bluuebunny/crossref_metadata_2025_split huggingface dataset:
SOR Model and Application of Virtual Reality Technology in 3D Animation Design
Authors: Xiong Anya , Wang Qin 
Published: June 2023

Abstract
This paper introduces 3D modeling and application based on virtual technology. This paper’s modeling and drawing of SOR can obtain the differential equation of linear segments composed of pixel points. The resulting output data constitute an image unit. Then this paper uses the visual difference theory and effect to realize the production of virtual reality 3D animation technology. Finally, this paper carries on the simulation test to the three-dimensional model. The results show that 3D modeling using virtual technology can significantly improve accurate coordinates. This makes the 3D animation production and post-correction work more precise and fast.
Simulation and Characteristic Analysis of College Music Teaching Based on Nonlinear Equation
Authors: Ma Chunyu 
Published: June 2023

Abstract
Musical symbols are a good way of expressing human emotions and communication. It is a kind of nonlinear dynamic system with hysteresis. It isn’t easy to analyze its nonlinear characteristics by conventional methods. This paper divides it into several parts from the form of music. Secondly, this paper studies the local attributes of music signals and generalizes and deduces their general features. Then the Lyapunov index of music is numerically simulated, and its energy spectrum is analyzed. It is proved that the method is weak to some extent. Through the music correlation dimension analysis, we find its inherent nonlinear characteristics. The nonlinear music signals corresponding to classical piano works are given in this paper. Finally, the correlation dimension is numerically simulated by differential operation. The results show that the nonlinear characteristics of this method are stable.
Application of Partial Differential Equation Models in English Reading Corpus
Authors: Wang Jianying 
Published: June 2023

Abstract
In order to understand the application of partial differential equation models, a study in English reading corpus is proposed. In this study, a quasi-experimental research method was used to select two classes of students in a school as the subjects. The two classes were taught by the same English teacher, and the two classes were comparable in terms of their basic English learning (including reading ability). The total number of English lessons per semester in the two classes was 96, including 32 reading lessons. Students were guided to apply corpus-assisted reading in the reading classes of the experimental class, while the traditional reading teaching method was used in the control class. The corpus-assisted reading method was used in the experimental class for 16 lessons. During the experiment, students’ performances in applying the corpus-assisted reading were observed, their thinking maps in class and after class assignments were collected and analyzed, and their reading scores in the midterm and final exams were used as indicators of the effectiveness of the corpus to compare and analyze the experimental and control classes. It was from the study results found that teachers were able to apply the corpus to assist reading instruction in the English reading process, and students’ application of the corpus in the reading process enhanced their participation and interest in reading lessons. The application of the corpus improved students’ higher-order reading reasoning skills, and students learned to think actively and holistically through corpus mapping.
Construction of Non-inherited Digital Platform based on PEST-SWOT Model
Authors: Xiong Wenjing 
Published: June 2023

Abstract
In order to protect non-genetic inheritance, this paper proposes the construction of digital platform for non-genetic inheritance based on PEST-SWOT model. Firstly, the classification of intangible Chinese heritage is summarized and the development of Jiaodong dough plastic intangible cultural heritage is summarized and analyzed by using SWOT and PEST analysis model. Finally, the strategy of digital protection and inheritance of Jiaodong dough plastic is constructed, and the digital information of Jiaodong dough plastic is collected and classified for data collection and archiving by using digital information technologies such as three-dimensional digital scanning of the Internet. To develop the information retrieval system of Jiaodong dough molding, establish the resource database of Jiaodong dough molding with complete, multiple and intuitive information, and record the whole picture of Jiaodong dough molding art in a real and systematic way. At the same time, convenient ways of inquiry exchange and utilization are provided to realize the digital preservation and sharing of Jiaodong dough plastic resources, so as to achieve the purpose of inheritance and dissemination of Jiaodong dough plastic art.
Computer Image Scene and Object Information Extraction based on Bayesian Network Model
Authors: Zhao Hui , Chen Guo 
Published: June 2023

Abstract
In order to better extract scene and object information from computer image, a construction object extraction algorithm based on Bayesian network is proposed. The algorithm is trained by multi-scene aerial images to build a grain dictionary and map the grain in the actual image to the grain dictionary to obtain the scene information of the image;Then naive Bayesian networks were used to model the constraints of the relationship between architectural targets and the spatial context of scene classes, and the extraction of architectural targets was converted into a posteriori probability problem for solving Bayesian network class nodes. The experimental results show that the proposed algorithm can effectively extract architectural objects from aerial images. The experiment result shows that:In this paper, the proportion of target pixels accurately extracted by the algorithm is taken as the standard to define the standard of target pixels accurately extracted by the algorithm to reach more than 90% of the building target pixels. The average time of training an image is 2 s, which is mainly spent on the convolution operation with the filter. After the training, the average time of processing a single test image is 0.5s. It is proved that Bayesian network model can effectively extract scene and object information from computer image.
Dissemination and Evolution of Ethnic Traditional Sports Culture Based on Spatial Diffusion Model
Authors: Wen Zhan 
Published: June 2023

Abstract
Cultural differences in sport have been studied according to the perspective of “culture of inter-normative differences”. Taking the promotion of traditional sports in tourism as an example, the aim is to strengthen the protection and development of athletes who do not know the culture and arts, and to provide theoretical advice to support the development of sports. It was found that the symbols of cultural spaces, sports and tourism products of ethno-cultural combination appeared in four areas: space-temporality, presence, openness and drama. National cultural and artistic leadership and tourism cooperation together are making a difference in the development of the “cultural zone”. Creating a cultural landscape that integrates national culture, sports culture, and tourism services in a unified and symbiotic way will promote the transition from the formation of social leadership trends to individual leadership knowledge and beliefs, and finally to the realization of social development. national sports culture. Those. The combination of national cultural sports and tourism products, and the construction of the epidemic cultural landscape is a process of digging up the traditional culture of a nation to the public and creating tourism products that tourists can use and experience. In this case, it is planned to create a cultural zone for the integration and symbiosis of ethnic culture, sports and tourism services.
The Application of PREMA Model in College Mental Health Education
Authors: Wang Chenxia , Sun Pingli , Li Min , Li Zheng 
Published: June 2023

Abstract
In order to make the mental health education in colleges and universities continue and let students find more of their advantages and potential, the author proposes the application of PREMA model in the mental health education in colleges and universities. The author applied and explored the positive mental health course of 399 subjects for 13 class hours, which included five modules: “positive emotions and happiness, positive cognition and self-efficacy, positive traits and positive personality, positive environment, summary and sharing”, after longitudinal tracking for a school year, the results show that about 34.81% of freshmen have different degrees of problems or confusion in their first class hours, and about 4.22% of them have mild or more psychological problems. After one academic year, the number of students with different levels of problems or confusion dropped to 2.51%, and only 1.04% of students with moderate or above psychological problems. The overall mental health level of students has been improved, and the level of positive development has been improved. The PREMA model not only provides a new perspective for examining college students’ mental health level and subjective well-being, but also points out a new direction for the teaching of college mental health education courses. The course of positive mental health education plays an important role in improving students’ positive mental quality and promoting the development of mental health education in colleges and universities.
Urban park healing landscape based on spatial correlation quantitative model
Authors: Wang Shuhua 
Published: June 2023

Abstract
The construction of city parks is an effective way to ease the tension between people and nature in cities, where the pace of life is fast and the pressure of work is high, relieving pressure and relaxing body and mind has become a common demand of urban residents. In view of this, the study constructs a quantitative model of spatial association to quantitatively analyze the spatial association structure and intensity of park green space and its service objects, create conditions for the measurement of park green space structure and land use efficiency, and fully combine the physiological and psychological characteristics of human beings in the four aspects of Park Components, Park Furniture, Park Zoning and Park Ecological Environment of Brillon Landscape Healing Park, it creates an environment for people to relax and release mental pressure, and plays an auxiliary role in treating psychological and physiological diseases.
Energy Efficiency Evaluation of HVDC Converter Station Based on Deep Neural Network Model
Authors: Rong Jingguo , Qi Lizhong , Wu Hongbo , Chen Songtao 
Published: June 2023

Abstract
This paper introduces a new idea of energy efficiency evaluation of high voltage direct current (HVDC) converter based on deep neural networks. This paper analyzes the leading operating indicators and finds the main influencing factors in constructing the energy-saving hands of each converter table. Then this paper uses the deep neural network method to establish the converter table's energy efficiency model. The deep neural network for energy efficiency evaluation of the converter table is obtained. In this paper, PSCAD/EMTDC was used for simulation to evaluate the energy-saving effect. The research shows that the method of energy efficiency evaluation based on deep neural networks is feasible.
Application and value of painting technique in art education based on improved ARMA model
Authors: Zhao Feng 
Published: June 2023

Abstract
With the deepening of the new curriculum reform, students’ comprehensive quality education has attracted wide attention from all walks of life, and people pay more and more attention to aesthetic education. As an important part of aesthetic education, fine art education plays an important role in cultivating students’ aesthetic ability. In the process of art education, painting technique teaching plays a very important role and value, which is conducive to students’ in-depth understanding of the connotation of painting art and training students’ ability of practice and image thinking. In this paper, ARCS model is used to investigate and analyze the current situation of students’ art learning, and ARCS model is used to design a teaching scheme for reference for art teachers, and teaching experiments are carried out. The concrete implementation methods, steps and case analysis of ARCS motivation model in middle school art teaching design were summarized, and the improvement measures were further proposed according to the experimental results. In the whole research process, a combination of qualitative and quantitative analysis is adopted. The final research shows that it is necessary for teachers to use ARCS motivation model to design teaching programs.
Defect prediction of big data computer network based on deep learning model
Authors: Ma Lei , Li Lihua , Hu Yingbin , Liu Hao 
Published: June 2023

Abstract
Computer network software prediction is a good way to improve software quality, and the predictions of the software prediction method are close to the characteristics of the data set. In order to solve the problem that the invisible size of special data set is too large for computer software prediction, the author proposed a computer network-based software prediction method with deep computer coding and power learning. deep exploration of data features. data features. This type of model first uses an unsupervised learning-based evaluation model to evaluate the data set of 6 open projects, which solves the problem of classification uncertainty in the data; Deep self-encoding network models were then investigated. The model reduces the size of the data set, which is used to connect our model at the end of the model, the model uses training sets of shortened length to train the workers, and finally it makes predictions using the benchmarks. Experiments show that this model's prediction is better than standard software defect prediction, better than existing model-based software prediction models for fabric processes with repeated data volumes, and can be used in different categories. algorithms.
El proyecto de suministro de agua “El Zapotillo”: hechos y percepciones
Authors: Briseño Ramírez Hugo 
Published: June 2023

El objetivo del presente trabajo es describir cronológicamente los hechos que se han suscitado en torno a la presa “El Zapotillo” y analizarlos a la luz del marco de análisis y desarrollo institucional (IAD) de Elinor Ostrom, con la finalidad de examinar la viabilidad del proyecto. Se revisaron fuentes periodísticas, informes técnicos, documentos gubernamentales y el Diario Oficial de la Federación (DOF) con la finalidad de rescatar los principales acontecimientos sobre este proyecto. Como resultados se encontraron elementos que explican las razones por las que el proyecto no se ha concretado. La presa genera muchas dudas e incertidumbres. Existe una situación legal complicada que hace inviable técnica y políticamente su culminación, al menos por ahora.
Peningkatan Pengetahuan Tentang Kesehatan Paru Dan Polusi Udara Pada Pengemudi Ojek Online
Authors: Khairani Rita , Anggiane Mustika , Ayu Woro Dyah , Widowati Henie 
Published: June 2023

The most common source of air pollution in urban areas comes from motor vehicles, which account for 70% of air pollution. Indoor or outdoor air pollution can cause illness and even death. The highest mortality is in countries with low to middle income, namely in Southeast Asia and the Western Pacific region with 3.3 million deaths caused by indoor air pollution and 2.6 million deaths caused by outdoor air pollution. Online ojek drivers are a group of workers who are vulnerable to exposure to air pollution as well as exposure to cigarette smoke. So far no studies or counseling activities have been found, especially regarding knowledge about lung health in online ojek drivers, so it is still necessary to hold health service activities in the form of education about the importance of lung health. The activity was held on Saturday, November 12, 2022 at the Faculty of Medicine Universitas Trisakti, attended by 30 online ojek drivers in the West Jakarta area. The results obtained through this activity are the increased knowledge of participants about the importance of maintaining lung health as evidenced by the increase in post test scores after attending counseling. The conclusion of this activity went well supported by all related parties starting from the institution, the implementation team and partners who actively participated. Suggestions that we can provide by conducting periodic evaluations of behavior change after receiving counseling.
Learning Al-Qur'an Using Asy-Syifaa Method at Islamic Pre-Elementary School
Authors: Muh. Hanif  , Rahma Kemala Dewi  , Abu Dharin  , Florian Pohl  
Published: June 2023

Islamic Pre-Elementary school or Taman Pendidikan Al-Qur’an (TPQ) was a non-formal education in the field of the Islamic religion to create a generation that was Al-Qur’an and has good morals. At TPQ, various methods of learning the Qur'an were used to assist the learning of the Al-Qur’an to teach effectively. The article aimed to describe how the Asy-Syifaa method was implemented in the Al-Qur'an learning process at TPQ MNU Miftahul Ulum. In the implementation of it’s learning, several activities start from opening, core, and closing. This research included qualitative research by using the collecting data of observation and interviews. This research is conducted at TPQ MNU Miftahul Ulum, Kalijambe Village Tarub District, Tegal Regency. The result indicates that the application of the Asy-Syifaa method in learning at TPQ is considered much more effective, which consists of 4 volumes in the Al-Qur'an learning process. The learning stages are opening in class, individual, classical, and closing. Three kinds of evaluation are applied: daily evaluation, volume increase evaluation, and final evaluation of learning the Qur'an. Keywords: Asy-Syifa Method, Al-Qur'an Learning Process, Asy-Syifaa Learning Method
Using machine learning to optimize production training processes in the oil and gas industry
Authors: Ахтямова Д.А. , Волкова К.Ю. , Кащеев С.А. , Максимов С.А. , Шайгатдарова А.Р. 
Published: June 2023

Нефтегазовая отрасль является важнейшей отраслью экономики России, которая вносит значительный вклад в экономический рост и развитие страны. В данной отрасли производственные процессы обучения являются одним из ключевых элементов, которые влияют на эффективность работы предприятий и на достижение высоких результатов. В настоящее время развитие машинного обучения во всем мире наблюдает стремительный рост, и его применение находит все больше отраслей экономики. Одной из таких отраслей является нефтегазовая промышленность, которая активно использует современные технологии, включая машинное обучение, для оптимизации производственных процессов и повышения эффективности добычи нефти и газа. Россия, являющаяся одним изкрупнейших производителей нефти и газа в мире, также активно развивает применение машинного обучения в нефтегазовой отрасли. Однако, в связи с быстрым развитием технологий и изменением экономической ситуации, компании должны готовиться к изменениям и постоянно совершенствовать свои методы и подходы для достижения успеха. В данной статье мы рассмотрим применение машинного обучения в нефтегазовой отрасли России, а также определим, как выпускники вузов, специализирующихся на машинном обучении, могут работать в этой отрасли. Мы также рассмотрим перспективы развития нефтегазовой отрасли в России в будущем, с учетом быстрого развития технологий и изменения экономической и политической ситуации в мире.
The oil and gas industry is the most important sector of the Russian economy, which makes a significant contribution to the economic growth and development of the country. In this industry, production training processes are one of the key elements that affect the efficiency of enterprises and the achievement of high results. Currently, the development of machine learning around the world is seeing rapid growth, and more and more sectors of the economy are using it. One of these industries is the oil and gas industry, which actively uses modern technologies, including machine learning, to optimize production processes and improve the efficiency of oil and gas production. Russia, which is one of the largest oil and gas producers in the world, is also actively developing the use of machine learning in the oil and gas industry. However, due to the rapid development of technology and the changing economic situation, companies must prepare for changes and constantly improve their methods and approaches to achieve success. In this article, we will look at the application of machine learning in the Russian oil and gas industry, and also determine how graduates of universities specializing in machine learning can work in this industry. We will also consider the prospects for the development of the oil and gas industry in Russia in the future, taking into account the rapid development of technology and the changing economic and political situation in the world.
Uzbek maqamat and composers creative
Authors: Абдуллаев Р.С. 
Published: June 2023

В статье рассматриваются вопросы взаимоотношений традиционной музыки и композиторского творчества в музыкальной культуре Узбекистана, в которой макомат в его различных аспектах проявления реализовал свои огромные креативные возможности при создании национальной стилистики в новых жанрах профессионального многоголосного искусства: в музыкально-сценических произведениях (музыкальная драма, опера, балет) В. Успенского и Г. Мушеля, М. Ашрафи, С. Василенко, Т. Садыкова, Р. Глиэра, М. Бурханова, У. Мусаева, И. Акбарова, М. Бафоева; в симфонической музыке Т. Курбанова, М. Таджиева, М. Махмудова и других.
The article deals with the relationship between traditional music and composer creativity in the musical culture of Uzbekistan, in which maqamat, in its various aspects of manifestation, has realized its enormous creative potential in creating national stylistics in new genres of professional polyphonic art: in musical stage works (musical drama, opera , ballet) V. Uspensky and G. Muschel, M. Ashrafi and S. Vasilenko, T. Sadykov and R. Glier, M. Burkhanov, U. Musaev, I. Akbarov, M. Bafoev; in symphonic music by T. Kurbanov, M. Tajiev, M. Makhmudov and others.
Improving the share circulation mechanism of business entities in the agroindustrial complex
Authors: Bychkov N. A. , Metlitskiy V. N. , Neskrebina M. V. 
Published: June 2023

In the Republic of Belarus, the stock market can be attributed to the emerging markets, where its mechanisms and tools are being formed and refined, and the infrastructure is being improved. This is one of the ways to attract the most inexpensive investments in agroindustrial complex, which allows to accumulate available cash assets from individuals and legal entities, while the cost of funds raised by selling a security is in some cases lower than raising credit funds.The article reflects the features of the share circulation. It is systemic in nature and includes a methodology for calculating the increase in the size of the authorized capital of a joint-stock company, in cases of increasing the nominal value of shares at the expense of equity, as well as carrying out an additional issue of shares at the expense of shareholders, third parties (investors). The authors present an algorithm for debt restructuring by increasing the authorized capital of a joint-stock company within the amount of the resulting debt with the transfer of shares (shares in the authorized fund) to the creditor, the procedure for placing additionally issued shares. The article proposes mechanisms for recognizing shares as escheat and exercising the rights certified by shares.