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 conducte

KE Sharquie, AA Noaimi, MR Al-Karhi, Journal of Cosmetics, Dermatological Sciences and Applications, 2014 - Cited by 2

    Conventional identification of three coccoid green algae isolates was attempted to characterize the studied algae morphologically under compound microscope, which demonstrated confusional phenomenal convergence; all were classified microscopically as the green alga Chlorella vulgaris Beijerinck, 1890.

    Phylogenetic studies were conducted to settle the argument about the phenotype by studying the genotype. Genotype the promising field in advance classification by using 18S rRNA and compared to GenBank database using to search the related sequences. The determined sequences showed high a similarity to the strains registered in GenBank.

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In the present work, steady two – dimensional laminar natural convection heat transfer of Newtonian and non-Newtonian fluids inside isosceles triangular enclosure has been analyzed numerically for a wide range of the modified Rayleigh numbers of (10³ ≤ Ra ≤ 10⁵), with non-dimensional parameter (NE) of Prandtl – Eyring model ranging from (0 to 10), and modified Prandtl number take in the range (Pr* =1,10, and 100). Two types of boundary conditions have been considered. The first, when the inclined walls are heated with different uniform temperatures and the lower wall is insulated. The second, when the bottom wall is heated by applying a uniform heat flux while the inclined walls at

The aerodynamic characteristics of general three-dimensional rectangular wings are considered using non-linear interaction between two-dimensional viscous-inviscid panel method and vortex ring method. The potential flow of a two-dimensional airfoil by the pioneering Hess & Smith method was used with viscous laminar, transition and turbulent boundary layer to solve flow about complex configuration of airfoils including stalling effect. Viterna method was used to extend the aerodynamic characteristics of the specified airfoil to high angles of attacks. A modified vortex ring method was used to find the circulation values along span wise direction of the wing and then interacted with sectional circulation obtained by Kutta-Joukowsky theorem of

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample