Papers by Abdelhadi Raihani
Microgrid Energy Management System: Technologies and Architectures Review
2020 IEEE International conference of Moroccan Geomatics (Morgeo)
The energy management concepts for Microgrid (MG) system had substantial attention in the last ye... more The energy management concepts for Microgrid (MG) system had substantial attention in the last years. The aim of integrating an Energy Management System (EMS) in MG and/or building is to improve the energy efficiency and reduce the energy cost. This article gives an overview of different MG electrical architectures and some popular MG concepts with EMS. Some Artificial Intelligence based (AI) methods, in the EMS field, such as Artificial Neural Networks (ANN), Fuzzy Logic ($\Gamma$L), Machine Learning (ML) and Expert System (ES) are also examined.
International Journal of Electrical and Computer Engineering (IJECE)
Interdigitated electrodes (IDEs) are commonly employed in biological cellular characterization te... more Interdigitated electrodes (IDEs) are commonly employed in biological cellular characterization techniques such as electrical cell-substrate impedance sensing (ECIS). Because of its simple production technique and low cost, interdigitated electrode sensor design is critical for practical impedance spectroscopy in the medical and pharmaceutical domains. The equivalent circuit of an IDE was modeled in this paper, it consisted of three primary components: double layer capacitance, Cdl, solution capacitance, CSol, and solution resistance, RSol. One of the challenging optimization challenges is the geometric optimization of the interdigital electrode structure of a sensor. We employ metaheuristic techniques to identify the best answer to problems of this kind. multi-objective optimization of the IDE using multi-objective particle swarm optimization (MOPSO) was achieved to maximize the sensitivity of the electrode and minimize the Cut-off frequency. The optimal geometrical parameters deter...
International Journal of Electrical and Computer Engineering (IJECE)
Arabic handwritten text recognition has long been a difficult subject, owing to the similarity of... more Arabic handwritten text recognition has long been a difficult subject, owing to the similarity of its characters and the wide range of writing styles. However, due to the intricacy of Arabic handwriting morphology, solving the challenge of cursive handwriting recognition remains difficult. In this paper, we propose a new efficient based image processing approach that combines three image descriptors for the feature extraction phase. To prepare the training and testing datasets, we applied a series of preprocessing techniques to 100 classes selected from the handwritten Arabic database of the Institut Für Nachrichtentechnik/Ecole Nationale d'Ingénieurs de Tunis (IFN/ENIT). Then, we trained the k-nearest neighbor’s algorithm (k-NN) algorithm to generate the best model for each feature extraction descriptor. The best k-NN model, according to common performance evaluation metrics, is used to classify Arabic handwritten images according to their classes. Based on the performance eval...
International Journal of Biomedical Imaging
Acute ischemic stroke represents a cerebrovascular disease, for which it is practical, albeit cha... more Acute ischemic stroke represents a cerebrovascular disease, for which it is practical, albeit challenging to segment and differentiate infarct core from salvageable penumbra brain tissue. Ischemic stroke causes the variation of cerebral blood flow and heat generation due to metabolism. Therefore, the temperature is modified in the ischemic stroke region. In this paper, we incorporate acute ischemic stroke temperature profile to reinforce segmentation accuracy in MRI. Pennes bioheat equation was used to generate brain thermal images that may provide rich information regarding the temperature change in acute ischemic stroke lesions. The thermal images were generated by calculating the temperature of the brain with acute ischemic stroke. Then, U-Net was used in this paper for the segmentation of acute ischemic stroke. A dataset of 3192 images was created to train U-Net using k -fold crossvalidation. The training time was about 10 hours and 35 minutes in NVIDIA GPU. Next, the obtained t...
E3S Web of Conferences
Optimization of interdigitated electrode sensor design is essential for practical impedance spect... more Optimization of interdigitated electrode sensor design is essential for practical impedance spectroscopy in the medical and pharmaceutical fields because of their easy fabrication procedure and inexpensive. The geometry presents a prospective for ameliorating sensitivity over other microelectrode designs. The geometric optimization of a sensor’s structure with interdigital electrodes is one of the difficult optimization problems. To solve this type of problem, we use metaheuristic methods to find the optimal solution. The method chosen in this paper is the differential evolution algorithm DE, which is widely used to solve the overall optimization problem. We will optimize the geometrical parameters of the interdigitated electrodes by minimizing the FLow, the proper band [FLow<-->FHigh] using MATLAB script, the validity of the obtained results is investigated using ADS tools
Multi-mode control strategy for a stand-alone wind energy conversion system with battery energy storage
Journal of Energy Storage
Screening Medical Face Mask for Coronavirus Prevention using Deep Learning and AutoML
2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)
In the last two years, the COVID-19 pandemic causes a global health crisis around the world. On t... more In the last two years, the COVID-19 pandemic causes a global health crisis around the world. On the other hand, given the current shortage and limits of medical resources, the World Health Organization (WHO) suggests several measures to control the infection rate and avoid depleting limited medical resources. In fact, wearing a medical mask is one of the non-pharmaceutical measures that can be used to limit the spread of this pandemic. This paper aims to present a new deep learning model based on AutoML for medical face mask detection. This proposed model was trained on a publicly available dataset that contained three classes: With mask, Incorrect mask, and Without mask. The achieved results show that the proposed model reaches an Accuracy and sensitivity of 99.74% and 99% respectively.
Parkinson's disease classification using machine learning algorithms: performance analysis and comparison
2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), 2022
Detection of Parkinson's disease remains challenge for physicians, especially, in the clinica... more Detection of Parkinson's disease remains challenge for physicians, especially, in the clinical field due to the difficulty of cure. Thus, algorithms of classification have the main role in the assessment of this neurodegenerative disorder. In this paper, we focus on the analysis and the evaluation of nine Machine Learning Algorithms (MLA), namely Support Vector Machine (SVM), Logistic Regression, Discriminant Analysis, K-Nearest Neighbors (KNN), Decision tree, Random Forest, Bagging tree, Naïve Bayes, and AdaBoost. Classification algorithms were applied to a Parkinson's dataset of 240 speech measurements with 44 features using several evaluation parameters to establish the efficiency score of each classifier. We found that the KNN classifier yielded the highest accuracy rate of 97.22% and F1-score of 97.30%.
Informatics in Medicine Unlocked, 2020
Atherosclerosis diagnosis is an indistinct and complex cognitive process. Artificial intelligence... more Atherosclerosis diagnosis is an indistinct and complex cognitive process. Artificial intelligence methods, such as machine learning algorithms, have proven their efficiency in Medical Diagnosis Support Systems (MDSS). In this paper, we developed a novel machine learning MDSS to boost the diagnosis of cardiovascular diseases. Our study performed using 835 patient medical records that suffer from atherosclerosis, usually caused by coronary artery diseases (CAD), collected from three databases. The system input layer includes several input variables based on three databases, the Cleveland heart disease, Hungarian, and Z-Alizadeh Sani databases. Seven independent classification methods are applied to assess the system: Artificial Neural Network (ANN), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Tree (DT), Naïve Bayes (NB), Classification Ensemble (CE), and Discriminant Analysis (DA) algorithms. The robustness of the proposed methods was evaluated through several performance measures. The results showed that the proposed MDSS reached an accuracy of (98%), which is a higher accuracy than the existing approaches. These results are a promising step toward facilitating large-scale clinical diagnostics for atherosclerosis diseases.
Nonlinear Control of an Aerogenerator Including DFIG and AC/DC/AC Converters
Innovations in Smart Cities Applications Edition 2, 2019
This paper addresses the problem of controlling wind energy conversion systems (WECS) involving d... more This paper addresses the problem of controlling wind energy conversion systems (WECS) involving doubly fed induction generator (DFIG) fed by IGBT based buck-to-buck converters. The main control objective is to maximize wind energy extraction which cannot be achieved without letting the wind turbine rotor operate in variable speed mode. A multiloop nonlinear controller is designed to meet three main control objectives: (i) speed reference optimization in order to extract a maximum wind energy whatever the wind speed by (MPPT) requirement; (ii) power factor correction (PFC) to avoid net harmonic pollution; (iii) regulating the DC Link voltage. A multiloop nonlinear controller is synthesized using the backstepping design technique. To determine the reference torque in order to allow DFIG turning at reference speed, the Sliding mode control approach is convoked. A formal analysis based on Lyapunov stability is carried out to describe the control system performances. In addition to closed-loop global asymptotic stability. It is proven that all control objectives (rotor speed tracking, stator flux regulation, DC link voltage regulation and unitary power factor) are asymptotically achieved.
Exploration Study on Learning Styles Identification and Prediction Techniques
2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)
Real-time functional explorations Computer Interface (FCI)
2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)
Electronics, 2021
Coronavirus (COVID-19) is the most prevalent coronavirus infection with respiratory symptoms such... more Coronavirus (COVID-19) is the most prevalent coronavirus infection with respiratory symptoms such as fever, cough, dyspnea, pneumonia, and weariness being typical in the early stages. On the other hand, COVID-19 has a direct impact on the circulatory and respiratory systems as it causes a failure to some human organs or severe respiratory distress in extreme circumstances. Early diagnosis of COVID-19 is extremely important for the medical community to limit its spread. For a large number of suspected cases, manual diagnostic methods based on the analysis of chest images are insufficient. Faced with this situation, artificial intelligence (AI) techniques have shown great potential in automatic diagnostic tasks. This paper aims at proposing a fast and precise medical diagnosis support system (MDSS) that can distinguish COVID-19 precisely in chest-X-ray images. This MDSS uses a concatenation technique that aims to combine pre-trained convolutional neural networks (CNN) depend on the tr...
Adaptive nonlinear observer for wind energy conversion system involving synchronous aero-generator
2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), 2022
E3S Web of Conferences, 2022
Wind power’s current growth rates are among the fastest in the world. Research on techniques to m... more Wind power’s current growth rates are among the fastest in the world. Research on techniques to make wind farms more energy efficient is warranted for this reason. Optimizing the location of wind turbines within wind farms makes the use of wind energy more efficient and makes wind farms more competitive with other energy sources. The investment expenses for the only substations and electrical infrastructures of the offshore wind farms represent between 15 and 30% of the overall investment cost of the project, this leads us to study the optimization of the location of the substation. can reduce these expenses, which also reduces the total cable length inside the wind farm. Our objective is therefore to study the optimization of wind farms with two objective functions aimed at minimizing the costs of installing wind turbines and reducing connectivity between wind turbines using a metaheuristic PSO algorithm.
International Journal of Power Electronics and Drive Systems (IJPEDS)
The emergence of renewable energy sources with controllable loads gave the opportunity to the con... more The emergence of renewable energy sources with controllable loads gave the opportunity to the consumers to build their own Microgrids. However, the intermittence of renewable energy sources such as wind and photovoltaic leads to some challenges in terms of balancing generation and consumption. This paper aims to present a novel multi-agent model based intelligent control scheme to balance the home/building alternative current (AC)-direct current (DC) load demands and renewable energy sources. The new proposed scheme consists of a three-level hierarchical multi agent system based on cooperation, communication and interaction between intelligent agents to fulfill the load's requirements. Then, the proposed multi agent framework is simulated using four different nanogrids to prove its effectiveness using different temporal profiles for loads and generators. The proposed model is designed to be modular, so that it can be considered as a sample from a set of similar modules, assigned...
Swarm Intelligence Optimization Techniques for an Optimal RF Integrated Spiral Inductor Design
2018 International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS)
Passive components such as inductors are used in many radiofrequency integrated circuits (RFIC... more Passive components such as inductors are used in many radiofrequency integrated circuits (RFIC's). In RF block., like Voltage Control Oscillators (VCO), Mixer., Low Noise Amplifier (LNA)., Phase-Locked Loop (PLL), the spiral inductor design constitutes a very important task to reduce the total system size and assembly cost. The aim of this present work is to design an optimal integrated spiral inductor by means of two swarm intelligence based metaheuristics namely Ant Colony Optimization (ACO) technique and Artificial Bee Colony Algorithm (ABC). The considered optimization applications uses the physical dimensions of the square spiral-integrated inductor as the design parameters while taking into consideration the most important constraints specifications including the fixed value of required inductance $(\mathbf{Ls}_{\mathbf{req}})$, the operating frequency., and the minimum factor of quality $(\mathbf{Q}_{{\mathbf{min}}})$. A comparison between the used swarm intelligence (SI) techniques is presented. Simulations using an electromagnetic software (ADS Momentum) are used to validate the obtained result/performances.
Thermal influence of brain tumor on MRI images with anisotropic properties
2018 4th International Conference on Optimization and Applications (ICOA)
The main aim of the present paper is the analysis of brain tumors thermal influence on simulated ... more The main aim of the present paper is the analysis of brain tumors thermal influence on simulated MRI T1-weighted signal intensity by considering tumor anisotropic properties. MRI offers a rich information of the studied tissues and tumors according to the MR nuclear parameters such as T1, T2 and proton density. However, some of these parameters change depending on the temperature. The temperature distribution in tumorous area is higher than surrounding normal tissues, which causes a significant changes on MR parameters, the studied MR parameter in this work is T1 relaxation time. The thermal effect of tumor is calculated by estimating tumor thermal profile, which is converted to T1-weighted signal intensity using Spin Echo sequence (SE). In this wok, numerical strategy by finite difference method was used to solve the Pennes bioheat transfer equation. We considered tumor anisotropic thermal conductivity tensor and found has a significant influence regarding the thermal profile on the tumorous region.
Artificial bee colony technique for a study of the influence of impact of metal thickness on the factor of quality-Q in integrated square spiral inductors
2018 4th International Conference on Optimization and Applications (ICOA)
The goal of this present paper is to investigate the impact of metal thickness on the factor of q... more The goal of this present paper is to investigate the impact of metal thickness on the factor of quality-Q in integrated square spiral inductor, using an efficient application of the Artificial Bee Colony (ABC) algorithm. The inductors were optimized at 2.4 GHz to determinate theirs major geometrical dimensions and theirs number of turns, for uses in radio-frequency integrated circuits (RFICs). The results are validated by simulation using an electromagnetic simulator (ADS Momentum). Using matlab software, the study on the influence of the impact of metal thickness, on the quality of factor-Q of spiral inductors, is shown.
E3S Web of Conferences
To improve efficiency and productivity of electric energy generators based on photovoltaic, wind ... more To improve efficiency and productivity of electric energy generators based on photovoltaic, wind or hybrid systems; several DC/AC conversion techniques have been developed and tested like multilevel inverters. Multilevel inverters are a performant solution for the ramp-up of converters. As soon as the DC supply voltage exceeds a few kV, it is necessary to combine switches, switching cells or converters. This paper presents a progressive study of an interesting type of these inverters namely flying capacitor multilevel inverters (FCMLI): architecture, evolutions, benefits and inconvenient. In fact, we processed 3-and 5-level FCMLI while presenting possible circuit schemes and simulation results on Matlab Simulink. Finally, a general formulation has been adopted and applied to a 17 level FCMLI.
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Papers by Abdelhadi Raihani