bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Impact of Shipping Tariffs on the Marginal Efficiency of Freight Forwarders Based on Cost Optimization and Supply Chain Resilience
Authors: Tang Jinyu
Published: January 2025

In contemporary society, globalized trade continues to develop and become the mainstream of economic trade. As an important role in the shipping industry connecting all parts of the shipping industry, the operational efficiency and cost control ability of freight forwarding enterprises are directly related to the competitiveness of foreign trade enterprises. This thesis aims to analyze the role of shipping rate fluctuation and supply chain resilience on the marginal efficiency of freight forwarding enterprises, which is assessed by collecting shipping rate indices and analyzing past literature. It is found that the marginal cost of freight forwarders is more sensitive to the fluctuation of shipping tariffs and fuel costs, and that firms with higher supply chain resilience can effectively mitigate the shock during the period of rising tariffs. While improving efficiency, shipping companies still need to balance the relationship between cost control and environmental sustainability and form closer collaborative relationships with partners to cope with the wave of digitization.
Research on Future Development and Challenges of New Energy
Authors: Cui Fugen
Published: January 2025

Renewable energy has emerged as a crucial solution to address the twin challenges of global climate change and the depletion of traditional energy resources. This study aims to analyze the potential of various renewable energy sources, including solar, wind, hydro, geothermal, and biomass energy, to replace conventional energy systems while mitigating environmental impacts. Through a review of current development status, this paper identifies key challenges, such as technological limitations, high initial costs, policy barriers, and resource intermittency, that hinder the adoption of renewables. Using a mixed-methods approach, including data analysis and case studies from leading renewable energy projects, the research highlights strategies for overcoming these challenges. The findings suggest that integrating innovative technologies, implementing supportive policies, and fostering international collaboration are critical to achieving a sustainable energy future. This paper concludes that while significant hurdles remain, renewable energy holds transformative potential to ensure long-term environmental and energy security.
Analyzing the Causes of the Slowdown in Economic Growth--From the Perspective of the Economic System
Authors: Dong Runze , Dong Yingwan
Published: January 2025

Following the conclusion of the Second Cold War, the economic landscape of the Soviet Union experienced a significant decline, in stark contrast to the rapid growth observed in its competitor, the United States. Even Russia, which implemented reforms via "shock therapy," not only failed to reverse the economic downturn during that period but also faced adverse effects from international lobbying due to the hasty liberalization of its capital account. In essence, Russia's current economic system still favors the extractive approach, which is reflected in the government's control of the main distribution of resources, small and medium-sized enterprises (SMEs) account for a small proportion of output, which in turn inhibits the enthusiasm and creativity of the labor force. Conversely, the United States, Japan, and Singapore safeguard private property rights via the judicial system and foster the growth of private enterprises through strategic policies or government-driven initiatives. By comparing the impact of countries adopting extractive and inclusive economic systems on their economic situation, this paper argues that developing countries need to ensure the independence of legislation when switching to an inclusive economic system so that private property rights can be protected from a legal perspective. Simultaneously, it is essential to restrict government involvement in the market via the state-owned sector to maximize the preeminence of the private economy.
The Integration of Digital Currencies with Traditional Financial Systems
Authors: Chen Siyuan
Published: January 2025

Digital currencies like Bitcoin and Ethereum are reshaping the financial landscape by challenging traditional banking and commerce. These technologies hold significant potential to enhance financial inclusion by providing access to underserved populations and streamlining cross-border payments, making transactions faster and more cost-effective. They also empower decentralized finance (DeFi), enabling innovative financial services without intermediaries. Blockchain, the foundation of digital currencies, facilitates secure, decentralized, and programmable systems, supporting key innovations like asset tokenization and Central Bank Digital Currencies (CBDCs). These advancements bridge the gap between digital and traditional financial systems, promoting efficiency and accessibility. Despite their promise, digital currencies face challenges, including cybersecurity threats, market volatility, and fragmented regulatory frameworks. Case studies on CBDCs and private-sector blockchain initiatives demonstrate viable integration pathways and underline the need for robust governance. By implementing balanced policies, stakeholders can harness the benefits of digital currencies while mitigating associated risks. These measures will be crucial to fostering a stable, inclusive, and innovative financial ecosystem that addresses global economic disparities and drives sustainable growth.
Research on Custom Algorithms and Hardware Accelerators Based on RISC-V Vector Extensions and Image Processing
Authors: Chang Hong , Ye Kunlin
Published: January 2025

RISC-V is an open, modular instruction set architecture (ISA) that has gained increasing adoption in fields such as image processing, machine vision, and deep learning inference due to its scalability and flexibility. This paper provides a comprehensive review of the latest research on RISC-V, with a focus on its vector extensions, custom instruction set optimizations, and the design and implementation of related hardware accelerators. The study employs a hardware-software co-optimization approach, featuring the design of a lightweight convolutional neural network (CSANet) and an artificial intelligence image signal processing (AI-ISP) accelerator to enhance image construction and inference efficiency. The experimental methods include performance evaluations based on FPGA hardware platforms, with a quantitative analysis of computational bottlenecks in the CSANet inference process, optimizing convolution operations and data flow handling. This research provides comprehensive technical support for the application of RISC-V in high-efficiency image processing and deep learning inference, especially in low-power and edge-computing scenarios.
A Study of Advances in Asynchronous FIFO Design
Authors: Wang Qianyi
Published: January 2025

With the continuous development of the new generation of microelectronics, there are several different clock domains in the complex digital systems. In order to iron out the complications caused by data transfer and storage in different clock domains, the designer used asynchronous FIFO (first in first out) in the design to realize cross-clock communication, data buffer. By analyzing and studying a number of results on asynchronous FIFO, this paper provides a comprehensive overview of the results of asynchronous FIFO up to now. This paper mainly summarizes the study of using Gray code to solve the substable problem in asynchronous FIFO, using the empty-full flag bit technique for the empty-full judgment of reading and writing, and summarizes how to make the structure of cyclic Asynchronous FIFO, and regulating the Asynchronous FIFO depth to improve their performance. For the practical application of asynchronous FIFO-based, this paper summarizes the optimization techniques of UART communication protocol based on asynchronous FIFO. the use of handshake signals for asynchronous FIFO design based on handshake-synchronous cross-clock-domain transmission technology is also a widely used technique for asynchronous FIFO.
Research on Inverse Kinematics and Block Grasping Techniques for Six-Axis Robotic Arms
Authors: Ren Zirui , Zhang Lisheng
Published: January 2025

Nowadays, large to a variety of factories and aerospace fields, small to mechanical toys, robotic arm has widely used in all works of life. Because of the interest of robotic arms, during the summer vacation, we did some research on the robot arm in order to better understand the operating principle of the robot arm and how to execute the task. This paper discusses the body frame and kinetic principles of a six-degree swivel manipulator arm. We confine to the High-Level APIs that ROS provides and focus this article on the analysis of mechanical design in a robotic arm using inverse kinematics theories. These theories not only help us recognize what goes on in the movement patterns of a robot arm but also for its well-considered control. There are unavoidable slight deviations in the calculation of inverse kinematics and the catching of objects. Even though, through some theories and program, we have already manipulate the robotics to finished some tasks.
Evolution and Challenges in Speech Recognition Technology: From Early Systems to Deep Learning Innovations
Authors: Xu Jingjia
Published: January 2025

Speech recognition technology is user-friendly and enables machines to understand and process human language, converting spoken language into text. As a critical component in numerous applications, this technology facilitates natural, hands-free interaction, enabling individuals to communicate and operate devices seamlessly, thereby enhancing the convenience and accessibility of everyday life. Additionally, speech synthesis assists users in multitasking and offers benefits to the visually impaired. Translation applications enable users of different languages to communicate with each other through one-to-one language conversion in the program. Speech recognition technology has evolved from rule-based methods to modern deep learning models. This paper explores the development history of speech recognition systems, focusing on analyzing its key technical milestones and challenges. Through a combination of historical analysis and technical insights, this paper examines how algorithms such as deep learning and neural networks can significantly improve speech recognition accuracy. The paper concluded that while deep learning has significantly boosted performance, hurdles such as managing diverse accents and environmental noise persist, indicating that there is still potential for future advancements.
The Analysis of the Development and Application Prospects of Nanomaterials
Authors: Ma Xingkai
Published: January 2025

Nanotechnology is one of the most revolutionary sciences and technologies in the 21st century, involving materials science, physics, chemistry, biology and other fields. Nanomaterials, as the core of nanotechnology, exhibit their unique physical and chemical properties that make them highly promising for a wide range of applications in various fields. In 1981, Japanese scientist Mieko Kawamura successfully prepared nanoscale ceramic particles for the first time, laying the foundation for the research of nanomaterials. Since then, the research of nanomaterials has gradually attracted the interest of scientists. This paper will discuss the development of nanomaterials, current research hotspots and future application prospects. The main research method we use in this article is a literature review, which mainly studies the development and application of nanomaterials in today's era, as well as some problems and challenges we are facing at present. The high production cost of nanomaterials limits their large-scale application. The safety of nanomaterials is still in doubt, and their impact on the environment and human health still needs to be further evaluated.
Factors Influencing Nanoscale Catalysts Prepared Impregnation Method
Authors: Guan Yuqiao , Li Linzhou , Piao Huimin
Published: January 2025

With the rapid advancement of nanotechnology, nanocatalysts have found extensive applications in chemical reactions and environmental remediation. The impregnation method stands as a pivotal technique for the synthesis of nanocatalysts, with its efficacy influenced by a multitude of factors. This study substantiates that the type and concentration of the impregnating agent significantly impact the catalyst's loading capacity and dispersion. Furthermore, the duration and temperature of impregnation effectively govern the particle size of the catalyst, thereby optimizing its catalytic performance. Additionally, the physicochemical properties of the support, along with the pH and ionic concentration of the solution, collectively alter the reduction behavior of metal ions, further affecting the formation mechanism and overall performance of the catalyst. Future in-depth investigations into the interplay of these factors will pave the way for innovative strategies and methodologies for the efficient fabrication of nanocatalysts. Understanding these complex interdependencies is crucial for designing catalysts with improved selectivity, activity, and stability, which are essential for advancing various catalytic processes and addressing challenges in sustainable chemistry and environmental protection.
The Analysis of Robust Optimization Methods in the Field of Virtual Power Plants
Authors: Wang Ruize
Published: January 2025

With the global energy transition and the rapid development of renewable energy, power systems are facing unprecedented challenges. As an innovative solution integrating and coordinating distributed energy resources, the virtual power plant (VPP) has gained increasing importance in the energy market, emerging as a highly regarded field in recent years with widespread applications. In response to many popular issues within this field, this paper categorizes them into three main aspects: cooperation/competition, market transactions and bidding strategies, as well as scheduling and forecasting. It examines the applications of robust optimization methods in each of these areas. Lastly, the paper summarizes potential future research directions for robust optimization, anticipating the development of more versatile methods that can address issues in the VPP field by considering multiple factors comprehensively.
Application and Challenge of 5G Communication Technology in Electronic Engineering
Authors: Wang Bangyu
Published: January 2025

5G, the fifth generation of mobile networks, represents a significant leap in technology, offering remarkable improvements in speed, connectivity, and data capacity. It holds vast potential in areas like radar imaging, IoT, education, and intelligent transportation. However, despite these advantages, the deployment of 5G faces notable challenges in terms of technical implementation, system integration, security, and cost management. This study focuses on how 5G can be effectively integrated into electronic engineering, analyzing its limitations, risks, and potential applications. Through a combination of literature review and case study analysis, the research explores the major challenges hindering 5G deployment in electronic engineering, strategies for addressing technical, security, and system integration issues, and approaches to enhance performance and mitigate risks. The findings highlight the importance of ongoing research and innovation to overcome these challenges. By addressing these issues, 5G can achieve its full potential in transforming electronic engineering and driving future technological advancements.
An Overview of the 11 and 1111 Systems in Iron-Based Superconducting Materials
Authors: Li Yuhang
Published: January 2025

Since the discovery of superconductivity in 1911, significant progress has been made in the research and development of superconducting technology. This progress spans from low-temperature superconductivity to high-temperature superconductivity and from theoretical exploration to experimental verification. Scientists have continuously overcome challenges, laying a solid foundation for the practical application of superconducting technology. This paper introduces and analyzes a large and promising iron-based superconducting system. It explores the historical background, development process, and influencing factors of the 11 and 1111 systems. By examining these factors, the paper investigates their relatively unique superconducting properties, providing valuable insights and guidance for related research fields
Investigation of Matrix Effect in the Determination of Bisphenols in Aquatic Products by Liquid Chromatography-Mass Spectrometry
Authors: Abduhabar Ankar
Published: January 2025

In this study, techniques such as liquid chromatography-ultraviolet photometric de- tector and evaporative light scattering detector were used to search for substances in the matrix that produced matrix effects when LC-MS was used to determine bisphenol compounds in aquatic products. This study provides new insights for researchers dealing with matrix effect problems. Bisphenols are introduced, with a focus on BPA and BPS. LC-MS is a commonly used method for the determination of bisphenols, but it is often affected by matrix effects, primarily due to phospholipids present in aquatic products. To confirm this, a chromatographic method was established to identify substances in the matrix that may co-elute with BPs. Phospholipids were confirmed as significant contrib- utors to matrix effects. Finally, commonly used methods to eliminate matrix effects are summarized
Rapid Portable Water Purification for Disaster Relief: Developing an Emergency Device to Quickly Purify Contaminated Water Sources to Potable Standards
Authors: Weng Qining
Published: January 2025

This study checked out the growth and also improvement of a practical, mobile water purification device indicated to quickly convert polluted water into potable requirements, resolving the crucial problem of water scarcity in disaster relief initiatives. By reviewing extensive literary works on different water filtration system techniques as well as their applicability in post-earthquake situations, the research dived right into aspects of water contamination, contaminant identification, materials and methods in water purification, and layout considerations for mobile devices. The findings of the research revealed that the quality of water sources following the earthquake generally satisfied the fundamental standard in Turkey. A simple yet effective water purification device that successfully reduced water turbidity, meeting WHO standards was designed and constructed. This study underscored the importance of complex systems while highlighting need for locally feasible solution that can effectively support disaster victims with clean drinking fluids especially after earthquakes, thereby anchoring future research on development of disaster relief water purification tools within this scope
Design and Implementation of the Precise Control System for the Robotic Arm Based on FPGA
Authors: Chen Zhixi
Published: January 2025

With the widespread application of robotic arms in industrial automation, and medical and service robots, improving their precise control capabilities has become a technical problem that needs to be solved urgently. Traditional control methods have limitations in dealing with target object deviation and motion accuracy, especially in complex tasks. To solve this problem, this paper proposes an innovative robotic arm motion optimization method, the "somersault" method, which significantly improves the grasping accuracy and motion stability of the robotic arm by decomposing the large-angle rotation of the robotic arm chassis into multiple small-angle continuous rotations. Especially when the target object is located on the negative semi-axis, it can effectively expand the grasping range of the robotic arm. This paper also optimizes the inverse kinematics, spatial solution and PID control algorithms of the robotic arm, and realizes efficient image processing and real-time control through FPGA. Experimental results show that after adopting the "somersault" method, the accuracy and stability of the robotic arm in complex environments are significantly improved, and it can quickly switch between multiple targets and accurately complete the grasping task. This method not only improves the control accuracy of the robotic arm, but also provides a new technical path for future applications in industrial automation, intelligent manufacturing.
Power Grid Stability Analysis Based on Artificial Intelligence Convolutional Neural Networks
Authors: Ge Fangyin
Published: January 2025

Power grid stability is key to reliable operation. The rise of renewables and growing loads demand better methods to ensure power supply quality. To address these issues, this paper proposes a method for power grid stability analysis based on Convolutional Neural Networks (CNN). First, the original grid data is preprocessed, and classification features are one-hot encoded. Then, a deep learning model based on CNN is designed and trained. Finally, the effectiveness of the proposed method is verified through case analysis. The case study compares fully connected neural networks with CNN, and the results show that CNN outperforms fully connected networks in accuracy, precision, recall, and F1 score.
Melt Pool Monitoring in Arc Additive Manufacturing Using Multi-branch Residual Networks
Authors: Shu Long , Wang Jiale
Published: January 2025

Wire arc additive manufacturing (WAAM) is a promising technology in aerospace, automotive, and marine industries due to its high efficiency and cost-effectiveness. However, the dynamic behavior of the melt pool significantly affects the forming quality and requires real-time and accurate monitoring. In this paper, a novel multi-branch residual network for melt pool monitoring is proposed, which addresses the limitations of traditional methods and single-branch networks. The multi-branch structure effectively extracts multi-scale features, while the residual module enhances feature fusion and training stability. The lightweight architecture ensures real-time processing in industrial scenarios. Experiments on a self-built dataset of 6,000 images of three melt pool states demonstrate the superior performance of the proposed method, achieving 95.1% accuracy, 94.2% precision, and 13.1 milliseconds inference time. Comparative and ablation studies confirm the significant contributions of the multi-branch structure and residual module, enabling robust and efficient monitoring under complex conditions.
High-performance Divider Performance Improvement
Authors: Yan Zhaomeng
Published: January 2025

Based on the applications of high-performance dividers in research and high-tech fields as well as their important roles in research, this paper summarizes the methods for improving the performance of high-performance dividers. Through the analysis of high-performance divider schemes, this study investigates the shortcomings of ordinary dividers, with an emphasis on analyzing the operating methods of two ordinary dividers, namely the restoring remainder divider and the non-restoring remainder divider. This paper mainly analyzes how three types of high-performance dividers improve their performance, which are Radix-16 SRT divider, Goldschmidt algorithm divider, and Goldschmid double-precision floating-point divider. It illustrates from aspects such as area, parallel computing, etc. why these algorithms can enhance the performance and energy efficiency of dividers. This article aims to provide some directional assistance to those researching the performance of dividers. I hope that during their research, they can utilize this article to obtain useful information that will help them more smoothly conduct research on high-performance dividers and advance digital circuit design technology, especially in terms of improving computational speed, reducing latency, and optimizing power consumption.
Development of Steel Structures in the Context of Carbon Peaking and Carbon Neutrality
Authors: Qin Rui
Published: January 2025

This paper discusses the current development status and future trends of the steel structure industry in the context of peak carbon and carbon-neutral targets. Through literature review and data analysis, it highlights the steel structure's benefits in energy saving, emission reduction, and resource recycling. And puts forward strategies and suggestions to promote the development of the steel structure industry. The results of the study show that the steel structure industry plays an important role in coping with climate change and realizing green and low-carbon development, and policy support and technological innovation should be increased in the future to promote the healthy development of the steel structure industry.
A Review: Application of Nanomaterials in New Energy Batteries
Authors: Qian Jingjie
Published: January 2025

The advancement of nanomaterials is propelled by technological progress, multidisciplinary studies, and the practical requirements for application, backed robustly by governmental and industrial entities. Nanomaterials exhibit great potential in sectors like electronic devices, information technology, energy, the environment, and biomedical studies. This article examines how nanomaterials can be utilized in the development of new energy batteries. The current market has extensively utilized lithium-ion batteries, but they face issues such as cost, resource limitations, and safety concerns. These challenges have driven scientists to research alternative new energy batteries, such as lithium-sulfur batteries. Nanomaterials, with their unique properties and various classifications, have the potential to improve the efficiency of novel energy batteries and propel the progression of renewable energy. The article details the progress of nanomaterials in battery separators, electrodes, and other areas, addresses some of the challenges faced, and provides an outlook for the future
Low-Temperature Processed Perovskite Solar Devices with High Photoelectric Conversion Performance
Authors: Gu Ruochen
Published: January 2025

This study presents the development of high-performance perovskite solar cells (PSCs) processed via low-temperature methods, utilizing dimethylacetamide (DMAc) as a solvent. By comparing its performance with the standard dimethylformamide (DMF) under both high (100 C) and low (20 C) temperature conditions, we demonstrate that DMAc-based PSCs maintain exceptional quality even at reduced processing temperatures, a pivotal advancement for scalable and cost-effective manufacturing. Furthermore, the formation of uniform, high-quality perovskite films is readily achieved, which is crucial for efficient light harvesting and favorable charge carrier dynamics. Photoluminescence (PL) and X-ray diffraction (XRD) analyses reveal DMAc's superiority in trap state passivation, yielding fewer defects, higher crystallinity, and larger crystallite sizes than DMF. Furthermore, transient photovoltage (TPV) measurements analysis confirms extended charge carrier lifetimes in DMAc-containing PSCs, accounting for their enhanced stability and, on average, higher power conversion efficiencies (PCEs). This work underscores the potential of DMAc as a game-changing solvent for advancing perovskite solar cell technology toward high-efficiency, low-cost, and flexible devices, poised for commercialization in the photovoltaic industry
Accelerated colorimetric gas sensors with emerging robotic laboratories
Authors: Fang Ziqian
Published: January 2025

Chemical sensing refers to the detection and identification of chemical substances by converting chemical or physical properties of molecular or ionic species (i.e., analytes) into analytical signals. Recently, the emerging robotic laboratories, or self-driving labs, have played a crucial role by efficiently exploring a vast design space of the chemical gas sensors with the Design-Build-Test-Learn (DBTL) developing cycle, enhancing the experiment efficiency and consistency as well as tackling complex multivariable optimization. This integration allows for rapid and effective optimization of chemical sensing materials, paving the way for fast and on-demand development and deployment of new materials to application
The Wearable Devices about the Sodium Detection
Authors: Lu Yixuan
Published: January 2025

This article focuses on wearable devices which used for detecting sodium. Sodium is an important parameter for assessing the state of our body, and real-time monitoring is essential. The amount of sodium in sweat is important because the level could show more like hydration assessment, exercise performance, medical conditions, individual differences, heat-related illnesses, and optimizing hydration strategies. The measurement of sodium content involves iontophoresis for stimulating sweat and electrochemical analysis which will use ion-selective electrodes. To ensure the accuracy of the measurement, solutions to the increase in sweat were proposed, including consideration of individual differences, minimization of contamination, and control of temperature and environmental factors. The factors that will influence the result of the measurement need to be eliminated. Advancements in materials for micro circuits and circuit structures are also discussed. The development of a wearable device for real-time sodium monitoring holds promise for health management, and challenges such as accuracy and environmental factors are being addressed
Analysis on the Current Status of Ecological Protection and Water Use in the Yellow River Basin
Authors: Liu Yuxuan
Published: January 2025

With only 2% of the nation's water resources, the Yellow River plays a vital role in supporting the livelihoods of people and sustaining industrial and agricultural activities in the provinces and regions it flows through, making it the lifeline of north and northwest China. Addressing the ecological and environmental challenges in the Yellow River Basin and improving water resource management are key to the sustainable development of the surrounding provinces. This paper investigates the water resource issues and obstacles in the Yellow River Basin by examining the region's current ecological conditions. By assessing water resources in the upper, middle, and lower reaches of the river, along with water usage and ecological protection practices, it outlines successful strategies for sustainable water use, focusing on ecological preservation, tailoring approaches to local needs, and implementing targeted measures. Furthermore, it recommends strengthening social support for equitable water allocation and promoting the restructuring of industries within the Yellow River Basin. This can be achieved by improving water resource management systems, enhancing administrative regulations, advancing scientific and technological standards, strengthening the legal framework, raising public awareness, and establishing a compensation mechanism
Traffic Light Controller System Analysis based on FPGA
Authors: Cao Kejia
Published: January 2025

Nowadays, the economy has developed to a high level, the construction of urban infrastructure grows in importance, and the vehicle parc is increasing quickly in our country. The Urban traffic congestion problem becomes more and more serious. Then it is one of the valid solutions to solve traffic issue in the reality. On the other hand, with the development and innovate of Programmable logic technology, Field Programmable Gate Array (FPGA) is used in the digital system design widely and becomes booming development. As a result, this article researches the Traffic signal controllers based on FPGA. Starting from the design requirements, the traffic light controller system is divided into three main parts to design, and it is simulated by using Verilog HDL language. Finally, the program is downloaded to the FPGA chip for hardware verification. The simulation and hardware verification results demonstrate that the traffic light control system not only achieves conventional traffic command functions but also adjusts traffic timing to some extent based on changes in traffic flow during peak and off-peak hours. Additionally, it includes a feature to prioritize emergency vehicles under special circumstances, effectively enhancing intersection traffic efficiency
Analysis of the Application of Automation in Smart Industry
Authors: Ruan Shichen
Published: January 2025

This paper explores the roles of passive and active devices in intelligent industrial automation. The study proposes a model for converting the volume energy density of passive components to the mass energy density and describes the use of highly miniaturized on-chip passive devices using coplanar waveguide structures. Additionally, the paper discusses the application of low-profile Ku-band active phased array antennas for automation communication systems, which achieve optimum volume, weight, and power consumption. In general, this paper discusses the key role of passive and active devices in advancing intelligent industrial automation through the method of literature review. The research results show that the miniaturization of passive components and the versatility of active devices lay the foundation for the development of more compact, efficient, and powerful automation systems, and promote the continued development of intelligent industries
An Overview of the Development and Energy Management Strategies in Hybrid Electric Vehicles
Authors: Zhang Teng
Published: January 2025

With the intensification of the global greenhouse effect and the restriction of energy use in countries around the world, hybrid electric vehicle (HEV) is one of the important solutions and has become a research hotspot and development trend in today's automotive field. This study reviews the development history of hybrid electric vehicles, and also discusses key energy management strategies. Hybrid electric vehicles use both motor and internal combustion engines, through a unique power transmission system, significantly reducing fuel consumption while also achieving low emissions and high energy efficiency. The ultimate objective is to transition towards fully electric vehicles. However, the primary challenge currently facing hybrid vehicles is energy management optimization. Enhancing energy efficiency and environmental performance through precise regulation of the power output between the internal combustion engine and the electric motor is the core technology driving the advancement towards a greener and more efficient future
Dynamic Record Linking Using Multi-Agent Machine Learning: An Architecture for Noisy and Variable Datasets
Authors: Xu Yichen
Published: January 2025

The aim of this article is to present a dynamic record linkage solution using high level machine learning to solve the problems associated with noisy, inconsistent and dynamic data sets. Classic deterministic and probabilistic models fail to work in such environments because they are static and based on assumptions. Incorporating supervised learning algorithm, active learning, and ensemble techniques such as random forests and boosting allows the proposed structure to change in response to different data types and thus become more accurate and scaleable. Some of its highlights are feature selection to ensure match accuracy, clustering to support noisy inputs, and active learning to minimize reliance on large labeled datasets. Simulations with real data, such as government or healthcare data, show that compared with the traditional approach, linkage is significantly more accurate and efficient. The flexible model led to 15% higher F1-scores on noisy datasets and was scalable across large data sets. This work demonstrates how adaptive machine learning can revolutionize the modern record linkage tasks and provides a powerful and effective solution to ever-changing data conditions.
Research on Interactive Control Algorithms for Lower Limb Exoskeleton Rehabilitation Robots
Authors: Wang JunShi
Published: January 2025

Lower limb exoskeleton rehabilitation robots represent an important development direction in modern rehabilitation technology. By integrating various sensors and control algorithms, these robots effectively enhance the specificity and efficiency of rehabilitation training. This paper systematically analyzes several widely used control methods, including position-based, force feedback, bioelectrical signal, and intelligent control strategies. Each strategy has its unique features and addresses different issues in the interaction between the robot and the patient, thereby improving the effectiveness and efficiency of rehabilitation training. For instance, position control provides stability and repeatability, force control ensures compliance, bioelectrical signal control offers rapid responsiveness, and intelligent control exhibits adaptability. Future research will focus on combining the advantages of different strategies to develop composite control methods that enable more efficient and personalized rehabilitation training, enhancing patient recovery outcomes and experiences
Gallium-based liquid metal nanoparticles for drug delivery applications
Authors: Zhang Haiming
Published: January 2025

Drug delivery systems have been widely investigated over the past decades for their ability to enhance drug efficacy and reduce side effects. However, in order to be applicable to a wide range of diseases and drugs, research on diverse and effective controlled delivery systems is imminent. The specificities of gallium-based liquid metal nanoparticles (Ga-based LMPs), such as low toxicity, core-shell structure, mobility, and photothermal effect, make them full of potential for development in drug delivery. Functional gallium-based LMPs can be driven by physical or chemical stimuli for targeted drug transport to the lesion. This review introduces the recent research progress of Ga-based LMPs by summarizing its unique advantages in the field of drug delivery. At the same time, this paper introduces some Ga-based LMPs drug delivery opportunities in conjunction with its advantages and challenges. This review will provide some directions for the future development of Ga-based LMPs in the field of drug delivery
Design and implementation of MOD60 counter based on Multisim
Authors: Chen Haoran
Published: January 2025

This paper primarily discusses the design schemes of asynchronous and synchronous counters, finding the characteristics of each circuit, and comparing the differences between them. In an asynchronous counter, asynchronous counters are driven by the output of the preceding flip-flops, with signals propagating stage by stage, causing cumulative delays. Although it is simpler in structure, the delay problem becomes significant as the number of bits increases, limiting its use in high-speed applications. Rather than asynchronous counters, all flip-flops of synchronous counters are driven by the same clock signal simultaneously, ensuring data changes synchronously. This results in higher stability and lower latency, making it suitable for scenarios requiring precise timing control. This paper systematically analyzes the working principles, characteristics, advantages, and disadvantages of two types of counters. Using Multisim and Logisim to present the design of an asynchronous MOD-60 counter and a synchronous MOD-60 counter, providing details of their design principles and each unit of circuits. The results indicate that while asynchronous counters are suitable for low-speed, simple applications, synchronous counters are a more reasonable choice for high-speed, precise counting scenarios
Preparation of Memristor and Research of Resistance-Change Mechanisms
Authors: Zhou Kunying
Published: January 2025

The memristor, a recently developed electronic component, has the potential to address the limitations of data processing and storage in traditional von Neumann architecture computers. It is a promising substitute for traditional CMOS components in artificial neural networks due to its distinctive low power consumption, rapid response time, and non-volatile memory characteristics. The precise nature of the resistive change mechanism of the memristor remains unclear. The majority of research to date has focused on three main mechanisms: ionic, electronic and thermal. In regard to the selection of materials, the electrode components of memristors may be composed of metals, carbon-based materials, or conductive oxides, which possess the capacity to carry the current and engage in the resistive reaction. Memristors display a multitude of prospective applications in the field of memory devices and brain-like computing systems, given their superior characteristics. For instance, organic memristors may be employed in the biomedical sector for the production of wearable devices, given their affordability, simplicity of fabrication and biocompatibility. Furthermore, inorganic and organic materials can be combined, which is anticipated to facilitate the development of memristors with enhanced performance. These developments underscore the significance of memristors in next-generation computing and storage technologies
Analysis of aerodynamic characteristics of various airfoils under subsonic flow under ground effect
Authors: Fang Pengxiang
Published: January 2025

In this comprehensive study, we utilize ANSYS Fluent, a sophisticated fluid dynamics simulation tool employing the finite volume method, to address intricate aerodynamic computations. Leveraging ANSYS Meshing, we meticulously craft precise geometric models and meshes for airfoils, ensuring the fidelity of our simulations. This meticulous attention to detail is crucial for accurately capturing the complex aerodynamic phenomena involved in ground effect scenarios. Our research delves into the aerodynamic attributes of various airfoils, particularly under subsonic ground effect conditions. We conduct a rigorous comparative analysis of the pressure distribution, drag coefficient, and lift coefficient for the NACA4412, NACA0012, and RAE6-9CK airfoils. By analyzing these parameters, we gain a deeper understanding of how different airfoil designs interact with the ground, which is essential for optimizing the performance of ground-effect aircraft. The insights derived from this analysis are pivotal for refining the design of ground-effect aircraft. They reveal areas for improvement in current designs and guide the development of new aircraft models. Additionally, these insights underpin the rigorous development and testing of novel aircraft models, ultimately enhancing their performance, efficiency, and operational prowess. Overall, this research contributes significantly to the progression of aerospace engineering and the aviation sector. It provides a foundation for future research and development efforts in ground-effect aircraft and has the potential to lead to significant advancements in the performance and efficiency of these aircraft
Researches on lightweight body structure design and optimization of electric vehicles
Authors: Kong Weiyi
Published: January 2025

As environmental concerns grow and fuel prices continue to rise, electric vehicles (EVs) are gaining increasing dominance in the automotive market. This shift has prompted extensive research aimed at improving EVs performance, particularly through lightweight vehicle design. Lightweighting is crucial for enhancing efficiency, range, and overall performance, as reducing weight allows for less energy consumption and better battery usage. This paper examines seven key methods for vehicle lightweighting, ranging from advanced materials like carbon composites and aluminum alloys to innovative engineering techniques such as topology optimization and computational modeling. Each method contributes to reducing vehicle mass without compromising safety or structural integrity. The paper concludes by addressing the current challenges, such as the high cost of advanced materials, and exploring future directions. These include innovations in material science, improvements in manufacturing processes, and refining computational tools. Overall, lightweighting research remains critical to advancing the efficiency and sustainability of electric vehicles in a rapidly evolving market
Application of Perovskite Solar Cells in Extreme Environments
Authors: Li Bohan
Published: January 2025

Exploring the utilization of renewable energy has become the primary emphasis of energy research, with perovskite solar cells increasingly playing a significant role in this field. These cells have gained significant attention due to their rapid increase in efficiency and their potential to be produced using cost-effective methods. However, perovskite cells encounter challenges, particularly when they are exposed to extreme environmental conditions. Factors such as temperature variations, humidity, light intensity, and chemical exposure can significantly impact the stability and performance of perovskite cells. In this work, the application requirements and shutdown technology of perovskite solar cells (PSCs) in extreme environments (such as space and underwater) were discussed, which provides an important reference for further improving the performance and stability of PSCs in special environments.
Mobile Robot Environment Perception System Based on Multimodal Sensor Fusion
Authors: Wang Xiao
Published: January 2025

In the context of rapid technological advancement, mobile robots' applications are expanding across intelligent manufacturing, autonomous driving, and disaster rescue, demanding enhanced environmental perception capabilities. Environmental perception systems based on Multimodal Sensor Fusion technology effectively improve mobile robots' understanding and adaptability in complex environments. Multimodal sensor fusion integrates data from multiple sensors to overcome individual sensor limitations. Through analysis of data fusion algorithms and real-time processing technology, efficient information extraction and noise reduction enhance mobile robot adaptability in dynamic environments. Case studies demonstrate that environmental perception systems incorporating deep learning and computer vision technologies achieve high-precision obstacle recognition and path planning across diverse settings. The system improves complex scene comprehension and autonomous navigation capabilities through neural network-based feature extraction models. Through systematic theoretical frameworks and case analysis, the research explores multimodal sensor fusion's potential and practical effects in mobile robot environmental perception systems, providing fundamental data support and theoretical foundations for future research developments.
CFD Analysis of NACA2412 and NACA0012 at Low Reynolds (2.210*6) Numbers Based on ANSYS Fluent
Authors: Gong Zhuo
Published: January 2025

The paper is about analysing two-dimensional aerodynamic characteristics of NACA 2412 and NACA0012 aerofoils at Reynolds number of 2.210*6 using the CFD method. Numerical analysis was performed through ANSYS Fluent, a fluid simulation software based on the finite volume method. The geometry model and mesh of the aerofoil are established by ANSYS Meshing, and the simulation calculation is carried out based on the pressure solver. During simulation processing, the Spalart Almaras model is used based on the incompressible continuity equation and Navier-Stokes Equation. The aerodynamic characteristics such as pressure, velocity distribution, CL and Cd, are systematically analysed and compared for these two airfoils. The results of the report show that if the aircraft needs to fly smoothly between 6-12, the NACA 0012 is a better choice and if you need to generate higher lift at low speeds, the NACA 2412 May be more suitable. The result of this paper can be applied to aircraft design, and new aerofoil development, and guide two-dimensional CFD analysis to these aerofoils.