bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction of Traditional Village Health Development Evaluation System Based on Ecological and Cultural Health Theory
Authors: Pang Chunyu , Lu Min 
Published: April 2024

Abstract
Traditional villages, as spatial carriers with rich cultural resources, are important cornerstones for cultural inheritance and promotion, and their ecological and cultural symbiosis has been formed in the process of long historical development, which contains rich ecological wisdom. To comprehensively analyze the development status of traditional villages and plan and design future development, this study is guided by the theory of ecological and cultural health, selects the evaluation elements of the target level, criterion level, and indicator level, and devotes itself to constructing an evaluation system of the healthy development of traditional villages, and applies the hierarchical analysis method and the entropy weight method to determine the index weight, to establish a comprehensive evaluation model of the healthy development of traditional villages. By evaluating the healthy development of traditional villages in Ning’an City, Mudanjiang City, and Heilongjiang Province, the study verifies the feasibility of the evaluation system constructed by the study for the healthy development of traditional villages. It proposes corresponding healthy development strategies for the evaluation analysis to provide reference ideas for traditional villages’ ecological and cultural health and sustainable development.
Factors and Mechanisms Influencing Consumers’ Willingness to Participate in Food Safety Social Co-governance: An Empirical Study from China
Authors: Zhang Chunsheng , Ji Mingxin , Deng Zhaoyan , Wu Di 
Published: April 2024

Abstract
Food safety governance and its performance improvement are inseparable from the cooperation of multiple subjects. The extensive participation of consumers is not only a powerful supplement to the deficiency of supervision resources but also an intrinsic request for seeking both temporary and permanent solutions to food safety problems. To ascertain the factors and mechanisms that influence consumers’ participation willingness of food safety social co-governance, an integrated conceptual model was constructed based on the Theory of Planned Behavior (TPB) and Benefit-Risk Analysis (BRA). 664 valid questionnaires collected in China were used to verify the hypotheses with the application of the Structural Equation Model (SEM). The results showed that behavior attitude, subjective norm, and perceived behavior control significantly impacted consumers’ participation willingness, and the influence strength was in the sequence of perceived behavior control, behavior attitude, and subjective norm. Perceived risk and participation willingness showed a strong negative relationship. Besides that, perceived risk also played a partial mediation role in predicting behavior attitudes toward consumers’ participation willingness. According to the conclusions, a series of policy suggestions were also proposed to help improve consumers’ participation willingness.
Analysis of the Yellow River water and sediment monitoring data
Authors: Liu Wenbin , Liu Dongbing 
Published: April 2024

Abstract
Graphics are drawn about the sediment content, water flow, and water level of the Yellow River with time. A cluster scatter plot of sand content is made with changes over time. Using variance analysis of a factor, it is concluded that sediment content is affected by two variables month and year. By studying the changing pattern of water-sand flux, the timing diagram of the water and sediment flux of the Yellow River with time is drawn. The flux of water and sand is predicted for the next two years. According to the prediction results, the optimal sampling and monitoring scheme is developed.
Investigation on Wind-Induced Structural Damage and Preventive Measures of Low-Rise Buildings in Coastal Areas
Authors: Zhang Maoyu , Tian Shengbao , Wang Yanru , Fu Bin , Zhang Chuanxiong , Zheng Shuqin , Jiang Ruinian 
Published: April 2024

Abstract
Strong winds, typhoons, and other extreme weather can cause significant damage to house structures, resulting in great harm to human life and property safety. It is imperative to prepare and strengthen infrastructure against these extreme weather conditions to minimize their impact. This paper conducts an on-site survey of low-rise houses in Cangnan County and Dongtou District, located on the south coast of Zhejiang, affected by typhoons. It summarizes the structural characteristics of houses and the damage caused by typhoons to house structures. The paper also performs a preliminary analysis of the damage mechanism of houses. Additionally, it examines wind-resistant measures used by the private sector, identifies potential issues with wind-resistant design, and proposes corresponding wind-resistant countermeasures and recommendations for low-rise houses. The research presented in this paper can be utilized for analyzing the wind damage mechanisms of low-rise houses in the future. Moreover, it offers a valuable reference for the analysis and simulation of wind damage in low-rise houses in typhoon-prone coastal areas. This research holds significant value in preventing wind damage to low-rise houses.
Impact Assessment of Large-scale Sports Events on Tourism: A Case Study of the 16th Asian Games
Authors: Yan Yanrong , Liu Chengqun 
Published: April 2024

Abstract
The positive impact of hosting large-scale sports events on tourism is examined in this study, focusing on the 16th Asian Games as the research subject. The Difference-in-Difference Method and Synthetic Control Method are employed to analyze the event’s influence on tourism in Guangzhou and other cities within Guangdong Province. The findings demonstrate a significant driving effect of such events on the growth of tourism in host cities over subsequent years. Moreover, it is revealed that the 16th Asian Games has a particularly pronounced impact on remote cities located far from Guangzhou, including those situated in the eastern, western, and northern regions of Guangdong Province. Consequently, this study suggests that host cities should seize opportunities by engaging in scientific planning and meticulous arrangements for large-scale events. Additionally, other cities within the province where these events take place should actively participate in enhancing their ability to serve such occasions while improving both the level and quality of their tourism services. This approach will enable them to capitalize effectively on hosting opportunities and facilitate high-quality development across all parts of the province.
Comparative Study on Flight Training of Chinese Airline Pilots at Home and Abroad
Authors: Zhu Shouxi , Chen Jian 
Published: April 2024

Abstract
The study aimed to analyze flight training methods for Chinese airline pilots, comparing domestic and foreign approaches while assessing their respective advantages and disadvantages. Various aspects including language, culture, airspace, flight support, teaching methods, training standards, and costs were examined. Additionally, a quantitative analysis was conducted on theory and practical exam results, as well as the personality development of cadets from both training backgrounds. Results revealed that foreign flight training offered several benefits over domestic training, such as shorter duration and lower costs due to airspace accessibility. Cadets undergoing foreign training demonstrated higher average scores and passing rates in Instrument Rating and Commercial License Examinations compared to domestically trained counterparts. Furthermore, foreign training positively influenced cadets’ personality development. In conclusion, foreign flight training demonstrated significant advantages in terms of overall cost-effectiveness, training quality, and cadet professionalism. However, domestic training also had its merits. Thus, the authors recommended a comprehensive evaluation to determine the most suitable training approach for individual cadets.
Development of a Residential Space Design Module Based on Virtual Reality (VR) Applications
Authors: Zhu Hua , Mansor Marzita 
Published: April 2024

Abstract
The adoption of virtual reality (VR) in architectural design is increasing, driven by its ability to create immersive simulated environments. This is particularly advantageous in residential space design, where understanding and evaluating solutions is critical. Although extensive research has focused on basic VR applications, few have explored VR modules tailored for residential design. Our study fills this gap by developing a VR module designed specifically for this purpose. We use a mixed-methods approach, blending quantitative analysis with qualitative feedback, to demonstrate how this VR module can improve design quality, efficiency, and user engagement.
Innovative Work Behavior and Job Performance of Corporate Employees in the Age of Artificial Intelligence
Authors: Chen Sidi , Zhang Xiao , Pan Ling , Hu Min 
Published: April 2024

Abstract
In the Artificial Intelligence era, organizations face unprecedented challenges and opportunities. The use of technology has not only changed the way work is done, but also had a significant impact on employee behavior patterns and performance. The innovative work behavior of employees greatly influences the sustainable development of enterprises. How AI affects explicitly employees’ innovative work behaviors and the mechanism of its impact on work performance is unclear. An in-depth analysis of this process is essential for optimizing the application of AI, promoting employees’ innovative behaviors, and improving job performance. The study of AI’s influence on employees’ innovative behavior and its effect on job performance was conducted using multiple regression and path analysis methods. It was discovered that the use of AI significantly impacts employees’ innovative behavior and work performance. In the paper, after controlling for factors such as gender, education, and enterprise size, the positive influence coefficient of AI on employees’ innovative behavior is 0.305 (p<0.01), and the positive influence coefficient on job performance is 0.520 (p<0.001). The relationship between artificial intelligence and employee innovative behavior is mediated by interpersonal trust. Artificial intelligence directly affects employees’ innovative work behavior, enhances their intrinsic and extrinsic motivation, and indirectly promotes work performance improvement. To encourage employee innovative behavior and improve work performance, enterprises should actively adopt AI technology while maintaining interpersonal trust.
Smart Energy Management Construction of Electric Power with Application of Bioelectricity Technology
Authors: Chen Yangbo , Wang Weirong , Guo Hao , Wang Zhongpeng , Li Jiawei 
Published: April 2024

Abstract
The search for sustainable energy solutions has become urgent against the current energy crisis and increasing environmental pollution. Biomass energy conversion and utilization technology, a clean and renewable energy source, constantly evolves, particularly in biomass power generation technology. This technology can effectively reduce greenhouse gas emissions and dependence on fossil fuels. Biomass conversion and utilization techniques include combustion, gasification, and biochemical methods that generate different energy forms, including heat, electricity, and fuel. Developing these technologies provides strong technical support for optimizing energy structures and protecting the environment. The article explores the application of biopower technology in intelligent energy management of electricity and improves its efficiency. The efficiency of biopower technology and its influencing factors were investigated using the Data Envelopment Analysis (DEA) model and Tobit regression analysis. A study was conducted on ten biopower energy companies. The energy management efficiency score of 1 was present in six of these companies, suggesting a relatively high operational efficiency level. Company C has a super-efficiency value of 2.654, indicating its outstanding energy management efficiency. Factors such as human resource input, total investment, and annual production costs significantly affect energy management efficiency. By optimizing resource allocation and improving management efficiency, biopower technology can be applied more effectively to intelligent energy management, thus promoting sustainable development.
A Study on the Multiple Dispute Resolution Mechanisms of Systemic Jurisprudence in the Context of Big Data
Authors: Ding Zhaozeng 
Published: April 2024

Abstract
The rise of complex social disputes in the digital age challenges traditional legal resolution methods. The SmartSettle platform emerges as a pioneering response, leveraging artificial intelligence to enhance the dispute resolution process. By integrating advanced algorithms, SmartSettle offers an efficient, fair, and user-friendly online environment for dispute resolution, marking a significant evolution in legal research and practice. This study examines SmartSettle’s effectiveness within the extensive data landscape, employing qualitative and quantitative methods to assess its seven core algorithms. In 2022, SmartSettle achieved a remarkable success rate of over 95% across 13,550 cases in M City. The platform guarantees equitable outcomes and high satisfaction levels among parties through its innovative minimum gain maximization algorithm. Consequently, SmartSettle effectively manages legal disputes in a big data context and sets a new trajectory for legal research and practice.
Research on Intelligent Design of Traditional Cultural and Creative Products Based on Digital Twin Network Modeling
Authors: Gao Pin , Zhang Yue , Mu Delan , Liu Mingying 
Published: April 2024

Abstract
This study investigates the integration of digital twin technology in the design of traditional cultural and creative products, addressing the challenges of innovation and efficiency in the cultural and creative industries. By employing digital twin network modeling, we develop an intelligent design method that digitally replicates and optimizes cultural products, enhancing design efficiency and innovation. Our approach involves digital modeling of traditional characteristics through preprocessing and feature extraction, followed by multi-scale design evolution experiments in a virtual environment. Results show a 30% improvement in design efficiency and increased product innovation and user satisfaction, demonstrating the method’s potential to revolutionize traditional product design while preserving cultural essence. This research contributes to the intelligent design of cultural and creative products and suggests new avenues for the cultural industry’s innovative growth.
A synergistic nurturing mechanism of party building and civic management education in colleges and universities combining synergistic modeling
Authors: Han Mingjiang 
Published: April 2024

Abstract
The Construction and practice of collaborative nurturing between party building and ideological and political management education in colleges and universities has been increasingly emphasized under the current field of higher education. Through an organic combination of party building activities and ideological and political education, this mechanism is committed to fostering high-quality talents with socialist core values. In the context of diversification and complexity of higher education, exploring an effective collaborative parenting mechanism is of great significance for improving college students’ ideological and political quality, moral cultivation and social responsibility. This study thoroughly analyzes the collaborative nurturing mechanism of party building and ideological and political education. It clarifies its components, operation mechanism and evaluation model, and provides theoretical support and practical guidance for ideological and political work. Using methods such as literature analysis, questionnaire survey and expert interviews, the study comprehensively analyzes the constituent elements, operation process and evaluation model of the collaborative nurturing mechanism of party building and ideological and political management education. The synergistic educating mechanism in the article improves the political awareness and moral cultivation of college students, in which the satisfaction of the management system is the highest (score 0.876), and the satisfaction of students is relatively low (score 0.518). The study also found that the implementation effect of collaborative parenting between party building and civic management education is closely related to its systematic, integrative, and dynamic adjustment ability. The strategic suggestions put forward in this paper to strengthen the mechanism construction, optimize the resource allocation and enhance the synergy efficiency have advanced to improve the quality and effect of collaborative parenting between Party building and Civic and Political management education in colleges and universities.
Exploration of high-quality development path of tourism and culture industry in the context of smart tourism
Authors: Hou Weigang 
Published: April 2024

Abstract
The emergence of intelligent tourism as a new trend in the travel industry has raised the bar for the excellent growth of the travel and cultural sectors. The merger of the artistic and tourist industries significantly advances tourism’s modernization and evolution. Finding a high-quality growth path for the tourist and culture industries within the context of intelligent tourism is a significant problem that must be overcome in order to achieve the two sectors’ in-depth integration and synergistic growth. A scientific assessment system and model analysis is necessary to uncover practical ways to support industry integration and upgrading based on the current industrial development status quo. A strong connection between this province’s cultural and tourism sectors is indicated by the coupling degrees generally higher than 0.85. Although the degree of coupling coordination has improved annually, many cities are still unable to achieve a higher level of coordination, according to an analysis. This study utilizes the degree of coupling coordination model as a basis for creating a coupling index for the culture and tourist industries and examining the growth situation of an area from 2015 to 2022. In a particular province, the median annual growth rates for the tourism and cultural sectors between 2015 and 2022 are 19.18% and 32.11%, respectively. This suggests that there is still more room for growth and integration between the two sectors in the context of intelligent tourism. The tourism industry is developing more slowly than the cultural industry. The research suggests ways to aid the integration and superior growth of the tourist and cultural sectors, including boosting infrastructure construction and enhancing employee knowledge.
An objective evaluation method of vocal singing effect based on artificial intelligence technology
Authors: Huang Danxia 
Published: April 2024

Abstract
The continuous progress of artificial intelligence technology has shown great potential for application in several fields, especially music. The research direction of Objective Evaluation of Vocal Singing Effectiveness uses advanced technologies to analyze and assess a singer’s performance across multiple dimensions, including pitch, rhythm, and timbre, and is highly valuable. Building an accurate and fair evaluation system faces many challenges, including how to accurately capture and analyze the subtle changes in the voice and synthesize the effects of different musical elements on the quality of the performance. This requires researchers to explore music theory, sound analysis techniques, and artificial intelligence algorithms, and develop a new methodology that can comprehensively evaluate the effectiveness of vocal singing. This paper constructs a complete set of vocal singing evaluation models by analyzing acoustic feature extraction, Hidden Markov Model, and Generalized Regression Radial Basis Function Network in detail. The study adopts a logarithmic Mel spectrum for acoustic feature extraction to effectively capture the essential attributes of the singing voice. Hidden Markov models and mixed Gaussian models are used to model the sound signal, improving phoneme recognition accuracy. Accurate singing effect was evaluated using a generalized regression radial basis function network. In this article, the accuracy of this evaluation method in terms of pitch, rhythm, and timbre reached 95%, 93%, and 89%, respectively, demonstrating high evaluation consistency and reliability. The research method provides a new objective evaluation tool for vocal singing effects, which is valuable for vocal teaching and self-practice.
Research on Industrial Economics Models in Rapid Development of Digital Economy
Authors: Ma Jing 
Published: April 2024

Abstract
Amidst the rapid evolution of the digital economy, this research positions fuzzy rough set theory at the forefront of industrial economic modeling, acknowledging its profound capability to manage uncertain information. This theory’s analytical precision facilitates a deep dive into the dynamics of industrial economic growth, enabling the refinement of industrial structures for sustainable development. Our empirical investigation into region A’s grain industry showcases a remarkable output growth of 272.88% from 2008 to 2018, with a model accuracy exceeding 95%. Analysis on cost inputs further demonstrates how innovation in science and technology plays a crucial role in cost reduction. By leveraging fuzzy rough set theory, this work contributes significantly to the strategic development of industrial economics, offering a robust methodology for data-driven analysis and forecasting in industrial sectors.
Construction and Algorithm Research of Online Learning Interaction Behavior Model Based on FBM
Authors: Wang Hui 
Published: April 2024

Abstract
The development of online learning environments has facilitated changes in educational interactions. This study focuses on an in-depth exploration of learners’ online interaction behaviors based on the theory of the Fogg Behavior Model, all in the context of accurately depicting and optimizing these interactions. Considering the complexity and richness of online education platform data, this paper proposes an improved analytical methodology to accurately model and predict learner behaviors, expecting to provide a scientific basis for the development of personalized teaching strategies and the enhancement of learning experience This methodology is based on the Fractional Brownian Motion and BAS algorithms to analyze the data of online learning platforms. The study collected data such as login, learning status, and course grades, and used the combination algorithm to optimize the Hurst index estimation and improve prediction accuracy. The number of view notifications is significantly correlated with the interactive learning behavior of resources at the 0.01 level, and the correlation coefficients are 0.297, 0.557 and 0.360. The algorithm accurately reflects learner behavior, provides optimization strategies for online learning platforms, and enhances learning efficiency and interaction quality.