bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection and Application of Concrete Compressive Strength with Machine Vision Technology
Authors: Chen Yan , Zhou Hailong 
Published: July 2024

Abstract
This paper proposes research on concrete compressive strength detection based on machine vision technology in response to the problems of traditional concrete compressive strength detection methods. The original image is directly input into the network for training. There will be too much memory occupation. The efficiency is too low, it needs to be visually preprocessed to meet the requirements of the dataset to establish a high-performance concrete compressive strength detection network model. Then, the processed high-performance concrete compressive strength feature images are inputted into the Mask R-CNN network. The compressive strength features are extracted and trained by the convolutional neural network. Then, the extracted features are further processed with a bilinear difference to ensure their integrity, and finally, the construction of the high-performance concrete detection model based on Mask R-CNN is completed. Simulation experiments are used to analyze the detection and application of high-performance concrete using the theory of machine vision. The data show that the training and validation accuracies of the Mask R-CNN model are 96.75% and 96.52%, respectively, which are 5% and 3.77% higher than that of the migration learning network model (91.75%, 92.75%). In addition, the predictions of the Mask R-CNN model have a relative error of less than 0.05 compared to the actual values. The research presented in this paper is applicable to field strength testing of common concrete structures and can provide theoretical references for the study of construction materials.
Application of Real-time Motion Capture Technology in Street Dance Movement Analysis and Optimization
Authors: Zeng Yuhao , Zhao Shuang 
Published: July 2024

Abstract
With the advancement of motion capture technology, its application in dance movement training has become increasingly prevalent. This study explores the use of real-time dynamic capture technology for the analysis and optimization of street dance movements. A street dance movement system based on real-time motion capture technology is designed. Initially, the data obtained from sensors are fused using the Extended Kalman Filtering gesture fusion algorithm to identify street dance movements. Subsequently, the gestures of the street dance movements are matched with template movements using the DTW algorithm, facilitating movement optimization. Finally, the system is scrutinized for its performance and application analysis. The number of concurrent users of the system is in the interval of [90,99], and the average response time for uploading street dance moves and street dance move evaluation is 7.631s and 0.35s, respectively, which basically meets the design objectives. The maximum error, average absolute error, and root mean square error of the pose angles solved by the algorithm in this paper do not exceed ±1.61°, 0.20°, and 0.25°, respectively, and the algorithm is highly accurate and smooth, which meets the requirements of pose solving. Through the evaluation of 12 training learning results of 6 testers, it is found that the movements of the testers are more and more similar to the template movements after several training sessions, which verifies that the system in this paper can guide the learners to learn and optimize the street dance movements.
Personalized and humanized design of building interior environment using IoT technology
Authors: Qiao Mingzhe , Lv Yumei , Li Shaoli , Zhang Hongtao 
Published: July 2024

Abstract
The application of Internet of Things (IoT) technology has become more and more widespread, and the smart home based on IoT technology has penetrated thousands of households and the design of the internal environment of the building is also gradually intelligentized and digitized. This study realizes the personalized and humanized design of IoT technology in the internal environment of buildings through the design of a personalized smart home system based on IoT, which focuses on the use of the Apriori algorithm to mine the association rules of the user’s preferences for the internal environment of the building. Then, it uses the GA-BP neural network algorithm to predict the audience’s preferences and the PMV indexes so as to achieve the personalized and humanized design of the smart home system. And human-centered design. The system is evaluated for its performance and practical application, and the design effect of the building’s interior environment is examined. The network bandwidth bottleneck of the system is 2M, and the absolute error of the GA-BP prediction model is within (−0.04, 0.19), with an average accuracy of 99.245% and an improvement of 20.38% over the BP prediction model. The importance and satisfaction of all the scenario models of this system are within (3,5), the scenario model settings are more reasonable, the user satisfaction is high, and it can meet the user’s personalized and humanized needs. The results of this research can guide the personalized and humanized design of the internal environment of the building and provide certain theoretical references for the systematic study of the design of the internal environment of the building.
Research on the Teaching Quality Assessment System of “Great Civics and Politics Class” in Private Colleges and Universities in Jilin Province Based on Data Mining Algorithm
Authors: Yang Cuiping 
Published: July 2024

Abstract
The effective integration of the Civic and Political Science Program into higher education and its positive impact on the career and ideological development of students is not only the purpose of setting up the Civic and Political Science Program but also a prominent manifestation of the fact that colleges and universities attach great importance to the effectiveness of educating people. This study aims to construct a teaching quality assessment system for “big ideology and politics course” in private colleges and universities in Jilin Province, effectively utilize the results of the development of data mining technology, and better provide advice for the development of ideology and politics course education in colleges and universities. The study utilizes cluster analysis in data mining technology to derive the overall assessment items of the teaching quality assessment system, i.e., the four aspects of teaching preparation, teaching implementation, teaching effect, and teaching research. Different weights were assigned to four items, 13 primary indicators, and 53 secondary indicators in the assessment system using the improved Apriori algorithm. From the constructed teaching quality assessment system of “big ideology and politics course” in private universities in Jilin Province, it can be seen that the highest weight of teaching effect indicators among the four evaluation items is 0.35, and the highest weight of student learning indicators among the teaching effect indicators is 0.57. Such a hierarchical progression can be concluded that the teaching quality of “big ideology and politics courses” in private universities in Jilin Province has been improved by the Apriori algorithm. It can be concluded that private colleges and universities in Jilin province, in the process of educational practice and construction of “big ideology and politics course”, should focus on the teaching effect of the course and, at the same time, should give full play to the students’ subjectivity and creativity in the process of the course practice, so as to push the education and teaching of “big ideology and politics course” to a new level.
A Study of Characterization and Scene Interaction Narratives of Animated Characters Empowered by AIGC
Authors: Yan Lili 
Published: July 2024

Abstract
The development of artificial intelligence technology has become an important trend today and also provides rich means for the development of the animation industry. In this paper, a three-dimensional skeleton extraction model is first proposed through skeletal coordinate transformation, and then a skin deformation technique based on LBS linear hybrid skinning technology is introduced to complete the construction of the character animation generation algorithm. On this basis, a statistical-based scene layout template generation algorithm is proposed to extract spatial relationships in the corpus using the spatial semantic information extraction method and calculate the occurrence probability of objects so as to realize the generation of animated scenes. The PSNR and SSIM scores of the new model have improved by 6.3 and 0.53 points, respectively, when compared to the old model. The recognition accuracy of the latest model reaches 99.6% at a 15° rotation angle and 97.9% at a 30° rotation angle. The average score of the audience for the AIGC-enabled animation scenes is 7.5, which is satisfactory in general. The AIGC-enabled animation character characterization and narrative scene generation have been found to have acceptable results.
Research on Channel Modeling of UAV Based on Artificial Intelligence Reflective Surface
Authors: Ju Jiatian 
Published: July 2024

Abstract
Artificial Intelligent Reflective Surface (AIRS) is a kind of artificial two-dimensional surface with special electromagnetic properties that can control the absorption, reflection, and refraction characteristics of electromagnetic waves, thus realizing the modulation of the channel. It has a broad application prospect. Based on the fading characteristics of wireless channels, the article explores artificial intelligent, reflective surface-related technology and establishes an IRS-assisted UAV-MIMO channel model in combination with the wireless communication link of the UAV. For the statistical characteristics of the UAV channel, wireless in-site simulation software is used to carry out simulation analysis of its impulse response, space-time frequency correlation function, path fading, Doppler power spectral density, and other statistical characteristics. The peak value of the UAV path loss decreases from 143.8 dB to 129.9 dB when the wind speed increases from 6 m/s to 18 m/s in a fixed-height ground environment, and the communication delay distributions are between [0,450 ns] and [0,1550 ns] when the hovering height of the UAV is 100 m and 500 m, respectively. The Rice factor’s Doppler power spectral density value decreases by 53.48% when it is reduced from 1.2 dB to 0.05 dB. The absolute envelope amplitude of the channel of the UAV fluctuates between [-26.3 dB and 21.8 dB] after the optimal reflective phase design based on IRS adaptation. The use of AI reflective surfaces can facilitate the construction of the UAV channel model, thereby improving the communication quality of the UAV channel.
Construction of a model of differentiation in music teaching combined with the theory of multiple intelligences
Authors: Yu Yuanyuan 
Published: July 2024

Abstract
This paper summarizes the theory and nature of multiple intelligences and differentiated pedagogy and proposes a differentiated teaching model that integrates learning styles with numerous intelligences theory. Based on this model, the system provides each learner with a personalized learning program and dynamically generates a sequence of activities that align with the learner’s style characteristics. Teaching cases illustrate the practical application of multiple intelligences differentiated instruction in music classes. Results indicate that prior to implementing Multiple Intelligences Differentiated Music Teaching, student interest in music and music appreciation lessons declined with age, with only 67 students expressing a strong liking for music by the third grade. Following the implementation of differentiated music teaching, the percentage of students who appreciate the repertoire increased to over 41% across all grades and continues to rise. Creating a differentiated music teaching strategy according to students’ intelligence characteristics is effective and significantly promotes the development of students’ multiple intelligences, particularly bodily-kinesthetic, musical, and self-cognitive intelligence (P<0.05).
An Accuracy Study of Personalized Recommendation System for E-commerce Based on Big Data Analysis
Authors: Zhang Hua 
Published: July 2024

Abstract
E-commerce, as an emerging value chain model for the global economy, has greatly promoted development, while the impact of digitalization on traditional publishing enterprises is increasingly evident. In this paper, we propose a TextRank keyword extraction algorithm based on comprehensive weights, which extracts and assigns keywords that identify user information, behavior, and product characteristics. We then output a keyword weight table for user information, user behavior, and product keywords. Finally, utilizing an optimized collaborative filtering recommendation algorithm, we establish a recommendation model between the user-commodity matrix to build an e-commerce personalized recommendation system that provides users with more accurate customized recommendations. The practical application of the designed personalized recommendation system is examined to evaluate its accuracy. The MAE of this algorithm is smaller than that of user-based (0.8915, 0.9470) or item-based (0.8873, 0.9327) collaborative filtering algorithms, indicating that the improved collaborative filtering algorithm effectively enhances system recommendation accuracy. The direct effect value of recommendation strength is 0.344, with an indirect effect value of 0.018, leading to the highest overall effect value. This study provides users with convenient and attentive services, significantly enhances user experience quality, and generates substantial profits for the e-commerce platform.
Research on Case Study and Teaching Improvement of Civic Education Based on Ethics Theory
Authors: Sun Siyao , Ye Chaochen 
Published: July 2024

Abstract
Curriculum Civic and Political Education is the requirement of cultivating talents in colleges and universities in the new era, and comprehensively promoting the construction of curriculum Civic and Political Education is a strategic move to implement the fundamental task of establishing morality and educating people. This paper begins with the case of civic and political education based on ethics and explores the case study approach to education. Then, it combines the DEMATEL algorithm and explanatory structural equation modeling and utilizes the DEMATEL-ISM algorithm to dig out the influencing factors affecting Civic and Political education so as to propose the improvement of the Civic and Political education method based on ethics. Furthermore, the improved teaching method is applied to explore the effects of civic and political education by combining the independent sample t-test method. Among them, the concept of nurturing, the idea of intention, and the environmental atmosphere, with a centrality of 7.982, 7.173, and 7.162, in turn, are the key influence indicators of ideological and political education. There are significant differences (P<0.01) in the experimental classes in the dimensions of patriotism and idealism education, dialectical materialism education, scientific quality and social responsibility education, and ethical teaching. In the case analysis process of the silent running through the Civics, to explore the application of curriculum Civics in the process of ethics case teaching, and to promote the deep integration of ethics case teaching and curriculum Civics.
Quantitative modeling and empirical analysis of the communication effects of cross-cultural economic discourse
Authors: Zhang Tingfang 
Published: July 2024

Abstract
In cross-cultural economic communication, language, culture, and business activities are closely linked. In order to construct China’s foreign economic discourse system, this study selects five types of economic discourses of China’s cross-cultural communication, climbs relevant research data, and tries to use the improved AHP-CRITIC combined assignment method to convert the abstract foreign communication effects into measurable indexes, and establishes a set of comprehensive and systematic quantitative assessment model of the impact, so as to make the communication effects of the assessment objects comparable. We summarize the degree of influence of each indicator on the communication effect of the five types of cross-cultural economic discourse based on their assigned weights. We also quantify the communication effects of the five types of economic discourse based on the differences in the TOPSIS method. The dissemination effects of the five types of cross-cultural economic discourses are ranked as follows: “Belt and Road Initiative” (0.64215), “China’s Financial Reform” (0.55381), “China’s Economic Reform” (0.41473), “China’s global economic role” (0.39387), and “China-US economic relations” (0.28852). From the perspective of audience cognition, attitude, and behavior, this study suggests that the effect of foreign communication on cross-cultural economic discourse can be enhanced through three aspects: strengthening communication media, innovating content production, and strengthening the content production and construction of economic discourse.
Three-dimensional modeling of ancient yiyuan architecture using static laser scanning technology
Authors: Yin Shimei , Chuan Qin , Gang li , Jingjing Chen 
Published: July 2024

Abstract
The awareness of protecting traditional culture and humanistic landscapes is increasing year by year, and the protection of ancient gardens is becoming more and more a consensus among people. This paper takes the architectural profile of Guyi Garden as the research basis, introduces the specific application of 3D laser scanning technology, plans the scope of architectural data acquisition in Guyi Garden, and designs the corresponding architectural data acquisition program. With respect to the acquired point cloud data of GuYiYuan, the bilateral filtering algorithm is used to reduce the noise of the data, the curvature thinning algorithm is combined to reduce the point cloud data of the buildings in GuYiYuan, the point cloud data are spliced based on the connection point, and the ICP algorithm with the introduction of the optimization of the rotational angle constraints is introduced to realize the alignment of the point cloud data. In addition, the shadows generated from the point cloud data are removed by combining the relighting method, and the linear transformation method is also used to globally correct the texture image generated from the point cloud data. The point cloud density was reduced from 0.95m² to 0.01m² when the thinning rate was increased from 8% to 96%, and the alignment error of the improved ICP algorithm under 25dB Gaussian white noise was only 0.083*10-4mm. The maximum error accuracy of the two-dimensional model of Yiyi Nodang generated based on the point cloud data was only 0.007m, and the error of the three-dimensional model was controlled to be within the range of ±9mm. Accurate architectural data can be obtained through the use of 3D laser scanning technology, leading to a new method for digitally preserving historical buildings.
Study on the Synergistic Development of Business Environment Optimization and Industrial Upgrading in the Area: Based on the Perspective of Investment and Financing
Authors: Liu Chao , Li Xing 
Published: July 2024

Abstract
The business environment is the starting point and foothold of industrial upgrading, and it is also an important driving force for industrial upgrading. This paper is based on the investment and financing perspective to study the optimization of the business environment in the area of industrial upgrading to promote and promote the role of the two so as to achieve the effect of synergistic development of the two studies were constructed in the area business environment and industrial upgrading index system, and in the entropy weighting method of the indicator assignment, selected the relevant regional research data, through the linear weighting method to measure the level of development of the two. Empirical testing of the influence of the business environment on industrial upgrading is conducted by selecting the fixed-effect model, and investment and financing are added as an intermediary variable in the benchmark model. Finally, according to the empirical study of the impact of the business environment on industrial upgrading, it is concluded that in the benchmark regression analysis, with the introduction of control variables, the business environment shows a significant positive impact on industrial upgrading at least at the level of 10%. Meanwhile, investment and financing have an important mediating effect on the influence of the business environment on industrial upgrading.
Construction of innovation and entrepreneurship teaching capacity in colleges and universities and its optimization path based on differential equation modeling
Authors: Lian Fangfang , Zhang Peng 
Published: July 2024

Abstract
The rapid development of information and artificial intelligence technology has brought new opportunities for innovation and transformation in higher education, leading to innovative applications of data-driven-assisted teaching decisions. This paper analyzes the equilibrium point in predicting students’ performance using nonlinear differential equations, solves the expected value of students’ performance, and constructs a prediction model for students’ innovation and entrepreneurship performance. Student achievement data and characteristics are preprocessed to improve the accuracy of the prediction model. Based on Pearson’s coefficient, students’ innovation and entrepreneurship achievement are significantly correlated with teaching ability (P<0.05). The results show that, after implementing innovation and entrepreneurship teaching based on this prediction model, the predicted achievement of students in the intervention group is significantly higher than that of students in the control group (P<0.05). In the actual achievement test, the average total grade for the innovative entrepreneurship course of students in the intervention group was about 4.68-8.78 points higher than that of students in the control group. The achievement prediction model developed in this paper, along with the proposed optimization path for building innovation and entrepreneurship teaching capacity, offers significant guidance for the teaching research department in implementing effective teaching interventions and in the development of innovation and entrepreneurship education.