bluuebunny/crossref_metadata_2025 huggingface dataset:
Equilibrium Modelling of Cost Control in Civil Engineering Management in the Context of Carbon Neutrality
Authors: Ni Bijun
Published: June 2024

In civil engineering management, under the background of carbon neutrality, there is a strong correlation and mutual constraints between cost, duration, and quality, and all civil engineering management must grasp cost control and multi-objective equilibrium. In this paper, the objective functions of duration, cost, and quality are constructed, the multi-objective equilibrium model of duration-cost-quality of civil engineering management is designed, and an improved non-dominant ranking genetic algorithm with elite strategy is constructed for solving the mathematical problem of multi-objective optimization. Finally, the model is used to analyze the case of a three-story mixed-structure office building, and it is found that the total cost of the model is 1089048 yuan, and the calculation is stopped when the programming cycle is 10096 times. Among them, scheme 1 has 146 working hours, a cost of 1.765 million yuan, and a quality of 0.95. Scheme 2 has 161 working hours, a cost of 1.693 million yuan, and a quality of 0.94. Scheme 3 has 176 working hours, a cost of 1.917 million yuan, and a quality of 0.99, and the specific plan can be selected according to the preference of the decision-maker. The model and algorithm’s effectiveness and matching are verified by analyzing actual data. This study enriches the theory of multi-objective optimization problems in engineering projects and provides a practical approach to managing project objectives.
Exploring the Direction of English Translation of Environmental Articles Based on Emotional Artificial Intelligence Learning Models
Authors: Xian Wensen
Published: June 2024

In this paper, we improve the performance of machine translation emotion recognition by fusing word features and linguistic features of environmentally friendly text with LSTM neural networks. Multi-channel LSTM’s unbalanced emotion classification method can address the problem of unbalanced numbers of samples in each emotion category in the emotion classification task. The bilingual semantic similarity degree feature is added to the translation process of English environmental protection data so as to make the translation of English environmental protection data more accurate. The proposed method is validated through experiments, and the results show that the translation quality of the LSTM model is generally higher than that of other models, and the mean value of the translation quality of the LSTM on the test17 dataset is 50.4. In terms of environmental protection terminology, mistranslations, common word mistranslations, etc. There is a significant reduction of 2–3 times in the absolute number of the LSTM model compared to the traditional method. A total of 94,788 corpora were obtained from 10 environmental translations, such as Silent Spring and Solace of the Heart, and 2,311 favorite emotion words were identified. Comparative analysis of the samples reveals that most of the translation results of some environmental terms are in the range of 0.7–0.9, and the range of semantic overlay between the machine translation results of the LSTM model and the standard translations is large. Most users believe the model improves the translator’s translation level and diction accuracy.
Innovative design of digital sculpture art under 3D modeling technology
Authors: Liu Shaowei
Published: June 2024

3D modeling technology is one of the most important research directions in computer vision, which is increasingly linked with digital sculpture art. Combined with the point cloud, a new type of image data, this paper innovatively proposes a multi-view 3D digital sculpture reconstruction model to realize the 3D digital sculpture reconstruction of point cloud data.3D digital sculpture reconstruction is mainly divided into two parts: point cloud data processing and 3D reconstruction. The former uses radius, statistical filtering, and bilateral filtering algorithms for point cloud data denoising and proposes an NDT alignment algorithm to integrate point cloud data. The latter triangulates the unreconstructed observation points introduced by the new image, uses beam method leveling to globally optimize the point cloud structure, and proposes incremental recovery and global recovery reconstruction methods, respectively. In the point cloud data alignment performance test, the reconstruction plotting time of the reconstruction model in this paper possesses a large improvement, and the proposed NDT algorithm outperforms the traditional algorithm in terms of accuracy and execution efficiency. In the reconstruction of architectural digital sculpture, the average error of the parts of the digital sculpture is 0.00775, and the maximum residual difference is at about 4.5 pixels. Hence, the sculpture’s accuracy and precision performance are better.
Research on Coupling Model of Foundation Treatment and Geological Hazard Risk Assessment
Authors: An Kangyue , Zhang Jing
Published: June 2024

High-risk areas of geologic disasters need to select appropriate foundation treatment techniques according to different risk assessment levels to ensure the overall quality and safety of housing construction projects. In this paper, for the three foundation treatment technologies for different geologies, the geologic condition sensing measurement algorithm is designed according to the principle of InSAR technology, and the informativeness-logistic regression algorithm is proposed for vulnerability risk evaluation. The TRIGRS algorithm that has been improved is used to construct the geologic hazard risk assessment model. Then, the data preparation work is carried out in the practical application, and input data are connected through a series of preprocessing operations. Taking the landslide geohazards occurring in a certain place as an example, the geologic deformation curve generated by the system was used to analyze them, and the risk assessment of geohazard susceptibility was also carried out in a certain area. It was found that the cumulative deformation curve from the 20th week to the 30th week of 2020 decreased significantly by more than 100mm. The actual major landslide disaster occurred at the beginning of June 2020, and the results of the system operation are in line with the time of the actual disaster. For all 11 factors, logistic regression analysis yielded significant results. The proportion of 5-level susceptibility areas of geologic hazards is 31.5%, 24.6%, 20.2%, 14.7%, and 9%, respectively, and the distribution of assessment results is reasonable. This study provides new ideas and effective methods for defining the level of geohazard risk assessment and selecting foundation treatment technology.
A Study on the Internal Logic and Governance Effectiveness of Platform-Based Organizations from the Perspective of Digital Governance
Authors: Chen Rui , Zhang Rongjie
Published: June 2024

This paper first constructs a basic framework for digital governance of platform-type organizations and explores the application of digital governance of platform-type organizations and the social governance process from the three dimensions of the logic of efficiency, the logic of legitimacy, and the logic of social relations. Then, the driving elements of digital governance of platform-based organizations are studied using the fsQCA method and QCA analysis, and the influence of social synergy and people’s participation on the effectiveness of digital governance of platform-based organizations is analyzed. The results show that attention allocation, social governance resources, digital governance capacity, social digital environment, cultural openness, peer competition pressure, and innovation environment need to reach at least 94.5%, 79.53%, 75.4%, 81.5%, 77.5%, 78.35%, and 78.33% of the social governance quality bottleneck level, respectively. This research paper explores the drivers and influencers of platform governance performance, which helps to identify the patterns of platform operations.
Breakthroughs and Applications of Augmented Reality (AR) Technology in the Digital Media Field
Authors: Lin Muye , Yang Kangyu
Published: June 2024

This study pioneers the application of augmented reality (AR) in the realm of digital media, integrating AR technology with cultural education and artistic media concepts to forge a novel trajectory for digital media art creation. It delves into AR 3D scene construction technologies, employing calibration through the reconstruction of 2D image sequences, feature point extraction for spatial coordinate transformation, and 3D model development. Furthermore, it utilizes Level of Detail (LOD) models and texture mapping technologies to enhance visualization and interaction. The research culminates in a comparative analysis of traditional and AR-based media, evaluating differences in appeal and assessing functional capabilities. The findings indicate that AR-based media outperforms traditional media across several functions: media search (0.385), virtual design (0.424), immersive experience (0.466), real-time interaction (0.525), and user communication (0.396), with users expressing high satisfaction with these enhanced capabilities. This study not only diminishes the complexities associated with integrating digital media and AR technologies but also optimizes and innovates traditional methodologies.
Revealing or concealing: The impact of environmental penalty spillover effects on corporate environmental information disclosure
Authors: Dong Baoxin
Published: June 2024

As a way of environmental protection, environmental administrative punishment affects the environmental decision-making of enterprises to a certain extent. This paper proposes the industry spillover effect of environmental administrative punishment, utilizes the variable factors affecting the quality of corporate environmental information disclosure, and puts forward the hypothesis of the relationship between the spillover effect of environmental punishment and the level and quality of environmental information disclosure, whether it is “displaying” or “disguising”. Companies listed in the heavy pollution industry are selected as research objects to test the relevance of each influencing factor on environmental information disclosure. The double-difference method is used to construct the regression model to verify the influence of government regulation on the level of environmental information disclosure, analyze the impact of environmental information disclosure level on the market value of enterprises, and the relationship between environmental administrative penalties and environmental information disclosure. The regression equation passed the F-test with an adjusted R
2 of 0.425 and the coefficient of EDI of 0.362. It passed the 1% significance level test, indicating that the level of environmental information disclosure is positively related to enterprise value. The higher the level of disclosure of the environment, the higher the market value. Whether the listed company is engaged in legitimacy management or impression management, manipulating environmental disclosure during this period has an impact on the level and quality of environmental disclosure.
Design of a new fast heating device in wireless portable water dispenser in the age of intelligence
Authors: Qian Tao , Liu Huayu , Chen Chunquan
Published: June 2024

In our daily life, the quickness of water dispensers provides great convenience for our life. By examining the PID control system and fuzzy control system, a fuzzy PID controller has been designed. This system can be used for both automatic and manual parameterization. The problem that the stable operation of the temperature controller cannot be guaranteed in the PID controller has been solved. In this paper, the designed extreme heating and temperature regulation system is installed in the controller of the wireless portable water dispenser to analyze the effects of using this new product. Comparative experiments indicate that the wireless portable water dispenser with a heating and regulating system has an average hot water production capacity of 3.68L/H, which is higher than the standard value of 3.0L/H. The high-speed heating and regulating system in the wireless portable water dispenser shows that it has a better heating capacity than the ordinary wireless portable water dispenser. Based on the regression analysis of this new product on the basis of user satisfaction, the overall innovativeness of the product = 0.62*usability + 0.032*emotion + 0.056*functionality. The “Usability” construct has the best predictive power with 62% explanation. It indicates that the demand for the product is high among users.
Research on safety accident risk of construction engineering based on natural language processing technology and neural network technology
Authors: Wang Shuo , Meng Haohan
Published: June 2024

In recent years, China’s construction industry has achieved rapid development, while the problem of safety accident risks brought by construction projects has also arisen. In this paper, based on natural language processing technology, using a graph neural network algorithm, we constructed a graph data model of safety accident reports in construction engineering and generated a database of association rules of safety risk factors in construction engineering to identify and classify the risk of safety accidents in actual construction engineering. The pictures of safety risk behaviors at the construction site are processed with feature mapping and inputted into a convolutional neural network to build a construction engineering safety warning model. Through simulation experiments, the identification results of risk factors for the model constructed in this paper and the effective degree of safety warning are tested. The top five factors in the centrality ranking of risk factors of construction engineering safety accidents are S17, S6, S1, S9, and S8, with centrality levels of 1.9779, 1.8626, 1.8204, 1.6332 and 1.4534, and the factor attribute of S6 is the outcome factor. The warning model constructed in this paper is measured against the level of safety risk of the construction project under the non-adoption of the warning model. The safety risk is reduced by 35.8% after the adoption of the safety accident warning model, which shows that the model in this paper has a certain inhibition effect on the risk of safety accidents.
Optimization of Import and Export of Aquatic Products in Zhanjiang City--Platform Construction Based on Blockchain Perspective
Authors: Yan Yanrong
Published: June 2024

Amid the advancement of the global economy and the digital era, Zhanjiang’s aquatic products have increasingly contributed to its total import and export volume. However, its geographical position, encircled by the sea on three sides, exposes the region’s aquaculture and processing industry to significant challenges, notably the discharge of nuclear wastewater from Japan. Traditional practices governing the import and export of Zhanjiang’s aquatic products face several issues, including complex transaction negotiations, inefficient customs supervision, inadequate logistics, high settlement costs, and difficulties in tracing product quality. The adoption of blockchain technology offers a promising solution to these challenges. By harnessing the inherent features of transparency, decentralization, security, and confidentiality, along with integrated consensus, trust, security, and synergy mechanisms, this study proposes the development of a comprehensive import and export platform for Zhanjiang’s aquatic products. This platform is structured across five layers: data source, data layer, network layer, service layer, and operation layer. Enhancements across five critical components—signing, supervision, logistics, payment, and consumption links—can significantly optimize the traditional pain points associated with Zhanjiang’s aquatic product transactions. The implementation of blockchain technology in this context is anticipated to foster healthy and rapid development within the sector, promoting a more sustainable and efficient trade environment.
Construction and validation of a model of the relationship between bra functional requirements and mammary gland development in adolescent girls
Authors: Zhao Yulin
Published: June 2024

The researchers studied whether there was a bra style or brand preference in adolescent girls and adopted a hybrid approach to study the girls’ expectations for bras regarding the comfort, protection, and support they provide, with a view to assessing the function of the bras for adolescent girls. The research took samples from girls aged eight to 18 who are concentrated in Guangdong Province. The researchers found that teenage girls desire improved bras that are properly sized and fit for them, providing comfort, protection, and support. Additionally, the bras that adolescent girls want should not interfere with their daily study or sports activities. Underwear manufacturers can improve the bra design for teenage girls by incorporating the results of this study, ensuring healthy breast development and meeting their needs and expectations.
Investigation into the Long-Term Stability of Carnallite Pillars Considering Creep Influence
Authors: Li Mingjie , Li Xibing , Chen Jiangzhan , Huang Linqi
Published: June 2024

In subterranean potash mines utilizing the room-and-pillar mining method, maintaining the long-term stability of carnallite pillars is imperative for the safety and ongoing viability of operations. This study undertakes uniaxial compression creep tests on carnallite samples sourced from the Dongtai Potash and Magnesium Salt Mine in Laos. The durability of carnallite pillars is evaluated using an advanced Burgers creep model combined with Flac3D numerical simulations. Results indicate that the creep strength of carnallite is approximately 60%–70% of its immediate strength, demonstrating significant creep behavior. The refined Burgers model provides an accurate representation of the carnallite’s creep characteristics. Post-excavation, the internal compressive stress within the pillars progressively increases, registering an approximate rise of 1 MPa, and stabilizes under pressure after one year. After three years of continuous observation through creep tests and Flac3D simulations, the maximum deformations detected in the roof and floor of the mining house, as well as the adjacent rock masses, were 60mm and 20mm, respectively, indicating minimal overall deformation. The width of the plastic zone within the pillars exhibits time-dependent growth, with rapid expansion occurring in the internal plastic zone and a significant deformation rate within the first six months post-excavation. To ensure the long-term stability of the mining pillars and voids, it is recommended that backfilling operations be conducted within six months following the excavation.
Internet usage and household energy poverty
Authors: Liu Yifei
Published: June 2024

Based on the double critical value method and the data of the China Household Panel Survey from 2014 to 2023, this paper measures the multidimensional relative household energy poverty in China. After confirming the impact of income poverty on energy poverty, this paper explores the formation mechanism of energy poverty from the perspective of opportunity acquisition. It explores the occurrence path of “opportunity access-income poverty-energy poverty” of residents by combining the structural equation model. Finally, the impact of Internet use on energy poverty was investigated through multiple regression analysis. According to the study, China’s official poverty line is about 2.0 US dollars, and the energy poverty line has increased by 49.6% in 2022 compared with 197.2 yuan in 2018. In the empirical analysis of access level and energy poverty, the coefficient of Internet learning is 0.311. Further, adding the moderating effect model regression results of the interaction term shows that the Internet penetration rate has a significant positive impact on multidimensional energy poverty. When it is increased by 1%, the multidimensional energy poverty is reduced by 9.25%.
The Impact of the Sino-US Intellectual Property Cases on the Evolution of Chinese Law and the Future Globalization Trend of Chinese Law from the Perspective of the WTO
Authors: Zhang Chenqing , Dong Zihou , Chi Junwei
Published: June 2024

This paper critically examines the trade relations between China and the United States, with a particular focus on the sensitive issue of intellectual property rights (IPR) trade frictions and disputes. It delves into the root causes of IPR conflicts between the two nations by analyzing IPR cases that have arisen since China acceded to the World Trade Organization. Notably, during the period from 2001 to 2016, the United States initiated a total of 243 “337 investigations” cases against China, which represents 77.66% of all such investigations targeting China. This study also considers the strategic implications of these cases and assesses the impact of the evolving IPR system in China. In 2008, China’s IPR policies were notably centered on enhancing protection, which is reflected in text mining results where the keyword “protection” emerged as one of the top eight high-frequency words, with occurrences ranging from 25 to 73. Furthermore, this analysis forecasts the future trends in China’s legal globalization, informed by the evolution of its intellectual property law.
Numerical Simulation of the out-of-plane mechanical properties of tall foam ceramic (FC) partition wall
Authors: Zhang Zhengze , Cheng Bei
Published: June 2024

This paper conducts simulation research using Abaqus software and Finite Element Software on the out-of-plane mechanical properties of large-scale FC partition walls. Exploring the structural columns of 1.2m, 1.8m, and 3m, respectively, in large-size FC partition walls under out-of-plane loading, the cracking pattern of wall panels, the distribution of cracks, the damage pattern, the load-deflection curve, and the weak parts of the wall panels and the weak points of the wall panels under out-of-plane loading. The simulation results of experimental software in this paper show that the three specimens meet the design requirements, have good integrity before cracking, and are interoperable with steel bone and foam ceramic. Then, the finite element models of the steel frame-embedded foam ceramic wall with different densities were established, and the influence of the density of the foamed ceramic on the out-of-plane mechanical properties of the wall was further studied. The results show that when the density of foamed ceramics increases from 400kg/cm3 to 500kg/cm3, the fracture performance is significantly improved, while when the density increases from 400 kg/cm3 to 500 kg/cm3, the fracture performance is not significantly improved. It is also found that the out-of-plane bearing capacity of foamed ceramic walls with embedded steel frames increases with the increase of foamed ceramic density, and the mid-span deflection decreases with the increase of density. However, with the rise of embedded steel frame spacing, the influence of foam ceramic density on the out-of-plane load and mid-span deflection gradually diminishes. The results of this paper can provide some guiding significance for the design and construction of large-size and story-building partition walls in the future.
Research on the Theory and Innovation Strategy of Digital Media Art Development Based on Artificial Intelligence Technology
Authors: Wang Juncheng , Zhang Jie
Published: June 2024

Artificial intelligence (AI) technology significantly enhances the creative capabilities and expressions of artists, playing a pivotal role in the innovation of digital media art. This paper delves into the technical aspects of digital media art expression, introducing a human-computer interaction (HCI) media art model. This model is designed to cater to the visual sensitivities of the human eye by optimizing text readability and interface color during interaction. We further enhance the interactive interface by converting the color space, applying de-blurring techniques, and mitigating the noise associated with image binarization to refine the HCI interface. The efficacy of these interventions is evaluated through practical implementations in digital media art, focusing on the application effectiveness of HCI and user satisfaction. Our experimental outcomes indicate that the noise level of the employed techniques is maintained within a narrow range of −1.5 to 1.5 dB, demonstrating minimal and consistent fluctuations that substantially improve image processing and influence the final visual output. Furthermore, in assessing user interaction satisfaction, the average user satisfaction scores for the four interactive modalities ranged between 3.316 and 3.684, indicating that most users are satisfied with the digital media art designs integrated with AI.
Human Resource Management Performance Assessment and Enhancement in Public Community Governance
Authors: Yang Lei
Published: June 2024

Human resource management is a more important part of public sector internal management. Based on the principles of objectivity, comprehensiveness, and significance of indicator construction, this paper constructs a human resource management performance assessment model in public community governance. It introduces the entropy weight method and TOPSIS method to comprehensively and objectively calculate the degree of influence of each evaluation indicator on public human resource management performance. Meanwhile, taking the data of public community governance in County S as an example, the vertical and horizontal comparisons of public human resource management performance are carried out to explore the corresponding public human resource management performance improvement strategies. The results of the study show that in the public human resource management of County S city, the weight of the character factor indicator is the largest (0.3801), and that of the diligence element is the smallest (0.0936), indicating that the character factor has the greatest influence on the human resource management performance of public community governance in County S city. In order to improve performance, it is recommended to promote the optimization of the management system by combining the performance management experience, as well as to continuously innovate the human resource incentive methods through multiple research.
Adaptive educational game design incorporating the psychology of early childhood development: a study of enhancing learning experiences and promoting cognitive development
Authors: Wang Jing
Published: June 2024

Grounded in the principles of developmental psychology, this study develops an innovative online educational game for young children titled “Fill in the Picture.” Utilizing the AppCan platform in conjunction with Photoshop technology, the game involves the automatic generation of randomly sampled, unordered point sets using network depth search algorithms. It captures the sequential order in which children connect these points onscreen to form coherent graphical representations, subsequently assessing the correctness of these connections against computer-judged standards. The effectiveness of “Fill in the Picture” was evaluated through a questionnaire survey, which revealed a weighting coefficient of 0.248 for the game’s educational quality. Additionally, it scored above 4 on various dimensions, including educational value, scientific basis, playfulness, artistic integration, immersion, and technological engagement. Importantly, in terms of pedagogical design satisfaction, 81.3% of respondents recognized that the game significantly enhances understanding and mastery of scientific concepts, while 81% appreciated the logical organization of its content. Thus, the “Fill in the Picture” game, designed and developed by integrating a tailored educational game design model based on developmental psychology, demonstrates substantial educational efficacy and user satisfaction.
Data Security and Privacy Protection in the Comprehensive Agricultural Administrative Law Enforcement Database
Authors: Song Wanqiang
Published: June 2024

Nowadays, cloud computing technology is developing rapidly, and cloud platforms as a new type of information service mode. The importance of its security is self-evident. This paper builds a comprehensive database for agricultural administrative law enforcement based on the cloud platform. It constructs a hybrid data encryption algorithm that utilizes the AES algorithm and ECC algorithm in parallel. The ECC algorithm uses the public key to encrypt the secret key, and after that, the AES algorithm converts plaintext data in the database into ciphertext data. Following the testing of the hybrid encryption algorithm’s security and operational performance through experiments, the database’s security and privacy performance are also evaluated. The comprehensive agricultural law enforcement database constructed in this paper is able to rapidly reduce the degree of trust in users with abnormal behavior in the monitoring of user behavior that is not conducive to data security and privacy protection and reduce the degree of user trust to 0.022 when the number of times of dynamic monitoring is 20 times, which effectively protects the data security and privacy in the database. The hybrid encryption algorithm database designed in this paper provides a reference for data security and privacy protection. It has strong practical application value in the field of comprehensive agricultural administrative law enforcement.
Application of anti-mapping security access technology in network security protection
Authors: Ma Dongjuan , Li Rui , Liu Zehui , Guo Min , Jin Xin
Published: June 2024

In the current era, characterized by the pervasive Internet of Everything, trillions of data points are exposed to high-level threats, presenting novel challenges to the domain of cyberspace security. This paper introduces a cybersecurity protection framework derived from the PDRR model, enriched with integrated cybersecurity measures. Utilizing a cyberspace mapping architecture that incorporates anti-mapping security access technology, we analyze the robustness of cybersecurity protections. The framework employs penetration testing queue technology to uncover vulnerabilities within cyberspace, the Hidden Markov Model to assess cybersecurity posture, and the QPSO-LightGBM model to evaluate cybersecurity vulnerabilities. To validate the efficacy of the cyberspace mapping architecture in employing anti-mapping security access technology, we have systematically conducted various experimental methodologies, including penetration testing, security posture sensing, and security vulnerability assessment. This integrated approach provides a comprehensive framework for addressing the complex challenges posed by the vast scale of data in today’s interconnected environments. The average send/receive telegram packets of the network I/O graph in the state of SYN flooding attack grows from 60 packets/sec in the normal state to 2.2*104 packets/sec, and the minimum time of security posture perception by the Hidden Markov Model is only 51.28ms. The accuracy of the QPSO-LightGBM model for network security vulnerability assessment reaches 86.58%. Fully utilizing anti-marker security access technology can improve the understanding of the threat situation in network security and enhance the protection ability.
Research on Comprehensive Evaluation Model of Supply Chain and Logistics Performance Based on Economic Management
Authors: Jiang Qiong
Published: June 2024

The establishment of a scientific and comprehensive comprehensive evaluation model of logistics performance is of great significance to enhance the cost reduction and efficiency of enterprises and market competitiveness. The research constructs a supply chain and logistics performance evaluation model based on supply chain management and logistics performance and performance evaluation with the help of a balanced scorecard, hierarchical analysis method, and fuzzy comprehensive evaluation method. The supply chain and logistics performance evaluation index system is then weighed and analyzed. The experimental object for investigating the evaluation effect of the constructed supply chain and logistics performance evaluation index system is Y Logistics Company. In the proposed supply chain and logistics performance evaluation index system, the weight of internal operation and customer dimension accounts for 61.2%. Y Express Company’s logistics performance evaluation from 2016 to 2020 shows a steady increase. The increase in customer dimension from 1.54 in 2016 to 9.47 in 2020 was the biggest increase among all indicators. Finally, Company Y performs better in the customer dimension, financial dimension, and internal operation, and its indicators of learning and development and social responsibility score lower. Company Y should increase its logistics digital learning and technological innovation and take the initiative to assume social responsibility.
Real-time tracking of the effect of jumping rope exercise using a wearable device
Authors: Liu Diyang , Zhang Qiang
Published: June 2024

With the development of science and technology, wearable devices, as an emerging field, have been gradually integrated into our daily lives and are widely used in the tracking of movement effects. In this paper, the data fusion algorithm combining complementary filtering and extended Kalman filtering and the human posture solving algorithm based on the D-H method is selected to solve the designed human jumping rope motion joint model, which realizes the construction of a wearable jumping rope motion capture system. Furthermore, the effect and commercial value of the wearable device designed in this paper for real-time tracking of jumping rope movement are tested by a single node posture test and a comparison experiment with posture solving. The experimental results show that the static test error and dynamic test accuracy of the sensor are 1.4° and 4°, respectively, which indicate that the sensor can accurately recognize the trajectory of jumping rope movements. The average values of RMSE for pitch angle, roll angle, and yaw angle were 0.37, 0.69, and 1.40, respectively. This indicates that the wearable device and the pose-solving algorithm used in this paper can meet the standard for commercial applications. This study provides a new approach to studying sports, which has rarely been done in the field of smart sports.
Meta-analysis of the Effect of Students’ Physical Activity Performance on Academic Achievement under Smart Physical Education Instruction
Authors: Ren Peng
Published: June 2024

With the continuous development and progress of society and the continuous improvement of educational concepts, the contradiction between physical exercise and the academic achievement of young people still always exists. In this paper, through the construction and identification of the association between smart sports and smart education in colleges and universities, we obtain the components of smart sports in colleges and universities and explore the intrinsic connection between physical exercise performance and academic achievement by analyzing the components of smart sports in colleges and universities. Literature quality was assessed by using an adapted quantitative research quality assessment tool and Meta-analysis method using Review Manager software to search six domestic and international databases to obtain a total of 3,128 documents, and 12 were finally included. The results showed that the percentage of high-quality research literature in this field was relatively low, and the 12 included high-quality literature contained a total of 3846 subjects, and the total effect size of physical activity on academic performance Z = 2.83 (SMD = 0.15, 95% CI = [0.05, 0.27]). The forest plot result shift to the right side highlights the positive impact of physical activity on academic achievement.
Feature extraction and classification of dance movements based on data mining
Authors: Sun Peng , Li Wei
Published: June 2024

In recent years, the expansive utilization of data mining techniques has revolutionized various fields, including the analysis of dance videos. This study leverages data mining to meticulously capture and analyze dance movements, thereby facilitating the enhancement and correction of dancers’ techniques. Within the scope of this research, images of dance movements extracted from videos are subjected to preprocessing, which involves grayscaling and thresholding, to prepare them for further analysis. Building on these processed images, this paper introduces a novel multi-feature dance action recognition approach. This method integrates several distinct features—directional gradient histogram features, optical flow directional histogram features, and audio features—employing a linear weighting scheme within a multi-core learning framework. The efficacy of the proposed approach is demonstrated through its performance on the FolkDance dance dataset, where it achieves a 3.5% increase in fusion accuracy over the traditional Dance Style Identification (DSI) method. Additionally, when compared with the Multi-Feature Learning-Combined (MFL-C) method, our approach shows an improvement of 0.6% in fusion accuracy. This research establishes a viable method for the recognition and classification of dance movements, laying a robust foundation for further inquiry and practical applications in this domain.
Contribution of 3D reconstruction techniques to the animated restoration of historical scenes
Authors: Wang Zhirun , Li Wenwen
Published: June 2024

Amid the escalating demand for heightened realism across diverse sectors such as film, television, gaming, tourism, virtual display, and the preservation of cultural heritage, there has been a notable advancement in reverse modeling technology that facilitates the extraction of three-dimensional models from image sequences. This study focuses on the classification of 3D reconstruction for the animation restoration of historical scenes. It delves into the technical pathways for the 3D reconstruction of such scenes, employing a clustering-based Scale Invariant Feature Transform (SIFT) feature-matching acceleration algorithm for the extraction and matching of image features. Subsequently, it integrates the Bundler method of camera self-calibration with the Patch-based Multi-view Stereo (PMVS) algorithm for dense reconstruction, culminating in the assembly and testing of the reconstructed historical scene. The acceleration time of the SIFT algorithm is higher than that of the standard algorithm when the number of images is 10. The standard algorithm’s acceleration time is the longest when there are more than 10 images. When the number of images is greater than 50, the acceleration ratio of sigma=60 is greater than that of sigma=120. This indicates that the clustering-based SIFT algorithm is suitable for accelerated matching of large-scale image sets. The acceleration effect can be improved by appropriately decreasing the value of sigma. The maximum difference between the five independent vectors in model 1 and model 2 is 3.18. After scaling model 2, the difference is narrowed to[ 0.01,0.03]. The small error of the model in scenes 3~9 and the clear graphic texture indicate that the 3D reconstruction model of the historical scene designed in this paper has high accuracy and provides a model reference for the animation restoration of the historical scene.
The impact path of uncertain economic policy on the high-quality development of technology-based innovative enterprises
Authors: Xu Jing
Published: June 2024

In recent years, macroeconomic policies have been characterized by significant uncertainty. This context of uncertainty has made it imperative to explore strategies that enterprises can adopt to pursue high-quality development. This paper specifically investigates the impact of economic policy uncertainty on science and technology enterprises. We categorize the productive activities of these enterprises into two types: technology-oriented and market-oriented. The paper further preprocesses the samples based on these categories. For analytical purposes, we employ the Cobb-Douglas production function to assess the level of enterprise development. A fixed-effects regression model is utilized, incorporating both control variables and mediating variables. Our baseline regression analysis reveals that the fintech coefficient for science and technology enterprises stands at 0.0721 without control variables and 0.0775 with them, demonstrating significance at the 1% level. These results suggest a positive correlation between economic policy uncertainty and the technology innovation activities of enterprises. Moreover, our findings indicate that economic uncertainty exerts a moderating effect on enterprise innovation. Specifically, the regression coefficients of economic uncertainty are −0.301, −4.687, and −3.154, while the industry characteristics regression coefficient is positive and significant at the 1% level. This pattern indicates that economic uncertainty significantly inhibits R&D investment in high-tech enterprises, adversely affecting their high-quality development.
Regression utility analysis of rural red cultural tourism industry chain for rural revitalization
Authors: Yu Lu
Published: June 2024

A large number of red cultural sites preserved in the Chinese countryside, as well as the red spirit are combined with cultural tourism, and the red cultural tourism industry comes into being. This paper takes the service personnel of the rural red cultural tourism industry in County M as the research object, designs the relevant questionnaire, conducts the reliability test, and then obtains the relevant data of rural revitalization and rural red cultural tourism industry chain through the questionnaire survey method. Then, using the industrial environment and policies of the rural red cultural tourism industry chain as the independent variables and rural revitalization as the dependent variable, a round-off multiple regression analysis was carried out to explore the interrelationship between the two. The results show that rural revitalization = 1.374+0.086*tourism projects + 0.147*infrastructure + 0.169*tourism market + 0.177*tourist distribution = 1.074+0.246*history and culture + 0.259*red culture + 0.214*government policies + 0.268*funding inputs. This paper assists Chinese villages in improving the red cultural tourism industry chain and promoting rural revitalization by developing the red cultural tourism industry chain.
Research on the application of deep learning-based machine vision in automated inspection
Authors: Zhao Ranran
Published: June 2024

The continuous updating of deep learning algorithms and theories has laid a solid foundation for the development of the machine vision field. Automated detection technology has become a hot topic of research in the field of machine vision in recent years. In this paper, we first introduce the traditional one-dimensional and two-dimensional image segmentation algorithm and then optimize the image segmentation algorithm by combining the conventional pigeon flocking algorithm and chaotic search algorithm so as to obtain a more accurate detection target image. Then, on the basis of a deep learning network, an attention mechanism is introduced to construct a Swin-Transformer image detection model to realize automatic detection of machine vision. Finally, the performance of the model is tested, and it is applied to watermelon seedling quality detection to explore its application value. The results show that in the performance test experiment of the image segmentation algorithm of this paper, the three indexes of F1, IoU, and accuracy of the image segmentation algorithm designed in this paper on the ISIC-2020 dataset are 93.90%, 93.74%, and 98.37%, which are ranked the first among the algorithms participating in the experiment. The precision, recall, and mAP values of the image detection model designed in this paper are 92.87%, 77.13%, and 83.21% on the experimental data test set, which are higher than those of other models participating in the experiment. The image detection model designed in this paper was practically applied to watermelon seedling quality detection. The accuracy of the model in detecting the presence or absence of diseased spots and cotyledon area, two key characteristic parameters of seedling quality, reached 100%. The model showed high reliability in practical application. The image segmentation algorithm and image detection model developed in this paper are highly useful in automated detection.
Policy Perspectives on Big Data and AI in Translation Services
Authors: Yu Hui
Published: June 2024

With the rapid advancement of scientific and technological innovation, the significance of intelligent translation services has grown considerably. This study leverages policy support to integrate AI technology into the domain of grammar error detection and correction. It utilizes a Long Short-Term Memory (LSTM) neural network and employs a Transformer model grounded in a self-attention mechanism to address the task of grammar error correction. This approach is designed to balance local contextual nuances and long-range dependencies within the text, culminating in the development of an AI-based grammar error correction model. A thorough evaluation of this model’s performance involved comparative analysis with alternative models, assessments across various types of syntactic errors, and detection of collocation errors. The findings indicate that our model exhibits superior grammatical error correction capabilities, outperforming comparative models. Specifically, it achieves Grammar Learning Evaluation Understudy (GLEU) scores that are 2.31% to 7.95% higher than those of its counterparts. Moreover, it demonstrates overall recognition rates for different grammatical and collocational errors between 18.88% to 58.98% and 50% to 70%, respectively, which underscore its practical applicability. This methodology not only enhances grammatical error detection but also holds promise for broader application in AI-driven translation services.
Application and effect analysis of virtual reality technology in innovation and entrepreneurship education
Authors: Dai Keqiang , Jiao Huijie , Wang Huilin , He Liangchun
Published: June 2024

Adding virtual reality technology to innovation and entrepreneurship education in colleges and universities can help stimulate students’ learning interest and enhance their practical operation ability, thus improving the quality and effect of innovation and entrepreneurship education. In this paper, after exploring the demand for the application of virtual reality technology in innovation and entrepreneurship education, combined with the interactive environment of virtual reality technology, we constructed the innovation and entrepreneurship teaching mode based on VR. We used this teaching mode as the basis for the design of teaching cases in M school. During the implementation of teaching practice, relevant data are collected by distributing questionnaires. Then, the experimental data are analyzed by combining independent sample T-test, regression analysis, and other statistical methods to explore the application effect. The results demonstrate that there is a statistically significant difference between before and after the application of virtual reality technology (P<0.05), which can significantly improve students’ innovation and entrepreneurship. The perceived usefulness (0.69) and cognitive development (0.09) of virtual reality technology applications were the highest and lowest scores. In addition, financial support for innovation and entrepreneurship programs (0.131) had the greatest degree of influence on VR-based innovation and entrepreneurship education. This study is intended to contribute to the construction of innovation and entrepreneurship education for college students in colleges and universities.