Publications Scientifiques
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Item Compact UWB Patch Antenna with Open-Loop Resonator for Dual-Band Rejection(Horizon House, 2025) Fortas, Ibrahim; Ayad, Mouloud; Zoubiri, BachirA novel approach to the design of a compact UWB patch antenna with improved rejection capabilities integrates a dual-ellipse structure in the patch geometry fed by CPW. It also employs four open-loop resonators to selectively target undesirable frequency bands, specifically WLAN (5.2 to 5.8 GHz) and the satellite downlink band (7 to 8 GHz). Experimental results closely align with the simulation, verifying the effectiveness of the open-loop resonators in enhancing rejection.Item Novel Machine Learning-Driven Road Accident Analysis: A Comparative Study for Predictive Safety and Infrastructure Planning(2025) Djerbi, Rachid; Bennai, M.Tahar; Boucif, AmineRoad traffic accidents remain a critical global safety concern, demanding proactive rather than reactive mitigation strategies. This paper presents a comprehensive analysis of the U.K. Road Accident dataset, leveraging machine learning to predict accident frequency and uncover contributing factors. We perform extensive data preprocessing and feature engineering to transform raw accident records into a structured format suitable for time-series forecasting. A suite of predictive models, including regularized linear models (Lasso, Ridge), Support Vector Regression (SVR), and Facebook’s Prophet, are trained and rigorously evaluated. Our comparative analysis, based on metrics such as Root Mean Squared Error (RMSE), R-squared, and Mean Absolute Error (MAE), demonstrates that models like Lasso, Prophet, and SVR consistently outperform traditional tree-based methods, achieving R² scores of up to 0.99. The findings highlight the efficacy of machine learning in providing robust predictive insights for proactive road safety interventions and data-informed civil engineering practices. This study offers a valuable framework for leveraging historical data to enhance transportation safety and guide future infrastructure developmentItem Linear and nonlinear control design for a quadrotor(2025) Hadid, Samira; Boushaki Zamoum, Razika; Refis, YoucefIn the current study, the quadrotor's nonlinear dynamic model is developed using the Newton-Euler approach. Following that, several nonlinear and linear control strategies for tracking the quadrotor's trajectory are applied. First, by employing distinct controllers for each output variable, direct application of the linear proportional integral derivative (PID) controller to the nonlinear system is realized. This system may also be linearized about an operational point to generate linear controllers, according to the linear quadratic regulator (LQR) demonstration. Nevertheless, in practice, the system dynamics may not always be accurately reflected by this linear approximation and may even be relatively wasteful. Nonlinear regulators, including the feedback linearization (FBL) controller, sliding mode controller (SMC), and modified sliding mode controller (MSMC), perform better in such situations. The trajectory tracking capabilities, dynamic performance, and potential disruption impact of both methods are evaluated and compared. The FBL with LQR was the best controller among them all. The SMC and the MSMC were also very good in tracking the trajectory.Item An efficient method to solve the Schrödinger equation with complex PT-symmetric potentials(World Scienti¯c Publishing Company, 2023) Rouabhi, Fatma Zohra; Ami, I.; Mezhoud, R.; Lombard, R. J.In this work, we present a simple and efficient method to compute numerically the eigenvalues of complex PT-symmetric Hamiltonian. Numerous works have been devoted to such Hamiltonians since the discovery that they admit totally or partially real spectra. To our knowledge, the method we are advocating has not been used in this context. Besides the determination of real eigenvalues, it allows us to observe the symmetry breaking and to calculate the imaginary parts of the energy.Item Anticancer and antiproliferative activities of Algerian Origanum majorana L.’s essential oil on PC-3 and SKBR3 cells(Taylor and francis, 2024) Hafid, Nourehouda; Bouchenak, Ouahiba; Serttas, Riza; Bouhenna, Mustapha Mounir; Khiari, Ouiza; Oussaid, Sounia; Suat, ErdoganCancer is a prominent cause of death globally, with breast cancer and prostate cancer being among the most devastating types. Therefore, the available anticancer treatments have some drawbacks, like higher toxicity and limited bioavailability. Thus, this study aimed to investigate for the first time the anticancer activity of Algerian Origanum majorana L.’s essential oil (OMEO). This research assessed the chemical profile of Algerian OMEO by gas chromatography coupled with mass spectrometry (GC-MS). The analysis revealed 29 compounds, which represent 98.08% of total volatile oil. The major compounds identified in OMEO were terpinen-4-ol (21.37%), γ-terpinene (15.78%), α-terpinene (10.43%), and trans-sabinene hydrate (9.27%). Additionally, MTT (3-(4,5-dimethylthiazol- 2-yl)-2,5-diphenyl tetrazolium bromide) was also used to test the cytotoxicity on prostate cancer (PC-3), breast cancer (SKBR3), and normal retinal pigment epithelium (ARPE-19) cell lines. The results showed a selective cytotoxicity effect by decreasing cell viability of PC-3 cancer cells with half inhibitory concentration (IC50) of 608.57 μg/mL and 672.5 μg/mL after 48h and 72h, respectively. Regarding SKBR3 cancer cells, the IC50 was 991.5 μg/mL. OMEO exhibited no significant cytotoxicity against normal (ARPE-19) cells. Furthermore, we conducted a cell apoptosis assay using Hochest 33342 dye to explore the potential mechanism pathway of OMEO. The findings verified that OMEO could trigger apoptosis in PC-3 and SBKR3 cancer cells. The ability of OMEO to inhibit cell migration assessed via wound healing assay revealed a significant decrease in cell migration. Our results imply that OMEO decreases cell viability by inducing cell apoptosis. Moreover, the oil suppresses cell migration in prostate cancer and breast cancer cells.Item Data aggregation point placement optimization in Smart Metering Networks(JES, 2024) Grainat, Youcef; Recioui, Abdelmadjid; Oubelaid, AdelThis study explores the application of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) within the framework of smart grids (SG), specifically for the optimal placement of data aggregation points (DAPs) across a network of 150 Z-wave smart meters distributed within various smart cities. The investigation aims to identify which of the two- optimization strategies offers a more cost-efficient solution while evaluating their performance in terms of transmission average latency (AL) and execution time (ET) efficiency. The results indicate that although ACO slightly edges out PSO in reducing overall costs in networks with a higher complexity and more DAPs, PSO demonstrates superior performance in execution speed, lower AL, and total cost, underscoring its viability for swift integration in smart metering infrastructures.Item Sensor Fault Detection in Uncertain Large-Scale Systems Using Interval-Valued PCA Technique(IEEE, 2025) Louifi, Abdelhalim; Kouadri, Abdelmalek; Harkat, Mohamed-FaouziPrincipal component analysis (PCA)-based fault detection and diagnosis (FDD) is a well-established, data- driven method that has shown remarkable performance. Despite the excellent reputation of the PCA, it is not an opti- mal solution, mainly due to the effect of system parameters’ uncertainties and imprecise measurements. These drasti- cally affect the decision-making concerning the operating state of the process. In this article, the data collected by different sensors are transformed from a single value to an interval value form by which errors and uncertainties in the measurements are quantified satisfactorily. Then, the process modeling based on the PCA technique has been duly performed for interval-valued. Afterward, the well-known fault detection statistics T 2 , Q, and 8 are obtained under an interval-valued representation. The developed technique is tested in the cement rotary kiln process. Its performance in terms of false and missed alarms and detection delay is compared with that of other techniques through an actual involuntary system fault and other different types of sensor faults. The obtained results show high superiority in detecting accurately and quickly distinct faults in a stochastic environment, including unknown and uncontrolled uncertainties. Consequently, the results have been reduced by more than 33%, 85%, and 45% for T 2 , Q, and 8, respectively, compared with the best results of the studied methods.Item Flows characteristics of two immiscible swirling fluids in a cylinder(Mechanika, 2024) Brahma, Kenza; Saci, Rachid; Mansouri, Kacem; Imoula, MalikaItem Grid-Connected and Grid-Islanded Energy Consumption Management(2023) Kaddour, Djillali; Hadjira, Belaidi; Belaidi, DehiaEnsuring microgrid continuity and improving system reliability in grid-connected and islanded modes is crucial for a reliable and sustainable power system. With intelligent EMS (Energy Management System), appropriate sizing, and resource optimization, the microgrid can handle the peak demand even under challenging weather conditions, in both (Connected/Islanded) modes without consuming any extra power from the grid facility or any external resources yet maintaining a reliable power supply. In this paper, a case study of load profile and power consumption estimation of some buildings in our institution IGEE (Institute of Electrical and Electronic Engineering) is used to test and illustrate our EMS performance via MATLAB Simulink. The DG-PV (Diesel Generator-Photovoltaic panel) synchronization technique is adopted to overcome the grid-tied PV system limitation and make it functional in off-grid mode. We used The same DERs (Distributed Energy Resources) sizing for (PV and BESS (Battery Energy Storage System)) in both modes, with advanced control algorithms and monitoring to ensure that our microgrid can have the ability to operate in both modes with a smooth transition from one to another. Hence, by improving the overall system reliability and continuity, we can benefit from all the microgrid mode's advantages to make our system work more efficiently and sustainably.Item Modern artificial intelligence technics for unmanned aerial vehicles path planning and control(2025) Zamoum, Yasmine; Baiche, Karim; Benkeddad, Youcef; Bouzida, BrahimUnmanned aerial vehicles (UAVs) require effective path planning algorithms to navigate through complex environments. This study investigates the application of Deep Q-learning and Dyna Q-learning methods for UAV path planning and incorporates fuzzy logic for enhanced control. Deep Q-learning, a reinforcement learning technique, employs a deep neural network to approximate Q-values, allowing the UAV to improve its path planning capabilities by maximizing cumulative rewards. Conversely, Dyna Q-learning leverages simulated scenarios to update Q- values, refining the UAV’s decision-making process and adaptability to dynamic environments. Additionally, fuzzy logic control is integrated to manage UAV movements along the planned path. This control system uses linguistic variables and fuzzy rules to handle uncertainties and imprecise information, enabling real-time adjustments to speed, altitude, and heading for accurate path following and obstacle avoidance. The research evaluates the effectiveness of these methods individually, with a focus on model-free learning in a gradual training approach, and compares their performance in terms of path planning accuracy, adaptability, and obstacle avoidance. The paper contributes to a deeper understanding of UAV path planning techniques and their practical applications in various scenarios.