bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modern Translation of Rural Traditional Culture Led by Digital Art
Authors: Yan Chang 
Published: June 2024

Abstract
As digital technology continues to evolve, the fusion of traditional cultural heritage with digital media art design has emerged as a crucial demand and innovative mode of expression. Within the context of digital art leadership, this study delves into the contemporary reinterpretation of traditional rural culture. By examining how rural traditional culture is portrayed under the guidance of digital art, we use the digital culture museum—which embodies both digital and rural traditional cultures—as a case study. A specifically designed questionnaire was employed to assess the effectiveness of this modern reinterpretation. Subsequently, key indicators influencing the efficacy of the contemporary translation of rural traditional culture were identified. The fuzzy set qualitative comparative analysis was utilized to conduct group analyses, aiming to delineate the pathways that could enhance the contemporary reinterpretation of rural traditional culture. The findings reveal that rural traditional culture, under the stewardship of digital art, achieves a more effective modern reinterpretation. Notably, over 85% of respondents exhibited a positive response to the amalgamation of digital art with traditional culture in museums, expressing a preference to engage with traditional cultural content through this medium. The analysis of pathways to enhance the modern translation of rural traditional culture showed overall consistency and coverage rates of 0.921 and 0.695, respectively. The integration of tradition with modernity, alongside enhanced interactivity and participation, are identified as pivotal elements in augmenting the modern reinterpretation of rural traditional culture.
Virtual Reality-Based Multi-Sensory Design of Chinese Gardens under the Perspective of Spatial Narrative
Authors: Zhou Hanhan 
Published: June 2024

Abstract
This paper makes comprehensive use of virtual reality, virtual plants, and other technologies, integrates parametric plants and buildings and other modeling methods, and flexibly manages and organizes all kinds of garden elements through digital vector layers. Based on the OSG graphic rendering engine, it visualizes all sorts of 3D garden landscape models. Combining multi-sensory expressions, the parameter-driven multi-sensory design of virtual Chinese gardens is comprehensively constructed. The findings indicate that the scheme with decentralized placement on both sides has a receding time of 312s, and the area of human flow density has been enhanced. In the soundscape design, the birdsong sound was favored more, and the mean value of the birdsong sound scores in the botanical garden, plaza, and stream was 4.43. The Sig values of experiential, realism, interactivity, and content richness between Group A and Group B were all less than 0.05. Therefore, this paper successfully designs and realizes multisensory interactions between people and the garden scenario design.
Exploring the Value Connotation and Path of Sino-Japanese Marine Literature Development under the Background of Internet+Interculturalism
Authors: Zhang Yong , Wang Zhen 
Published: June 2024

Abstract
Marine literature, as a reflection of the evolving maritime culture, has experienced a rising trajectory of scholarly interest in recent years. This study delves into the intrinsic ties and foundational mechanisms underpinning the evolution of marine literature within China and Japan, advocating a developmental pathway akin to an industrial cluster for this literary genre. Utilizing a meticulously constructed input-output table for the marine literature industry, this paper conducts a comparative horizontal analysis of the sector’s growth across six coastal cities in China and Japan for the year 2023. The study encompasses three primary dimensions: correlation effects, supply-push effects, and demand-pull effects. The empirical findings underscore the developmental value of marine literature in both nations. Notably, the development potential index for China’s marine literature industry stands at 26.36, surpassing Japan’s by 13.88, with the variance largely attributable to differences in the marine economic and social environments. This comparative analysis not only highlights potential growth avenues for China’s marine literature but also offers fresh insights into the cultural disparities between China and Japan.
A Study on Data-Driven Cluster Analysis of Teaching Quality in Civic and Political Education in Colleges and Universities
Authors: Wu Xiaoying 
Published: June 2024

Abstract
The implementation of teaching quality evaluation has a certain guiding effect on a series of teaching works, such as teaching reform and teaching management, and the selection of appropriate evaluation methods is very important for the implementation of teaching quality evaluation. In this study, the hierarchical analysis method and K-means clustering algorithm were used to construct and assess a teaching quality evaluation model for college Civics education. Prior to evaluating the teaching quality of Civic and political education in colleges and universities, the hierarchical structure model and index system were established using the hierarchical analysis method. Then, the K-means clustering algorithm is utilized to execute the data mining work to assess the quality of data-driven teaching through clustering. The algorithm’s purity and F1 values are 0.895 and 0.834, respectively, and it performs well in clustering. Finally, the clustering analysis of the teaching quality of college civic education was conducted. The final scores of teaching quality, teaching method, teaching content, teaching effect, and teaching characteristics accounted for 98.28%, 87.76%, 88.03%, 71.4%, and 83.2% of the total scores of each, respectively. All the scores are in the middle of the range, indicating that the overall teaching situation is in the middle of the range with better results. The purpose of this study is to provide lessons and references for cluster analysis of civic education teaching quality in colleges and universities.
Promoting the transformation of agricultural supply chain management under the development of digital economy in the Internet era
Authors: Wang Xueliang , Qin Xi 
Published: June 2024

Abstract
Agricultural products, as the necessities of people’s daily consumption, are related to the national economy and people’s livelihood, and the development of information technology provides a new direction and ideas for the transformation of agricultural products supply chain management. The article proposes the risk assessment method for the agricultural products supply chain based on the Bayesian network inference algorithm and OWA algorithm, firstly constructs the Bayesian network model for risk assessment of agricultural products supply chain, elaborates on the belief updating algorithm and the belief-free updating algorithm in the Bayesian network, then combines with the OWA operator, proposes the method of risk diagnosis of agricultural products supply chain based on the Bayes-OWA hybrid operator, and with this The algorithm is the core of the proposed agricultural supply chain management strategy. Through empirical tests, it can be obtained that the average supply time of enterprise 4 in agricultural products is 22.3 days, and the reliability of supply is 92.3%, which is highly efficient. In the agricultural products supply program, the average value of quality qualification rate has been improved by 2.67%, the average number of days for supplier delivery has been shortened by 13 days, and the supplier’s ability to respond quickly to demand has been improved by 3.61%. Therefore, actively constructing the informationization construction of the agricultural supply chain, building a logistics information platform, improving rural communication facilities, and providing timely market information to farmers can better ensure the efficient operation of the agricultural supply chain.
Gray correlation analysis of ideological and political education and college students’ ideological dynamics in new era colleges and universities
Authors: Kang Fei 
Published: June 2024

Abstract
This study employs gray correlation analysis to process and evaluate the data pertaining to the effectiveness of ideological and political education in higher education institutions. Comparative analyses were conducted between experimental and control groups, utilizing group counseling to foster positive mental qualities. The data collected before and after the educational interventions were subjected to statistical analysis. The findings indicate significant variations in learning outcomes across different dimensions for certain student groups, offering educators a foundation for targeted interventions. Furthermore, the results from the positive psychological quality education experiment reveal that the experimental group exhibited a notable enhancement in positive psychological qualities post-intervention compared to the control group. Specifically, there was a substantial increase in the attributes of love, tolerance, perseverance, faith, and hope. For instance, the score for love in the experimental group improved from 2.45 to 3.36, an increase of 0.91, with the most pronounced growth observed in the qualities of faith and hope, which increased by 1.16. The application of gray correlation analysis in this context demonstrates its utility in assessing the effectiveness of ideological and political education, allowing for the refinement of educational focus and methodologies to enhance overall academic outcomes. This research provides pivotal strategies and directions for collegiate education, aiming to nurture a larger cohort of students equipped with positive psychological qualities and preparing them for successful future endeavors.
Research on the Formation Mechanism, Contagion Effect and Regulatory Strategy of Digital Asset Price Bubble Risk in the Information Age
Authors: Ku Xiangfang 
Published: June 2024

Abstract
As an emerging financial instrument, the risk of asset price bubbles is becoming more and more prominent and has a far-reaching impact on the global financial market. Based on the ADF model and PSY algorithm, the study constructs an asset price bubble identification model, explores the formation mechanism of asset price bubbles in the financial market, the contagion effect of asset price bubbles in the inter-market, and ultimately puts forward suggestions for targeted regulatory strategies. In the numerical simulation of the formation mechanism of asset price bubbles, both Bubble 1 and Bubble 2 experience 10 periods, and the peaks of the two bubbles appear at t=14 and t=34.5, respectively. The rate of rise of asset prices is slower than the rate of decline, and the impact on the financial market is greater when the financial asset bubble bursts. There is a two-way bidirectional contagion effect between the three markets of stock, bond, and property. Therefore, regulation of asset price bubbles should focus on improving the stock market trading system, publicizing and educating, and restricting real estate loans.
Analysis of the value of news and cultural communication using multimodal learning
Authors: Shi Wei 
Published: June 2024

Abstract
News serves as a critical medium for mass communication, characterized by its distinct purpose, comprehensiveness, and authenticity. It is essential to explore the developmental trends within the news sector from the perspective of communicative value and to provide appropriate guidance. This study employs multimodal learning techniques to develop a new content detection model that leverages multimodal fusion for effective content identification. Building on this framework, a sentiment analysis model utilizing multimodal data is constructed to assess the emotional impact of news communication. Additionally, the cognitive mediation model is used to establish an analysis model for determining the value of news communication. Empirical analyses indicate that the multimodal news content detection model presented in this study achieves high-performance metrics, with each index exceeding 0.9. Similarly, the sentiment direction model demonstrates robust accuracy, precision, recall, and F1 values, all-surpassing 0.83. The models exhibit Pearson correlation coefficients (Corr) of 0.758 and 0.785 and mean absolute errors (MAE) of 0.624 and 0.948, respectively, outperforming comparable models. Further analysis into the value of news and cultural communication reveals significant impacts of sound attention (0.328), sound-associated thinking (0.210), and image attention (0.284) on communicative value. Conversely, leisure Internet time shows a negative correlation with knowledge acquisition (-0.090). The findings underscore a positive correlation between the value of news and cultural communication and sound content, thereby affirming that the methodologies employed in this study provide a viable approach to analyzing the communicative value of news. This study not only advances the theoretical understanding of news communication but also enhances practical approaches to media analysis.
Construction of a Classification Model for Teacher and Student Behavior in Physical Education Classrooms –Based on Multimodal Data
Authors: Zhao Yan , Yu Bingyan 
Published: June 2024

Abstract
The analysis of teachers' and students' behaviors in physical education classrooms is an important way to improve the quality of physical education teaching and teaching methods, which helps teachers to check the gaps and improve the teaching level. In this paper, for the problems of data differences between multiple modalities and the conflict between feature extraction modules of different modalities, we designed a dual-stream framework HRformer algorithm based on Transformer, which unifies the skeletal modalities and video modalities in the algorithm. The relationship between skeletal and video modalities is modeled using the self-attention mechanism, and the matching and fusion of skeletal features and video data is performed to construct a behavior recognition model for teachers and students in the sports classroom based on multimodal data. Then, the model is compared with mainstream networks on the dataset to verify its performance. To conduct model application and example analysis, a university collects data on physical education classroom teachers and students for a semester. It is found that the multimodal model in this paper has a classification F1 value of 95.61%, 93.19%, and 93.74% for the three types of behavior recognition, namely, skill training (ST), game activity (GA), and rest, respectively, which are higher than the two methods of single skeletal modality and video modality. The model has the highest recognition accuracy of 97.12% and 98.15% for Game Activity (GA). Based on real physical education classroom data, the practical application of the model in physical education teaching classrooms in this paper is fruitful, and the results of behavioral recognition classification are in line with the design expectation. This study develops an effective method for classifying teacher and student behaviors in a physical education classroom. It provides a useful exploration for the integration and innovation of physical education teaching and information technology.
Battery Energy Storage Participation in Primary Frequency Regulation Considering SOC Consistency
Authors: Li Shichun , Luo Linhua , Su Lingjie , Wang Xiaoyu , Wang Lijun 
Published: June 2024

Abstract
In recent years, battery energy storage has garnered increasing attention in the frequency regulation field due to its rapid and precise output characteristics. The focus of this paper is on the control strategy for battery energy storage that is involved in primary frequency regulation and addresses the coordination control issues of different storage units when implemented on a large scale. A control method is proposed that considers the consistency of the State of Charge (SOC) in battery energy storage, which is involved in primary frequency regulation. The control of the battery energy storage system is divided into upper-level and lower-level control. The upper-level control uses model predictive control to obtain the total frequency regulation power of the energy storage station. The lower-level control allocates the corresponding power based on the capacity of each battery energy storage unit. It introduces a proportional integral adjustment term related to the average SOC to achieve SOC consistency control for each unit. Simulation results demonstrate that, regardless of whether the capacities of various storage units are identical, the proposed method achieves good frequency regulation performance, restores SOC to the ideal range, and ensures SOC consistency among different storage units. This approach aids the efficient and safe operation of battery energy storage systems.
Protection of (Personal) Data in Armed Conflicts
Authors: Kelemen Bence Kis 
Published: June 2024

Abstract
Despite the increased attention that was given to data protection laws in national jurisdictions – especially after the adoption of the General Data Protection Regulation by the European Union – international law still does not offer a higher standard of protection to the personal data of civilians in times of armed conflict, where the deletion or manipulation of personal data of the civilian population can have significant harmful effects. This article explains that at the time of the adoption of the relevant international treaties and the development of customary international law, international humanitarian law (IHL) did not protect personal data stored electronically, and even though commentators in contemporary times tend to accept the object status of electronic data, State practice still remains inconclusive, largely excluding computerized personal data from the protective regime of IHL. The article argues further that a stricter protection of personal data regulation could potentially lead to harmful effects for protected persons, such as civilians, therefore it is undesirable. The protective nature of IHL must prevail over the data protection interests.
Testing Europe Salience and Second-Order Election Theories: 2019 European Parliamentary Elections in Lithuania
Authors: Jurkynas Mindaugas 
Published: June 2024

Abstract
The article assesses the 2019 elections to the European Parliament (EP) in Lithuania and their theoretical relevance. The analysis presents the political stances of parties and the electorate towards the EU. The focus then shifts to information and political campaigns, the parties participating in the EP elections, and the electoral results. These aspects serve to evaluate the theoretical relevance of Second-order election theory and the Europe salience theory, revealing the absence of Eurosceptic, protest, populist, and postmaterial mood in the 2019 EP elections in Lithuania.
“Access Denied” – Interpreting the Digital Divide by Examining the Right of Prisoners to Access the Internet in the Case Law of the European Court of Human Rights
Authors: Lendvai Gergely Ferenc , Gosztonyi Gergely 
Published: June 2024

Abstract
The present paper aims to investigate prisoners’ rights to use and access the Internet, focusing on the jurisprudence of the European Court of Human Rights (ECtHR). The study’s principal objective is to assess the fundamental rights aspects of Internet access, particularly within the context of relevant EU legislation, and to interpret how the digital divide impacts prisoners. The study primarily relies on a thorough review of pertinent literature and legal materials, and it incorporates case studies from Estonia, Lithuania and Türkiye to contextualize the literature findings within specific legal jurisdictions. The research findings suggest that prisoners’ Internet access should be evaluated in accordance with fundamental rights, including Article 10 of the European Convention on Human Rights. Regarding the digital divide, the study concludes that limiting prisoners’ access to the Internet could exacerbate the already existing societal gap, potentially hindering their reintegration into society. The particular focus on the above three countries stems from the fact that as per the precedent of the ECtHR, only four countries are involved in cases concerning restriction of access to the Internet (Estonia, Lithuania, Türkiye and Russia); however, Russia ceased to be a party of the European Convention on Human Rights, so analyzing the future of the issue of Internet acces there is highly limited. Our research contributes significantly to the literature on the digital divide, particularly in terms of its legal implications. The study’s comprehensive approach, which integrates both theoretical and practical aspects, is beneficial for domestic legal professionals and researchers engaged in interdisciplinary investigations of EU law and fundamental rights.
Constructing a Corrected Stations Network Using Some Geomatic Techniques
Authors: Ali Amal Mahdi , Al-Soudani Maha , Radhi Faten Mezher 
Published: June 2024

Abstract
The major objective of this study is to establish a network of Ground Control Points-GCPs which can use it as a reference for any engineering project. Total Station (type: Nikon Nivo 5.C), Optical Level and Garmin Navigator GPS were used to perform traversing. Traversing measurement was achieved by using nine points covered the selected area irregularly. Near Civil Engineering Department at Baghdad University Al-jadiriya, an attempt has been made to assess the accuracy of GPS by comparing the data obtained from the Total Station. The average error of this method is 3.326 m with the highest coefficient of determination (R2) is 0.077 m observed in Northing. While in the Easting the average error is 4.634 m with (R2) 0.099 m observed. The average error 5.513 m with (R2) is 0.071 m is observed in Reduced Level. The accuracy assessments of the interpolation methods (Total Station and Level) have been calculated using the average error 0.240 m with (R2) is 0.735 m is observed in Reduced Level. The GIS 10.3 program can automatically transform the saved data to text format and produce digital plans with attribute.
Thermophysical Properties of Concrete Blended with Iron Powder and/or Iron Fibers
Authors: Kanibou Fatima , Moufakkir Abdelkrim , Samaouali Abderrahim , Bakari Randa , Ouaazizi Karima , Arbaoui Asmae , Charkaoui Abdellah 
Published: June 2024

Abstract
The use of iron waste in concrete is now of considerable importance, mainly because of the benefits for the environment and for improving the strength of concrete. The increased and unused of this industrial byproducts represents a challenge for the environment and human health. This article experimentally explores the influence of utilizing iron powder waste and iron fibers in concrete in order to enhance the thermophysical properties of concrete and reduce the environmental impact resulting from iron waste. The aim of this work is to study the thermophysical properties (thermal conductivity, volumetric heat capacity, thermal diffusivity and thermal effusivity) of concrete with waste iron powder and iron fibers for application in building construction. The iron powder waste was added to the concrete with different percentages of 0%, 5%, 15%, 20% and 25% respectively as a partial replacement of sand. The iron fibers were added with mix proportions including 1.0%, 1.5%, 2.0% and 2.5% by volume of concrete, and in two different arrangements, uniform and random. The thermal conductivity and the volumetric heat capacity of these samples were measured experimentally in the dry state at ambient temperature (20 °C), and at 28 days of age. The effect of the integration of iron powder and fiber on thermal properties was analysed.