Iyad Katib
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View article: Enabling Safe Co‐Existence of Connected/Autonomous Cars and Road Users Using Machine Learning and Deep Learning Algorithms
Enabling Safe Co‐Existence of Connected/Autonomous Cars and Road Users Using Machine Learning and Deep Learning Algorithms Open
As the number of vehicles increases in cities, traffic accidents continue to rise. Connected and Autonomous Cars have become important because they aim to be safer than non‐intelligent vehicles. Connected and Autonomous Cars can reduce up …
View article: Safeguarding IoT consumer devices: Deep learning with TinyML driven real-time anomaly detection for predictive maintenance
Safeguarding IoT consumer devices: Deep learning with TinyML driven real-time anomaly detection for predictive maintenance Open
Internet of Things (IoT) security is paramount for enterprises, as it includes several strategies, techniques, actions, and protocols that aim to alleviate the high vulnerability of cutting-edge businesses. IoT consumer devices, from smart…
View article: Harnessing variable reduction approach with deep recurrent neural network for student’s academic performance analysis
Harnessing variable reduction approach with deep recurrent neural network for student’s academic performance analysis Open
Predicting student performance aids the educational stakeholders in making interventions and taking proactive decisions for developing education quality and addressing the ever-evolving demands of society. Deep learning (DL) methods, parti…
View article: Adaptive event‐triggered lateral control for autonomous vehicle system under stochastic‐sampling subject to dynamic quantization
Adaptive event‐triggered lateral control for autonomous vehicle system under stochastic‐sampling subject to dynamic quantization Open
Summary In this paper, we delve into the intricate problem of lateral control in autonomous vehicles, utilizing adaptive event triggering, dynamic quantizers, and incorporating stochastic sampling. By integrating the Adaptive Event‐Trigger…
View article: Federated Learning-Based Security Attack Detection for Multi-Controller Software-Defined Networks
Federated Learning-Based Security Attack Detection for Multi-Controller Software-Defined Networks Open
A revolutionary concept of Multi-controller Software-Defined Networking (MC-SDN) is a promising structure for pursuing an evolving complex and expansive large-scale modern network environment. Despite the rich operational flexibility of MC…
View article: Blockchain-Based Control Plane Attack Detection Mechanisms for Multi-Controller Software-Defined Networks
Blockchain-Based Control Plane Attack Detection Mechanisms for Multi-Controller Software-Defined Networks Open
A Multi-Controller Software-Defined Network (MC-SDN) is a revolutionary concept comprising multiple controllers and switches separated using programmable features, enhancing network availability, management, scalability, and performance. T…
View article: Security‐based fault detection filtering design for fuzzy singular semi‐Markovian jump systems via improved dynamic event‐triggering and quantization protocols
Security‐based fault detection filtering design for fuzzy singular semi‐Markovian jump systems via improved dynamic event‐triggering and quantization protocols Open
Summary This article concerns the problem of event‐protocol‐based asynchronous fault detection filtering design for discrete‐time fuzzy singular semi‐Markovian jump systems subjected to system parameters uncertainties, unmatched one‐sided …
View article: Enhancing Cyber Security Governance and Policy for SMEs in Industry 5.0: A Comparative Study between Saudi Arabia and the United Kingdom
Enhancing Cyber Security Governance and Policy for SMEs in Industry 5.0: A Comparative Study between Saudi Arabia and the United Kingdom Open
The emergence of Industry 5.0 has revolutionized technology by integrating physical systems with digital networks. These advancements have also led to an increase in cyber threats, posing significant risks, particularly for small and mediu…
View article: Hybrid Hunter–Prey Optimization with Deep Learning-Based Fintech for Predicting Financial Crises in the Economy and Society
Hybrid Hunter–Prey Optimization with Deep Learning-Based Fintech for Predicting Financial Crises in the Economy and Society Open
Financial technology (Fintech) plays a pivotal role in driving contemporary technology, society, economies, and many other fields. The new-generation Fintech is Smart Fintech, mainly empowered and inspired by data science and artificial in…
View article: Differentiating Chat Generative Pretrained Transformer from Humans: Detecting ChatGPT-Generated Text and Human Text Using Machine Learning
Differentiating Chat Generative Pretrained Transformer from Humans: Detecting ChatGPT-Generated Text and Human Text Using Machine Learning Open
Recently, the identification of human text and ChatGPT-generated text has become a hot research topic. The current study presents a Tunicate Swarm Algorithm with Long Short-Term Memory Recurrent Neural Network (TSA-LSTMRNN) model to detect…
View article: Distributed artificial intelligence: Taxonomy, review, framework, and reference architecture
Distributed artificial intelligence: Taxonomy, review, framework, and reference architecture Open
Artificial intelligence (AI) research and market have grown rapidly in the last few years, and this trend is expected to continue with many potential advancements and innovations in this field. One of the emerging AI research directions is…
View article: Systematic Review on Reinforcement Learning in the Field of Fintech
Systematic Review on Reinforcement Learning in the Field of Fintech Open
Applications of Reinforcement Learning in the Finance Technology (Fintech) have acquired a lot of admiration lately. Undoubtedly Reinforcement Learning, through its vast competence and proficiency, has aided remarkable results in the field…
View article: Explainable Crowd Decision Making methodology guided by expert natural language opinions based on Sentiment Analysis with Attention-based Deep Learning and Subgroup Discovery
Explainable Crowd Decision Making methodology guided by expert natural language opinions based on Sentiment Analysis with Attention-based Deep Learning and Subgroup Discovery Open
There exist a high demand to provide explainability to artificial intelligence systems, where decision making
\nmodels are included. This paper focuses on crowd decision making using natural language evaluations from
\nsocial media with th…
View article: Blockchain-Assisted Hybrid Harris Hawks Optimization Based Deep DDoS Attack Detection in the IoT Environment
Blockchain-Assisted Hybrid Harris Hawks Optimization Based Deep DDoS Attack Detection in the IoT Environment Open
The Internet of Things (IoT) is developing as a novel phenomenon that is applied in the growth of several crucial applications. However, these applications continue to function on a centralized storage structure, which leads to several maj…
View article: Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses
Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses Open
Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment; however, more important is to remove the root causes of menta…
View article: Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses
Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses Open
Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment, however, more important is to remove the root causes of menta…
View article: AI explainability and governance in smart energy systems: A review
AI explainability and governance in smart energy systems: A review Open
Traditional electrical power grids have long suffered from operational unreliability, instability, inflexibility, and inefficiency. Smart grids (or smart energy systems) continue to transform the energy sector with emerging technologies, r…
View article: Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses
Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses Open
Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment, however, more important is to remove the root causes of menta…
View article: Self-Upgraded Cat Mouse Optimizer With Machine Learning Driven Lung Cancer Classification on Computed Tomography Imaging
Self-Upgraded Cat Mouse Optimizer With Machine Learning Driven Lung Cancer Classification on Computed Tomography Imaging Open
Machine learning (ML) roles a vital play in analysing lung cancer. Lung cancer has notoriously problem to analyse but it has progressed to late phase, accomplishing the main reason for cancer-related mortality. Lung cancer can be fatal if …
View article: Heap Based Optimization with Deep Quantum Neural Network Based Decision Making on Smart Healthcare Applications
Heap Based Optimization with Deep Quantum Neural Network Based Decision Making on Smart Healthcare Applications Open
The concept of smart healthcare has seen a gradual increase with the expansion of information technology. Smart healthcare will use a new generation of information technologies, like artificial intelligence, the Internet of Things (IoT), c…
View article: Data Locality in High Performance Computing, Big Data, and Converged Systems: An Analysis of the Cutting Edge and a Future System Architecture
Data Locality in High Performance Computing, Big Data, and Converged Systems: An Analysis of the Cutting Edge and a Future System Architecture Open
Big data has revolutionized science and technology leading to the transformation of our societies. High-performance computing (HPC) provides the necessary computational power for big data analysis using artificial intelligence and methods.…