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Teaching Documents by Aziza EL OUAAZIZI

La programmation consiste à écrire un ensemble d'instructions dans un ordre bien défini, avec un ... more La programmation consiste à écrire un ensemble d'instructions dans un ordre bien défini, avec un langage compréhensible par l'ordinateur, qui une fois exécuté aboutit à la résolution d'un problème.

Objectifs : Découvrir Microsoft Access Créer, fermer et ouvrir une base de données Créer et modif... more Objectifs : Découvrir Microsoft Access Créer, fermer et ouvrir une base de données Créer et modifier la structure d'une table Ajouter et supprimer un enregistrement en mode feuille de données Etape 1: Créer, fermer et ouvrir une base de données 1. Démarrer Microsoft Access. (Démarrer/Tous les programmes/Microsoft Access) 2. Créer une nouvelle base de données sous le nom Gestion client sur votre disquette. (Dans le volet Office/Base de données vide) Définition Une base de données c'est un ensemble de données relatives à un sujet particulier par exemple les données relatives aux clients d'une société. Microsoft Access est un Système de Gestion des Bases de Données (SGBD) relationnel qui vous permet de stocker et gérer toutes vos informations à l'aide d'un fichier unique de base de données (extension .MDB). Dans ce fichier, vous devez répartir ces données entre plusieurs tables reliées entre eux (d'où la nomination SGBD relationnel). Autres les Tables, un fichier Access peut contenir des : • Requêtes: permettent d'afficher les informations d'une ou plusieurs qui répondent à une ou plusieurs conditions. • Formulaires : permettent d'afficher, saisir et modifier facilement et d'une manière conviviale les données d'une ou plusieurs tables. • Etats: permettent d'imprimer des données contenues dans des tables selon une présentation définie en y intégrant éventuellement des calculs. • Macros: permet d'automatiser une suite d'opérations répétitives. • Modules: Programmes écrits en Visual Basic for Application (VBA) pour réaliser des opérations plus compliquées que les fonctionnalités d'Access.

 La La réalisation réalisation d'un d'un système système informatique informatique (logiciel) (... more  La La réalisation réalisation d'un d'un système système informatique informatique (logiciel) (logiciel) nécessite nécessite: : une une phase phase d'analyse d'analyse   comprendre comprendre et et décrire décrire de de façon façon précise précise les les besoins besoins des des utilisateurs utilisateurs ou ou des des clients clients. . Imaginer Imaginer la la solution solution. . Une Une phase phase de de conception conception   apporter apporter plus plus de de détails détails à à la la solution solution et et clarifier clarifier les les aspects aspects techniques, techniques, tels tels que que l'installation l'installation des des différentes différentes parties parties logicielles logicielles sur sur un un matériel matériel. .  La La réalisation réalisation de de ces ces deux deux phases phases nécessite nécessite des des méthodes, méthodes, des des conventions conventions et et des des notations notations. .

Diagramme de classe Diagramme de classe  le le diagramme diagramme de de classes classes montre... more Diagramme de classe Diagramme de classe  le le diagramme diagramme de de classes classes montre montre la la structure structure interne interne du du système, système, il il contient contient principalement principalement des des classes classes. .

Le département d'informatique vous demande de développer un logiciel de gestion des cours en lign... more Le département d'informatique vous demande de développer un logiciel de gestion des cours en ligne. Ils ne sont pas satisfaits des systèmes présentement disponibles. Ce sont les techniciens qui s'occupent de la gestion des cours dans ce système. Ils sont donc en mesure d'enregistrer des cours, de supprimer un cours, d'inscrire des étudiants, d'inscrire un étudiant dans un cours, d'enlever un étudiant d'un cours. Quand le technicien inscrit un étudiant, il doit absolument l'inscrire à au moins un cours pour que l'inscription soit valide. Quand le technicien supprime un cours, il doit aussi enlever tous les étudiants de ce cours. Le technicien peut aussi envoyer des e-mails aux intervenants d'un cours.

La société C fabrique des pièces métalliques réalisées dans son atelier. La société C est en rela... more La société C fabrique des pièces métalliques réalisées dans son atelier. La société C est en relation commerciale uniquement avec des clients réguliers. Les factures sont mensualisées: toutes les commandes d'un client dans le mois sont facturées à la fin du mois.

Modéliser le texte suivant par un diagramme de classes:

TP 3: Implémentation des arbres de décision L'apprentissage par arbre de décision consiste à cons... more TP 3: Implémentation des arbres de décision L'apprentissage par arbre de décision consiste à construire un arbre depuis un ensemble d'apprentissage étiqueté. Chaque noeud interne décrit un test sur une variable d'apprentissage, chaque branche représente un résultat du test, et chaque feuille contient la valeur de la variable de sortie.

Le K-Means Clustering est un algorithme d'apprentissage machine non supervisé. Contrairement aux ... more Le K-Means Clustering est un algorithme d'apprentissage machine non supervisé. Contrairement aux algorithmes traditionnels d'apprentissage machine supervisé, K-Means tente de classer des données sans avoir été entrainé au préalable avec des données étiquetées. Une fois l'algorithme exécuté et les groupes définis, toute nouvelle donnée peut être facilement attribuée au groupe le plus le plus proche.

Multimedia Tools and Applications, Feb 22, 2023

The growing chronic diseases patients and the centralization of medical resources cause significa... more The growing chronic diseases patients and the centralization of medical resources cause significant economic impact resulting in hospital visits, hospital readmission, and other healthcare costs. This paper proposes a scalable and real-time system for disease prediction from medical data streams. This is carried out by integrating Twitter, Apache Kafka, Apache Spark and Apache Cassandra. Thus, Twitter users tweet attributes related to health, Kafka streaming receives all desired tweets attributes and ingest them to Spark streaming. Here, a machine learning algorithm is applied to predict health status and send back a response message through Kafka. The heart disease dataset, obtained from the UCI repository, was used for experiments. In order to enhance prediction accuracy, Relief algorithm is used for features selection. We compared sex types of relevant machine learning algorithms implemented by Spark MLlib such as Random Forest (RF), Naive Bayes, Support Vector Machine, Multilayer Perceptron, Decision Tree and Logistic Regression with the full features as well as selected features. The highest classification accuracy of 92.05% was reported using RF with selected features. The scalability of RF using Spark MLlib and WEKA framework for both training and application stages was measured. The results show significantly better performances of Spark in terms of scalability and computing times.

Pattern Recognition Letters

The Processing of Arabic text to generate images is a challenging task. Because the Arabic langua... more The Processing of Arabic text to generate images is a challenging task. Because the Arabic language belongs to the Semitic group of languages and it is less discovered than English in the Artificial Intelligent community. It is also a right-to-left language that needs special natural language tools to process. On the other hand, efficient text-to-image generation architectures have been built by the Generative Adversarial Network methodology, which had shown incredible results in so many tasks. In this paper, because the text is the first domain of the text-to-image generation task, we increase the effectiveness of Arabic text-to-image generation by implementing tree approaches. Firstly, We fuse the AraBERT with DF-GAN by injecting the AraBERT sentence vector into the DF-GAN generator and discriminator. Secondly, we fuse a sample text transformer with a DF-GANs generator and discriminator to overcome the out-of-vocabulary limitation. Thirdly, we keep the training process and the tex...

Advances in Science, Technology and Engineering Systems Journal

Bird watchers and people obsessed with raising and taming birds make a kind of motivation about o... more Bird watchers and people obsessed with raising and taming birds make a kind of motivation about our subject. It consists of the creation of an Android application called "Birds Images Predictor" which helps users to recognize nearly 210 endemic bird species in the world. The proposed solution compares the performance of the python script, which realizes a convolutional neural network (CNN), and the performance of the cloud-bound mobile application using IBM's visual recognition service to choose the platform one. android form. In the first solution we presented an architecture of a CNN model to predict bird class. While the other solution, which shows its effectiveness, is based on IBM's visual recognition service, we connect the IBM project that contains the training images with our Android Studio project using an API key , and the IBM process classifies the image captured or downloaded from the application and returns the prediction result which indicates the type of bird. Our study highlights three major advantages of the solution using IBM's visual recognition service compared to that of CNN, the first appears in the number of images used in training which is higher compared to the other and the strong distinction between bird types where images and bird positions come together in color. The second advantage is to create a trained model saved on the cloud in order to use it with each prediction the most difficult thing to do locally due to the low processing capacity of smartphones. The last advantage is reflected in the correct prediction with a certainty of 99% unlike the other solution due to the instability of the CNN model.

The growing chronic diseases patients and the centralization of medical resources cause significa... more The growing chronic diseases patients and the centralization of medical resources cause significant economic impact resulting in hospital visits, hospital readmission, and other healthcare costs. This paper proposes a scalable, big data, real-time health status prediction and analytical system to filter, manage, process, predict and store streaming health data. The proposed system uses Twitter as data source, Apache Kafka as ingestion tool, Apache Spark as computing engine, Apache Cassandra as storage engine and Apache Zeppelin as analytical tool. Proposed Spark Parallel Random Forest (SPRF) is used as data classifier. The idea is to use Twitter as a communication channel to transmit data generated by IoT medical devices to a system to perform analytics in a real-time fashion, using streaming. Thus, Twitter users tweet attributes related to health, Kafka streaming receives all desired tweets attributes and ingest them to Spark streaming. Here, a machine learning algorithm model is a...

Current AI systems have shown impressive results in the Automatic synthesis of high-resolution re... more Current AI systems have shown impressive results in the Automatic synthesis of high-resolution realistic images from texts descriptions. Specifically, Generative Adversarial Networks (GANs) as a powerful technology that utilizes computer vision tools to create two models, the Generator that generates realistic images and the discriminator that distinguishes whether the images synthesized are real or fake. Further, Most text-to-image generation frameworks leverage the power of GANs to generate realistic images conditioned with texts descriptions. In this paper, we fuse a sample and efficient text-to-image generation framework called DF-GAN and AraBERT architecture to generate images conditioned with Arabic texts descriptions. Firstly, we recreate new datasets matching the Arabic text-to-image generation task by applying super translation using the DeepL-Translator from English to Arabic on texts descriptions. Secondly, we leverage the power of AraBERT which is trained on billions of Arabic words to produce a strong sentence embedding, and we reduce that vector's dimension to match with DF-GAN shape. Thirdly, we inject the reduced sentence embedding into the DF-GAN framework to generate high-resolution realistic, and textmatching images conditioned with Arabic texts descriptions. Such as in previous work, we use CUB and Oxford-102 flowers as original datasets. Further, we measure our framework with FID and IS. Our framework Springer Nature 2021 L A T E X template 2 is the first that achieve much success in generating high-resolution realistic and text matching images conditioned with Arabic text.

E3S Web of Conferences

This paper proposes an automatic COVID-19 detection model using chest X-ray images. The proposed ... more This paper proposes an automatic COVID-19 detection model using chest X-ray images. The proposed model is developed to give accurate diagnostics for multiclass classification (COVID vs. PNEUMONIA vs. NORMAL). Our model produced a classification accuracy of 96%. Evaluation has been done on publicly available databases containing covid19, pneumonia and normal X-ray images. The proposed approach uses the VGG-16 model with pre-trained weights in the initialization step.

Crack defect detection and localization using genetic-based inverse voting Hough transform

In this paper, a hybrid method is applied to recove r parameters and motion of camera from a set ... more In this paper, a hybrid method is applied to recove r parameters and motion of camera from a set of silhouettes of an object taken under circular motio n. Camera parameters can be obtained by maximizing the total coherence between all silhouettes. Two optimi zation methods, the Powell optimizer (PO) and the Genetic algorithms (GA), are applied to maximize th silhouette coherence and their performances are compared for several experiments. To take advantage of the strengths of the two methods, we developed a hybrid method that combines the genetic algorithm a nd the Powell optimizer to improve the performances in term of convergence speed and accuracy. The reco vered parameters are used for 3D image-based modeling to obtain high fidelity 3D reconstruction.

In this paper, a hybrid method is applied to recover parameters and motion of camera from a set o... more In this paper, a hybrid method is applied to recover parameters and motion of camera from a set of silhouettes of an object taken under circular motion. Camera parameters can be obtained by maximizing the total coherence between all silhouettes. Two optimization methods, the Powell optimizer (PO) and the Genetic algorithms (GA), are applied to maximize the silhouette coherence and their performances are compared for several experiments. To take advantage of the strengths of the two methods, we developed a hybrid method that combines the genetic algorithm and the Powell optimizer to improve the performances in term of convergence speed and accuracy. The recovered parameters are used for 3D image-based modeling to obtain high fidelity 3D reconstruction.

Object recognition supported by user interaction for service robots

We propose a genetic-based inverse voting Hough transform (GBIVHT) method to detect buried crack ... more We propose a genetic-based inverse voting Hough transform (GBIVHT) method to detect buried crack defects in engineering structures. The method is applied to B-scan images obtained according to the ultrasonic time of flight diffraction technique. In these image representations of the ultrasound data, crack defects are characterized by multiple arcs of diffraction that can be approximated by a parabolic model.

IIEEE International Conference on Acoustics Speech and Signal Processing, 2002

In this paper we propose a Genetic-Based Inverse Voting Hough Transform (GBIVHT) method for detec... more In this paper we propose a Genetic-Based Inverse Voting Hough Transform (GBIVHT) method for detecting parabolic shapes in B-scan images obtained by the ultrasonic Time Of Flight Diffraction inspection technique. These parabolic shapes are characteristics of the presence of crack defects in the engineering structure under inspection. In our method, the local peak detection problem in the parameters space of conventional Hough Transform is converted into a parameter optimization problem that operates directly on the ultrasound B-scan image. The optimization is done using the well-known Genetic Algorithms. Our main goals are an accurate detection of the parabolas while circumventing the computational complexity and huge storage problem tied to conventional Hough Transform.

ICT 2013, 2013

ABSTRACT We present a novel approach for recovering the camera parameters and motion from the con... more ABSTRACT We present a novel approach for recovering the camera parameters and motion from the concept of coherence of a set of silhouettes of an object taken under circular motion. These parameters can be obtained by maximizing the total coherence between all silhouettes. For this purpose, we propose in this paper to use genetic algorithm instead the conventional optimization procedures. Genetic algorithm can correctly find the optimal solution without the need of initial values of parameters. The performance of the proposed method is shown in term of convergence and accuracy to recover camera parameters. The recovered parameters may be used for 3D image-based modeling to obtain high quality 3D reconstructions.

QUINZIEME COLLOQUE GRETSI - JUAN-LES-PINS - DU 18 AU 21 SEPTEMBRE 1995 A Genetic Algorithm for Mo... more QUINZIEME COLLOQUE GRETSI - JUAN-LES-PINS - DU 18 AU 21 SEPTEMBRE 1995 A Genetic Algorithm for Motion Estimation Fabrice Moscheni and Jean-Marc Vesin Signal Processing Laboratory, Swiss Federal ... [2] P. Amindan, JR Bergen, KJ Hanna, and R. Hingo-rani. ...

2014 Tenth International Conference on Signal-Image Technology and Internet-Based Systems, 2014

ABSTRACT

IOSR Journal of Research & Method in Education (IOSRJRME)

With the huge technological progress, Technology fever has invaded all social and economic fields... more With the huge technological progress, Technology fever has invaded all social and economic fields and one of these fields is the educational one. The e-learning systems which are based on the principle of the online courses, these systems are the most important aspects of the involvement of technology in education. However, when we are talking about any computer system using any kind of networks we are supposed to treat the security issue of this system. Although the security issue is important, it hadn't got much attention in the development of an e-learning platform. In this article we're going to expose some vulnerability that we can find in the connecting bridge between the profiles of learners and other resources in the e-learning platform.

Journal of Cultural Heritage, 2017

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)

Pattern Recognition Letters, 2015