Said Jai Andaloussi

• Pr
• Professor at University of Hassan II Casablanca

Artificial Intelligence (AI) chatbots play an important role in modern izing education, particularly e-learning platforms by acting as intelligent tools to address issues such as disengagement and dropout rates. AI chatbots are also used to captivate students through engaging and enjoyable learning activities. These chatbots can enhance the peda...

A healthy lifestyle encompasses physical, mental, and emotional well-being, with healthcare and nutrition as central components. For those with chronic diseases such as diabetes, effective self-management involves continuous monitoring and dietary adjustments. Understanding the glycemic index (GI) is vital, as it indicates how carbohydrates affect...

In the evolving landscape of health information management, the application of blockchain and edge computing technologies to chronic disease management remains underexplored, despite the urgent need for scalable, secure, and real-time solutions. This systematic review examines the integration of these technologies in healthcare, with a specific foc...

Blockchain-based smart contracts are an emerging technology that has attracted significant interest from financial institutions, the banking sector, the academic community, and technology developers, particularly within the context of Industry 5.0. These sectors recognize that smart contracts have significant potential for benefit and innovation. D...

Early diagnosis and screening of eye disorders are crucial for effective treatment. However, with the increasing prevalence of these conditions and a shortage of ophthalmic specialists, it is imperative to employ automated image evaluation methods to ensure consistent diagnoses and address this growing concern. Previous studies have focused on iden...

Bipolar disorder is a challenging mental health condition characterized by recurrent periods of depression and mania. Successful management of bipolar disorder necessitates ongoing monitoring of symptoms, triggers, and individual behaviors. The emergence of the Internet of Behaviors (IoB) offers a promising prospect to enhance bipolar disorder mana...

Food image recognition and nutritional analysis, in particular glycemic index (GI), play a crucial role in understanding the impact of diet on human health and the management of chronic diseases such as diabetes. Deep learning, a subset of machine learning, has proven to be a powerful tool in this field. It enables precise recognition of foods from...

In fishery acoustics, surveys using sensor systems such as sonars and echosounders have been widely considered to be accurate tools for acquiring fish species data, fish species biomass, and abundance estimations. During acoustic surveys, research vessels are equipped with echosounders that produce sound waves and then record all echoes coming from...

The management of daily food intake aids to preserve a healthy body, minimize the risk of many diseases, and monitor chronic diseases, such as diabetes and heart problems. To ensure a healthy food intake, artificial intelligence has been widely used for food image recognition and nutrition analysis. Several approaches have been generated using a po...

The unexpected outbreak of the Corona virus (COVID-19) disrupted schools and universities around the world. Traditional classes were canceled, forcing schools and universities to switch to online learning. While developed countries have already adopted e-learning and online learning into their teaching practices, which made the transition relativel...

Diabetic retinopathy (DR) is the most important complication of diabetes. Early diagnosis by performing retinal image analysis helps avoid visual loss or blindness. A computer-aided diagnosis (CAD) system that uses images of the retinal fundus is an effective and efficient technique for the early diagnosis of diabetic retinopathy and helps speciali...

In the area of ophthalmology, glaucoma affects an increasing number of people. It is a major cause of blindness. Early detection prevents severe ocular complications such as glaucoma, cystoid macular edema, or diabetic proliferative retinopathy. Intelligent systems are proven to be beneficial for the assessment of glaucoma. In this paper, we descri...

This paper introduces a novel homogenization method to calculate the effective constitutive parameters of chiral artificial structures with mirror cells in two directions. This technique is applied when the wavelength is very large compared to details of the structure. On the one hand, it is based on reducing of the studied structure to an elementa...

In many developing countries, the healthcare sector is facing several challenges, mainly due to the lack of personal, institutions, and medications in public health systems. Over the past decade, information and communication technology has proved its ability to improve medical quality, reduce costs, and promote data security. Developing countries...

Because retinal hemorrhage is one of the earliest symptoms of diabetic retinopathy, its accurate identification is essential for early diagnosis. One of the major obstacles ophthalmologists face in making a quick and effective diagnosis is viewing too many images to manually identify lesions of different shapes and sizes. To this end, researchers a...

Diabetes is a chronic metabolic disease which is characterized by a permanently high blood sugar level. A distinction is made between two forms: Type 1 diabetes and Type 2 diabetes. It is believed that there are around 415 million people between the ages of 20 and 79 worldwide who have some form of diabetes illness today. In Europe, over 60 million...

Nowadays, healthcare is growing rapidly due to the large development of new technologies such as IoT and wearable devices. These devices are widely used to ensure remote patient monitoring. The current implementation is based on a client/server architecture. This raises several challenges regarding security and privacy that make healthcare systems...

In the area of ophthalmology, glaucoma affects an increasing number of people. It is a major cause of blindness. Early detection avoids severe ocular complications such as glaucoma, cystoid macular edema, or diabetic proliferative retinopathy. Intelligent artificial intelligence has been confirmed beneficial for glaucoma assessment. In this paper,...

Nowadays, traditional and online educational systems generate huge amounts of data. Extracting the useful knowledge and the hidden patterns from this data can help decision makers to improve teaching and learning by detecting undesirable students’ behaviors and predicting students’ performance. Educational data mining is the application of data min...

Near-duplicate video content has taken the large storage space in the age of big data. Without respecting the copyright ethic, social media users mirror, resize, and/or hide certain online video content and re-upload it as new data. This research aims to avoid the complex and high-dimensional matching and present an efficient approach for detecting...

Many approaches have proposed successful systems to recognize objects from an image. However, Overlapped objects recognition is still a main challenge for all kinds of objects. It is difficult for a machine to recognize two or more objects that partly hide each other. On the other hand, the new artificial neural network capsule network (CapsNet) ha...

In the area of ophthalmology, glaucoma affects an increasing number of people. It is a major cause of blindness. Early detection avoids severe ocular complications such as glaucoma, cystoid macular edema, or diabetic proliferative retinopathy. Intelligent artificial has been confirmed beneficial for glaucoma assessment. In this paper, we describe a...

With the rapid growth in the amount of video data, efficient video indexing and retrieval methods have become one of the most critical challenges in multimedia management. For this purpose, Content-Based Video Retrieval (CBVR) is nowadays an active area of research. In this article, a CBVR system providing similar videos from a large multimedia dat...

Objectives With the rapid evolution and technology advancement, the healthcare sector is evolving day by day. It is taking advantage of different technologies such as Internet of things and Blockchain. Several applications related to daily healthcare activities are adopting the use of these technologies. In this paper, we present a review in which...

Periodic boundary conditions are a set of boundary conditions that are often used to simulate large periodic structures by analysing an elementary cell. To enforce these boundary conditions over the side surfaces, the classical method requires identical meshes on opposite faces. This condition is not always easy to satisfy for arbitrary meshes. In...

With the rapid growth of the volume of video data and the development of multimedia technologies, it has become necessary to have the ability to accurately and quickly browse and search through information stored in large multimedia databases. For this purpose, content-based video retrieval ( CBVR ) has become an active area of research over the la...

This paper introduces a new method to impose the periodic boundary conditions on the arbitrary mesh when we use the edge finite element method. By using the Floquet theorem, we reduce the analysis of an infinite bi-periodic structure to an elementary cell with pseudo-periodic conditions on the lateral sides. In this method, we establish a relations...

With the rapid development in smart medical devices, Internet of things has a large applicability in healthcare sector. The current system is based on a centralized communication with cloud servers. However, this architecture increases security and privacy risks. This paper describes an architecture of a smart healthcare system for remote patient m...

In this paper, a content-based video retrieval (CBVR) system called Bounded Coordinate of Motion Histogram version 2 (BCMH v2) was processed on a distributed computing platform by using Apache Hadoop framework and a real-time distributed storage system using HBase. In fact, the amount of multimedia data is growing exponentially. Most of this data i...

Like any other distributed system, the Blockchain technology relies on consensus algorithms in order to reach agreement and secure its network. Over the past few years, several kinds of consensus algorithms were created in the Blockchain ecosystem. In this paper, we present some main consensus algorithms used by the Blockchain technology. We also p...

This paper proposes a binary classification method for high-resolution retinal images by using convolutional neural networks. The convolutional neural network is first, formed to recognize and classify the fundus images of the eye as normal retina or proliferative diabetic retina. We are training proposed network by using a graphics processor and a...

Time processing is a challenging issue for content-based video retrieval systems, especially when the process of indexing, classifying and retrieving desired and relevant videos is from a huge database. A CBVR system called bounded coordinate of motion histogram (BCMH) has been implemented as a case study. The BCMH offline step requires a long time...

Cloud Computing (CC) is an innovative computing model in which resources are provided as a service over the Internet, on an as-needed basis. It is a large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power, storage, platforms, and servi...

Traffic sign recognition is among the major tasks on driver assistance system. The convolutional neural networks (CNN) play an important role to find a good accuracy of traffic sign recognition in order to limit the dangerous acts of the driver and to respect the road laws. The accuracy of the Detection and Classification determines how powerful of...

The paper studies the influence on the similarity by extracting and using m from n frames on videos, the purpose is to evaluate the amount of the proportion similarity between them, and propose a new Content-Based Video Retrieval (CBVR) system. The proposed system uses a Bounded Coordinate of Motion Histogram (BCMH) [1] to characterize videos which...

We are entering an era of data, which are spatially and temporally referenced, this paper offers an opportunity to enhance geographic understanding, more especially in the term of air pollution and its relationship with human health, especially in the city of Mohammedia (Northern part of Morocco). Authors build a tool in the form of data mining sch...

To evaluate the electromagnetic properties of heterogeneous materials using the finite element (FE) method, the appropriate boundary conditions should be defined. The periodic boundary condition is one of the most efficient in terms of convergence rate. To impose these boundary conditions, the classical method (CM) requires a periodic mesh, where t...

Cancer tissues in mammography images exhibit abnormal regions; it is of great clinical importance to label a mammography image as having cancerous regions or not, perform the corresponding image segmentation. However, the detailed annotation of the cancer region is often an ambiguous and challenging task. The authors describe a fully automatic comp...

As the adoption of Cloud Computing is growing exponentially, many issues linked to security and lack of governance have been noted increasingly. In the domain of payment, other than coins and banknotes, the security of digital transaction is a big concern. In this paper, we extend the work done on APSIS (Advanced Persistent Security Insights System...

In this paper, we present new expressions of the effective constitutive parameters of bi-isotropic multilayered structure having an arbitrary number of layers and different thicknesses. The present method uses the decomposition scheme, and the commutativity between the homogenization process and the decomposition scheme is supposed. The effective c...

In this paper, the authors present a novel ContentBased Video Retrieval (CBVR) system based on Bounded Coordinate of Motion Histogram (BCMH). The authors propose to characterize videos by using spatio-temporal features (e.g. motion direction, intensity and the residual information features). Bounded Coordinate of Motion Histogram is introduced to c...

Mammography remains the most effective tool for the early detection of breast cancer and Computer-Aided Diagnosis (CADx) is usually used as a second opinion by the radiologists. The main objective of our study is to introduce a method to generate and select the features of suspicious lesions in mammograms and classifying them by using support vecto...

Mammography remains the most effective tool for the early detection of breast cancer, as well as the systems of computer-aided detection/diagnosis (CAD) is typically used as a second opinion by the radiologists. So, the main goal of our method is to introduce a new approach for automatic detecting the suspicious lesions in mammograms (regions of in...

Computer-aided detection/diagnosis (CAD) is usually used as a second opinion by the radiologists and the mammography represents the most effective tool for the early detection of breast cancer. The main objective of this study is to introduce a new approach to extract and select the features of suspicious lesions in mammograms and classifying them,...

Mammography remains the most effective tool for the early detection of breast cancer and Computer Aided Diagnosis (CAD) is usually used as a second opinion by the radiologists. segmentation and classification of breast masses in mammography play a crucial role in Computer Aided Diagnosis system (CAD) . In this paper we propose an approach based on...

Breast cancer is the most common cancer and the leading cause of morbidity and mortality among women’s age between 50 and 74 years across the worldwide. In this paper we’ve proposed a method to detect the suspicious lesions in mammograms, extracting their features and classify them as Normal or Abnormal and Benign or Malignant for diagnosing of bre...

This issue (DOI: 10.13140/RG.2.1.2915.0163) includes the following papers; P1150946919, Y. Es Saady and A. Rachidi and M. El Yassa and D. Mammass, "Printed Amazigh Character Recognition by a Syntactic Approach using Finite Automata" P1150945913, Santosh V. Chapaneri and Jeffrey J. Rodriguez, "Content-Adaptive Temporal Error Concealment Scheme for H...

This paper presents a method for segment and detects the boundary of different breast tissue regions in mammograms by using dynamic K-means clustering algorithm and Seed Based Region Growing (SBRG) techniques. Firstly, the K-means clustering is applied for dynamically and automatically generated the seeds points and determines the thresholds' value...

This paper presents a method for segment and detects the boundary of different breast tissue regions in mammograms by using dynamic Kmeans clustering algorithm after evaluate it by using Seed Based Region Growing (SBRG) techniques. Firstly, the K-means clustering is applied for dynamically and automatically divides mammogram into homogeneous region...

This paper introduces a new paradigm regarding the relationship between content and application. We propose to aggregate content and application in a new abstraction level called Capsid and we show its benefits. In this paradigm, documents are considered as live objects, distributed in a next-generation network. Duplication, tracking and security i...

This paper presents a method for the detection of regions of interest (ROI) in mammograms by using a dynamic K-means clustering algorithm. This method is used to partition automatically an image into a set of regions (clusters or classes). Our method consists of three phases: firstly, preprocessing images by using thresholding and filtering methods...

Breast mass segmentation in mammography plays a crucial role in Computer-Aided Diagnosis (CAD) systems. We propose in this article a method for the segmentation of mammography images. We use a combined solution of the two approaches; one based on levels set theory and the other based on the principle of the minimization of the energy of active cont...

Segmentation and classification of breast masses in mammography play a crucial role in Computer Aided Diagnosis system (CAD) . In this paper we propose an approach consisting of two methods. The first is the main stage in image processing which is the mammograms segmentation. This method is based on the theory of all levels and minimization of the...

Breast mass segmentation in mammography plays a crucial role in Computer-Aided Diagnosis (CAD) systems. In this paper a Bidimensional Emperical Mode Decomposition (BEMD) method is introduced for the mass segmentation in mammography images. This method is used to decompose images into a set of functions named Bidimensional Intrinsic Mode Functions (...

This paper presents a video coding and decoding technique based on vector quantization. The objective is to develop a lightweight, efficient and real-time video decoder able to decode in real-time several video streams simultaneously, on low-end hardware. We show how to layout the output bitstream in order to facilitate decoding on highly constrain...

Most medical images are now digitized and stored in large image databases. Retrieving the desired images becomes a challenge. In this paper, we address the challenge of content based image retrieval system by applying the MapReduce distributed computing model and the HDFS storage model. Two methods are used to characterize the content of images: th...

Most medical images are now digitized and stored in patients files databases. The challenge is how to use them for acquiring knowledge or/and for aid to diagnosis. In this paper, we address the challenge of diagnosis aid by Content Based Image Retrieval (CBIR). We propose to characterize images by using the Bidimensional Empirical Mode Decompositio...

In this paper, we address the problem of medical diagnosis aid through content based image retrieval methods. We propose to characterize images without extracting local features, by using global information extracted from the image Bidimensional Empirical Mode Decomposition (BEMD). This method decompose image into a set of functions named Intrinsic...

Nous nous intéressons à la recherche d'images médicales par leur contenu numérique, et proposons une approche basée sur la décomposition BEMD (Bidimensionnel Empirical Mode Decomposition des images). La BEMD permet de décomposer une image en plusieurs modes BIMFs (Bidimensionnel Intrinsic Mode Functions), qui permettent d'accéder à des informations...

Nous nous intéressons à la recherche d'images médicales par leur contenu. Pour construire un vecteur caractéristique d'une image, nous effectuons une analyse fréquentielle de l'image basée sur la méthode BEMD (Bidimensionnel Empirical Mode Decomposition). La BEMD permet de décomposer une image en plusieurs modes BIMFs (Bidimensionnel Intrinsic Mode...

Bidimensional empirical mode decomposition BEMD is a new form of multi-scale decomposition has superior quality in extracting intrinsic components of texture and reconstruction. This paper proposes a new technique based on block-based BEMD method (BBEMD) compared with the global BEMD in the characterization of the textured image and reconstruction....