bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the application of SDN technology in cloud computing environment
Authors: Xing Zuohui
Published: December 2024

Openflow is one of the representative technologies of SDN, and it is necessary to process a large number of flow table entries when deploying network resources using this technology in cloud computing centers, which is prone to cause problems such as link congestion. The purpose of this paper is to propose a distributed OpenFlow flow table storage architecture (DSFoF). The architecture uses an improved hash algorithm to determine the deployment of flow table items, achieves centralized management of Openflow switches, and achieves large flow table storage and load balancing. The architecture has an average packet loss rate of 2.52% in the range of 6-10Mbps. The bandwidth utilization is basically higher than 80%, and it can effectively avoid node overload within the threshold. The experiments also show that the architecture can handle the network race and improve the throughput, and the task completion is always higher than 95% when the number of pending tasks is within 100, which has a better performance.
Historical Narrative and Cultural Memory Construction in Film and Television Art
Authors: Peng Liu
Published: December 2024

Historical and cultural films and TV movies focus on recording and presenting historical events, characters, cultural traditions and other contents through audiovisual means, and explore the cultural connotations and values behind them in depth. The study takes the film and television movie “30,000 Leagues in Chang’an” with the background of Tang culture as the case study object, analyzes the audience’s viewing and commenting data of the film and television, and analyzes the method of constructing the audience’s cultural memories by the historical stories and cultural characteristics in the film and television art. The study established the BERT-CCPoem-TextCNN text extraction model. On this basis, the audience’s online comments are mined from the online platform. Preprocessing is carried out in R language, the keywords in the comments are screened, and the theme keywords are cultural symbols such as poems, dresses, etiquette and so on are obtained after generalization. Then, the LDA theme model is used to analyze the direction of the audience’s emotions towards the film and television. According to the results of the theme, word speculation shows that what looks good and attracts the audience lies in the history and characters of films and televisions. The speculative value falls between 0.035 and 0.034. Finally, quantitative statistics are performed on the time changes of characters and events in films and television programs. The results show that the time interval of historical characters’ participation in historical events conforms to the power law characteristic, and the correlation between the importance of character nodes and the frequency of characters’ participation in events is stronger. This can serve as a reference for future work on historical themes in film and television art.
Ergonomics-based Park Trail System Planning and Health Promotion Effect Analysis
Authors: Zhang Wenjin , Wang Qiuhong , Zhang Shaoguang
Published: December 2024

The Park is the most important place for residents to have recreation and leisure, physical and mental relaxation. With the increasing pressure on residents in modern society, people’s needs for park trails are becoming more and more apparent, and designing park trails that meet these needs is becoming an important issue for designers. This paper takes ergonomics theory as a guide and proposes a humanized planning strategy for the park trail system. The first step is to establish a safe and convenient system for organizing trail traffic from the macro-level perspective. The second step establishes an ecological and humanized trail space from the mesoscopic point of view, and the third step designs the landscape of the trail, reflecting the application of ergonomics from the details of the trail design. Human-centered health and ergonomic design principles are integrated into the design. Then, through the application of the design strategy proposed in this paper to design the park, for example, analysis, summarized the park in the design process of the elderly attention is not enough and other urgent needs for improvement, verified that the ergonomics of the park-based on the design of the steps and barrier-free facilities and noise absorption design can meet the requirements of most of the residents travel, and at the same time verified that the ergonomics based on the principles of planning and designing of the walkway height and width and the greening rate are all Meanwhile, it is verified that the height and width of the trail and the greening rate designed based on ergonomic principles are close to the optimal coupling value, which can efficiently carry out the residents’ health promotion activities, and have a significant effect on the residents’ health.
A study on the characteristics of historical evolution of vocal works based on data mining
Authors: Chen Shuyu , Yu Qian , Song Jie
Published: December 2024

Data mining is able to discover the laws and fixed patterns of data in complex data, which has the advantages that traditional data analysis methods do not have, and has been applied to the analysis of musical works in a large number of applications. Firstly, the historical publication data of vocal works is organized, which is used to outline the historical evolution stages and trends of vocal works. The collected information on Chinese vocal works was analyzed with CiteSpace, and multiple vocal works were clustered into five categories based on the theme keywords, and 11 cluster labels were delineated on the basis of the word frequency results. The timeline mapping results show that the creation of Chinese vocal works can be categorised into three periods: the period of development, the period of prosperity, and the period of adjustment. Finally, based on the different periods, it can be summarized that the historical evolution of Chinese musical works is characterized by diversification of themes, singing styles, and musical styles.
Research on the optimisation of the path of ideological and political rule of law education based on big data analysis of legal litigation cases
Authors: Yang Aiai
Published: December 2024

In this paper, K-means clustering technology is used to process the data of legal litigation cases, and the similarity of different types of learners is calculated and clustered. After that, a personalized recommendation algorithm is used to rate legal litigation cases, accurately recommend learning resources based on the evaluation results, and test the recommended results. The clustering results show that calm students are objective and fair in judging legal cases, and the results of the rating are real and reliable (35-80 points), so various types of legal cases can be recommended for them to evaluate and learn. Weak students are composed of lazy, young, and timid students. The results of their resource rating are generally biased. Challenging students are mostly active males who are more interested in learning about lawsuits, with scores ranging from 35-90, and for whom more complex cases with more points of view can be recommended. Lazy students, whose scores on cases span a wide range (0-95 points), should be recommended a small number of simple learning resources of different categories for their reference and learning. Students’ scores improved by 15-17 points after personalized recommendation learning, proving that the recommendation method of this paper improves students’ learning effect on legal proceedings, which is of great significance to students’ ideological and political education on the rule of law.
Quantitative Analysis and Model Optimisation Research on the Enhancement of the Effect of Students’ Civic and Political Education in Colleges and Universities
Authors: Qu Peng
Published: December 2024

The use of existing data analysis tools to analyse students’ data to reflect the achieved teaching effect has been paid attention to by the teaching management department. In this paper, we design a quantitative model for the effect of Civic Education to analyse the clustering of students’ performance in Civic Education in different school years and the correlation between different Civic Education courses so as to carry out a quantitative assessment of the improvement of the effect of Civic Education. The clustering effect can be improved by using a GA-CLARANS algorithm for large-scale data computing. The optimized model is used to analyze the performance of civics and politics majors in School B in the freshman and sophomore academic years. The improvement in the students’ performance is mainly related to the courses they are required to take. Among them, the Pearson coefficients between the six compulsory courses are above 0.5, while the Pearson coefficients between the elective courses are mostly between 0.3-0.5, and the Pearson coefficients between some of the elective courses and the compulsory courses are around 0.5. It shows that the main reason for the improvement of the effects of students’ Civic and Political Education is related to the compulsory course curriculum, and some elective courses can play an auxiliary role.
Research on Content Organisation and Ecological Optimisation Strategies for English Learning in Colleges and Universities Based on Knowledge Graphs
Authors: Sun Ling
Published: December 2024

After years of developing English education in colleges and universities, its ecology is urgently in need of optimization and innovation in today’s rapidly changing environment. This paper introduces the knowledge graph into the study of English learning content in colleges and universities, collects the data on English learning content in colleges and universities, and extracts the effective data from the complicated related information data after constructing the ontology of the knowledge diagram manually. Then, a graphical database is used to store them. Create the entity-relationship joint extraction model, the head entity recognition module, the relationship module, and the tail entity recognition module. Then, correctly extract the entity relationships to build the knowledge graph for college and university English learning content. Conduct similarity matrix analysis and cluster analysis on high-frequency keywords in English learning content at colleges and universities and propose corresponding optimization suggestions. Among the high-frequency keywords in the English learning content of colleges and universities, vocabulary has the highest frequency of occurrence, which is 86 times. The top 6 keywords with the highest frequency are: vocabulary, CET-4, comprehension, CET-6, vocabulary, and expression, in order. The keywords are ranked in descending order of closeness distance: grammar (0.326) > CET-4 (0.285) > CET-6 (0.217) > comprehension (0.134) > expression (0.096). The content of English learning in colleges and universities can be clustered into 3 categories (English application skills, English fundamentals, and specific content).
Quantitative analysis of choir sound integration and practical application of harmonic theory
Authors: Du Shanshan
Published: December 2024

Chorus is a polyphonic vocal art. Sound fusion and harmony are an important basis for measuring the quality of the chorus. How to train many chorus members into fusion, harmony and unity of acoustics is the unremitting pursuit of chorus conductors and chorus members. In this paper, after studying the physical properties of sound and the physiological mechanism of its generation, we use the spectrum analysis method based on acoustic theory to quantify the sound fusion of the choir and introduce the base-2FFT algorithm extracted by time to improve the spectrum analysis method, so as to achieve the audio signal identification and noise reduction of the sound fusion. The analysis of the mixed chorus “The Good Place of the Wujin Sand Sea” shows that the chorus members sang by using the method of head voice straight voice, which can do their best to eliminate each person’s singing individuality and timbral characteristics, and integrate the individual timbre into the collective, and sang with a smooth breath, with the amplitude in the range of [-40,40]. In contrast, the choristers sang using the solo state method, the choristers retained their personalities in their singing, did not integrate their colours into the collective, and the sound between the voices was not sufficiently balanced in their singing, with amplitude values between [-80,80]. The use of spectral visualisation allows conductors to control musical elements more accurately in the professional practice of rehearsing choral works.
Research on Optimization Strategy of Agricultural Water Conservancy Costs Based on Clustering Algorithm
Authors: Ma Yongren , Wang Jiao , Zhu Meiling
Published: December 2024

In the process of agricultural water conservancy cost management, capital control belongs to a core content. This paper proposes optimization strategies for the costs incurred in agricultural water conservation, mainly taking agricultural water conservation in agricultural water conservation projects as an example to carry out research. The study uses SPSS software to fit the distribution of the various influencing factors in the unforeseeable costs of agricultural water conservancy projects to analyse and establish an unforeseeable cost rate estimation model and then uses the Monte Carlo method to simulate the unforeseeable factors of agricultural water conservancy project data for the last three years in a city in a certain province A. Finally, the algorithmic performance of the FCM clustering method proposed in this paper is compared with the experiments, and the performance of the algorithms is compared to that of the algorithms according to the FCM. An algorithm to mine cost data for agricultural water conservation projects, study the relationship between project time, cost, and total cost, and propose strategies for optimizing agricultural water conservation. The results show that the algorithm proposed in this paper performs well and meets the requirements followed the unforeseeable cost rate of the agricultural water conservancy project is 5%, which is in line with the actual situation, while the total cost of agricultural water conservancy is roughly in a positive correlation with the cost cost, and the higher the cost cost is, the higher the total cost of the project is.
A Study on the Construction of a Computational Model for Online International Chinese Cultural Diffusion Based on Minecraft
Authors: Sun Wei
Published: December 2024

In order to understand the online international dissemination of Chinese culture through online games, this paper constructs a computational model of cultural dissemination based on a hypergraph. The model constructs a network topology based on hypergraph theory, divides the states of individuals spreading Chinese cultural information in online social networks, and calculates the transfer probability of individual states based on the rules of cultural information spreading. The analysis of the algorithms reveals that the maximum infection ratio of the model in this paper decreases slowly, and the coverage rate of immune nodes reaches 0.9, indicating good stability and adaptation performance. The model accurately simulates the process of Chinese culture diffusion in the Minecraft community. The mean value of the evaluation of the six entries on learning motivation and attitude is 3.73 points, which indicates that the use of Minecraft helps improve students’ motivation for learning about Chinese culture.
Computer Vision Technology Integration and Art Education Practices for Modern Printmaking
Authors: Yan Weina , Wang Dewei , Meng Jun
Published: December 2024

Printmaking has a long history and high artistic value, and it is challenging research to integrate computer vision technology into artists’ printmaking process. In this paper, the line, texture, and frequency features of modern prints are extracted according to their artistic characteristics and then restructured by a convolutional neural network. The parameters of the conversion network are updated using gradient descent, and CLIP is used as a pre-training model to establish a modern printmaking-style migration algorithm. Computer vision technology is used to construct a modern printmaking digital image simulation and synthesis system. Practice shows that the usability of the system is 67.675, which is close to the level of”good”in the process of creating modern printmaking art by art students. The system’s diverse features of real-time interaction, integration of digital resources, virtual scene construction and autonomous learning further enhance the cultivation of modern printmaking creative ability and have high practical significance in art education value.
Optimised design of digital teaching resources for Civic and Political Education in colleges and universities under the integration of big data technology
Authors: Xie Shufang
Published: December 2024

It is impossible to separate the design and development of teaching resources from the teaching of ideological education in colleges and universities. However, the current digital teaching resources for ideological education exist in large quantities and vary in quality in many colleges and universities. In order to tackle these issues, the study employs big data technology for optimization. Specifically, it proposes an Apriori improvement algorithm, which is based on MapReduce parallelism, and an enhanced hybrid K-Means clustering algorithm, which is based on an intelligent single-particle algorithm. The optimized algorithms are then applied to the optimal design of digital teaching resources for civic and political education in a university. When the order of Civics courses is well switched, students have an 81.2% probability of getting “good” grades. The K-Means clustering algorithm divides 31 types of digital teaching resources for civics education in colleges and universities into 3 categories to enhance the quality of teaching.
A Study of Key Elements of Computer Linguistics Extraction Based on Artificial Intelligence NLP
Authors: Wang Liang , Tan Jinlin , Wang Weiming , Chang Wenjie , Zhang Min , Liu Yan , Wang Wei , Shi Baobao , Zhao Pengpeng
Published: December 2024

Key element extraction is an important research field in computational linguistics. Based on the Hidden Markov Model in natural language processing technology, this paper utilizes the Viterbi decoding algorithm, along with its optimization and improvement algorithms, to construct a key element extraction model. This model then extracts the key legal elements from the original corpus of traffic collision litigation cases. To further validate the performance of this paper’s model, a public newspaper dataset released by a university was selected to deeply explore its effectiveness. This paper’s model significantly improves the accuracy and F1 values of the key elements of legal text extraction, reaching 93.28% and 90.83%, respectively, compared to all other models. The model’s extraction effect on the six key elements in the legal text reaches an ideal state, where the F1 value of the extracted element’s sentence results reaches 100%. In comparison to the HMM model in the public dataset, the model in this paper has improved by 10.93%, 8.78%, and 10.29% in the three indexes, indicating its superior performance in key element extraction.
Research on the Strategy of Curriculum Ideology and Politics in Improving the Comprehensive Quality of College Students Based on Intelligent Education Technology
Authors: Li Cheng , Dong Yinxia
Published: December 2024

This paper integrates intelligent educational technology into the political thinking course, constructing a learning system based on recommendation technology to cater to students’ personalized learning needs and enhance their overall quality. This paper establishes that the core function of the learning system is to recommend personalized educational resources for students. The recommendation algorithm based on collaborative filtering and the recommendation algorithm based on content are combined to form a hybrid recommendation algorithm, which is used to design and implement the learning system with B/S architecture. We create the evaluation system for students’ comprehensive quality by selecting scientific indicators and calculating the gray correlation between their scores and comprehensive quality. The results show that the correlation between ideology and morality and students’ comprehensive quality is 0.75836, which ranks the highest among all indicators. Simultaneously, a comparison of the evaluation scores for each index of students’ comprehensive quality before and after the implementation of the ideology and politics learning system in this paper’s course elucidates the significance of incorporating these elements into the course through intelligent educational technology, thereby enhancing the overall quality of students.
From Single Mode to Integrated Parenting: A Study on the Intelligent Level of Student Management and Parenting in Maritime Vocational Characteristics Colleges and Universities by Internet of Things (IoT) Technology
Authors: Chen Maojia
Published: December 2024

Student management and nurturing is an important part of the education system of colleges and universities. To address the issue of student management and parenting work in nautical vocational colleges and universities, this paper develops a student management system that utilizes IoT technology. The RFID system, front-end operation and back-end management system in the Internet of Things technology constitute the main structure of the student management system of this paper for nautical vocational colleges and universities, and the system carries out tests such as multi-tag reading time to verify the effectiveness of this paper’s student management system. The density peak clustering algorithm, undersampling algorithm and improved Adaboost algorithm are used to construct the student academic abnormality prediction model, while the K-means clustering algorithm is used to cluster and analyse the students’ consumption behaviour. The DP-2W-Adaboost model constructed in this paper effectively improves the overfitting phenomenon caused by noisy data, and compared with the DP-Adaboost algorithm, the SE value is improved by 7.91%, the SP value is improved by 3.40%, in the F1 value is improved by 9.60%, and in the G-mean metric is improved by 5.39%. 1057 students with real academic abnormality were found by the DP-2W-Adaboost model in the prediction of student academic abnormality. K-means clustering algorithm clusters student consumption behaviour into 3 categories by analyzing the mean value of total student consumption data and single consumption data, which provides data support for student management and parenting work in nautical vocational featured colleges and universities.
Research on enterprise economic efficiency assessment and management decision-making based on big data analysis
Authors: Du Qian , Sun Libing
Published: December 2024

Enterprise economic efficiency is an important indicator for measuring the input and output of enterprises, and it has a certain guiding role in the formulation of enterprise management decisions. This paper constructs an enterprise economic efficiency assessment model using big data analysis and explores the application of big data analysis in enterprise management decision-making. First, we extract the principal component factors for measuring enterprise economic efficiency indexes using principal component analysis, and then construct the comprehensive evaluation function of enterprise economic efficiency based on this. The particle swarm algorithm is used to optimize the BP neural network, and the PSO-BP neural network model is constructed to intelligently evaluate the economic efficiency of the enterprise. This paper extracts three principal components of enterprise economic efficiency, namely “enterprise solvency and profitability,” “enterprise operating ability,” and “net asset growth ability,” and achieves a cumulative variance explanation rate of 84.431%. The PSO-BP neural network model and the standard BP neural network model satisfy the error criterion of MAPE<0.001 when they are trained about 170 times and 820 times, respectively, and the number of operations of the former is only about 20.73% of that of the latter, which greatly shortens the running time of the model and indicates that the PSO-BP-based enterprise economic efficiency assessment model in this paper is practical. Practicality. This paper serves as a reference for the application of big data analysis in enterprise economic benefit assessment and management decision formulation.
An Exploration of the Application of Virtual Reality Technology in Enhancing the Interactive Experience in Online Education
Authors: Gao Xiaoli
Published: December 2024

Virtual reality is the process of new development in the new era. The continuous development of education technology is always fueled by the application of new technologies in the field of education and teaching, even though the technology has not yet matured. In this paper, 3D scanning technology is used to construct a three-dimensional scene after collecting point cloud data from the online education environment. The motion capture instrument is used to collect the action characteristics of teachers and students in the online education classroom, and the Kalman filter algorithm is used to process the data for the recognition of interactive actions. Based on this, the online education teaching system based on virtual reality technology is constructed to achieve good interaction between teachers and students in teaching. The results of the teaching experiment show that the post-test learning performance of students in the VR group who learned through virtual reality is better than that of the traditional group, and the pre and post-test scores of students’ learning motivation in the VR group are improved in all dimensions, and all of them reach the level of significance (P<0.001). Additionally, the language of students in VR classroom teaching saw a significant improvement (34.99%), and they gained a positive interactive experience. This paper found that virtual reality technology has a positive impact on student motivation and learning outcomes, which lays the foundation for promoting students’ interactive experiences and learning outcomes in online education.
Construction and Application of Personalised Classroom Teaching Model of College English Combined with Recommendation Algorithm
Authors: Liu Qinli
Published: December 2024

This paper primarily designs and implements a collaborative filtering recommendation algorithm, which is based on user, content, and student profiles. It constructs the user’s learning style or learning interest by analyzing the user’s historical behaviors, and then generates recommendation results by searching for the required information in the information resource database. Through the learner’s basic personal information and behavioral data, the learner is profiled, and the user profile is constructed to achieve personalized teaching in the English classroom, thus realizing the personalized classroom teaching mode combined with the recommendation algorithm. The results indicate that the average heat value of text-based English teaching resources in the cloud classroom is 0.220, higher than that of video-based resources. In terms of time commitment, most students have low levels of commitment to online learning, with all of their online learning hours being under 150 hours. The personalized classroom teaching mode can significantly improve students’ overall performance compared to ordinary teaching methods (p<0.01).
Research on the New Path of Business English Talent Cultivation in Higher Vocational Colleges in the New Era
Authors: Ran Li
Published: December 2024

With the advent of the Internet + era, business English presents many new development situations and characteristics, which puts forward new and higher requirements and challenges for the cultivation of higher vocational business English composite talents. Based on the stakeholder model, this paper extracts the participating subjects of the industry-teaching integration project, and their main motivational elements. Based on the synergy model, it identifies the internal and external synergistic elements of industry-teaching integration and builds a model of internal and external synergistic mechanisms, which lays a theoretical foundation for the subsequent proposal of innovative paths of business English talent cultivation in higher vocational colleges. From 64 policies on industry-teaching integration in higher vocational colleges, synergistic elements of industry-teaching integration talent cultivation are identified, and the fuzzy set qualitative comparative analysis method is used to explore the combination of synergistic elements that can improve the effectiveness of industry-teaching integration talent cultivation projects, i.e., the new path of business English talent cultivation. The study found that enterprise size, discipline type, project motivation, project action, and project constraints are five conditional variables of the industry-teaching integration project. The necessity analysis of individual condition variables found that the consistency and coverage of the five variables did not exceed 0.8 at the same time, indicating that none of the five condition variables could be a necessary condition. Under the condition that the 5 conditional variables are combined, 5 innovative paths of collaborative industry-education cultivation of business English talents are obtained, and the coverage and consistency values of the paths are 0.808042 and 0.913024, both exceeding 0.8, which are able to explain adequately the high performance of collaborative talent cultivation in higher vocational colleges and universities.
A Study on the Impact of Digital Marketing Strategies on Consumers’ Purchase Intention - A Case Study of Social Media Advertising
Authors: Liu Guangqian , Zhu Yiming
Published: December 2024

The advent of the social media era has catapulted the advertising industry into a new phase, marked by a decline in traditional media advertising and a gradual dominance of digital media marketing modes that rely on social media platforms. In fact, these modes have become the primary source of revenue for some social media platforms. This paper explores the influence of different qualities of digital media marketing on consumers’ purchase intentions. Using the technology acceptance model, the theory of planned behavior, the expectation confirmation theory, and other consumer psychological analysis tools, the latent variables of perceived usefulness, perceived ease of use, and subjective norms of social media advertisements are established to complete the conceptual model of the mechanism of action as well as the establishment of the corresponding research hypotheses. Questionnaires are designed and randomly selected by consumer users on social media platforms as research samples. The collected data from the processed questionnaires were inputted into the structural equation model for validation. The model’s output confirms the support for all hypotheses, with a significance level below 0.05. Among them, perceived ease of use has the greatest degree of influence on satisfaction, and consumer satisfaction with social media advertisements largely depends on how easy or difficult it is for users to use the advertisements. Perceived usefulness and satisfaction have significant positive effects on consumers’ final purchase intentions, and satisfaction is more direct and obvious. This study successfully reveals the complex path of action between various types of consumer perceptions and purchase intention in social media advertisements, providing direct evidence for the optimization of digital marketing strategies.
A study on the perception of sense of meaning of life and positive psychological communication law based on social media data analysis
Authors: Zhang Hui , Zhu Ming
Published: December 2024

In modern society, social media has become an important platform for individuals to express themselves and communicate their thoughts and emotions, which profoundly affects our perception of the sense of meaning in life and the spread of positive psychology. The research design for theme identification and sentiment analysis based on social media data includes five steps: data collection, data cleaning, TF-IDF calculation, theme clustering, and sentiment analysis. In this paper, we take the “Xin Guan epidemic” as a case study to identify the core topics of discussion on the sense of meaning of life and assess the sentiment tendency of users under these topics so as to reveal the influence of the perception of the sense of meaning of life on the dissemination of positive psychology on social media. A total of 11 topics related to the sense of meaning of life were obtained from the microblogging platform, and each topic effectively promoted the positive psychology of social media users. It is shown that the perception of the meaning of life is positively related to the spread of positive psychology.
Research on the role of computer-aided design technology in the innovation of ceramic ware surface decoration
Authors: Zhang Xingrong
Published: December 2024

With the development of the times, on the basis of inheriting traditional ceramic decoration, modern ceramic decoration is also changing, and it is moving towards personalisation and diversification. In this paper, firstly, we preprocess the images of the decoration features on the surface of ceramic vessels and use the LBP feature extraction method to extract the detailed features on the surface of ceramic vessels, transform them into HOG data, and represent the pattern information by histogram. Subsequently, an attention mechanism is added to achieve accurate segmentation of ornaments on the surface of ceramic vessels by learning the semantic features of the image. Then, based on the CGM model, the extracted ornament is deconstructed and restructured to design new ornament elements, which are applied to the surface of ceramic vessels. The investigation of the market demand for ceramic ware surface decoration was done to create a data base for ceramic decoration design. The research results show that 53.456% of users buy ceramic ware mainly because of daily use, and 49.563% pay more attention to the color pattern of ceramics. In the characteristic colours of ceramic patterns completed in the design, the characteristic colours 1→2 and 1→5, the correlation between the two groups of characteristic colours is strong, and the intensity is 3.554 and 4.265, respectively.
Strategies and Practices of Artificial Intelligence Technology in Open Education Serving Elderly Education
Authors: Qi Zhiming
Published: December 2024

This paper discusses the study of open education services for the elderly education and proposes the Internet + elderly education model. Two senior classes were selected as the research object and divided into experimental and control groups, with the experimental group adopting this paper’s education model and the control group adopting the traditional education model. After the questionnaire reliability test, the online and offline distribution of questionnaires to obtain the data of this paper, borrowing the independent samples t-test in the knowledge of statistical theory, from the theoretical knowledge, basic skills, and emotional value dimensions of this paper’s educational model for verification and analysis. The data show that the reliability and validity of the questionnaire are 0.870 and 0.8797, respectively, which meets the rigour of the questionnaire. In addition, there is a significant difference (P<0.05) in theoretical knowledge, basic skills, and emotional value of this paper’s educational model, which indicates that this paper’s educational model has an important effect of enhancing the practice of open education to serve the elderly education, and puts forward a three-point strategy of artificial intelligence technology in open education to serve the elderly education.
Study on Improving the Communication Effect of Ideological and Political Education in the Face of New Media Environment
Authors: Su Yanhua , Xu Dan , Hu Xuefeng , Zhang Lu , Zheng Dan
Published: December 2024

According to the problems of ideological and political education communication in the context of new media, the factors influencing the effect of ideological and political education communication in the new media perspective are elicited. Combined with relevant resources and experts’ opinions, the questionnaire design is completed directly, and research data is obtained by distributing questionnaires. A comprehensive Pearson correlation coefficient and a multivariate linear regression model are used to explore the communication effect of ideological and political education in the face of the new media environment. The data revealed that the regression equation for the dissemination effect of ideological and political education is as follows: 0.66+0.357* Communication subject (X1)+0.243* Communication medium (X2)+0.199* Receiver (X3)+0.186* Communication environment (X4). This equation demonstrates significance at the 0.05 level and proposes a two-point strategy to enhance the dissemination of ideological and political education in the context of new media.
Strategies and Practices of Intelligent Algorithms in Dynamic Allocation of Teaching Resources in Primary Education
Authors: Sun Yanting
Published: December 2024

Based on an analysis of the current state of teaching resources in primary education, this paper summarizes the challenges these resources are currently facing. In order to improve the above situation, it is proposed to introduce the theory of resource dynamic allocation strategy into primary education teaching. The fuzzy association algorithm, which leverages big data technology, extracts resource features, calculates the fuzzy association feature quantity of teaching resources, and facilitates the integration of these features in primary education through priority scheduling and dynamic allocation techniques. Based on the actual situation, determining the constraints and objective function, and finally completing the mathematical modeling work, the genetic algorithm can be used to solve the optimal dynamic allocation strategy of educational teaching resources. This paper used selected experimental data from simulation experiments to verify the dynamic allocation model of teaching resources. The recall of this paper’s method (0.261) is significantly higher than that of the other two methods (0.163, 0.155), and similarly, this paper’s method has superiority in utilization, load balancing, latency, efficiency, throughput, and practical satisfaction. This study is able to achieve efficient teaching resource allocation and provide better teaching resources for primary education teaching practice.
A Study on the Enhancement of Learners’ Language Proficiency by English Situational Simulation Teaching Based on Virtual Reality Technology
Authors: Wan Yan
Published: December 2024

Virtual reality technology has a high priority in the field of English language teaching, and it is used to enhance learners’ language proficiency through the way of integrating virtual reality technology into the process of English language teaching in colleges and universities. In order to confirm the hypothesis, freshman and junior students of a university were selected as the research subjects and the English teaching model of this paper was set as the experimental group, while the traditional English teaching model was the control group. Combining the scale data and independent samples t-test, the four dimensions of listening (listening), speaking (speaking), reading (reading in writing) and writing (writing) confirm the effect of this English teaching model on students’ language proficiency. In the dimensions of students’ listening (listening), speaking (speaking), reading (written reading), and writing (writing) abilities, there is a significant difference between the traditional English teaching mode and the English teaching mode of this paper (P<0.05), which greatly confirms the facilitating effect of the teaching mode of this paper on the enhancement of the language ability of the learners.
The Educational Value and Implementation Strategies of Sports Data Mining Techniques in Physical Education Courses
Authors: Xing Qiang
Published: December 2024

Driven by science and technology, the amount of information in today’s society has increased at an unprecedented rate, and the explosion of big sports data has brought challenges to the development of sports data mining. For the education of physical education courses, in order to comply with the educational requirements of the times, based on the rise of the sports recognition model in recent years, this paper carries out sports recognition and evaluation on the basis of data mining to achieve the auxiliary efficacy of physical education course teaching. The study first conducted an in-depth analysis of the data mining technology, and then in order to guarantee the accuracy of the sports behaviour data, this paper compared and analysed different processing methods so as to select a third-order low-pass filter. Subsequently, a sports recognition and assessment model based on the random forest algorithm is proposed, and in the comparative analysis of the algorithms, it can be seen that the recognition method in this paper has the best recognition and assessment effect, and the average recognition rate is as high as 0.924. Based on this, this paper constructs an education management system for the education of physical education courses, which is composed of a data source, a data access layer, a data storage layer, a data analysis layer, an application layer, and a support function, and finally, it takes 30 students of M Physical Education College as the experimental objects to carry out the teaching experiment and to analyse the actual performance base of the students. Before and after the teaching experiment, the experimental group based on the teaching system of this paper to assist in teaching the performance of all indicators by a significant improvement, and P is less than 0.05. At the same time, after the teaching experiment, its average performance is much higher than the control group, which shows that this paper is based on the data mining construction of the physical education teaching system that can actually improve the effect of physical education courses.
Effects of speed, agility, and quickness training on grass versus sand surface on sprinting, jumping, and change of direction performance of amateur male soccer players
Authors: Narvariya Pushpendra , Rathore Prakhar , Dhull Mohit , Kumar Ajit , Pal Inder S. , Sarmah Bhargav , Thapa Rohit K.
Published: December 2024

Study aim

The study compared the effects of speed, agility, and quickness (SAQ) training performed on grass versus sand surfaces on improvements in sprinting, jumping, and change of direction speed (CODS).

Materials and methods

Twenty-four male university soccer players were randomly assigned to SAQ training on grass or sand surfaces. The intervention lasted four weeks with a weekly frequency of two sessions. The variables assessed were 30-m linear sprint, CODS, countermovement jump (CMJ), drop jump (DJ; jump height, ground contact time [GCT], reactive strength index [RSI]), squat jump (SJ), standing long jump (SLJ), and triple-hop distance. A two-by-two mixed design ANOVA was used to analyze the training effects.

Results

A significant positive main effect of time was observed for CMJ, DJ, and SJ height (p < 0.001) and triple-hop distance, with significant pre-to-post improvement in both groups (all p < 0.001). In addition, a negative main effect of time was observed for DJ GCT and DJ RSI (p = <0.001–0.024), with a significant increase in DJ GCT for both groups but a significant decrease in DJ RSI only for the group training on sand. No main effect of time was found for the 30-m linear sprint, CODS, or SLJ distance (p = 0.080–0.792). An interaction effect on CMJ height was noted (p = 0.027), favoring the group training on the sand surface.

Conclusion

SAQ training on grass and sand surfaces showed similar improvements in the DJ, SJ, and triple-hop performance. However, compared to the grass surface, training on the sand surface induced greater improvements in CMJ but showed negative effects on DJ RSI.
Sustainability of Shared e-Scooter Services in Riga
Authors: Rubenis Aivars , Celms Armands , Adrian Leslie , Garkevics Martins
Published: December 2024

This study examines the shared electric scooter usage patterns in Riga across 2021 and 2022 and assesses the potential for reducing greenhouse gas emissions in the city’s urban transport system. Analysing 3.9 million scooter trips over the two-year period, the research highlights a tripling in the use of shared scooters and a shift towards shorter rides, resulting in an average use of only 7 km per day per scooter. This trend has resulted in CO2 emissions to 54.16 g CO2 per passenger kilometre, raising the total emissions from shared scooters in 2022 to 163.3 tonnes, and in fact increasing the net transportation CO2 emissions in Riga by 49.2 tonnes, by largely replacing zero-emission modes of transport like walking. In response to these challenges, the research explores the implementation of photovoltaic (PV) energy-powered charging docks as a method to maintain scooter operations. While energy consumption is not the largest contributor to the scooters’ CO2 emissions, by also eliminating the need for scooter transportation for charging the adoption of on-site generated PV energy could yield a substantial CO2 emission reduction of up to 34 %. This approach could hypothetically result in a 71-tonne reduction in CO2 emissions from electric scooters, thus potentially establishing scooters as a net positive influence to Riga’s transport emissions, producing a net 11 tonne CO2 emisssion reduction.
NIPPING IT IN THE BUD: EXPOSING THE FOUNDATIONS OF #METOO THROUGH THE LIBERATION OF SITA
Authors: SHIRODKAR Preeti
Published: December 2024

The #MeToo movement has largely focussed on exposing sexual abuse, sexual harassment and rape culture, in an attempt to rid it of shame and build solidarity and empathy. However, it is important to actually delve into the roots of the unfair treatment that is meted out to women and their stereotyping, at times as a misplaced understanding or display of love, to expose the mindset that helps in justifying actions of cruelty and violence. Unearthing this palimpsest cannot merely aid in exposing what lies at the root of unjustifiable actions, but can also contribute, over time, in nipping the issue in the bud rather than protesting or tackling its manifestation. Written by Volga in Telugu as Vimukti, The Liberation of Sita a novella or as the author likes to call it a collection of stories revolves around the lives of 5 women from Ramayana, each finding her identity and realising that to a great extent she too was a victim of patriarchal structures and beliefs that both makes injustice possible and unfortunately often gives it a stamp of acceptability, which is what the #MeToo movement seeks to protest. By choosing to examine characters from mythology, The Liberation of Sita draws attention to where it all begins both in context of time and space. Reclaiming the mythological space and trying to rid it of its patriarchal stronghold, the book moves the focus from the manifestation to the mindset that generates and justifies it. This paper would explore and expose this paradox in an attempt to comment on the need to nip the issue in the bud by observing and questioning the mindset that makes #MeToo possible.