This paper presents a hierarchical model of localized company effective when is used in a university campus or site. To highlight the standard criteria for each layer of the model and to prove the positive aspects of this model is the best in use and make the Dell Network as case of study. Through the case of study it has been shown that the expansion of the on-site network does not affect services or bandwidth.

This study was conducted to investigate the antibacterial activity of green synthesized copper oxide nanoparticles (CuO NPs) using Aloe vera. Initially, bacteria were collected from clinical samples of patients having otitis media infection and the isolates were identified at the species level following biochemical tests. Copper oxide nanoparticles were prepared by green synthesis using Aloe vera leaves and characterized using UV- visible spectroscopy at 260 nm peak. The shape and size were determined by using transmission electron microscopy (TEM) and the dimensions of the particles were more precisely determined by using scanning electron microscopy (SEM) and x-ray diffraction (XRD). Different concentrations of nanopa

Escherichia coli  infections are becoming difficult treated because of extensive resistance to antibiotic among these organisms and manufacturing extended-spectrum beta lactamases enzymes (ESBLs) make them resistant to beta-lactam antibiotics. This study aims to offer a summary of the main horizontal transmission  apparatuses  between E. coli as well as  Staphylococcus aureus and emergence resistance to antibiotics. Fifty of the E. coli and  50 of S. aureus isolates were examined to obtain minimum inhibitory concentration (MIC) results. These isolates were then tested by  conventional polymerase chain-reaction for the existence or absenc

In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

In the current research, multiple mixing ratios of gamma -transitions of the energy levels 60𝑁𝑑 142−150 isotopes populated in 𝑁𝑑(𝑛, 𝑛 ˊ 60 142−150 ) 60𝑁𝑑 142−150 interaction are calculated using the constant statistical tensor (CST) method. The results obtained are, in general, in good agreement or consistent, within the experimental error, with the results published in the previously researches. Existing discrepancies result from inaccuracies in the experimental results of previous works. The current results confirm the validity of the constant statistical tenser method of calculating the values of mixing ratios and its predictability of errors in experimental results

Based on analyzing the properties of Bernstein polynomials, the extended orthonormal Bernstein polynomials, defined on the interval [0, 1] for n=7 is achieved. Another method for computing operational matrices of derivative and integration D_b and R_(n+1)^B respectively is presented. Also the result of the proposed method is compared with true answers to show the convergence and advantages of the new method.

The concept of fully pseudo stable Banach Algebra-module (Banach A-module) which is the generalization of fully stable Banach A-module has been introduced. In this paper we study some properties of fully stable Banach A-module and another characterization of fully pseudo stable Banach A-module has been given.

This study focuses on CFD analysis in the field of the shell and double concentric tube heat exchanger. A commercial CFD package was used to resolve the flow and temperature fields inside the shell and tubes of the heat exchanger used. Simulations by CFD are performed for the single shell and double concentric tube.

This heat exchanger included 16 tubes and 20 baffles. The shell had a length of 1.18 m and its diameter was 220 mm. Solid Works 2014, ANSYS 15.0 software was used to analyze the fields of flow and temperature inside the shell and the tubes. The RNG k-ε model was used and it provided good results. Coarse and fine meshes were investigated, showing that aspect ratio has no significant effect. 14 million

     A global pandemic has emerged as a result of the widespread coronavirus disease (COVID-19). Deep learning (DL) techniques are used to diagnose COVID-19 based on many chest X-ray. Due to the scarcity of available X-ray images, the performance of DL for COVID-19 detection is lagging, underdeveloped, and suffering from overfitting. Overfitting happens when a network trains a function with an  incredibly high variance to represent the training data perfectly. Consequently, medical images lack the availability of large labeled datasets, and the annotation of medical images is expensive and time-consuming for experts. As the COVID-19 virus is an infectious disease, these datasets are scarce, and it is difficult to get large datasets