bluuebunny/crossref_metadata_2025 huggingface dataset:
The Value of Reggio's Educational Experience to the Cooperative Education of Kindergartens and Communities in China
Authors: Zhao Jiayi
Published: December 2024

This work summarizes the theories, strategies and experiences of the Reggio education system, analyzes the causes and proposes feasible strategies for cooperation between kindergartens and the community to enrich the theory of community preschool education in the light of the current situation and dilemmas of kindergarten-community cooperative education in China. This study focuses on China's kindergartens, identifies and solves existing community preschool education problems, combines Reggio's educational experience and improves kindergarten-community cooperative co-education policies, and promotes kindergarten-community cooperation as well as young children's own development. This study uses the literature analysis method, by searching for literature and reading and analyzing related literature, to summarize and analyze the literature related to the Reggio education system, kindergarten-community cooperative coeducation and community preschool education, to understand the current status of the research in this field and the unsolved problems, and to use it as an inspiration for the study.
"Quantifying the Impact of Football Program Participation on the Holistic Development of Middle School Students: Basis for Training Program Initiatives"
Authors: Xia Chenxiang
Published: December 2024

This study examines the effects of a football program on the overall development of middle school students aged 18-19. Using a quantitative approach, the research aims to measure how regular participation in the program influences various aspects of student growth, including physical fitness, emotional well-being, social interaction, and cognitive skills. To assess these outcomes, students underwent evaluations before and after participating in the program, with the data analyzed through statistical tools. The study uses Jamovi software to compare the results and identify any significant changes. The goal is to provide concrete evidence of the positive role sports can play in education, offering insights that could help shape future policies focused on student development through physical activity.
The Aesthetic Presentation of Tristan Und Isolde and Its Critique
Authors: Ji Yufan
Published: December 2024

This paper takes Richard·Wagner's "holistic art" as the research object, uses comparative analysis to explore the controversy of Wagner's "holistic art" by comparing the application of holistic art in the opera Tristan Und Isolde and the criticism of Wagner's "integral art" and "Tristan and Isolde" in Igor·Stravinsky's lecture "Six Lectures on the Poetics of Music". Through the research results, it is found that Stravinsky and Wagner's musical stance is different, so the creative ideas alluded to in their works are also different, Wagner's revolution has brought tonality to the verge of disintegration, and Stravinsky's tonality concept is neither abandoning tonality nor sticking to tonality. The difference in the concept of the two has led to the difference in the work they create. However, they all provided new ideas for the development of opera in the late 19th century and even in the 20th century, and also opened up an important path for the preservation and innovation of the genre after the 20th century.
Power Rivalry and Energy Transition: A Comparative Analysis from the Perspectives of China and the United States
Authors: Gao Zihan
Published: December 2024

This paper examines the energy transition and rivalry between China and the United States. Following the commitment made in the Paris Agreement, both countries face challenges and opportunities in energy transition. The research applied a comparative analysis of motivations, strategies, and actions. China, heavily reliant on imported fossil fuels, seeks energy security and economic growth through clean energy. By leveraging multiple Five-Year Plans, they achieved remarkable results in renewable energy distribution. The US, a major energy exporter, wishes to keep its dominance. However, the different political views of their parties hindered the implementation of energy transition policies. China positions itself as a global climate leader. Trade tensions arose as China's solar panels crowded out US products. China's control over critical minerals for renewable energy infrastructure poses a potential pressure on the US. To address these conflicts, the paper calls for a global recognition of climate change, actively engaging in sincere talks and collaboration between governments. By doing this, both nations can promote energy transition while effectively addressing the climate crisis.
Interpretable Machine Learning for Mortality Prediction in S-AKI Patients Undergoing Hemodialysis
Authors: Xu Kunyuan , Huang Yun
Published: December 2024

This study developed a machine learning model to predict in-hospital mortality risk among ICU patients with sepsis-associated acute kidney injury (S-AKI) undergoing hemodialysis. A retrospective analysis of 1,467 patients from the MIMIC-IV database and 226 from the eICU-CRD database was conducted, with models evaluated internally and externally. The RF model achieved excellent performance, with AUROCs of 0.798 (95% CI: 0.754–0.843) and 0.790 (95% CI: 0.723–0.857) in internal and external validations, respectively. Decision curve analysis indicated a net benefit of ~0.2 at a 10% mortality threshold, demonstrating good clinical applicability. SHAP analysis identified prothrombin time, APS III, systolic blood pressure, mean arterial pressure, and respiration rate as key predictors, with increased mortality risk associated with prothrombin time >10s, APS III >80, Nibp_systolic <110 mmHg, and Nibp_mean <70 mmHg. This model offers potential for supporting prognosis management and individualized treatment in clinical practice.
Wireless Charging Technology for Electric Vehicles
Authors: Jin Yitian
Published: December 2024

Currently, global energy structure transformation and environmental protection concerns have drawn the attention of all sectors of society to electric vehicles. However, issues such as inadequate charging facilities, long charging times, and charging safety impede the popularization and promotion of electric cars. Against this backdrop, wireless charging technology, as an innovative charging method, is increasingly gaining public attention and showing enormous potential for development. Wireless charging technology employs the principles of electromagnetic induction and magnetic resonance to transmit electrical energy through the air, allowing electric vehicles to be charged without needing a physical connection, thereby increasing the convenience and safety of the charging process. After reading a lot of research, the author summarizes three common wireless charging methods, shows how this technology can be used in electric vehicle scenarios, and suggests ways to improve things based on current issues. The goal is to give the electric vehicle industry new ideas and solutions for its long-term growth.
Revitalizing Diesel Technology in Aircraft: A Path Toward Fuel Efficiency and Sustainability
Authors: Xu Yilin
Published: December 2024

As the aviation industry seeks to reduce its environmental impact and improve fuel efficiency, diesel engines have re-emerged as a promising alternative to traditional aviation fuels. This paper explores the historical development, advantages, challenges, and current applications of diesel engines in aviation. With their superior fuel efficiency, lower emissions, and enhanced durability, diesel engines offer significant potential for reducing operational costs and contributing to the industry's sustainability goals. However, challenges related to engine weight, performance limitations, certification processes, and noise concerns have slowed their widespread adoption. Key advancements in turbocharging, direct fuel injection, and hybrid integration are poised to overcome these obstacles, making diesel engines increasingly viable for various aviation sectors. Current applications, such as the Diamond DA40 and DA62, the Aero Vodochody L-39 Albatros, and the Pipistrel Alpha Electro, demonstrate the adaptability and cost-saving potential of diesel engines. The paper concludes by discussing future prospects for diesel engine technology in aviation, highlighting ongoing technological innovations and the critical role of regulatory support in fostering sustainable aviation solutions.
Research on Wireless Charging System Based on Photovoltaic Power Supply
Authors: Dong Yahan
Published: December 2024

Given the popularity of mobile devices and rapid advances in wireless technology, it is impossible to overlook how important charging methods should be as convenient and environmentally sustainable. This paper investigates the PV power supply integration in their wireless charging systems, which aligns well with developing an environmentally safe and renewable alternative for recharging that would alleviate pressure on conventional harvesting of electricity, while also improving ecological conservation and reducing carbon emissions following earlier interests. Firstly, based on the PV battery model modeling methods and fully considering light intensity conditions at various temperatures throughout a year-long experimental validation of the electrical output characteristics of these PV panels. Second, it adapts and optimizes DC-DC converters to the output of PV panels for higher energy conversion efficiency by stabilizing energy outputs due to weathering issues. Additional area for research includes the choice and tuning of Maximum Power Point Tracking (MPPT) algorithms that will enable this system to follow maximum power point under diverse weather and light conditions in order to maximize energy harvesting. Moreover, the paper also performs an in-depth study of coupling transformer design and optimization of main circuit parameters for better energy transmission efficiency and System stability. The feasibility and effectiveness of the PV-powered wireless charging systems are validated by simulation verification as well as experimental testing in this paper.
The Evolution and Future Trajectory of Diesel Engine Technology: Applications, Environmental Challenges, and Innovative Solutions for Sustainability
Authors: Yuan Qien
Published: December 2024

Diesel engines, introduced by Rudolf Diesel in 1897, have played a significant role in the global transportation and energy sectors due to their reliability and efficiency. However, increasing environmental concerns and the need for sustainable solutions have driven the evolution of diesel technology, leading to innovations that reduce emissions and improve performance. This paper reviews the historical development and diverse applications of diesel engines, particularly in marine vessels, trains, and aircraft. It explores the technological advancements that have enhanced fuel efficiency and reduced pollutants, such as the introduction of alternative fuels like biodiesel and hybrid diesel-electric systems. The review also highlights the importance of emissions control technologies like diesel particulate filters (DPF) and selective catalytic reduction (SCR). Furthermore, the paper discusses the long-term projections for diesel engines considering evolving government policies and the push towards carbon neutrality. While diesel technology faces challenges in achieving sustainability, continued innovation and regulatory support will ensure its relevance in future energy landscapes.
Research And Future Application Analysis of Multimodal Fusion
Authors: Xue Haowen , Zhu Zhitao
Published: December 2024

This manuscript delves into the origin, progression, and future of multimodal fusion by conducting a comprehensive review of seminal research at various phases of its ontogeny. It encompasses three foundational methodologies of multimodal integration: Early Fusion, late Fusion, and Hybrid Fusion. Moreover, the article presents three novel methodologies for integration. It culminates in a discourse on potential subsequent applications, obstacles, and progress within the domain. solve the fusion problem of heterogeneous neural networks, and improve the correlation and consistency between modes in the aspects of cross-modal representation learning, multi-modal sentiment analysis, multi-modal intelligent interaction, so as to achieve better human-computer interaction experience.
Digital Tax Administration and Corporate Debt Default Risk: Evidence from China’s Golden Tax Project III
Authors: Chen Jiale
Published: December 2024

Using China’s Golden Tax Project III as a quasi-natural experiment, this study empirically examines the impact of digital tax administration on corporate debt default risk and its mechanism based on data from Chinese A-share listed companies from 2009 to 2022. The results show that digital tax administration can reduce the risk of corporate debt default. Further, digital tax administration exerts governance effects by reducing agency costs and enhancing the information environment, thereby reducing the risk of corporate debt default. Additionally, the negative effect of digital tax administration on corporate debt default risk can be more significant in firms with a higher level of regional rule of law, poorer quality of internal control, and a higher degree of cash flow volatility. The findings of the current study provide a scientific reference for the enhancement of national governance systems in the digital era.
Exploring Pragmatics Teaching in Chinese High School English Classrooms
Authors: Zeng Xinni
Published: December 2024

This paper delves into the efficient ways of teaching pragmatics in Chinese high school English classes, focusing on applying Role play, analyzing pragmatic failures, and comprehending Speech Act Theory to enhance learners' successful acquisition of pragmatic, positive competence in communication. Pragmatic failure in cross-cultural contexts leads to misunderstandings and communication interruption between individuals. Through methods such as Role play, students can acquire authentic experience in real communication scenarios and develop an awareness of language and cultural differences. In addition, the paper introduces Austin's Speech Act Theory, which emphasizes "locutionary", "illocutionary," and "perlocutionary." It additionally provides suggestions on how these concepts can be integrated into classroom activities to enhance language teaching. The study results indicate that pragmatic teaching is indispensable for developing learners' capacity to communicate appropriately in various social settings.
Innovative Discussion on Enterprise Business Administration and Human Resources Management Model in The Era of Big Data
Authors: Liu Yifei
Published: December 2024

This article discusses the innovative path of enterprise business administration and human resources management model in the era of big data. By analyzing the limitations of the traditional management model and combining the application of big data technology, the impact of management model innovation on the core competitiveness of enterprises is put forward. This article focuses on the synergy of business administration and human resources management. The extensive application of data sharing and analysis improves the operational efficiency and adaptability of enterprises, and optimizes the allocation and performance management of human resources. The big data-driven management model can effectively enhance the competitive advantage of enterprises in the rapidly changing market and provide important support for the strategic development of enterprises.
Vehicle Travel Time Prediction Based on SSA-LSTM
Authors: Wang Yuanrong , Wang Tingmei , Dong Guoxia
Published: December 2024

Highway travel time, defined as the time difference between a vehicle entering and exiting the highway, is primarily influenced by factors such as the highway's characteristics, current road conditions, and the driver's behavior. Travel time is a crucial parameter for assessing the operational state of a highway and serves as an important reference for both drivers when selecting routes and for traffic managers in implementing control measures. Therefore, predicting highway travel time is of significant importance. Long Short-Term Memory (LSTM) is a type of recurrent neural network, an improved version of the traditional recurrent neural network, known for its excellent performance in predicting sequential data, such as time-series data on highway travel times. In operations research, search optimization algorithms have been a key area of focus in conjunction with machine learning. The Sparrow Search Algorithm (SSA), a relatively new search optimization algorithm, boasts high convergence speed and accuracy, along with strong global search capabilities, reducing the risk of getting trapped in local optima. This study utilizes vehicle entry and exit data collected by the ETC system at the Jin-Gang Expressway toll stations to analyze the highway's basic information. Building upon the traditional LSTM model, we integrate the SSA to optimize the LSTM model parameters. By using SSA to search for the optimal parameters, we form a new SSA-LSTM model. Finally, we apply this model to predict travel time data, showing a 120% improvement in prediction accuracy compared to the original LSTM model.
Integrating Biological Systems with Electronic Technologies in Bioelectronics Advancements
Authors: Xu Yiwei
Published: December 2024

Bioelectronics is a multidisciplinary field that seamlessly integrates the biological systems with electronic techniques, driving the progress in areas such as modern medication, military management and environmental monitoring. This paper explores the fundamental underlying the bioelectronic devices, viewing some recent advancement in biometric sensors that are central to their operation. By examining the recent research on the different applications of the bioelectronic devices, including medical diagnosis, real-time health monitoring and environmental detection, this paper provides some future prospect on this technique to address contemporary issues. In addition, paper discusses some main challenges it faces such as the biocompatibility and the efficiency to process enormous information. The transformative impact that bioelectronics provide enhance people’s understanding of the way humans interact with their own bodies and the external environment. This integration of biology and electronics also offers people a new insight on the biological process and revolutionize the way human use to treat disease and the environment detection.
Enhancing Gesture-Based Interactions for Individuals with Disabilities through Dual-Attention Wireless Sensing Networks
Authors: Pan Jingzhi
Published: December 2024

This paper investigates the application of wireless sensing technology to develop a more natural and intuitive gesture-based interaction framework for individuals with disabilities. The study begins by identifying the primary challenges faced by this demographic when interacting with conventional devices. It then introduces a novel approach for WiFi-enabled gesture recognition and interpretation using dual attention networks. This methodology comprises two essential components: Channel State Information (CSI) preprocessing and a gesture recognition module. The paper details the implementation of these modules and elucidates their roles in enhancing gesture detection accuracy. Furthermore, the discussion extends to the future prospects of wireless sensing technologies, envisioning their integration into smart home systems, public services, and enhanced social interactions. The research underscores the transformative potential of integrating gesture-based interactions with wireless sensing to significantly elevate the quality of life for people with disabilities, suggesting a paradigm shift in how assistive technologies are developed and utilized.
Using Bloom’s Taxonomy to Evaluate HOTS in the Tasks of the Chinese Grade 7 English Textbook
Authors: Hong Yi
Published: December 2024

This study evaluates the cognitive demands of tasks in the Chinese Layman’s Edition Grade 7 English textbook using Bloom’s Revised Taxonomy. The primary objective is to assess the distribution of lower-order thinking skills (LOTS) and higher-order thinking skills (HOTS) across the textbook’s tasks. Six cognitive categories were identified through a content analysis of 224 tasks: Remembering, Understanding, Applying, Analyzing, Evaluating, and Creating. The findings show that just 26.7% of activities concentrate on HOTS, such as Analyzing, Evaluating, and Creating, whereas 73.3% of tasks concentrate on LOTS, especially in Understanding and Applying. This disparity implies that fundamental cognitive abilities are being overemphasized, which is preventing children from engaging in critical analysis, evaluation, and innovation. The study emphasizes the need for textbook changes that support students' cognitive growth and are in line with contemporary educational objectives by better integrating HOTS-oriented tasks.  Recommendations for curriculum enhancement and instructional strategies are provided to better prepare students for real-world challenges through more complex cognitive engagement.
Progress made in researching autonomous vehicle systems based on BeiDou navigation
Authors: Wu Weiting
Published: December 2024

The evolution of smart transport systems has made autonomous vehicles a central focus for research. The BeiDou navigation system's highly accurate location data is vital for environmental detection, autonomous vehicle decision-making, and navigation. This research aims to develop and actualize a system for autonomous vehicles to plan routes and evade obstacles, utilizing the BeiDou satellite navigational framework. Consequently, this document introduces an algorithm for planning paths and avoiding obstacles that integrate BeiDou navigation data, capable of adjusting to intricate traffic conditions and enhancing the safety and efficiency of autonomous vehicles. Verification of the suggested algorithm was conducted on the environment simulation platform within the ROS operating system, revealing the algorithm's capability to create the ideal path and successfully evade dynamic obstacles. The practical vehicle testing verifies the algorithm's practicality and steadiness in traffic situations. Ultimately, the document encapsulates the study's findings and outlines prospective research avenues, encompassing the acquisition of both image and depth information, along with conducting image recognition and car tracking.
Investigation on Reasons for Normal University Students' Willingness to Enter Teaching Employment in the Post-Pandemic Era
Authors: Li Chuanming , Wang Jixian , Yu Haoxuan , Huang Saiqiong , Li Siyao
Published: December 2024

The COVID-19 pandemic has had a profound impact on the global economy and society, both during the pandemic and in the post-pandemic era. Against this background, normal university students, as the main force in cultivating educational talents, have attracted attention regarding their employment intentions. This study focuses on normal university students from a university in Zhejiang province. By investigating and collecting relevant data through interviews and questionnaires, the study explores the reasons for the employment intentions of students under the influence of the pandemic, aiming to discuss methods to enhance the employment management level of normal graduates. The survey results indicate that due to the pandemic, the employment opportunities for normal university students are limited. However, their enthusiasm for the education sector remains undiminished, and a sense of social responsibility persists. They also demonstrate a strong interest in education reform and innovation. Therefore, various measures should be taken to increase the employment opportunities and satisfaction of normal university students, thereby promoting the development of the education sector.
Key Sensing Systems in Autonomous Driving
Authors: Cai Lipeng
Published: December 2024

With the rapid and dynamic evolution of autonomous driving technology. The escalating demand for transportation that is not only safer but also more efficient has spurred an intense exploration of advanced sensing technologies. This article centers on the sensor system within the domain of autonomous driving. The principal methods encompass an in-depth study of various distinct sensors such as lidar, cameras, radar, and ultrasonic sensors. The research findings reveal that these sensor systems can synergistically collaborate to furnish highly precise environmental perception. Specifically, lidar offers elaborate 3D depictions, granting vehicles a comprehensive understanding of the surrounding landscape. Cameras capture essential visual cues, providing detailed information regarding road signs, traffic conditions, and the presence of pedestrians or other vehicles. Radar effectively detects the velocity and distance of objects, significantly enhancing the vehicle's capacity to anticipate potential hazards. Moreover, ultrasonic sensors play a critical role in short-range detection, ensuring safety during parking and low-speed operations. The conclusion is that the seamless cooperation and continuous refinement of these sensor systems are of utmost significance for successfully realizing autonomous driving. This not only elevates traffic safety to a higher level but also holds profound implications for enhancing efficiency and convenience on the roads.
Deep Learning and Visual SLAM for Autonomous Navigation of UAVs: Status, Challenges, and Future Perspectives
Authors: Long Keyu
Published: December 2024

This paper discusses the application and integration of deep learning and visual SLAM technology in UAV autonomous navigation. With the wide application of UAVs in the fields of transportation, agriculture, military and environmental monitoring, improving the autonomous navigation capabilities of UAVs has become an important demand. This paper first analyses the advantages and disadvantages of deep learning and visual SLAM. Then, this paper emphasizes the core role of deep learning in feature extraction, target recognition and path planning. The key role of visual SLAM in real-time localization and environment mapping is highlighted as well. This paper discusses the combined application of these two technologies and demonstrates how to enhance the stability and accuracy of visual SLAM systems through deep learning in complex dynamic environments. Although the current technology still faces high computational requirements and real-time challenges, this paper proposes future research direction to promote the continued development of UAV autonomous navigation technology.
The Continuity or Discreteness of Space-time
Authors: Liu Maijie
Published: December 2024

General relativity and quantum field theory have always held opposite views on the continuum and the dispersion of space-time. Scientists have debated this for nearly a century. This paper reviews the basis of general relativity and quantum field theory on the continuity and discreteness of space-time in a unified viewpoint, describing what both stand for in this discussion point and their respective experimental evidence to illustrate their plausibility. By using mathematical reasoning and figures to help describe and apply string theory's ideas, this paper describes the universe as a wave. Based on this, a new conjecture of the unified field theory is obtained: space-time is described as a piecewise function, which presents different states under different conditions. In the normal state, the continuous wave appears, and in the energy exchange with the outside world, it is transformed into a discrete particle state. Space-time is similar to the waves described in string theory, but it is more similar to electromagnetic waves, taking on an ever-changing form.
Design and Analysis of Electric Vehicle Wireless Charging System
Authors: Fang Zicheng
Published: December 2024

because of its higher safety, convenience and flexibility than traditional wired charging. Studying the power transmission theory of the wireless charging system and improving the essential components is a significant way to increase its performance. This essay first outlines the present state of research in this field and highlights its primary issues. It then goes on to discuss the various forms of wireless power transmission also called WPT, the elements that make up a magnetic coupling resonant circuit, and its compensation structure based on the theory. Through theoretical derivation and the summary of the analysis of the design optimization scheme, it is concluded that the planar circular coil is better, and the optimization design process is explained to increase this system's efficiency even further. The results show that S-S topology is more suitable and then provides a scheme for the optimization of coil parameters.
An Image-Text Sentiment Analysis Method for Small Samples Based on Image Captioning
Authors: Chen Shuailin
Published: December 2024

With the wide popularity of personal terminals, people prefer social media to share their lives, which provides a rich source for sentiment analysis methods. However, challenges still exist in small-sample sentiment analysis methods. A sentiment analysis method for Small Samples based on Image Caotion and BERT is proposed. Specifically, the model takes a pre-trained language model as the image description decoder and uses a cross-modal attention mechanism to eliminate the effects of misaligned regions. This can further increase the interaction from image to text. Then, the generated descriptions are coupled with the original text in the dataset. The BERT model is used to extract word vectors and output sentiment analysis results. The COCO dataset is used to train the model for image Captioning, and the MVSA dataset is used for training and evaluation of sentiment analysis. The experiment creates Less Sample Segmentation by randomly selecting samples from the dataset. Accuracy and F1 value are used to compare with baseline models to evaluate the model performance. The results show that the Image Captioning-BERT model has a certain performance improvement in sentiment analysis of image-text pairs with small samples.
Enhancing Aircraft Glide Performance through Wing Geometry Modifications
Authors: Jin Fengzhou
Published: December 2024

Modifications to wing geometry can significantly influence the glide performance of an aircraft, affecting critical aspects such as lift, drag, and overall flight efficiency. This study investigates how variations in wing design parameters, including aspect ratio, wing loading, and camber, impact the glide ratio and performance of fixed-wing aircraft. Using a combination of computational fluid dynamics (CFD) simulations and scaled model flight tests, the research provides a detailed analysis of how these geometric adjustments affect aerodynamic characteristics during unpowered flight. The results indicate that increasing the aspect ratio, which involves lengthening the wingspan relative to the wing chord, significantly improves glide performance by reducing induced drag, thus enhancing the aircraft's lift-to-drag ratio. This improvement is particularly beneficial during extended glide phases, as it allows for greater distances covered per unit of altitude loss. Adjustments to wing loading, defined as the aircraft’s weight divided by the wing area, showed that lower wing loading generally improves glide efficiency but at the cost of increased sensitivity to turbulence and gusts. Changes in camber, or the curvature of the wing, had more complex effects; higher camber increased lift but also raised drag, highlighting the need for a balanced approach depending on flight conditions.
Qinglong Temple: A Nexus for The Exchange and Integration of Chinese and Japanese Buddhism
Authors: Cui Zhonghao
Published: December 2024

The Qinglong Temple, located in the ancient capital of Xi’an, is an important temple of Chinese Buddhist Tantric Buddhism, whose history can be traced back to the Sui Dynasty. The purpose of this paper is to explore the unique position of Qinglong Temple as an important link between Chinese and Japanese Buddhist exchanges and its far-reaching influence, and to reveal its contribution to the dissemination of religious culture and ideas. By exploring the history of the development of the Qinglong Temple, its architectural form, related cultural relics and historical figures, the paper discusses ways to promote friendly and peaceful exchanges between China and Japan, and finally proposes measures that can be taken by the relevant authorities to protect the site of the Qinglong Temple, which reveals the unique contribution of the Qinglong Temple to the promotion of the integration of Buddhism between China and Japan. Through the study of the Qinglong Temple, we can better disseminate Chinese and Japanese culture, exchange Buddhist ideas, protect related cultural heritage, and promote the prosperity of culture. Therefore, it is necessary to study and explore the Qinglong Temple and its cultural connotation.
Exploring the Application of Constructivist Theory in English Language Teaching
Authors: Guo Xinzhe
Published: December 2024

This paper explores the application of constructivist theory in English language teaching (ELT). This report focuses on three essential methods: situational learning, task-based teaching, and collaborative writing. Swiss psychologist Jean Piaget first introduced constructivist theory and later developed by Soviet psychologist Lev Vygotsky. The active production of knowledge via social interaction and real-world circumstances is emphasized by constructivist theory. The review first explores situational learning, which uses actual settings to improve language acquisition in real-life contexts. Case studies show how well it works to enhance students' communication skills. After that, the topic of task-based education is covered, emphasizing strategies for task design and assessment that are focused on the completion of meaningful activities. According to reviews, collaborative writing is a technique that improves language proficiency through group communication, enhancing vocabulary richness, grammatical accuracy, and critical thinking.  The review concludes by summarizing the key findings and discussing challenges in implementation, such as task design and group dynamics. It offers suggestions for future research, particularly in refining assessment techniques and integrating technology into these constructivist approaches.
Research on the Practice of Sculpture Dematerialization in the Context of Conceptual Art
Authors: Lu Jie
Published: December 2024

As one of the most influential art schools in the second half of the 20th century, the conceptual art has had a profound influence on the development of sculpture art. This paper aims to explore the practical path and artistic value of sculpture dematerialization in the context of conceptual art. Through the in-depth analysis of the core concept of concept art and the trend of sculpture de-materialization, this paper reveals the transformation process of sculpture from material entity to concept expression, and the influence of this change on the artistic form, creative technique and aesthetic experience of sculpture. The study shows that the dematerialization form of sculpture not only enriches the expressive force of sculpture art, but also expands the boundary of sculpture art, providing new possibilities for the development of sculpture art in the contemporary society. The research of this paper is of great significance for understanding the interactive relationship between conceptual art and sculpture art, as well as the practical application of sculpture dematerialization form.
Biometric Technology Based on Wireless Sensing: Principles, Applications, and Challenges
Authors: Su Peican
Published: December 2024

With the rapid advancement of computer technology, image processing, and artificial intelligence, biometric identification technology has seen widespread application, gradually permeating areas such as national security, public security, and home security. However, traditional biometric technologies exhibit certain limitations. In contrast, biometric identification based on wireless sensing offers distinct advantages, including non-contact operation and strong concealment, making it a promising alternative in various security applications. This paper provides a comprehensive overview of the history and current state of biometric technology, alongside the development background of wireless sensing technology. It details the principles of wireless sensing-based biometric identification, covering essential characteristics of wireless signals, and related technologies such as RFID, Wi-Fi, Bluetooth, and millimeter wave technology, as well as relevant signal processing algorithms. Furthermore, the paper analyzes the application of this technology in areas like human posture and motion recognition and physiological feature recognition, supported by practical case studies. Finally, it addresses the environmental dependencies, data privacy, and security concerns associated with this technology, while offering insights into future development directions.
Simulation Research on Improving Wireless Charging Efficiency of Electric Vehicles
Authors: Xu Zihan
Published: December 2024

Accompanied by the continuous development and progress of science and technology worldwide, wireless energy transmission has become an increasingly important research focus for researchers in related fields. Wireless charging technology, with its advantages of safe operation, flexibility, convenience, and low maintenance costs, has received more and more attention and is one of the mainstream development trends of electric vehicles in the field of future power technology. The efficiency of wireless charging technology is an important factor affecting its promotion. This article summarizes and discusses the magnetic coupling resonance wireless energy transmission technology, analyzes the basic structure and working principle of the magnetic coupling resonance wireless energy transmission technology, and theoretically analyzes the magnetic coupling resonance wireless energy transmission circuit through a mutual inductance model. The circuit is built using the mutual inductance model in Multisim for simulation experiments to verify the correlation between wireless charging efficiency and circuit load and frequency. Plotted the correlation curve between wireless charging efficiency, circuit load, and frequency.
ASSESSMENT OF KNOWLEDGE, PERCEPTION, ATTITUDES AND BARRIERS TO POLIO VACCINATION AMONG PARENTS
Authors: MUMTAZ OM , YOUSAF AI , KHAN SU , RIZVI Z , JAMSHAID F , HUSSAIN AK
Published: December 2024

Polio remains a significant public health challenge in Pakistan, necessitating an understanding of parental knowledge, perceptions, attitudes, and barriers to vaccination in urban and rural areas. Objective: To assess the knowledge, perceptions, attitudes, and barriers towards polio vaccination among parents in urban and rural regions of Pakistan. Methods: A descriptive cross-sectional survey was conducted from October 2019 to February 2020, involving 609 respondents (mothers and fathers) with an 87% response rate. A pretested, anonymous, self-administered questionnaire was used to evaluate participants' knowledge, perceptions, attitudes, and barriers to polio vaccination. Results: Participants exhibited good knowledge and positive attitudes towards polio vaccination. No significant differences were noted in awareness of polio terminology between urban and rural participants (p=0.427). A majority supported polio vaccination for all children (p=0.0001*) and recognized its importance (p=0.007*). Concerns regarding vaccine sterility (p=0.0001*) were prevalent. Barriers such as lack of knowledge (p=0.216) and distrust in medical facilities (p=0.0001) were identified. Conclusion: Parents in Pakistan demonstrate good knowledge and positive attitudes towards polio vaccination. However, addressing gaps in knowledge and mistrust in medical services is critical to enhancing vaccination uptake, particularly in rural areas.
Urinary Tract Injuries Following Obstetric Operations: A Retrospective Study in Iraqi Tertiary Care Center
Authors: Fadhil Amenah , Nori Wassan , Hameed Ban Hadi , Daraji Saad Dakhil Farhan
Published: December 2024

Background: Urinary tract injuries (UIn) are commonly reported after obstetrical and gynecological operations. They contribute to higher morbidity rates, longer hospital stays, and lower patient life quality. Objective: To identify risk factors and predictors of UIn, as well as the best therapeutic techniques for preventing further harm and improving patient outcomes. Methods: A retrospective analysis examined UIn cases from obstetrical and gynecological procedures conducted at Yarmouk Hospital during 2021-2023. The records included information about the patients' demographics, operative data (surgery type, after diagnosis of UIn, and injury type, size, and confirmation), repair data (suture used, how many layers, and the use of suprapubic catheter), and post-operative complications (admission to intensive care, sepsis, renal failure, and maternal death). Results: 51.6% of the cases were between 30 and 40 years old. Cesarean hysterectomy was performed in 54.84% of instances, with 66.13% being diagnosed intraoperatively without the requirement for IVU, which was employed in just 30.65%. Bladder injuries account for 80.65% of all cases, with 48% of them measuring 3–5 cm. Injuries were healed in 77.4% of cases using two two-layer methods and Vicryle sutures. Most patients (69.35%) had a suprapubic catheter. 93.5% of cases had no serious problems. Conclusions: Early diagnosis during surgery, as well as a two-layer repair using Vicryle sutures and a suprapubic catheterization, are critical for reducing morbidity, enhancing recovery, and improving healthcare in high-risk settings.
Optimized Cash Forecasting Models for Banking Applications Using Soft Computing Techniques
Authors:   Professor, University of St.Thomas, MN, USA, Manjeet Manjeet
Published: December 2024

The Artificial Neural Network-based Cash Forecasting Model (ANN-CFM) is introduced in this part as one way of mitigating the vices that are characterised with linear approach to financial management. This paradigm is quite helpful when the analysis is focused on non-linear and, generally, troublesome data. ANN-CFM, therefore, simultaneously takes both the linear and non-linear information for improving on the cash forecasting. Due to this fact, it is able to realise and leverage over advantage from the computational competence that neural systems provide. The hidden, output and input layers use randomised initial biased and weights. These include biases together with weighting that is altered regarding a standard basis with the use of a learning strategy to try to find the greatest cash needs. This design is actually composed of three various layering. This is exactly what the ANN-CFM is capable of dealing with and it accepts inputs, both for LT and ST forecasting. Among these inputs, you have factors of the working days, wages’ impact, and the impacts of holidays. The ANN-CFM is a system that revolutionises the way a human would perform hisher decisions and is a highly parallelized and efficient analytical tool for large data. As a result, this results in enhancement of precision to that which is predicted. The kind of architecture used in the system is feed forward neural network, which uses back propagation to help in reducing the numbers of errors that prevail at the time of prediction. In this part, extensive application of ANN, including its ability to learn in environments that may be constantly evolving is also highlighted. Thus, this innovative approach allows for sure receipt of accurate solutions for the management of these funds by companies operating in the financial industry. Comparing it with Normal Data, it is clear that the ANN-CFM technique proposed here provides an overall accuracy of approximately 95%.
Optimizing Business Process through Fault-Tolerant Scheduling in Cloud Environments: A Comparative Study
Authors:   Cumulus Solutions, South Africa, Anil Anil
Published: December 2024

The fault tolerance study carried out in this research explores Bidirectional Long Short-Term Memory (LSTM) and Generative Adversarial Networks (GAN) to improve cloud computing dependability and functionality. Being an integral part of the rage for business operations, cloud-computing fundamentals of resource provisioning and fault tolerance have a bearing on the overall cost-dynamics, ROI and OpEx. Reliability covers such issues as hardware failures, configuration problems and other network issues that may have financial implications and even lead to revenue loss, and failure to meet service level agreement (SLA). The work develops a novel GAN-BiLSTM model for the accurate prediction of faults and the enhancement of recovery management, resulting in resource efficiency and cost of capital reduction (CapEx). Evaluation criteria involve deadline guarantee ratio, average task delay, and system scalability, confirming that the proposed model has better financial performance than DPSO and ANFIS. Cutting wastage of resources and increasing energy capacity in a system, the model displays attractive cost reduction and operating effectiveness for cloud service providers. In the simulation, important results of the model are demonstrated in the business continuity, financial risk reduction as well as maintaining accurate and resourceful service in high demand situations. All these developments have placed the fault tolerant systems powered by machine learning as indispensable instruments that can also enhance profitability, resources utilisation and sustainable competitiveness in the cloud computing business.
Leveraging Time Lag-Based Diffusion Models to Predict Innovation Adoption for Optimized Product Development
Authors:   School of Management, Zhejiang Shuren University, PR China, Muddassar Muddassar
Published: December 2024

The suggested models for the spread of technical breakthroughs make use of a phase structure to illustrate the steps involved in becoming familiar with the problem and making a choice. For it to portray genuine adopting conduct, a time-lag factor is included into the dispersion process. Depicts a two-step dissemination process by taking into account the reliance of adopting on the informed group of potential purchasers. Assuming that a prospective customer first becomes intrigued by an upcoming the item's availability and then accepts the novel idea at an ulterior point, a method of analysis for sales functions that incorporates time delay is proposed. The efficient propagation method for invention is shown using the various lag factors. Applying nonlinear regression modelling to worldwide shipping data of Acer PCs and Samsung smartphones experimentally validates the suggested models for mathematics. Several comparison models are used to evaluate the predicting abilities of the suggested models. By integrating a distributed time delay function into the implementation manage, a theoretical intergenerational diffusion model is created. To measure how long it takes for innovation to be eventually accepted, the distributed time lag function that follows the Erlang distributions is used. This framework incorporates switch and substituting, two forms of pragmatist shift behaviour. Using real shipping data of LCD (Liquid Crystal Display) computer monitors from consecutive generations, the predicted effectiveness of the suggested methods is examined and contrasted with well-established research. Here is the total accuracy of the approaches that have been proposed: When contrasted with more conventional models, MGDM 1 achieves a 99.33% accuracy rate, MGDM 2 a 99.81% rate, and MGDM 3 a 99.91% accuracy rate.