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

irrigation use at many stations along the Euphrates River inside the Iraqi lands and to try to correlate the results with the satellite image analyses for the purpose of making a colored model for the Euphrates that can be used to predict the quality classifications of the river for irrigation use at any point along the river. The Bhargava method was used to calculate the water quality index for irrigation use at sixteen stations along the river from its entrance to the Iraqi land at Al-Qaim in Anbar governorate to its union with the Tigris River at Qurna in Basrah governorate. Coordinates of the sixteen stations of the Euphrates River were projected at the mosaic of Iraq satellite image which was taken from LANDSAT satellite for bands 1, 2

Background: Chronic periodontitis (CP) is greatly prevalent condition of inflammatory behavior. Salivary biomarker total antioxidants capacity (T-AOC) status, may be related to both periodontal condition and oral hygiene. Aims of the study: To assess the level of salivary T-AOC of patients with chronic periodontitis in comparison to healthy control and to correlate between the level of this marker with the clinical periodontal parameters (plaque index (PLI), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment level (CAL)). Materials and Methods: Ninety subjects of males and females with an age ranged between (35-55) years were participated in this study. Participants were divided into two grou

This article proposes a new technique for determining the rate of contamination. First, a generative adversarial neural network (ANN) parallel processing technique is constructed and trained using real and secret images. Then, after the model is stabilized, the real image is passed to the generator. Finally, the generator creates an image that is visually similar to the secret image, thus achieving the same effect as the secret image transmission. Experimental results show that this technique has a good effect on the security of secret information transmission and increases the capacity of information hiding. The metric signal of noise, a structural similarity index measure, was used to determine the success of colour image-hiding t

Multilayer reservoirs are currently modeled as a single zone system by averaging the reservoir parameters associated with each reservoir zone. However, this type of modeling is rarely accurate because a single zone system does not account for the fact that each zone's pressure decreases independently. Pressure drop for each zone has an effect on the total output and would result in inter-flow and the premature depletion of one of the zones. Understanding reservoir performance requires a precise estimation of each layer's permeability and skin factor. The Multilayer Transient Analysis is a well-testing technique designed to determine formation properties in more than one layer, and its effectiveness over the past two decades has been

Background: Recurrent Aphthous Stomatitis (RAS) is the most common painful oral mucosal disease, affecting approximately 20% of the population. RAS presents with a wide spectrum of severity ranging from a minor nuisance to complete debility. Many of factors thought to have been involved in its etiology; that might have at the same time a direct or indirect impact upon oxidant/antioxidant system and trigger free radicals production. The aim of this study was to determine the possible association of oxidant/total antioxidant status and recurrent aphthous stomatitis (RAS). Subjects, materials and methods: The study consisted of thirty patients with recurrent aphthous stomatitis and thirty healthy controls from which saliva and blood samples we

The radon gas concentration in environmental samples soil and water of selected regions in Al-Najaf governorate was measured by using alpha-emitters registrations which are emitted form radon gas in (CR-39) nuclear track detector. The first part is concerned with the determination of radon gas concentration in soil samples, results of measurements indicate that the highest average radon concentration in soil samples was found in (Al-Moalmen) region which was (100.0±7.0 Bq/m3), while the lowest average radon concentration was found in (Al-Askary) region which was (38.5±4.7 Bq/m3), with an average value of (64.23±14.9 Bq/m3) ,the results show that the radon gas concentrations in soil is below the allowed limit from (ICRP) agency which is (

Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme