This study addresses quantum computers as one of the most significant contemporary technological transformations that promise to reshape the future of global computing. It aims to clarify the conceptual foundations of quantum computing and to identify the fundamental differences between quantum and classical computers in terms of processing mechanisms, computational speed, and the ability to solve highly complex problems. The study focuses on key concepts such as the qubit, superposition, and entanglement, highlighting their role in enabling computational capabilities that exceed the limits of classical computing. It also discusses the future applications of quantum computers in areas such as cryptography, artificial intelligence, big data

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

When dye is present in wastewater, it is considered a hazardous organic pollutant and must be eliminated. The goal of the current study was to evaluate the elimination of Malachite green (MG) and Methyl violet (MV) dyes using Ni foam (NiF) as an anode, along with stainless steel mesh electrodes as cathodes, and alum sludge (AS) as a third particle electrode in a three-dimensional electrocoagulation-flotation system (3DECF). With an electrolysis period of 30 minutes and pH = 7, response surface method was used to estimate the optimum conditions of studied parameters. These parameters were current density within the range of 1–5 mA/cm², concentration of NaCl within the range of 0.4 –1 g/L, and air flow rate within a range of 1–5 L/min.

Based on the diazotization reaction of 4-aminoacetophenone with sodium nitrite in acid medium to form diazonium salt, which was coupled with Methyldopa to form a violet reddish soluble azo dye with maximum absorbance at 560 nm,a batch procedure had been developed for the estamination of Methyldopa. Under optimum experimental parameters affecting on the development and stability of the colored product, Beer´s law obeyed in the range (0.5-45) ?g.ml-1 with a correlation coefficient (0.9979).The proposed method was successfully applied to the determination of Methyldopa in either pure form and in commercial brands of pharmaceuticals, no interference was observed from common excipients in the formulations. The analytical results obtained by app