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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 01 2019
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment And Total Dissolved Solids Prediction For Tigris River In Baghdad City Using Mathematical Models
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Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

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Publication Date
Thu Jun 05 2014
Journal Name
Arabian Journal Of Geosciences
Applying the cluster analysis technique in logfacies determination for Mishrif Formation, Amara oil field, South Eastern Iraq
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Publication Date
Tue Jul 01 2014
Journal Name
Ieee Transactions On Circuits And Systems I: Regular Papers
Crosstalk-Aware Multiple Error Detection Scheme Based on Two-Dimensional Parities for Energy Efficient Network on Chip
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Achieving reliable operation under the influence of deep-submicrometer noise sources including crosstalk noise at low voltage operation is a major challenge for network on chip links. In this paper, we propose a coding scheme that simultaneously addresses crosstalk effects on signal delay and detects up to seven random errors through wire duplication and simple parity checks calculated over the rows and columns of the two-dimensional data. This high error detection capability enables the reduction of operating voltage on the wire leading to energy saving. The results show that the proposed scheme reduces the energy consumption up to 53% as compared to other schemes at iso-reliability performance despite the increase in the overhead number o

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Publication Date
Fri Mar 01 2024
Journal Name
Construction And Building Materials
Uni- and tri-axial tests and property characterization for thermomechanical effect on hydrated lime modified asphalt concrete
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Permanent deformation, fatigue and thermal cracking are the three typical distresses of flexible pavement. Using hydrated lime (HL) into the conventional limestone mineral additive has been widely practiced, including in Europe, to improve the mechanical properties of hot mix asphalt (HMA) concrete and as the result the durability of the constructed pavement. Large number of experimental studies have been reported to find the optimum addition of HL for the improvement on HMA concrete mechanical properties, moisture susceptibility and fatigue resistance. Pavement in service is under complex thermomechanical stress-strain conditions due to coupled atmospheric and surrounding environment temperature variation and the traffic loading. To predic

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Tue Sep 07 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Wellbore instability management using geomechanical modeling and wellbore stability analysis for Zubair shale formation in Southern Iraq
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Abstract<p>Wellbore instability problems cause nonproductive time, especially during drilling operations in the shale formations. These problems include stuck pipe, caving, lost circulation, and the tight hole, requiring more time to treat and therefore additional costs. The extensive hole collapse problem is considered one of the main challenges experienced when drilling in the Zubair shale formation. In turn, it is caused by nonproductive time and increasing well drilling expenditure. In this study, geomechanical modeling was used to determine a suitable mud weight window to overpass these problems and improve drilling performance for well development. Three failure criteria, including Mohr–Coulomb, modifie</p> ... Show More
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Publication Date
Wed Sep 30 2020
Journal Name
Cfd Letters
Numerical Analysis for Solar Panel Subjected with an External Force to Overcome Adhesive Force in Desert Areas
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Publication Date
Sun Jun 12 2022
Journal Name
Journal Of Positive School Psychology
international Accounting Standards for Presentation and Disclosure and their Consistency with Islamic Accounting Standards in Ialamic Banks
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The aim of the research is to identify the international accounting standards and accounting standards for Islamic banks, and to analyze the most important problems in the application of Islamic accounting standards, as well as to analyze some of the principles and methods used in the application of accounting standards in Islamic banks. The research was built on three hypotheses, the first being (there is a tangible impact on the application of international accounting standards for banks’ management of liquidity, achieving profits, maintaining property rights and fulfilling their obligations), and the second (the bank facing obstacles using Islamic accounting standards, as it is expected that when using Islamic accounting standar

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Two Domain Flow Method for Leachate Prediction Through Municipal Solid Waste Layers in Al–Amari Landfill Site
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Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to

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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Composition operator induced by ?(z) = sz + t for which |s|?1, |t|<1 and |s|+|t|?1
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We study in this paper the composition operator that is induced by ?(z) = sz + t. We give a characterization of the adjoint of composiotion operators generated by self-maps of the unit ball of form ?(z) = sz + t for which |s|?1, |t|<1 and |s|+|t|?1. In fact we prove that the adjoint is a product of toeplitz operators and composition operator. Also, we have studied the compactness of C? and give some other partial results.

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