 1901 to 1921, the ICC used accounting to ensure rate equity; a second implicit goal was to reduce the rail industry’s informational asymmetries to investors, morphing over time to ensuring a reasonable return to investors. In the 1920s, the ICC used accounting to reduce securities speculation, facilitate regional rail consolidation, and govern industry finance. This accounting-based model of regulation continued until the Great Depression of the 1930s, when new economic circumstances called into question the ICC’s ability to serve the most pressing public policy concerns. The technologies used by the ICC, however, continued to be exploited by other regulatory bodies.
Features of measurement uncertainty evaluation during calibration of digital ohmmeters
Authors: Zakharov Igor , Semenikhin Valerii , Zakharov Oleksandr , Shevchenko Svitlana 
Published: September 2023

The scheme for transferring the size of the unit of resistance during the calibration of digital ohmmeters at direct current is considered. The procedure for the measurement uncertainty evaluation is described: recording the measurement model and its refinement, evaluation of input and measured values, evaluation of standard uncertainties of the input and measured values, evaluation of the expanded uncertainty. The refined model includes the dependence of the resistance of the reference resistor on temperature and a correction to the drift of the resistance value of the reference resistor since its last calibration. To evaluate the expanded uncertainty, the kurtosis method was used. An uncertainty budget has been made, including the kurtosis of input and measured values. The use of the Excel package makes it possible to implement, based on this budget, a program for automation of measurement uncertainty calculations. An example of the measurement uncertainty evaluation during the calibration of a digital ohmmeter of type 2318 at a point of 1 mOhm using an electrical resistance coil R310 with an accuracy class of 0.01 is considered. The influence of nonlinearity of the measurement model on the estimates of the numerical value of the measurand and its combined standard uncertainty is studied. To verify the results, the distribution law of the measurand was modelled by the Monte Carlo method. An algorithm for determining the expanded uncertainty using the NIST Uncertainty Machine web application for the missing confidence level of 0.9545 is proposed. The comparison of the results of the measurement uncertainty evaluation by the kurtosis and Monte Carlo methods has shown their good agreement.
Research on information visualization for digital media design methodology based on big data technology
Authors: Zhang Ruhe , Zhao Lu , Wang Xiaochen 
Published: September 2023

Abstract
Information visualization is one of the important contents of digital media design, and they have a mutually complementary relationship. This paper combines the realistic background of the big data era and makes a more comprehensive introduction to the theoretical study of data visualization, including visual perception, visualization functions, judgment indexes, and principles. Secondly, by collecting the time series data, anomaly detection is carried out in the pre-processing stage, while the ring test is divided into a short-term ring and a long-term ring because the time series carries the property of time succession. Finally, anomaly detection is performed by its statistical features, which include distribution, moving average, exponential smoothing, standard deviation, and mean, whose values are equivalent to observing single-dimensional data when the sample data distribution is used as a perspective. The results show that through the comparative analysis of data visualization and traditional mathematical statistics, the correlation coefficients of information visualization for digital media design are between 0.8003 and 0.8129, while the traditional statistical methods for digital media design are only between 0.5038 and 0.5523. The information visualization proposed in this paper is better for digital media design to convey the art expressed by data and deeper mining analysis of spatiotemporal data.
Research on the physical training of athletes in ice and snow sports based on big data
Authors: Jiang Xiangzhi , Qu Xinyi 
Published: September 2023

Abstract
Through big data technology, we analyze the effect of functional fitness training on the physical quality of cross-country skiers and explore a scientific training method suitable for cross-country skiers. The MCDM-Apriori algorithm is proposed based on matrix compression, partitioning, and subsumption to solve the problem that the Apriori algorithm continuously generates the candidate set of intermediate processes during the operation and scans the original database several times, which causes huge consumption to the computer. The HDWA-Kmeans algorithm was used to analyze the effect of experimental training on the physical quality of athletes before and after the training, and the MCDM-Apriori algorithm was used to analyze the quality of functional movements to demonstrate the effect of functional training on the physical quality of cross-country skiers. In the physical quality comparison, the increase of 15 quality indexes in the experimental group was greater than that in the control group except for the push-up strength exhaustion, in which the increase of 49.91% and 54.05% in the experimental group of single-leg squat left and single-leg squat right, respectively. The increase in the quality of movement screening indexes compared with the experimental group, except for the deep squat, all other movements were increased to varying degrees, including a 20.77% increase in quadriceps rotation stability, while the increase in the control group was much worse than the experimental group. The results indicate that the functional training method and the training intensity and volume are consistent with and adapted to the physical training needs and physical characteristics of the athletes in the experimental group.
A study on the management of big data technology in financial decision-making of enterprise cloud accounting
Authors: Zhang Pei 
Published: September 2023

Abstract
Exploring the effectiveness of the application of big data technology in financial decision management of enterprise cloud accounting is to help better enterprises achieve economic growth and sustainable development. In this paper, a decision tree algorithm based on information gain and attribute dependency is jointly analyzed under big data technology using attribute dependency of rough set theory, attribute parsimony algorithm, and information gain of ID3 algorithm. The analysis of enterprise cloud accounting and financial decision-making is explained, including the process and content. The data analysis of financial decision management of WK Group, BL Real Estate, and LD Holdings is carried out using a decision tree algorithm. In terms of financing structure, debt financing mainly consists of long-term borrowings, short-term borrowings, and bonds payable, accounting for 66.06%, 21.18%, and 12.76%, respectively. In terms of gearing ratio, the average ratios of WK Group, BL Real Estate, and LD Holdings are 76.6%, 81.54%, and 80.05%, respectively. It shows that the decision tree algorithm based on information gain and attribute dependency can effectively perform corporate financial decision management analysis and visualize the company’s sustainable development strategy through the data.
Research on digital transformation innovation of the exhibition industry in the era of big data
Authors: Zhang Jieli 
Published: September 2023

Abstract
The changing world situation has put the requirement of digital transformation to the traditional exhibition industry. In this paper, we propose a big data-based exhibition exhibit recommendation system, which adopts the improved ALS collaborative filtering algorithm as an offline recommendation and combines window-based real-time TopN recommendation with dynamic perception-based exhibit recommendation as a real-time recommendation algorithm. Then, the big data-based recommendation system is applied to the digital transformation of the exhibition industry to analyze its impact on exhibition-viewing efficiency, exhibition service evaluation, and digital evaluation of exhibition projects. The impact assessment of digitally transformed exhibitions is 0.737 on average, which is 10.61% higher than that of exhibitions in traditional mode. The assessment of the degree of digital application is 0.778 on average, which is 12.59% higher than that of the exhibitions in the traditional mode. The average evaluation of exhibit specialization is 0.872, which is 17.69% higher than that of the traditional model. The research based on big data can provide references and case studies for the digital transformation of traditional exhibition enterprises and help the whole industry chain of the exhibition industry to carry out digital transformation.
Coupling research of Confucianism and Chinese philosophy based on data mining model
Authors: Ba Wenze 
Published: September 2023

Abstract
Confucianism is a cultural school guided by Confucianism, which is of great significance to the development of Chinese philosophy. This paper first introduces the steps of the outlier data mining algorithm of weighted deep forest, describes the construction method of weighted deep forest, divides the data into several different dimensions, and enters the random forest training in turn. Then outlier detection is introduced, dividing the data into classes with different densities and calculating their local isolation factors and outlier data. Then the algorithm’s performance is tested, and finally, the influence of Confucianism on Chinese philosophy and the main position of Confucian philosophy in the history of Chinese philosophy is analyzed. In terms of algorithm performance, the number T of different decision trees has an impact on AUC. When the number T of subtrees is 50, the AUC value starts to converge, and when the number T is 100 and 200, the AUC value of the algorithm is close to 1. In terms of the influence of Confucianism on Chinese philosophy, 75% of the people think that Confucianism Confucianism is precocious and has enriched the connotation and promoted the evolution of Chinese philosophy. Confucianism is an essential part of the Chinese philosophical calendar, advancing Chinese philosophy and moral culture.
Research on brand operation strategy of integrating traditional culture into the modern tourism industry based on big data analysis
Authors: Zhao Xiang , Wei Jinchan , Chen Jiaping 
Published: September 2023

Abstract
The rich traditional culture is an inexhaustible treasure trove of resources for the brand operation of the modern tourism industry. This paper proposes an improved method for the LDA model of text big data mining, optimizing the topic representation of LDA by introducing the Topic2Vec model, optimizing the probability calculation of generated words by combining the original Dilley distribution and Bernoulli distribution and optimizing the assignment of topic words in the Gibbs adoption process of LDA model with the help of likelihood function. Then, the big data of tourism brand design text, promotion, and cultural products are mined and analyzed based on the improved LFV-LDA model. In the design of tourism brands focusing on traditional culture, the frequency of the keyword “pattern” was the highest, accounting for 8.20%. In brand promotion, the most distributed channel from 2017 to 2021 was a live broadcast, and the growth rate in 2020 and 2021 reached 22.71% and 36.29%. Regarding traditional cultural and creative products, tourism cultural and creative products have maintained a high growth momentum from 2012 to 2021, with an average annual growth rate of 154.25%. Based on the analysis of big data, it can guide the operation of tourism industry brands in all aspects, such as design, promotion, and landing, and give full play to the value connotation of traditional culture.
The Fit of Constructivist Teaching Theory and Foreign Language Teaching Reform in the Background of the Internet Era
Authors: Deng Ting 
Published: September 2023

Abstract
The development of the fit between constructivist teaching theory and foreign language teaching is explored to improve learners’ language proficiency and comprehensive application skills effectively. This paper discusses a constructivist teaching model in the Internet era, using the fruit fly algorithm to optimize the kernel function of support vector machines and then constructing an FOA-SVM classification analysis model. The FOA-SVM model was used to analyze the fit data of the foreign language culture introduction teaching model based on constructivist teaching theory, including teaching principles and teaching practices. Regarding teaching principles, 55.69% of the students thought that the appropriateness principle was the best for the constructivist teaching theory to fit foreign language teaching. In terms of teaching practice, students’ learning attitude, learning initiative, learning ability, language ability, and application ability increased by 65.55%, 71.94%, 62.23%, 62.22%, and 78.42%, respectively. This shows that the integration and development of constructivist teaching theory and foreign language teaching should be based on the principle of appropriateness, and the use of a foreign language culture introduction mode of teaching is conducive to improving students’ learning attitudes and initiatives.
Heritage development of traditional culture in folk art education based on the decentralized Internet
Authors: Cui Yuting , Yu Xuanli 
Published: September 2023

Abstract
Folk art education is an important way to inherit and develop traditional culture. In this paper, the cascade propagation of typical decentralized Internet-social networks is modeled as a propagation dynamic graph model, and an enhanced graph-aware neural network is proposed through the analysis of the learning process of neural graph networks. A further recurrent graph-aware neural network is proposed for the characteristics of information dissemination in the decentralized Internet, and the transmission and development of traditional culture in folk art education are analyzed based on this network model. In folk art education, the most common type of traditional culture dissemination is ink painting, accounting for 20.32%, which is 6.91%, 12.35%, and 14.86% higher than other types, respectively. From 2014 to 2021, the percentage of Internet-based communication media increased from 12.47% to 24.78%, an increase of 12.31 percentage points. The analysis based on the decentralized Internet can accurately extract the characteristics of traditional culture integrated into folk art education, which helps to inherit further and promote the excellent traditional culture.
A study on the application of creative writing in literature teaching based on multiple linear regression algorithm
Authors: Zhang Qingbo 
Published: September 2023

Abstract
Under the background of the big data era, the rapid development of the Internet has driven the development of the education field. The traditional creative writing teaching is hardly suitable for the new curriculum reform requirements, prompting the rapid rise of creative writing and being highly recognized by the National Education Bureau. This paper applies creative writing based on multiple linear regression algorithms, i.e., teaching literature and education. Firstly, we understand the formula and principle of multiple linear regression algorithm, establish multiple linear models, extract and matrix students’ characteristic data, collect students’ data when learning on the online platform, pre-process the collected data, and analyze the performance and behavior of creative writing based on the end element linear regression algorithm. The results show that the number of clustering centers and visits are linearly correlated with the student’s grades, final overall grades, and test scores and that the student’s grades eventually improved to above 90. This study identifies the extent to which learning behaviors impact students’ final grades, allowing teachers to refine their teaching methods by selecting the learning styles that have a greater impact on students’ final grades among the many online platform student activities. It is conducive to improving cultural literacy and creative writing skills and has historical significance for developing Chinese literature and education.
Teaching reform and innovation of vocational development and employment guidance courses in colleges and universities based on random forest model
Authors: Lu Xi , Wei La 
Published: September 2023

Abstract
The current employment situation of graduates is serious and complicated, and employment work is very difficult. Furthermore, the employment quality of college graduates is an important reflection of the quality of education teaching and talent cultivation in higher education. Using big data to provide all-round and multi-perspective feedback on employment quality can find the direction of efforts to improve employment quality further, provide an important reference basis for schools to adjust the layout of majors, make development plans, reform education teaching, optimize career guidance courses and optimize enrollment policies and measures, and effectively promote universities to fulfill better their historical mission of serving the society. This paper extracts features for a series of school behavior data of students and carries out feature selection through appropriate methods. Specifically, the construction problem of the traditional random forest model is analyzed, and a new model is proposed by combining it with a decision tree algorithm; then, the model is constructed and adjusted by grid parameters to ensure the accuracy of the model, and finally, the model is compared and analyzed. The research shows that the accuracy of the RF prediction model using standard features is 0.702, and the LSTM prediction model using only temporal features is only 0.683. In contrast, the prediction accuracy of the model in this paper reaches 0.805. Therefore, the prediction accuracy of the model based on the decision tree algorithm is much higher than the other two, which is effective for optimizing the teaching of career development and employment guidance courses in colleges and universities, thus can improve the education and management-related to career planning and career guidance in schools.
Desempenho cognitivo e escolar em crianças com transtorno de déficit de atenção e hiperatividade (TDAH)
Authors: Simão Adriana Nobre de Paula , Ciasca Sylvia Maria 
Published: September 2023

O Transtorno de Déficit de Atenção e Hiperatividade é um transtorno de conduta é crônico, com substrato biológico muito importante, não devido a uma única causa, apresenta forte base genética e é formado por um grupo heterogêneo de crianças. Inclui crianças com inteligência normal, que apresentam dificuldades significativas para se adequar em termos de comportamento e/ou aprendizagem às normas esperadas para sua idade. Sendo dividido em três subtipos denominados como Subtipo Desatento, Subtipo Hiperativo/Impulsivo e Subtipo Combinado. O objetivo deste trabalho foi caracterizar o desempenho cognitivo, de funções corticais superiores e escolar. Utilizando como instrumento de avaliação o WISC Ill, TLN-Ce TDE. Foram avaliadas 13 crianças, com idade média de 9 anos, sendo a sua maioria do sexo masculino, frequentando o ensino fundamental da rede publicada região de Campinas. Como resultado, o grupo apresenta desempenho cognitivo dentro da média, com melhor resultado nos índices fatoriais de organização perceptual e compreensão verba. Na avaliação das funções corticais tiveram pior desempenho nas áreas cadêmicas, ritmo e habilidade tátil. Na avaliação de desempenho escolar apresentou dificuldade em escrita, aritmética e leitura.
Awake craniotomy for fenestration of motor cortex neuroglial cyst: A case report
Authors: Hamzah Abdulaziz , Ashqar Alaa Adel , Alshanqiti Maryam , Lary Ahmed , Samkari Alaa 
Published: September 2023

Background:
Neuroglial cysts (NCs) are uncommon benign cysts covered by an epithelial layer, accounting for <1% of all intracranial cysts. The optimal management approach for these cysts remains a subject of debate. Given their rarity, management principles used for arachnoid cysts can be applied to NCs.

Case Description:
We present a case of a 35-year-old male without prior medical history, who presented to the neurosurgery clinic with complaints of absence seizures. A neurological examination revealed subtle weakness in the left upper limb. Brain magnetic resonance imaging demonstrated a large cystic lesion in the posterior frontal and anterior parietal lobes of the right hemisphere. The patient underwent an awake craniotomy, during which a cystoventricular fenestration was performed on the motor cortex cyst. Histopathological examination confirmed the diagnosis of NC. At the 4-month follow-up, the patient experienced complete recovery, with normal strength (5/5) in all limbs and absence of seizure remission.

Conclusion:
This case highlights the successful use of awake craniotomy for the fenestration of an NC in the motor cortex. Given the rarity of NCs, there is no consensus on the optimal treatment strategy. However, in this particular case, the patient achieved complete recovery without any new neurological deficits following the procedure.
Problems and possibilities for developing the risk concept of technical systems
Authors: Лепихин А.М. , Лещенко В.В. , Махутов Н.А. 
Published: September 2023

Дан краткий анализ развития концепций риска аварий технических систем. На основе концепции минимизации стоимости жизненного цикла предложена новая трактовка риска технических систем, включающая потери как от аварий, так и от нарушений работоспособного состояния. Рассмотрены задачи оценки риска в предлагаемой формулировке. Ввиду ограниченности возможностей аналитических методов оценки риска основное внимание акцентируется на использовании методов Монте-Карло. Рассмотрены возможности оценок риска на основе статистических данных об авариях и нарушениях работоспособности. В качестве примера выполнены оценки риска аварий наземных и морских подводных трубопроводных систем с учетом нарушений работоспособности. Показано, что предлагаемый подход дает более высокие оценки риска по сравнению с традиционным подходом
The article gives a brief analysis for development of the concepts for risk analysis of accidents in technical systems. The new interpretation of the risk of technical systems is proposed, including both losses from accidents and losses from violations of the working condition and based on the concept of minimizing the cost of the life cycle. The problems of risk assessment in the proposed formulation are considered. The main attention is paid to the prospects of risk assessments using Monte Carlo methods due to the limited capabilities of analytical methods for risk assessment. The capabilities of risk assessments based on statistical data on accidents and malfunctions are considered. The assessments of the risk of accidents and malfunctions of onshore and offshore underwater pipeline systems are carried out. It is shown that the proposed approach gives higher risk estimates compared to the traditional approach