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

Background: Breast lump is one of the most common prevalent complaint of patients attending breast clinics.

Objective: To determine if there is any change in the pattern of common breast, diseases presenting as breast lumps between pregnant and non-pregnant women among patients attending Al-Elwiya Breast Clinic.

Methods: This is a cross – sectional study, with convent's patient sampling setting in AL-Elwiya Breast Cancer Early Detection Clinic from 1^st Feb. to 1^st May 2018, we collected data from patients with breast lumps including the age groups, pregnancy status, parity status, previous breast diseases, hormonal drugs, menstrual cycle, breast fe

The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.

Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.

The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.

In the analysis of d

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

In this research weights, which are used, are estimated using General Least Square Estimation to estimate simple linear regression parameters when the depended variable, which is used, consists of two classes attributes variable (for Heteroscedastic problem) depending on Sequential Bayesian Approach instead of the Classical approach used before, Bayes approach provides the mechanism of tackling observations one by one in a sequential way, i .e each new observation will add a new piece of information for estimating the parameter of probability estimation of certain phenomenon of Bernoulli trials who research the depended variable in simple regression  linear equation. in addition to the information deduced from the past exper

This study was done to test the activity of some plant extracts as antioxidant agents. The plants were (Morus rubra, Hibiscus sabdariffa L ., Rhus coriaria L., Anethum graveolens and Petroselinum sativum).
Ethanolic 98% (24 hours/ 25˚c) and distilled water (30 minutes/ 25˚c have been used for extraction.The Total phenols, total flavonoids, total anthocyanin, antioxidant activities were studied.
The extract of Morus rubra was chosen because it has a higher antioxidant activity.
The phenolic extract of Morus rubra was prepare and examined by application it in burger . The antioxidant activity test of Morus rubra was made before and after 3,6 days of cold storage. The sensory evaluation of all treatments were done within 5,1

This study investigates asset returns within the Iraq Stock Exchange by employing both the Fama-MacBeth regression model and the Fama-French three-factor model. The research involves the estimation of cross-sectional regressions wherein model parameters are subject to temporal variation, and the independent variables function as proxies. The dataset comprises information from the first quarter of 2010 to the first quarter of 2024, encompassing 22 publicly listed companies across six industrial sectors. The study explores methodological advancements through the application of the Single Index Model (SIM) and Kernel Weighted Regression (KWR) in both time series and cross-sectional analyses. The SIM outperformed the K

Dapagliflozin is a novel sodium-glucose cotransporter type 2 inhibitor. This work aims to develop a new
validated sensitive RP-HPLC coupled with a mass detector method for the determination of dapagliflozin, its
alpha isomer, and starting material in the presence of dapagliflozin major degradation products and an internal
standard (empagliflozin). The separation was achieved on BDS Hypersil column (length of 250mm, internal
diameter of 4.6 mm and 5-μm particle size) at a temperature of 35℃. Water and acetonitrile were used as
mobile phase A and B by gradient mode at a flow rate of 1 mL/min. A wavelength of 224nm was selected to
perform detection using a photo diode array detector. The method met the

This paper describes a number of new interleaving strategies based on the golden section. The new interleavers are called golden relative prime interleavers, golden interleavers, and dithered golden interleavers. The latter two approaches involve sorting a real-valued vector derived from the golden section. Random and so-called “spread” interleavers are also considered. Turbo-code performance results are presented and compared for the various interleaving strategies. Of the interleavers considered, the dithered golden interleaver typically provides the best performance, especially for low code rates and large block sizes. The golden relative prime interleaver is shown to work surprisingly well for high puncture rates. These interleav

Czerwi’nski et al. introduced Lucky labeling in 2009 and Akbari et al and A.Nellai Murugan et al studied it further. Czerwi’nski defined Lucky Number of graph as follows: A labeling of vertices of a graph G is called a Lucky labeling if  for every pair of adjacent vertices u and v in G where . A graph G may admit any number of lucky labelings. The least integer k for which a graph G has a lucky labeling from the set 1, 2, k is the lucky number of G denoted by η(G). This paper aims to determine the lucky number of Complete graph K_n, Complete bipartite graph K_m,n and Complete tripartite graph K_l,m,n. It has also been studied how the lucky number changes whi