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Enhancing Upper Limb Prosthetic Control in Amputees Using Non-invasive EEG and EMG Signals with Machine Learning Techniques
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Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducted in this study utilized the Binary Grey Wolf Optimization (BGWO) algorithm to select optimal features for the proposed classification model. The results demonstrate promising outcomes, with an average classification accuracy of 93.6% for three amputees and five individuals with intact limbs. The accuracy achieved in classifying the seven types of hand and wrist movements further validates the effectiveness of the proposed approach. By offering a non-invasive and reliable means of recognizing upper limb movements, this research represents a significant step forward in biotechnical engineering for upper limb amputees. The findings hold considerable potential for enhancing the control and usability of prosthetic devices, ultimately contributing to the overall quality of life for individuals with upper limb amputations.

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Publication Date
Mon Jun 01 2020
Journal Name
Pjmhs Jun
Non-polio Enterovirus Isolation in children with acute Flaccid Paralysis in Iraq
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Aim This study is an overview of NPEV investigated during AFP surveillance programs for the period 2010–2017 in Iraq. Methods Stool samples from 4296 AFP cases and 2933 healthy contacts among children less than 15 years of age were processed for virus isolation as a part of AFP surveillance for the Global Polio Eradication Program in Iraq at National Polio Laboratory. NPEV detection was performed by virus isolation on cell culture according to WHO recommendations. Results The NPEV isolation rate was 14% of total AFP cases and 14.5% of healthy contacts. The infection rate was higher in males than females with a male/female ratio of 1.5: 1. The highest NPEV infection rate was observed among the children aged 1-2 years and decrease significa

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Scopus
Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Southwest Jiaotong University
Enhancing Privacy and Improving Security in Scalable Blockchain
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Bitcoin is a decentralized blockchain-based cryptocurrency that has taken the world by storm. Since its introduction in 2009, it has grown tremendously in terms of popularity and market cap. The idea of having a decentralized public ledger while maintaining anonymity and security attracted the attention of developers and customers alike. Special nodes in the bitcoin network, called miners, are responsible for making the network secure by using a concept called proof-of-work. A certain degree of anonymity is also maintained as no personally identifiable information of a person, like name, address, etc., is linked to the bitcoin wallet. In terms of bitcoin, a user is anonymous if different interactions of the user cannot be linked to

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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Improving Reverse Engineering Processes by using Articulated Arm Coordinate Measuring Machine
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The invention relates to a coordinate measuring machine (CMM) for determining a measuring position of a probe. The AACMM isdepends on the robotkinematics (forward and reverse) in their measurementprinciple, i.e., using the AACMM links and joint angles todetermine the exact workspace or part coordinates. Hence, themeasurements are obtained using an AACMM will be extremely accurate and precise since that ismerely dependent on rigid structural parameters and the only source of measurement error is due to human operators. In this paper, a new AACMM design was proposed. The new AACMM design addresses common issues such as solving the complex kinematics, overcoming the workspace limitation, avoiding singularity, and eliminating the effects of

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Publication Date
Sun Apr 22 2007
Journal Name
Al-anbar University Journal For Pure Sciences
Geochemical and paleontological study of Gulneri Formation (Upper Cretaceous) NE Iraq
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Publication Date
Sat Jun 30 2007
Journal Name
Al-kindy College Medical Journal
Iron Deficiency Anemia: The Utility of Upper Gastrointestinal Endoscopy and Histopathology
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Background: occult blood loss must be considered as a
possible cause in every case of iron deficiency anemia.
Objective: to evaluate upper gastrointestinal endoscopy
in finding a potential cause for iron deficiency anemia
among children in Al-Anbar governorate.
Methods: Twenty five children aged 2-14 years, referred
to the gastroenterology unit in Al-Ramadi General Hospital
for upper gastrointestinal endoscopy had iron deficiency
anemia. Fiberoptic endoscopy was used under general
anesthesia and endoscopic tissue biopsies were taken from
22 patients for histopathological examination.
Results: The main presenting signs and symptoms were
pallor, abdominal pain, and stunting. The upper
gastrointestinal

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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 Feb 24 2026
Journal Name
Baghdad Science Journal
EEG Lossless Signal Compression Based on Magnitude Classification and Run Length Encoding
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Publication Date
Sun Jul 06 2025
Journal Name
Jordan Medical Journal
Enhancing Adherence and Satisfaction with Disease-Modifying Therapies in Multiple Sclerosis Through Pharmacist-Led Interventions: Interventional Study
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Background: Pharmacists are essential in treating MS. Pharmacists' involvement and patient consultation may improve patient adherence and satisfaction. Aim: To evaluate the influence of pharmacist-led interventions (PLI) on medication adherence and satisfaction in patients with multiple sclerosis receiving disease-modifying therapies (DMTs). Methods: This study was conducted on patients with relapsing-remitting multiple sclerosis who were receiving DMTs and attended a neurological consultant clinic in the medical city of Baghdad. It was a pre-post-intervention study. Each patient underwent two educational sessions: the first session took place at the beginning of the study, after completing the Arabic version of the treatment satisfaction q

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Publication Date
Sun Dec 30 2012
Journal Name
Al-kindy College Medical Journal
Effect of Metformin Therapy on Reducing Leptin Resistance and Enhancing Ovulation in Women with Polycystic Ovary Syndrome
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Background: The relation between insulin resistance ,leptin levels and other hormones in women with polycystic ovary syndrome(PCOS) is still controversial.Metformin therapy is proved effective in reducing insulin resistance and also in some studies it was seen to be effective in reducing leptin levels.
Al- Kindy Col Med J 2012 ; Vol .8 No. (2) p: 65
Objective: to study the effect of metformin on reducing leptin levels and enhancing ovulation in PCOS women.
Methods:metformin 500mg 3 times daily for 3 months was was given to 36 women
with proved PCOS, in addition to that, other parameters were included.
Results:28 women out of 36(77.78%) showed an evidence of ovulation ovulation after 3 months of metformin therapy(p<0.01)

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