bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on art design and application of cognitively oriented thinking in the following creative products
Authors: Cui Ronghua , Chen Liyuan 
Published: January 2024

Abstract
At present, the knowledge of cultural relics in cultural creative design is fragmented and fragmented, and lacks the support of a unified system. In this paper, firstly, with the help of a topological model to characterize the creative process of image thinking, effective reasoning is carried out on the objects, things and relations of cultural and creative products according to the expansion analysis of primitives. Then, a conceptual network of art design for cultural and creative products is constructed based on semantic association, and an identification model of art design elements for cultural and creative products is built based on quantitative theory. Finally, through the experiment of art design for cultural and creative products, the perception of cultural and creative products was analyzed in multiple dimensions. The results show that the maximum factor influencing the value of art design of cultural and creative products is 0.951, among which the cultural characteristics have a strong correlation with the color characteristics of 0.642, and the functional characteristics have a strong correlation with the cultural characteristics of 0.837. The results of this paper provide new ideas and methods for the development and maturation of artistic design of cultural and creative products.
Personalized teaching of college psychology based on information fusion technology
Authors: Huang Tao 
Published: January 2024

Abstract
This paper explores the cognitive attention mechanism in mental activities, analyzes the learning emotion contained therein as well as the information of thinking activity that carries out the whole cognitive process of mental learning, and obtains the information construction data of the three-dimensional interest model after the estimation of the learner’s head gesture and the recognition of dynamic expression. A conditional random forest model is built using multimodal information fusion technology, and a natural smile detection method is proposed based on it. After training, it realizes the information estimation of the learner’s head pose data, generates the smiley face classifier based on conditional random forest, and determines the teaching decision boundary using K-Means clustering. To analyze the psychological personalized teaching results of the model, an empirical study is conducted through a controlled experiment. The experimental results show that the learning efficiency of the model on the CelebA dataset and SMILEsmileD dataset is improved, the accuracy rate is stabilized at 95% after the number of iterations 10, and the model’s performance is superior. The majority of the students in the experiment have a mastery of psychological knowledge that is around 0.85, and there is a significant positive correlation, and personalized teaching has a more significant effect.
Research on Curriculum Construction and Capacity Cultivation of Innovation and Entrepreneurship Education in Colleges and Universities in the Context of Digital Curriculum Civics and Politics
Authors: Wang Cong , Liu Yuening , Yin Huamin 
Published: January 2024

Abstract
When colleges and universities develop courses on innovation and entrepreneurship, they frequently concentrate on teaching theories related to these topics, which results in students having limited practical skills. Based on the complete assessment approach, this research develops a coordinated development model for innovation and entrepreneurship education in the context of civics and politics. It examines the components of education related to innovation and entrepreneurship, as well as the supporting role that the civics curriculum plays in these areas. Three factors, namely the objective, content, and development prospect, are considered when analyzing the applicability of the Civics and Politics course to teaching innovation and entrepreneurship. Establish the coordinated degree value of digital curriculum development and the creation of college entrepreneurial and innovative education curriculums. Determine the degree of link between civic and political matters by using them as a reference point. The current state of education in entrepreneurship and innovation in colleges and universities is analyzed using the coordinated development model, and corresponding solutions are put forth for the issues with curriculum development and entrepreneurial ability. The findings demonstrate that the range of [0.6,0.85] is often where the teaching impact of integrating curriculum and practice falls. After combining politics and ideology with innovation and entrepreneurship education, the percentage of students who said that their entrepreneurial aims were to gain money fell from 0.8751 to 0.2103. In order to allow students’ values and opinions to be reflected in the new curriculum for innovation and entrepreneurship education, this study combines the benefits and resources of politics and ideology with the study of innovation and entrepreneurship.
Research on Teaching Resource Management in Colleges and Universities Based on Multiple Data Chain Networks
Authors: Wang Kunpeng 
Published: January 2024

Abstract
In this paper, we first take the datalink network as the entry point and construct a university teaching resource management model based on a multivariate datalink network. A Link-22 data chain time synchronization algorithm with KF-RTPT is proposed to address the actual existence and unavoidable time deviation based on accuracy and timestamp acquisition errors. Meanwhile, a time slot allocation and optimization algorithm designed to maximize message transmission benefits is being developed to optimize the allocation of node time slot requirements. Finally, the constructed teaching resource management model is empirically analyzed from three perspectives: error optimization, dynamic time slot allocation, and model application effect. According to the findings, the KF-RTPT algorithm increases motion error efficiency by 3.83 in low-speed motion states and 8.16 in high-speed motion states when compared to the conventional RTT method. This effectively eliminates motion error and boosts the effectiveness of teaching and managing resources in colleges and universities.
Mining and Teaching Design of Civic and Political Elements in Digital Electronics Technology Course Based on Markov Modeling
Authors: Zhang Jie 
Published: January 2024

Abstract
This paper proposes a course knowledge resource extraction method based on the improved Hidden Markov Model and combines the method with hierarchical classification ideas. The improved Hidden Markov Model is used in the study of the text classification process of course knowledge resources, the expected cross entropy selects the feature words, and the semantic space composition is obtained by using the implicit semantic indexing method. When setting the observation output probability matrix for the HMM classifier model, the improved TFIDF method is introduced to reflect the semantic relations between feature words. An evaluation criterion such as macro-micro mean is used to analyze the performance of the whole text set classification and gradually improve the HMM model. Finally, the HMM resource information extraction model has been improved to mine the elements of civics in digital electronics technology courses. It is found that in the compulsory textbook knowledge of digital electronics technology, the trigger knowledge has the greatest integration degree with the Civic-Political elements with a percentage of 0.3382, followed by the analog-digital and digital-analog converter knowledge with a percentage of 0.2818. In the textbook column on digital electronics technology, the extended knowledge has the greatest integration degree with the Civic-Political elements with a percentage of 0.5043, followed by the strengthened category column with a percentage of 0.1712. The analysis of the students’ different Civic-Political dimensions after the instruction has been done. In the political identity category, national sentiment, scientific spirit and ecological environment topics improved by 7.23, 2.01, 3.2 and 2.14 points, respectively. It shows that students can improve their cultural knowledge in digital electronics and establish a correct worldview, life view, and values.
Exploring the Development, Dilemmas and Countermeasures of College English Teaching by Combining the Hierarchical Analysis Approach
Authors: Xu Jiayu 
Published: January 2024

Abstract
College English teaching has formed a long-term historical persistent problem in the process of higher education expansion, and it is urgent to explore its development dilemma and corresponding countermeasures. This study uses hierarchical analysis to analyze the connection between relevant factors in English teaching activities, constructs a judgment matrix for teaching evaluation, establishes the index ordering through a consistency test, and applies intuitive fuzzy logic to establish the index weights. At the same time, a genetic algorithm was applied to the weight optimization process to iterate the better matrix indicator weights. After verifying the optimization effect through experiments, the comprehensive assessment method was applied to specific teaching cases and analyzed. The comprehensive evaluation results of students, teachers, and experts were obtained respectively, the latter being [0.3459 0.2961 0.1848 0.1086 0.0636]. The final evaluation result of the university English teaching case is [0.3358 0.2790 0.1874 0.1272 0.0695], which corresponds to the grade of “general”. Through the evaluation of university English teaching, the difficulties of current English teaching are fed back, which lays the foundation for the countermeasures to be put forward.
Research on the Innovation of Piano Music Teaching in Colleges and Universities Based on the Characteristics of Music Culture
Authors: Hu Dongming , Zheng Ying 
Published: January 2024

Abstract
Starting from the communication characteristics of piano music culture in colleges and universities, this paper proposes a piano music signal detection technology that includes two parts: note onset and fundamental frequency detection. Based on the characteristics of the harmonic structure of the music signal, the degree of harmonic matching between the signal to be recognized and the standard note signal is calculated, and the task of multi-fundamental frequency estimation is accomplished by using the timbre characteristics and harmonic structure. The detection technology of piano music signals is applied to the recognition of teaching short notes, playing music and playing evaluation to get a new model of piano music teaching in colleges and universities. The results show that the algorithm in this paper can recognize piano music correctly by more than 91%, and the method has no obvious decrease in recognition rate in the process of gradually increasing noise, which is conducive to improving the effect of piano music teaching in colleges and universities.
Study on the Application in the Protection and Renewal of Ancient Architectural Cultural Heritage in the Age of Smart Media
Authors: Jiao Ziyun 
Published: January 2024

Abstract
In this paper, the candidate region network in the Fast R-CNN algorithm is used to obtain the feature values of surface damage of ancient buildings, and the regression algorithm is applied to the target bounding box after the features are successfully obtained, which can more accurately complete the task of detecting and locating the damage on the surface of buildings. The three-dimensional laser scanner and total station are used to explore the surrounding environment of the buildings on the site, and the sketch is drawn according to the research and analysis results combined with the exploration to design a digital archive of the cultural heritage of the ancient buildings. Aiming at the ambiguity of the assessment system of the integrity of ancient buildings, we constructed the assessment system of the cultural heritage of ancient buildings with the fuzzy affiliation of the data of the integrity of ancient buildings and multilevel fusion assessment and carried out an example analysis of the research on the protection of the cultural heritage of ancient buildings in the era of smart media. The results show that when the number of iterations is 15000, the mAP value is 0.9411 (where 1 represents the maximum AP value), which is higher than the training results with the number of iterations of 20000 and 25000, i.e., the Faster R-CNN training model has good applicability for the autonomous visual detection of the damage on the surface of the ancient buildings. “Q9 I will not damage the ancient buildings in Zhuge Village” has the highest mean value of 4.71 and the highest approval rate of 99.1, and the standard deviation of each question item is small, i.e., it indicates that there is a high degree of consistency in the positive attitudes of residents towards the protection of the cultural heritage of ancient buildings. This study contributes new ideas to the protection of ancient architectural, cultural heritage and tourism development, which is crucial for advancing the research field.
An Analysis of the Impact of Insider Trading on Executive Compensation in Listed Companies Based on VAR Modeling
Authors: Jin Li 
Published: January 2024

Abstract
In this paper, we first establish a VAR model, screen the variables using the CSIS method so as to achieve fast dimensionality reduction, and use the cointegration theory to model non-stationary time variables to determine the pseudo-regression analysis between variables. Impulse response functions and variance decomposition are then used to analyze the dynamic effects of changes in random disturbance terms on the whole system and other variables. Finally, the effects of insider trading on executive compensation are explored using corporate performance and market-based executive pay entitlement as references, respectively. The results show that the regression coefficients of executive compensation level and cumulative excess turnover rate of the event announcement period are 0.805 and 0.018 for corporate performance and market-based compensation, respectively, and the higher the level of executive compensation based on corporate performance and market-based compensation, the lower the impact of insider trading on executive compensation. Equity incentives reduce the impact of insider trading on executive compensation, and the regression coefficient of excess turnover on executive compensation is less than 0 in firms with shareholding levels higher than 10%.
Measures for the Integration of Digital Media Art and Film and Animation Creation Based on Virtual Reality Technology
Authors: Liu Yongchun , Li Juan 
Published: January 2024

Abstract
In this paper, we propose a scene animation network (FSGAN) method that uses spectral features to perceive the deep style of an image, which uses three loss functions for perceiving the distribution of image style features in the same style domain to generate anime style-consistent images. The recurrent consistency adversarial network is supplemented with a local reinforcement module based on self-attention, adapted to the animalization of portrait scenes based on their characteristics and needs. This module guides the network to pay attention to the salient regions in the image and combines layer normalization and instance normalization methods through the weighting of the attention weight coefficients to construct a portrait animation network based on local reinforcement perception. Then, based on the digital media technology to complete the virtual reality scene construction, the constructed space for three-dimensional division, and the use of generative adversarial network training model, the proposed key events and random sampling technology combined with the control of virtual animation scene generation method, to achieve the controllability and diversity of the virtual animation scene generation. The first-stage design efficiency, the second-stage design efficiency and the overall design efficiency of the animation creation method in this paper are all basically stabilized between 0.8-1. Compared with the traditional method, they are higher by 0.3932, 0.3596, and 0.5635, respectively. The extreme pixel percentage, standard deviation and contrast of the animation images created by this paper’s method are 0.0349, 0.0037 and 0.3382, respectively, and the overall color performance is better. Thus, the method presented in this paper has the best overall effect on processing anime images using digital media art effects.
A Study on the Relationship between Human Resource Management and Firm Performance Based on VAR Modeling
Authors: Qin Yue , Lv Di 
Published: January 2024

Abstract
In this paper, after analyzing the VAR model, we design the Gram causality test between human resource management and enterprise performance and establish a structural equation combining multiple regression and factor analysis to explore the interrelationship between the two, in addition to evaluating enterprise performance based on mutation theory. In order to study the relationship between human resource management and enterprise performance, assumptions are made about the relationship between the two, a conceptual model of the role path relationship between human resource management and enterprise performance is established, and the proposed assumptions are empirically analyzed based on the existing literature and actual data. The results show that the coefficient of HR practices is 10.048343, which is significant at the 0.0031 level, and the goodness of fit is 0.403881, and HR practices do have a relatively significant impact on business performance, and the marginal impact is 10.048343, which indicates that HR practices significantly amplify business performance. This study confirms that human resource management is positively correlated with firm performance and that firms can optimize their human resource management strategies, which in turn will enhance their performance and provide impetus for their progress and development.
Research on action recognition for college dance teaching based on deep learning
Authors: Wang Rui 
Published: January 2024

Abstract
In this paper, Gaussian modeling is established to perform background subtraction of action feature images of dancers and combined with median filtering to denoise the background of feature images. The cumulative edge feature algorithm extracts relevant features from the dance dataset using the dance itself. Based on this, the directional gradient is introduced to output the extracted dance histogram features and cascade the optical flow histogram feature vectors in all blocks to form the HOF features of the image. The deep learning model is used to design the dance teaching model, and the teaching objectives are determined. The effect of dance teaching is tested through the method of simulation experiments and empirical analysis. The loss value of the model without deep learning is very high, reaching 1.25, and the loss values after convergence of the parametric model using deep learning are 0.85 and 0.95, and the deep learning algorithm has a better optimization effect on the model. The scores of the seven measures of teaching effectiveness are all above 12, and the significance p-value of each indicator is <0.05. The dance teaching effect is significant.
Innovation of Civic Education Path in Colleges and Universities under the Integration of Big Data Technology
Authors: Chen Xinjie , Liu Zhiqin 
Published: January 2024

Abstract
In the era of big data, different countries and regions use big data in the field of education. This paper constructs a personalized teaching model for Civics based on big data text-mining technology. Combined with the DIKW pyramid composition structure analysis, it shows how the data can be used to guide the process of teaching decisions. The frequency of Civics keywords in the teaching classroom and the key teaching content in the Civics classroom are determined using the word frequency analysis method. Similarity and KNN calculations are used to classify the students’ civics knowledge level, and personalized teaching plans are developed for their level of knowledge. The application of personalized teaching in Civics is practiced from the aspects of tracking students’ knowledge status and enhancing personalized teaching effects. The results show that the average final grade of class A in the experimental group is 102.37, and the average grade of class B in the control group is 97.37 in the final exam. Class A students have an average grade that is 5 points higher than that of class B. The average grade of students in class A is 5 points higher than that of class B. The two groups are tested using independent t-tests. The results of the two groups were subjected to independent t-test, F=7.047, p=0.00, 8<0.05, variance is not uniform. The t-test results show Sig=0.048<0.05, which indicates that there is a significant difference between the final grades of the experimental and control groups.
Digital Information Technology Enabling Computational Thinking C Language Blended Teaching
Authors: Cao Jingxin 
Published: January 2024

Abstract
Digital information technology provides an innovative way for the obsolete and inefficient C language classroom. This paper applies computational thinking to the design of C language hybrid teaching and builds a task-driven model for teaching C language using a driven teaching approach. Digital information technology is applied to TDT teaching; test questions are dynamically extracted in the process of students’ tests, intelligently analyzed according to the student’s answers to the test questions, and a genetic algorithm is used to adjust the difficulty, differentiation and knowledge points of the group paper. Based on the hybrid similarity model, we optimize the mutation operation in the genetic algorithm and verify the effect of similarity calculation through the practice of grouping papers for C language teaching. Hybrid similarity yields weighted average similarity scores of test questions that are 0.14 and 0.16 higher than edit distance and cosine similarity, respectively. On the basis of similarity calculation, the time taken to improve the GA to generate the test paper is no more than 1 second, and the difficulty coefficient obtained does not differ from the expected coefficient by more than 0.05. The intelligent paper grouping method can maximize the coverage of the needs of more students and improve the investigation of C language teaching. The way of teaching C language.