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3rd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Vivek, V. Tr, Mahesh Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350399264

The computer system that is used to take attendance online is going to be upgraded as part of this project. This attendance tracking system is able to hold the technology known as facial recognition, which is a useful feature. This device helps students take attendance by utilizing both a biometric technology and artificial intelligence algorithms in one convenient package. When pupils enter the classroom, the face recognition software can identify them, making it useful for educational institutions of any kind. The existing system has a number of flaws that make it difficult to accurately record the attendance of both students and teachers. The approach makes it simpler to mark attendance and lowers the number of mistakes that might occur when doing *** students and teachers will gain a significant amount by utilizing these techniques. The ability to recognize people based on their faces is becoming increasingly significant in practically every industry. Face recognition techniques will be used to understand the faces. An attendance record is compared to the record that corresponds to it that was previously saved in the database. A student's photograph is used as a check point for this comparison. © 2023 IEEE.

关键词： Face recognition

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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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Research of Cell-Decomposition in Polar Coordinate system for Point Cloud Semantic Segmentation

Research of Cell-Decomposition in Polar Coordinate System fo...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Tsai, Min-Han Lin, Chien-Chou Yunlin University of Science & Technology Department of Computer Science and Information Engineering Yunlin Taiwan

ISBN: (纸本)9798350324174

In this paper, a polar-coordinate-based PointNet++ is proposed to classify objects such as roads, cars, motorcycles, and pedestrians using point clouds of outdoor scenes captured by LiDAR. Since the outdoor point clouds obtained by LiDAR are sparse in distance, if the point clouds are partitioned by a grid of Cartesian coordinates, the number of points in each partition varies greatly, which causes the bias of the learning network. With the SemanticKITTI data set, the experimental results of polar-coordinate-based PointNet++ show that the proposed method can improve the overall accuracy and processing speed. The results show that Mean Intersection over Union (mIoU) is 52% and overall accuracy (oAcc) is 78%, processing speed per frame improve from 300ms to 30ms. © 2023 IEEE.

关键词： Semantic Segmentation

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A Hybrid Neural Network and Box-Jenkins Models for Time Series Forecasting

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computers, Materials & Continua 2022年第3期70卷 4829-4845页

作者： Mohammad Hadwan Basheer M.Al-Maqaleh Fuad N.Al-Badani Rehan Ullah Khan Mohammed A.Al-Hagery Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Intelligent Analytics Group(IAG) College of ComputerQassim UniversityBuraydahSaudi Arabia Faculty of Computer Sciences and Information Systems Thamar UniversityThamarYemen Faculty of Administration Science Ibb UniversityIbbYemen Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia

Time series forecasting plays a significant role in numerous applications,including but not limited to,industrial planning,water consumption,medical domains,exchange rates and consumer price *** main problem is insufficient forecasting *** present study proposes a hybrid forecastingmethods to address this *** proposed method includes three *** first model is based on the autoregressive integrated moving average(ARIMA)statistical model;the second model is a back propagation neural network(BPNN)with adaptive slope and momentum parameters;and the thirdmodel is a hybridization between ARIMA and BPNN(ARIMA/BPNN)and artificial neural networks and ARIMA(ARIMA/ANN)to gain the benefits of linear and *** forecasting models proposed in this study are used to predict the indices of the consumer price index(CPI),and predict the expected number of cancer patients in the Ibb Province in *** standard measures used to evaluate the proposed method include(i)mean square error,(ii)mean absolute error,(iii)root mean square error,and(iv)mean absolute percentage *** on the computational results,the improvement rate of forecasting the CPI dataset was 5%,71%,and 4%for ARIMA/BPNN model,ARIMA/ANN model,and BPNN model respectively;while the result for cancer patients’dataset was 7%,200%,and 19%for ARIMA/BPNNmodel,ARIMA/ANN model,and BPNNmodel ***,it is obvious that the proposed method reduced the randomness degree,and the alterations affected the time series with data *** ARIMA/ANN model outperformed each of its components when it was applied separately in terms of increasing the accuracy of forecasting and decreasing the overall errors of forecasting.

关键词： Hybrid model forecasting non-linear data time series models cancer patients neural networks box-jenkins consumer price index

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Self-Adaptive Facial Expression Recognition Based on Local Feature Augmentation and Global information Correlation

Self-Adaptive Facial Expression Recognition Based on Local F...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Yan, Lingyu Xia, Jinyao Wang, Chunzhi Hubei University of Technology Faculty of Computer Science WuHan430086 China Hubei University of Technology Department of Computer Science WuHan430086 China

ISBN: (纸本)9798350337020

Facial expression recognition(FER) is one of the important research in computer vision, which has been widely applied in human-computer interaction, education, healthcare, transportation, etc. However, the wide application of facial expression recognition technology also brings new challenges, where occlusion and pose variation are two of the worst factors that disturb facial expression recognition in the wild. We propose a facial expression recognition method based on local feature augmentation and multi-scale global correlation which can adaptively extract robust local features and global features from the feature level to suppress the disturbances of occlusion and pose variation on facial expression recognition. The experimental results show that our method performs well on the RAF-DB dataset and has stronger robustness compared with other algorithms. © 2023 IEEE.

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Liver Tumour Detection through Artificial Intelligence: A Comprehensive Study 8

Liver Tumour Detection through Artificial Intelligence: A Co...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Varalakshmi, V. Hemamalini, U. Vistas Computer Science Chennai Pallavaram India Vistas Department of Information Technology Chennai Pallavaram India

ISBN: (纸本)9798350376425

Liver tumours are a serious and life-threatening condition, which, if left untreated, can lead to fatal outcomes. Given the various challenges in early disease prediction, chronic impacts, and unbalanced diagnostic information, this study focuses on creating a comprehensive analysis of liver tumour segmentation techniques. It explores the roles of machine learning, deep learning, and neural networks in diversifying early detection frameworks. The study includes an examination of feature extraction techniques used in existing frameworks, emphasizing high-quality annotations. It also addresses the limitations of current datasets and the impact of real-time databases. Detailed insights into liver tumour segmentation methods are provided, highlighting the potential of artificial intelligence frameworks for future advancements. The primary goal of this system is to develop an efficient and robust framework for detecting, segmenting, and analysing liver tumours, with a key emphasis on early detection. © 2024 IEEE.

关键词： Adversarial machine learning

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Revolutionizing Medical Diagnostics: Exploring Creativity in AI for Biomedical Image Analysis

Revolutionizing Medical Diagnostics: Exploring Creativity in...

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2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Krishnamoorthy, P. Swetha, Devulapally Geetha, Pamidimukkala Sai Karunambiga, K. Ayyasamy, Ramesh Kumar Kiran, Ajmeera Thiruthangal Nadar College PG Department of Computer Science Tamil Nadu Chennai India Vaagdevi Engineering College Department of Computer Science and Engineering Telangana Bolli Kunta India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India Karpagam Institute of Technology Department of CSE Tamil Nadu Coimbatore India Faculty of Information and Communication Technology Kampar Malaysia MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798331540685

Biomedical image analysis plays a crucial role in the early and accurate diagnosis of diseases, significantly impacting patient outcomes. This study presents an innovative approach to biomedical image analysis by integrating machine learning techniques with a user-friendly web interface. The system takes input images uploaded through the web interface and processes them using advanced machine learning algorithms implemented in Python. The goal is to automate the detection of diseases from these images, enhancing the efficiency and precision of diagnosis. Convolutional Neural Networks (CNNs), a specialized class of deep learning models designed for image analysis, are employed to learn and characterize disease-specific patterns. The proposed approach is evaluated using diverse biomedical images encompassing various diseases and conditions. Extensive experiments demonstrate the system's effectiveness, achieving high accuracy, sensitivity, and specificity in disease detection. Integrating machine learning with a web interface simplifies the diagnostic process and enables remote consultations, making healthcare services more accessible and timelier. In conclusion, this study presents a robust framework for automated biomedical image analysis, demonstrating the potential of machine learning and web technologies in revolutionizing healthcare diagnostics. The system's accuracy and user-friendly interface make it a valuable tool for healthcare professionals, contributing to early disease detection and improved patient care. © 2024 IEEE.

关键词： Convolutional neural networks

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Bi-Static Inverse Synthetic Aperture Radar Imaging Based on 5G NR Signal 23

Bi-Static Inverse Synthetic Aperture Radar Imaging Based on ...

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23rd International Symposium on Electrical Apparatus and Technologies, SIELA 2024

作者： Lazarov, Andon Kostadinov, Todor Nikola Vaptzarov Naval Academy Information Technology Department Varna Bulgaria Burgas Free University Computer Science and Engineering Faculty Burgas Bulgaria

ISBN: (纸本)9798350382365

This study addresses Bi-static Inverse Synthetic Aperture Radar (BISAR) concept with a 5G NR waveform. BISAR scenario with uncooperative transmitter and specially designed receiver, and flying target as helicopter is discussed. The positions of the transmitter, receiver and flying target are defined by vector kinematic equations. Mathematical models of 5G NR waveform and BISAR signal reflected from a target with complex geometry are described. Two dimensional (2-D) image reconstruction is realized by applying correlation with an emitted waveform or Fourier transform on a range direction, and Fourier transform on an azimuth direction. Simulation experimental results are provided to illustrate the correctness of mathematical models and imaging algorithms. © 2024 IEEE.

关键词： Inverse synthetic aperture radar

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Enhancing single-lead electrocardiogram arrhythmia detection with empirical mode decomposition

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Neural Computing and Applications 2025年第17期37卷 11583-11605页

作者： Issa, Mohamed F. Yousry, Ahmed Tuboly, Gergely Wang, Zeyu Zoltan, Juhasz Selim, Mazen M. AbuEl-Atta, Ahmed H. Department of Scientific Computing Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Computer Science Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Electrical Engineering and Information Systems University of Pannonia Veszprem8200 Hungary Department of Mechatronics Delta University for Science and Technology Gamasa35712 Egypt

Cardiac arrhythmias pose a significant challenge to health care, requiring accurate and reliable detection methods to enable early diagnosis and treatment. However, traditional ECG beat classification methods often lack robustness and fail to generalize effectively to diverse clinical scenarios, particularly when using single-lead-I recordings, which are less studied compared to lead II. To address this gap, this paper proposes a novel method that combines deep learning and empirical mode decomposition (EMD) for arrhythmia detection using single-lead-I ECG recordings obtained with electrodes on each hand. The hybrid model comprises 149 layers of one-dimensional convolution, max pooling, and residual blocks. By leveraging EMD, it classifies ECG beats into normal beats, premature ventricular contractions, and atrial premature beats with high sensitivity (99.86%, 99.72%, and 99.84%, respectively) using the first four intrinsic mode functions (IMFs). The proposed method is applicable in clinical and out-of-hospital monitoring scenarios, and an accompanying web application provides real-time analysis and diagnostic results. This approach addresses a critical gap in lead-I ECG analysis, enhancing diagnostic precision and expanding the scope of ECG applications in health care. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Empirical mode decomposition

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IoT based automated Wheel Chair for Physically Challenged

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Materials Today: Proceedings 2022年 56卷 533-541页

作者： Mishra, Priyanka Shrivastava, Sanatan Department of Computer Science and Engineering Indian Institute of Information Technology Kota Jaipur India

The purpose of an automatic wheelchair (AWC) is to assist and support paraplegics. The proposed chair is particularly suited for people with a higher level of impairment, such as quadriplegics who are unable to move any of their body parts except their head due to their advanced age or infirmity. We created a microcontroller-based wheelchair that moves with the patient's head motion. Electronic and mechanical components make up the system. An accelerometer monitors the patient's head nodes in all four dimensions for head motion recognition. The paper goes over the Bluetooth technology on the wheelchair, as well as the accelerometer that powers the motors and controls the chair's motions inside the house. Our wheelchair is designed with the patient's health in mind as well as the device's maneuverability. The pulse rate and blood oxygen levels are monitored by sensors using an Internet of Things approach. The ultrasonic sensors aid with obstacle recognition, making it easier to move the chair in a certain direction. By observing the directions of head movement along the x and y axes, the implanted accelerometer aids the chair in determining which movement the patient wishes to make. The signal is then sent to the microcontroller. The wheelchair is controlled by a microprocessor-based on the direction of acceleration, and it moves in LEFT, RIGHT, FORWARD, and BACKWARD with the help of viper motors. © 2022

关键词： Microcontrollers

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