bluuebunny/crossref_metadata_2025_split huggingface dataset:
Challenges and Opportunities of Civic Education in Colleges and Universities in Digital Environment
Authors: Zhang Xingli 
Published: June 2024

Abstract
Civic education in colleges and universities plays a pivotal role in fostering students’ national identity and civic responsibilities. Enhanced by digital learning environments, it promises to cultivate exemplary citizens more effectively. This paper details the development of a MOOC interactive communication platform utilizing the open-source edX framework, which serves to enhance civic education. It delves into optimizing resource storage technologies on the platform. It introduces an innovative assignment mutual evaluation algorithm tailored for Civics and Political Science education, which accounts for rater bias and scoring patterns. The newly implemented resource storage and mutual assessment algorithms have notably improved the functionality of the civic education platform. Performance metrics from the platform indicate an encouraging trend in student achievement across three courses, with average scores of 78.32, 79.24, and 83.27, respectively, showcasing a consistent upward trajectory. Further analysis reveals a converging trend in the variance of data distribution, indicating a reduction in disparities in student learning outcomes as evidenced by a decrease in standard deviation values. Comprehensively, students’ overall test scores have shown significant improvement. Notably, mastery of subject matter knowledge saw an increase from 2.3% to 21.4%, and the pass rate escalated from 92.6% to 98.3%. Although there were initial discrepancies in the cognitive rating of civic education values between the experimental and control groups, the experimental group exhibited substantial gains, underscoring the efficacy of the platform and its methodologies.
Assessment of Electricity Demand Response Potential under Consideration of Uncertainties
Authors: Zhang Xudong , Zhang Ran , Cao Xiaobo , Shan Yajing , Dong Hao 
Published: June 2024

Abstract
The assessment of customer electricity demand potential is a critical part of further stimulating electricity demand growth and promoting utility development. The main aim of this paper is to investigate how electricity demand response potential can be assessed under uncertainty. The decision variables are set through a two-stage stochastic planning model, focusing on fuzzy decision-making through linear programming in interval planning, combining with consequent opportunity constraint planning and fuzzy opportunity constraint planning to realize artificial regulation of unfavorable factors, and finally completing the treatment of uncertain factors. Combining a Gaussian mixture model to construct a model for measuring electricity demand response potential. It has been found that different electricity pricing policies lead to other potential demand response values for peak electricity load. The optimal electricity pricing and revenue of each user will be greatly affected by the participation of different users in the electricity demand response. The optimal power pricing decreases from 3-4 when the number of users is 4 to 2.5 when the number of users is 20 because of the generation of scale rewards, and the benefits to the users increase substantially when the number of users participating in electricity demand response is 20. Evaluating customer electricity demand in an uncertain environment can help drive electricity system reform to some extent.
Deep belief networks in understanding and predicting changes in students’ political attitudes
Authors: Pang Daojing , Wang Yanhui 
Published: June 2024

Abstract
Leveraging data collection software, this study gathered and preprocessed text data reflecting students’ political attitudes across five dimensions: political cognition, ruling party cognition, positive political emotion, negative political emotion, and political behavioral tendency. The processed data were subsequently stored in Excel format. These dimensions of change in students’ political attitudes served as inputs for a deep belief network (DBN) model, with the changes in attitudes being the outputs. The model’s parameters were meticulously tuned to optimize its predictive capabilities, aimed at effectively constructing a prediction model for shifts in students’ political attitudes using the deep belief network. To refine the model’s parameters and minimize errors during inverse fine-tuning, the chimpanzee algorithm (ChOA) was employed. This novel approach, termed ChOA-DBN, facilitated the successful construction of the predictive model for students’ political attitude changes. The model’s efficacy was assessed using the collected data on students’ political attitudes. Notably, the DBN model optimized via the chimpanzee algorithm demonstrated robust predictive performance, particularly when processing sample points exhibiting significant changes in students’ political attitudes (ranging from 20 to 45). The model’s predictions predominantly fell within a ±15% error margin. This research not only showcases the accuracy of the ChOA-DBN model in predicting alterations in students’ political attitudes but also underscores its potential contribution to fostering the development of accurate political perspectives among students.
GAN-based Visual Creative Generation Process Automation and Its Application Efficiency in Brand Image Design
Authors: Wang Qian 
Published: June 2024

Abstract
New social, economic, cultural, and technological trends bring new challenges to designers, and the use of data intelligence analytics is a very promising way to improve the efficiency and quality of their results. In this paper, we use convolutional neural networks to improve and optimize the GAN model, resulting in a more stable DCGAN network model. Visual innovation-related features are inputted into the discriminator in the DCGAN model, and creative visual images are automatically generated in the generator under the constraint label restriction. The network parameters of the DCGAN model are optimized through the training process to construct the brand image design process of automated visual creativity. The performance test analysis of the DCGAN model reveals that the analysis results of its IS index and FID index values are much higher than those of the WGAN and CGAN models, indicating that the generated visual creative images have high quality. The analysis of the visual creativity of the designed brand image found that the subjects’ favorability of the brand image intended by the DCGAN model reached 3.57 points on average and brought a visual feast to the subjects. This paper provides support for the application of Generative Adversarial Networks in the field of brand image design and achieves automated brand creative image design.
Sentiment analysis of ethnic artworks using deep learning
Authors: Wang Yanfang 
Published: June 2024

Abstract
Deep learning models, characterized by their complex network layers, have demonstrated significant utility in the recognition and classification of ethnic artworks, particularly excelling in emotion recognition within such works. This study delves into the convolutional neural network (CNN) model underpinned by deep learning algorithms. The architecture of the model—encompassing the convolutional layer, pooling layer, fully connected layer, and activation layer—is meticulously constructed to extract emotional features from ethnic artworks. Subsequently, an activation function is employed to visualize these features, followed by the integration of emotional knowledge to optimize the network structure. The training of the model utilizes both the loss function and optimization function to enhance performance. The efficacy of the sentiment analysis is assessed through simulation experiments and practical applications, highlighting the model’s superior capability in identifying negative emotions such as Fear and Anger, achieving accuracies that are 0.101 and 0.137 higher, respectively, than those of the benchmark model. Additionally, a detailed analysis of the emotion scores of ethnic artworks reveals intriguing findings. Notably, Jiye Li’s “Four Seasons of Essays” registers the highest positive mean emotional score of 4.1026, with an overall mean of 3.5392, indicating a predominantly positive emotional response. Across the works of nine subjects analyzed, the aggregate mean emotional score stands at 1.0123, suggesting a generally positive emotional tone. This research underscores the nuanced capability of CNNs in the domain of emotional recognition in ethnic art, offering insights into both methodological advancements and interpretive analyses.
Research on Innovative Practice and Theoretical Exploration of Visual Communication Design for Future Media
Authors: Yang Yang 
Published: June 2024

Abstract
The rapid development of the new media era has brought brand new opportunities for visual communication design, and the creation concept and expression of visual communication design have undergone obvious changes. In this paper, the ant colony algorithm is applied to automatically arrange graphic text in visual communication design to achieve the purpose of visual communication design innovation. Additionally, an image synthesis model based on generative adversarial networks is proposed for visual communication design, and examples are analyzed to analyze visual communication design in the context of future media. As a result of the study, the average loss values of the generator and discriminator of its generative adversarial network model are 9.894 and 2.319, respectively, and the Inception score (3.74) corresponding to the GAN is undoubtedly the highest, which has a high communication effect. This study enhances the effectiveness of visual communication design, promotes efficient communication and interaction with the audience, and promotes the innovative practice and theoretical exploration of visual communication design.
Research on the Generative Mechanism of Intelligent Reconstruction for the Integration of Traditional Paper-cutting Art Symbols and Modern Pattern Designs
Authors: Zhang Zhe , Xu Jiang 
Published: June 2024

Abstract
In the realm of Chinese traditional arts, paper-cutting symbols embody deep-seated aesthetic and cultural values. Within the framework of artificial intelligence, the fusion of these conventional symbols with contemporary pattern design through intelligent reconstruction processes promotes innovation in modern design. This paper introduces a novel pattern feature extraction algorithm specifically designed for identifying and extracting the essence of traditional paper-cutting art. Utilizing Deep Convolutional Generative Adversarial Networks (DCGAN), an automated method for generating woven patterns is developed, integrating conventional motifs with modern design elements. Additionally, a segmentation model based on DeepLabV3+ semantics is constructed to facilitate this integration. The study focuses on the fusion of traditional paper-cutting symbols with fabric patterns, providing a new direction for textile design research. The empirical evaluation involved seven experimenters who predominantly favored patterns that blended abstract and traditional styles, with the average style rating exceeding 3.2. Moreover, the color performance analysis of the reconstructed fabric patterns across five regions showed color difference values greater than 4, indicating superior color fidelity. These findings underscore the potential of combining AI-driven techniques with traditional art forms to enhance and revolutionize modern design practices.
Digital Enabling Rural Revitalization: An Innovative Study of Intangible Cultural Heritage in Animation-based Inheritance and Dissemination
Authors: Yang Jiaming , Xu Chenfan 
Published: June 2024

Abstract
With the development of digital technology, the animation of intangible cultural heritage provides a new form of cultural carrier for its transmission and dissemination. The innovative use of animation in intangible cultural heritage is examined in this thesis through the lens of digital empowerment for rural revitalization. After selecting indicators for animating intangible cultural heritage, a questionnaire was designed. Data was collected based on the Kano model to study the audience demand for animating intangible cultural heritage. Then determine the variables affecting the animation of non-heritage culture, construct the structural equation model, validate the model after correlation analysis, and explore the influencing factors of the dissemination of non-heritage culture animation. Finally, user needs are divided into four different attributes, of which animation action design (0.8265) and scene props design (0.7817) have the greatest impact on user satisfaction. In contrast, animation art style design (-0.7483) and folklore (-0.7175) have the greatest impact on user dissatisfaction. Except for cultural context and perceived pleasure, animation information quality, and perceived usefulness, the hypotheses of this paper are all verified (p less than 0.05), and audience satisfaction has the greatest influence on communication behavior among the perceived factors. This paper discusses the animation-based transmission and dissemination of intangible cultural heritage, which has a positive significance in promoting the protection and transmission of intangible cultural heritage.
Research on optimization model of rural e-commerce distribution efficiency and cost under smart logistics framework
Authors: Zhou Dongmei 
Published: June 2024

Abstract
Despite advancements in information technology, rural e-commerce distribution continues to struggle, characterized by inefficient capacity resource allocation and exorbitantly high logistics costs. These challenges severely impede the growth of the rural e-commerce industry and the economic performance of logistics and distribution firms. This study delves into the specific dynamics of rural e-commerce logistics and the prominent issue of the “last kilometer” bottleneck. It constructs a multi-objective planning model aimed at minimizing both distribution costs and time, incorporating constraints such as the load capacity of distribution vehicles, as well as the number and routes of service vehicles. Utilizing the simulated annealing algorithm, this research addresses the shortcomings of genetic algorithms, particularly their tendency to converge on local optima. This enhancement enables the genetic algorithm to effectively identify optimal solutions for distance, cost, and profit within the operational constraints of rural e-commerce distribution. The model’s efficacy was validated and subsequently applied to a case study involving a rural e-commerce enterprise in a county. The findings reveal that the combined genetic algorithm-simulated annealing (GA-SA) approach yields an average optimal solution error of 0.25 and an average solution error of 0.46. Furthermore, the optimized distribution strategy for the four vehicles resulted in total travel distances of 47.46 km, 40.47 km, 28.36 km, and 3.1 km, respectively, culminating in a substantial reduction of 61.29 km compared to the pre-optimization scenario. The reduced iteration count of the algorithms also contributes to enhanced profit outcomes. This research offers valuable insights for rural e-commerce distribution companies seeking to bolster their market competitiveness through upgraded information technology, reasonable resource allocation, cost efficiencies, and enhanced operational effectiveness.
Quantitative analysis of the impact of port economic development on maritime logistics and supply chain efficiency
Authors: Chen Shijie , Wang Zitong , Xiao Guangnian 
Published: June 2024

Abstract
Entering the new century, the role of the ocean as a growth of regional economic development has become more prominent. This study focuses on the quantitative analysis of the impact of port economic development on the efficiency of maritime logistics and supply chain, using the synergy model to analyze multiple ordinal covariates of the port economy and naval logistics supply chain subsystems. And find out the optimal synergy matching degree between port economies and maritime logistics supply chain sub-systems among multiple ordinal covariates. Finally, X port is taken as a research case to demonstrate the coordination relationship between port economic development and the efficiency of the maritime logistics supply chain. The results show that from 2012 to 2023, the synergy value between the economy and the marine logistics supply chain of Port X shows a growing trend, and the level of synergistic development between the two is also increasing year by year. It shows that the synergy model constructed by the research can reflect the degree of synergistic development between the port’s economic development and the maritime logistics supply chain in a more comprehensive way and has general applicability. Meanwhile, the results of the study can provide a theoretical basis for the formulation of port logistics policy and regional economic development planning in the coastal economic zone.
An Exploratory Study of Japanese Language Teaching Models Toward POA Theory
Authors: Ayinuer  
Published: June 2024

Abstract
This study is grounded in the Principles of Accounting (POA) teaching philosophy, which advocates an output-oriented approach and integrates multimedia and network-assisted instruction within physical classroom settings. It examines the effectiveness of a blended teaching model—combining both online and offline elements—in Japanese language courses. This research seeks to address deficiencies in traditional teaching methodologies by offering solutions and insights that could enhance the current pedagogical framework for Japanese language education. During the practical implementation of conversational Japanese teaching, a case experiment was conducted to assess the pedagogical impact. The results demonstrated marked improvements: the pre-and post-test mean differences for vocabulary acquisition, expression, and conversational skills in the first cycle were -6.86, -4.94, and -4.13, respectively. The second cycle showed further enhancement, with differences of -8.01, -5.51, and -5.11, respectively. Statistically significant differences were observed between the performances of classes A and B across both cycles (p < 0.01), indicating the effectiveness of the intervention. Furthermore, there was a notable improvement in the students’ listening skills (p < 0.001). The reception towards the POA blended teaching approach was overwhelmingly positive, with 100% of participants reporting a favorable view. This methodology not only increased student engagement and participation but also significantly enhanced their enjoyment of learning the Japanese language.
The association between the ethical guidance of science and technology in family moral education and the formation of personal values in adolescents
Authors: Hao Xiaoqi 
Published: June 2024

Abstract
The development of adolescents’ thoughts and behaviors will be influenced by the environment, and the family, as an important place for adolescents to grow up, has an outstanding influence on the formation of adolescents’ values. The article first analyzes the connotation of family ideological and moral education and adolescents’ values. It explores the positive contribution of scientific and technological ethical guidance in family ideological and moral education to the formation of adolescents’ values. Primary and secondary school students in W city were selected as the research objects, and a questionnaire was designed to clarify the current development of adolescent personal values; and factor analysis and multiple linear regression model were introduced to explore the influencing factors on the formation of adolescent personal values. The reliability of the survey data was assessed through exploratory factor analysis and validation factor analysis, and the correlation between science and technology ethics in family education and adolescent personal values was examined. The eigenvalue of ethical values is 5.114 and contains 36.65% of the information on adolescents’ values, and the correlation coefficient between parental literacy and ethical values is 0.163. The regression coefficient between parental literacy and the formation of adolescents’ values is 0.429, and the moral guidance of science and technology in family education requires parents to be more literate to help adolescents better establish their values. This will help adolescents develop their values better.
Study on the improvement of measurement accuracy of grid short-circuit parameters based on semi-physical simulation
Authors: He Siyang , Yu Hailin , He Guanglu , Wang Shuai , Pan Fuxiang 
Published: June 2024

Abstract
Short-circuit current calculation is one of the most basic and commonly used calculations in power systems, which is related to the setting of distribution network relay protection, selection of electrical equipment, identification of short-circuit accidents, and so on. This paper establishes the grid structure of grid short-circuit with 220kV substation as the boundary, analyzes the current composition of grid short-circuit, designs the basic method of grid short-circuit current calculation based on the Davignan equivalence model, and calculates its steady-state value. In the calculation of grid short-circuit current parameters, the idea of casting and cutting capacitors is introduced to construct the measurement strategy for short-circuit current capacity parameters. Based on the semi-physical simulation test technology, the semi-physical simulation verification platform of grid short-circuit is established by combining the real-time digital simulation system, and the error between the calculated value of short-circuit current and the simulation measurement value is analyzed by this platform. When the short-circuit capacity parameter is 100MVA, the measurement error is only 1.46% near the extreme load, and the minimum error of short-circuit current and in-ring current obtained by the semi-physical simulation platform can be controlled to 2.45% and 4.11%, respectively, and the range of transient peak coefficient error is in the range of [-1.66%,1.39%]. The application of the semi-physical simulation platform for measuring grid short-circuit parameters has high accuracy and guides optimizing grid configuration.
Research on Cultural Inheritance of Non-Heritage Handicrafts Based on Big Data Analysis
Authors: Li Zhi 
Published: June 2024

Abstract
Non-heritage handicrafts are outstanding achievements and wisdom crystallization jointly created by people of all ethnic groups in long-term life practice, and they are an important expression of the cultural values of the Chinese nation. From the perspective of tourism resources, this paper proposes the coupling path between non-heritage handicraft resources and rural tourism and constructs the planning mode of “non-heritage handicraft tourism”. The evaluation model of the potential of industrialized development of non-heritage handicrafts, which contains 12 factor-level indicators, is constructed by comprehensively applying big data analysis, kernel density analysis, and hierarchical analysis method. The empirical results show that, among the four non-heritage handicrafts, Nixing pottery has the greatest industrialization potential with a high degree of affiliation (0.3621) and a high potential for industrialization and development. The evaluation results have established a scientific and reasonable system for developing or protecting handicrafts for different potential non-heritage craft projects. This can guide the current practice of revitalizing non-heritage crafts in full swing.