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Recognition of Upper Limb Movements Based on Hybrid EEG and EMG Signals for Human-Robot Interaction
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Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that using mean absolute value (MAV), waveform length (WL), Wilson Amplitude (WAMP), Sine Slope Changes (SSC), and Cardinality features of the proposed algorithm achieves a classification accuracy of 89.6% when classifying seven distinct types of hand and wrist movement. Index Terms— Human Robot Interaction, Bio-signals Analysis, LDA classifier.

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Study of Spectroscopy and Thermodynamic Properties for Phoshours dioxide PO2 Molecular and Influence Study of Bond ( P-O ) on Spectroscopy Properties
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In This research a Spectroscopic complement and Thermodynamic properties for molecule PO2 were studied . That included a calculation of potential energy . From the curve of total energy for molecule at equilibrium distance , for bond (P-O), the degenerated of bond energy was (4.332eV) instate of the vibration modes of ( PO2 ) molecule and frequency that was found active in IR spectra because variable inpolarization and dipole moment for molecule. Also we calculate some thermodynamic parameters of ( PO2 ) such as heat of formation , enthalpy , heat Of capacity , entropy and gibb's free energy Were ( -54.16 kcal/mol , 2366.45 kcal/mol , 10.06 kcal /k/mol , 59.52 k

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Publication Date
Thu Dec 01 2022
Journal Name
Case Studies In Construction Materials
Push-out test of waste sawdust-based steel-concrete – Steel composite sections: Experimental and environmental study
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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Enhancement in Lubricating, Rheological, and Filtration Properties of Unweighted Water-Based Mud Using XC Polymer NPs
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In this research, an enhancement in lubricating, rheological, and filtration properties of unweighted water-based mud is fundamentally investigated using XC polymer NPs with 0.2gm, 0.5gm, 1gm, 2gm, and 4gm concentrations. Bentonite, that had been used in the preparation of unweighted water-based mud, was characterized using XRF-1800 Sequential X-ray Fluorescence Spectrometer, XRD-6100/7000 X-ray Diffractometer, and Malvern Mastersizer 2000 particle size analyzer, respectively. Lubricating, rheology and filtration properties of unweighted water-based mud were measured at room temperature (35°C) using OFITE EP and Lubricity Tester, OFITE Model 900 Viscometer, and OFITE Low-Pressure Filter Press, respectively. XC Polymer N

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Publication Date
Thu Dec 01 2022
Journal Name
Case Studies In Construction Materials
Push-out test of waste sawdust-based steel-concrete – Steel composite sections: Experimental and environmental study
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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Water Process Engineering
Immobilization of cobalt ions using hierarchically porous 4A zeolite-based carbon composites: Ion-exchange and solidification
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Publication Date
Mon Jan 01 2024
Journal Name
Optical Materials
Design and analysis of a high sensitivity open microchannel PCF-based surface plasmon resonance refractometric sensor
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Publication Date
Fri Oct 17 2025
Journal Name
Ieee Access
Optic Flow-Based Gait Symmetry Assessment of Center and Peak Pressure Trajectories Applied to Foot Deformities
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Analyzing plantar pressure trajectories is crucial for assessing foot behavior in dynamic gait stability. We propose the identification of foot symmetry and the detection of deformities by analyzing the trajectories of the center of pressure (CoP) and peak pressure (PP). First, using a foot pressure mapping system, plantar pressure data are acquired during a normal gait cycle. After the data have been acquired, post processing extracts both the CoP and PP trajectories over the spatiotemporal domain of foot motion for each foot independently. For this purpose, we used the optical flow technique which accurately estimates the direction of foot motion. The extracted trajectories of each foot are then segmented into, the medial and lateral regi

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economic And Administrative Science
On Shrinkage Estimation for Generalized Exponential Distribution
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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Adsorption Study for Trifluralin on Iraqi ? –Alumina
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Equilibrium adsorption isotherm for the removal of trifluralin from aqueous solutions using ? –alumina clay has been studied. The result shows that the isotherms were S3 according Giels classification. The effects of various experimental parameters such as contact time, adsorbent dosage, effect of pH and temperature of trifluralin on the adsorption capacities have been investigated. The adsorption isotherms were obtained by obeying freundlich adsorption isotherm with (R2 = 0.91249-0.8149). The thermodynamic parameters have been calculated by using the adsorption process at five different temperature, the values of ?H, ?G and ?S were (_1.0625) kj. mol-1, (7.628 - 7.831) kj.mol-1 and (_2.7966 - _2.9162) kg.

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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