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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
Sun Dec 31 2023
Journal Name
Iraqi Journal Of Information And Communication Technology
EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
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This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
A proposed method for cleaning data from outlier values using the robust rfch method in structural equation modeling
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Scopus
Publication Date
Tue May 05 2015
Journal Name
International Journal Of Advanced Scientific And Technical Research
Fuzzy Stochastic Probability of The Solution of Single Stationary Non- Homogeneous Linear Fuzzy Random Differential Equations
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Publication Date
Thu Oct 03 2013
Journal Name
J. Of University Of Anbar For Pure Science
Determination of thyroid hormone levels in the serum of Non- dialyzed patients with chronic renal failure
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Thyroid hormones, triiodothyronine (T3) and thyroxin (T4) play an important role in growth, development, and physiology of the kidney. The kidney has a central role in metabolism and clearance of these hormones as well as thyroid – stimulating hormone (TSH). Chronic renal failure (CRF) is a state of irreversible deceleration in renal function results in alterations in internal milieu, which affects the synthesis and secretory rate of hormones. To evaluate the thyroid hormone levels in non-dialyzed patients with chronic renal failure (CRF); 24 patients with CRF aged 30-70 years, mean±S.d. (48.458 ± 13.569) and 48 healthy volunteers who served as controls aged 30-70 years (43.104 ± 12.387) were studied for their thyroid function status u

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Publication Date
Mon Jul 09 2018
Journal Name
اتحاد الاحصائيين العربوقائع المؤتمر الدولي العلمي السادس لاتحاد الاحصائيين العرب
The Use of Markov Chain to reveal the reality of non- oil econ0miv indicators in Iraq
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The research mainly seeks to predict the amounts of non- oil Iraqi exports which concludes ) Food & Animals , Raw materials and non- tanned Leather and fur , Mineral fuels and Lubricating Oil , Chemical substances and amounts , Manufactured goods , Electrical and non - electrical machines , Supplies and Total non- Oil exports ) by using Markov Chain as one of Statistical approach to forecasting in future . In this search We estimate the transliteration probabilities matrix according to Maximum Likelihood on a data collected from central organization for Statistics and information technology represents an index numbers of non- Oil exports amount in Iraq from 2004 to 2015 depending on 2007 as a basic year . Results shown that trend of index

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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of ginger extract on Mutans streptococci in comparison to chlorhexidine gluconate
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Background: The rhizome of ginger is used in cooking and for medicinal purposes such as anti-bacterial, anti-fungal, anti-inflammatory and antioxidant. The aims of the study were to test the effect of ethanolic extract of ginger on growth, adherence and acidogenicity of mutans streptococci in comparison to chlorhexidine gluconate 0.2% and de-ionized water. Materials and methods: From saliva often volunteers (dental students 20-22 years); mutans streptococci was isolated, purified and diagnosed according to morphological characteristic and biochemical tests. Ginger was powdered and extracted, different concentrations of ginger extract were prepared. Chlorhexidine gluconate 0.2% used as a control positive; while de-ionized water was used as a

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Medical Sciences
Comparison of ABGAR Score among Gestational, Pregestational Diabetes and Normal Pregnant Women
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Background: The Apgar score is calculated based on the five features: heart rate, reflexes, color, muscle tone, and respiratory effort. Each element is scored from 0 to 2, with a total probable score of 10 at 1 minute and 5 minute. Aim: To study the influence of gestational diabetes mellitus (GDM) and diabetes mellitus on APGAR score in neonate. Materials and methods: The samples were studied from Department of Obstetrics and Gynaecology in Al-Imamain Al-Kadhimiyain (AS) Medical city, Baghdad Teaching Hospital and Al-Karkh Maternity Hospital in the period between 1 December 2016 and 1 may 2017, after obtaining the approval from Iraqi Ministry of Health. A total of 102 neonates were included in this study which includes 34 neonates of mother

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Engineering
Comparison of Seepage Trough Zoned Earth dam Using Improved Light-Textured Soils
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Seepage through earth dams is one of the most popular causes for earth dam collapse due to internal granule movement and seepage transfer. In earthen dams, the core plays a vital function in decreasing seepage through the dam body and lowering the phreatic line. In this research, an alternative soil to the clay soil used in the dam core has been proposed by conducting multiple experiments to test the permeability of silty and sandy soil with different additives materials. Then the selected sandy soil model was used to represent the dam experimentally, employing a permeability device to measure the amount of water that seeps through the dam's body and to represent the seepage line. A numerical model was adopted using Geo-Studio software i

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Publication Date
Fri Jan 01 2016
Journal Name
Al-qadisiyah Medical Journal
Comparison between dome and wedge osteotomy in management of hallux valgus deformity
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Background: the condition of hallux valgus is considered as the most common deformities affecting females more than males, characteristically manifested as lateral deviation of the big toe and widening of first and second inter -metatarsal angle with a deformity of second toe in some severe cases. Objective: to make a radiological and clinical assessment of two surgical methods of osteotomy used in treatment of hallux valgu and to compare between them: first one is the distal dome osteotomy, and second one is a distal wedge metatarsal osteotomy. Patients and methods: a total of 36 feet of 28 patients suffer from hallux valgus, with mean age of 50.3 years were included in this study, followed for 6- 30 months ( mean follow-up of 8.8 months).

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
CALCULATION BIASES FOR COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES
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Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

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