This work deals with the study and performance improvement of the direct power control of DFIG based on backstepping Controller. Direct power control using hysteresis regulator has certain disadvantages such as significant powers ripples, variable switching frequency and sensitivity to parametric variations. To surmount these disadvantages, we present a robust controller such as the backstepping-based direct power control using SVM. A comparison study was made between the classic direct power control and the backstepping controller. The simulation results show that the backstepping controller provides good results reduces powers ripples.

In the industry, automated inspection is important for ensuring the high quality and allows acceleration of procedures for quality control of parts or mechanical assemblies. Although significant progress has been made in precision machining of complex surfaces, precision inspection of such surfaces remains a difficult problem. Thus the problem of the conformity of the parts of complex geometry is felt more and more. Motivated by the need to increase quality and reduce costs, and supported by the progress made in the field of it as well as the automation of production which in recent years has seen a considerable evolution in all these stages: from design to control through manufacturing. Due to, we used a 3D computer aided inspection technique on a physical gear using a coordinate measuring machine equipped with a “PC-DMIS” measurement and inspection software. Our work consists in developing a procedure for inspection for reproduction of gear profile by reconstruction of a circle involute gear from a cloud point’s measurement. In order to obtain a reliable result. In this works, we design the CAD-model of the part as accurately as possible (using a mathematical model) and matched with the 3D points cloud that represents the measurement that obtained from scanner. we compare the measurement cloud points from coordinate measurement machine with the mathematical model of construction by ICP (Iterative Closest Point) methods in order to obtain a conformed result and to show the impact of the dimensional inspection and geometric.

The workplace, and more particularly the healthcare sector, has recently experienced a staggering increase in violence. These aggressive behaviors are resulting in considerable consequences on healthcare workers, both in terms of mental and physical health. In light of this observation, this study aims to provide a quantitative analysis of the potential causes leading to violence in Algerian hospitals, which have become the place where tensions arise, especially during these uncertain times caused by the COVID-19 pandemic. Therefore, we started with conducting a field survey, in order to highlight the main causes behind this violence, as well as the strategy in terms of how it is managed as a risk. Then we used ISHIKAWA diagrams to classify predefined causes into several categories and anticipate the likelihood of such violent behaviors. Finally, the results of this study revealed that working conditions were the main cause of violence in Algerian hospitals. In order to remedy this gap, we recommend improving the healthcare staff well-being, as well as prioritizing proactive measures preventing violent behaviors. 

Requirements of users in developing countries differ from those of developed countries. This difference can be seen through wheelchair displacement in infrastructures that don't meet international standards. However, developing countries are obliged to purchase products from developed countries that don't necessarily meet all user's requirements. The modification of these requirements will generate disruption on all the supply chain. This paper proposes a model for optimising the cost of requirement modification on the supply chain and seeks to evaluate the introduction of a new requirement on an existing product/process. This model is adapted to the redesign and development of products, such as wheelchairs, satisfying specific Algerian end-user requirements.

Diabetic retinopathy is a severe retinal disease that can blur or distort the vision of the patient. It is one of the leading causes of blindness. Early detection of diabetic retinopathy can significantly help in the treatment. The recent development in the field of AI and especially Deep learning provides ambitious solutions that can be exploited to predict, forecast and diagnose several diseases in their early phases. This work aims towards finding an automatic way to classify a given set of retina images in order to detect the diabetic retinopathy. Deep learning concepts have been used with a convolutional neural network (CNN) algorithm to build a multi-classification model that can detect and classify disease levels automatically. In this study, a CNN architecture has been applied with several parameters on a dataset of diabetic retinopathy with different structures. At the current stage of this work, obtained results are highly encouraging.

In this paper, we propose an implementation of a new technique of power maximization using a photovoltaic system emulator. The PV system design and its performance evaluation test before installation would be both costly and time-consuming. To overcome this problem the use of an emulator adds more performance and efficiency in the laboratory. Also, by measuring the voltage and current from the PV emulator the characteristic I-V and P-V are extract.The need to consider the measure power state is strongly nonlinear distribution curve with noise. For that reason, to establish and to detect the power value, measurement equations and dynamic equations proposed MPPT control strategy based on Kalman filter algorithm. The correctness and effectiveness of the strategy is verified by simulation and experiment. This algorithm was experimentally implemented. Data acquisition and control system were implemented using dSPACE1103. The results show that the Kalman filter MPPT work accurately and successfully under the change of solar irradiation.

In recent years the development of health science to improve people’s lives and reduce the death rate from cardiovascular disease, researchers have invested in the solution of stents to treat cardiovascular disease. Usually a permanent implant (metal stent) is used to treat a temporary disease, effective on elastic recoil and negative remodeling, but promoting intimate proliferation. This is combated by an active stent, which nevertheless induces chronic inflammation and delayed healing (because of active drugs), with the risk of late thrombosis. The idea of resolution leads to the study of the behavior of temporary stent biodegradable and bioresorbable, once the healing process is completed. The purpose of this study is to reduce the disadvantages of metal stents, to do this; a biodegradable material (polylactic acid) is used. The fatigue behavior of a stent after its placement using geometric parameters selected from clinical cases (diastole and systole). A finite element numerical study in the field of biomaterial fatigue is proposed in order to investigate and understand the biodegradable behavior of the stent. The results of the numerical study show the predicted lifetime of the biodegradable fragrance.

The integration of a fault tolerance mechanism in critical real-time embedded systems is an important and required property to ensure the continuity of delivering the expected service even in the presence of faults to avoid catastrophic consequences that can be generated in the event of failure of these systems. In this research paper we present a solution to tolerate permanent faults of one processor in heterogeneous distributed real-time embedded systems by using software redundancy solutions based on active and passive replication of dependent tasks in the point-to-point connection. The methodology proposed consists to generate a distribution/scheduling of tasks on hardware architecture and also to tolerate permanent faults of a single processor by executing simultaneously two replicas of a task, the first which ends its execution blocks the second is running. this principle saves very considerable time in distribution/scheduling length with and without errors.

Image classification has been one of the most widely topic in artificial intelligence, deep models need larger datasets and powerful hardware to improve the highperformance classification. ImageNet Challenge was started in 2010 to classify 100,000 test images into 1000 different classes. Tiny ImageNet challenge is similar to ImageNet challenge, where images are taken from the standard ImageNet and resized to be 64x64. In this paper a fine-tuned Xception to classify images into the 200 classes is presented using the standard Tiny ImageNet dataset, the down-sampling (64x64) of images and the low similarity inter-class makes feature extraction and classification difficult and more challenging. We used a transfer learning algorithm to fine-tune the Xception architecture using the Extreme version of the Inception module to achieve a high validation accuracy of 65.14%.

The direct power control of the doubly fed induction generator using conventional controllers is characterized by unsatisfactory performance: high ripples of stator powers and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the higher law sliding mode developed on the super twisting algorithm associated with the fuzzy logic control in order to realize optimal command performance, Finally, the efficiency of the envisaged control scheme, is investigated against. The proposed regulation scheme is efficient in reducing the powers ripples; successfully suppress chatter and the effects of parametric variations that do not affect the performance of the regulation.

In this paper, the role of introducing Germanium (Ge)/IGZO heterostructure in enhancing the Infrared (IR) photodetection properties of thin-film phototransistor (Photo- TFT) is presented. Numerical models for the investigated device are developed using ATLAS device simulator. The influence of Ge photosensitive layer thickness on the sensor IR photoresponse is carried out. It is revealed that the optimized IR Photo-TFT based on p-Ge/IGZO heterojunction can offer improved IR responsivity of 4.1×10(exp2) A/W, and over 10(exp6) of sensitivity. These improvements are attributed to the role of the introduced p-Ge/IGZO heterostructure in promoting IR photodetection ability and improved separation and transfer mechanisms of photo-exited electron/hole pairs. The photosensor is then implemented in an optical inverter gate circuit in order to assess its switching capabilities. It is found that the proposed phototransistor shows an improved optical gain thus indicating its excellent performance. Therefore, providing high IR responsivity and low dark noise effects, the optimized Ge/IGZO IR Photo-TFT can be a potential alternative photosensor for designing optoelectronic systems with high-performance and ultralow power consumption.

This paper focuses on the efficient control of a photovoltaic device's voltage. Under irradiation variation and constant load, a robust controller is proposed. The second-order sliding mode controller for buck converter based on super twisting algorithm is designed to ensure both the reliability and robustness of the global system. The proposed control strategy's reliability is demonstrated by experimental results using dSpace 1104.

New 2-pyridone derivatives were hemi-synthetised in situ using essential oils of endemic Algerian plants; Ammodaucus Leucotrichus and eucalyptus citriodora as source of chiral aldehydes (perillaldehyde and citronellal respectively). The one pot reaction was carried out in Ethanol including cyanoacetohydrazide, essential oil, and malononitrile. The reaction mixture was catalysed by potassium carbonate. In the present work, two new compounds of highly functionalized 2-pyridones were obtained as privileged medicinal scaffolds. The structures of 2-pyridone derivatives were confirmed by 1H NMR, 13C and 2D

Condition Monitoring of photovoltaic systems plays an important role in maintenance interventions due to its ability to solve problems of loss of energy production revenue. Nowadays, machine learning-based failure diagnosis is becoming increasingly growing as an alternative to various difficult physical-based interpretations and the main pile foundation for condition monitoring. As a result, several methods with different learning paradigms (e.g. deep learning, transfer learning, reinforcement learning, ensemble learning, etc.) have been used to address different condition monitoring issues. Therefore, the aim of this paper is at least, to shed light on the most relevant work that has been done so far in the field of photovoltaic systems machine learning-based condition monitoring.

The issue of robustness of stability has been prominent in the literature on control theory over the last two decades. An important state-space approach to robustness analysis is the stability radii theory. The robust stability problems of infinite dimensional systems subjected to stochastic bounded structured perturbations have been studied using the stability radius approach. In the applications it is important to study these problems in the case where the perturbations operator structure are unbounded, because it covers the case of partial differential equations with boundary and ..

As compared to a fixed Photovoltaic (PV) system, a two axis solar tracker system can increase electrical energy production from 35% to 45% in a year. Vibration characteristic is an essential factor in evaluating the reliability and stability of solar tracker structure during operating course. In this paper, the free vibration behaviour (modal analysis) of 12 kW two axis PV solar tracker structure is investigated numerically. The modal analysis by using commercial finite element package (SOLIDWORKS SIMULATION) to identify the modal parameters of the tracker structure (natural frequencies and corresponding modal shapes). The simulation results obtained for tracker structure at maximum elevation angle (60deg) indicate that no resonant problem (according to ASHRAE Standard) during solar tracker operation under wind load (from 0 to 36 m/s).

In this work, a modified perturbs and observes (P&O) technique is used in the hybrid power generation system with power management. There are several algorithms for extracting the maximum power point (MPP) provided from the PV generator; P & O algorithm has a good performance, ease of implementation by analog and digital electronics. However, this algorithm has disadvantages because it oscillates at the point of maximum power and has a relatively long convergence time; therefore, a modification is made to the P & O algorithm in order to reduce setup time and oscillations in the MPP. The proposed system allows optimal use of the photovoltaic (PV) system and the DFIG wind proves its efficiency under variable load conditions. The model is implemented in the MATLAB / Simulink platform.

The present study investigates the spectral analysis for natural convection in a tilted rectangular cavity, lled with high Prandtl oil ”Pr =880” by the code CFD. A constant vertical temperature gradient has been performed by subjecting the horizontal walls to constant temperatures Th and Tc; respectively. Other walls are adiabatic except the left small sidewall is differentially heating with temperature TA creating the horizontal temperature gradient. The results are presented for different values of lateral heating and inclination angle. The spectral analysis is used to identify and show effects on the original oscillation of the natural convection by the various investigated parameters (TA and θ)

In this work, a novel multifunction, multiband, and implantable PIFA antenna for biomedical telemetry is proposed. The covered frequency bands are the Medical Device Radiocommunications Service (MedRadio) (401 – 406 MHz), and Industrial, Scientific, and Medical (ISM) (433.1 – 434.8, and 902.8 – 928.0 MHz, and 2.4 – 2.4835 GHz), and the Wireless Medical Telemetry Service (WMTS) (1.395 – 1.400, and 1.427 – 1.432 GHz). The third ISM frequency band is reserved to the Wireless Power Transfer (WPT) function, The fourth ISM frequency band is dedicated to the wake - up operation, and the other operation frequency bands are proposed for data telemetry communications. The miniaturization is achieved by the shorting in PIFA, the radiating patch shaping by meandering and arms inserting, and open-ended slots inserting in the ground plane, the occupied volume is of 78.52mm ³ . Both the Equivalent Isotropic Radiated Power (EIRP) and the Specific Absorption Rate (SAR) restrictions are considered for the data telemetry, and the WPT functions performances. The obtained performances make the proposed antenna a good candidate for telemetry functions through muscle implants devices.