Omar Bouattane

Université Hassan II de Casablanca · Department of Electrical Engineering

This article proposes a load balancer to meet the unbalance voltage and charge balancing between capacitors issues. A distributed charge balancing in a 1-D grid of supercapacitor is studied in this paper. Different mathematical finding are developed and demonstrated. The stability of the 1-D grid of supercapacitors is shown by Matlab and described...

Analyzing historical stock market data using machine-learning techniques is crucial for data scientists and researchers to optimize stock price prediction models. This study uses machine learning regression algorithms and feature selection methods to optimize a simulated stock price prediction model using real historical data from Bank of Africa, a...

Parkinson's disease is a progressive neurodegenerative disorder that causes significant physical disabilities and reduces the quality of life. This disease is caused by the loss of dopamine-producing cells in the brain. Its symptoms are Speech disorders, muscle rigidity, bradykinesia and tremors that cause involuntary shaking or trembling, typicall...

This paper investigates the integration of Zero-Knowledge Proofs (ZKP) and OAuth 2.0 to enhance anonymity and security in multi-agent distributed systems. We propose an approach that allows agents to authenticate and prove possession of specific data without revealing the underlying details. Additionally, we outline a potential access control strat...

According to the World Health Organization (WHO), cardiovascular disease is one of the leading causes of death worldwide. Thus, the prevention of this kind of illness is considered as a huge human health challenge. Additionally, the diagnostic process often involves a combination of clinical examination, laboratory tests, and other diagnostic proce...

In this paper, we present a new method based on deep learning for the detection of cardiac arrhythmias. The proposed method is based on three fundamental components: an inception-ResNet structure, bidirectional LSTM layers and a multi-scale signal analysis technique. To improve processing of the MIT-BIH arrhythmia dataset, we have developed a three...

Parkinson’s disease is the second most common neurological disorder that causes significant physical disabilities, decreases the quality of life, and does not have a cure. Because it is a nervous system disorder, it impacts people in different ways, affecting movement and speech and causing muscle stiffness. Approximately, 90% of people with Parkin...

In this paper, a sustainable, intelligent energy management system for a microgrid based on a multi-agent system (MAS) is studied. The system is designed to address the challenges posed by the intermittence of renewable energy sources. Also, the system optimizes the use of available AC–DC renewable energy sources by utilizing load flexibility and t...

Road traffic accidents caused by traffic violations are a major public health issue that results in loss of lives and economic costs. Therefore, it is important to prioritize road safety measures that reduce the incidence and severity of accidents. In this study, we suggest an incremental road safety strategy that identifies high-risk areas and com...

With their many advantages, including low power dissipation in power switches, low harmonic content, and reduced electromagnetic interference (EMI) from the inverter, multilevel converter (MLI) topologies are becoming more and more in demand in high and medium power applications. This paper introduces a novel multi-level symmetric inverter topology...

One of the main contemporary health issues in the healthcare system is multimorbidity, which is the co-existence of two or more diseases in the same patient. With the emerging of big data era, the need of analytical tools to extract actionable knowledge from high volumes of medical data is increasing to better understand Multimorbidity and manage h...

In the last decade, healthcare systems have played an effective role in improving medical services by monitoring and diagnosing patients' health remotely. These systems, either in hospitals or in other health centers, have experienced significant growth with emerging technologies. They are becoming of great interest to many countries worldwide nowa...

In this thesis work, we are particularly interested in three essential points related to oriental music, a work of extraction and modelling of the characteristics resulting from the audio signals of the oriental music, a work of classification based on machine learning to identify the influence of the style of play of the artist, and a work of arti...

Photovoltaic (PV) power has became an attractive research subject, despite the variability and uncertainty of the phenomenon, PV power forecasting is considered as a promising solution for successful PV power integration, and also an important decision making information for both, grid operators and energy traders. Forecasting the aggregated PV pow...

DISPOSITIF POLYMORPHIQUE ADAPTATIF BIDIRECTIONNEL ET REVERSIBLE DE CONVERSION D’ENERGIE ELECTRIQUE

Image processing by segmentation technique is an important phase in medical imaging such as MRI. Its objective is to analyze the different tissues in human body. In research area, Fuzzy set is one of the most successful techniques that guarantees a robust classification. Spatial FCM (SFCM); one of the fuzzy c-means variants; considers spatial infor...

Due to the rapid growth of urban vehicles, traffic congestion has become more serious. The signalized intersections are used all over the world and still established in the new construction. This paper proposes a self-adapted approach, called evolutionary rienforcement learning multi-agents system (ERL-MA), which combines computational intelligence...

Aim: Multi-morbidity remains poorly understood due to the multifactorial complexity of this phenomenon and the lack of a standardized methodology for building and analysing Multimorbidity network. A comparative analysis of methods of modeling Multimorbidity network in literature may help to understand the pros and cons of these methods, then to fac...

Multimorbidity is one of the major problems in recent health care systems, the more conditions the patients suffer from, the worst psychological pressures are put upon these patients. We formulate Multimorbidity detection as a hypergraph learning problem. Then we propose an implementation of a multimorbidity pattern detection using Multimorbidity c...

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 r...

Traffic congestion remains a hard phenomenon problem to solve. Due to the difficulty and high cost of solutions, many studies are trying to find the most inexpensive solutions. However, with the exponential growth of technology, new opportunities and challenges are opening up to reduce congestion problems. This paper focuses on the minimization of...

Quadtrees are known hierarchical data structures to represent image if sizes 2r*2r. Quadtree construction is one of the biggest operation for many algorithms that manipulate data structures. Determining the level(depth) of each image pixels (quadtree construction)takes almost O(r) computational times , where r is the height of a given quadtree. The...

Breast thermography is a promising screening technique for the early detection of breast cancer. Abnormalities like inflammation and malignancies cause localized increases in temperature which appears as hot spots. Accurate segmentation of the hottest regions as the suspicious region is a challenging issue in the infrared thermal images processing....

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 ba...

Multimorbidity is one of the major problems in the modern medical system. The more conditions the patient has, the greater the psychological pressure will be. We propose a formal definition of the general case of Multimorbidity Disease Network detection. Based on pairwise association method, we constructed an undirected weighted graph of co-occurre...

In this article, we propose a model based on Q-learning to correct, in real-time, the frequent errors in the incoming flows in a company. When receiving a stream that contains structured data, and which may contain errors, it should be known what it is the succession of algorithms to be used to make a record go from a state where errors exist to a...

Age and sex are important biological factors that should be taken into account in each medical phenomenon. With the increasing amount of recorded data, data science methods became necessary tools for extracting useful knowledge. We propose in this work to investigate the role of age and sex in prediction of developing multimorbidity. In machine lea...

Multimorbidity is the existence of two or more than two diseases in the same patient at the same time. It is a major problem in the modern healthcare system and several studies have pointed out the association between the burden of multimorbidity and poor quality of life. It is quite intuitive to represent multimobid diseases as a weighted graph. W...

This paper proposes polymorphic storage unit based on a grid of supercapacitors, enabling the interchanging and the switching of the supercapacitors (SCs) to meet the available voltage in the load or source side, to be consumed or provided. This paper shows the polymorphic storage unit interest that is more much relevant in the small voltage recove...

This paper proposes an advanced control scheme for a hybrid renewable energy system based on a PV conversion system and Li-ion Battery. This strategy ensures three operating modes are handled by a suitable algorithm based specifically on battery State of Charge (SoC): (i) MPPT mode: used when the system is controlled to operate in its Maximum Power...

In this paper, we propose a model for recognizing the playing style of the oud player according to the grandmasters, and we identify the influence rates of each oud player concerning a way to play, this solution is based on the extraction of technical characteristics of the audio signals through the signal processing mechanism. Standardization, dat...

IT transformation has revolutionized the business landscape and changed most of organizations business model into digital and innovation driven firms. To fully take advantage of this digitalization and the exponential growth of data, organizations need to rely on resilient, scalable, extremely connected, highly available & very performant systems....

The digital age is accompanied by a proliferation of crimes and attacks against institutions handling banking data, such as card fraud and electronic payments. The traditional protection systems used by banks based on rules and signatures are proving increasingly insufficient and ineffective in the face of constantly evolving attack techniques. Art...

Social robots keep proliferating. A critical challenge remains their sensible interaction with humans, especially in real world applications. Hence, computing with real world semantics is instrumental. Recently, the Lattice Computing (LC) paradigm has been proposed with a capacity to compute with semantics represented by partial order in a mathemat...

In this paper, we propose a computer-aided diagnostic system based on a fuzzy expert system, in order to help physicians, make the right diagnosis and offer an opportunity to improve access to health care in rural areas in Morocco, where there is a lack of infrastructure and medical experts. The system is mainly based on the diagnoses of various ph...

In this paper, we propose a new epidemic SIR model with infection during transport, SIR-M. Under biologically motivated assumptions, we prove the positivity and boundedness of the solutions, calculate the basic reproduction number and the disease-free equilibrium. We prove that the disease-free equilibrium is globally asymptomatically stable if R0...

Human middle ear ensures sound transfer due its ossicular chain, any disorder or abnormalities in this structure leads to a conductive hearing loss (CHL). Tinnitus is a health problem, associated with hearing loss, it remains a devastating symptom. In this work, we present an electrical model of the human middle ear including middle ear cavities (Z...

This paper deals with a dynamical analysis of a proposed charge balancing device. In Fact, many energy converters or harvesters need to supply a uniform signal and continuous energy flow to loads. In the context of a decentralized renewable energy sources, the intermittency poses a real challenge to ensure stable production and energy consumption f...

Reality is shaped differently in software environments through Virtual Reality VR and augmented Reality AR, it has a remarkable position and an important background with its role of ensuring contact between the software environment and the user. It was popular in the entertainment sector, in particularly industry, but over time, it becomes apparent...

Modeling of an intersection is a sensible step to achieve due to the interference of various actors, and it is a mandatory phase to attain efficient public transportation in big cities. Several attempts methods try to imitate the intersection, such as queuing theory, Petri net, cell transmission model, and intersection graph. In this paper, a gener...

Cardiac cine magnetic resonance imaging (MRI) continues to be recognized as an established modality for non-invasive assessment of the function and structure of the cardiovascular system. Making full use of fully convolutional neural networks CNNs ability to operate pixel-wise classification, cine MRI sequences can be segmented and volumetric featu...

Industrial networks based on the Internet of Things (IoT) have become the backbone of Industry 4.0. Indeed, these connected objects increase the efficiency, flexibility and autonomy of machines, thus improving the productivity and profitability of factories. However, the opening up of digitization technologies, especially in environments where fail...

A nonlinear control of a PV Energy Conversion System (PVECS) with energy storage system and maximum power extraction is presented. The control strategy is designed in two steps. Firstly, a MPPT algorithm is designed to tracking the maximum power point in variable irradiations, battery state of charge (SOC) and load changes. Then, thanks to its many...

Most of NLP research fields (Translation, Classification, Dialogue Systems ...) have been revolutionized by the rise of deep learning methods, which rely on the new dense and low-dimensional feature representation. We present in this article the basic training techniques of Word Embeddings as well as the recent works on Abstractive Neural S ummari...

Visual stimuli are essential in many applications in human robot interaction. However, such tasks are usually computationally intensive. Also, data received from the various sensors on a robot require different data representation and processing techniques, which increases the complexity and makes the fusion of sensory data for decision making more...

The field of multi agent systems (MAS) presents a multitude of middlewares allowing an ease to create and deploy applications of MAS. These middlewares are designed with programming models that strongly couple the communication framework of the agent and its cognitive pattern. Usually, more the number of agents used is large, more the communication...

This paper presents a new distributed polymorphic learning model for a community of heterogeneous cyber physical robots operating in a multi agent environment. This model allows a community of intelligent physical agents to exchange their minds represented by configured and trained neural net-works. The training operation of the neural networks is...

This paper details a hardware implementation of a distributed Θ(1) time algorithm allows to select dynamically the master device in ad-hoc or cluster-based networks in a constant time regardless the number of devices in the same cluster. The algorithm allows each device to automatically detect its own status; master or slave; based on identifier wi...

The growth of Big Data, memory wall and power wall are posing unprecedented demand for Processing In Memory (PIM). A computational memory architecture supporting in bit-Line processing can be a major key for PIM to eliminate the overhead of moving data from processing unit to memory and vice versa. It promises high bandwidth, massive parallelism, a...

Machine learning (ML) technique behind the most existing abilities fields in several areas like languages processing, robotics, including medicine. The most important medical applications are the early prediction system for heart diseases especially, coronary artery disease (CAD) also called atherosclerosis. The need for a medical diagnosis support...

High quality virtual and/or augmented scenes using (multiple) mobile/robot projectors requires precise auto-positioning and auto-correcting of projectors and their corresponding frames' buffers, respectively, in order to auto-fit projections into a single planar 3D display screen. The ideal projector camera system, using a stationary calibrated cam...

Tinnitus is a phenomenon for which the patient hears sound in the absence of any external sound source. To this day, there is no cure for this phantom sound perception. But it can be masked temporarily to help relief the patient's pain. In order to allow this, a better understanding of the phenomenon is needed. A validated acoustic model of the out...

This paper is a case study of the integration of an energy management system (EMS) in a commercial building. A detailed analysis of this EMS's impact on energy consumption is presented. High energy demand is very common in commercial and industrial facilities. With this in mind, the present work aims to improve the energy consumption rate within a...

The Computational Memory Architecture (CMA) is composed of interconnected and controlled computelines (CL). CL supports in bit-line processing that brings parallel computation as close as possible to the location of the stored data. CL supports in memory computing without requiring dedicated computational, pre-charging and/or sensing (logic) circui...

The Internet of Things (IoT) is becoming an indispensable part of the actual Internet and continues to extend deeper into the daily lives of people, offering distributed and critical services. Mobile agents are widely used in the context of IoT and due to the possibility of transmitting their execution status from one device to another in an IoT ne...

Multi-morbidity, or the co-occurrence of two or more diseases at the same time for the same patient, is a major modern health problem in medicine. It can be modeled in network perspective and we can make use of advances in network analysis studies to get insight about this phenomenon. Despite recent trials of applying theoretical network analysis i...

The computational Memory Architecture (CMA) supporting in bit-line processing brings parallel computation as close as possible to the location of the stored data without using any dedicated logic unit(s) for computation. It is composed of multiple compute-lines and introduces promising potentials to cope with the growth of Big Data, memory wall and...

This paper aims to present a new model based on JSON Web Token (JWT) and Public Key Infrastructure (PKI) for communication security as part of a Multi-Agent System Middleware for massively distributed systems. The proposed model aims to provide secure communications between agents to ensure the integrity of the exchanged messages, the authenticatio...

A hybrid genetic approach (HGA) is proposed to solve the fuzzy graph coloring problem. The proposed approach integrates a number of new features, such as an adapted greedy sequential algorithm, which is integrated in genetic algorithm to increase the quality of chromosomes and improve the rate of convergence toward the chromatic number. Moreover, a...

The Music Composition Library of the great composers constitutes an intellectual heritage. This article introduces an algorithm of artificial Oriental composing music based on the descriptors determined on a large learning base to automatically write Oriental music as the logic identical to any composer. Musical words are called a grammatical alpha...

Insurance fraud is one of the most practiced frauds in the sectors of the economy. Faced with increasingly imaginative underwriters to create fraud scenarios and the emergence of organized crime groups, the fraud detection process based on artificial intelligence remains one of the most effective approaches. Real world datasets are usually unbalanc...

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 usi...

Today, Processing In Memory (PIM) is in demand more than ever to cope with the growth of Big Data, memory wall and power wall. Most existing PIM works are concentrated on near-memory processing (NMP) and/or in-memory processing (IMP). A computational Memory Architecture (CMA) supporting in bit-line processing brings parallel computation as close as...

The roundabout is a very old shape of junction which have been used, but when there are more than two lanes create a congestion problem. This paper deals with a fluid mechanics model to calculate the total capacity in roundabout, then a solution algorithm based on SUMO simulation is developed. The concept is collecting traffic data from inputs and...

Emotional child-robot interaction helps catching quickly child attention and enhancing information perception during learning and verbalization in children with Special Educational Needs (SEN). This will improve the pedagogical rehabilitation for these children and also develop their emotional knowledge and memory in play-like activities mediated b...

The roundabout is a very old shape of junction which have been used, but when there are more than two lanes create a congestion problem. This paper deals with a physical model, simulation and analysis traffic congestion occur at roundabout, the concept is collecting traffic data from inputs and outputs sources of a specific roundabout to avoid cong...