Algerian Journal of Signals and Systems

Comparative Evaluation of Swarm Intelligence- Based Multipath Routing Protocols for Video Streaming in Vehicular Ad-Hoc Networks

Sarra BENZEROGUE — 2025-09-30

Video streaming in Vehicular Ad-Hoc Networks (VANETs) poses significant challenges due to strict Quality of Service (QoS) requirements, such as high throughput, reliable packet delivery, low transmission delay, and stable performance—particularly critical in emergency scenarios. These challenges are exacerbated by the inherently dynamic nature of VANETs, characterized by rapidly changing network topologies, varying vehicle densities, and environmental obstacles. This study examines the potential of Swarm Intelligence (SI) algorithms in optimizing routing protocols, emphasizing their adaptability and flexibility, which make them well-suited to the dynamic conditions of VANETs.
This paper provides an in-depth review of various SI-based multi-path routing protocols, including Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Moth Whale Optimization Algorithm (MWOA), and the Butterfly Optimization-PSO Hybrid (BO-PSO). The performance of these protocols is assessed based on key QoS metrics—End-to-End Delay (E2ED), Throughput (Th), and Packet Delivery Ratio (PDR)—under different vehicle density scenarios (50 and 100 nodes).
The results demonstrate that the ACO-based protocol excels in minimizing delay, making it particularly effective for emergency situations. Conversely, the MWOA protocol achieves superior throughput and enhanced packet delivery, rendering it more suitable for non-safety applications. These findings underscore the potential of SI algorithms in developing robust, efficient multi-path routing solutions for reliable, high-quality video streaming in dynamic vehicular environments.

Computationally Efficient Estimation of Heart Rate from PPG Signals

Salah FERDI — 2025-09-30

Heart rate (HR) monitoring using photoplethysmographic (PPG) signals is becoming increasingly popular due to the simplicity of device design and the low cost of wearable technology. Measuring HR from PPG signal using battery-powered wearable devices with limited resources requires computationally efficient
algorithms. This paper presents a simple yet accurate heart rate estimation method based on a systolic peak detection algorithm that employs a fractional-order calculus-based filter. The proposed method was validated on the CapnoBase benchmark dataset, demonstrating an overall Average Absolute Error (AAE) of 1.78. These results are comparable to those achieved with state-of-the-art methods, while the proposed method offers the advantage of simpler implementation.

Safety Lifecycle of Safety Instrumented System

Nabil BOUDJOGHRA — 2025-09-30

In this article, we explored the safety lifecycle of the Safety Instrumented System (SIS). First, we introduced the SIS, its Safety Instrumented Function (SIF), its Safety Integrity Level (SIL) and its Safety Lifecycle. Then, we illustrated the safety lifecycle stages of an SIS belonging to a boil-over risk safety system of diesel storage tank using engineering techniques and methods: HAZOP, LOPA, FTA, and SIF test scheduling, which interact with each other’s data.

Simulation and Analysis of Protection of Electrical Networks against Lightning Strikes Using ATP/EMTP and MATLAB/SIMULINK

Aissa SOULI — 2025-09-30

The objective of my work is the simulation and analysis of the protection of electrical networks against lightning strikes. To achieve this goal, I will use the simulation programs ATP/EMTP and MATLAB/SIMULINK to simulate a lightning strike in two cases: in the first case, simulate a lightning strike in an electrical networks without a surge arresters installed, and in the second case , simulating a lightning strike in an electrical networks with a surge arresters installed, to see the behavior of our electrical network in both cases, and to know the importance of surge arresters in the protection of electrical networks and also to validate and
compare the results obtained by the two simulation programs.

Modelling and Analysis of Brushless Permanent Magnet Motor based on Loss Maps

Layachi CHEBABHI — 2025-09-30

In this study, a brushless permanent magnet motor (BPM) with high performance and efficiency
was modeled using Motor CAD. At first, the basic characteristics and various operating conditions have been determined. After evaluating the design, a two-dimensional model was created for electromagnetic analysis and various performance curves. Based on these results, losses and efficiency maps were created to evaluate the performance and efficiency of the BPM. The finite element method (FEM) was used to analyze various results for its accuracy and speed. The results include the curves of torque, currents, voltages, Airgap flux density and the torque speed curve in addition to the magnetic flux density, vector potential and current density. The maps include the map of electromagnetic torque, the stator current phase peak, the iron losses map of the stator and rotor and the losses in the magnet.

Design and Analysis of 24/18 Switched Reluctance Motor using ANSYS Maxwell

Layachi CHEBABHI — 2025-09-30

In this study, a design for a 24/18 switched reluctance motor (SRM) characterized by high efficiency and effective performance is proposed using ANSYS Maxwell. First, the dimensions, basic characteristics and operating conditions have been determined based on various mathematical calculations, after evaluating and analyzing the results to ensure that the desired design model was achieved. A twodimensional model was created to analyze the performance curves and electromagnetic analysis based on
the Finite Element Method (FEM) for its speed and accuracy. The results include the magnetic flux density and flux lines, in addition to the torque curve, speed, currents, flux linkages, and induced voltages.

PSO-Based Fractional-Order PID Control for Stabilizing the Chaotic Lorenz-84 Atmosphere Model

Nasr-Eddine MELLAH — 2025-09-30

This study presents a novel control approach for stabilizing the chaotic behavior of the threedimensional
fractional-order Lorenz-84 atmosphere model. By leveraging the Grünwald–Letnikov discretization method, the fractional dynamics of the system are accurately modeled. A fractional-order proportional–integral–derivative (FOPID) controller is designed, with its parameters optimally tuned using Particle Swarm Optimization (PSO). The controller adapts the input signals based on real-time state-space feedback, enabling efficient suppression of chaotic oscillations. Numerical simulations demonstrate the
effectiveness of the PSO-tuned FOPID controller in achieving precise trajectory tracking and robust stabilization. The proposed method offers a promising solution for controlling fractional-order chaotic systems in atmospheric and other nonlinear contexts.

Severity Estimation of Plant Leaf Diseases based on a CNN ensemble

Mohamed Rayane LAKEHAL — 2025-09-30

The estimation of plant disease intensity is essential for various purposes, including monitoring epidemics, understanding yield loss, and evaluating treatment effects. Despite the availability of sensor technology to measure disease severity using the visible spectrum or other spectral range imaging, deep learning has emerged as a recent and advanced technique for image processing and data analysis. To enhance the severity estimation in diseased leaves, a CNN ensemble is proposed by fusing deep features
extracted from outputs of fully connected layers of various CNN models. A SVM (Support Vector Machine) is utilized to achieve the classification stage. Experiments are carried out on wheat leaf images infected by the Yellow rust disease. Experiments conducted using three CNN models that are VGG16, MobileNetV2 and a customized CNN reveal that the CNN ensemble outperforms individual models.