bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Exploration of Customer Experience Design Innovation in Tourism and Hospitality Industry Driven by Emerging Technologies
Authors: Liu Hui 
Published: May 2024

Abstract
With the rapid development of tourism hotels, there are many problems, such as uneven design quality and poor user experience. In response to the above issues, this paper proposes a digital design for tourism hotels that integrates VR technology. Using the network crawling technology in the network LDA model, the text data on customer experience design in the tourism hotel industry is obtained, and in order to avoid the problem of duplicate values and null values in the data, data processing is carried out to ensure the precision of the research results. Based on the principle of evaluation system construction, we determine the evaluation index system for tourism hotel customer experience design that allows the integration of VR technology and constructs the LDA-AHP model for hotel customer experience design. Based on the acquired research data, the customer experience design of the tourism hotel industry is analyzed by examples. The results indicate that the comprehensive evaluation score for tourism hotel user experience based on the LDA-AHP model is 3.3075, which suggests that the design of tourism hotel user experience based on the LDA-AHP model is at the 3-crown level. This study provides theoretical references for the design of tourist hotel customer experiences, which can help the tourist hotel industry improve and develop rapidly.
Ecological Network Construction of Putian Rural Landscape Based on Geospatial Analysis
Authors: Lu Xiaoxue , Chen Zhen , Cao Mengqi , Chen Zujian 
Published: May 2024

Abstract
As the countryside continues to expand and develop, ecological issues are becoming increasingly complex and critical. The creation of environmental networks plays a vital role in ensuring ecological protection and promoting sustainable development in these areas. This study selects the Putian countryside as the focal area for research, utilizing remote sensing technology to collect pertinent data. By integrating geospatial analysis methods, we constructed a landscape ecological network. The methodology involved several key steps: employing a landscape index to delineate the spatial pattern of the rural landscape, evaluating the service function value of the established ecological network, and applying the Minimum Cumulative Resistance (MCR) model to formulate the security pattern of the network. This approach underscores the importance of structured ecological planning in rural development initiatives. The analysis found that among the four types of rural green landscapes in the study area, the regional green space occupies a dominant position, with an LSI value of 116.1734, mainly large patches with uneven spatial distribution, and based on the Putian Rural Minimum Cumulative Resistance Surface Model = 0.41*Land Use + 0.33*Slope + 0.26*Distance from Water Bodies, the Putian Rural Landscape Ecological Network with a nucleus, a belt, five axes, and multiple points has been formed. The research in this paper provides a reference basis for the development of the Putian countryside and helps revitalize the Putian countryside.
Analysis of National Wave Brand Value and New Consumer Class Loyalty Combined with the HIROSE Model
Authors: Ma Lan 
Published: May 2024

Abstract
With the continuous development of China’s market economy and the gradual transformation of market competition to brand competition, the brand has an increasingly important role for enterprises. Based on the HIROSE model, this study constructs the M-HIROSE model, which is more suitable for the evaluation of the value of the National Tide brand by adjusting the brand revenue, brand expansion power, and period. To explore the relationship between the loyalty of the new consumer class and national brands, multiple regression is used for analysis. By empirically analyzing the basic financial data of China’s five national tide brand operators in the past three years, the results show that the ranking of the final brand value of the enterprises and the ranking order of the loyalty drivers are consistent, and the loyalty drivers basically determine the final brand value of the enterprises. The direct effect of new consumer class loyalty on the National Tide brand is significant (R2=0.235, p<0.001). This study, based on the M-HIROSE model of the National Tide brand value assessment, is feasible, and the new consumer class loyalty has a significant effect on the National Tide brand.
Meta-Universe Enabled Digital Modeling for Urban 3D Reality Visualization
Authors: Xie Qian , Jiang Chao 
Published: May 2024

Abstract
The rapid acquisition of 3D data with high accuracy and efficiency, along with the reduction of production cycles and costs, are pressing challenges in the field of 3D reality modeling. This paper introduces a novel approach for urban 3D real-view modeling from a metacosmic perspective. Utilizing tilt-shift photography technology, this method captures three-dimensional data of urban scenes under the meta-universe framework. The data are then processed through an integration principle, combining DOM (Digital Orthophoto Map), DEM (Digital Elevation Model), and vector data to filter out interference. Subsequently, a high-density digital point cloud is generated using tilted imagery combined with aerial triangulation. This point cloud, along with a TIN (Triangulated Irregular Network) model, facilitates the construction of a comprehensive three-dimensional visualization model of urban environments, enabling detailed digital analysis. Data presentation demonstrates that with an increase in the number of image control points, the planimetric error decreases from 0.0536 m to 0.0388 m, reflecting a 27.61% improvement. Similarly, elevation accuracy improves from 0.0927 m to 0.0539 m, marking a 41.86% enhancement. This methodology supports the creation of highly precise and cost-effective three-dimensional realistic models of urban built-up areas, providing robust data support for the development and management of smart cities.
Research on the Application of Northwest Traditional Patterns in Modern Design under the Background of Big Data
Authors: Guo Duhua 
Published: May 2024

Abstract
Northwest traditional patterns possess a rich history and a distinctive artistic style, offering immense potential for innovative design applications. This paper delves into the integration of these conventional motifs into contemporary design frameworks. Initially, we employ the semantic differential method to select vocabulary for the perceptual assessment of Northwest traditional patterns when incorporated into modern designs. We analyze the components of the design samples and utilize the partial least squares method to construct a correlation model between the perceptual assessment vocabulary and the design elements. This approach facilitates a detailed correlation analysis between the application of Northwest traditional motifs and their perceptual evaluation, leading to the formation of associative links between the imagery vocabulary and design features. Subsequently, we define theme, symbol, composition, and color as independent variables, with audience preference as the dependent variable, to conduct a multiple regression analysis. This analysis explores the impact of these dimensions on audience preference. The findings indicate that the significance levels of theme, symbolism, composition, and color are all below 0.05, demonstrating a positive influence on audience preferences. Notably, symbolism, with a regression coefficient of 0.356, exerts the most substantial impact on audience preference. The established correlations between design elements and perceptual evaluations, alongside the analysis of design dimensions’ influence on audience preferences, provide valuable insights for the application of Northwest traditional motifs in modern design contexts.
Research on Industry-Education Integration Model of Vocational Education Applying Automatic Coding
Authors: Pei Shuguang 
Published: May 2024

Abstract
Many applied undergraduate institutions in China have recognized that the integration of industry and education is essential for the advancement and innovation of educational practices. To expedite the development of this integration within vocational education, this paper introduces the Genetic Automatic Coding Assisted Integration of Industry and Education Teaching Mode. This approach begins with the cultivation of vocational education talents in higher education institutions, offering a comprehensive analysis of the industry-education fusion mode and delineating its implementation strategies and guiding principles. Employing the principles of automatic coding, the curriculum content of this integration mode is represented through genetic algorithm gene coding. The model for genetic automatic coding in industry-education integration for vocational education is established by assessing the compatibility of the integration mode and incorporating mechanisms for conflict detection and mutation crossover. The empirical analysis reveals that in genetic automatic coding, the eigenvalues stabilize after approximately 200 iterations. This suggests that this method enhances scheduling effectiveness in the vocational education-oriented industry-education fusion mode. Moreover, the results indicate a significant improvement in educational outcomes: students in the experimental group, where this model was applied, achieved an average assessment score of 88.38, compared to 78.47 in the control group. This substantial improvement confirms that the industry-education fusion mode, underpinned by genetic automatic coding, not only enhances the quality of education but also boosts students’ mastery of professional courses.
Modular Application of Evaluation System for Innovation and Entrepreneurship Education of College Students--Based on Big Data Platform Analysis
Authors: Wang Zhen 
Published: May 2024

Abstract
Based on the objectives of innovation and entrepreneurship education for college students, this paper constructs the evaluation index system, utilizes the improved Apriori algorithm to mine the association rules between the indicators, and reflects the relevant influence between the evaluation indicators through the association rules with higher support and confidence. Meanwhile, based on the big data platform, an evaluation system for innovation and entrepreneurship education for college students is established, and the level of innovation and entrepreneurship education for students is evaluated. The analysis of the correlation rules between the evaluation indicators found that the support degree of the rule that students with stronger independent ability are better at grasping innovation and entrepreneurship opportunities is 29.97%, which provides a reference for the teachers’ teaching objectives and content development. The results of the empirical analysis of the evaluation system of innovation and entrepreneurship education show that the modular application of the evaluation system created in this paper has a positive effect, and there is a highly significant difference in the evaluation of the “Z13 personal willingness” index before and after the application (P=0.000<0.001). The correlation rule of evaluation indexes in this study lays a theoretical foundation for the effective development of innovation and entrepreneurship teaching, and the modularized application of the innovation and entrepreneurship evaluation system constructed in this paper can improve the level of innovation and entrepreneurship education in colleges and universities to a certain extent.
Effects of the BRI on Sustainable Development Evidence from a Panel Difference-In-Differences Method
Authors: Huang Jinghan , Qin Peng , Zhao Xuan 
Published: May 2024

Abstract
The paper calculates the economic system coupling coordination level of the countries along the Belt and Road Initiative (BRI) from 2000 to 2020. On this basis, the paper analyzes the eco-economic effects and mechanisms of the BRI using the difference-in-difference method. The research shows that the “Belt and Road” initiative will significantly improve the eco-economic system coupling coordination level of participating countries. A series of robustness tests, including parallel trend test, placebo test, control of other policy impacts, and replacement of the “Belt and Road” occurrence time, all show that this promoting effect exists. Second, the “Belt and Road” initiative has improved the coupling coordination level of eco-economic systems through trade and investment behavior, but its driving role still needs to be strengthened. The study confirms the global value of the BRI and offers a reference for crafting appropriate policies to enhance the sustainable development level of countries in the BRI.
The etymology study of “fetish opposition” based on FTA analysis and the police PR avoidance approach
Authors: Ge Sichen , Liu Yuanshuo , Luo Yudong , Wang Haiyang , Li Mingshuo 
Published: May 2024

Abstract
In the contemporary post-truth era, there is a marked increase in the individual’s need for emotional expression and self-awareness. This paper introduces and defines the concept of “Fetish Opposition” through etymological research. Employing fault tree analysis, this study analyzes the risk identification and structural importance of “Fetish Opposition” in the context of “Public Security Prohibition” enforced by police departments. This is approached from the perspective of security system engineering, aiming to elucidate the underlying issues and delineate strategies to mitigate the phenomenon of “anti-public security.” This exploration seeks to provide theoretical guidance for enhancing the effectiveness of public security organs. The findings indicate that “lack of law enforcement transparency” holds structural importance of 0.186 within the fault tree of “Fetish Opposition,” making it the most significant factor affecting the entire system. Based on this insight, the police public relations department could develop targeted strategies to prevent such situations, thereby also opening new avenues for research in social psychology and the stabilization of police-community relations.
The impact of homestead system reform on farmers’ well-being: an empirical study based on the structural equation model
Authors: Liu Zhaojun , Zhang Yige 
Published: May 2024

Abstract
The reform of the homestead system is an important way to vacate inefficient and idle land, revitalize the stock, and visualize the asset properties of homesteads in the vast rural areas nowadays. In this study, we first carry out the selection of indicators for measuring the changes in farmers’ well-being under the reform of the homestead system and take a certain region that has carried out the reform of the rural land system as an example and use the fuzzy comprehensive evaluation to measure the changes in the overall well-being of the farmers in that region and the changes in the well-being of the farmers in different villages. The impact of the reform of the homestead system on farmers’ well-being is modeled using structural equations, and the corresponding hypotheses and validations are carried out. The analysis shows that farmers’ well-being in the study area improved by 0.254 overall and by 0.208, 0.204, and 0.350 in urban, peri-urban, and remote villages, respectively. The reform of the homestead system of uncompensated withdrawal, compensated withdrawal, compensated use, and construction of houses by farmers all positively affected the improvement of farmers’ well-being, with the compensated withdrawal policy having the greatest impact (0.315). It is necessary to innovate the homestead system, safeguard and expand farmers’ property rights, promote the reform of the expropriation system, and explore the establishment of a reasonable homestead withdrawal mechanism to encourage the further enhancement of farmers’ well-being.
Research on New Chinglish usage Mode based on emotion computing model: Acceptance and Preference of Chinese College Students
Authors: Liu Xiaoman 
Published: May 2024

Abstract
This study delves into the characteristics and emotional dimensions of New Chinglish, scrutinizing its expressive connotations. By examining the inner architecture of an emotion computation model, we propose a multi-layered cognitive affective computing model. This model integrates personality traits, mood states, and emotional conditions to refine the mapping relationship between PAD mood states and emotional responses. We introduce this multi-layer cognitive model as a novel method for preference mining, integrated with multi-objective decision-making processes. Additionally, we investigate the reception of New Chinglish among Chinese college students by examining various layers of engagement. We categorize the emotional types of New Chinglish utilizing the affective computing model, explore the students’ reception towards positive or negative expressions, and analyze preference patterns based on the attributes of New Chinglish. The findings indicate a favorable overall acceptance of New Chinglish among Chinese college students, with average scores for usage attitude and behavioral intention being 3.215 and 3.236, respectively. The three most favored aspects are humor (2.7986), phonetic appeal (2.5805), and innovativeness (2.4325).
Face orientation recognition based on Kinectv2 and an improved ELM model
Authors: Li Houcheng , Li Yanfei 
Published: May 2024

Abstract
Face orientation recognition is a crucial component of human behavior analysis. Challenges such as face occlusion and varying lighting conditions frequently degrade recognition accuracy. This study introduces an innovative approach using the Kinect sensor’s skeleton tracking technology to capture face orientation images across different lighting scenarios. To enhance image quality, techniques such as light attenuation and compensation are applied. Furthermore, multiple feature vectors based on face orientation are extracted and fused, followed by the optimization of the Extreme Learning Machine (ELM) model through the Archimedean Optimization Algorithm (AOA). The developed AOA-ELM model for face orientation recognition is compared with traditional models, including Back Propagation (BP), Radial Basis Function (RBF), standard ELM, and Genetic Algorithm enhanced ELM (GA-ELM). The AOA-ELM model exhibits superior performance in estimating face orientation amidst lighting disturbances, achieving an accuracy exceeding 95% in varied lighting conditions, thereby outperforming other classification models.
Combining the streamlined bilinear attention network of preschool teaching young children’s learning habit cultivation
Authors: Zhao Jianheng 
Published: May 2024

Abstract
In the preschool education period of young children, the cultivation of good learning habits is launched for young children, and the value is gradually increased along with the growth of young children’s age, which ultimately leads to the development of children. The DSBC dataset is manually completed after collecting and classifying the learning behaviors of young children in this paper. The dataset is expanded by using data enhancement, and a bilinear convolutional neural network-based model for learning behavior habit detection for young children is proposed. The embedded attention module is utilized to create a simplified bilinear attention network model, and the SLBAN model is employed in real preschool teaching work. After the experimental analysis, the model of cultivating young children’s learning habits proposed in this paper produced a 27.65% amount of change in young children’s self-efficacy. Meanwhile, the F-test value was 265.255, P<0.01, which showed a significant positive influence effect. In the analysis of young children’s interest level in learning, the overall interest level of student #1 in the classroom for 40 minutes remained around 0.5, which indicates a high level of interest in learning.
Robot kinematics analysis and trajectory planning based on artificial potential field method
Authors: Li Yayun , Zhang Dawei 
Published: May 2024

Abstract
In order for a robot to complete a given task, it must first be made to autonomously reach a specified target location, so optimizing the robot path trajectory planning is a prerequisite for the use of robots. In this paper, for the two problems of the traditional artificial potential field method of target unreachable and local optimization, we first improve the repulsive potential field function so that the robot’s gravitational force and repulsive force are zero at the target position and then construct the robot kinematic analytical model by setting the virtual target point away from the local minimum value point. On this basis, the improved algorithm is used to compare simulation experiments in three environments with the real trajectory planning test in the showroom. In the climate “near the obstacle of the target point” and the pure U-shaped area environment, the robot of the traditional APF algorithm cannot reach the target point. However, the algorithm in this paper reaches the target point in all three environments, with a time taken of only 21, 33, and 42 seconds, respectively. In the real trajectory planning of the showroom, the improved algorithm in this paper reaches the target point quickly and accurately, with a total path trajectory length of 77.7835m, a time of 43 seconds, and a total turning angle of 793°. This paper provides an effective method for planning robot path trajectories in a complex and variable environment.
The Construction and Application of the Effectiveness and Dynamic Teaching Evaluation Model of Big Civic and Political Science Courses
Authors: Dai Jixiu , Kang Xiancai 
Published: May 2024

Abstract
How to make the teaching quality of the Civics and Political Science class continuously improve, the teaching effectiveness is highlighted in the growth of students, and the comprehensive development of students is effectively promoted, which has become an important part of the educational evaluation reform of the Civics and Political Science class in colleges and universities. Based on the construction concept of the objectivity evaluation index system, this paper determines the evaluation index system of the effect and dynamic teaching of the big Civic and Political Science class. It adopts expert knowledge to pre-process the research data. According to the judgment affiliation degree and weight set, determine the single-factor evaluation matrix of evaluation indexes, calculate the weight value of evaluation indexes, and then complete the construction of a fuzzy comprehensive evaluation model oriented to the effect of big Civic and Political Science teaching and dynamic teaching and based on the data analysis software, carry out the comprehensive evaluation and analysis. The results show that the size of the weight value of the first-level indexes in order of magnitude, dynamic teaching process A2 (0.5478) > teaching preparation A1 (0.2353) > big Civics effect A3 (0.2169), indicating that the weight accounted for by the dynamic teaching and teaching preparation is relatively large and there is a not-so-small gap between the weight value of the big Civics effect A3, so the teaching of big Civics courses should focus on teaching preparation and dynamic teaching. This study can not only enrich the teacher’s Civics teaching method, but also improve the students’ Civics level, which has a promoting effect on promoting the development of the teaching of Big Civics courses in colleges and universities.