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4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021

作者： Ren, Jing Gaber, Hossam Al Jabar, Sk Sami Ontario Tech University Dept. of Electrical and Computer Engineering OshawaON Canada Ontario Tech University Faculty of Energy Systems and Nuclear Science OshawaON Canada

ISBN: (纸本)9780738131702

Autonomous vehicles will revolutionize the future automotive industry by reducing or eliminating human errors and increasing vehicle safety. The design of autonomous vehicles will bring together many modern technologies such as control, computer vision, path planning, sensor fusion and fault diagnosis. Although traditional algorithms can be used to implement these technologies, in the last decade, deep learning has been proposed to challenge traditional algorithms and excels in many applications and research areas. Deep learning has shown its significant use in the design and operation of autonomous vehicles. In this paper, we will review the application of deep learning in five major research areas of autonomous vehicles i.e. path planning, control, computer vision, sensor fusion and fault diagnosis. Recent advances of the deep learning in autonomous vehicles will be reviewed and discussed. © 2021 IEEE.

关键词： Failure analysis

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Digitalization of Education: An Urgent Need of Sustainable Teaching Process Caused by Covid 19 20

Digitalization of Education: An Urgent Need of Sustainable T...

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20th IEEE International Conference on Modern electrical and Energy Systems, MEES 2021

作者： Brin, Pavlo Polancic, Gregor Prokhorenko, Olena National Technical University 'Kharkov Polytechnic Institute' Department of Management and Taxation Kharkiv Ukraine University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia

ISBN: (纸本)9781665423663

The study aims to identify the benefits and problematic aspects of applying e-learning technologies at Ukrainian universities, taking into account several influential factors, such as technical capabilities, the necessary skills of students and tutors, etc. Using e-learning has several advantages, such as more convenience, greater accessibility, the possibility of an individual approach, and better demonstration opportunities. The article discusses specific tools for educational digitalization, using which should increase the effectiveness and availability of training in COVID 19 pandemic conditions. © 2021 IEEE.

关键词： Students

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AI-BASED THERMAL VIDEO ANALYSIS IN PRIVACY-PRESERVING HEALTHCARE: A CASE STUDY ON DETECTING TIME OF BIRTH

arXiv

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arXiv 2025年

作者： García-Torres, Jorge Meinich-Bache, Øyvind Rettedal, Siren Engan, Kjersti Dept. of Electrical Engineering and Computer Science University of Stavanger Norway Laerdal Medical AS Stavanger Norway Dept. for Simulation-based Learning Stavanger University Hospital Norway Faculty of Health Sciences University of Stavanger Norway

Approximately 10% of newborns need some assistance to start breathing and 5% proper ventilation. It is crucial that interventions are initiated as soon as possible after birth. Accurate documentation of Time of Birth (ToB) is thereby essential for documenting and improving newborn resuscitation performance. However, current clinical practices rely on manual recording of ToB, typically with minute precision. In this study, we present an AI-driven, video-based system for automated ToB detection using thermal imaging, designed to preserve the privacy of healthcare providers and mothers by avoiding the use of identifiable visual data. Our approach achieves 91.4% precision and 97.4% recall in detecting ToB within thermal video clips during performance evaluation. Additionally, our system successfully identifies ToB in 96% of test cases with an absolute median deviation of 1 second compared to manual annotations. This method offers a reliable solution for improving ToB documentation and enhancing newborn resuscitation outcomes. © 2025, CC BY.

关键词： Video analysis

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Full-Duplex Communication for ISAC: Joint Beamforming and Power Optimization

Full-Duplex Communication for ISAC: Joint Beamforming and Po...

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作者： He, Zhenyao Xu, Wei Shen, Hong Ng, Derrick Wing Kwan Eldar, Yonina C. You, Xiaohu Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China The University of New South Wales School of Electrical Engineering and Telecommunications SydneyNSW2052 Australia Weizmann Institute of Science Faculty of Mathematics and Computer Science Rehovot7610001 Israel

Beamforming design has been widely investigated for integrated sensing and communication (ISAC) systems with full-duplex (FD) sensing and half-duplex (HD) communication, where the base station (BS) transmits and receives radar sensing signals simultaneously while the integrated communication operates in either downlink or uplink. To achieve higher spectral efficiency, in this paper, we extend existing ISAC beamforming design to a general case by considering the FD capability for both radar and communication. Specifically, we consider an FD ISAC system, where the BS performs target detection and communicates with multiple downlink users and uplink users reusing the same time and frequency resources. We jointly optimize the downlink dual-functional transmit signal and the uplink receive beamformers at the BS and the transmit power at the uplink users. The problems are formulated under two criteria: power consumption minimization and sum rate maximization. The downlink and uplink transmissions are tightly coupled due to both the desired target echo and the undesired interference received at the BS, making the problems challenging. To handle these issues in both cases, we first determine the optimal receive beamformers in closed forms with respect to the BS transmit beamforming and the user transmit power. Subsequently, we invoke these results to obtain equivalent optimization problems and propose iterative algorithms to solve them. In addition, we consider a special case under the power minimization criterion and propose an alternative low complexity design. Numerical results demonstrate that the optimized FD communication-based ISAC brings tremendous improvements in terms of both power efficiency and spectral efficiency compared to the conventional ISAC with HD communication. © 1983-2012 IEEE.

关键词： Signal to noise ratio

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Enabling AutoML for Zero-Touch Network Security: Use-Case Driven Analysis

TechRxiv

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TechRxiv 2024年

作者： Yang, Li Rajab, Mirna El Shami, Abdallah Muhaidat, Sami Faculty of Business and Information Technology Ontario Tech University OshawaONL1G 0C5 Canada Department of Electrical and Computer Engineering Western University LondonONN6A 3K7 Canada Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates

Zero-Touch Networks (ZTNs) represent a state-of-the-art paradigm shift towards fully automated and intelligent network management, enabling the automation and intelligence required to manage the complexity, scale, and dynamic nature of next-generation (6G) networks. ZTNs leverage Artificial Intelligence (AI) and Machine Learning (ML) to enhance operational efficiency, support intelligent decision-making, and ensure effective resource allocation. However, the implementation of ZTNs is subject to security challenges that need to be resolved to achieve their full potential. In particular, two critical challenges arise: the need for human expertise in developing AI/ML-based security mechanisms, and the threat of adversarial attacks targeting AI/ML models. In this survey paper, we provide a comprehensive review of current security issues in ZTNs, emphasizing the need for advanced AI/ML-based security mechanisms that require minimal human intervention and protect AI/ML models themselves. Furthermore, we explore the potential of Automated ML (AutoML) technologies in developing robust security solutions for ZTNs. Through case studies, we illustrate practical approaches to securing ZTNs against both conventional and AI/ML-specific threats, including the development of autonomous intrusion detection systems and strategies to combat Adversarial ML (AML) attacks. The paper concludes with a discussion of the future research directions for the development of ZTN security approaches. © 2024, CC BY.

关键词： Network intrusion

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Chaotic Pigeon Inspired Optimization Technique for Clustered Wireless Sensor Networks

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computers, Materials & Continua 2022年第12期73卷 6547-6561页

作者： Anwer Mustafa Hilal Aisha Hassan Abdalla Hashim Sami Dhahbi Dalia H.Elkamchouchi Jaber S.Alzahrani Mrim M.Alnfiai Amira Sayed A.Aziz Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University Malaysia53100Kuala LumpurMalaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaifP.O.Box 11099Taif21944Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Wireless Sensor Networks(WSN)interlink numerous Sensor Nodes(SN)to support Internet of Things(loT)*** the data gathered from SNs can be divulged,tempered,and *** WSN data processes manage the data in a centralized format at terminal *** devices are prone to attacks and the security of systems can get *** is a distributed and decentralized technique that has the ability to handle security issues in *** security issues include transactions that may be copied and spread across numerous nodes in a peer-peer network *** breaches the mutual trust and allows data immutability which in turn permits the network to go *** some instances,few nodes die or get compromised due to heavy power *** current article develops an Energy Aware Chaotic Pigeon Inspired Optimization based Clustering scheme for Blockchain assisted WSN technique abbreviated as EACPIO-CB *** primary objective of the proposed EACPIO-CB model is to proficiently group the sensor nodes into clusters and exploit Blockchain(BC)for inter-cluster communication in the *** select ClusterHeads(CHs)and organize the clusters,the presented EACPIO-CB model designs a fitness function that involves distinct input ***,BC technology enables the communication between one CH and the other and with the Base Station(BS)in the *** authors conducted comprehensive set of simulations and the outcomes were investigated under different *** simulation results confirmed the better performance of EACPIO-CB method over recent methodologies.

关键词： Blockchain wireless sensor networks clustering energy efficiency security data transmission

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Compact NSGA-II for Multi-objective Feature Selection

Compact NSGA-II for Multi-objective Feature Selection

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IEEE International Conference on Systems, Man and Cybernetics

作者： Sevil Zanjani Miyandoab Shahryar Rahnamayan Azam Asilian Bidgoli Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa ON Canada Department of Engineering Brock University St. Catharines ON Canada Faculty of Science Wilfrid Laurier University Waterloo ON Canada

Feature selection is an expensive challenging task in machine learning and data mining aimed at removing irrelevant and redundant features. This contributes to an improvement in classification accuracy, as well as the budget and memory requirements for classification, or any other post-processing task conducted after feature selection. In this regard, we define feature selection as a multi-objective binary optimization task with the objectives of maximizing classification accuracy and minimizing the number of selected features. In order to select optimal features, we have proposed a binary Compact NSGA-II (CNSGA-II) algorithm. Compactness represents the population as a probability distribution to enhance evolutionary algorithms not only to be more memory-efficient but also to reduce the number of fitness evaluations. Instead of holding two populations during the optimization process, our proposed method uses several Probability Vectors (PVs) to generate new individuals. Each PV efficiently explores a region of the search space to find non-dominated solutions instead of generating candidate solutions from a small population as is the common approach in most evolutionary algorithms. To the best of our knowledge, this is the first compact multi-objective algorithm proposed for feature selection. The reported results for expensive optimization cases with a limited budget on five datasets show that the CNSGA-II performs more efficiently than the well-known NSGA-II method in terms of the hypervolume (HV) performance metric requiring less memory. The proposed method and experimental results are explained and analyzed in detail.

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Low-Complexity Beam-Oriented Linearization Approaches for Massive MIMO Transmission

Low-Complexity Beam-Oriented Linearization Approaches for Ma...

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IEEE Conference on Vehicular Technology (VTC)

作者： Abdelwahab Fawzy Sumei Sun Teng Joon Lim Yongxin Guo Institute for Infocomm Research (I2R) Agency for Science Technology and Research (A*STAR) Singapore Electrical and Computer Engineering National University of Singapore Singapore Faculty of Engineering University of Sydney Australia

Digital beamforming is a crucial technology that enables fifth-generation (5G) devices to operate on millimeter wave (mmW) radio frequencies. However, linearizing massive arrays at the transmitter (TX) side remains a significant challenge as the complexity scales with the number of antennas. This work focuses on the orthogonal frequency division multiplexing (OFDM) modulation in 5G and beyond networks and presents low-complexity linearization approaches that can be used before the precoder. These approaches do not scale with the number of antennas and provide flexible control of the linearization performance across different parts of the spectrum. Simulation results for a 64-element uniform linear array (ULA) demonstrate that the proposed techniques can achieve performance comparable to conventional multi-digital pre-distortion (DPD) with only 8.91% and 3.52% of the complexity.

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SD-Based Low-Complexity Precoder Design for Gaussian MIMO Wiretap Channels

SD-Based Low-Complexity Precoder Design for Gaussian MIMO Wi...

引用

IEEE Globecom Workshops

作者： Hao Xu Kai-Kit Wong Giuseppe Caire Department of Electronic and Electrical Engineering University College London London U.K. Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany

ISBN: (纸本)9781665459761

This paper considers a Gaussian multi-input multi-output (MIMO) multiple access wiretap (MAC-WT) channel, where an eavesdropper (Eve) wants to extract the confidential information of all users. Assuming that both the legitimate receiver and Eve jointly decode their interested messages, we aim to maximize the sum secrecy rate of the system by precoder design. Although this problem could be solved by first using the iterative majorization minimization (MM) based algorithm to get a sequence of convex log-determinant optimization subproblems and then using some general tools, e.g., the interior point method, to deal with each subproblem, this strategy involves quite high computational complexity. Therefore, we propose a simultaneous diagonalization based low-complexity (SDLC) method to maximize the secrecy rate of a simple one-user wiretap channel, and then use this method to iteratively optimize the covariance matrix of each user. Simulation results show that in contrast to the existing approaches, the SDLC scheme achieves similar secrecy performance but requires much lower complexity.

关键词： Simulation Receivers Minimization Iterative algorithms Data mining Covariance matrices Computational complexity

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Lightweight Blockchain-Based Architecture for 5g Enabled Iot

SSRN

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SSRN 2022年

作者： Maroufi, Mohammad Abdolee, Reza Tazehkand, Behzad Mozaffari Mortezavi, Seyed Amir Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Computer science California State University Channel Islands United States

Fast and secure network connectivity is essential for emerging Internet of Things (IoT) applications and services. Distributed Blockchain technology offers compelling opportunities to solve IoT security, privacy, and reliability issues. However, using blockchain in IoT networks introduces a new set of issues, including high computational overhead, latency, and bandwidth overhead that can adversely affect the proper operation of the IoT. This paper proposes a new lightweight blockchain-based architecture for 5G-enabled IoT. This architecture combines small cells, network functions virtualization (NFV), software-defined networking (SDN), and distributed clouds with a lightweight Blockchain consensus algorithm to guarantee high availability, real-time data delivery, security, resiliency, and low latency. We compare the performance of the proposed architectures in six different scenarios with conventional 5G in terms of processing time and power consumption. The proposed structure added data overload, superior hashing, and encryption protocols to conventional 5G to improve the security level of IoT networks against data manipulation and fraud. However, it reduces the traffic passed through the Internet and local transaction processing time. © 2022, The Authors. All rights reserved.

关键词： Blockchain

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