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

Between the 1980s and 1990s, the HURIER model was developed by Brownell and consist of six interrelated components, which are represented in these acronyms (Hearing, Understanding, Remembering, Interpreting, Evaluating, and Responding). This model can be considered as a framework of the behavioral approach which can be used to improve students’ listening performance and to foster a positive attitude toward listening. Many learners find it challenging to improve their listening skills when learning a second or foreign language because it requires the integration of both listening and speaking. Consequently, enhancing this skill will help students improve other language skills, including reading, speaking, and writing. The HURI

Background: Dental caries is a localized, progressive destructive, largely irreversible microbial based disease of multifactorial nature; these factors include (host, microbes and food) they influence differently on the initiation and progression of dental caries. The aims of the study: was to evaluate the effect of smoking on salivary flow rate, secretory immunoglobulin (SIgA) level and viable count of mutans streptococci (M.S) bacteria in oral cavity and their relation to dental caries experience. Material and method: The samples were collected from 80 male students ranging in ages from 18-22 years old. Where they divided in to two groups, 40 non-smokers (control group) and 40 smokers (study group). Unstimulated salivary samples were c

Soft red winter wheat (SRW) is characterized by high yield and relatively low protein content. In Kentucky, there is growing demand from local artisan bread bakers for regionally produced flour, requiring production of grain with increased protein content and/or strength. The objective of this two-year field experiment was to evaluate the effect of nitrogen (N) management on five cultivars of winter wheat on yield and bread baking quality traits of modern and landrace SRW cultivars (Triticum aestivum L.). All five cultivars were evaluated using two N application rates in conventional and organic production systems. All traits measured were significantly affected by the agricultural production system and N rate, although plant height

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security