Abstract Ternary Silver Indium selenide Sulfur AgInSe1.8S0.2 in pure form and with a 0.2 ratio of Sulfur were fabricated via thermal evaporation under vacuum 3*10-6 torr on glasses substrates with a thickness of (550) nm. These films were investigated to understand their structural, optical, and Hall Characteristics. X-ray diffraction analysis was employed to examine the impact of varying Sulfur ratios on the structural properties. The results revealed that the AgInSe1.8S0.2 thin films in their pure form and with a 0.2 Sulfur ratio, both at room temperature and after annealing at 500 K, exhibited a polycrystalline nature with a tetragonal structure and a predominant orientation along the (112) plane, indicating an enhanced de

The main objectives of this study are to study the enhancement of the load-carrying capacity of Asymmetrical castellated beams with encasement the beams by Reactive Powder Concrete (RPC) and lacing reinforcement, the effect of the gap between top and bottom parts of Asymmetrical castellated steel beam at web post, and serviceability of the confined Asymmetrical castellated steel. This study presents two concentrated loads test results for four specimens Asymmetrical castellated beams section encasement by Reactive powder concrete (RPC) with laced reinforcement. The encasement of the Asymmetrical castellated steel beam consists of, flanges unstiffened element height was filled with RPC for each side and laced reinforced which are use

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

Objectives This work presents laser coating of grade 1 pure titanium (Ti) dental implant surface with sintered biological apatite beta-tricalcium phosphate (β-TCP), which has a chemical composition close to bone. Materials and methods Pulsed Nd:YAG laser of single pulse capability up to 70 J/10 ms and pulse peak power of 8 kW was used to implement the task. Laser pulse peak power, pulse duration, repetition rate and scanning speed were modulated to achieve the most homogenous, cohesive and highly adherent coat layer. Scanning electron microscopy (SEM), energy dispersive X-ray microscopy (EDX), optical microscopy and nanoindentation analyses were conducted to characterise and evaluate the microstructure, phases, modulus of elasticity

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

<p>Photovoltaic (PV) systems are becoming increasingly popular; however, arc faults on the direct current (DC) side are becoming more widespread as a result of the effects of aging as well as the trend toward higher DC voltage levels, posing severe risk to human safety and system stability. The parallel arc faults present higher level of current as compared with the series arc faults, making it more difficult to spot the series arc. In this paper and for the aim of condition monitoring, the features of a DC series arc fault are analyzed by analysing the arc features, performing model’s simulation in PSCAD, and carrying out experimental studies. Various arc models are simulated and investigated; for low current arcs, the heur