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

Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft

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 current article an easy and selective method is proposed for spectrophotometric estimation of metoclopramide (MCP) in pharmaceutical preparations using cloud point extraction (CPE) procedure. The method involved reaction between MCP with 1-Naphthol in alkali conditions using Triton X-114 to form a stable dark purple dye. The Beer’s law limit in the range 0.34-9 μg mL^-1 of MCP with r =0.9959 (n=3) after optimization. The relative standard deviation (RSD) and percentage recoveries were 0.89 %, and (96.99–104.11%) respectively. As well, using surfactant cloud point extraction as a method to extract MCP was reinforced the extinction coefficient(ε) to 1.7333×105L/mol.cm in surfactant-rich phase. The small volume of organi

Two different oxidative desulfurization strategies based on oxidation/adsorption or oxidation/extraction were evaluated for the desulfurization of AL-Ahdab (AHD) sour crude oil (3.9wt% sulfur content). In the oxidation process, a homogenous oxidizing agent comprising of hydrogen peroxide and formic acid was used. Activated carbons were used as sorbent/catalyst in the oxidation/adsorption process while acetonitrile was used as an extraction solvent in the oxidation/extraction process. For the oxidation/adsorption scheme, the experimental results indicated that the oxidation desulfurization efficiency was enhanced on using activated carbon as catalyst/sorbent. The effects of the operating conditions (contact time, temperat

Iraq suffers from lack of water resources supply because the headwaters of the rivers located outside its borders and the influence of upstream countries on the quantities of flowing water, in addition to the increase of pressure on available water as a result of population increase and not adopting the principle of rationalization where misuse and wastage and lack of strategic vision to treat and manage water use in accordance with the economic implications fall.  This is reflected fallout on water security and subsequently on national and food security, while the issue of using water resources is development top priority in different countries in the world because of the importance of water effect on the security of indivi

The genetic diversity was studied in sixteen barley Hordeum vulgar L. species cultivated in Iraq , which are differ in their ability to drought stress tolerance by using random amplified polymorphic DNA polymerase chain reaction (RAPD - PCR ) .Barley species was evaluated to drought stress  after treatment the plant seedling at germination stages to different concentration of polyethylene glycol (PEDG6000) . The results showed that the Broaq and Arefat species have the highest tolerance to drought stress in contrast the rest of Barly species like Alkhair, Alwarkaa, Ebaa99, Shoaa, Alrafidain,Sameer Rehana 3 , forat9 , jazeral ,and ebaa7 revealed sensitivity to drought stress .      The primes which used RAPD technique

Sliver / Sliver chloride is as old used from human but the sliver / sliver chloride nanoparticles have only recently been recogenized. They have used in medicin and agiculture. In the present study have been investigation the effecte biosynthesis Sliver / Sliver chloride nanoparticles as antibacterial by demonstrated that Ag / AgCl NPs arrest the growth of many bacterial: S.typhimurium, k. pneumonia. S. aureus, L.monocytogenes, B. Anthracis, E. coli, C. frundi, S. Pneumonia, P. Aeruginosa. The elements compestion and crystallization panal of biosynthesized nanoparticles were chracterazated by FTIR, XRD and SEM. From XRD, It is confirmed the synthesized nanoparticles contain Sliver / Sliver chloride elements. Synthesized Ag / AgCl NPs showed