The entrance process re-engineering one of the main entrances of administrative and technology appropriate to keep pace with scientific progress and the continuing changes in business environment and for the purpose of achieving the goal sought by the organizations in the pursuit of rapid developments and renewable energy in the market competition by changing its operations and activities of the radical change which contributes to an effective contribution to reducing the cost of product or service taking into account the quality improvement in the management of change to keep the increase value and speed of placing on the market to meet customer needs and desires to achieve a

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

The results shows existence of metals such as copper, iron, Cadmium, lead and zinc in most of examined samples , the highest concentration are up to (2.26, 40.82, 282.5, 31.02, 19.26, 4.34) Part per million) ppm) in pasta hot (Zer brand), Indomie with chicken, granule (Zer brand), brand (Zer brand), and rice (mahmood brand) respectively, with presence nickel in spaghetti( Zer brand), granule, Zer brand with concentration reached to 4.34 ppm and 1.06 ppm respectively.
The results of cereals group and its products show that two kinds of fungi, Aspergillus spp. and Penicillin spp. were found in rice (Mahmood brand) with numbers got to 1.5×103 Colony Forming Unit/ gram (c.f.u./g),while Bacillus cereus and Staphylococcus aureus were isola

Soils at Al-Koot-Btera were choosen to determine their sedimentary
environments. It is found that there are , five soil series and as mentioned :
MF11-MW9-DM97-DM57-DF95 . The five found soil series are of internal
well drained ,moderate and imperfect. Their textures vary in moderately,fine
and moderately fine.
indicating that sediments rang from poorly to very poorly sorting. Values of median
diameter Md Ø range between 4.11-7.80 Ø .The relation between the sorting
and median diameter shows that 95.24% of samples is a sedimentary
environment of aquite river , while 4.76% is aeolian sediments.
The values of meso to platy kurtic of most horizon materials rang
between 0.67-1.26 Ø .That is to say the samples

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

In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har