Faris K. Al-Shammri

• Karbala at University of Warith Al-Anbiyaa

A novel 4-to-2 photonic crystal encoder is proposed by modulating the intensity of four input optical signals, and four distinct output states are achieved. Nonlinear rods are employed to couple input waves into resonant cavities, directing the light to the desired output waveguides. The proposed design, with a footprint of 114 µm², demonstrates ef...

The Large Communication Substitution between vehicles to infrastructure (V2I) or between vehicles (V2V), called as Vehicular Ad-Hoc Networks (VANETs), in new Tale Intelligent Transportation Systems (ITS) are degree and stop developing for extensive traffic manage, highway safety, and driverless cars. VEINS is a simulator framework that couples OMNe...

Background Artificial Intelligence (AI) and Machine Learning (ML) have significantly transformed predictive analytics across domains such as healthcare, finance, and environmental sciences. However, traditional ML models face limitations when dealing with large-scale, high-dimensional datasets, particularly due to computational inefficiencies and t...

and m.alshareeda@iuc.edu.iq, 5 6 7 dr.asri@utm.my, 8 Abstract-Security in vehicular ad-hoc networks (VANETs) as a result, vehicular ad-hoc networks (VANETs) need to adopt and implement strong security protocols respective to vehicle-to-vehicle and vehicle-to-infrastructure communication. But state-of-the-art authentication methods have drawbacks li...

Flying Ad Hoc Networks (FANETs) are indispensable in applications such as Surveillance, Disaster response missions, and Military operations. Both security and communication efficiency must meet certain requirements. However, their effectiveness is hobbled by dynamic topologies, resource constraints, and cyber threats. Therefore, Post-Quantum Crypto...

The plentiful and low-cost nature of resource-constrained platforms e.g., Raspberry Pi devices has made them a backbone of modern applications particularly in sectors such as IoT, healthcare, and industrial systems. Nevertheless, they still have some constraints in terms of processing power, memory, and available energy that could limit the deploym...

This paper presents an all-optical 4 × 2 encoder based on graphene-plasmonic waveguides for operation in the wavelength range of 8–12 μm. The basic plasmonic waveguide consists of a silicon (Si) strip and a graphene sheet supported by two dielectric ridges. Surface plasmon polaritons (SPPs) are stimulated in the spatial gap between the graphene she...

This The proliferation of Internet of Things (IoT) devices has led to a corresponding rise in cyberattacks targeting these interconnected devices. Among the most concerning threats are botnet-based attacks, known for their complexity and destructive potential within the IoT ecosystem. Researchers have explored various machine learning (ML) and deep...

This study introduces a temperature sensor based on solid-core photonic crystal fiber that exhibits insensitivity to polarization. The coupling condition between the core and defect modes is investigated by employing the finite element method. To enhance sensitivity, a thermo-sensitive liquid with a refractive index of 1.65 at 25 °C is injected int...

The plasmonic-based switch plays an important role in controlling terahertz waves and transferring them toward the desired paths. In this study, a graphene-based electro-optical switch has been designed to control surface plasmon polariton propagation in a plasmonic channel. A plasmonic channel is made of a SiO2 layer sandwiched between a silicon r...

The importance of each person's healthcare should be viewed as fundamental in the modern world due to the rise in various health issues. A decrease in the proportion of doctors is caused by an increase in the number of cases. The diagnosis is consequently delayed, or some patients are overlooked. As a result, people become more reliant on doctors f...

Object detection and recognition play a crucial role in computer vision applications, ranging from security systems to autonomous vehicles. Deep learning algorithms have shown remarkable performance in these tasks, but they often require large, annotated datasets for training. However, collecting such datasets can be time-consuming and costly. Data...

Object detection and recognition play a crucial role in computer vision applications, ranging from security systems to autonomous vehicles. Deep learning algorithms have shown remarkable performance in these tasks, but they often require large, annotated datasets for training. However, collecting such datasets can be time-consuming and costly. Data...