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

Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete

A preventing shield for neutrons and gamma rays was designed using alternate layers of water and iron with pre-fixed dimensions in order to study the possibility of attenuating both neutrons and gamma-rays. ANISN CODE was prepared and adapted for the shield calculation using radiation doses calculation: Two groups of cross-section were used for each of neutrons and gamma-rays that rely on the one – dimensional transport equation using discrete ordinate's method, and through transforming cross-section values to values that are independent on the number of groups. The memory size required for the applied code was reduced and the results obtained were in agreement with those of standard acceptable document samples of cross –section, this a

For this research, the utilisation of electrocoagulation (EC) toremove theciprofloxacin (CIP) and levofloxacin (LVX) from aqueous solutions was examined. The effective removal efficiencies are 93.47% for CIP and 88.00% for LVX, under optimum conditions. The adsorption isotherm models with suitable mechanisms were applied to determine the elimination of CIP and LVX utilizingtheEC method. Thefindingsshowed the adsorption of CIP and LVX on iron hydroxide flocs followed the Sips isotherm, with correlation coefficient values (R2) of 0.939 and 0.937. Threekinetic models were reviewed to determine the accurate CIP and LVX elimination methods using the EC method. The results showed that itfittedfor the second-order model, which indicated that the c

The influence of pre- shot peening and welding parameters on mechanical and metallurgical properties of dissimilar and similar aluminum alloys AA2024-T3 and AA6061-T6 joints using friction stir welding have been studied. In this work, numbers of plates were equipped from sheet alloys in dimensions (150*50*6) mm then some of them were exposed to shot peening process before friction stir welding using steel ball having diameter 1.25 mm for period of 15 minutes. FSW joints were manufactured from plates at three welding speeds (28, 40, 56 mm/min) and welding speed 40mm/min was chosen at a rotating speed of 1400 rpm for welding the dissimilar pre- shot plates. Tow joints were made at rotational speed of 1000 rpm and welding speed of 40m/min f

For this research, the utilisation of electrocoagulation (EC) toremove theciprofloxacin (CIP) and levofloxacin (LVX) from aqueous solutions was examined. The effective removal efficiencies are 93.47% for CIP and 88.00% for LVX, under optimum conditions. The adsorption isotherm models with suitable mechanisms were applied to determine the elimination of CIP and LVX utilizingtheEC method. Thefindingsshowed the adsorption of CIP and LVX on iron hydroxide flocs followed the Sips isotherm, with correlation coefficient values (R2) of 0.939 and 0.937. Threekinetic models were reviewed to determine the accurate CIP and LVX elimination methods using the EC method. The results showed that itfittedfor the second-order model, which indicated that the c

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

This work was carried to study the capability of activated alumina from bauxite compared with activated carbon adsorption capability to reduce the color content from Al-Hilla Textile Company wastewater. Six dyes were studied from two types(reactive and dispersed) namely (blue, red, yellow) from wastewater and aqueous solutions.
Forty eight experiments were carried out to study the effect of various initial conditions (bed height, flow rate, initial concentration, pH value, temperature, and competitive adsorption) on adsorption process.
The results showed that the adsorption process using activated carbon insured a good degree of color reduction reaching (99.7%) and was better than activated bauxite which reached (95%).

Bismuth oxide nanoparticle Bi2O3NPs has a wide range of applications and less adverse effects than conventional radio sensitizers. In this work, Bi2O3NPs (D1, D2) were successfully synthesized by using the biosynthesis method with varying bismuth salts, bismuth sulfate Bi2(SO4)3 (D1) or bismuth nitrate. Penta hydrate Bi(NO3)3.5H2O (D2) with NaOH with beta-vulgaris extract. The Bi2O3NPs properties were characterized by different spectroscopic methods to determine Bi2O3NPs structure, nature of bonds, size of nanoparticle, element phase, presence, crystallinity and morphology. The existence of the Bi2O3 band was verified by the FT-IR. The Bi2O3 NPs revealed an absorption peak in the UV-visible spectrum, with energy gap Eg = 3.80eV. The X-ray p