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

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 availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

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

BACKGROUND: Nebulized Salbutamol have great advantages for patients with respiratory problems by depositing drugs directly to the lungs, inspite of reported adverse metabolic effects on different electrolytes and glucose heamostasis of patients.AIM OF STUDY: To evaluate the effect of nebulized salbutamol used in the management of patients with asthma who have normal serum potassium and blood glucose levels. in the emergency department after 30 and 60 minutes of administration and to find out if these results are of clinical importance that should be taken in consideration when treating patients especially those with abnormal glucose hemostasis or electrolyte disturbance. PATIENTS & METHODS: The study is a prospective follow

Purpose: The research aims to study the measurement of the performance of accounting units level of the research sample by using the Federal quality Model European (EFQM)   Design/methodology/approach: the (EFQM) which included seven dimensions "Leadership, Strategic Planning, External Focus, Information and Analysis, Faculty / Staff and Workplace Focus, Process Effectiveness & Outcomes and Achievements" And its effect on the Control Environment, which includes three dimensions: "Integrity, management philosophy and commitment to powers" . the sample is supervisory units of colleges affiliated with the University of Baghdad in Iraq, and a sample was chosen that included fifty-one individuals in the accounting departments.

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