With the continuous progress of science and technology and the acceleration of global informatization, online education, as a new educational model, is gradually becoming an important way for people... Show More

With the continuous progress of science and technology and the acceleration of global informatization, online education, as a new educational model, is gradually becoming an important way for people to learn. How to effectively transform massive learning data into educational benefits is a major challenge facing the development of online education at present. This paper focuses on the students who learn English online, and uses big data and machine learning technology to build a prediction system for each student's English course performance. The system predicts academic performance according to students' individual learning situation, helps teachers to give targeted guidance and improve the overall teaching quality. The results of questionnaire survey show that most students think that the prediction system can accurately predict English academic performance, which is of great help to improve the learning effect. The system has a friendly interface and is easy to operate.

As a teaching method that integrates online and offline teaching resources, the application of blended teaching mode in landscape design professional courses has attracted much attention. With the... Show More

As a teaching method that integrates online and offline teaching resources, the application of blended teaching mode in landscape design professional courses has attracted much attention. With the background of landscape design professional teaching, this paper carries out in-depth research and analysis on the definition, advantages and application of blended teaching mode in landscape design professional teaching. By means of questionnaire survey, this paper evaluates the application effect of the blended teaching mode of Blue Ink Cloud Classroom in landscape design majors in colleges and universities. Therefore, by comprehensively and systematically discussing the application of blended teaching mode in landscape design professional courses, the article provides useful reference and inspiration for the teaching reform and development of landscape design majors. It is hoped that the research results of this article will have a positive impact on the application of blended teaching mode in landscape design majors.

This study integrates Protection Motivation Theory (PMT) with cultural dimensions to design a cybersecurity education framework tailored to Kuwait. The study uses advanced analytical techniques like... Show More

This study integrates Protection Motivation Theory (PMT) with cultural dimensions to design a cybersecurity education framework tailored to Kuwait. The study uses advanced analytical techniques like K-means clustering and Association Rule Mining (ARM) to find important patterns in how age, education level, and cultural norms (like religious adherence and family reputation) affect how people act online safely. The findings highlight key gaps in awareness and coping mechanisms, informing a framework that incorporates gamification, microlearning, and culturally relevant scenarios. We design these strategies to enhance engagement and foster meaningful behavioral change. Although we developed the framework for Kuwait, its scalable design ensures applicability to other culturally diverse regions, offering a replicable model for improving global cybersecurity awareness and resilience.

This manuscript explores an innovative vocational education evaluation system designed based on the theory of multiple intelligences. Aimed at enhancing the structure of educational content and... Show More

This manuscript explores an innovative vocational education evaluation system designed based on the theory of multiple intelligences. Aimed at enhancing the structure of educational content and training materials, the system's effectiveness is validated through rigorous pre-test and post-test simulations. Results from paired sample t-tests (P<0.05) indicate a significant improvement in students' linguistic intelligence, demonstrating the theory's positive impact on educational outcomes. This study supports the practical application of multiple intelligences theory, offering empirical evidence for future educational reforms and emphasizing the importance of identifying and cultivating diverse intelligences in students to promote their comprehensive development and success.

Eco-sports teaching serves students' physical and mental health and pays attention to the interaction between natural environment and people, which is one of the teaching methods in line with the... Show More

Eco-sports teaching serves students' physical and mental health and pays attention to the interaction between natural environment and people, which is one of the teaching methods in line with the current teaching reform trend. From the perspective of students' sustainable and healthy development, this paper studies the influence of urban PM2.5 concentration on students' physiology and psychology.It is found that when PM2.5>100 ug/m3, the frequency of students' medical treatment and the rate of abnormal pulmonary ventilation function will increase. Based on 857 valid questionnaires and Pearson correlation analysis,the research shows that when the concentration of PM2.5 increases,the air visibility changes and the air smells,it is highly correlated with the psychological stress of students. Creating physical education courses suitable for high PM2.5 concentrations both meets students' needs and promotes sustainable development of ecological physical education classes.

The study utilizes structural equation modeling to examine issues related to normality, missing data, and sampling errors in digital marketing engagement research. The primary focus is on exploring... Show More

The study utilizes structural equation modeling to examine issues related to normality, missing data, and sampling errors in digital marketing engagement research. The primary focus is on exploring relationships between self-esteem, social comparison, social interactions, perceived social support, and psychological well-being, with perceived social support as a mediating factor. Confirmatory factor analysis is applied to evaluate model fit using data from 400 social media users. Skewness and Kurtosis values are assessed to ensure normality, with scores kept within the acceptable range of -2 to +2. Questionnaires with over 30% missing values are excluded to maintain data quality, and the “10-times rule” is used to ensure adequate sample size and reduce sampling errors. Results confirm a normal distribution and indicate that the model aligns with SEM assumptions, meeting all fit indices. The research offers insights into SEM's application in digital marketing and suggests future studies should investigate advanced modeling techniques for further exploration.

Nowadays, with the rapid development of the Internet, the use of electronic mobile terminals such as mobile terminals has become very popular, and people who are at the forefront of the times are... Show More

Nowadays, with the rapid development of the Internet, the use of electronic mobile terminals such as mobile terminals has become very popular, and people who are at the forefront of the times are almost completely covered by electronic mobile terminals such as mobile phones. The traditional physical fitness test becomes more complicated and often needs the help of others. Therefore, this paper mainly introduces the new technology of intelligent health fitness testing based on the mobile terminal, discusses its application at home and abroad, and puts forward some suggestions for promoting physical fitness testing. The evaluation criteria of healthy physical fitness items are introduced, and make full use of the characteristics of mobile Internet to realize real-time physical fitness testing. Intelligent physical measurement is of great significance to promote the development of physical fitness testing in China.

The study aimed to investigate the computational thinking traits of third-grade middle school students while using RoboMind for programming within a project-based learning setup. It also aimed to... Show More

The study aimed to investigate the computational thinking traits of third-grade middle school students while using RoboMind for programming within a project-based learning setup. It also aimed to determine if incorporating RoboMind into project-based instruction improved students' computational thinking skills, attitudes toward programming, and programming performance based on project outcomes. Implemented through a quasi-experimental design with 138 students from two Saudi Arabian schools, the results indicated a significant improvement in computational thinking skills and positive changes in attitudes toward programming post-RoboMind implementation. The study identified four primary dimensions and seven sub-dimensions of computational thinking, emphasizing its diverse aspects. Furthermore, notable correlations were found between RoboMind project scores and post-RoboMind computational thinking scores in the experimental group. These findings advocate for the integration of RoboMind into programming education, especially within Saudi Arabian educational institutions.

Work engagement is crucial in organizational development as it improves and enhances performance and innovative behavior. This is influenced by personal, work environment, and other factors.... Show More

Work engagement is crucial in organizational development as it improves and enhances performance and innovative behavior. This is influenced by personal, work environment, and other factors. Therefore, it is worthwhile to study whether and how contemplation as a personality trait affects work engagement. This study extends previous research on contemplation and work engagement by introducing emotional intelligence to construct mediation and regulation models A questionnaire survey was conducted on the contemplation, emotional intelligence, and work engagement of 930 employees in central enterprises. Our results indicate that contemplation has a significant negative predictive effect on work engagement This study enriches the research on rumination and work engagement by revealing the impact of rumination on work engagement. Our research has certain implications for enterprises to improve their employees' mental health level and work engagement.

This study aimed to investigate the relationship between mobile technology-based music education and employee well-being and corporate digital economic benefits within the biotechnology industry. A... Show More

This study aimed to investigate the relationship between mobile technology-based music education and employee well-being and corporate digital economic benefits within the biotechnology industry. A mixed-methods design was employed, combining quantitative and qualitative research techniques. Employees reported positive perceptions of mobile technology-based music education programs. There is a positive correlation between employee engagement and company revenue, suggesting that engaged employees contribute to organizational success. Music education programs can lead to increased productivity, reduced employee turnover rates, and improved company reputation. Employees reported reduced stress and anxiety, improved mood and morale, and increased resilience. Additionally, the programs were found to enhance job engagement, improve work-life balance, and foster creativity and innovation. From a corporate perspective, music education programs can be associated with improved employee retention, enhanced company culture, and increased productivity and efficiency.

Wireless communication technology is playing an increasingly important role in society. In view of the current situation of physical education teaching in colleges, the construction of a sports... Show More

Wireless communication technology is playing an increasingly important role in society. In view of the current situation of physical education teaching in colleges, the construction of a sports network teaching platform is conducive to students' autonomous, collaborative and exploratory sports knowledge and skills. This paper presents a method of evaluating the quality of physical education teaching in Colleges based on a wireless communication system. This method is based on a wireless communication system and is used for information exchange between students and teachers in physical education. After collecting the information, the evaluation of college physical education teaching quality is realized on Matlab based on analytic hierarchy process and BP network. The results show that this method successfully solves the problems of incompleteness and subjectivity when experts determine the weight of college physical education teaching indicators in the past, and realizes the prediction and warning function of college physical education teaching based on wireless communication systems.

In order to promote the development of personalized recommendation system in the tourism industry, this study adopts a machine learning collaborative filtering algorithm model, and uses data... Show More

In order to promote the development of personalized recommendation system in the tourism industry, this study adopts a machine learning collaborative filtering algorithm model, and uses data provided by users and data mining technology to reduce the overload of Internet messages and provide customized content recommendations. The construction of tourist attractions recommendation model based on machine learning is 18% better than the traditional algorithm under the demand of tourists' “slow life”. This research can effectively solve the problems of sparse data and cold start. It provides users with more personalized and people-centered travel route recommendations, which significantly enhancing the travel experience.

This paper aims to revolutionize teaching and learning practices in higher education by optimizing prediction accuracy through recommendation system methods in applied art education. The study... Show More

This paper aims to revolutionize teaching and learning practices in higher education by optimizing prediction accuracy through recommendation system methods in applied art education. The study explores advanced machine learning techniques, particularly intuitive fuzzy C-means clustering and user interest collaborative filtering (IFCM-UIR-CF). Quantitative analysis reveals significant performance differences among three methods: FCM-CF, IFCM-CF, and IFCM-UIR-CF. FCM-CF starts with a Mean Absolute Error (MAE) of 0.845, improving to 0.750 with 150 neighbors. IFCM-CF starts at 0.810 and decreases to 0.700. IFCM-UIR-CF outperforms both, starting at 0.800 and reaching a minimum MAE of 0.658. These results show that increasing the number of nearest neighbors enhances prediction accuracy, with IFCM-UIR-CF providing the most accurate recommendations. The study emphasizes the significance of user-commodity relationships and decomposition processes in improving recommendation accuracy, offering insights for future research.

This paper proposes a novel optimization method for task offloading in Multi-Access Edge Computing (MEC) environments. The method combines Ant Colony Optimization (ACO) and Genetic Algorithms (GA)... Show More

This paper proposes a novel optimization method for task offloading in Multi-Access Edge Computing (MEC) environments. The method combines Ant Colony Optimization (ACO) and Genetic Algorithms (GA) to minimize total execution latency. ACO explores the solution space for potential optimal solutions, while GA refines these solutions through evolutionary processes. Simulation experiments validate the effectiveness of this approach, showing significant reductions in overall execution latency compared to conventional single-algorithm methods. The paper also discusses key factors influencing task offloading strategies, providing practical insights for real-world deployments. The proposed hybrid ACO-GA strategy offers a high-efficiency and adaptable solution to the task allocation problem in MEC, enhancing the system's performance and quality.

Using hashes for user authentication allows systems to verify identity without storing or transmitting plaintext passwords, preventing theft or leakage. At the system level, access is granted if the... Show More

Using hashes for user authentication allows systems to verify identity without storing or transmitting plaintext passwords, preventing theft or leakage. At the system level, access is granted if the hash matches and denied if it doesn't. A recent development in this area is chaos-based hashing, though it's not fully matured due to its complex and flawed design principles. This work proposes a novel chaos-based hash using a sponge construction. The design includes a four-state finite automaton to build the chaos structure, with a sponge mechanism for optimal bit mixing. Statistical evaluations show that the proposed hash offers strong diffusion, confusion, collision resistance, and balanced distribution. In addition to its provable security, it extends indifferentiability from random oracles in sponge-based constructions. Moreover, compared to existing chaos-based hashes, the proposed solution achieves superior performance.

Emotional analysis of netizens' expressions on social media is a branch of natural language processing that aims to mine people's opinions and emotional tendencies toward events and things.... Show More

Emotional analysis of netizens' expressions on social media is a branch of natural language processing that aims to mine people's opinions and emotional tendencies toward events and things. Analyzing public opinion in higher education has become a trend in recent years, helping guide the reform of higher education. This paper presents an optimized design scheme for college pupils' emotional online perception model using Weibo comments. Three types of emotional articles—“joy,” “anger,” and “sadness”—are collected and preprocessed. Word2Vec is used for algorithmic network feature extraction, and key features are annotated with emotions in an artificial dictionary. Hidden themes or topic categories are found from a large number of documents, and emotion classification is completed assuming each document is a mixture of multiple topics. The study of online emotional perception in colleges has high practical significance and value, aiding in the implementation of control measures and psychological development of pupils.

This study delves into the relationship between multimedia digital transmission technology and modern art design, along with the public's satisfaction with their integration. Using a mixed-method... Show More

This study delves into the relationship between multimedia digital transmission technology and modern art design, along with the public's satisfaction with their integration. Using a mixed-method approach of online questionnaires and offline interviews, data from diverse participants was collected. The data was then analyzed using methods such as factor analysis, χ2 test, and correlation analysis. Correlation analysis revealed positive correlations among perceived quality, the maturity of informatization construction, and art design expectations. This implies that enhancing people's understanding of smart city construction and forming reasonable expectations can strengthen the maturity of information services. Moreover, public trust in art design and a favorable public perception of art design are positively correlated with public satisfaction with art design, highlighting the importance of a people-centered concept in urban construction. This research provides valuable references for technology developers, art designers, and policymakers.

At present, college English teaching is generally faced with problems such as an imperfect evaluation system of teaching effect and uneven teaching quality. Therefore, how to scientifically and... Show More

At present, college English teaching is generally faced with problems such as an imperfect evaluation system of teaching effect and uneven teaching quality. Therefore, how to scientifically and effectively evaluate the effect of English teaching in higher vocational colleges has become the key to improve the teaching quality. In this study, the analytic hierarchy process (AHP) and grey theory are used to evaluate the effect of college English teaching in many aspects. This study constructs an evaluation model of English teaching effect in higher vocational colleges for research and analysis. The results show that the model has good applicability in the evaluation of college English teaching effect, and also has certain reference value for the evaluation of teaching effect of other courses. This study provides a systematic framework for improving the quality of English teaching in higher vocational colleges and has important implications for educational practice and policy.

In recent years, Internet teaching has become more and more popular. In the field of aesthetic education, many scholars have successfully integrated artificial intelligence technology into... Show More

In recent years, Internet teaching has become more and more popular. In the field of aesthetic education, many scholars have successfully integrated artificial intelligence technology into innovative teaching. This paper analyzes the aesthetic status quo of Chinese universities, its advantages and disadvantages and innovative ideas. Taking music in artificial intelligence as an example, this paper combines high technology with aesthetic education to explore the effect of integrating artificial intelligence music into college students' aesthetic education. The results show that most students think that music in artificial intelligence has great advantages in assisting aesthetics. The aesthetic level of students who combine traditional teaching with artificial intelligence music is higher than that of students who adopt traditional teaching as a whole. This study is of great significance to the combination of artificial intelligence music in college aesthetic education, which is conducive to promoting the development of college students' aesthetic education.

Focusing on the field of social media influence prediction, this study aims to evaluate the efficacy of a model that incorporates Long Short-Term Memory Networks (LSTMs) with fuzzy logic. Through... Show More

Focusing on the field of social media influence prediction, this study aims to evaluate the efficacy of a model that incorporates Long Short-Term Memory Networks (LSTMs) with fuzzy logic. Through experimental comparisons, we found that LSTM combined with fuzzy logic performs well in predicting social media interaction metrics, especially when dealing with complex and uncertain social media data. The experimental design covers datasets from two typical social media platforms, and multiple models are used for comparison, including traditional ARIMA, rule-based models, and deep learning models such as GRU and RNN. The results show that the fusion model not only improves the prediction accuracy but also demonstrates stable performance improvement under different event categories. In addition, we analyzed the association between user behavior and influence, proposed a multi-dimensional approach to comprehensively assess user influence, and tailored influence enhancement strategies for users.

Based on knowledge-building theory, this study examines the impact of interactive behaviors on the depth of opinions within knowledge-building learning communities. Focusing on a third-grade Chinese... Show More

Based on knowledge-building theory, this study examines the impact of interactive behaviors on the depth of opinions within knowledge-building learning communities. Focusing on a third-grade Chinese language class in Xinjiang, China, this manuscript per the authors developed and validated coding systems for interactive behaviors and opinion depth through classroom observations and content analysis of students' artifacts. These tools were applied to analyze interactions and opinion depth in the community. Correlation and regression analyses, complemented by interview results, reveal how specific interactive behaviors significantly influence the depth of students' opinions. This research clarifies the current state of interactions and deepens our understanding of effective learning environments that promote deeper perspectives among learners.

This paper introduces a novel enhanced Big Data Analytics (BDA) algorithm designed to improve user experience in the animation industry. By combining data mining and machine learning techniques... Show More

This paper introduces a novel enhanced Big Data Analytics (BDA) algorithm designed to improve user experience in the animation industry. By combining data mining and machine learning techniques, including K-means clustering, the algorithm analyzes user behavior based on demographic factors, particularly age. Using data from a major Chinese animation platform, the study identifies age-specific preferences: children prefer simpler plots, while teenagers favor complex narratives. The algorithm enables precise user segmentation, enhancing targeted marketing and significantly improving viewer engagement and click-through rates. This research contributes to the field by demonstrating how Big Data and machine learning can optimize content recommendations and marketing strategies, fostering user loyalty and promoting the growth of domestic animation content. The study offers a comprehensive framework for future BDA applications in creative industries, advancing personalized marketing practices in the animation sector.

This study explores how CAD and multimedia technologies transform artistic creation. CAD's precision in drawing and modeling is crucial for fields like automotive design and landscape architecture... Show More

This study explores how CAD and multimedia technologies transform artistic creation. CAD's precision in drawing and modeling is crucial for fields like automotive design and landscape architecture, enabling detailed and functional designs. Multimedia technology, by integrating visual, audio, and video elements, enhances artworks' appeal and allows for complex narratives. The combination of CAD and multimedia has led to innovative styles such as surreal sci-fi, abstract minimalism, and cross-cultural retro aesthetics. While these technologies boost creative efficiency and detail refinement, they also pose challenges, including high costs for skill acquisition and the risk of over-reliance on technology. Addressing these challenges through accessible education and balanced integration of digital and traditional techniques can unlock new possibilities for diverse and thought-provoking art.

This study discusses how to use CAD technology and deep learning to improve the collaborative application effect of art design under the background of artificial intelligence (AIGC). By improving... Show More

This study discusses how to use CAD technology and deep learning to improve the collaborative application effect of art design under the background of artificial intelligence (AIGC). By improving the accuracy of design drawings, establishing an image generation model, marking feature points, building a color imitation system, and using deep learning algorithm to classify images, efficient and accurate image processing and automatic generation of design works are realized. Research shows that the combination of CAD and deep learning can not only improve work efficiency in art design, but also automatically generate design works according to the style of big data.

Blockchain technology is increasingly recognized as a catalyst for business model innovation, offering new value creation, delivery, and capture opportunities. This study systematically examines... Show More

Blockchain technology is increasingly recognized as a catalyst for business model innovation, offering new value creation, delivery, and capture opportunities. This study systematically examines blockchain's role in transforming business models through the lens of the Antecedent-Decision-Outcome (ADO) framework. Integrating insights from a systematic literature review with empirical findings from expert interviews, the research identifies key drivers, barriers, and outcomes of blockchain adoption. It demonstrates how blockchain enables decentralization, transparency, and disintermediation, reshaping governance structures and revenue streams while fostering trust and operational efficiency. The findings contribute to business model theory by situating blockchain adoption within established frameworks, including the Business Model Canvas, Diffusion of Innovations, and Transaction Cost Economics. Practical implications include a roadmap for organizations to evaluate blockchain's strategic fit and recommendations for policymakers to create conducive regulatory environments.

Dance training as a unique kinesthetic art has a significant impact on adolescent brain development and function. As a hub for sensory and emotional integration, the insular plays a key role in... Show More

Dance training as a unique kinesthetic art has a significant impact on adolescent brain development and function. As a hub for sensory and emotional integration, the insular plays a key role in multiple cognitive functions. To address the unclear impact of dance training on sensory training functional areas in the adolescent insular, the study proposes to utilize various analytical methods such as voxel-based morphometry technique. By comparing the structural brain changes and functional connectivity differences between the dance training group and the control group, the study investigates the specific effects of dance training on insular functional areas. The results demonstrated that the dance training group showed a significant increase in gray matter in areas such as the posterior insular and the shell nucleus.

This paper comprehensively analyzes the National Association of State Chief Information Officers' (NASCIO) annual priorities from 2013 to 2023, highlighting the evolving focus areas in state IT... Show More

This paper comprehensively analyzes the National Association of State Chief Information Officers' (NASCIO) annual priorities from 2013 to 2023, highlighting the evolving focus areas in state IT advancements. Examining survey data from government technology leaders identifies key trends in cybersecurity, workforce development, strategic planning, digital services, data management, and connectivity. The research underscores cybersecurity and data management as persistent priorities, reflecting the critical role of technology in ensuring information security and effective data governance within state governments. Through a decade-long perspective, the study offers insights into how policy changes, technological innovations, and shifts in cultural and consumer expectations have shaped the strategic direction of state CIOs, providing a foundation for predicting future trends and opportunities in government IT management.

In the current integration of digital technology and cultural inheritance, Multimedia Information Retrieval (MIR) technology is crucial for large-scale data management and cultural dissemination.... Show More

In the current integration of digital technology and cultural inheritance, Multimedia Information Retrieval (MIR) technology is crucial for large-scale data management and cultural dissemination. This study constructs an optimized MIR model for promoting Zhuxian Town woodblock New Year paintings. It innovatively uses the spatial vector model to analyze New Year painting features and builds a feature extraction-retrieval-precise promotion model to enhance dissemination. Experiments show that this technology improves the dissemination of New Year paintings in multiple dimensions, such as more stable decorative feature extraction and a higher matching degree of color combinations with modern themes. Meanwhile, the study points out its challenges in cultural heritage applications and indicates that relevant methods have cross-industry value, providing support for the digital dissemination of traditional art and cross-industry data processing.

This study explores the intersection of intangible cultural heritage (ICH) and tourism in Xuzhou City, China, with a focus on sustainable development in the face of globalization challenges. It... Show More

This study explores the intersection of intangible cultural heritage (ICH) and tourism in Xuzhou City, China, with a focus on sustainable development in the face of globalization challenges. It employs the Clip Shots dataset and videos from the National Cultural Industry Research Center to develop a shot boundary detection method utilizing 3D convolutional neural networks. Furthermore, the research enhances the traditional Single Shot MultiBox Detector algorithm, leading to improved detection performance. Preliminary experiments on target detection of specific non-legacy musical instruments and backgrounds demonstrate the superior effectiveness of the improved Single Shot MultiBox Detector algorithm compared to conventional deep learning methods. The research explores innovative technological approaches to enhance the visibility of ICH, ensuring its relevance to contemporary audiences. Ultimately, this study aims to provide actionable strategies for leveraging ICH in tourism, contributing to both cultural preservation and local economic development.

Sentiment analysis, a key NLP branch, is widely used in social media and market analysis. Traditional methods, reliant on feature engineering and shallow ML models, face limits in text length... Show More

Sentiment analysis, a key NLP branch, is widely used in social media and market analysis. Traditional methods, reliant on feature engineering and shallow ML models, face limits in text length, diversity, and contextual understanding. Recently, deep learning models, especially those using the Transformer architecture, have become dominant due to their self-attention and parallel computing. This paper introduces a Transformer-based model for English sentiment analysis, studying its construction and optimization. Using datasets like IMDB and Twitter, it achieves efficient classification. Experiments in hyperparameter tuning, regularization, and data augmentation further enhanced performance, with ablation studies assessing each strategy's impact. Results show the model outperforms traditional and mainstream deep learning methods in accuracy, F1 score, etc., especially in long text analysis. This research highlights that optimized deep learning models boost English sentiment analysis performance, offering new insights for related research and applications.

This study explores the integrated application of Computer-Aided Design (CAD) and Artificial Intelligence (AI) in animation production. Aiming at the bottlenecks of AI-generated animation in... Show More

This study explores the integrated application of Computer-Aided Design (CAD) and Artificial Intelligence (AI) in animation production. Aiming at the bottlenecks of AI-generated animation in emotional expression, geometric accuracy, and motion smoothness, a hybrid production paradigm of “CAD definition → AI generation → CAD refinement” is proposed. Through three strategies—parametric modeling, intelligent material mapping, and AI-driven motion interpolation—and a case study of the 3D animated film Fantastic Adventure, the method's effectiveness is verified in reducing mechanical artifacts, enhancing visual realism, and improving production efficiency. The research notes that while integration technologies face challenges such as system compatibility, data security, and artistic balance, the concept of “collaboration between technical precision and artistic creativity” provides a new paradigm for the animation industry's high-quality development.

With the aging of bridges and the increase in traffic load globally, the real - time monitoring and evaluation of bridge structure health status are of great significance. This research proposes a... Show More

With the aging of bridges and the increase in traffic load globally, the real - time monitoring and evaluation of bridge structure health status are of great significance. This research proposes a novel bridge health status detection method that combines an attention mechanism and hybrid feature extraction technology with deep learning, and uses ANSYS software for explicit dynamic analysis. The BridgeHealthNet model developed in this study shows excellent performance in algorithm performance evaluation, with a recall rate of 94.1%, an F1 value of 93.7, an average detection time of 139 ms, and a CPU utilization rate of 15%, outperforming algorithms like GoogleNet, Vgg16, and ResNet - LSTM. The finite element model of the bridge structure based on ANSYS and the performance evaluation of non - destructive testing technology demonstrate the effectiveness of the model in simulating bridge dynamic behavior and performance evaluation. This research provides a new solution for bridge health monitoring, which is expected to improve the reliability and efficiency of infrastructure maintenance.

In the new media era, Virtual Reality (VR) art has revolutionized audience experiences through immersive interactivity. This paper examines VR art's key characteristics, implementation methods, and... Show More

In the new media era, Virtual Reality (VR) art has revolutionized audience experiences through immersive interactivity. This paper examines VR art's key characteristics, implementation methods, and its impact on modern art. VR creates realistic 3D environments that facilitate active audience participation, enhancing engagement and immersion. The study identifies core features—intuitiveness, immersion, and collaboration—that enable VR art to offer richer experiences beyond traditional forms. Experimental results indicate that increased interaction complexity and immersion significantly enhance user experience and artistic impact. User feedback affirms that interactivity is a distinguishing feature of VR art, providing deeper emotional resonance. The development of VR art's interactivity enriches artistic expression and introduces new creative possibilities. As technology advances, VR art is expected to become mainstream, offering more innovations to both artists and audiences. This research offers valuable insights into the future of VR art and the integration of technology with art.

In contemporary art and design education, traditional methods relying on two-dimensional presentations restrict students' spatial perception and creativity, offering limited practical opportunities.... Show More

In contemporary art and design education, traditional methods relying on two-dimensional presentations restrict students' spatial perception and creativity, offering limited practical opportunities. Meanwhile, the rise of virtual reality (VR) technology has transformed multiple sectors with its immersive and interactive capabilities. This study explores the innovative application of VR in art and design education, examining its technical principles, unique characteristics, and suitability for educational purposes. Integrating VR into course instruction, practical projects, and interdisciplinary collaborations enhances students' spatial perception, creativity, and practical skills, leading to improved learning outcomes and more innovative final projects. Despite challenges such as mastering new technologies and ensuring equitable access, educators have successfully adapted their teaching methods to incorporate VR.

This study delves into strategies for overcoming software access barriers in educational settings for a course on Database Management Systems. It demonstrates how access to course materials and... Show More

This study delves into strategies for overcoming software access barriers in educational settings for a course on Database Management Systems. It demonstrates how access to course materials and software via a virtual desktop can mitigate challenges such as schedule conflicts and limited resources, benefiting student retention and overall achievement. The Experimental Group, which benefited from the virtual desktop, demonstrated superior performance and retention compared to the Control Group. Notably, the Experimental Group exhibited a lower dropout rate (4.1% vs. 7.4%), indicating enhanced retention. Additionally, they consistently outperformed the Control Group across all assignments, with differences ranging from 3.29% to 23.07%, suggesting significant improvement over the course duration. The findings suggest that implementing virtual desktops can enhance software accessibility, promote educational equity, and significantly improve both student performance and retention in courses requiring specialized tools.

This article explores the transformative effects of digital media technology on artistic creation and communication. It highlights how advancements such as virtual reality, augmented reality, and... Show More

This article explores the transformative effects of digital media technology on artistic creation and communication. It highlights how advancements such as virtual reality, augmented reality, and artificial intelligence have revolutionized the art world, enabling artists to transcend traditional media limitations. Through a comparative empirical study involving two groups of artists—one using traditional methods and the other employing digital tools—the research reveals significant benefits of digital integration. The experimental group demonstrated a 15% reduction in creation time, a 20% decrease in costs, and a substantial increase in audience engagement, with a 3.8-fold rise in viewers and 180% more interactions. Additionally, the quality of digital works surpassed traditional ones in both professional scoring and innovation. The findings underscore the necessity for collaboration between art and technology sectors to enhance creative processes and broaden the global reach of contemporary art, ultimately fostering a richer artistic landscape.