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M. KHODJA Mohammed abdallah

MCA

Directory of teachers

Department

Departement of Microbiology and biochemistry

Research Interests

Artificial Intelligence Algorithms

Contact Info

University of M'Sila, Algeria

Email : mohamedabdellah.khodja@univ-msila.dz

On the Web:

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Recent Publications

2025-02-05

The Influence of gene flow on the genetic diversity of SARS-CoV-2 and Its Variants (British, South African, and Brazilian)

SARS-COV2 Omicron in Algerian compared to the neighbor countries using Global and local alignment algorithms

Citation

M. KHODJA Mohammed abdallah, (2025-02-05), "The Influence of gene flow on the genetic diversity of SARS-CoV-2 and Its Variants (British, South African, and Brazilian)", [national] Journal of Umm Al-Qura University for Applied Sciences , Umm Al-Qura University

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2024-12-31

Maghnite Grafting with (3-Mercaptopropyl) Triethoxysilane and its Influence on the Interlamellar Distance Blocking Value

In a water/ethanol mixture, Maghnite (Algerian Montmorillonite) was grafted with (3-Mercaptopropyl) triethoxysilane. The phenomenon of grafted product intercalation was investigated after a modification with trimethyl tetradecyl ammonium chloride at various cation exchange capacities (CEC). The XRD results showed that the d001 value (21.47 Ă) was fixed after the grafting reaction caused by the condensation of the silane molecules with the two adjacent clay sheets. When non-grafted montmorillonite was modified with the same surfactant, the d001 increased as the trimethyl tetradecyl ammonium chloride concentration increased. The results of the various analyses (XRF, CHN, XRD, FTIR and TGA) demonstrate that the grafting and modification reactions were successful. Mastering the fixation of an alkoxysilane-grafted clay's interlamellar space can lead to an organophilic material with immobile reactive organic groups and controlled swelling.

Citation

M. KHODJA Mohammed abdallah, (2024-12-31), "Maghnite Grafting with (3-Mercaptopropyl) Triethoxysilane and its Influence on the Interlamellar Distance Blocking Value", [national] SSRN - Elsevier , Elsevier

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2024-12-03

Genomic analysis of SARS-COV2 using Biopython and Simplot comparison

The presented work case interests pairwise sequence alignment algorithms for two analysis cases. The first analysis is SARS-COV2 Omicron in Algerian compared to the neighbor countries using Global and local alignment algorithms, and the second compared coronaviruses from animal sources like Pangolin, Bat, Civet, and Camal, to predict its origin. Of course, with real applications and samples from GISAID, NCBI, and GenBank, and deal with them using the Biopython command line in the Colab platform. The presented work confirms that the local alignment algorithm for the spike region provides better family classification and grouping by matching score sorting. The identity percentage of SARS-COV-2 compared to animal coronaviruses published previously using Simplot software from other authors have wrong values and reviewed in the presented work with the right values using the Biopython library. A high matching score found in bats and pangolins confirms that the origin of SARS-COV-2 is from animal wildlife.

Citation

M. KHODJA Mohammed abdallah, (2024-12-03), "Genomic analysis of SARS-COV2 using Biopython and Simplot comparison", [national] Journal of Bioscience and Applied Research (JBAAR) , the society of pathological biochemistry and hematology

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2024-11-13

Leveraging Omics and Bioinformatics for Personalized Therapy and Prognostic Prediction in Colorectal Cancer: Insights from AI-Driven Subclassification.

our study is considered as first draft to dive into CRC research which provides a foundation for developing models to
test drug resistance and personalized treatments. These findings have significant implications for enhancing treatment efficacy and
prognosis in CRC through personalized medicine.

Citation

M. KHODJA Mohammed abdallah, (2024-11-13), "Leveraging Omics and Bioinformatics for Personalized Therapy and Prognostic Prediction in Colorectal Cancer: Insights from AI-Driven Subclassification.", [international] The 2nd International Conference on Bioinformatics , Boumerdes

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2024-05-15

Pairwise sequence alignment of Algerian SARS-COV2 Omicron

The presented study case interest by pairwise sequence alignment of SARS-COV2
Omicron in Algerian compared to the neighbor's countries using Global and local
alignment algorithm, to check what introduced in different literature about scoring
matching of alignment between two sequences of course with real application and
samples from GISAID with Biopython command line in Colab platform. The study case
confirms with real application that Global alignment technique is most suitable for
closely related sequences of similar lengths, and Local alignment method gives better
family classification and grouping of scoring match of alignment that may be inferred
to the importance of the Spike region chosen for Local alignment for virus family
classification.

Citation

M. KHODJA Mohammed abdallah, (2024-05-15), "Pairwise sequence alignment of Algerian SARS-COV2 Omicron", [international] the Letters in Applied Microbiology Early Career Scientist Research Symposium , UK

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2022-08-17

UBER: UAV-Based Energy-Efficient Reconfigurable Routing Scheme for Smart Wireless Livestock Sensor Network

This paper addresses coverage loss and rapid energy depletion issues for wireless livestock sensor networks by proposing a UAV-based energy-efficient reconfigurable routing (UBER) scheme for smart wireless livestock sensor networking applications. This routing scheme relies on a dynamic residual energy thresholding strategy, robust cluster-to-UAV link formation, and UAV-assisted network coverage and recovery mechanism. The performance of UBER was evaluated using low, normal and high UAV altitude scenarios. Performance metrics employed for this analysis are network stability (NST), load balancing ratio (LBR), and topology fluctuation effect ratio (TFER). Obtained results demonstrated that operating with a UAV altitude of 230 m yields gains of 31.58%, 61.67%, and 75.57% for NST, LBR, and TFER, respectively. A comparative performance evaluation of UBER was carried out with respect to hybrid heterogeneous routing (HYBRID) and mobile sink using directional virtual coordinate routing (MS-DVCR). The performance indicators employed for this comparative analysis are energy consumption (ENC), network coverage (COV), received packets (RPK), SN failures detected (SNFD), route failures detected (RFD), routing overhead (ROH), and end-to-end delay (ETE). With regard to the best-obtained results, UBER recorded performance gains of 46.48%, 47.33%, 15.68%, 19.78%, 46.44%, 29.38%, and 58.56% over HYBRID and MS-DVCR in terms of ENC, COV, RPK, SNFD, RFD, ROH, and ETE, respectively. The results obtained demonstrated that the UBER scheme is highly efficient with competitive performance against the benchmarked CBR schemes.

Citation

M. KHODJA Mohammed abdallah, (2022-08-17), "UBER: UAV-Based Energy-Efficient Reconfigurable Routing Scheme for Smart Wireless Livestock Sensor Network", [national] Sensors , MDPI

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2022-07-13

Dynamic target search using multi-UAVs based on motion-encoded genetic algorithm with multiple parents

In this paper, a new optimization algorithm called Motion-Encoded Genetic Algorithm with Multiple Parents (MEGA-MPC) is developed to locate moving targets using multiple Unmanned Aerial Vehicles (UAVs). Bayesian theory is used to formulate the moving target tracking as an optimization problem where target detection probability defines the objective function as the probability of detecting the target. In the developed MEGA-MPC algorithm, a series of UAV motion paths encodes the search trajectory. In every iteration of the MEGA-MPC algorithm, UAV motion paths undergo evolution. The proposed approach for dynamic target search using multi-UAVs uses parallel computations to solve the optimization problem based on the MEGA-MPC algorithm where Each UAV can communicate with other UAVs if requested. The algorithm’s performance is tested with various characteristics under six distinct scenarios using a different number of UAVs and targets. The statistical analysis of the results obtained using MEGA-MPC compared with other well-known metaheuristics shows that MEGA-MPC offers better solutions to find dynamic targets since it outperforms all the compared algorithms

Citation

M. KHODJA Mohammed abdallah, (2022-07-13), "Dynamic target search using multi-UAVs based on motion-encoded genetic algorithm with multiple parents", [national] IEEE Access , IEEE

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2021-09-30

Motion-encoded electric charged particles optimization for moving target search using unmanned aerial vehicles

this paper, a new optimization algorithm called motion-encoded electric charged particles optimization (ECPO-ME) is developed to find moving targets using unmanned aerial vehicles (UAV). The algorithm is based on the combination of the ECPO (i.e., the base algorithm) with the ME mechanism. This study is directly applicable to a real-world scenario, for instance the movement of a misplaced animal can be detected and subsequently its location can be transmitted to its caretaker. Using Bayesian theory, finding the location of a moving target is formulated as an optimization problem wherein the objective function is to maximize the probability of detecting the target. In the proposed ECPO-ME algorithm, the search trajectory is encoded as a series of UAV motion paths. These paths evolve in each iteration of the ECPO-ME algorithm. The performance of the algorithm is tested for six different scenarios with different characteristics. A statistical analysis is carried out to compare the results obtained from ECPO-ME with other well-known metaheuristics, widely used for benchmarking studies. The results found show that the ECPO-ME has great potential in finding moving targets, since it outperforms the base algorithm (i.e., ECPO) by as much as 2.16%, 5.26%, 7.17%, 14.72%, 0.79% and 3.38% for the investigated scenarios, respectively.

Citation

M. KHODJA Mohammed abdallah, (2021-09-30), "Motion-encoded electric charged particles optimization for moving target search using unmanned aerial vehicles", [national] Sensors , MDPI

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2021-07-23

Comparative study between Type I and type II Fuzzy controller for semi active suspension system

In this article, a type-2 fuzzy interval controller is proposed to solve the nonlinear control problems of semi-active suspension system. A suspension model with two degrees of freedom and A fuzzy approach for controller synthesis were proposed. The performance of the IT2FLC-based semi-active vehicle suspension system in terms of sprung mass displacement, suspension deflection and tire deflection are compared to the homologous fuzzy type-1 controller (T1FLC), and to the passive suspension system conventional using MATLAB / SIMULINK software for simulation and controller design. The vehicle parameters, called suspension deflection and speed of suspended mass are given as inputs for both controllers. The Csemi control signal is the variable damping coefficient. Inputs and outputs are presented by triangular membership functions. Mamdani inference system is used, along with a Karnik-Mendel algorithm to locate the center of gravity in reduction type for IT2FLC controller. Simulation results show that IT2FLC-based semi-active suspension system outperforms T1FLC and passive suspension system. Thus, they show a major improvement in control signal i.e. IT2FLC controller generates a lower damping coefficient than T1FLC controller. In addition, a remarkable reduction in signal energy by IT2FLC compared to same semi-active suspension system with T1FLC.

Citation

M. KHODJA Mohammed abdallah, (2021-07-23), "Comparative study between Type I and type II Fuzzy controller for semi active suspension system", [national] Turkish Journal of Computer and Mathematics Education , Karadeniz Technical University

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2020-12-02

A second-order sliding mode controller tuning employing particle swarm optimization

The intention of this research is to provide tuning for the coefficients of the switching sliding manifold for
the second-order sliding mode employing Particle Swarm Optimization. This research was carried out in noisy
conditions with a homemade prototype apparatus employing cheap componentry. A Teensy development board was
used as flight controller for a quadcopter, with the second-order sliding mode controller being used for attitude
stabilization. Other research has offered confirmation for the control law in both theory and simulation where they
identify the nonlinear coefficients based on Hurwitz stability analysis and linearization around equilibrium point. But
in this research, we shall be focusing upon identification of the coefficients for the switching siding manifold of the
second-order siding employing Particle Swarm Optimization, the obtained coefficient validated both practically and
experimentally; this has never previously been undertaken. New data samples will also be provided regarding the short
time execution for the physical system; this data will prove useful for future applications using artificial intelligence.
The outcomes of the research demonstrate that the proposed tuning method for second order sliding mode controller
confirm its robustness and effectiveness both in simulation and experiment.

Citation

M. KHODJA Mohammed abdallah, (2020-12-02), "A second-order sliding mode controller tuning employing particle swarm optimization", [national] International Journal of Intelligent Engineering and Systems , Intelligent Networks and Systems Society

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2020-10-18

The Use of an Optimal Fuzzy Controller Algorithm for a Low-cost Microcontroller.

Fuzzy gain-scheduled PID (FuGSPID) controllers have attracted significant interest in contemporary
research. This paper provides mathematical description help to reduce the code program for a Fuzzy gain-scheduled
controller FuGSPID that is subsequently used to stabilize the altitude of a home-constructed Quadcopter. The subject
particle swarm optimization approach was employed to optimize the fuzzy output sets of the controller. MATLAB
was used to generate the dynamic model, the FuGSPID, and the optimization. A simulation exercise revealed that the
new parameters employed in the FuGSPID that were generated as a result of the particle swarm optimization produced
fewer trajectory tracking errors. Fuzzy systems are required to process large volumes of tasks and processes. This
subsequently impedes the performance of the microcontroller. In light of this, this paper outlines a mathematical
description that can potentially reduce the algorithm code employed in the FuGSPID controller and, thereby, making
it more intuitive and reducing the processing speed of the microcontroller and reducing the sampling time of the
controller and the whole flight controller. The findings of this study revealed that the mathematical description it be
useful to reduce instruction of fuzzy controller program to implement it in low cost microcontroller and tested
effectively for a quadcopter altitude stabilization.

Citation

M. KHODJA Mohammed abdallah, (2020-10-18), "The Use of an Optimal Fuzzy Controller Algorithm for a Low-cost Microcontroller.", [national] International Journal of Intelligent Engineering & Systems , Intelligent Networks and Systems Society

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2019-03-03

Implementation of Heuristical PID Tuning for Nonlinear System Control

Quadcopter based technology utilizes a hybrid structure that delivers the ultimate services for auto control system and managements. The main objective of this study is to identify PID parameters for real nonlinear system, which is a Quadcopter flying based on certain parameters via experiment method. The control law has been programmed in Teensy development board wired to 10-DOF IMU ‘Inertial Measurement Unit’ and other sensors in order to get a home-made autopilot. Accordingly, the procedure for PID controller is tuning the autopilot using ‘Ziegler-Nichols’ in order to identify the three parameters of PID which generate a stable response in lowest time-consuming. The Z-N ‘Ziegler-Nichols’ has been implemented in real time case for Quadcopter application through altitude stabilization in a nonlinear system. In conclusion, the results shows that, the significant contribution of Ziegler-Nichols implementation in nonlinear system of the altitude stabilization has been accurately defined as an alternative method of Ziegler-Nichols which has been originally designed for linear system only.

Citation

M. KHODJA Mohammed abdallah, (2019-03-03), "Implementation of Heuristical PID Tuning for Nonlinear System Control", [national] International Review of Automatic Control (IREACO) , Praise Worthy Prize

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2019-01-21

Type-1 and type-2 fuzzy sets to control a nonlinear dynamic system

This paper is related to the simulation, in Matlab environment, of a robot manipulator controlled by both type-1 and interval type-2 fuzzy controllers, in which a modification in Karnik-Mendel algorithm has been proposed. To calculate the output of interval type-2 fuzzy system there is a main step called type-reduced; this operation is based on Karnik-Mendel algorithm, which uses arithmetic mean to calculate the control output. In this work, we propose to change the arithmetic mean by harmonic one. The performances of modified interval type-2 controller and type-1 fuzzy controller with and without noises are compared in terms of integral of squared error. The proposed modification in type reduction of Karnik-Mendel algorithm for interval type-2 fuzzy set shows best performance. Indeed, the amount of error in case of modified interval type-2 fuzzy controller is less two times than type-1 fuzzy controller.

Citation

M. KHODJA Mohammed abdallah, (2019-01-21), "Type-1 and type-2 fuzzy sets to control a nonlinear dynamic system", [national] Revue d'Intelligence Artificielle , Lavoisier

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2017-05-09

Experimental dynamics identification and control of a quadcopter

Simulation of a Quadcopter in Matlab need identify their dynamic parameters for that in this work will present experiment to identify some needed dynamic parameters for Quadcopter. The obtained parameters simulated in Matlab and give us good results. The simulated system checked in an experiment. Successful Implementation PID controller for attitude stabilization found. The implementation based on home-made autopilot based on Arduino and 10DOF Inertial Measurement Unit (IMU). The Ziegler-Nichols (ZN) PID tuning were done in experiments help determine stable PID gains in less time. The procedure of Ziegler-Nichols experimentally proofed the capability to determine PID gains for attitude stabilization of a QuadCopter.

Citation

M. KHODJA Mohammed abdallah, (2017-05-09), "Experimental dynamics identification and control of a quadcopter", [international] 2017 6th International Conference on Systems and Control (ICSC) , Batna

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2017-03-03

Tuning PID attitude stabilization of a quadrotor using particle swarm optimization (experimental)

Proportional, Integral and Derivative (PID) controllers are the most popular type of controller used in industrial applications because of their notable simplicity and effective implementation. However, manual tuning of these controllers is tedious and often leads to poor performance. The conventional Ziegler-Nichols (Z-N) method of PID tuning was done experimentally enables easy identification stable PID parameters in a short time, but is accompanied by overshoot, high steady-state error, and large rise time. Therefore, in this study, the modern heuristics approach of Particle Swarm Optimization (PSO) was employed to enhance the capabilities of the conventional Z-N technique. PSO with the constriction coefficient method experimentally demonstrated the ability to efficiently and effectively identify optimal PID controller parameters for attitude stabilization of a quadrotor

Citation

M. KHODJA Mohammed abdallah, (2017-03-03), "Tuning PID attitude stabilization of a quadrotor using particle swarm optimization (experimental)", [national] International Journal for Simulation and Multidisciplinary Design Optimization , EDP Sciences

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2016-10-30

Optimization of a proportional derivative (PD) fuzzy controller using the particle swarm optimization (PSO) technique for a 3DOF robot manipulator

This paper deals with the optimization of a proportional derivative (PD) fuzzy controller using the particle swarm optimization (PSO) technique. More precisely, we conduct a comparative study to access the performance of the PD fuzzy controller by optimizing its gain and its structural parameters separately, the optimization will done offline; thus leading two distinct fuzzy controllers. The two controllers are applied to control a 3DOF PUMA560 robot manipulator. The structure of the proposed controller is composed of a symmetric fuzzy set ranging between [-1 1] with triangular symmetric membership function. It is shown that the fuzzy controller with optimized gain performs better, compared to the one with optimized parameters, in ideal conditions without noise. Additionally, it is easy and simple to program and implement since there are only a few gain variables to optimize. Also, the execution time is much lower than that required by the optimized parameter fuzzy controller. On the other hand, the optimized parameter controller performs better in the presence of noise in some joints.

Citation

M. KHODJA Mohammed abdallah, (2016-10-30), "Optimization of a proportional derivative (PD) fuzzy controller using the particle swarm optimization (PSO) technique for a 3DOF robot manipulator", [national] The Mediterranean Journal of Measurement and Control , Softmotor

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