Cloud computing is the new technological trend for future generations. It represents a new way to use IT resources more efficiently. Cloud computing is one of the most technological models for developing and exploiting infrastructure resources in the world. Under the cloud, the user no longer needs to look for major financing to purchase infrastructure equipment as companies, especially small and medium-sized ones, can get the equipment as a service, rather than buying it as a product. The idea of cloud computing dates back to the sixties of the last century, but this idea did not come into actual application until the beginning of the third millennium, at the hands of technology companies such as Apple, Hp, IBM, which had a great impact in supporting the march and development of various electronic cloud services. Despite its criticisms, cloud computing is here to stay. The current economic situation will force universities and more organizations to at least consider adopting a cloud solution. The results of the study showed a professional relationship between the use of cloud computing and the development of accounting education at the level of significance of 0.05. The most important recommendations of the study for universities to provide the material and technical capabilities to activate the use of cloud computing in accounting education
In this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
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Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
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A Stereomicroscopic Evaluation of Four Endodontic Sealers Penetration into Artificial Lateral Canals Using Gutta-Percha Single Cone Obturation Technique, Omar Jihad Banawi*, Raghad
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A chemometric method, partial least squares regression (PLS) was applied for the simultaneous determination of piroxicam (PIR), naproxen (NAP), diclofenac sodium (DIC), and mefenamic acid (MEF) in synthetic mixtures and commercial formulations. The proposed method is based on the use of spectrophotometric data coupled with PLS multivariate calibration. The Spectra of drugs were recorded at concentrations in the linear range of 1.0 - 10 μg mL-1 for NAP and from 1.0 - 20 μg mL-1 for PIR, DIC, and MEF. 34 sets of mixtures were used for calibration and 10 sets of mixtures were used for validation in the wavelength range of 200 to 400 nm with the wavelength interval λ = 1 nm in methanol. This method has been used successfully to quant
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Some metal ions (Mn+2, Fe+2, Co+2,Ni+2,Cu+2 and Cd+2) complexes of N-acetyl Tryptophan (AcetrpH) and α-Picoline (α-Pic) have been synthesized and characterized on the basis of their FTIR,UV-Vis spectroscopy , conductivety measurements , magnetic susceptibility. From the results obtained, the following general formula has suggested for the prepared complexes. [M+2(Acetrp)2(α-Pic)2]. XH2O Where M = Mn+2, Fe+2, Co+2,Ni+2,Cu+2 and Cd+2 X = 0 , 0 , &nb
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Abstract
Psoriasis is defined as a series of events that begins in its initial stage with dermatitis and then progresses to more widespread inflammation and increased oxidative stress. The aim of this study was to determine whether psoriasis and the levels of IL-15, IL-23, and TNF-α are related, the ELISA technique was used to detect the levels of inflammation in psoriasis patients and to compare them with healthy individuals. This study included 150 samples, including 90 patients with psoriasis and 60 healthy individuals, and the study was conducted from November 2021 to April 2022. The current study revealed that there was a significant difference in the level of TNF-α in the group of psoriasis patients compa
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