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signal Recognition Methods in Motor Imagery BCI 3

Signal Recognition Methods in Motor Imagery BCI

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3rd international Seminar on Artificial Intelligence, Networking, and Information Technology, AINIT 2022

作者： Liu, Weiheng Bao, Fengge Southwest Jiaotong University 999 Xi'an Road Sichuan Chengdu610000 China

ISBN: (数字)9781510662971

ISBN: (纸本)9781510662964

Brain computer interface constructs the direct connection between human brain and external devices, which is becoming a promising method in reconstructing human's motor abilities who suffered from body disability. Among several kinds of BCI technologies, Motor Imagery based Brain-computer Interface (MI-BCI) has attracted more and more attentions since it's a more intuitive method. In the procedure of MI-BCI, the signal recognition methods play a significant role. Therefore, this paper would search into the classification techniques utilized in the processing procedure in MI-BCI systems, including machine learning techniques, naïve bayes classifier (NB), support vector machines (SVM) and linear discriminant analysis (LDA). For deep learning techniques, sparse autoencoder (SAE), convolutional neural network (CNN), recurrent neural network (RNN) was introduced. Then the paper would compare them in terms of accuracy, classification speed and data requirement. This paper would give an overview on the commonly seen classification method used in MI-BCI, and also present researchers who are selecting classification methods the most suitable choice. © 2023 SPIE.

关键词： Brain computer interface

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Research on 3D Animation Simulation Based on Machine Learning 3

Research on 3D Animation Simulation Based on Machine Learnin...

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3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big data Forum, AIBDF 2023

作者： Huang, Xinran Li, Panpan Tan, Yupeng Zhang, Yining Deng, Mengyuan Chengdu Neusoft University No. 1 Neusoft Avenue Qingchengshan Town Dujiangyan Irrigation Project City Sichuan Province China Fujian University of Technology No. 69 Xuefu South Road Shangjie Town Minhou County Fujian Province Fuzhou City China

ISBN: (纸本)9798400716362

The provided document is a research paper on 3D animation simulation based on machine learning, focusing on the application of machine learning in three-dimensional human animation technology. The paper discusses the importance of virtual reality technology based on computer three-dimensional animation in various fields such as film production, game development, sports simulation, and simulated training. The authors emphasize the significance of three-dimensional human animation technology in portraying subtle changes in human movement and simulating human emotions contained in movement. The paper also explores the application of machine learning methods in processing human body movement data and synthesizing new realistic movement sequences. Various machine learning theories and methods, including regression, function approximation, dimension reduction, classification, clustering, and decision-making, are discussed in relation to their application in three-dimensional human animation technology. The document also reviews the research status of human body movement synthesis technology at home and abroad, highlighting the contributions of various researchers in the field. The authors conclude that machine learning methods have unique advantages in processing human body movement data and can significantly improve the utilization rate of movement capture samples, thereby reducing the cost and time cycle of three-dimensional human animation production. © 2023 Copyright held by the owner/author(s).

关键词： Machine learning

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Novel Preprocessing and data Augmentation Method for Bearing Fault Diagnosis

Novel Preprocessing and Data Augmentation Method for Bearing...

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Electrical Machines and Drives (ICEMD), international conference on

作者： Mohammad Mahdi Montasseri Jawad Faiz Farbod Parvin Ahmad Kalhor School of Electrical and Computer Engineering University of Tehran Tehran Iran

To avoid financial and life risks, early diagnose of bearing faults is particularly important, and this has made intelligent fault diagnosis popular. Intelligent fault diagnosis faces challenges such as the need for sufficient data and suitable performance for noisy data. This paper presents a preprocessing and data augmentation method to improve the performance of a few-shot learning method based on these two challenges. In this method first vibration signal is converted to two-dimensional images by means of mel spectrogram, then two image processing methods, namely, histogram equalization and gamma correction are applied. Finally, a data augmentation method based on gamma correction method is used. By using the Case Western Reserve University dataset, it is shown that the proposed method can improve the fault diagnosis process.

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Review of Network Anomaly Detection in the High-speed Railway signal System Based on Artificial Intelligence

Review of Network Anomaly Detection in the High-speed Railwa...

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Computer Communication and Artificial Intelligence (CCAI), international conference on

作者： Siyuan Li Jian Wang School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

The advent of network communication technology and associated equipment has significantly enhanced the operation efficiency and automation of the high-speed railway signal system. However, these open and complex networks also face increased security threats. To mitigate the risk of malicious network attacks, effective network anomaly detection methods are progressively being adopted. Artificial intelligence (AI), with its exceptional self-learning, environmental adaptability, and massive data processing capabilities, has emerged as the development trend for network anomaly detection in the high-speed railway signal system. This paper first provides an overview of the current state of network security in the high-speed railway signal system and examines potential network security threats. It then offers a detailed comparison of AI-based network anomaly detection methods. Lastly, it discusses future research directions in this field.

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Application of adaptive beamforming technology in underwater acoustic

Application of adaptive beamforming technology in underwater...

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Neural Networks, Information and Communication Engineering (NNICE), international conference on

作者： Bingjie Yin Jianqing Chen Kunming Shipborne Equipment Research and Test Center Kunming China

Beamforming technology is the core part of the underwater target location research. It is very important to study adaptive beamforming algorithm. Adaptive beamforming technology can not only effectively extract the desired target signal, but also form a null in the interference direction to suppress interference and noise, thereby reducing the output power of interference and noise, maximizing the signal to interference noise ratio of array output, and then improving the detection performance of sonar. However, in the actual beamforming environment, the performance of adaptive beamforming algorithm will be affected by steering vector error, sampling covariance matrix error and array response error. This paper studies the traditional methods of beamforming, introduces the methods to improve the robustness of adaptive beamforming algorithm, and briefly describes the application of adaptive beamforming algorithm in underwater acoustic array signal processing.

关键词： Array signal processing Adaptive arrays signal processing algorithms Sonar Interference Parallel processing Acoustic arrays

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Thermogram-based Regions With Convolutional Neural Network (RCNN) and Facial Biometrics for Safe Driving

Thermogram-based Regions With Convolutional Neural Network (...

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international conference on Robotics,Electrical and signal processing Techniques (ICREST)

作者： Sukanta Sarkar Tammat Bin Khayer Nafish Haque Kisan Mohammad Nasir Uddin Dept. of Electrical and Electronic Engineering American International University-Bangladesh Dhaka Bangladesh

A significant number of wrongful death cases involve motor vehicle accidents. In most car accidents, the driver is somehow at fault. This can be due to a lack of visibility, slow decision-making, or bad weather, among other things. The proposed system aims to create a safe driving assist technology consisting of thermal camera-based object detection and intelligent vehicle anti-theft measures to assist in safe driving and provide vehicle security on top of the existing system. This proposed system not only can easily detect objects in low visibility under unsuitable weather conditions, with an average accuracy of 97% but also provides vehicle safety by using facial-biometrics-based vehicle authentication where the accuracy is 95%. This also has a 36 facial data saving capacity in the database at a time. The authorized user doesn't always require internet support to access the vehicle, whereas the unregistered user needs app-based permission from the user to access the car.

关键词： Road accidents Roads Vehicle safety Object detection signal processing Automobiles Convolutional neural networks

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Optimal control of slow traffic at intersections based on green building materials and signal processing technology 3

Optimal control of slow traffic at intersections based on gr...

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3rd international conference on Electronics and Communication;Network and Computer Technology (ECNCT)

作者： Kong, Wei Liang, Zijun Zhan, Xuejuan Zhu, Kai Liu, Wei Wang, Ruihan Shi, Mengping Hefei Univ Sch Urban Construct & Transportat Hefei 230601 Peoples R China Anhui Prov Transportat Big Data Anal & Applicat E Hefei 230601 Peoples R China Anhui Lufeng Traff Engn Co Ltd Hefei 231131 Peoples R China Hefei Rd Traff Safety Res & Engn Ctr Hefei 231131 Peoples R China

ISBN: (数字)9781510652118

ISBN: (纸本)9781510652118;9781510652101

Under the influence of China's sustainable development strategy, the design of urban road traffic engineering should adhere to the concept of environmental protection and develop in the direction of green and modernization. This paper proposes a slow traffic optimization at intersections based on green building materials and signal processing technology. The green building materials, such as colored asphalt concrete pavement and polyurethane elastic isolation column, are used for the channelization design of the traffic space for slow traffic at the intersection. Then the slow traffic signal optimization processing technology is used that is the slow traffic signal timing algorithm model to optimize the slow traffic crossing time. Finally, the evaluation and analysis are carried out through VISSIM traffic simulation. The results show that the method presented in this paper can effectively reduce the average delay of vehicles and the average travel time of slow traffic at intersections.

关键词： Green building materials signal processing technology Slow traffic Optimized control VISSIM traffic simulation

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Research on Denoising Method of Oil Well Liquid Level Resonance signal Based on CEEMDAN-KSVD 3

Research on Denoising Method of Oil Well Liquid Level Resona...

引用

3rd international conference on Applied Mathematics, Modeling and Computer Simulation, AMMCS 2023

作者： Sun, Xia Li, Shiyi Chongqing Institute of Engineering Chongqing400056 China

ISBN: (纸本)9781643684581

Oil well liquid level resonance signal is an important indicator fo4r oil production and transportation. However, it is often contaminated by noise, which affects the accuracy of signal analysis and processing. In order to solve this problem, a denoising method based on complete ensemble empirical mode decomposition with CEEMDAN and K-SVD is proposed in this study. Firstly, the CEEMDAN algorithm is used to decompose the original signal into a number of intrinsic mode functions (IMFs). Then, the IMFs containing noise are selected according to the correlation coefficient, and the remaining IMFs are reconstructed to obtain a denoised signal. Secondly, KSVD is employed to learn a dictionary from the noisy IMFs, and sparse coding is carried out to represent the denoised signal using the learned dictionary. Finally, the denoised signal is obtained by inverse transform of the sparse coefficients. Experiments were conducted on real oil well liquid level resonance signals, and the results show that the proposed method can effectively remove noise and retain the useful components of the signal. In addition, compared with other denoising methods, the proposed method has better denoising performance. © 2023 The Authors.

关键词： Intrinsic mode functions

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Performance Analysis of Visual Cryptography and Watermarking Algorithms 3

Performance Analysis of Visual Cryptography and Watermarking...

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3rd international conference for Emerging Technology, INCET 2022

作者： Anish, K Sai Dinesh, C K Ranjit, S Venkatesh, E Shruthi, S V Pes University Electronics and Communication Engineering Department Bengaluru India

ISBN: (纸本)9781665494991

Images are a common source of data transfer in numerous domains. They can be a source for transferring confidential information across various mediums. As this practice has been adopted on a large scale, securing the images become a major important aspect. Our paper here is an attempt to aid the security of images and also to reduce the illegal tampering of images while transferring them. We aim to provide algorithms which are robust and imperceptible that help in enhancing the security of images and also provide an analysis of those algorithms. A technique for digital image watermarking and kn sharing is presented in this paper. Digital Image Watermarking is accomplished using functions such as the wavelet transform and cosine transform. Given an image as the input signal, the watermarks would be used to verify the image's validity. The scheme is resistant against certain threats and normal image processing actions. In the case of KN Secret Sharing a user-supplied key is used to encrypt the input image. Using the K out of N technique, the given image is further divided into N separate shares. Although these N shares can be distributed, the end user only requires K of them to produce the original image. The original image is still encrypted after it is recreated. The recreated encrypted image can be decrypted and the required image obtained using the authenticated key. Watermarking finds its applications in forensics and numerous such domains. Etc. KN Sharing can be used in Distributed systems and also in data transfer systems. © 2022 IEEE.

关键词： data transfer

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Hybrid EEG signal processing Framework for Driver Drowsiness Detection Using QWT, EMD, and Bayesian Optimized SVM 3

Hybrid EEG Signal Processing Framework for Driver Drowsiness...

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3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Sardesai, Shilpa Gedam, Rahul Pune India Lcit Department of Electronics and Telecommunication Bilaspur India

ISBN: (纸本)9798331508456

Drowsiness among drivers poses an urgent safety problem in road transportation because it creates serious risks to both drivers and their passengers. Carrying out prolonged driving operations creates a mind state between full wakefulness and sleep. The research presents a new supervised learning approach to evaluate sleep stages which helps detect driver sleepiness and trigger prompt alerts. A deep feature extraction system based on QWT with time-frequency scalogram and EMD artifact removal generates features from EEG signals. The system uses evaluation of decomposition levels' energy measurements to build Energy Vectors which lead to the processing of each EEG signal into feature vectors. data classification in this research occurs through implementation of the BO-SVM classifier which features Bayesian optimization. The BO-SVM classifier delivers exceptional accuracy results because it reaches 99.17% maximum accuracy beyond typical SVM classifier performance levels. This paper combines signal processing methods with machine learning techniques which result in advanced EEG data-based sleep stage diagnosis to enhance driver safety. © 2025 IEEE.

关键词： Image reconstruction

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