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Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury
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Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental stages (pre-and post-lesion) using electromyography signals. Eight time-domain features were extracted from the collected electromyography data. To overcome the imbalanced dataset issue, synthetic minority oversampling technique was applied. Different ML classification techniques were applied including multilayer perceptron, support vector machine, K-nearest neighbors, and radial basis function network; then their performances were compared. A confusion matrix and five other statistical metrics (sensitivity, specificity, precision, accuracy, and F-measure) were used to evaluate the performance of the generated classifiers. The results showed that the best classifier for the left- and right-side data is the multilayer perceptron with a total F-measure of 79.5% and 86.0% for the left and right sides, respectively. This work will help to build a reliable classifier that can differentiate between these two phases by utilizing some extracted time-domain electromyography features.

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Updating the uniform accounting system in Iraq for installment sales transactions framework
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Due to the intensity of competition between economic units that run the trade in durable goods had to pay a lot of these companies to follow the new selling methods aimed at attracting customers to be able to increase its sales and thereby increase their profits ,  these methods are installment sales, which had been in great demand by the customers with limited income, who provides them with the possibility of possession and use of such goods and to postpone the full amount of the payment to the seller, This transaction sales have grown even became installment sales system at the present time of the common types of sales transactions and deployed a lot in our environment and in many sectors of the market, and in some cases m

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Publication Date
Thu Apr 20 2023
Journal Name
Fire
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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Publication Date
Sun Oct 01 2023
Journal Name
Ieee Transactions On Industrial Electronics
Singular Perturbation-Based Adaptive Integral Sliding Mode Control for Flexible Joint Robots
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The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha

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Publication Date
Mon Aug 01 2022
Journal Name
Water, Air, & Soil Pollution
Cladophora Algae Modified with CuO Nanoparticles for Tetracycline Removal from Aqueous Solutions
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Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

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Publication Date
Wed Nov 01 2023
Journal Name
Biocatalysis And Agricultural Biotechnology
Enhancing the prodigiosin pigment by adding Ag\TiO2 synergism for antibacterial activity
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Fri Oct 01 2010
Journal Name
Analytica Chimica Acta
A reversed phase high performance liquid chromatography method for the determination of fumonisins B1 and B2 in food and feed using monolithic column and positive confirmation by liquid chromatography/tandem mass spectrometry
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The development of a reversed phase high performance liquid chromatography fluorescence method for the determination of the mycotoxins fumonisin B1 and fumonisin B2 by using silica-based monolithic column is described. The samples were first extracted using acetonitrile:water (50:50, v/v) and purified by using a C18 solid phase extraction-based clean-up column. Then, pre-column derivatization for the analyte using ortho-phthaldialdehyde in the presence of 2-mercaptoethanol was carried out. The developed method involved optimization of mobile phase composition using methanol and phosphate buffer, injection volume, temperature and flow rate. The liquid chromatographic separation was performed using a reversed phase Chromolith® RP-18e column

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Evaluating Educational Programs in Combating Indecent Behaviors Among University Students Using Structural Equation Modeling (Field study: Northern Border University)
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The study aimed to evaluate educational programs efficiency in applying the best educational practices to educate students from the dangers of indecent behaviors, in line with higher education policy and the appropriateness of educational program dimensions to spread awareness among students to not fall into the indecent behaviors clutches. The study adopted the inductive exploratory approach through structural equation modeling and the descriptive analysis of the collected data from randomly selected sample (n=385) from educational academics at Northern Border University in the Saudi Arabia using a specially designed survey tool to meet study purposes to evaluate dimensions of teaching methods, evaluation tools, training courses, course

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Publication Date
Fri Jun 05 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Tensile force measurement by using different lingual retainer wires, bonding materials types and thickness (A comparative in vitro study)
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Background: The bonded orthodontic retainer constructed from multistrand wire and composite is an efficient esthetic retainer, which can be maintained long-term. Clinical failures of bonded orthodontic retainers, most commonly at the wire/composite interface, have been reported. This in vitro investigation aimed to evaluate the tensile forces of selected multistrand wires and composite materials that are available for use in the construction of bonded fixed retainers. Materials and Methods: The study sample includes 120 wires with three types of retainer wires (3 braided strands\ Orthotechnology, 8 braided strands\ G&H Orthodontics, 6 coaxial strands\ Orthoclassic wires), two types of adhesive (flowable\ Orthotechnology, non flowable\ G&H O

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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Comparative Study between Oral Hypoglycemic Drugs Repaglinide, Glibenclamide and Rosiglitazone on Some Biochemical Parameters in Type 2 Diabetic Patients
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Type 2 diabetes mellitus is often characterized by hyperglycemia as a result of increased insulin resistance in hepatic/peripheral tissues and pancreactic B-cell dysfunction. Approximately 92% of patients with type 2 diabetes mellitus demonstrate insulin resistance, however hyperglycemia is always a consequence of insulin deficiency. This study was done on 120 patients newly diagnosed diabetes type 2 characterized by dyslipidemia that is increased triglycerides and decreased HDL. Hypoglycemia and weight gain are common problem with oral sulfonyl urea drugs. In this work three different oral hypoglycemic drugs repaglinide and glibenclamide (insulin secretagogues) and rosiglitazone (insulin sensitizer) were used for treatment of patients w

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