Yaoli Wang
Abstract: With the increasing demand for transistors that work in high-power, high-frequency, and high-voltage environments, diamond transistors are set to become an indispensable part of future transistor development. This article reviews the development history of hydrogen-terminated diamond transistors and silicon-terminated diamond transistors. Specifically, this article summarizes the invention of hydrogen-terminated and silicon-terminated diamond transistors, along with recent structural innovations …
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Shuning Cui
Abstract: Relations between Schottky contact and ohmic contact in diamond Schottky diode is attentively studied. Whether the metal-semiconductor contact forms metal carbide at high temperature on the interface of p-diamond is showed to determine the character of the contact. Formation of carbide and/or intermixing of metal and p-diamond at elevated temperature are believed to lower the Schottky barrier height and make Schottky contact “ohimicize” in a certain extent. This transformation can be …
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Zhengyang Li
Abstract: High-Voltage Direct Current (HVDC) transmission technology plays a pivotal role in modern power systems due to its capability for efficient long-distance power transmission. Compared to traditional High-Voltage Alternating Current (HVAC) transmission, HVDC systems offer significant advantages in reducing transmission losses, enhancing transmission capacity, and bolstering system stability. In recent years, the use of Silicon Carbide (SiC) materials in power electronic devices has gained …
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Jiaoyang Meng
Abstract: Recently, there has been an increased utilization of wide bandgap polymer electron donors in non-fullerene organic polymer solar cells. Consequently, scientists and engineers worldwide have shown substantial interest and research focus on all-polymer solar cells utilizing wide bandgap conjugated polymers. These advanced materials provide distinct benefits in terms of adjustable electronic properties, superior effectiveness, and possibility for cost-effective manufacturing, making them a central …
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Ouwei Dai
Abstract: Silicon, known for its high capacity, has become a key material in developing anodes for lithium-ion batteries (LIBs). However, the substantial increase in volume that silicon-based anodes undergo during the process of charging and discharging presents a significant obstacle. This expansion can lead to structural disintegration and loss of electrical conductivity. It also initiates undesirable parasitic reactions, all of which significantly reduce the cycle life of the battery. Consequently, …
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Chuanjie Wang
Abstract: Silicon carbide (SiC) power devices have gained significant attention due to their broad applications in high voltage, high frequency, and high temperature environments. Traditional silicon (Si) power devices, although well-established, face performance limitations that SiC devices can overcome. High-voltage 4H-SiC MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor) devices are essential for the advancement of power electronics, and this work focuses on their design and optimization. …
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Lihang Shi
Abstract: This paper presents an extensive overview of the current research progress of Virtual Reality (VR) games in the realm of cognitive abilities. With a particular emphasis on their utilization in cognitive rehabilitation and enhancement, it explores their profound effects. Various studies have established that VR games notably influence the mitigation of cognitive decline among older adults. This is primarily achieved by augmenting participation and compliance with rehabilitation programs. These …
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Yufei Liu
Abstract: Diamond PN junctions exhibit exceptional properties such as high electric breakdown field, the largest bandgap and the highest thermal conductivity compared to any known materials. These unique attributes make diamond highly suitable for high-power, high-frequency and harsh-environment applications. Currently, chemical vapor deposition (CVD) and high-pressure high-temperature (HPHT) methods can be used to synthesize diamond substrates. Among these, synthetic diamond produced by CVD has garnered …
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Xincheng Zhang
Abstract: As new type of biodegradable material, polylactic acid (PLA) is synthesized by plant resources. This material features high mechanical properties, biocompatibility and biodegradability. It is mainly used in agriculture, medicine, biology, environmental protection, engineering and other fields. With the progress of science and technology, new requirements and applications have been put forward for the properties of PLA material, thus it must be modified to improve its processing and application …
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Yuehang Ding
Abstract: Considerable financial resources have been allocated towards the design and development of wide and ultra-wide bandgap semiconductor circuits due to their use in power and radio frequency electronics. This is due to the fact that these circuits possess the capability to accomplish these tasks. Due to their minimal loss rates and capacity to rapidly switch high currents and voltages, these devices exhibit great versatility. The presence of parasitic effects in silicon-based CMOS circuits, which …
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Ao Zhang
Abstract: In this article, researchers have investigated the design and capability optimisation of SMPS with a particular emphasis on increasing the efficiency of power transfer and developing new manufacturing techniques. Nowadays, the PV industry mostly depends on silicon base technique, but it has many advantages such as high cost, low flexibility and great environment impact. By comparison, the structure of small molecular materials is easily duplicated and has a promising future in the field of PV …
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Zhaoyang Ye
Abstract: The spread of spam emails presents serious problems for both email security and user experience. This research aims to develop an effective spam email classification system utilizing machine learning techniques, specifically Logistic Regression and Naive Bayes, within the Apache Spark framework. The methodology encompasses a thorough preprocessing of the Enron email dataset. This process involves several critical steps: text cleaning to remove irrelevant information, tokenization to break down …
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Qichen Xue
Abstract: As the urgency to ensure energy sustainability and environmental preservation grows in response to climate change and escalating energy demands, transitioning from conventional grid systems to technologically advanced systems become imperative. The proliferation and complexity of data generated during energy production, conversion, measurement, and calculation pose significant challenges to traditional power system management methods. Consequently, the development of a new advanced grid system, …
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Wenjing Wang
Abstract: Over the past few decades, extensive exploration has been conducted on quantum dot light sources. Researchers have continuously improved the synthesis techniques of quantum dots, developing various materials and structures to enhance their optical performance and stability. This has also led to the expansion of application fields for quantum dot light sources. This paper provides a concise overview of the fundamental background knowledge on self-assembled quantum dot (QD) single-photon sources. …
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Haozheng Ling
Abstract: Memristors, a new kind of resistive device, have attracted considerable attention in recent years because of their nonvolatile nature, low energy consumption, and highly integrated performance. The key theory of the memristor is described, and its application in the structure of neural networks and arithmetic optimization is discussed. First, the fundamental models and operating properties of the memristor are evaluated, with emphasis on its voltage, current, and time variations. This paper …
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Lebin Hu, Xinyang Liu, Changwen Luan
Abstract: This study provides a comprehensive examination of machine learning models and deep learning algorithms for detecting financial fraud. We begin by introducing the basic concepts of commonly used algorithms, discussing their strengths and limitations in identifying fraudulent activities. The focus is on the unique capabilities of deep learning models, particularly Graph Neural Networks (GNNs), in handling large-scale and high-dimensional data, and their proficiency in enhancing fraud detection …
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Zihao Lian, Xitong Lin, Liuyuan Yin
Abstract: The advent of big data in the healthcare sector necessitates real-time data analysis and processing capabilities to enhance medical decision-making. This study explores the optimization of Apache Spark, a powerful big data processing framework, for healthcare big data management. The research aims to assess Apache Spark's performance in handling large volumes of healthcare data and its potential for integration with emerging technologies. Utilizing the Medical Information Mart for Intensive Care …
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Zitian Li
Abstract: The convergence of Artificial Intelligence (AI) and robotics has led to the emergence of embodied AI, where intelligent systems equipped with sensors and actuators interact with the physical world and operate alongside humans. These systems are transforming industries such as autonomous driving, healthcare, and household assistance. However, despite extensive research, embodied AI systems face significant limitations, including poor generalization and performance degradation in complex …
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Wanlin Gao
Abstract: Recently, there have been notable advancements in TTS technology, with researchers optimizing the efficiency, quality, and flexibility of speech generation through various models. This paper systematically explores end-to-end TTS models based on waveform generation, including Parallel WaveGAN, NaturalSpeech, and Multi-Band MelGAN, each of which has unique features in enhancing real-time generation capabilities and sound quality. Additionally, the paper discusses the development of speech …
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Daiyu Qian
Abstract: Since the beginning of this century, subways have increasingly occupied a higher share of daily transportation in Chinese cities. The growing network traffic has imposed higher demands on operating companies. Therefore, accurate passenger flow prediction is crucial for operational management and precise service level matching. With the maturity of machine learning methods, there are numerous cases of using these methods for passenger flow prediction. However, the influence of weather factors has …
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Mengyu Li
Abstract: The diagnosis and treatment of autism spectrum disorder (ASD) are highly challenging, demanding extensive preventative and intervention plans. With an emphasis on the use of artificial intelligence (AI) technology, this study aims to look into efficient prevention and therapy approaches for ASD. The study highlights the shortcomings in the present approaches and emphasizes the significance of early diagnosis and intervention. Using a mixed-method approach, the study looks at the effectiveness of …
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Yiwei Chu
Abstract: Solar power has been widely acknowledged to be the purest and most economical power in the 21 st century. Flexible wearable solar cells are becoming the first choice for power generation because of their high power to weight ratio, stable mechanics, affordable and practical applications. Additionally, the rapid advancement of wearable devices and transport has created a need for flexible and portable power sources with adequate mechanical stability to support such advanced technologies. …
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Rui Li
Abstract: Multi-sensory interaction technology has a wide range of applications in virtual environments, covering a variety of fields such as urban planning, healthcare, education, etc., and demonstrating its potential for significant value in these fields. This paper reveals how multi-sensory interaction technology can enhance user immersion and interaction experience by simulating multiple sensory experiences through specific application cases. The purpose of this review is to integrate the research and …
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Yongxuan Li
Abstract: An overview of the relationship between corporate financial performance (CFP) and environmental, social, and governance (ESG) concerns is given in this study from three angles: based on different industries, the impact of ESG dimensions, and the national development level. By reviewing and synthesizing the existing literature to examine how ESG performance affects a company's financial performance from various aspects. The analysis considers different ESG components, industry sectors, and the …
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Jing Cao
Abstract: Virtual Reality (VR) technology, characterized by immersive environments entirely generated by computers, has gained significant attention during the fifth information revolution. This paper explores the core elements of VR—Immersion, Interaction, and Imagination—as described by Burdea and Coiffet (1994). It emphasizes the importance of virtual embodiment in enhancing user experience within VR gaming. The development of technologies such as the CAVE system, head-mounted displays (HMDs), handheld …
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Xuanyi Xiang, Xinyue Zhang, Qingyi Huang, Jingyi Liu
Abstract: The intensity of solar activity varies with the solar cycle of about 11 years, reaching a peak during the solar maximum. Solar activity can affect space weather in ionospheric states and conditions related to shortwave radio propagation or satellite communications, which brings challenges to space exploration, communications, and weather forecasting. Therefore, accurate prediction of the start time and duration of the solar maximum becomes pivotal. In order to solve this problem, this research …
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Jifan Chen
Abstract: Compared to traditional three-dimensional semiconductors, two-dimensional semiconductors exhibit a multitude of distinctive electronic transport and optical properties at the nanoscale. These exceptional properties, such as enhanced electron mobility, direct bandgap, and quantum confinement effects, offer groundbreaking possibilities for the development of novel nanoelectronics and optoelectronics devices. The unique characteristics of 2D materials enable the creation of ultra-thin, flexible, …
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Zhaoxi Chen
Abstract: This study aims to predict traffic volumes in New York City using integrated datasets from transportation, weather, and collision records. The author employed multiple machine learning models, including Random Forest Regressor, XGBoost, LightGBM, and an Ensemble Model combining Random Forest and LightGBM, to utilize their strengths. The data preprocessing involved cleaning, merging, and encoding categorical features, resulting in a comprehensive dataset that integrated traffic volume, collision, …
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Zheng Jiang
Abstract: With the development of artificial intelligence, convolutional networks have powerful multi-dimensional data processing capabilities and can extract and process features in various images, which has great potential in the field of medical image processing. The development of convolutional neural networks has greatly promoted the development of computer aided diagnosis technology. This paper reviews the principle of four kinds of convolutional neural networks, including AlexNet, GoogleNet, U-Net, …
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Yunshang Wang
Abstract: The Myers-Briggs Type Indicator (MBTI) is a widely-used tool in psychology for determining personality types, playing a crucial role in fields like team building, communication, and personalized marketing. Despite its popularity, accurately classifying MBTI types using machine learning remains a significant challenge. This study focuses on addressing this challenge by exploring the effectiveness of logistic regression in MBTI classification tasks. Two approaches are used: four-times binary …
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Minhao Gao
Abstract: Depression is a common mental disorder that can lead to suicide in specific severe cases. A large number of suicides occur each year due to a lack of timely observational attention and treatment worldwide. This paper indicates that social media posts should be monitored for implicit depression and categorized immediately to reduce the risk of suicide and improve public mental health. In the data preprocessing, the NLTK library is used to slice the labeled social media text collected from Kaggle. …
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Ao Liu
Abstract: Deep learning has achieved impressive results in computer vision but typically requires extensive datasets, which are often costly and difficult to obtain, particularly in specialized domains like medical imaging and autonomous driving. To address this challenge, various image augmentation algorithms have been introduced, aimed at enhancing the size and diversity of training datasets. While model based techniques make use of picture production models, model-free techniques employ conventional …
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Moran Zeng
Abstract: The purpose of this research is to ensure the authenticity of information, guarantee the reliability and credibility of information sources, and prevent the spread of false information, fabricated data, and misleading content. In the academic field, detecting AI-generated papers, articles, and assignments helps maintain academic integrity, prevent academic fraud and plagiarism, and thus improve academic capabilities. This study summarize the characteristics of the three selected models, which …
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Yuxin Cai
Abstract: The volume of online consumer reviews has surged as e-commerce continues to grow, providing valuable insights for both consumers and business owners. Aspect Category Based Sentiment Analysis (ACSA) identifies sentiment polarity based on specific aspect categories in reviews. Despite extensive research in other languages, Cantonese remains underexplored due to its unique linguistic features and limited datasets. This study seeks to bridge this gap by fine-tuning a RoBERTa-based model for Aspect …
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Wenxi Wu
Abstract: Virtual reality technology has the characteristics of strong immersion, realistic experience, and rich imagination. Therefore, virtual reality technology has also been applied in many fields. Currently, its main application is in the gaming field.As technology advances, the demand for immersion in virtual reality games by players continues to grow. Simple sensory stimulation and experience cannot meet the practical needs of current players, and the iterative upgrade of virtual reality game …
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Zizhi Lin
Abstract: With the continuous progress of the era of science and technology and the increasing abundance of technology products, the influence of VR technology has attracted increasing attention, and people are constantly exploring the uses and possibilities of VR. The evolution history of virtual reality technology can be divided into four stages, and the simulation of sound shape dynamics is the first stage containing the idea of virtual reality. Virtual reality germination is the second stage. The …
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Zhouyang Li
Abstract: As VR technology continues to advance as an emerging technology, an increasing number of enterprises are recognizing the extensive development and application prospects of VR technology. This article provides a summary of the development history and principles of VR technology. This paper thoroughly examines the utilization of VR technology in the gaming industry, analyzing the advantages, current status, and challenges associated with VR technology in this field. VR games offer the unique …
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Yuyun Xiang
Abstract: With the rapid development of artificial intelligence and machine learning technologies, image recognition technology has become a key force driving progress in many fields. Deep learning and machine learning algorithms have made remarkable progress in image recognition. Therefore, this article deeply explores the role of image recognition technology in three aspects: autonomous driving, medical imaging and face recognition. This article concludes that autonomous driving technology mainly relies …
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Jiafeng Chen
Abstract: Stroke, characterized by high morbidity, mortality and disability, seriously jeopardizes human health. Timely and accurate prediction and diagnosis of the disease is of great significance. Machine learning can efficiently analyze large-scale datasets and shows great potential for application at various stages in the treatment of stroke disease. In this paper, we start from the common data processing, feature selection, model training and evaluation of the conventional application process of …
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Huili Huang
Abstract: Real estate and the housing market are vital for the U.S. economy, with factors such as economic growth, interest rates, government policies, and subsidies influencing housing prices. This paper will be focusing on the drinking water quality on housing prices by employing the existing researches of different methodologies. Hedonic property value analysis and production function have been used to assess the worth of environmental assets. One research has developed a household production function …
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Baihan Yu
Abstract: This study examines the multiple applications of Artificial Intelligence (AI) technologies in game design and development and their implications. First, this paper outlines the main types of machine learning, including supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning, and introduces deep learning methods such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). Subsequently, the …
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Mu He
Abstract: The advent of e-health systems has significantly addressed the challenges of inefficiencies, high operational costs, and limited accessibility in traditional healthcare systems. This paper explores the critical role of Natural Language Processing (NLP) in e-health systems, particularly the transformative potential of sentiment analysis in improving patient care and system efficiency. The study employs NLP techniques to analyze and interpret large volumes of healthcare data, utilizing sentiment …
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Yufan Bai
Abstract: California’s real estate market has been in the spotlight for its unique geography and economic advantages, and home prices have been volatile. Therefore, accurate prediction of house price increases is of great importance to home buyers, investors and policy makers. This paper utilizes the California house price dataset, combines macroeconomic indicators and micro property attributes, and analyzes house price prediction through random forest, decision tree and neural network models. The study …
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Wenxiao Chen, Zihan Gao
Abstract: Autonomous vehicles achieve motion perception and path planning through object recognition. With the integration of deep learning into object detection, numerous practical and innovative studies have emerged in this field. Considering both hardware costs and recognition accuracy, object detection algorithms can be categorized into vision-based and Light Detection and Ranging (LiDAR)-based approaches. This paper reviews classic literature and cutting-edge technologies of both methods, detailing …
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Yifan Lin, Sen Wang
Abstract: This study explores the prediction of stock price trends in the financial market, emphasizing the impact of investor sentiment and macroeconomic policies. Traditional research often uses mathematical, statistical, or deep learning methods to predict stock prices but overlooks the emotional factors in vast unstructured text data, such as financial news. This paper proposes a Bidirectional Encoder Representations from Transformers (BERT)-Transformer model that integrates sentiment analysis to …
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Yaping Pan
Abstract: Earthquakes pose severe disasters and losses due to their sudden and destructive nature, and despite extensive research, predicting earthquakes remains a significant challenge. Recent advancements in earthquake observation and geophysical methods have highlighted the potential of machine learning technologies in improving prediction accuracy. This study aims to explore earthquake distribution in China through machine learning methods, specifically logistic regression and random forest, to …
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Ruyi Xie
Abstract: The field of time series forecasting (TSF) increasingly leverages deep learning architectures. This study examines the latest advancements in Multi-layer Perceptron (MLP)-based models for TSF, focusing on the MLP Mixer, MLP Encoder-Decoder, and Frequency-Domain MLP models. Each model's principles are analyzed to identify commonalities and potential areas for improvement. These innovative approaches enhance the ability to capture features and global dependencies in complex and lengthy time series …
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Chang Yuan
Abstract: This study provides a comprehensive overview of advancements in Text-to-Image (TTI) generation through the application of Transformer models and Self-Attention Mechanisms. It begins with a review of the evolution of Generative Adversarial Networks (GANs) and highlights the benefits introduced by Self-Attention, such as improved contextual understanding and clearer image generation. The paper explores the theoretical foundations of Transformers and GANs, detailing how their integration can …
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Chang Chen
Abstract: Internet technology is developing rapidly today. It not only brings new experiences to people but also brings huge security risks. The attack methods of cyber criminals are becoming more and more complex and unpredictable. The rise of artificial intelligence offers promising solutions for detecting and mitigating network attacks, but challenges such as insufficient and imbalanced datasets continue to hinder the effectiveness of these models. Transfer learning has emerged as a valuable technique …
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Cenyue Yao
Abstract: Artificial intelligence has great potential value in the music industry. From the perspective of music recognition based on machine learning, there are numerous possibilities in the industry of music and computer science intersection, music composition and generation; music analysis and preprocessing; music education and interaction, etc. After elaborating on music analysis and preprocessing, a potent about musical instrument recognition can be done with artificial intelligence have discovered. …
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Yimin Wang
Abstract: Data visualization becomes an important tool for effective processing and analysis of large databases during epidemics, helping researchers, public health experts, and policymakers quickly identify trends, patterns, and anomalies by translating complex data into easy-to-understand graphs and charts. This study examines the application of Python and machine learning techniques to the analysis of outbreak data, specifically the methods used to process and analyze data during the COVID-19 outbreak. …
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Yangming Tang
Abstract: Nowadays, as the technology of AI is becoming more and applying in more fields, there rises some doubt about the safety of using AI. This paper explores the application of machine learning in the field of network security. The introduction provides an overview of machine learning and its importance in ensuring the security of networks. It also highlights the challenges and opportunities when implementing machine learning techniques in network security. The second section delves into the various …
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Shaoyang Qu
Abstract: This paper investigates recent advancements in integrating Generative Adversarial Networks (GAN) with Neural Radiance Fields (NeRF) for image generation and 3D reconstruction. This integration is pivotal for significantly enhancing the quality of image and 3D scene generation across diverse applications, including medical imaging, virtual reality, animation, and film production. The objective of this study is to summarize and compare existing methods, providing both theoretical and …
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Yixuan Li
Abstract: Long-term care insurance (LTCI) is important for addressing the needs of aging populations and increasing long-term care demand. China initiated its LTCI pilot in 2016 and expanded it in 2019. This study employs Natural Language Processing (NLP) to analyze the sentiment impact of policyholders on LTCI decisions. By classifying sentiments in comments from various Chinese provinces, this study trained a Long Short-Term Memory (LSTM)-based deep learning model using annotated data and validated its …
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Zehao Wu
Abstract: Human face is one of the most important features of human beings. In the information age, the face has personal information and emotional expression, social communication, public safety and other extremely important attributes. Due to the characteristics of inconspicuous facial features and small differences, traditional face recognition by manual training leads to low efficiency and high error rate. Based on the advantages of computer automation, face recognition technology has tended to be …
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Haoyi Li
Abstract: Synthetic Aperture Radar (SAR) originated from military needs during the Second World War. Today, this technology has become an important tool for Earth observation in many fields, including environmental monitoring, military reconnaissance, resource exploration, disaster monitoring, agricultural applications, marine research, and urban management. This article will elaborate on the basic principles of SAR, including its range and azimuth resolution, as well as the relevant techniques for …
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Ruiqi Qin
Abstract: Microwave radiometers are gaining increasing attention for their ability to measure the temperature inside biological tissues, a capability that is of great significance in medical applications such as cancer treatment and burn therapy. However, there is still a research gap in their precise application in these areas. This study aims to explore the feasibility of using microwave radiometers to detect subcutaneous tissue temperature by analyzing low-frequency microwave signals. A miniature …
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Mai Takada
Abstract: Electrocardiograms (ECGs) are essential for diagnosing cardiac diseases, and recording the heart's electrical activity across cycles. Despite their critical role, there remains a gap in understanding the detailed principles and historical development of ECGs. This article introduces the historical development, basic principles, and application of ECG in the diagnosis of heart diseases. The working principle of ECG is studied, including the depolarization and repolarization process of myocardial …
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Chuxi Zhou
Abstract: Natural Language Processing (NLP) is a pivotal area in artificial intelligence, aiming to make computers capable of understanding and generating human language. This study evaluates and compares three prominent NLP models—the Generative Pre-trained Transformer (GPT) model, Bidirectional Encoder Representations from Transformers (BERT) model, and Generalized Autoregressive Pretraining for Language Understanding (XLNet)—to determine their strengths, limitations, and suitability for various tasks. …
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Wenxing Wang
Abstract: The application of machine learning in cancer prediction has important academic value and practical significance, and can make important contributions to improving the accuracy and efficiency of early cancer detection. The article explores the key concepts of contemporary machine learning, the processes and steps involved in data processing, and its application in cancer prediction. It particularly focuses on the accuracy of different machine learning models in predicting specific cancers and …
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Yun Chen, Yufei Hu, Sixu Li, Chenxu Wang
Abstract: With the development of science and technology, scientists' demands for fineness in fields such as semiconductors, materials, and bioimaging are increasing day by day. Traditional electron microscopes have certain limitations in observing the microstructure of substances. The helium ion microscope (HIM) has a higher imaging resolution and more refined nano-processing capabilities, playing a breakthrough role in the development of science and technology. In this paper, the literature analysis …
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Yuyang Zhou
Abstract: Radio astronomy plays a crucial role in advancing the understanding of space objects by utilizing radio waves, allowing us to observe phenomena and celestial bodies that are otherwise invisible when using traditional optical telescopes. This technique, called Very Long Baseline Interferometry (VLBI), combines signals from different radio telescopes to give a much clearer picture. This paper talks about how VLBI works, including how it picks up signals, measures time delays, and fine-tunes these …
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Yuchen Wang
Abstract: In the article, the author mainly focuses on how to launch a rocket from the earth to go around the sun and return to the earth. The equation and solution of this motion are obtained by means of Newtonian mechanics, calculus and conic curve. To find the expression of the trajectory of the rocket, the article will obtain Kepler’s Law by using Newton’s Law, after setting a polar coordinate system. Similarly, plenty of mathematical methods are used to obtain the result in the article, hence, the …
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Zheyang Wang
Abstract: This paper evaluates the feasibility and advantages of implementing optical atomic clocks in Global Navigation Satellite System (GNSS). Traditional GNSS relies on atomic clocks that works on microwave frequencies, which, while reliable, have limitations in precision and stability. Optical atomic clocks, operating at higher frequencies and narrower linewidths, promise significantly enhanced precision and stability due to their utilization of highly stable lasers, atomic references, and optical …
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Zihan Zhang
Abstract: Since the discovery of the Rydberg atom in 1885, research on the Rydberg atom has presented numerous discoveries about the Rydberg atom. As the atoms has valence electron in a high principal quantum number state, Rydberg atoms can interact with each other in a unique way, such as dipole-dipole interactions, Rydberg blockade and anti-blockade. To reach the Rydberg state, it is usually necessary to use a laser to excite the atoms from their ground state. Due to the special characteristics about …
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Guowen Xu
Abstract: Whispering Gallery mode (WGM) optical microcavities represent a significant focus in current laser research. Initially, this paper elucidates the concept of WGM and its acoustic significance, before delving into its development in the optical field and its crucial role in optical devices. Subsequently, the author explores the theoretical foundations of WGM, elucidating the photon confinement effect due to total internal reflection. These optical microcavities are noted for their high symmetry …
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Qiuyu Cao
Abstract: This article first presents some background and facts about the development of the field of gas sensing with lasers. Subsequently, the relevant content about using lasers for gas sensing was introduced. The introduction starts with the technical system and laser light sources. Laser light sources include several important and widely used lasers. The research directions and content suitable were identified for different lasers based on the existing research progress of different light sources. …
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Zhexi Zhao
Abstract: The concept of Matrix Optics is explained in detail and some key matrices which are used in Optics are given, including ABCD matrices and Jones matrices. Some examples of matrices to model optical components are provided. The basic principles of Optical Communication Systems are explicated, along with their principal components. The key performance metrics are mentioned, each with a brief explanation: Bandwidth, signal-to-noise ratio, and bit error rate. The applications of Matrix Optics in …
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Qinghua Liu, Boshen Zhu, Jiran Wang, Tongtong Sun
Abstract: In recent years, with the popularization and technological progress of tennis, momentum has been an important indicator of changes in the players' state. Traditional evaluation methods cannot fully reflect their dynamic changes and multi-factor effects, so it is essential to establish a more accurate momentum evaluation model. In this study, seven key indicators, such as serve advantage, breakpoints, etc., were selected to measure momentum fluctuations in matches, and weight was assigned to each …
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Yongqi An, Yizhe Feng
Abstract: As a non-parametric regression technique widely applied across various disciplines, Gaussian Process Regression (GPR) faces certain challenges in the selection of the kernel function. To address this issue, this paper innovatively adopts a model aggregation strategy to dynamically determine the kernel function, rather than selecting a single model, thereby enhancing the model's adaptability and predictive power. Specifically, on one hand, the proposed method integrates Gaussian processes with …
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Di Wang, Qingyuan Cao, Yujun Liu, Shan Ma
Abstract: Solar thermal tower power is an innovative technology that uses a field of heliostats to convert solar energy into electricity. The ability to accurately compute the optical efficiency and thermal power output is a crucial aspect of effectively employing this technology, subsequently enhancing power generation efficiency through strategies such as optimizing the distribution of the heliostat field. An innovative approach for calculating the annual mean optical efficiency, annual mean output …
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Jialin Li, Binbin Li, Zheng Luo, Weikang Chen
Abstract: Rock bursts are one of the most common and hazardous disasters encountered in coal mining operations, particularly in China. The occurrence of rock bursts poses significant risks to the safety of miners and the structural integrity of mining operations. Consequently, coal mines are required to conduct extensive and frequent rock burst risk assessments, which contribute to the increasing workload and operational pressures on mine personnel. Addressing this challenge is critical for enhancing the …
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Yuanke Meng, Yusheng Lei, Yikun Kang, Yiyuan Zhao
Abstract: In this paper, this paper address the challenges of multibeam line measurement in the sea by first analyzing the correlation between two-dimensional (2D) and three-dimensional (3D) models through the construction of mathematical models. Based on these mathematical models, this paper further develop ocean models and measurement models. These models aid in determining the characteristics of different sea models, as well as the properties of measurement signals under various measurement modes and …
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Feiyang Ding, Rongjing Wang, Jiazheng Song, Yuxin Qian, Xiaohan Yang
Abstract: In the face of the global demand for carbon reduction, the construction of new energy power system has become the key. The traditional power system is facing the pressure of transformation, and the innovative application of new energy technology is imminent. This paper establishes an optimal design model for a heliostat mirror field, aiming at the efficient use of solar energy and the improvement of heat collection efficiency and performance. The model reduces power generation cost and enhances …
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Junmeng Zhang
Abstract: As multibeam bathymetry is widely applied to the detection of complex terrain on the seafloor, how to optimize the coverage width and overlap rate by reasonably setting the measurement parameters has become a key issue in improving the accuracy and efficiency of the measurement. Starting from the actual situation, this study establishes a spatial geometric model based on the seabed topography. It combines the MATLAB programming tool to accurately calculate and analyze the coverage width of …
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Qiaochu Li, Xinyu Zhuang
Abstract: Artificial Intelligence today demonstrates an astonishing productivity, and its development has become one of the directions for many countries. However, while developing, it is also necessary to consider the adverse impact of AI development on carbon emissions and to seek environments and regions suitable for AI development. To address this issue, this paper innovatively proposes the concept of "fertility" to describe the AI development potential of a region, and fully considers the adverse …
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Zhengyang Liu
Abstract: The habits of students, with a focus on smoking and alcohol consumption, about their academic performance, is an essential area of study. The findings of this study will seek to fill a significant gap in recent empirical evidence concerning the issue at hand. For the research, data from student questionnaires and academic records were used, while correlation and regression analyses were done to test these relationships. The findings show that high smoking and drinking frequency is significantly …
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Huang Huang
Abstract: Artificial Intelligence (AI) has rapidly developed across multiple fields, for example, in the medical field, various diseases are prevented, diagnosed, and classified. In the financial field, the trend of some stocks is predicted. In the education field, teachers are assisted in teaching and grading homework. This paper provides a comprehensive analysis of the “2024 AI Index Report,” which offers a detailed account of the current state of AI, including technological advancements, public …
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Junyang Xu
Abstract: With the rapid development of computer technology, the application of image recognition technology and machine learning technology in society has become more and more proven. Through consulting a large number of data and literature, this paper probes into the development status of image recognition technology and its future development trend and shortcomings. This paper concludes that there is a certain advanced technology development at present, and machine learning and image recognition are …
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Weixuan Feng
Abstract: The basic concepts of the Big Bang theory and the inflation theory are introduced in this paper. Besides, this paper concludes the current research on modern cosmology, especially for the Big Bang theory and the inflation model. In addition, some current and future Cosmic Microwave Background (CMB) experiments are also summarised. In the final part, some new unsolved problems and interdisciplinary connections in modern cosmology related to the Big Bang theory and the inflation model are …
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Zhujia Kuang
Abstract: In recent years, the advancement of radio astronomy has played a critical role in the exploration of space. The development of large-scale radio telescopes, such as the Five-hundred-meter Aperture Spherical Telescope (FAST) in China, has enabled astronomers to capture high-resolution images of celestial bodies and improve people's understanding of the universe. However, challenges remain in achieving higher precision and sensitivity in astronomical observations. This review paper provides an …
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David He
Abstract: Autism, a neurological disorder and developmental impairment, affects roughly 1 in 36 children in the US. However, relatively few machine learning algorithms, the majority being Logistic Regression models, have been used to predict autism using national data. In this study, other than the Logistic Regression algorithm, four other Machine Learning (ML) algorithms, namely the Random Forest, KNN, Extreme Gradient Boosting, and Support Vector Classifier algorithms, are applied to the NSCH data …
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Helin Yang
Abstract: With the exploitation of resources and environmental pollution, the Earth has suffered countless damages. As a result, there are more and more environmental problems such as the greenhouse effect and desertification. People only have one home, one Earth, so if the Earth becomes extinct, people will not exist anymore. Therefore, people need to repair and protect the planet. Humans have tried many ways to protect the Earth, but some damage is irreversible. Thus, to find another home and save …
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Aiming Zhan
Abstract: This document delves into the theoretical foundation and design principles of nuclear weapons, commencing with an exploration of the characteristics of fissile materials. Due to the high level of confidentiality of nuclear weapons, their specific details cannot be known by the vast majority of people, but this article focuses solely on their theoretical analysis. It elucidates the fundamental mechanisms of nuclear reactions, introducing the concept of nuclear criticality—the point at which a …
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Yiting Wang
Abstract: The interaction between supernova explosions and black hole formation is a significant study in astrophysics, explaining the map of cosmic evolution. This study delves into the late stages of a star's life cycle, the evolution of white dwarfs and neutron stars, and the early stages of black hole formation. Through the fusion of theory and data observation, the study has deepened the understanding of stellar evolution cycles and revealed the complex process of black hole origin, as well as the …
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Jiayang Li
Abstract: The study of near-Earth asteroids (NEAs) is vital for understanding the solar system and enhancing planetary defense. By researching these asteroids, scientists gain valuable insights into planetary evolution and impact history, aiding in the prediction and prevention of potential future threats. This article introduces how advancements in technology have enabled more precise classification and analysis of NEAs, such as categorizing them into groups like Amor, Apollo, and Aten. It points out …
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Enzheng Su
Abstract: Visual object tracking is one of the important topics in computer vision: given a target object in the first frame of a video, follow this target object on subsequent frames. Its applications are found in autonomous driving, human-computer interaction, military operations, and game development. However interesting these applications may be, the implementation remains very challenging because occlusions happen among other factors like scale variations or rotations that require a tracker to be …
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Yuhan Xue
Abstract: As a matter of fact, astronomical research depends heavily on distance measurement between the Earth and celestial objects, so it’s crucial to employ effective method along with advanced instrument for distance measurement. This study talks about the three most commonly used strategies to measure distance in space. Stellar parallax, based on trigonometry and the concept of stereoscopic vision, is the most conventional method to measure the distances within the Milky Way. Cepheid Variables, with …
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Ruidong Tian
Abstract: The search for exoplanets, particularly Earth-like planets, has garnered significant attention as potential second homes for human beings. Highlights of the urgency of finding alternative habitable planets due to the dire consequences of global warming and climate change on Earth. This underscores the importance of exoplanet research and the potential it holds for humanity's future. This paper delves into the two fundamental methods used in the discovery of exoplanets include the transit method …
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Xiaoxi Zhao
Abstract: The exoplanet study is important for exploring life's origins in the universe. With the development of astronomical observation technology, more and more exoplanets have been discovered, and the exploration of habitable planets and the study of planetary atmospheres have become focal areas of study. In this paper, the transit and radial velocity methods for finding exoplanets are introduced and analysed in detail, by introducing the principles of these two methods and showing the calculation …
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Zhenming Fan, Zichen Huang
Abstract: This paper presents the development and application of a Python program designed to simulate the orbital trajectory of a lunar probe using the fourth-order Runge-Kutta (RK4) method, a method known for its accuracy and computational efficiency. The program models the entire journey of a lunar probe, from its initial launch on the Earth to its stable circular orbit around the Moon. By allowing users to input specific parameters for acceleration and deceleration phases, the program generates …
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Zichen Huang
Abstract: This paper Since NASA launched the Transiting Exoplanet Survey Satellite (TESS) in 2018, many exoplanets beyond the solar system have been discovered. The TESS mission has collected a magnificent amount of photometric data for scientists to analyze and its instrument observes more than 200,000 target stars in its mission. Scientists identify and analyze the patterns of light curve data for each target and determine if it is a planetary candidate or false positive due to an eclipsing binary star …
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Jialun Chen
Abstract: Loan defaults pose significant threats to financial institutions' financial stability and reputation. Although existing risk assessment models have addressed this issue to some extent, they exhibit significant limitations when dealing with large-scale, high-dimensional data. Therefore, developing an advanced model that can predict loan defaults with higher accuracy is crucial. This paper aims to optimize loan default prediction by combining innovative algorithms and models to enhance the risk …
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Mingjie Guo
Abstract: Boron neutron capture therapy trials, BNCT trials, took place in the United States firstly, BNCT was still far from mainstream medicine at that time [1]. However, in recent years, BNCT has already been applied in the therapy of many major diseases, including cancer, and recurrent glioma for example. BNCT is an extremely effective cancer treatment, which has a unique property of tumor-cell-selective heavy-particle irradiation. BNCT can form large dose gradients between cancer cells and normal …
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Jianzhang Li
Abstract: Machine learning classification models have been widely used in gene identification tasks. However, high-dimensional gene loci and label imbalance are still urgent problems to be solved. To this end, this paper proposes a classification model that combines combinatorial sampling and random forest feature selection. This method applies random forest to randomly selected subsamples for feature selection, aiming to retain effective prediction information and alleviate the impact of the curse of …
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Zizhou Fang
Abstract: To explore the intrinsic patterns and characteristics of the generation and dissemination of online public opinion in a big data environment, this paper collected the top 100 most influential and high-ranking public events from 2022. After quantifying these events with relevant indicators, we employed the classic K-means clustering algorithm in SPSS to perform a cluster analysis on these high-impact 2022 events. This analysis yielded several distinct categories of high-interest online public …
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Xiaomeng Li
Abstract: In the era of big data, data has become a national strategic resource, in which patent data represents core technology and core competitiveness. Identifying and mining core patent data is helpful to analyze the technical layout and development trend of an industry and an enterprise. From the perspective of complex network science, a patent citation network is constructed and visualized, a core patent data identification method is proposed, and empirical analysis is conducted on the …
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Zhaowen Gu
Abstract: Since the current methods for precise underwater navigation are either insufficient in terms of accuracy or environmentally unfriendly, C-SLAM aims to address the critical issue of underwater localization for Uncrewed Underwater Vehicles (UUVs) undertaking seabed surveys. To improve the accuracy of navigation and overall operational efficiency, we’ll use Simultaneous Localization and Mapping (SLAM) techniques, which can achieve precise localization by looking at matching landmarks and Inertial …
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