Yuxuan Wang
Abstract: The main way to get emotional data has been through how they looked, which are able to interact a variety of feelings like joy, grief, fear, rage, disgust, and surprise. These expressive emotions are vital to communication due to their enable people to better understand one another's thoughts and desires. Therefore, we thought that we could utilize technologies such as computer vision to obtain images of students' expressions in the classroom through cameras and other related devices. In order …
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Jiayi Hao
Abstract: In recent years, deep learning technology has been exploited to create fake videos, leading to the widespread presence of deepfake content on the Internet. This technology facilitates the production of counterfeit content, including pornographic films, fabricated news, and political misinformation, by altering or substituting the facial data, expressions, and body movements in original videos, as well as synthesizing voices of specific individuals. Various generative tools, such as generative …
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Senyi Gong
Abstract: Digital signatures are essential for verifying the authenticity and integrity of information, thus facilitating digital authentication. The Elliptic Curve Digital Signature Algorithm (ECDSA) and the Digital Signature Algorithm (DSA) play critical roles in the field of digital signatures. This paper explores the conceptual frameworks and mathematical underpinnings of these algorithms, providing an in-depth analysis of their advantages and disadvantages with a focus on computational time …
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Shaoxukang Liu, Houjiang Liu, Hong Cao
Abstract: Momentum is crucial in tennis matches, influencing player performance and match outcomes. However, quantifying and evaluating momentum has long been a challenge in sports science research. This study aims to quantify momentum in tennis matches by establishing a hierarchical analysis-based model for momentum flow. The model analyzes factors affecting momentum through five criteria: Service Level, Catch Level, Competition Result, Finishing Ability, and Winning Streak, with respective weights of …
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Yufei Li, Yujie Xi, Xin Zhou
Abstract: With the advent of the era of big data and artificial intelligence, predicting and managing the remaining service life of aero-engines has become a key challenge, which has a direct impact on the enhancement of autonomous control capabilities. In this paper, a new deep learning model combining a one-dimensional convolutional neural network (1D-CNN) and a bidirectional long and short-term memory network (BiLSTM) is proposed to efficiently handle dynamic and uncertain engine health state data. The …
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Jinjin Xu
Abstract: With the development of modern electronic technology, the electromagnetic environment is becoming increasingly complex, which poses a severe challenge to the normal work of radar, communication and other systems. Polarization sensitive array can more effectively distinguish and suppress interference signals by using polarization information of electromagnetic waves, and improve the signal-to-noise ratio (SNR) and anti-interference ability of the system. Conformal array can be closely attached to …
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Shenglong Zhou
Abstract: In the era of digital transformation, marked by the widespread adoption of cloud-based technologies such as cloud computing and storage, ensuring data security and protecting user privacy have emerged as critical industry concerns. Fully Homomorphic Encryption (FHE) addresses these issues by allowing various computations to be performed on ciphertexts without the need for decryption, thus safeguarding data security and privacy. This paper explores the mathematical and algorithmic foundations …
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Dingshan Liu
Abstract: This paper examines the impact and emerging prospects of generative artificial intelligence (AI) content creation (AIGC) within the educational sector. As AI technology continues to evolve rapidly, the potential for AIGC to revolutionize educational practices has garnered significant interest and scholarly focus. AIGC is proving instrumental in developing customized educational content, facilitating personalized learning experiences, and enhancing assessment methods. These capabilities have the …
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Bonan Feng
Abstract: As deepfaking technology advances, it increasingly facilitates the seamless splicing of a person's voice, facial expressions, and body movements into source images or videos to create hyper-realistic virtual content. This growing technological sophistication, paired with the open-source nature of neural network algorithms, has unfortunately led to the exploitation of deepfake technology by individuals for illicit activities, seeking financial gain. This situation highlights the urgent necessity …
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Lixiao Dong
Abstract: Since the 21st century, with the continuous development and progress of science and technology, the possibility of fire danger is also rising, the requirements of public fire safety management have also been improved accordingly, and the problems in its fire safety management work make it difficult to meet the management requirements. The selection of firefighters has also become the top priority of management, good psychological quality of firefighters can keep calm in the face of fire …
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Jiayi Zhang
Abstract: With machine learning being widely used in many fields. In this paper, we study how machine learning methods can be used to make predictions in financial problems and analyze the applications.Machine learning is a branch of artificial intelligence that enables computer systems to learn from data and make decisions or predictions without being explicitly programmed at every step. Machine learning models are trained on large amounts of data to discover patterns and relationships in the data and …
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Liang Zhou
Abstract: This paper addresses the issues of increasing traffic volume leading to frequent traffic congestion and accidents by studying the effectiveness of occluded vehicle detection based on the YOLOv5 algorithm. The aim is to explore the performance of this algorithm in various occlusion scenarios. Firstly, we introduce the occluded vehicle images used for testing and describe different types of occlusions in detail. Then, the basic principles and construction process of the YOLOv5 algorithm are …
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Yichen Ding, Hangyu Zhou
Abstract: The underwater environment is intricate, and light stands as one of the foremost influences. When the model trained with fish pictures under ideal conditions is applied to real underwater recognition, the influence of light will challenge the recognition accuracy, and it is costly to collect new underwater fish datasets. In this paper, Data Augmentation is applied to enhance the model's accuracy for underwater fish recognition. This paper begins by introducing the Residual Network (ResNet) …
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Yingcheng Zhang
Abstract: This article examines a speech emotion recognition (SER) technique based on the enhanced one-dimensional convolution neural network ResSE_CNN1D. With the artificial intelligence developing rapidly, SER has a profound impact in many areas. The model of this article is used to extract the characteristics of the input data through opensmile, and is sent into the ResSE_CNN1D model, which is eventually classified by the softmax activation function and obtains the final results. The key to this model …
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Wenlong Gan
Abstract: Semiconductor wafers are widely used in integrated circuit chips. Because of the complex production process, it is easy to cause various defects. Therefore, the defect detection of semiconductor wafers is an important means to ensure their yield and productivity. This paper mainly expounds on the detection method of wafer defects combined with the machine vision algorithm, including the CNN model, and the classification of the learning-based methods. Current problems and future prospects for …
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Yuyang Wang
Abstract: The integration of Field Programmable Gate Arrays (FPGAs) into the design of digital taximeters signifies a transformative step forward in the field of Electronic Design Automation (EDA), catering to the evolving needs of urban transportation systems. This paper details the development and implementation of an FPGA-based digital taximeter that aims to enhance fare calculation accuracy, operational reliability, and adaptability to regulatory changes through the use of sophisticated technology. …
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Jiawen Shi
Abstract: Visual cryptography represents a sophisticated and innovative approach to secure information sharing, gaining traction within the field of information security. This technology adeptly transforms sensitive data into visually interpretable graphics or images. These images are then segmented into multiple independent parts, each distributed among different stakeholders. This strategy ensures that no single party can access the complete data without collaboration, thereby enhancing security. This …
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Tianrun Niu
Abstract: This paper introduces a comprehensive analytical framework designed to assess the efficacy of blockchain technology in financial accounting and its broader implications for the financial sector. The analysis explores how blockchain can revolutionize financial accounting by enhancing both efficiency and accuracy, facilitating real-time financial reporting, and expediting audit processes. It also examines blockchain's current deployment across various financial domains, including insurance, …
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Chuanyue Zhang
Abstract: In the digital age, secure storage and communication of information are crucial aspects of everyday life, drawing significant global interest. Steganography serves as a pivotal method for concealing private information within various media forms—such as images, videos, and text—enabling secure information transmission. This paper delineates the distinctions between information hiding and encryption and delves into image steganography. The focus here is on spatial-based image steganography …
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Zhengqi Hu
Abstract: In today's digital age, people often use images to convey information. However, during the process of sending images, they can become damaged for various reasons, causing the images to lose their original meaning. In such cases, image repair is necessary to restore the damaged areas to their original, undamaged appearance. Traditional image repair methods often struggle to produce effective results for highly damaged images. However, image repair using deep learning techniques can address these …
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Jingxing Zhang
Abstract: Data augmentation is a technical method that generates additional data samples by applying different transformations and processes to the original training data. It aims to increase the size and diversity of the dataset, thus improving the models' generalization ability. This paper provides a detailed introduction to geometric transformations, data mixing, automated data augmentation methods, and generative adversarial methods. Geometric transformations manipulate the spatial configuration of …
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Xueqing Zou
Abstract: The paper examines the evolution and impact of generative artificial intelligence (AI) technology in the field of painting, tracing its ascent from the early 21st century. It highlights pivotal developments in AI-generated content (AIGC), starting with Harold Cohen's "AARON" program in the early 1990s, progressing to Yang Zhiping's introduction of generative adversarial networks (GANs) in 2000, and culminating in Robbie Barrat's innovative applications in 2018. These milestones underscore the …
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Siran Yang
Abstract: With the rapid development of information technology, the application of intelligent recommender systems in various fields has become more and more extensive, and vocational rehabilitation, as a field focusing on personalized services, faces the challenge of how to effectively use big data and intelligent algorithms to enhance the rehabilitation effect. This paper discusses the design principles and key technologies of intelligent recommender system in vocational rehabilitation, combining …
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Linjie Tang, Kangyu Chen
Abstract: In tennis, there is an increasing emphasis on the significance of “momentum,” particularly in comprehending and effectively using this phenomenon in a scientific manner. However, The existence of momentum in competitions is sometimes challenging to scientifically prove. This work strives to develop techniques based on random forest to quantify momentum and predict players’ winning rates. Upon analysis, the paper extracts three features that have a significant impact on the player’s winning rate …
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Ziyi Xu, Qiya Shu, Yilan Ye
Abstract: Momentum has been widely recognized as a psychological factor affecting athletes' performance during sports events. Quantifying the momentum of both athletes in a match and predicting its future trends and reversals can provide effective information for coaches to make tactical decisions during a match. In this paper, taking the Wimbledon dataset as an example, the quantitative model of momentum is firstly constructed by the rank-sum-ratio evaluation method based on EWMA. Subsequently, this …
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Xueyu Zhu, Kaixing Liu
Abstract: In this paper, a Momentum Scoring Model is developed to quantify the abstract concept of Momentum through a set of important factors such as the base point, the hold point, and the break point. The model has the flexibility to capture player's in-game scoring changes with high accuracy and has a visualization process that is easy for tennis coaches and tennis players to understand. In order to statistically test whether momentum score changes are beyond random fluctuations, this paper validates …
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Haoming Tian, Ye Zhang, Runduo Ding
Abstract: The changes in momentum in a tennis tournament have a significant impact on players' performance and the outcome of the match. The application of big data and machine learning techniques can effectively enhance the accuracy of predicting these dynamic changes. This article aims to delve into the impact of momentum on matches and how it can be leveraged to help players achieve success. Firstly, this paper determines the confidence level of each indicator through multiple logistic regression and …
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Sihao Wang, Jiawei Xu, Haocheng Yang
Abstract: In a pioneering study of lamprey population dynamics, we employ an enhanced Lotka-Volterra model to illuminate the profound influence of sex ratio shifts on ecosystems. This exploration delves into how such changes affect resource availability, ecosystem equilibrium, and sustainability. We employ dynamic differential equations to simulate population fluctuations among males, females, and predators, incorporating elements like birth rate, mortality rate, competition coefficient, mating success …
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Ronghang Zhang
Abstract: This paper studies the sex ratio and resource availability of lamprey population, through the predator model and Logistic model of lamprey population dynamic simulation. Differential equations were used to dynamically describe the dynamic changes within lampreys population, and then the effects of changes in sex ratio on the food chain, population reproduction rate, habitat occupation and resource availability were analyzed. Optimize and analyze the population dynamic change model to simulate …
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Lige Deng
Abstract: This article uses the distribution data of rookie stations in Jinan City to explore the allocation problem of express delivery transportation networks. Firstly, in response to the uneven spatial layout of rookie Station, a corresponding evaluation index system was established based on K-means and TOPSIS models. The results showed that rookie Station exhibited characteristics of agglomeration in the central urban area and dispersion in the remote urban area. Secondly, by establishing a Floyd …
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Xinyue Wang
Abstract: More and more people like tennis, and the demand for the accuracy of predicting the results of tennis matches in sports betting is getting higher and higher. In this paper, a model is built to predict the results of tennis matches. In this paper, we first use the random forest model to analyze the factors that will have an impact on the outcome of the game, and the authors have selected out five factors that may have an impact on the outcome, which are: break of serve, Serve, Score, Net points , …
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Wenzhuang Liu, Dehui Xu, Xinyu Wang, Ruiqian Sun
Abstract: With the development of Internet technology, e-commerce has become the primary choice for consumers to shop, and the huge order transaction volume has generated logistics problems. As an important part of the logistics network, the sorting platform is essential to improve its management efficiency. To enhance the efficiency of the sorting center, the topological relationship diagram is used to show the logistics network, and the cargo volume of the sorting center in the next 30 days and every …
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Xinyu Gan, Min Zhang, Fuyao Meng
Abstract: As an important animal model for the study of biological evolution and disease, lamprey has attracted the attention of many scholars. Its variable sex ratio is also becoming the focus of studying because of the impact of ecological system. This paper utilizes mathematical method, and establishes the Lotka-Volterra Model to simulate the variations of the sex ratio among lamprey larvae populations. Additionally, Holling II function and Weak Alley Effect are adopted to establish a Predator-Prey …
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Jiawei Tian, Yuhang Yang
Abstract: The global situation of the world's submersible technology is experiencing a boom, with countries competing to develop advanced submersible equipment to explore the deep sea, undersea resources, and uncharted territories. With the wide range of applications of submersibles in various fields, the risks of communication loss and mechanical failures faced during their missions require the establishment of accurate predictive models of submersible positions to ensure safe and efficient rescue. In …
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Yufeng Liu, Yiming Ma, Shichao Liu
Abstract: Tennis, as one of the most popular sports worldwide, includes exciting matches between players. In some matches, score advantage can swing constantly from one side to another. These score swings may impact players’ performance and the result. To accurately predict the swings during a match between players, the article aims at building a score swing prediction model based on ID3 algorithm and logistic regression algorithm. The article will focus on analyzing tennis players’ behaviors and …
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Jinbing Ha, Yamei Gao
Abstract: In this paper, a short video popularity prediction model MFMA is designed based on Multilayer Perceptron (MLP) and artificial intelligence, and the popularity prediction in saturation is modeled as a regression problem. Through multimodal fusion, the four video attributes of visual, auditory, text, and social features are compressed as the input of the network to the greatest extent. Using nMSE and SRC as evaluation indicators, compared with other classical regression algorithms and evaluating …
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Chuhao Zhou
Abstract: With time going by, depression is getting more and more concern from society. With depression, they don’t have stable emotions, which leads to a problem that they tend to feel hopeless and sometimes even drop into despair when they’re viewing webs. Apart from that, there’re also lots of people with depression teies. And lots of people are still suffering from the pain of the disease and the effects of depression.Therefore, This study is aimed to design a website for those people with depression …
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Yu Zhang
Abstract: In recent years, physical layer security has become one of the core technologies for wireless communication system security. Physical layer encryption is based on the inherent reciprocity, time-varying, spatial uniqueness and unpredictability of wireless communication systems to generate keys, which are naturally unforgeable and steganography-proof. However, the research of physical layer key generation technology also faces many challenges, such as the problem of poor key generation performance …
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Wenfei Zhao, Xinyang Li, Zhaoxin Li
Abstract: With the rapid development of logistics industry, logistics sorting center, as a key node in e-commerce logistics network, its cargo volume prediction and personnel scheduling strategy are of great significance to improve operational efficiency and reduce costs. The purpose of this study is to deeply analyze the cargo volume data of 57 sorting centers through machine learning method, establish an accurate cargo volume prediction model, and optimize the personnel scheduling strategy based on the …
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Zhiyao Ti
Abstract: Stock market prediction (SMP) is one of the most important areas in finance that greatly helps investors and financial institutions to anticipate market fluctuations and make wise decisions. This becomes very important in view of the potential challenge of obtaining optimum revenues and effective portfolio management strategies in view of the volatile market environments typically governed by underlying economic and socio-political influences. This paper proceeds to categorize stock prediction …
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Haolun Zhang
Abstract: The research topic of this paper is the field of credit card anti-fraud, using the European credit card data of the past two days in September 2018 for research, describing the data distribution through exploratory data analysis, data normalization, and finally using logistic regression for anti-fraud identification prediction.
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Yang Wang
Abstract: In recent years, with the expansion of the game market and the rapid growth of game users, the game market has great potential. At the same time, open world games are loved by the vast majority of users. [Purpose/Significance] Explore the factors that affect the immersion of players in open world games, drive the improvement of the quality of open world games, help improve the industrial ecology, and achieve richer functional values. [Research design/Methods] Taking the open world adventure …
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Siyi Du, Sihan Qiu
Abstract: As a key index to measure product quality and processability, the hardness of cold-rolled strip steel has an important influence on the production efficiency of iron and steel enterprises. However, due to the coupling between the process parameters at each stage of the continuous annealing process, and the setting of traditional process parameters depending on the experience of the operator, the lack of scientific and systematic optimization methods, which easily leads to the problem of high …
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Wenpeng Liu, Bin Liu, Xiaoli Huang
Abstract: In recent years, the UAV technology has developed rapidly and is widely used in military, civil and scientific research fields. In order to avoid external electromagnetic interference, the bearings-only passive positioning method is usually used to adjust the position of the UAV to maintain the formation.In this study, according to the circular formation of Uavs, the positioning model of the received signal of Uavs on the excellent arc and the positioning model of the received signal of Uavs on …
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Lei Tang, Yining Zhou, Peilan Zhao
Abstract: Accurate forecasting of international air cargo volumes is crucial for air cargo carriers, which optimizes operational efficiency and profitability and strengthens market competitiveness and risk response capabilities. This study focuses on the open-source cargo data of over 100 international airlines in India from January 2015 to March 2017. Firstly, the missing data must be dealt with. Then, histograms and probability density plots are used to depict the distribution of the cargo volume and …
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Zhihua Deng
Abstract: In the twenty-first century, the "double carbon" plan is advancing steadily. Energy saving and emission reduction is one of the key points of the plan. A power grid independent park, if energy storage equipment can be configured, it can greatly improve the park microgrid power utilization, in order to achieve the purpose of energy saving. Therefore, research on the optimization of the proportion of power grid and microgrid in the park and the optimization of the configuration of energy storage …
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Hanjing Lan, Zhenlong Zhao, Qin Wang
Abstract: With the growing global energy demand and worsening environmental issues, microgrids have gained attention for integrating renewable energy. However, their economic operation is challenged by the volatility of renewable energy, making efficient operation a key research focus. This study collected and integrated microgrid data from three parks and established a microgrid energy storage optimization model using the NSWOA algorithm. Economic indices were calculated through methods like the …
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Yang Chen, Haitao Xu, Jingfeng Li, Cihai Qiu, Yitian Zhang
Abstract: This study aims to address the challenge of quickly and accurately detecting high-risk behaviors such as falls in elderly people in hardware environments with limited power consumption and cost. Therefore, this article proposes an optimized behavior anomaly detection algorithm based on the AlphaPose model. The algorithm first improved the human target detection and pose estimation models to achieve faster pedestrian detection and pose joint point inference; Then, using the adjusted AlphaPose …
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Jiaze Dong, Qilang Feng
Abstract: During a tennis match, players may encounter various circumstances that can significantly influence their performance. This force, known as "momentum," can drastically alter the game's flow and ultimately determine the winner. Addressing the challenge of analyzing and predicting momentum shifts, this study applied the Entropy Weight TOPSIS method combined with fuzzy comprehensive evaluation to assess player performance across technical, physical, and psychological factors. These methods provided …
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Jingyu Chen
Abstract: This paper introduces the definition and background of real-time simulation and hardware-in-the-loop technology, and explains the concept, development process and application field of real-time simulation and hardware-in-the-loop technology, as well as its importance and advantages in practical applications. The research methods and technologies for real-time simulation and hardware-in-the-loop technology include commonly used methods and technologies for model establishment, control algorithm …
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