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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 Jan 01 2020
Journal Name
Biochemical & Cellular Archives
MORPHOLOGICAL STUDY OF THE BRAIN AND SPINAL CORD OF THE IRAQI FROG, RANA RIDIBUNDA RIDIBUNDA
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The frog has a highly developed nervous system. It consists of a brain, a spinal cord and nerves. The brain is the only center for the control of all vital activities as it receives impulses from different parts of the body through sensory nerves and issues orders through motor fibers to different parts of the body for appropriate action. The Aims of studyis general morphological structural of the brain and spinal cord in the Iraqi frog Rana ridibunda ridibunda. The brains of twenty of frogs belonging to class Amphibia were studied using conventional techniques of dissecting microscopy. All samples were sacrificed and anesthetized and then they were removed completely from the neurocranium, cranial, sensory nerves and the meninges and trans

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Some Estimation Methods Of GM(1,1) Model With Missing Data and Practical Application
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This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Comparison Different Estimation Methods for the Parameters of Non-Linear Regression
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   Nonlinear regression models are important tools for solving optimization problems. As traditional techniques would fail to reach satisfactory solutions for the parameter estimation problem.  Hence, in this paper, the BAT algorithm  to estimate the parameters of  Nonlinear Regression models is used . The simulation study is considered to investigate the performance of the proposed algorithm with the maximum likelihood (MLE) and Least square (LS) methods. The results show that the Bat algorithm provides accurate estimation and it is satisfactory for the parameter estimation of the nonlinear regression models than MLE and LS methods depend on Mean Square error.

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Publication Date
Thu Jul 01 2021
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Embryonic Development of Spinal Cord in White Choeked Bulbul (Pycnonotus leucotis)
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The study concerned the embryonic development of spinal cord of white choeked bulbul Pycnonotus leucotis. The spinal cord at the age 40 hour’s incubation from the neural tube and its tissue wall is composed of two layers, the ependymal layer and mantle layer. The spinal cord differentiation is completed at the age 7 day’s incubation, its, were we notice that the central canal is clear and cavity lined with neurons and we note the arrangement of gray matter in the form of the letter H and its inside and it is characterized by dorsal and ventral horns and the gray matter substance and note the formation of dorsal medium spetum and ventral medium fissure.

Publication Date
Sat Aug 25 2018
Journal Name
Pak. J. Biotechnol
Histological structure of Spinal Cord in Quail Coturnix coturnix (Linnaeus,1758)
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The study is done in the period between (February 20 and October 20) by using ten adult quail Coturnix coturnix (Linnaeus, 1758). The sections are preparing by paraffin method then stain in Harris haematoxylin-eosin. The histological aspects of spinal cord in quail (Coturnix coturnix) the white matter is in the outer part, while the gray matter is arranged in from of X represents its internal part, the dorsal region is called the dorsal horns while the ventral region is called the ventral horns and the central canal cavity, the spinal cord areas appeared as follows: The medial column, column of von Lenhossek, lateral column, dorsal magnocellular column and marginal paragriseal, columns are also called Hoffmann’s nuclei.

Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Non-Parametric Quality Control Methods
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    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor (

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Publication Date
Wed May 01 2013
Journal Name
Ieee Journal Of Biomedical And Health Informatics
Classification of Finger Movements for the Dexterous Hand Prosthesis Control With Surface Electromyography
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Publication Date
Sat Dec 31 2016
Journal Name
Al-kindy College Medical Journal
A Comparison of Sagittal Sections of Short T1inversion Recovery and T2 Weighted Fast Spin Echo Magnetic Resonance Sequences for Detection of Multiple Sclerosis Spinal Cord Lesions
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Background: Multiple sclerosis is a chronic autoimmune inflammatory demyelinating disease of the central nervous system of unknown etiology. Different techniques and magnetic resonance image sequences are widely used and compared to each other to improve the detection of multiple sclerosis lesions in the spinal cord. Objective: To evaluate the ability of MRI short tau inversion recovery sequences in improvementof multiple sclerosis spinal cord lesion detection when compared to T2 weighted image sequences. Type of the study: A retrospective study. Methods: this study conducted from 15thAugust 2013 to 30thJune 2014 at Baghdad teaching hospital. 22 clinically definite MS patients with clinical features suggestive of spinal cord involvement,

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating the Scheff'e Model of the Mixture
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Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
ESTIMATED NON-PARAMETRIC AND SEMI-PARAMETRIC MODEL FOR LONGITUDINAL DATA
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