Statistics, Optimization & Information Computing

Preface for the Special Issue of International Congress on Engineering and Complex Systems ICECS’21

Mohamed BENSLIMANE — 2023-01-23

Ten papers selected and revised from the International Congress on Engineering and Complex Systems ICECS’2021, are highlighted.

Quadratic Programming and Triangular Numbers Ranking to an Optimal Moroccan Diet with Minimal Glycemic Load

Karim El moutaouakil — 2023-01-23

In this work, we suggest a variety of optimal daily diets for people with diabetes in Morocco. To this end, we model the foods glycemic load in term of triangular fuzzy numbers. Then, we model the problem of daily diet in term of fuzzy quadratic optimization programming. To transform this model into a line model, we use a very performance ranking function. To solve the obtained model, we call particles swarm algorithm due to its performance and simplicity. Various experiments were carried out on the basis of feeds available on the Moroccan market and for different sizes of the PSO swarm. The experimental results show that our system proposes optimal diets with a reasonable glycemic load between, acceptable favorable gaps and unfavorable nutrients excesses. We show how to combine the proposed diets to obtain a balanced weekly regime.

A Hybrid Skin Lesions Segmentation Approach Based on Image Processing Methods

Hanae Moussaoui — 2023-01-23

Presently image segmentation remains the most crucial stage in the image processing system. The main idea of
image segmentation is to partition or divide a random image into several partitions depending on the problem to solve. In this paper, we will be presenting a new method of skin cancer detection based on Otsu’s thresholding algorithm and markercontrolled watershed method. This hybridization process is first of all started by segmenting the input image using fuzzy c-means algorithm which is a clustering method that gives the possibility to a pixel to belong to one or more clusters. After that, we will apply multi-Otsu which is a thresholding algorithm that separates the pixels of an image into a variety of classes depending on the intensity of the gray levels. The next step of this proposed method is the marker-controlled watershed
algorithm that divides the image into homogenous areas or regions by using edge-detection concepts including mathematical morphology. The proposed technique was applied and experienced using several images of different types of skin cancer that were collected and gathered from the web and also from the Kaggle dataset. To assess the worth of the achieved results, we used several evaluation metrics like dice coefficient, sensitivity, specificity as well as Jaccard similarity that all have shown good and satisfactory results.

Application of NURBS in the Fracture Mechanics Framework to Study the Stress Intensity Factor

Soufiane MONTASSIR — 2023-01-23

In this investigation, we successfully employed the Non-Uniform Rational B-spline (NURBS) to study the fracture mechanics. the NURBS functions are very popular in the design field (CAD model) and it is used as an alternative to Lagrange interpolation polynomials. The extended isogeometric analysis based on this basis function is used to evaluate the stress intensity factors (SIFs) in order to control the crack propagation. For various crack lengths, SIFs were calculated to validate the accuracy of this technique. The results obtained are in good agreement with the available techniques as CFEM, X-FEM.

Visual Servoing of a 3R Robot by Metaheuristic Algorithms

Inssaf HARRADE — 2023-01-23

In planar robot control, the singularity problem is frequently encountered when determining the geometric or kinematic robot model. To overcome this problem, a new method is presented in this paper. Indeed, this method is used to compute the joint positions of 3R robots with high accuracy. The main idea of the proposed method is to use a metaheuristic algorithm for retrieving the coordinates of four reference points in the object image that is captured by a hand-eye camera of the 3R robot. Then, the joint positions are estimated by using a metaheuristic algorithm. The resulting positions are then used for controlling the 3R robot for moving to the desired position. The simulation experiments are conducted by using several metaheuristic algorithms with the same population size (N = 400). The obtained results show the high accuracy of the proposed method in terms of determining the exact positions of the 3R robot joints, which leads to finding the optimal robot trajectory.

Analysis of The Progressive Damage of A Notched AS4/PEEK Composite Laminate Subjected To Tensile Loading

Hamza El idrissi — 2023-01-23

The purpose of this work aims to assess the failure of an open-hole composite laminate subjected to tensile loading, using different progressive damage approaches. Within Abaqus, a user-defined material subroutine (UMAT) was developed and implemented by applying a combination of Puck’s failure criterion and the gradual degradation model. In addition, the integrated model in Abaqus based on the Hashin failure criteria coupled with the continuous damage model has been also considered. Moreover, the effect of different specimen sizes on the behaviour of the AS4/PEEK composite laminate has been performed. The predicted results were compared to those available in the literature. The results of this comparative study showed good agreement between the experimental outcomes and the numerical predictions.

Fuzzy Logic Control for Balancing a Two-Armed Inverted Pendulum

Boutaina EL Kinany — 2023-01-23

The unicycle robot is an activated model with only one wheel, which ensures its safety. Researchers were particularly interested in the unicycle robot because of its great robustness, which allows it to travel around without colliding with the ground. The inverted pendulum having two arms is modelled using a mathematical representation based on the Lagrangian formulation in this work, which embodies our concept of the unicycle robot. The fuzzy logic control algorithm will then be used to produce a high level of solidity for this system.

Modelling and Simulation of the Hybrid System PV-Wind

Alpha Alhaji Bangura — 2023-01-23

In this paper, we focused on modeling and simulation of a hybrid solar-wind energy system, consisting of a photovoltaic cell and a wind turbine driven by a Permanent Magnet Synchronous Generator (PMSG). The proposed system gives details of the hybrid solar-wind system. In the PV subsystem, there will be a photovoltaic energy subsystem, MPPT controller, and a DC-DC boost converter. The wind turbine subsystem includes a wind turbine energy subsystem, PMSG, and MPPT controller. The MPPT controllers were designed to extract the maximum power regardless of the weather conditions and temperatures. The P and O algorithm is introduced in the MPPT used in the PV energy subsystem and on the control of the machine side converter (MSC). The proposed wind turbine energy subsystem is based on Direct Torque and Flux Control (DTFC). The simulated results are demonstrated to show that the hybrid solar-wind generating system can realize a maximum power point tracking control of wind and solar power to satisfy the energy demand over an extensive range under unpredictable atmospheric conditions. The system has been demonstrated by MATLAB/Simulink and tested for variable weather conditions and temperatures.

Thermal Performance Analysis of Functional Parameters of the Floor Heating System in Africa

Safaa Oubenmoh — 2023-01-23

Buildings frequently utilize radiant heating floors because they offer benefits including effective use of space and homogeneous temperature distribution, which results in increased thermal comfort. The present work aims to investigate the perfect use of floor heating systems analytically and numerically with improved thermal performance to prove their efffficiency in various African climates. The evaluation depends on the functional parameters of the heating system and particularly focuses on floor surface temperature to acquire the desired heat flux and the perfect supply water temperature. According to results, It is desirable to use floor coverings with low thermal resistance and should not exceed R = 0.15 m2 . K/W since it has considerable influence on the thermal efffficiency of the underfloor heating components. The pipe diameter is suggested to be about 20 mm. By comparing pipe spacings of 15 mm and 30 mm, the difference in supply water temperature is approximately 7.4 C. The smaller the pipe spacing, the more energy it delivers and makes the floor much warmer while reducing heating time. Regarding the effect of pipe materials, PE-X is chosen for this study because of its low cost and resistance to corrosion and scaling. As the influence of these studied parameters on floor heating is remarkable, there is also the impact of the ambient temperature of each city on the floor heating efffficiency. The proposed model can be applied and considered potentially beneficial and helpful to the control, and design of floor heating systems, and choosing the right heating source.

Applications of Machine Learning Algorithms for Photovoltaic Fault Detection: a Review

Abdelilah Et-taleby — 2023-01-23

Over the years, the boom of technology has caused the accumulation of a large amount of data, famously known as big data, in every field of life. Traditional methods have failed to analyse such a huge pile of data due to outdated techniques. In recent times, the use of photovoltaic systems has risen worldwide. The arena Photovoltaic (PV) system has witnessed the same unprecedented expansion of data owing to the associated monitoring systems. However, the faults created within the PV system cannot be detected, classified, or predicted by using conventional techniques. This necessitates the use of modern techniques such as Machine Learning. Its powerful algorithms, such as artificial neural networks (ANN), help in the accurate detection and classification of faults in the PV system. This review paper introduces and evaluates the applications of Machine Learning (ML) algorithms in PV fault detection. It provides a brief overview of Machine Learning and its concepts along with various widely used ML algorithms. This review various peer-reviewed studies to investigate various models of ML algorithms in the PV system with the main focus on its fault detection accuracy and efficiency.

Industry 4.0 Implementation in Lean Supply Chain Management: a Systematic Literature Review

Asmae El Jaouhari — 2023-01-23

The major aspects and impacts of the interrelationships between Industry 4.0 (I4.0) technology and Lean Supply Chain Management are discussed in this article (LSCM). Many practical LSCM systems based on I4.0 have lately appeared. Despite this, there has been little research into the use of I4.0 technologies within LSCM. Machine learning, smart factories, blockchain, and the internet of services (IoS) are all possible LSCM revolution enablers. The goal of this research is to find out more about present and potential I4.0 technologies that can improve LSCM research and application in order to fill a gap in the current literature. A Systematic Literature Review (SLR) technique was used for the collection, selection, and evaluation of published literature. We looked at 79 studies published between 2010 and 2021 that were found in the Scopus database.