bluuebunny/crossref_metadata_2025 huggingface dataset:
Practice of the First School of Creative Industries in Khanty-Mansi Autonomous Okrug – Yugra: Key Directions of Development
Authors:   Surgut State Pedagogical University, Borovinskaya Daria N. , Lisyutina Irina B.
Published: May 2024

The article presents regional practice and current results of the work of the school of creative industries of the District House of Folk Art (Khanty-Mansiysk), which is a regional methodological center in matters of preserving and popularizing the traditional culture of the peoples living in Ugra. The key directions for the development of the school of creative industries in the fields of education and science are delineated and characterized, with the aim of meeting educational needs and improving the quality of supplementary education, taking into account regional specifics. Thus, an important aspect of the activities of the school of creative industries of the District House of Folk Art is the organization of a creative space based on master classes, intensive platforms in various fields of creative industries and inter-studio practical activities aimed at studying the cultural, spiritual and moral heritage of the northern peoples using modern technologies. Specific results of the study may be utilized in the educational process of students in humanities disciplines and all those interested in the issues related to the formation and development of the creativity phenomenon. This exploration emphasizes the importance of creating an educational and creative environment that not only preserves the unique cultural heritage of the region but also integrates it ingeniously with modern technological advancements. The school’s multifaceted strategy, encompassing both theoretical knowledge and practical application, endeavors to foster an ecosystem conducive to the development of creativity and innovation. These endeavors highlight the school’s role in nurturing a new generation of professionals equipped to contribute significantly to the dynamic and evolving field of creative industries.
Catalogue of the specimens of Trichodactylidae (Crustacea, Brachyura) housed in the Museo de La Plata, Argentina
Authors: César Inés I. , Damborenea Cristina
Published: May 2024

We present here a catalog of the Trichodactylidae (Crustacea, Brachyura) deposited in the Crustacean Collection of Museo de La Plata, Argentina. Eighty lots were studied, comprising eight species. Among these lots, many had been characterized by R. Ringuelet and by C. Magalhães; several lots from different regions of Argentina were identified. For each lot the following information is provided: georeferenced locality of collection, collector and collecting date, collection number, labelling data (a precise transcription of the original wording), remarks, and map of the locations.
Rede de cooperação entre pesquisadores do XIX ENANPUR
Authors: Mauricio Nathanni Marrelli Matos , Pizzio Alex , Oliveira Nilton Marques de , Almeida Lia de Azevedo
Published: May 2024

O presente estudo objetivou analisar a existência de uma rede de colaboração científica entre os pesquisadores participantes das sessões temáticas do XIX ENANPUR; bem como analisar a forma de organização e cooperação para o desenvolvimento da produção científica entre os atores envolvidos. Para tanto, desenvolveu-se um estudo descritivo, de natureza quantitativa, com emprego de técnicas de análises de redes sociais de cooperação. Os dados obtidos foram tabulados em planilha eletrônica do software Microsoft Excel e exportados para o software UCINET 6.0. Na edição pesquisada foram divulgados 449 artigos dispostos nas doze sessões temáticas do evento e envolveram a participação de 935 pesquisadores. A maioria dos autores desenvolveram os artigos através de colaboração científica, observou-se que a rede de cooperação dos autores apresenta baixa densidade e descentralizada. Os autores estão ligados a 137 instituições, sendo que 41 atuaram de maneira isolada. Assim, com relação a rede de colaboração levando em consideração as instituições que os autores estão vinculados, observou-se uma rede que apresenta baixa densidade e descentralizada, sendo que a instituição com maior índice de intermediação foi a Universidade de São Paulo (USP). 
Palavras-chaves: Redes de colaboração; ENANPUR; Densidade; Centralidade; Intermediação.
Dendritic Cells and the Establishment of Fetomaternal Tolerance for Successful Human Pregnancy
Authors: Mahajan Deviyani , Kumar Tarun , Rath Prasana Kumar , Sahoo Anjan Kumar , Mishra Bidyut Prava , Kumar Sudarshan , Nayak Nihar Ranjan , Jena Manoj Kumar
Published: May 2024

Pregnancy is a remarkable event where the semi-allogeneic fetus develops in the mother’s uterus, despite genetic and immunological differences. The antigen handling and processing at the maternal–fetal interface during pregnancy appear to be crucial for the adaptation of the maternal immune system and for tolerance to the developing fetus and placenta. Maternal antigen-presenting cells (APCs), such as macrophages (Mφs) and dendritic cells (DCs), are present at the maternal–fetal interface throughout pregnancy and are believed to play a crucial role in this process. Despite numerous studies focusing on the significance of Mφs, there is limited knowledge regarding the contribution of DCs in fetomaternal tolerance during pregnancy, making it a relatively new and growing field of research. This review focuses on how the behavior of DCs at the maternal–fetal interface adapts to pregnancy’s unique demands. Moreover, it discusses how DCs interact with other cells in the decidual leukocyte network to regulate uterine and placental homeostasis and the local maternal immune responses to the fetus. The review particularly examines the different cell lineages of DCs with specific surface markers, which have not been critically reviewed in previous publications. Additionally, it emphasizes the impact that even minor disruptions in DC functions can have on pregnancy-related complications and proposes further research into the potential therapeutic benefits of targeting DCs to manage these complications.
Research on electrical automation devices under embedded real-time operating system design
Authors: Liu Yuxuan
Published: May 2024

As the scale of the electrical system becomes more and more large and the structure becomes more and more complex, the performance of the electrical automation device is therefore required to be higher. This paper studies the electrical system automation device, and from the perspective of universality, designs and establishes the hardware platform of the electrical system automation device composed of six plug-ins, such as human-machine interface, auxiliary switch input, AC input, communication, power supply, and central processor. On this basis, μC/OS-II is adopted as the embedded real-time operating system of this paper to develop and design the software of the electrical system automation device. Then, the principle of the protection device for embedded system electrical automation is analyzed, and a microcomputer line protection device based on the full-circle Fuchs algorithm is proposed. The empirical analysis of the embedded system electrical automation device shows that the maximum system task response time is 145 μs and the minimum is 10 μs, which are all no more than 1 ms. When testing including the single board state, the keyboard, the alphabetical mode, the basic function, and the single board line module sending and receiving, the pass rate of all the testing items is more than 99%, which verifies that this paper is based on the embedded real-time operating system of the feasibility and effectiveness of the electrical automation device.
Research on the Multimodal Integration of Visual Communication Design and Public Art in Digital Perspective
Authors: Chang Li , Cai Dongxue , Liu Zhaohui
Published: May 2024

With the rise of digital media, the visual design of public art has gradually added multimodal interactive experience from purely conforming to information communication. Starting from the multimodal integration of public art visual communication design, this study takes several groups of public art landscape projects in a certain region as research objects to explore the relationship between the multimodal visual design of public art landscape and its public satisfaction. Firstly, the evaluation standard for public art visual communication design is constructed. The sample visual communication design is analyzed using the semantic difference method and then combined with the factor analysis method to provide a comprehensive evaluation. Based on determining the satisfaction effect indexes, the AHP method is used to assign weights to each index. Finally, the satisfaction effect results of the sample visual communication designs are obtained. After utilizing the result equation, the relationship between public art visual communication design and landscape satisfaction effect is explored. The overall appearance of public art visual communication design is presented better, and the impact of multimodal fusion visual communication design is especially prominent in samples 3, 2, and 10. The satisfaction effect of the sample visual communication design is also more satisfactory, with 70% of the sample landscapes scoring above 1.5. Meanwhile, the study verified the positive and significant influence of public art visual communication design on the satisfaction effect of landscapes. The theoretical basis and methodological exploration for the multimodal integration research of public art can be provided by this study.
Optimization Strategies and Efficacy Evaluation of Cross-Language Embedding Model in Teaching English in Colleges and Universities
Authors: Liu Jie
Published: May 2024

With the trend of information technology, contemporary English language teaching is moving positively in the direction of intelligence. This study utilizes the text embedding model to represent language and convert it into a format that computers can process. Through the methods of adversarial training and self-learning training and adding the fine-tuning process to improve the effect of cross-linguistic word vectors, the machine reading comprehension and translation model is constructed to ensure the semantic consistency between it and the input source text. Meanwhile, this study combines the model to implement an innovative teaching model of English in colleges and universities and evaluates its effectiveness. The results show that the effectiveness of the proposed method in this paper on this indicator has been narrowed to a gap of 11.48%, which significantly confirms the effectiveness of the proposed model. In the direction of E2C, the cross-linguistic embedding model has the highest average F1 score (0.894). The average score of class 1 results is 82.6843, corresponding to a critical confidence level of 0.036<0.05, which indicates that there is a significant difference between the results of class 1 and class 2. The reference value of this study is important for English teaching and related system development in colleges and universities.
Research on the application of vocal music teaching methods and techniques in colleges and universities based on proportional integral differentiation algorithm
Authors: Ye Jing
Published: May 2024

With the continuous development of modern information technology, the combination of intelligent audio processing technology and vocal music teaching has gradually become a research hot spot. In this paper, we first build a vocal music teaching system based on music emotion and instrument recognition, optimize the support vector machine using the PSO algorithm, construct the music emotion recognition and instrument recognition method based on SVM, and control and optimize the vocal music teaching system through multi-objective proportional integral differentiation algorithm. Through the comparison experiments of different models of music emotion recognition and musical instrument recognition, the performance of music emotion recognition and musical instrument recognition of this paper’s model is explored. Then, the application effect analysis of the vocal music teaching system is carried out. The results show that the SVM model optimized by PSO has a more satisfactory effect on music emotion recognition, with a recognition accuracy 16.67% higher than the comparison model and an average adaptability of 70%–90%. In addition, this model has a higher instrument recognition rate of 18.17% and 7.45% compared to the other two models. After using the vocal teaching system, 63.04% of the students thought that it could promote learning, 47.83% of the student’s classroom interest increased, and more than 70% of the students were more satisfied with its functions. In this paper, the vocal teaching system can be applied to college vocal teaching to promote the improvement of the vocal teaching effect.
Characteristics and Optimization of University English Translation from a Cross-cultural Perspective-Based on Functional Translation Theory
Authors: Zhou Xi
Published: May 2024

Drawing on the theoretical framework of functional translation, this study presents a multifaceted exploration of university English translation through functional, constructive, evolutionary, and cultural lenses. Positioned within a cross-cultural context, the paper categorizes university English translation into three primary attributes: the frontier nature of translation, linguistic and cultural divergences, and the professionalism required in translation activities. Utilizing Super Decision software, these attributes serve as input variables to construct a Network Hierarchical Analysis model. This model is further integrated with the Interpretive Structural Modeling (ISM) recursive structure to assess the influence of various factors on translation quality. The study employs a multidimensional approach to dissect the impact of cultural and professional variances on the quality of university English translation. The results reveal that 54 out of 65 cultural dimensions (83.08%) significantly affect translation quality. In the realm of professional characteristics, four out of six dimensions (66.67%) are found to have a considerable influence on translation quality. Based on these comprehensive findings, the paper proposes four strategic optimizations aimed at enhancing the quality of university English translation, thereby offering valuable insights and practical recommendations for the field.
Research on the Application of Knowledge Graph in Demand-Side Flexible Resource Profiling and Aggregation Techniques
Authors: Yang Chao , Wang Libin , Feng Lida , Xu Lei , Yao Tao , Lv Yuntong , Lei Shuya
Published: May 2024

This paper commences by assessing the current landscape of power system development, focusing on the theory, principles, and structures of demand-side flexible resources and their aggregation technology. Utilizing network crawler technology within a knowledge graph framework, the research data pertinent to demand-side flexible resources and aggregation technology are extracted. These data undergo a meticulous cleaning process before being stored, culminating in the development of a knowledge graph tailored to the imaging and technology of demand-side flexible resources. The findings reveal a response rate of 7.25% ± 1.15%, with an uncertainty interval of 2.33%. Variations in air-conditioning load states appear to exert minimal impact on the response time lag. Following the issuance of a response signal, all systems can rapidly initiate appropriate response actions, demonstrating an uncertainty interval of approximately 52s±11s and 22s. The duration of the responses averages around 75s±11s, with an uncertainty interval of about 30s. This study fulfills the power system criteria for standards of demand-side flexible resources and augments the competitiveness of China’s power market.
5G Network Performance Optimization Strategies for Smart Grids
Authors: Yao Honglei , Liu Xin , Sun Mengqian , Zhao Fuhui , Xu Shanjie , Liu Donglan
Published: May 2024

In this paper, a network slice resource allocation algorithm based on delay sensing is proposed for the problems of service delay and QoS reduction, and resource utilization reduction caused by unreasonable network slice resource allocation. MIMO technology is being studied to establish a communication system that supports multiple inputs and outputs for channels. A resource preallocation method for 5G edge computing is proposed by reasonably allocating resources in the 5G edge computing environment. Then, the performance of the 5G network is optimized, and the optimized network performance is analyzed based on case studies. The results show that the buffer depth of the optimized 5G network is reduced by 1.25, the network delay is reduced by 0.02s, and the network throughput is significantly improved. This study provides the theoretical basis and technical support for the further development of a smart grid in a 5G environment.
Applying Knowledge Mapping Techniques to Enhance Contextual Understanding and Accurate Correspondence in Translating Metaphorical Information in Japanese Literature
Authors: Yue Shengting
Published: May 2024

Metaphorical information is prevalent in literary texts, and understanding the cultural and historical contexts of Japanese literature can significantly enhance the translation of its metaphors. This paper introduces a knowledge graph specifically designed for translating metaphorical content in Japanese literary works. This graph facilitates the categorization, extraction, and storage of symbolic information. To refine the knowledge graph further, the RAEA model is employed, coupled with a distinct attention mechanism assigned to each node of symbolic information. This approach significantly improves the entity alignment in translations, thereby enhancing translational accuracy. In constructing a dataset that includes background symbolic information, the knowledge graph demonstrated a precision of 0.9256 and a recall of 0.9136. Additionally, the graph achieved an average Mean Reciprocal Rank (MRR) index of 0.810, markedly surpassing traditional translation models. This paper’s knowledge graph thus offers an effective methodology for the precise translation and interpretation of symbolic information in Japanese literature, aiding in the deeper comprehension and accurate representation of such content.
The Construction of Teaching System of Foreign Language Courses in Colleges and Universities Based on the GFKE Model
Authors: Bian Yuzhu , Li Yanfang
Published: May 2024

Under the guidance of foreign language curriculum design theory, foreign language courses in colleges and universities should construct a foreign language course teaching system from the aspects of reconfiguring the course objectives, updating the course content, and designing a diversified evaluation system. This paper combines the 5Ds framework with the GFKE model to establish the teaching system of foreign language courses in colleges and universities, designs the blended teaching mode of foreign language courses in colleges and universities, and constructs the corresponding course evaluation index system. Taking Z University in H province as the research object, the relevant teaching process of foreign language courses was designed, the coefficient of variation method solved the weights of evaluation indexes, and the teaching effect of foreign language courses in universities was comprehensively evaluated by set-pair analysis. On this basis, a validation analysis was carried out using the dimensions of teaching effect and teaching evaluation. The reading scores of students in the Experiment 1 class went up by 3.31 points, and the average score of students’ writing test scores went up by 53.86%, as per the findings. In the posttest of the depth of knowledge of English vocabulary, the experimental 1 class scored 25.83 points, which was 45.28% more than the control 2 class’s score. Blending foreign language courses based on the GRKE model can promote the improvement of students’ foreign language learning ability, and teaching evaluation results will be more accurate.
Improvement of Students’ Sports Performance in VR-Based Smart Sports Teaching in Colleges and Universities
Authors: Li Dongpeng , Sun Yan
Published: May 2024

In the complex landscape of educational information, the integration of Virtual Reality (VR) technology into secondary school physical education presents a promising avenue to enhance both teaching quality and efficiency. This article delineates the construction of a VR-based smart sports classroom, focusing on the overarching structure of the teaching program and the pivotal teaching processes. It discusses methods for analyzing and editing sports teaching videos and details the integration of VR with sports posture estimation. This includes the development of a virtual human body motion imaging model and corresponding motion-solving algorithms. An empirical study was conducted within a secondary school sports classroom to assess the feasibility and impact of VR technology on physical education. The study involved a comparative analysis of physical quality between an experimental group taught using VR technology and a control group taught using traditional methods. Additionally, the study examined changes in learning interest pre- and post-intervention in both groups. Statistical analysis revealed that the p-values for the three evaluated physical tests—20-meter sprint, shuttle run, and 30-second rope skipping—were all above 0.05, suggesting no significant difference in physical performance due to the VR intervention. However, significant improvements were observed in the dimensions of sports participation (p < 0.05), positive interest (p = 0.013 < 0.05), and focus on sports (p > 0.05), indicating an enhancement in students’ engagement and attitudes toward learning. Conversely, the negative interest dimension also showed significant changes (p < 0.05). These findings underscore the beneficial role of VR technology in enriching the learning experience and potentially improving academic outcomes in college-level physical education.
Design of physical function monitoring system for athletes in soccer training in college sports
Authors: Ji Bin , Sun Xiaolong , Wang Zhen
Published: May 2024

A comprehensive assessment of the physical capabilities and attributes of soccer players is essential for effective college soccer training. The ability to implement targeted tactical training relies on a thorough understanding of each player’s physical condition. This paper presents a monitoring system for soccer players’ bodily functions, developed using inertial sensor technology alongside Beer’s Law, tailored to recognize human body movement states and to measure blood oxygen and heart rate. The system’s efficacy in movement recognition and physiological monitoring was evaluated through comparative testing, assessing its performance against established algorithms. Notably, this system demonstrated a 9.75% improvement in the average accuracy for recognizing walking and running actions compared to the Juha Parkka decision tree algorithm and a 6.5% increase in accuracy over the D.M. Karantonis algorithm for walking action recognition. Heart rate measurements incurred an error of approximately ±2 BPM, with a maximum error of 1.7, and oxygen saturation monitoring displayed an error margin of ±2%, with a maximum deviation of 1.6. These deviations fall within acceptable limits. The results of this study furnish valuable data to support the customization of training content and intensity for college soccer athletes and offer insights for optimizing player selection and tactical strategies during matches.
Digital finance and regional systemic financial risk forecasting
Authors: Tang Enlin , Bai Chunsong , Qin Teng
Published: May 2024

The abrupt and destructive nature of systemic financial risks underscores the imperative for modern societies to prioritize early detection and prevention over post-crisis management. This paper introduces a dual-perspective early warning indicator system for regional systemic financial risks, encompassing both macro and market dimensions. It further enhances this system by incorporating the ReliefF algorithm into the feature selection phase of a modified random forest model aimed at predicting regional systemic financial risks. The model’s efficacy was assessed using data spanning from 2009 to 2023, enabling dynamic early warning evaluations of regional systemic financial risks. The model was also employed to project the risk landscape for 2024. The results demonstrate superior performance metrics for the random forest model, with an accuracy of 0.9909, precision of 0.9847, recall of 0.9871, and an F1 score of 0.9785—outperforming three comparative models. Notably, during years of significant systemic risk (2008, 2010, and 2013), the model’s predictions exceeded 0.8, while in 2015 and 2020, they surpassed 0.9. For 2024, the model predicts a higher likelihood of maintaining a “normal” state of systemic financial risk in China, with probabilities ranging between 0.3 and 0.5. This study thus offers robust theoretical support for forecasting regional systemic financial risks.
Information technology-assisted analysis of college students’ physical fitness test data and research on physical education teaching reforms
Authors: Xie Bing
Published: May 2024

Enhancing the physical quality of students in higher education institutions is crucial for ensuring the successful completion of their academic pursuits. This article begins by analyzing the fundamental algorithms of decision trees, subsequently building upon this theoretical foundation to develop an ID3 decision tree model. It employs the decision tree model for data classification, extraction, and other related processes. By integrating the C4.5 algorithm and further segmentation techniques, a more stable decision tree is derived, allowing for a comprehensive analysis of physical fitness test data. The study’s findings indicate that using rope skipping test data as an example, the analytical model maintains an error margin of 3%. Over four years of physical test data, there was a notable classification of 1% of students into the “excellent” category in 2020, with nearly 20% achieving “good” status. The proportions of “excellent” and “good” students in 2021 saw a significant rise from the previous year. Furthermore, the percentage of students categorized as “failing” in 2023 decreased by 0.88%. To enhance the effectiveness of physical education, reforms could focus on multi-faceted collaborative efforts, reinforcing the application of the ID3 decision tree model in analyzing physical fitness data and targeting interventions to boost physical fitness outcomes.
Translation of Metaphorical Information in Japanese Literature Combined with Text Mining Techniques
Authors: Wang Tingting
Published: May 2024

Japanese literature is renowned for its conciseness and the profound, multi-layered meanings conveyed through its economical use of language and rich symbolic content. This paper explores the creative impact of these linguistic features in Japanese literature by analyzing the deep meanings and varied classifications of literary metaphors. The construction of a Japanese literature corpus involved the collection, cleaning, and organization of Japanese literary texts, followed by the selection of specific linguistic features. The corpus was then aligned using a dynamic programming approximation algorithm. A semantic representation model of the Japanese literature text corpus was developed by integrating the Attention Word Embedding Model with the Extended Topic Information Model, and metaphoric corpus features were fused using the static fusion strategy of Extended Topic Information and Attention Word Embedding. This study also examines the translation of symbolic information in Japanese literature, focusing on linguistic and stylistic features. The findings reveal that translations into Chinese tend to employ augmentation translation, resulting in 1,706 additional sentences compared to the original Japanese texts. Furthermore, the lexical density in the Chinese translation reference corpus is 2.45 percentage points higher than in the Japanese literature corpus. Analysis of verb modifications shows that among the 90 altered verbs in the Chinese translation corpus, only 24 have corresponding instances in the original Japanese texts. Text mining techniques were employed to conduct a deep analysis of symbolic content, enhancing the understanding of the nuanced connotations inherent in Japanese literature.
A study of applications in archive management empowered by artificial intelligence
Authors: Wang Yue , Wu Changjing , Li Wenjie , Wang Zhen
Published: May 2024

As a critical component of information management, the development of digital and information archive systems enhances both the efficiency and quality of enterprise operations, thereby increasing economic value. This paper employs the ReLU activation function to augment the non-linear capabilities of the neural network model. Additionally, we introduce the MP-CNN model, designed to extract and recognize textual content from archival images. These images are initially processed using the BP neural network algorithm, followed by grayscale conversion for clarity, and subsequently backed up for analytical purposes. The implementation of intelligent archive management resulted in a more than 35% improvement in efficiency. The distribution interval of the Return on Investment (ROI) values from archival data at the test site ranged between [0,5], displaying a concentrated pattern that aligns with the typical economic value distribution. The integration of AI technology in archive management not only streamlines processes but also maximizes resource utilization and enhances returns.
Study on the historical landscape evolution of the core reserve of Guangfu Ancient City based on computer simulation
Authors: Li Qinghong , Xu Jiaxuan
Published: May 2024

In the conservation of the historical landscape within the Guangfu Ancient City Core Protection Area, traditional descriptions via drawings and textual narratives often exhibit subjective biases. To address this, a theoretical model for the historical architectural landscape has been developed to objectively measure and characterize the spatial patterns and morphologies of the landscape. This study introduces Exploratory Spatial Data Analysis (ESDA) techniques, utilizing spatial weights and spatial correlation measures as primary analytical tools. Additionally, meta-cellular automata are employed to simulate the spatial and temporal evolution of the historical landscape. Geographical Information Systems (GIS) and Remote Sensing (RS) technologies have been leveraged to establish a spatial database and facilitate the visualization of the historical landscape’s evolutionary processes. This integrated model and technological approach enable a detailed analysis of the architectural landscape characteristics and the spatial structure’s evolution within the study area. The findings reveal distinct spatial distribution characteristics, with an undulation index ranging from 5 to 20 and a predominant index over 7, accounting for 15.67% of the land. Based on these insights, the study proposes strategic interventions to safeguard the historical integrity of Guangfu Ancient City’s core conservation area.
Semantic network model in Chinese vocabulary generation and evolution
Authors: Tu Jianan
Published: May 2024

This study delves into the semantics of Chinese vocabulary generation and evolution, providing insights into the profound connotations of the Chinese language and culture. We begin by vectorizing Chinese vocabulary data using the Word2Vec algorithm, which is subsequently input into a deep neural network model. Within this framework, the neurons are tasked with extracting semantic features pertinent to the developmental trajectory of Chinese vocabulary. Following this, the Intersection over Union (IoU) value for each semantic feature is computed, enabling the semantic annotation of the vocabulary. Additionally, the formulation of constraint rules significantly enhances the model’s accuracy in semantic recognition analysis. This approach not only advances our understanding of linguistic structures but also enriches our appreciation of the cultural dynamics embedded within the language. The accuracy and recall of the semantic network model in this study are much higher than those of other comparative models, with an average semantic annotation accuracy of 91.33% in the three Chinese vocabulary datasets, which supports further research and analysis in follow-up. The exploration of the practical application of the semantic network model shows that it achieves better results in the semantic identification and annotation of words in poems, and it is found that the lexical semantic class with the highest frequency in the Three Hundred Song Lyrics is {Func word}, which accounts for 0.056. The semantic network model designed in this paper provides an effective method in the field of Chinese vocabulary semantics analysis and lays the foundation for a deep understanding of the generation and evolution of the culture of the Chinese language. A foundation is laid for a deep understanding of the generation and evolution of Chinese language culture.
Research on the application of machine vision in the design of machine automation
Authors: Zhang Dawei , Li Yayun
Published: May 2024

The application of machine vision technology to mechanical automation design is an inevitable measure to improve the comprehensive productivity of mechanical production manufacturing. In this paper, a mechanical automation system based on SOA architecture is designed to cover the image acquisition, processing, and recognition workflow of an image processing module based on machine vision. The binocular camera calibration is completed by the Zhang Zhengyou calibration method. The image is preprocessed by using algorithms such as the mean value method, segmented linear transformation and median filtering, and an algorithm is proposed to improve the ORB feature point extraction, which can extract and match the feature points quickly and efficiently. Meanwhile, a Harris corner point detection algorithm is proposed to improve the SIFT algorithm to enhance the accuracy of target recognition and localization. The designed mechanical automation system is applied to the lychee picking robot, for example, analysis, which shows that the overall recognition P-R value of the system reaches 0.953, and the classification accuracy is above 0.917. In the mechanical automation route localization, the lateral deviation is lower than 4.80cm. The maximum time for image processing and parameter transfer is 117.966ms, which indicates that the system involved in this paper is relatively stable in operation and has a better effect on the localization of the navigation line, which is of certain application value in the field of mechanical automation design.
Research on Visual and Interactive Evaluation Methods for Space Design Based on Virtual Reality Technology
Authors: Zhang Tao
Published: May 2024

This paper establishes different detail-level terrain grids for different terrain data blocks and generates multi-resolution terrain based on the tree-structured LOD model as a way of layering large-scale terrain data. Then, the virtual environment’s visual and image texture are rendered to visualize the virtual spatial environment. Then, the overall architecture of the interaction platform was designed, and the virtual space design visualization and interaction effects were studied based on spatial distance perception, presence experience perception, and error analysis. The results show that there is a significant difference between the mean value of people’s perceived satisfaction in the interaction space and non-interaction space M=163.138, t=1.376, p=0.005<0.05. The error in the interaction of the system in this paper is between (0.2 and 1.8), which indicates that the system performs well. This study of interaction design research proposes a new research dimension for the traditional interaction interface based on virtual reality technology, which provides an effective reference basis for future related designs.
Application and testing technology of new road materials in highways
Authors: Jia Chunyan
Published: May 2024

In the face of annual highway construction and highway maintenance projects, traditional road materials and road testing technology are difficult to meet the current highway construction needs. Based on this research background, the article first discusses the three-dimensional ground-penetrating radar nondestructive testing technology, analyzes the detection principle from the fluctuation equation of electromagnetic wave, the propagation characteristics of electromagnetic wave, and the propagation speed in the medium, and specifically analyzes its detection performance and application in the detection of the thickness of the structural layer. Finally, some sections of the Shanzhan Expressway are chosen as test objects and test experiments are designed and implemented. The test results show that the strength of the road material with water water-reducing agent increases compared to the material without water water-reducing agent. By using red mud instead of cement, road materials can have a relatively high strength. Therefore, using red mud as a substitute for conventional materials is entirely feasible and can save costs. The cracking rate of the highway was reduced by using the “leaching recycled” material, and the small cracks of less than 2mm were basically sealed, while the cracks of more than 2mm were alleviated. There is no water seepage on the pavement at 28 points of the 7 sections tested, so the “leaching regeneration” material has a better waterproof effect on the highway pavement.
Tax Strategy and International Financial Management of Multinational Companies
Authors: Jin Qisen , Fu Yu
Published: May 2024

In the context of intensifying global competition, the exploration of corporate tax strategy is emerging as a pivotal area within financial management. This paper develops a flowchart for a tax planning scheme tailored to the economic strategy of multinational corporations. It examines the tax planning approaches related to enterprise financing strategy and capital operation strategy, identifying the optimal tax planning scheme based on two primary service objectives outlined in the flowchart. An empirical analysis is conducted using the case of H Communication Company to investigate the tangible benefits of its tax strategy on international financial management during its multinational operations. The results demonstrate that following tax planning, the coefficient for the cross-term of the multinational company’s earnings per share stands at 0.8340, suggesting that the market has positively received the company’s effective tax avoidance measures. This study not only advances practical research on tax planning for multinational projects but also serves as a dual theoretical and practical reference for the operations of multinational enterprises.
Analysis of Innovative Strategies of English Literature Teaching in Colleges and Universities under the Guidance of Ecological Literature Criticism
Authors: Liao Haiyan
Published: May 2024

This paper analyzes the theory of ecological literary criticism from the perspectives of anthropocentrism, environmentalism, ecologism, materialistic developmentalism, and technological supremacy and points out the prospects for the application of the theory of ecological literary criticism in the teaching of English literature in colleges and universities. Based on the characteristics and contents of English literature teaching in colleges and universities, a model of English literature teaching that incorporates ecological literary criticism is proposed. Taking the English majors of Normal University as the research object, using SPSS software and Coh-Metrix 3.0 as the analyzing tool, we set up the control group and the experimental group. We conducted an instance analysis of the English literature teaching mode that incorporates the theory of ecological literary criticism. The results show that the grouping presents a 0.05 level of significance (t=2.265, p=0.032) for the posttest of the application essay achievement, as well as the specific comparison of the differences can be seen, the mean value of the experimental group (11.935), which will be significantly higher than the control group’s mean value (10.915). It means that compared with the traditional English writing teaching mode, the English literature teaching mode based on the ecological literary criticism theory is more helpful in promoting the improvement of the English literature writing level of the students in the experimental group.
Inclusive teaching through a musical instrument: the case of the musical studio in Aktobe, Kazakhstan
Authors: Spulber Diana , Magzimbetova Gulsana
Published: May 2024

The manuscript aims to analyze the impact of learning musical instruments on the inclusion process. Music represents a universal language capable of bringing together and connecting seemingly different worlds. Due to this facilitator function in communication, music can become an effective tool for inclusion. Learning music and musical instrument music is fundamental for the cognitive, emotional, and motor development of individuals, with particular regard to children with different disabilities. Adapting the method of Skriabin of Itten and figure notes and to teaching music to disabled children has shown a positive impact on social and emotional improvement and, respectively, on the inclusion of children with disabilities. The study case results will permit the improvement of inclusion through music learning using the developed method.
Social Responsibility in Ukrainian HEIs: Sociological Analysis of Current Situation and Key Trends During the Wartime
Authors: Orzhel Olena , Petroye Olha , Shofolova Nataliia , Lytovchenko Olena
Published: May 2024

The goal of the paper is examination of social responsibility implementation by Ukrainian HEIs, its modifications during wartime and prospective adjustments to fit the purposes of postwar revival. Several methods were applied in this study: content analysis for literature review; survey method to collect and interpret data on USR at Ukrainian HEIs; descriptive and mathematical statistics methods for data processing and presentation; synthesis method and reflexion for analysis, discussion and drafting conclusions. The main findings of the survey are as follows: the dominant share of university community believes that social responsibility policy is present and implemented in their HEIs; for the majority of respondents, university social responsibility is primarily associated with ensuring high quality of education, volunteer activities and philanthropy, responsible research, and educating students to be responsible citizens; academic staff and students are the major agents who initiate projects, programs and events focusing on social responsibility; university social responsibility has intensified with the beginning of fully-fledged war; currently HEIs understand their social responsibility as ensuring safety of students and staff, support to the Ukrainian army, caring for displaced persons, maintaining and restoring mental health of students and staff, as well as other citizens.
Transformational Leadership, Perceived Organizational Support Sharing, Organizational Commitment and Employee Performance: the Role of Religiosity
Authors: Sulaeman Moh. Muklis , Haryono Tulus , Sunaryo Sinto , Hendarsjah Hidajat , Riani Asri Laksmi , Wahyuni Salamah
Published: May 2024

Objective: The purpose of this study is to examine how transformational leadership, knowledge sharing, and perceived organizational support affect organizational commitment and how their effects on performance are influenced by religiosity at Nahdlatul Ulama University in East Java. This kind of study is known as explanatory research.
 
Method: Purposive sampling is the kind of sample strategy that should be applied. 345 samples were successfully obtained for this study. A Likert scale questionnaire was employed as the data gathering method in this investigation. The Partial Least Square (PLS) method was used to analyze the data, and SmartPLS version 3 PLS software was used.
 
Research Findingsand Discussions: The following factors have been found to have a positive and significant impact on organizational commitment: 1) Transformational Leadership; 2) Perceived Organizational Support; 3) Knowledge Sharing; 4) Organizational Commitment has a positive and significant impact on performance; and 5) Religiosity strengthens the relationship between organizational commitment and employee performance.
 
Research Implications: Research implicates poor lecturer performance with low-quality tertiary institutions. Studies must expand focus to include knowledge sharing, organizational support, and leadership to enhance relationships and improve organizational commitment and performance.
 
Originality/Value: The poor performance of lecturers as members of the teaching staff in higher education is inextricably linked to the low quality of tertiary institutions. Numerous studies that have been done only look at a few variables and ignore the importance of knowledge sharing, perceived organizational support, and transformational leadership in maximizing the potential for relationships that are mediated by organizational commitment and moderated by religiosity to improve company performance.
Rains, Tragedies and Media Coverage: Analysis of Floods In Rio Grande do Sul
Authors: Oliveira Felipe Moura , Holanda Thiago Costa , Ramalho Ana Lidia de Oliveira Silva , Kloeckner Natalia Varela da Rocha , Moura Italo Emmanoel Mesquita Oliveira de , Ricarte Thiago Limoeiro , Ribeiro Karina Valdez
Published: May 2024

Objective: The objective of this study is to present how the tragedy in Rio Grande do Sul is handled by the media, in order to observe whether it is being related to climate change.
 
Theoretical Framework: Environmental disasters have been intensifying with the great advances of human actions, which cause climate change and journalistic structures play a crucial role in shaping the public perception of natural disasters, framing them in the context of climate change.
 
Method: From the use of text mining techniques in reports published in Brazilian news portals about the floods in Rio Grande do Sul, a corpus of 100 texts from Google News was selected, being processed through the Voyant Tools software for extraction and analysis of textual data.
 
Results and Discussion: Media coverage of the tragedy in Rio Grande do Sul highlighted the social consequences and the impact on urban centers. The news simplifies the understanding of the causes of the tragedy, focusing mainly on heavy rains and neglecting factors such as global warming and El Niño. In addition, socioeconomic influences that amplify flood risks, such as poor infrastructure and housing conditions, were neglected in the discussions. The media also emphasized the importance of understanding the interaction between climate and geography to formulate strategies that minimize the effects of flooding and promote the sustainable development of the affected regions.
 
Research Implications: By revealing how climate change narratives are being integrated into coverage of natural disasters, this study helps to understand the role of the media in educating the public and influencing public perception of the need for climate mitigation and adaptation policies.
 
Originality/Value: This study examines how the Brazilian media approaches flooding in Rio Grande do Sul, highlighting the social consequences and the importance of understanding the interaction between climate and geography. Using text mining techniques to analyze a corpus of news stories, the research offers a succinct and objective analysis of media coverage, contributing to an understanding of communication about extreme weather events.