In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.

Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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

new six mixed ligand complexes of some transition metal ions Manganese (II), Cobalt(II), Iron (II), Nickel (II) , and non transition metal ion zinc (II) And Cadmium(II) with L-valine (Val H ) as a primary ligand and Saccharin (HSac) as a secondary ligands have been prepared. All the prepared complexes have been characterized by molar conductance, magnetic susceptibility infrared, electronic spectral, Elemental microanalysis (C.H.N) and AA . The complexes with the formulas [M(Val)2(HSac)2] M= Mn (II) , Fe (II) , Co(II) ,Ni(II), Cu (II),Zn(II) and Cd(II) L- Val H= (C5H11NO2) , C7H5NO3S The study shows that these complexes have octahedral geometry; The metal complexes have been screened for their in microbiological activities against bacteria.

The effect of Wood Flour addition to the gamma alumina powder used in the preparation of gamma alumina (ɤ-Al₂O₃) catalyst carrier extrudates on the pore volume and BET surface area physical properties was investigated. Two parameters which are size of wood flour particles and its quantity were studied. The sizes of wood flour particles used are 150 µm, 212 µm and 500 µm and the weight percentage added to the gamma alumina powder during the preparation of the extrudates are (1%, 3%, 5% and 10%). The results showed that the addition of wood flour to the gamma alumina powder in order to get gamma alumina extrudates used as catalyst carrier is one of the successful methods to improve the pore volume

The present work involved a study the effect of cobalt(II) complex with formula [CoL(H2O)NO3] .4ETOH where L=Nitro [5-(P-nitro phenyl) -4-phenyl-1,2,4 traizole-3-dithiocarbamato hydrazide] aqua. (4) Ethanol and anti-cancer drug - cyclophosphamide on specific activity of two liver enzymes (GPT,ALP) by utilizing an in vivo system in female mice. On the enzymatic level an inhibition in the activity of GPT was noticed in different body organs such as liver, kidney and lung. The inhibition was noticed in both test and cyclophosphamide drug (cp). Mice were treated with three doses of cyclophosphamide (90,180, 250) ?g/ mouse for three days. The same doses were used for the cobalt (II) complex. The liver shows the highest rate of(GPT) inhibition co