This paper aims to evaluate the reliability analysis for steel beam which represented by the probability of Failure and reliability index. Monte Carlo Simulation Method (MCSM) and First Order Reliability Method (FORM) will be used to achieve this issue. These methods need two samples for each behavior that want to study; the first sample for resistance (carrying capacity R), and second for load effect (Q) which are parameters for a limit state function. Monte Carlo method has been adopted to generate these samples dependent on the randomness and uncertainties in variables. The variables that consider are beam cross-section dimensions, material property, beam length, yield stress, and applied loads. Matlab software has be

          The aim of the present study is to formulate, evaluate and characterize the nanoemulsion of Domperidone a poorly water-soluble anti-emetic drug.

           Domperidone powder is white or almost white powder, photosensitive, practically insoluble in water, slightly soluble in ethanol and in methanol; soluble in dimethylformamide. It is used as an antiemetic for the short-term treatment of nausea and vomiting of various etiologies.

           Solubility studies were conducted to select the oil, surfactant and cosurfactant. Phase diagrams were constructed by aqueous phase

Objective: To examined the common frequency of cervical cancer in Iraqi women. Study Design: Descriptive study Place and Duration of Study: This study was conducted at the Iraqi Cancer Agency and the Cancer Registry data from the Iraqi Ministry of Health provided assistance in data gathering from 1st April 2020 to 31st December 2021. Methods: The study examined 504 women diagnosed with cervical cancer. Their ages ranged from 20 to over 80 years. The data analysis employed descriptive statistics to determine the frequency, proportion, and incidence of cervical cancer. Results: The cervical cancer was predominantly caused by human papillomavirus in women in 2020 (1.29%) and 2021 (2.1%). In 2020, the number of cases of cervical can

Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa

The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival

This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.