bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of System Quality and Self-Efficacy in E-Learning Users: Exploring the Determinants of Academic Achievement
Authors: Widyaningrum Tutut , Sholihah Qomariyatus , Haryono Bambang Santoso
Published: June 2024

An e-learning conceptual model is a framework for evaluating the quality of learning systems and outcomes. The results of the BAN-PT assessment show that the values for academic and non-academic achievement indicators are still low, this indicates that there are challenges that need to be overcome in implementing e-learning. This study aims to analyze the role of system quality and self-efficacy on e-learning use and user satisfaction that affect academic performance by developing the D&M IS Success Model. The study was an explanatory quantitative survey design model with 40 structured questionnaire items sent online. 66 respondents were sampled, taken using purposive sampling method with the Taro Yamane formula at a significance level of 10% of the population of undergraduate psychology students of 197 students. PLS-SEM method was used in analyzing the connection of exogenous and endogenous variables simultaneously. The research findings show that the overall q square value of the contribution of exogenous variables to academic performance through use and user satisfaction is 95.4% and exogenous variables affect academic performance by 75%. Self-efficacy has a positive and significant effect on use and user satisfaction with t-statistic values of 3.761; 2.422 and p-values of 0.000; 0.016, respectively. User satisfaction has a positive effect on academic performance with a path coefficient value of 0.588. E-learning evaluation allows measuring the success of implementing e-learning in achieving increased academic achievement.
Teaching Style, Digital Literacy, and Self-Efficacy on Early Childhood Education Teacher Capabilities
Authors: Sya’dullah Achmad , Setyosari Punaji , Ulfa Saida , Praherdhiono Henry , Saroinsong Wulan Patria
Published: June 2024

Problems experienced by PAUD teachers during online learning are viewed from educational background, length of teaching and self-efficacy. The purpose of the study was to analyze the relationship between digital literacy (LD), teaching style (GM) and self-efficacy (ED) on the capabilities of PAUD teachers (KG) during the Covid 19 pandemic. This research is quantitative using the expost facto model to determine the causal relationship between events and conditions. The sample used proportional stratified random sampling of 355 teacher respondents with more than three years of teaching experience and a diverse educational background. The instrument used was a questionnaire with descriptive statistical analysis techniques and Structural Equation Modelling (SEM). We collected data through digital literacy questionnaire, teaching style scale, self-efficacy instrument and ECD teachers' capabilities. The study found that: 1) there is a relationship between LD and GM; 2) there is no relationship between LD and ECD KG; 3) there is a relationship between LD and ECD teachers' ED; 4) there is a relationship between GM and teachers' ED; 5) there is a relationship between GM and KG; 6) there is a relationship between ED and KG; 7) there is a relationship between LD and KG through ED; 8) there is no relationship between GM and KG through ED.
Pelatihan Penggunaan Microsoft Excel untuk Meningkatkan Keterampilan, Memperluas Kemampuan dan Pengetahuan Siswa kelas 7 SMPN 2 Depok
Authors: Gau Mark Dionisius Alvin Putra , Simanungkalit Jesica Febiola , Surbakti Fenia Karenina , Samura Fransiska Artha Apriani , Rahayu Flourensia Sapty
Published: June 2024

Dengan perkembangan zaman, penggunaan teknologi semakin penting. Microsoft Excel merupakan salah satu implementasi teknologi yang dapat memberikan manfaat dalam kehidupan sehari-hari maupun di masa depan. Untuk meningkatkan keterampilan, memperluas kemampuan, dan pengetahuan siswa SMPN 2 Depok dalam menggunakan Microsoft Excel, dilakukanlah pelatihan. Pelatihan dilaksanakan melalui metode pengajaran tatap muka dan pemberian studi kasus untuk membantu siswa memahami lebih dalam tentang Microsoft Excel. Hasil dari pelatihan ini menunjukkan bahwa para siswa telah mengalami peningkatan pemahaman dalam penggunaan Microsoft Excel, seperti dalam pengolahan data. Peningkatan ini diharapkan dapat memberikan kontribusi positif bagi kehidupan sehari-hari siswa di masa depan.
Implementasi Pembelajaran Etika Berinternet Menggunakan Media Pembelajaran Kreatif di SMP Pangudi Luhur St. Vincentius Sedayu
Authors: Johanes Valentina Graciella , Tirajoh Mona , Damanik Dhea Rosenta Adveranda , Dew Maria Matilda , Pritalia Generosa Lukhayu
Published: June 2024

Perkembangan teknologi dan penggunaan internet yang semakin meluas, terutama di kalangan generasi Z, menimbulkan kebutuhan akan pemahaman yang lebih mendalam tentang etika berinternet. Kegiatan ini bertujuan untuk mengimplementasikan pembelajaran etika berinternet melalui media pembelajaran kreatif di SMP Pangudi Luhur St. Vincentius Sedayu. Dengan melibatkan 63 siswa kelas 8, kegiatan ini dilaksanakan selama dua hari dengan fokus pada pengenalan konsep etika berinternet dan penggunaan media pembelajaran Canva untuk membuat poster yang mengilustrasikan konsep tersebut. Evaluasi tahap awal dan tahap akhir dilakukan untuk mengukur efektivitas pembelajaran. Hasilnya menunjukkan antusiasme siswa terhadap materi dan peningkatan pemahaman tentang pentingnya perilaku yang baik saat menggunakan internet. Kegiatan ini diharapkan dapat menjadi dasar untuk pengembangan lebih lanjut dalam pendidikan etika berinternet di sekolah.
Optimalisasi Teknologi Informasi untuk Peningkatan Penjualan dan Daya Saing pada UMKM Alkabes
Authors: Valensia Elsa Kurnia  , Evelyn Michelle Aurelia  , Ni Gusti Putu Saniskalita Desniari  , Stephanie Caroline Cen  , Nastiti Putri
Published: June 2024

Usaha Mikro, Kecil, dan Menengah (UMKM) memiliki peran penting dalam mengembangkan perekonomian Indonesia. Salah satu faktor utama yang memengaruhi daya saing UMKM adalah kemampuan untuk memanfaatkan teknologi informasi. Pengabdian ini bertujuan untuk meningkatkan daya saing dan penjualan Warung Makan Alkabes melalui pemanfaatan teknologi informasi, termasuk e-commerce ShopeeFood, Google Business Profile, dan media sosial Instagram. Metode yang digunakan adalah pelatihan secara offline selama 2 hari dengan materi mengenai pengelolaan Google Business Profile, pendaftaran UMKM di e-commerce, strategi promosi menggunakan media sosial Instagram, dan pembuatan konten promosi menggunakan aplikasi Canva. Implementasi dari pengabdian menunjukkan bahwa optimalisasi teknologi informasi pada Warung Makan Alkabes membawa keuntungan dan dampak yang signifikan dalam meningkatkan penjualan dan daya saing. Mitra usaha mendapatkan pemahaman mengenai teknologi dan mampu menerapkannya pada usaha Warung Makan Alkabes.
A multidimensional EEG feature extraction attention detection for BCI System
Authors: Zhang Ran , Shen Chengyuan , Sui Linfeng , Cao Jianting
Published: June 2024

Brain-computer interface (BCI) systems are highly valued for their applications in medicine and biology, where accurate analysis of attention levels and electroencephalography (EEG) data is crucial for the success rate of BCI systems. To improve this aspect, we propose to perform attention level determination prior to the execution of the BCI system. To accurately determine the level of attention, we propose a novel feature extraction approach that involves multidimensional feature extraction across multiple frequency bands of EEG data. The multi frequency band waveforms extracted using this method can be cross validated, thereby increasing the robustness of our research. We used publicly available datasets to train a Support Vector Machine (SVM) classifier to develop an efficient attention detection system, and developed a system for collecting EEG data to validate attention levels. The effectiveness and accuracy of the multidimensional feature extraction method was validated by classifying the data collected by the attention detection system. This study highlights the potential of integrating attention detection into BCI systems, pathways for advances in brain science research.
Research on the Importance of Cybersecurity Education on the Cultivation of Healthy Social Mindset of College Students
Authors: Hu Qinting
Published: June 2024

This paper first discusses the basic functions and basic ways of network security education, then explores the basic characteristics of students’ social mentality, analyzes the main influencing factors of college students’ healthy social mentality, and the influence of network security education on college students’ social mentality, and based on this, proposes an innovative path of network security parenting. Then, the students’ network security literacy and healthy social mentality were analyzed for differences, and the influence of network security education on their critical thinking ability was studied using ANOVA. The use of heterogeneity analysis was used to investigate changes in students’ healthy social mindset at both high and low levels of cybersecurity education. The results showed that the effect of cybersecurity education on students’ total critical thinking ability was significant at the 1% level, F=3.219, η2=0.013. Students’ healthy social mindset was affected by both high and low cybersecurity education levels, with substantial coefficients of 0.00189 and 0.00152, respectively. The present study systematically examines the mechanism of the influence of cybersecurity education on college students’ social mindset and the path of influence, which helps to enrich the research paradigm on college students’ social mentality.
Analysis of the Importance of Ceramic English to the Communication of Ceramic Culture to Foreign Countries
Authors: Li Xiang
Published: June 2024

With the continuous improvement of China’s international status, the status of Chinese culture in global communication is also gradually apparent; ceramic culture as an important component of Chinese traditional culture in the foreign exchange and dissemination of value can not be ignored. The purpose of this study is to evaluate the status and impact of ceramic English on the external communication of ceramic culture. First, we analyze the characteristics and importance of ceramic English. Then, we construct a mechanism model for ceramic English and ceramic culture communication by combining the relationship between ceramic English and ceramic culture communication. Then, through the analysis of the communication path of ceramic culture, we explore the development direction in the communication of ceramic culture in foreign exchange, construct the audience model of ceramic culture based on cognitive behavior, and quantify the importance of ceramic English to the communication of ceramic culture in foreign exchange by combining with the statistical analysis method. The investigation and analysis have revealed that the comprehensive scores of the five samples are above 4 points, and the ceramic products are all at an excellent level. The effectiveness of ceramic English and the perfection of ceramic English have the highest standard coefficients of 0.224 and 0.231, respectively, and the p-value is 0.001. In the external communication of ceramic culture, the effectiveness and perfection of ceramic English have the greatest influence, and ceramic English has a pivotal position in the external communication of ceramic culture, which also proves that improving the development of the ceramic English level can effectively promote the development of ceramic culture. It also proves that improving the development of ceramic English can effectively promote the level of foreign exchange and dissemination of ceramic culture.
Multimodal Analysis and Optimisation Strategy of Teaching Behaviour in Physical Education Classroom
Authors: Liu Guannan
Published: June 2024

In the context of the new curriculum, physical education has become an important part of school teaching. In this paper, the edge extraction algorithm and TV-L1 optical flow method are utilized to extract key image features in physical education classroom teaching, and the improved TE network structure extracts the skeletal data features of teachers and students in the classroom based on the TEMS module. Then, the MTHA-MDCNN deep migration model is established to fuse the three features to identify multimodal teaching behaviors in the sports classroom. Experiments show that the accuracy of this paper’s method for recognizing teaching behaviors in physical education classrooms can reach 77.63%. In the actual behavior recognition, the average values of teachers’ and students’ behavioral coverage are 32.68% and 67.77% respectively, which is in line with the optimal division of teaching time in physical education classrooms. In contrast, the students’ behavioral coverage of physical practice is low, which is not conducive to their physical and mental health development. The construction of teachers and supervision of teaching should be strengthened in schools, and students’ learning paths should be expanded. The multimodal analysis method of teaching behavior in this paper provides a reference method for targeted improvement of physical education teaching, and the proposed optimization strategy is important for the successful optimization of physical education classroom teaching in schools in the future.
Implementation and Effectiveness Evaluation of Library Virtual Reference Service
Authors: Wang Liping
Published: June 2024

This study aims to elucidate the relationship between user demand and library virtual reference services, as well as to explore the development of such services across fifteen colleges and universities in China. Leveraging user research data, we established goals for virtual reference services. We introduced the VCRA-CP (Virtual Consultation Resource Allocation-Customer Profile) model for resource scheduling to better align with user needs. User clustering techniques were utilized to categorize users, and a hybrid push information service combining clustering service and collaborative filtering was adopted. This approach was further enhanced by integrating a “user-service evaluation model” to score and deliver services. The operational dynamics of the virtual reference consultation service were meticulously analyzed, particularly focusing on the real-time consulting function module. We proposed evaluating the effectiveness of virtual reference services based on three dimensions: consulting system performance, service impact, and information control. The evaluation metrics included average acceptance value, average perceived value, and average expected value from users. A critical finding concerning the “timeliness and accuracy of responses in virtual reference consultations” revealed a discrepancy, with the average perceived value minus the average acceptance value equaling −0.15, indicating a significant area for improvement in response timeliness and accuracy. User satisfaction was quantified at 65.86%, with a dissatisfaction rate of 6.93%. Although the overall satisfaction with the virtual reference consulting service was high, there remains a need to enhance the standardization of these services to better meet user expectations.
Research on the Integration Strategy of Student Management and Curriculum Education in Colleges and Universities Based on the Integration Model
Authors: Wang Xiaoxia , Xia Fan
Published: June 2024

Improving the efficiency of curriculum education and student management according to the changing characteristics of the social environment is of great significance to the construction of a perfect social and cultural system. This paper constructs a fusion model of student management and curriculum education, taking into account the weaknesses and outstanding problems in both areas. In order to accurately control the behavior of university students, a student behavior prediction method based on the fusion model is proposed, which first uses the k-means clustering method to cluster the daily activity frequency sequences of all users and then realizes the prediction of the individual mobility of students through the LSTM model based on the historical records, and extracts the collective location preference of each user cluster. The effectiveness of the proposed fusion model is assessed using BJ University Daxing Campus as a case study. The results show that after applying the model proposed in this paper, students’ perceptual, language expression, language comprehension, cognitive, social, emotional, and behavioral abilities are improved by 0.941~1.256 points compared with those before the application of the model, with a significant difference of P<0.01, which verifies that the fusion model has strong feasibility. It has positive significance for the work of student management and curriculum education. Research has a positive significance.
Research on the Application of Intelligent Sports Tracking System in Improving the Teaching Effect of University Physical Education
Authors: Yan Xinting , Luo Zhongjian , Wu Li
Published: June 2024

The enhancement of physical education’s stature necessitates imminent reforms in university physical education models. This study examines the deployment of an intelligent motion-tracking system within physical education, exploring facets such as the precise capture and real-time analysis of movement postures, movement evaluation, and optimization, as well as movement recording and tracking. It further investigates the system’s accuracy and convenience, assessing its impact on enhancing university physical education pedagogy. Our methodology involved constructing a framework for the intelligent motion tracking system, followed by developing a motion model. The design of the intelligent tracking model proceeded through initialization, sampling and prediction, observation, and resampling phases, concluding with the implementation of a complete human body tracking motion algorithm utilizing the VHMT algorithm. Our analysis revealed optimized posture and morphology of the upper arm and forearm during exercise, indicative of enhanced physical education teaching at the university level. Prior to implementation, in the volleyball class scenario, no significant difference was observed between the experimental and control groups in terms of motor skills, with a difference ranging from 1.82 to 4.4 (P>0.05). Post-implementation, however, the motor skill level of the experimental group in each class significantly surpassed that of the control group (P<0.05), with improvements ranging from 6.8% to 43.4%. The integration of an intelligent motion-tracking system in university physical education substantially fosters students’ motor skill acquisition and invigorates their enthusiasm for learning.
Automatic Identification and Tracking Method of Case-Related Vehicles Based on Computer Vision Algorithm
Authors: Wei Dan , Chen Bin , Lin Yujie
Published: June 2024

Amidst the rapid advancement of artificial intelligence, computer vision algorithms have found extensive applications across various societal sectors. This paper presents the development of an automatic vehicle identification algorithm for crime-related scenarios, leveraging enhancements in computer vision technology. Initially, we refine the multi-scale feature fusion within the YOLOv4 architecture, subsequently substituting the standard convolution in the feature extraction network with depth-separable convolution to minimize parameter computation. Furthermore, we replace the conventional CIOU target localization loss function with EIOU to expedite model convergence. To address the issue of target vehicle detection failures, we incorporate the Kalman filter algorithm, ensuring precise tracking. Our experimental analysis, which utilizes both target detection and multi-target tracking evaluation indices, demonstrates that the modified YOLOv4 algorithm excels in recall, precision, and average IOU metrics compared to other algorithms, with a mean Average Precision (mAP) of 95.68% and an average detection speed of 0.039 seconds per image, satisfying real-time operational criteria. Vehicle tracking efficacy, compared using the YOLOv4-based detector before and after the modifications, shows significant improvements, indicated by a reduction in Identification Switches (IDS) across all video samples. This study introduces a robust method for the accurate identification and localization of vehicles involved in criminal activities, significantly enhancing case resolution efficiency.
A dynamic planning method for satellite imaging mission based on improved genetic algorithm
Authors: Zhao Demin , Xiong Wei , Wang Yiran
Published: June 2024

The ongoing enhancement of imaging satellite platforms in terms of payload capacity, coupled with the proliferation of imaging satellites, introduces new complexities to the mission planning processes. These enhancements enable broader applications and significantly increase the societal benefits derived from imaging satellites. To address these challenges, a specific kinematic model for dynamic imaging attitudes is constructed, taking into account the dynamics of satellite imaging missions. This model uses information from satellite imaging observation tasks to design constraints that govern the planning of imaging tasks. Additionally, an optimization objective function is established to ensure compliance with these planning constraints. Building on the encoding method for relative imaging moments, an adaptive genetic algorithm tailored for satellite imaging task planning is introduced. This algorithm enhances the iterative efficiency of decision variables involved in satellite imaging tasks. Empirical validation through comparative simulation experiments, using a typical satellite imaging mission as a case study, demonstrates the effectiveness of the adaptive genetic algorithm. In various phases of imaging mission planning, the algorithm achieved a 100% task completion rate. The index function gain was enhanced by 21.47%, and the maximum synthetic angular velocity of attitude maneuvers between different targets peaked at the satellite’s maneuvering threshold of 7 degrees per second. By leveraging adaptive genetic algorithms, satellite imaging mission planning can optimize mission completion rates and effectively utilize the satellite’s maximum attitude maneuver capabilities.
The Impact of Artificial Intelligence and Consumer Behavior Interaction on Corporate Brand Management and Marketing Strategies
Authors: Luo Lei
Published: June 2024

The behavioral interaction between artificial intelligence and consumers can bring consumers multifaceted experiences, which are of great value for enterprises to improve brand management and adjust and optimize market strategies. In this paper, we construct a gray multiple linear regression model by combining the classical multiple linear regression model and gray system theory. Taking consumers as the research object, we design a questionnaire and carry out the reliability test to obtain the data related to the experience brought by behavioral interaction with consumers and the brand management and marketing strategy of enterprises. Finally, this paper takes AI and consumer behavioral interaction as the independent variable and corporate brand management and marketing strategy as the dependent variable. It carries out regression analysis to explore the influence of the independent variable on the dependent variable. The results show that: corporate brand management = 1.879 + 0.317*sensory experience + 0.283*emotional experience + 0.168*thinking experience + 0.221*personalized experience − 0.187*privacy concerns, and corporate market strategy = 1.943 + 0.285*sensory experience + 0.266*emotional experience + 0.191*thinking experience + 0.307*personalized Experience + 0.144*Privacy Concerns. The research results of this paper are of strategic significance to help enterprises understand the significance of the interaction between AI and consumer behavior, use AI to understand consumer groups, maintain good brand management, and adjust market strategies in a timely manner.
Workers and Safety Helmets Detection in Day and Night Scenes based on improved YOLOv5
Authors: Ma Guofeng , Jing Yiqin
Published: June 2024

Safety helmets, as crucial protective equipment, significantly contribute to the head safety of workers. Adherence to safety helmet regulations is integral to construction site safety management. Recognizing the limitations inherent in manual supervision methods, we have developed a vision-based framework for the detection of workers and their safety helmets. This framework features enhancements to the YOLOv5s model, resulting in the advanced YOLOv5-Pro. The enhanced YOLOv5-Pro model achieved a mean Average Precision (mAP) of 95.4% on the validation set, marking an improvement of 3.6% over the original model. Furthermore, we expanded the utility of the YOLOv5-Pro model by incorporating nighttime data augmentation. The augmented YOLOv5-Pro model demonstrated robust performance in both daytime and nighttime conditions, as evidenced by our experimental results.
Experimentation and analysis of network anti-mapping security access techniques for illegal scanning
Authors: Li Rui , Liu Zehui , Guo Min , Gao Wei , Liu Hengwang
Published: June 2024

With the rapid development of network technology, the increasing scale of the network, and the more complex network structure, network anti-mapping puts forward higher requirements. In this paper, based on the game theory of the network anti-mapping strategy selection method, the network mapping attack is divided into the reconnaissance stage and the mapping stage. According to the opacity of the information of both attackers and defenders, the attacker collects the defender’s information in the reconnaissance stage and introduces the signal game to construct the reconnaissance game model. The attacker and defender in the two-stage game utilize Bayesian equilibrium to solve the problem and select the strategy that maximizes their utility based on the assumed conditions. The results show that for the attack of illegal scanning, the CFE statistics of the attack data increase from 1.5~1.9. The game theory-based network anti-surveillance security access technology can effectively identify subnet and multi-IP devices and, at the same time, reduce the network load, and the network topology nodes can be up to 2134 degrees of freedom, which effectively improves the efficiency of network anti-surveillance.
Research on Quality Evaluation of Smart Education Schools Based on Fuzzy Clustering Algorithm and Strategies for Future Development
Authors: Lou Yingying
Published: June 2024

The burgeoning field of wisdom education has led to a disparity in the quality of educational institutions, thereby necessitating enhancements to the existing school quality evaluation systems. This study refines the traditional fuzzy C-mean clustering algorithm by incorporating a Gaussian mixture distribution and information entropy regularization. It then employs this enhanced algorithm to construct a quality evaluation system for smart education schools. The improved fuzzy C-mean clustering algorithm demonstrated in this paper significantly outperforms the standard C-means used at SCU and the K-means algorithm in terms of Mean Absolute Error (MAE) and Total Hit Rate (THR). Specifically, the optimized algorithm decreased the MAE to 0.572 from 0.619, a reduction of 16.01% compared to the K-means algorithm. It increased the THR to 0.158 from 0.147, marking an improvement of 17.04% over the Kmeans algorithm. Furthermore, the refined clustering algorithm achieved an impressive accuracy of 95.71%. Analysis through this clustering approach reveals that the developed quality evaluation system accurately reflects the operational level of smart education within schools. The establishment of such a system is anticipated to significantly guide the future progression of smart education and aid in the foundational development of smart education schools.
Innovative Application of Data Mining Technology in College Information System Based on Informatized Teaching Environment
Authors: Chen Liguan
Published: June 2024

With the rapid development of information technology, the development of information technology has become the main focus of national development, and the informationization of education in colleges and universities has also been mentioned as a strategic height, and various fields such as student management and teaching methods are also being continuously intelligentized and informative. In this paper, we obtain relevant data from the information systems of colleges and universities and use the K-Means clustering algorithm based on information entropy and density optimization to cluster and analyze educational data. The optimal clustering coefficient is used to determine major school behavioral characteristics, such as students’ academic performance, consumption amount, access control records, and so forth. It can be analyzed. Are respectively used as the clustering dimensions of K-Means, and the information entropy is used to determine the attribute weight values to classify these dimensions, and to find out the common prominent characteristics in their same class. Then analyze the laws of student behavior and cluster them into categories. The academic early warning model evaluation index is used to verify the model’s accuracy. Among them, the academic early warning model proposed in this paper has an accuracy rate of 95.2%, while the precision rate and recall rate at different warning levels reach more than 90%. The validity of the model has been verified. The study shows that the introduction of educational data mining technology can solve the pain points for modeling and analyzing diverse data and accurately predict student behavior.
A Study of the Challenges of Digital Currencies to the Traditional Financial System and Their Implications for Economic Policy
Authors: Shi Yue
Published: June 2024

Digital currencies, as an emerging monetary form, have profoundly transformed the landscape of financial transactions and redefined the structure of economic ecosystems, exerting an unprecedented influence on traditional financial systems. This study scrutinizes the ramifications of digital currencies on conventional financial systems, utilizing a theoretical framework as the foundation. It specifically employs Vector Autoregression (VAR) and Dynamic Stochastic General Equilibrium (DSGE) models to construct an impact model that examines the influence of digital currencies on monetary policies. The analysis utilizes empirical data to assess the efficacy of digital currencies in shaping economic policy, focusing particularly on their effect on monetary intermediation targets. The findings reveal that digital currencies significantly affect monetary policy, primarily through mechanisms of interest rate and exchange rate transmission. Moreover, the advent of digital currencies is associated with reductions in the money supply, exchange rates, and credit volumes of commercial banks. The analysis establishes a long-term stable equilibrium among the money supply, digital currency volume, cash leakage rate, fixed-to-floating rate ratio, and excess reserve ratio. Notably, the scale of digital currency exerts the most substantial impact on the money supply, contributing 10.89% to its variance. This study underscores the intricate relationships between digital currencies and economic policies, highlighting their critical role in contemporary financial systems.
Research on the design and application of wind turbine mechanical parts based on parametric modeling
Authors: Bi Yadong
Published: June 2024

Based on ANSYS finite element analysis software, a parametric modeling interface for wind turbine blades and pitch bearings is developed using parametric design language. The parametric modeling interface is used to quickly establish a simplified finite element model of the blade and pitch bearing so as to optimize the design of the blade structure, calculate the maximum tensile stress of the bearing and bolt connection, and analyze the relationship between the working stress of the bearing and bolt and the bolt preload. The analysis and calculation results guide the safety and reliability of wind turbine parts design. After analysis, the optimization of blade structure is mainly in the region of leaf root enhancement, the number of layers laid in the cross-section of No. 1-3 has no major modification, the bi-directional cloth in the cross-section of No. 3-6 is increased by 55 layers, 5 layers reduce the cross-section of No. 7-8, and the cross-section of No. 16-23, 1 layer of the bi-directional cloth is increased in order to improve the strength of the tip of the blade and the resistance to bending capacity. The preload force applied to the pitch bearing during the actual installation process is generally 50% to 70% of the yield limit of the bolt material. The pitch bearings have the best load-carrying capacity under ultimate loads, with the ditch curvature radius coefficient and clearance generally around 0.530 and −0.12mm.
Strategies for Integrating Historic District Preservation and Modern Functions in Urban Renewal
Authors: Bian Hongxu , Shi Yuefeng
Published: June 2024

Through the corresponding investigation and analysis, this paper derives the evaluation indexes of the coupling degree of coordination between the protection of historical neighborhoods and tourism development, establishes the weight of each index through the entropy method, conducts the mathematical and statistical analysis of the data, and applies them to the coupling relationship between the protection of historical neighborhoods and the development of modern functions, and constructs the coupling degree of coordination evaluation model to evaluate the relationship between the two. The results show that the commercial/residential interface ratios of Sanfangqixiang, Langzhong, and Zhouzhuang in the sample historic districts are 0.67, 0.88, and 049. In the type structure of the sample districts’ businesses, retail businesses account for 50% or less, catering businesses account for 36%-57%, and specialty businesses account for less at present. Langzhong and Nanluoguxiang have the best coupled and coordinated development of historic district protection and tourism development, with coupled coordination degrees of 1.968 and 1.956, respectively. Therefore, this paper uses the coupled coordination evaluation model to explore the coordinated development of historic district protection and modern functions and to continuously adjust and optimize the integration strategy for sustainable development.
Interventions and Reflections on Digital Music Technology in Vocal Performance
Authors: Hu Hong , Yang Jichao
Published: June 2024

With the continuous development of the digital era, digital technology is more and more closely combined with various fields, and the integration and development of digital music technology in vocal performance has also received wider attention. This study analyzes the hierarchical relationship of digital music in depth, explores the effect relationship of digital music technology in combination with vocal recording collection, and further studies the interaction effect of intervening digital music technology in vocal performance from the perspective of interaction relationship. In the actual vocal performance, the peaks of the left and right channels of the music signals of the intervening digital music technology were around ±0.30 and 0.10, respectively, and the volume of the left channel was larger than that of the right channel. In all aspects, the effect of vocal performance on music acquisition is better with digital music technology. Meanwhile, the highest ratio of audience silence in the interactive impact of vocal performance intervening digital music technology was reduced by 10% compared with the traditional vocal performance, which proved that the vocal performance based on digital music technology has a better interactive effect and provided a solid and reliable basis for the development of the integration of digital music technology and vocal performance.
Research and Practice on Digital Transformation of Higher Vocational Intelligent Manufacturing Professional Group under the Background of Industrial Internet
Authors: Wang Hong , Jiang Zhizhen
Published: June 2024

The swift advancement of digital technology introduces both challenges and opportunities for the education and training of students in intelligent manufacturing programs at higher vocational colleges. This study proposes a digital course model contextualized within the framework of the industrial Internet. To enhance the utilization of digital teaching resources and elevate the quality of these resources, a personalized approach to acquiring teaching resources is developed. Additionally, this paper refines the collaborative filtering recommendation algorithm by integrating similarity metrics and K-means clustering techniques, thereby augmenting the efficiency of learning resource recommendations for professional groups in intelligent manufacturing. And further practice to explore the effects of its digital transformation. Significance at the 0.01 level is shown between the teacher’s concept of teaching and the application of teaching equipment, teaching preparation, learning attitude, learning response, equipment use, teaching resources, and the application effect of digital teaching resources. Digital Transformation Effect = −0.215+0.134*Teacher Concept of Instruction + 0.174*Instructional Equipment Application + 0.134*Instructional Preparation + 0.154*Learning Attitude + 0.14*Learning Response + 0.071*Equipment Usage + 0.045*Instructional Resources. As a result of this study, the construction of a teaching resource platform should be focused on, and the classification, organization, and sequencing of resources should be strengthened.
Innovative Application of Color Pottery Patterns in Modern Clothing Design Based on Three-Dimensional Image Processing Technology
Authors: Pan Zaoxia
Published: June 2024

Nowadays, the convergence of global clothing culture is becoming more and more significant, and “Chinese style” clothing, which integrates traditional Chinese cultural elements into clothing design, is being sought after by more and more contemporary consumers. This paper proposes research on modern clothing design that incorporates pottery patterns supported by three-dimensional image processing technology. After using three-dimensional measurement technology to obtain pottery image data, the extracted three-dimensional image is smoothed, segmented, and binarized to complete the extraction of pottery patterns. The extracted pottery pattern features are then automatically reorganized using shape grammar, so that the pattern features can be better integrated into modern clothing design, and a case study is conducted on the clothing design that incorporates pottery pattern features. The data show that the indexes of pottery pattern extraction based on 3D image processing are Recall=95.23%, Precision=91.64%, Jaccard index=94.12%, F-measure=93.36%, and the performance of pottery pattern extraction can satisfy the standard of modern clothing design. In the pattern characteristics and “individualized - mass” clothing design, the prominent design method is the uniform and different shapes and sizes of the full-body pattern combination (0.947). The application of colored pottery patterns to clothing in this study not only meets people’s demands but also has significant significance for the preservation of traditional Chinese culture.
Design and Optimization Analysis of Mechanical Hydraulic System Based on ANSYS Workbench
Authors: Zhang Yiyue
Published: June 2024

The piping system in the mechanical hydraulic system occupies a large proportion, and the working environment of the whole piping system is relatively complex. This paper is based on the digital model of the mechanical hydraulic system and the optimization of the piping system in the mechanical, hydraulic system. Through the Newton method, we establish a mechanical, hydraulic piping model by studying the two ends of the solid support of a simple straight single pipe so as to optimize the mechanical, hydraulic piping system. Using ANSYS Workbench software, the optimized fluid and solid states are solved using the fluid-solid coupling method to analyze the fluid-solid coupling modes of the pipeline. In the first four orders of the pipeline system, the intrinsic frequency decreases with the increase of the flow velocity, and the inherent frequency tends to 0. As the axial force increases, the first four orders of the intrinsic frequency increase slowly. As fluid pressure increases, there is a small decrease in the inherent frequency of the first four orders. The simulation results are compared with experimental data, and the relative errors of the simulation results obtained by the fluid-solid coupling method do not exceed 2% under typical pressure conditions. The simulation calculation results are virtually identical to the test data, indicating that the simulation results are genuine and reliable.
Artificial Intelligence Technology Boosts the Construction of Intelligent Translation Teaching Mode of English in Colleges and Universities
Authors: Xu Qilu
Published: June 2024

The integration of artificial intelligence (AI) across various domains marks a significant trend in contemporary development, with its application in English translation teaching in higher education emerging as a focal area of research. In response to the evolving needs of English translation instruction, this study advocates for a novel AI-supported teaching method leveraging a translation system. We incorporate a multi-hop attention mechanism within a Long Short-Term Memory (LSTM) network to develop an intelligent neural network machine translation model. This model is enhanced with a meta-learning recommendation algorithm, which delivers personalized translation learning materials to students, facilitating an intelligent teaching paradigm. The efficacy of this innovative teaching method was empirically tested by assessing its translation performance prior to classroom implementation. The evaluation involved comparative tests on English-to-Chinese and Chinese-to-English translation. The results reveal that students taught under this AI-enhanced model scored mean values of 27.68 and 37.42 in these respective tests, exhibiting statistically significant improvements over those taught via traditional methods (P<0.05). The findings suggest that the intelligent translation teaching system proposed in this study holds promising potential for redefining English translation teaching frameworks in universities, indicating a substantial stride toward the integration of AI in educational methodologies.
3D animation stereo space design based on digital visual communication technology
Authors: Bao Wenjun
Published: June 2024

With the rapid development of science and technology, digital visual communication technology has become an important tool for 3D animation stereo space design. The study constructs a 3D animation stereo space design framework model using NURBS-based surface modeling and texture mapping algorithms. It compares it with the traditional 3D modeling algorithm to explore the authenticity and reliability of the stereo space design framework model for 3D animation. Finally, by comparing the differences in user experience between the 3D animated stereo spatial design framework model proposed in this paper and the spatial design of the traditional 3D modeling model, the user experience effect and superiority of the 3D animated stereo spatial design framework model are explored. After comparison, the detection time of the 3D stereo spatial design framework model in three-time indicators is 307ms, 324ms, and 318ms, respectively, which is significantly faster than the traditional 3D modeling algorithm. Its detection accuracy is 17% higher than that of the conventional 3D modeling algorithm, and the number of delays, scene stutters, and black screen flashes of the 3D stereo spatial design framework model and the traditional 3D modeling algorithm increase with the extension of detection time, but the former is always better than the latter. The 3D stereo spatial design framework model has a higher mean score than the traditional 3D modeling algorithm by 8.12 to 9.82 points in terms of user experience.
Innovation and Implementation of Teaching Mode of Higher Vocational Advertising Planning Course in the Context of AI Smart Marketing
Authors: Zeng Cuifeng
Published: June 2024

With the ongoing advancement of AI in intelligent marketing, there is a pressing need for the continuous innovation and evolution of advertising planning courses in higher vocational education to keep pace with environmental shifts. This paper introduces a sophisticated smart learning model, beginning with the construction of a subject knowledge map and detailing its development methodology. Building upon this foundation, the paper enhances the Dijkstra algorithm and integrates it with the ant colony algorithm to offer personalized learning path recommendations. Furthermore, an improved convolutional neural network is employed to generate these customized learning paths. An empirical study is conducted using the advertising planning course of a higher vocational school as a case study. The findings of this research highlight the efficacy of the proposed intelligent learning model in the instructional process. Notably, there is a significant increase in student engagement, with the level of active problem-solving in the classroom rising from an initial average of 14 to 26. Additionally, the average final grades of the experimental group exceeded those of the control group by 7.63 points. The average comprehensive competence score also showed a substantial enhancement, registering at 0.447, indicating a marked improvement in overall student performance.
Intelligent Teaching Model Construction of Chinese Language and Culture Courses in Higher Education
Authors: Chai Yu
Published: June 2024

The development of Internet technology injects intelligent elements into Chinese language and literature education in Chinese universities. This paper will rely on the algorithms and models of Internet technology to create a new smart mode for Chinese language and literature education in Chinese universities. In terms of intelligent teaching, this paper adopts data mining and Web network technology to build two functional modules of online and offline processing and designs a user interest model based on multiple factors in offline analysis to further analyze the user behavior pattern so as to provide more accurate teaching support for teachers and students studying Chinese language and literature. In terms of teaching resource library design, this paper describes the process of teaching resource association based on knowledge points and, at the same time, solves the problem of manual entry in the traditional association method based on BERT text semantic encoding technology. The model can also recommend personalized teaching resources to users through the ITR model based on feature fusion. Comparative analysis indicates that the ITS model in this paper has a 6.24% increase in AUC value over the SKAT model, which is the next most effective model. The MAE values of the ITR teaching resource recommendation algorithm used in this paper on the data set with a training set ratio of 75% are 0.36, 0.40, 0.37, and 0.37, respectively, and the recommendation effect is significantly better than that of other algorithms in comparison. The inclusion of intelligent elements will promote the further development of Chinese language and literature education in Chinese universities.