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

Vol. 6, Issue 1 (2025)

The researcher focused on the importance of the physical abilities of the tennis game, as this game is one of the games that are characterized by its specificity in performance as this game is characterized by continuous movement and dealing with different elements, so this game requires the development of muscle strength, which plays an important role in Performance skills in the game of tennis. There are several methods to develop strength, including flat hierarchical technique, which is one of the most common forms of training in the development of muscle strength.     As for the research problem, the researcher found a method that has an effect on the development of force. Therefore, the researcher tried to diversify a

The researcher focused on the importance of the physical abilities of the tennis game, as this game is one of the games that are characterized by its specificity in performance as this game is characterized by continuous movement and dealing with different elements, so this game requires the development of muscle strength, which plays an important role in Performance skills in the game of tennis. There are several methods to develop strength, including flat hierarchical technique, which is one of the most common forms of training in the development of muscle strength.     As for the research problem, the researcher found a method that has an effect on the development of force. Therefore, the researcher tried to diversify a

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

This study deals with the corrosion inhibition of metal corrosion process of medium carbon steel using 1M HCl for kinetic studies and rate reaction determination. The weight loss method is applied to pieces of Medium carbon steel divided to Cubans with dimensions (0.4*2*2.4) cm , and use Tafel Extrapolation Method, the samples were polished using carbide silicon paper with dimensions of (180,200,400,600,800,1000). The samples were immersed in the alcoholic medium ethanol at a temperature 293K for 3hr. Natural inhibitor Kujarat Tea (Hibiscus sabdarriffa L.) is used which is extracted in aqueous and alcoholic medium, different concentrations (1000،2000, 3000) ppm have been used ; The best concentration found through the results is a

This study deals with the corrosion inhibition of metal corrosion process of medium carbon steel using 1M HCl for kinetic studies and rate reaction determination. The weight loss method is applied to pieces of Medium carbon steel divided to Cubans with dimensions (0.4*2*2.4) cm , and use Tafel Extrapolation Method, the samples were polished using carbide silicon paper with dimensions of (180,200,400,600,800,1000). The samples were immersed in the alcoholic medium ethanol at a temperature 293K for 3hr. Natural inhibitor Kujarat Tea (Hibiscus sabdarriffa L.) is used which is extracted in aqueous and alcoholic medium, different concentrations (1000،2000, 3000) ppm have been used ; The best concentration found through the results is a conce

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