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

This work reports the development of an analytical method for the simultaneous analysis of three fluoroquinolones; ciprofloxacin (CIP), norfloxacin (NOR) and ofloxacin (OFL) in soil matrix. The proposed method was performed by using microwave-assisted extraction (MAE), solid-phase extraction (SPE) for samples purification, and finally the pre-concentrated samples were analyzed by HPLC detector. In this study, various organic solvents were tested to extract the test compounds, and the extraction performance was evaluated by testing various parameters including extraction solvent, solvent volume, extraction time, temperature and number of the extraction cycles. The current method showed a good linearity over the concentration ranging from

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

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The aim of the currnet study to examine the effect of subclinical hypothyroidism (SCH) in diabetic patients on coagulation parameters. This retrospective case–control study involves 130 patients diagnosed with type 2 diabetes mellitus (T2DM), divided into 65 T2DM with newly diagnosed SCH and 65 euthyroid (EUT) T2DM patients without SCH. Fibrinogen (FIB) was significantly higher in SCH (508.2 ± 63.0 mg/dL) than EUT (428.1 ± 44.8 mg/dL). In the SCH patients, FIB correlated with several parameters, such as age (β = 0.396), body mass index (β = 0.578), glycated hemoglobin (β = 0.281), and activated partial thromboplastin time (β = 0.276). In conclusion SCH in DM patients appears to increase the magnitude of coagulopathy.

FH Ghanim, Journal of Global Pharma Technology, 2018

Background: Direct measurement of intracellular magnesium using erythrocytes has been suggested as a sensitive indicator for the estimation of body magnesium store. Marked depletion in plasma and erythrocyte magnesium levels was particularly evident in diabetic patients with advanced retinopathy and poor diabetic control. While insulin has been shown to stimulate erythrocyte magnesium uptake, hyperglycemia per se suppressed intracellular magnesium in normal human red cells.
Aim of the study: To investigate the erythrocyte magnesium level in Iraqi type I and II diabetic patients, with specific emphasis on the effect of both, metabolic control and the type of antidiabetic treatments.
Methods: Sixty two diabetic patients (7 with type

The present study included the collection of fresh samples of species of genus Oxalis and examined the anatomical characteristics of the stem, scape, petiole, leaf and pedicel

Many experiments were achieved to determine the allelopathic potential of the plant Myrtle parts in which it may affects other plants, like: volatile substances which released from the Myrtle leaves , and its effect examined on the germination (GE) and growth (GR) of the selected crops ; Chickpea ( C ) , Wheat(W) , and Lentil (L)., the aqueous extract of the leaf and the root of the plant examined to test its effect on the (GE) and (GR) of the selected crops ; (C) , (W) , and (L)., also plant residue of (M) and its effect tested on the (GE) and (GR) of the selected crops ; ( C ) , (W) , and (L) . Experiments proceeded on Spring 2007 in the greenhouse conditions , and main results which found were that; the effect of the volatile s