Abdoun Otman

• Professor
• Associate Professor at Faculty of Science of (FS-Tetouan), Abdelmalek Essaadi University, Tetouan, Morocco

The genetic algorithm includes some parameters that should be adjusted, so as to get reliable results. Choosing a representation of the problem addressed, an initial population, a method of selection, a crossover operator, mutation operator, the probabilities of crossover and mutation, and the insertion method creates a variant of genetic algorithm...

This paper presents an effective approach to optimize the reassignment of Human Resources in the enterprise that is formed by several units of productions to take into consideration the human characteristics. This approach consists of two steps; the first step is to formalize the studied problem that is practically take the form of the generalized...

Genetic algorithm includes some parameters that should be adjusting so that the algorithm can provide positive results. Crossover operators play very important role by constructing competitive Genetic Algorithms (GAs). In this paper, the basic conceptual features and specific characteristics of various crossover operators in the context of the Trav...

In this work, we are interested in improving the performance of genetic algorithm (GA) to solve the Asymmetric Traveling Salesman Problem (ATSP). Several approaches have been developed with genetic algorithms based on the adaptation and improvement of different standard genetic operators. We proposes a new GA adopting immigration strategies to mait...

The multi-agent system (MAS) is a nature-inspired method, which supports cooperative search by the self-organization of a group of compact agents situated in an environment with certain sharing public knowledge. Moreover, each agent in MAS is an autonomous entity with personal declarative memory and behavioral components. In recent years, multi-age...

Before starting the process of adaptive e-learning, it is essential to define the learner’s style which reflects all the characteristics that enable the learner to learn effectively. Traditional style identification methods provide a questionnaire to extract data. This can result in a loss of learning time, and the data obtained may not be relevant...

This chapter examines skin cancer, particularly melanoma, which has a high mortality rate, making early diagnosis essential. It explores how convolutional neural networks (CNNs) can improve melanoma detection, providing a detailed technical analysis of hyperparameters and their impact on model performance. Strategies for tuning hyperparameters, inc...

Early detection and diagnosis of breast cancer are critical for saving lives. This paper addresses two major challenges associated with this task: the vast amount of data processing involved and the need for early detection of breast cancer. To tackle these issues, we developed thirty hybrid architectures by combining five deep learning techniques...

Melanoma, one of the most dangerous types of skin cancer, is a significant global health issue. Globally, 325,000 new melanoma cases are expected to be detected in 2020, according to the International Agency for Research on Cancer (IARC), with a predicted mortality rate of 57,000. Early detection of melanoma is crucial, and artificial intelligence...

Smart and sustainable dermatology takes on a new dimension within Green Smart Cities with the integration of artificial intelligence (AI) into dermatological diagnosis. This study explores the success of deep learning models in accurately recognizing skin lesions, focusing on the use of the HAM10000 dataset. Our comparative analysis highlights the...

Recent developments in communication technologies, intelligent transportation systems, and computer systems have created many opportunities for intelligent traffic solutions that improve efficiency, ease, and safety. Researchers have recently used AI techniques in many application fields because it can improve data-driven networks. Moreover, The Io...

This paper provides a brief review of the application of machine learning in agriculture. For this purpose, several machine-learning algorithms were considered as SVM, ANN and CNN. Furthermore, a case study for the detection of various diseases of tomato with DNN. The efficiency of the DNN algorithm for the detection of pepper diseases has been dem...

Brain stroke is a Cerebrovascular accident that is considered as one of the threatening diseases. Depending on the area of the brain affected and amount of time, the blood supply blockage or bleeding can cause permanent damage or even lead to death. Face to this urgent medical situation, early detection of different stroke aspects can provide signi...

Thyroid is one of the major glands in the human body. It is responsible for various hormones secretion like Triiodothyronine (T3) and Thyroxin (T4). Indeed, they stimulate our metabolism and act on various organs. So, its malfunction can cause various disorders, like hypothyroidism, hyperthyroidism and thyroid nodules as small tumors in the gland,...

Adaptive learning has proved its effectiveness in several research studies. It aims to offer a personalised and adaptive learning process to the needs and preferences of each learner using artificial intelligence technologies. Nevertheless, there is a category of learners who require special support in their learning, social life, nutrition and wel...

In December 2019, the first case of coronavirus 2019 (COVID-19) appeared in China, quickly leading to a global pandemic. Early and accurate diagnosis is crucial for effective disease management. While reverse transcription polymerase chain reaction (RT-PCR) is the standard diagnostic test, it may yield false negative and misleading results. Artific...

Artificial intelligence, or augmented intelligence (AI), is the subfield of the computer science that enables machines to exhibit increasingly intelligent behavior. Due to its intelligent features, AI has changed the world and significantly impacted all fields such as medicine, agriculture, the economy, and so on. These features enable machines to...

Artificial intelligence, or augmented intelligence (AI), is the subfield of the computer science that enables machines to exhibit increasingly intelligent behavior. Due to its intelligent features, AI has changed the world and significantly impacted all fields such as medicine, agriculture, the economy, and so on. These features enable machines to...

Pneumonia is a respiratory disease that kills a million children each year, primarily in low-income countries where it is difficult to obtain timely treatment. Furthermore, the discovery of this illness is only detected after it has advanced to a severe state. Therefore, the image analysis can provide early detection of this sickness and save a lot...

The intelligent tutoring system registers the reference data of the learners in a database. This data is stored for later use in the instructional module. Designing a student model is not an easy task. It is first necessary to identify the knowledge acquired by the learner, then identify the learner's level of understanding of the functionality and...

The explosive rate of the evolution of IoT leads to a demand for nodes and data security. IoT nodes are vulnerable to a variety of critical attacks and security threats because of the heterogeneity of standards and data handled by these nodes. However, nodes and data security are critical challenges for researchers. Thus, we need to explore a solut...

Agriculture production is significantly affected by weeds. Improving production levels in agriculture is important, and getting only weeds sprayed accurately is crucial. Only weeds need to be sprayed accurately, while distinguishing them from crops. Several methods have been used by scholars in recent years to accomplish this goal. There are two ap...

Nowadays, face (or image) recognition represents a challenging problem and an important area in various applications due to issues that can be encountered in different domains such as monitoring operations, security, criminal identification, identifying a person, and so on. For that reason, many methods are proposed to develop the intelligent face...

Respiratory disorders endanger people’s lives. A novel Sars species was discovered for the first time in 2019 in Wuhan when it was isolated from three people suffering from respiratory sickness, indicating that early discovery can help save lives. The purpose of this study is to implement and evaluate six hybrid architectures for multiclass chest X...

Technology integration has been crucial in the practice of the learning process. The use of technology aims to find effective solutions to traditional learning problems. Despite the enormous efforts adopted, using e-learning systems was optional in many education systems. However, the COVID-19 health crisis has shown the importance of the transitio...

This paper describes an agent-oriented approach that aims to create learning situations by solving problems. The proposed system is designed as a multi-agent that organizes interfaces, coordinators, sources of information, and mobiles. The objective of this approach is to get learners to solve a problem that leads them to get engaged in several lea...

In this paper, we propose a hybrid system that can automatically detect coronavirus disease and speed up medical image analysis processes by using artificial intelligence technique. Our system consists of two parts: First, to perform feature extraction, we used a deep convolutional network that is based on the transfer learning technique, in this s...

The agriculture sector in the Tangier-Tetouan-Al-Hoceima-Region (Northern Morocco) contributes a significant percentage to the national revenue. The Larache Province is at the regional forefront in agriculture terms due to its large irrigated areas. Golden-Gogi is a biological farm located in the Larache Province, and its objective is to produce or...

Technological progress has led to the integration of technology into the practices of the learning process. The aim of this integration is to overcome the deficiencies of traditional methods to ensure greater efficiency. Despite the technology revolution, the adoption of e-learning has always been a choice in the educational process. The COVID 19 c...

Assessment is a crucial phase in the learning process. Its purpose is to measure the mastery degree of the acquired knowledge to take the appropriate decisions. The assessment phase accompanies the learner during the whole learning process by different types: diagnostic, formative and summative. In the context of e-learning, the choice of technolog...

The expert module is an essential part of the intelligent tutoring system. This module uses only declarative knowledge, excluding other types of domain knowledge: procedural and conditional. This elimination makes the expert module very delicate. To solve this issue, the authors propose to embed knowledge processing into the expert model. The contr...

Agriculture is an important sector for developing countries and farmers. Recently, numerous techniques for increasing agricultural productivity have been utilized. However, different issues are still encountered by farmers including various plant diseases. Plant disease diagnoses are challenging research, and they should be analyzed and treated by...

The world has experienced the spread of a dangerous virus, Coronavirus (COVID-19), that has caused the death of millions of people worldwide at an extremely rapid rate, many studies have confirmed that the virus can be detected effectively using medical images. However, it takes a long time to analyze each image by radiologists who suffer from high...

Counter-Propagation-Artificial-Neural-Networks (C P-ANNs) have been applied in several domains due to their learning and classification abilities. Regardless of their strength, the CP-ANNs still have some limitations in pattern recognition tasks when they encounter ambiguities during the learning process, which leads to the inaccurate classificatio...

The expanding population necessitates the development of solutions to make human life easier. Smart transportation plays an important role in society by improving road security, lowering mishap rates, and making the travel experience more valuable for passengers. As a result, the vehicular ad hoc network (VANET) provides communication between vehic...

The metallic structures are performed and reinforced by combining composite materials in one fiber-reinforced composite structure. This process improves the resistance and the lightness of the structures. In effect, the composite structures are more resistant to shocks, heating and cooling temperature or cracking, explained by the multiple advantag...

E-learning systems have undergone a mutation thanks to the integration of several technologies, especially those of artificial intelligence, in order to improve their efficiency. The concept of adaptive learning has been the subject of this evolution. Several researches focus on the suggestion of new approaches ensuring a better method of presentat...

This article presents a new approach of integrating parallelism into the genetic algorithm (GA), to solve the problem of routing in a large ad hoc network, the goal is to find the shortest path routing. Firstly, we fix the source and destination, and we use the variable-length chromosomes (routes) and their genes (nodes), in our work we have answer...

This paper proposes a comparison of three machine learning algorithms for a better intelligent irrigation system based on internet of things (IoT) for differents products. This work's major contribution is to specify the most accurate algorithm among the three machine learning algorithms (k-nearest neighbors (KNN), support vector machine (SVM), art...

Combinatorial optimization problems refer to intractable problems that can’t be performed using exact methods. The resolution of combinatorial problems geared towards the application of heuristics, metaheuristics also matheuristics, in order to provide good enough approximations. As exact methods provide resolution corresponding to small problem sc...

The automatic diagnosis of the Coronavirus has become essential to minimize the workload of the health system in the face of the epidemic. Today, the coronavirus is spreading at an accelerated rate. It is Therefore essential to identify infected persons in order to avoid any contamination. This virus can be detected using real-time polymerase chain...

With the appearance of new technologies: ICT, IoT, 5G, the spread of wireless internet, increasingly growing services and the current explosion of information systems on Ad Hoc networks, it is therefore necessary to have a new efficient routing strategy especially for large Ad Hoc networks, which takes into consideration the quality of service to i...

Feedback may be an effective interaction provided by the intelligent tutoring system. Nevertheless, the learning feedback is not easily definable, especially in front of learners with their characteristics and preferences. In this work, the authors propose to predict personalized feedback in a programming language learning context that promotes the...

The optimization provides resolutions to complex combinatorial problems that generally deal within large data size and expensive operating processes. Metaheuristics target the promoting of new applied algorithms to resolve NP-Hard problems in order to improve resolutions requiring enhanced search strategies. Travelling Salesman Problem (TSP) is a c...

The smart tutoring system is a system that helps learners to solve their exercises. To improve this system, an integration of collaborative technique is required. This tool, aid learners to understand very well their courses and resolve the difficulties of case studies that are based on team work. The aim of this paper is to fix the problem of the...

This article presents a hybrid genetic algorithm (GA) with two-optimization algorithm, to find a solution to the problem routing in Ad Hoc network big map, the objective is to find the shortest possible distance between a transmitter head (cluster, node, intermediate or advanced) and the base station. From studies and remarks, it has been proved th...

On 31 December 2019, COVID-19, a novel coronavirus, appeared for the first time in the Chinese city of Wuhan, to act as a preliminary warning and affected a wider human being in the world. This virus, declared a pandemic by the auspices of the World Health Organization (WHO), given its high rate of transmissibility. The protocol most often used to...

Recently, most countries suffer a decrease the crop productivity due to weather conditions, so many kinds of research are suggested for growth and enhance crop productivity with different methodologies and techniques. The Semantic Web (SW) approach is proposed in this work to build a recommendation system for helping the farmers to take an adequate...

p>The human resources (HR) manager needs effective tools to be able to move away from traditional recruitment processes to make the good decision to select the good candidates for the good posts. To do this, we deliver an intelligent recruitment decision-making method for HR, incorporating a recruitment model based on the multipack model known as t...

In recent years, artificial intelligence (AI) represents a crucial domain or technology that can be found everywhere, it can solve many problems facing the researchers. Hence, the powerfulness of Artificial intelligence contributes enormously to the sustainable growth of various domains (e.g., medical, agriculture, data analysis, and so forth). For...

The higher education in Morocco knows a real challenge due to the consequences of covid19. This challenge was effect by the transformation of the teaching mode from face to face (learning at school) into a distance learning (home based learning). This paper reports comparative studies of technologies that used in Moroccan Higher education and the c...

An isotropic mechanical structure cannot withstand shocks, accidents, and mechanical loading. In this perspective, composite structures have been introduced to improve the performance of mechanical structures. We are interested in the study of laminates with the aim to find an optimal structure resistant to vibrations and buckling. To remedy the pr...

Data analysis methods have been widely used in various domains, such as medical, marketing, and agriculture. Since they have a good performance to reduce massive data. Unfortunately, those methods are limited without the usage of Computer Technologies (computer technologies, 'CT'), which lead to developing autonomous systems capable of making appro...

Several studies have identified the importance of knowledge domain in the intelligent tutoring system. However, this system required a knowledge processing especially in the expert model. In this paper, we report that the combination of the state of the activity (Implicit/ explicit) and the knowledge processing of: declarative, procedural and condi...

Knowledge management (KM) is one of the main factors that have become extremely popular in recent years. KM is the processes which people explain information data using scientific and technological media and summarize it into concepts and rules to generate knowledge. This later can be implicit or explicit one. The aim of this contribution is to con...

With the emergence of new technologies, a new way of learning called 6 "e-learning" has appeared, based on interactive training. This helps learners to 7 develop their skills, while making the learning process independent of time and 8 place. Artificial intelligence (AI) techniques in education were tested to increase 9 learning experience. AI rese...

This paper discusses the implementation of new hybrid algorithm to solve efficiency a constrained personnel reassignment to preferred posts by generating of high optimal solution quality. Each post must be occupied by an employee with rotation organized by the decision-makers to adapt it for a qualified employee. Generally, this problem is a NP har...

Agriculture is a major source of life that plays a predominant role in the development of the economy in most countries but with the phenomenon of droughts and the decrease of water, we are facing problem in decreasing agricultural production that’s why in this work we propose to make an intelligent system of diagnosis and control to improve agricu...

To solve an NP-complete problem we automatically cerebrate of metaheuristic methods, which are in the majority of times inspired from natural phenomena, for example, genetic algorithms, ant colony algorithms, and bee colony algorithms, then they are the logical and algorithmic representation of an optimal solution of a complete problem called NP-co...

The decision to locate an economic activity of one or several countries is made taking into account numerous parameters and criteria. Several studies have been carried out in this field, but they generally use information in a reduced context. The majority are based solely on parameters, using traditional methods which often lead to unsatisfactory...

The decentralized nature of ad hoc wireless networks makes them suitable for a variety of applications, where the central nodes cannot be invoked and can improve the scalability of large map networks, the topology of the ad hoc network may change rapidly and unexpectedly. Mobile Ad hoc (VANET) are used for communication between vehicles that helps...

Agriculture form one of the most important aspects of life necessities, it is responsible to feed 7.7 billion person for the time being, and it is expected to supply more than 9.6 billion individual in 2050, The thing that made classical farming insufficient, and give birth to the notion of smart farming, and the race has begin toward using the lat...

An accurate and lower cost hybrid machine learning algorithm based on a combination of Kohonen-Self Organizing Map (SOM) and Gram-Schmidt (GSHM) algorithm was proposed, to enhance the crop yield prediction and to increase the agricultural production. The combination of GSHM and SOM allows to withdraw the most informative components about our data,...

Le système de tutorat intelligent (STS) est un système qui fournit une rétroaction aux apprenants. Les STS les aident à résoudre les problèmes liés aux activités. Pour améliorer ce système, nous intégrerons un apprentissage collaboratif dans notre système. L'apprentissage collaboratif est très essentiel dans le processus d'apprentissage, il aide le...

the results obtained by a heuristic or an exact method remains insufficient for a combinatorial optimization problem, so we use metaheuristics which is an algorithm inspired by natural phenomena, in this paper we will see two recent metaheuristics which are the cuckoo search (CS) and Fireworks Algorithm (FWA) as well as a proposal to hybridize them...

Artificial neural networks (ANN) are currently massively used in different fields, especially for very complex problems. In this work we propose an approach to use these systems, and in particular the paradigm of the self-organizing map (SOM) in the medical field. The idea is to use this paradigm to develop an intelligent system able of learning to...

The worldwide economic progression in the last century and the Demographic growth has given rise to a huge consumption in the market of goods and services, while globalization decreased the cost of shipping and transportation. The production, transportation, storage and consumption of all these goods, however, have created big environmental problem...

Learning analysis consists of collecting the traces that learners leave behind and using these traces to enhance learning [1]. The Learning analytics use techniques from different fields such as Artificial intelligent, Machine learning, data mining, text mining and web analytic, etc. Moreover, individual learners intended methods to stimulate refle...

The evolution of computing and the appearance of the parallel architecture pushed the world to reconsider all the existing algorithm and enhance their performance given the impact that parallel programing could do to improve the performance. And it’s worth to be tried on NP-Complete problems such as TSP and its variants. The traveling salesman prob...

In this work, we are interested to propose a new genetic approach to improve the optimal solution of a constrained assignment problem of human resources within the multi sites enterprise. By taking into consideration various constraints, this problem can be defined as a NP-hard combinatorial problem as we have showed [2]. In this work, we have deve...

E-Learning platform represents nowadays a real revolution for the professional training. However, in this type of system. Learning in a collaborative environment is very essential but is not always easy, because one of the difficulties when organizing online learning courses may be that these courses are not adapted to this type of learning based o...

E-Learning platform represents nowadays a real revolution for the professional training. However, in this type of system. Learning in a collaborative environment is very essential but is not always easy, because one of the difficulties when organizing online learning courses may be that these courses are not adapted to this type of learning based o...

Faced with the difficulties encountered by heuristics to have a workable solution of good quality for combinatorial optimization problems, metaheuristics are nature-based methods are generally iterative stochastic algorithms have appeared. These algorithms are more comprehensive and complex than a simple heuristic, and generally allow a very good s...

In this paper, we interest to present an expert system to simplify the management the human resources mobility within a multi-sites enterprise. This expert system uses new methods to solve a complex problem of spatial mobility of Human resources witch is studied in works [01] and [02]. In this system, we incorporate algorithm based on bilateral per...

To solve a NP-complete problem we automatically think of metaheuristic methods, which are in the majority of times inspired from natural phenomena, for example genetic algorithms, ant colony algorithms and bee colony algorithms, then they are the logical and algorithmic representation of an optimal solution of a complete problem called NP-complete....

In this paper, we are studying the Vehicle Routing Problem (VRP) as a combinatorial optimization programming problem and seeking to serve a number of cus- tomers with a eet of vehicles. The VRP problem has many applications in the �elds of transport, distribution and logistics. In this passage we will show that it is an NP- complete problem that i...

The decision to locate an economic activity of one or several countries is made taking into account numerous parameters and criteria. Several studies have been carried out in this field, but they generally use information in a reduced context. The majority are based solely on parameters, using traditional methods which often lead to unsatisfactory...

Users in a class have different interactions in a particular situation in front of the machine. The tutor or face-to-face trainer has the ability to adapt his content according to the immediate feedback he can get from the learners. If one of the students gets bored, or stalls, the trainer can intervene to modify this behaviour, and improve the eff...

In this paper, we propose a new genetic approach to improve the solution of a constrained recruitment problem of human resources. This problem is an extension of a Multiple Knapsack Approach for Assignment Problem of Human Resources that is a NP-hard combinatorial problem. In the previous work [1], we have formulated this problem and solved it usin...

Genetic algorithms are metaheuristic algorithms, which mean that it generates useful solutions to solve NP-hard optimization problems in moderate execution times. However, Genetic algorithms usually require more computation power than other heuristic approaches do. Due to the complexity of problem such as TSP, finding a good solution with tradition...

The Emergence of new technologies appear a new way of learning called "E-Learning", this latter based training into interactive lines. This access helps learners to develop their skills, while making the learning process independent of time and place. Artificial Intelligent techniques in education was testing to increase learning experience. AI res...

Many companies now offer group transportation service to help ease the commute for their employees. The environmental benefits of the trend are clear: fewer cars burning fuel, crowding urban streets, and taking up valuable parking areas. However, the problem with personal transportation is that it can be so difficult to choose the perfect path for...

Metaheuristics methods are the most efficient if not the only way to solve difficult problems in both science and industry. In computer science, these methods are being used to find a good answer for NP-hard optimization problems in moderate execution times by shrinking the size of the search space to focus on regions with the height change of havi...

The Traveling Salesman Problem (TSP) is a combinatorial optimization problem of great importance which continues to interest several researchers in order to develop methods to achieve an optimal solution. Genetic algorithms (GAs) as meta-heuristic methods have been widely applied to this problem. Inspired by biological phenomena, we introduce two i...

In this work, we are interested in improving the performance of genetic algorithm (GA) to solve the Asymmetric Traveling Sales- man Problem (ATSP). Several approaches have been developed with genetic algorithms based on the adaptation and improvement of di�erent standard genetic operators. We proposes a new GA adopting immigration strategies to mai...

span lang="EN-US">This paper presents an effective approach to optimize the reassignment of Human Resources in the enterprise that is formed by several units of productions to take into consideration the human characteristics. This approach consists of two steps; the first step is to formalize the studied problem that is practically take the form o...

In this paper, we propose the assignment problem of resources humans’ methodology by using the multiple knapsack approach to formulate the studied problem, and solve it by using the genetic algorithm for obtaining the optimal assignment of the new qualified employees that ensures the maximization the productivity by introducing constraints correspo...

In this paper, we present a novel approach to improve communication within a multi-agent system. The present invention concerns a renovation of a cache multi-agent system. In one embodiment, the method is to keep the content of the dialogue between agents in the form of items stored in a local cache system and ADM to recover these hidden elements t...

In this paper, we are going to present a hybrid heuristic method for solving the assignment problem of human resources with constraints for a multi-site enterprise that is a NP-hard combinatorial optimization problem. This method combines two approaches: the first one is the flow graph approach for modeling and constructing the space solution. The...

In this papers we are going to present a hybrid heuristic method for solving the assignment problem of human resources with constraints for a multi-site enterprise that is a NP hard combinatorial optimization problem [1]. This method combines two approaches: the first one is the flow graph approach for modeling the space solution. The Second one is...

This study problem consist to reassign the agents under objective constraint from one unit to another composed an enterprise, each agent realizes same activity and has a weight calculated using predefined criteria. The agents reassigned engender an overall weight considered as the performance. This objective constraint is parameterized by a toleran...