Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

The Leishmania donovani parasite causes visceral leishmaniasis (VL), an acute and fatal form of leishmaniasis. Because traditional therapy alternatives, such as glucantime and other pentavalent medicines, are toxic and have side effects, new treatments with fewer negative effects are needed. Only a handful of drugs are clinically beneficial to treatments of the disease, but considerable limitations threaten their very usage. Novel, safe, and efficient drugs, including those against antimalaria and leishmaniasis co-infections, are so essential. Artemether (ATM) is an Artemisinin derivative that has been demonstrated to be useful in the treatment of malaria and, more recently, leishmaniasis. The current research was carried out to evaluate th

          Cardiovascular risk is independently increased by plasma lipids abnormalities (low- density and high density lipoprotein -cholesterol and triglycerides). Most patients have more than one lipid abnormality. Combination therapy with lipid-modifying agents could offer an important therapeutic option for improving the overall lipid profile. Combinations have demonstrated to provide additive efficacy and significant reductions in coronary events . This study was designed to evaluate the effect of ezetimibe, when used in combination with other hypolipidaemic agents ( statins) on lipid  profile as well as on liver function ,renal function, oxidative stress, and platele

The aim of this research is to find out the impact of cognitive incompatibility schemes on the development of creative thinking skills among first grade students.
To prove the objective of the research, the researcher put the following hypothesis:
There is no statistically significant difference at the level of (0.05) between the average score of the experimental group who study the history of ancient civilizations according to the patterns of cognitive conflict and the average grades of the control group students who study the same subject in the usual way in the test of post-creative thinking skill

The nuclear level density parameter  in non Equi-Spacing Model (NON-ESM), Equi-Spacing Model (ESM) and the Backshifted Energy Dependent Fermi Gas model (BSEDFG) was determined for 106 nuclei; the results are tabulated and compared with the experimental works. It was found that there are no recognizable differences between our results and the experimental -values. The calculated level density parameters have been used in computing the state density as a function of the excitation energies for ⁵⁸Fe and ²⁴⁶Cm nuclei. The results are in a good agreement with the experimental results from earlier published work.