This paper deals  with constructing mixed probability distribution  from exponential with scale parameter (β) and also Gamma distribution with (2,β), and the mixed proportions are (  .first of all, the probability density function (p.d.f) and also cumulative distribution function (c.d.f) and also the reliability function are obtained. The parameters of mixed distribution, ( ,β)  are estimated by three different methods, which are  maximum likelihood, and  Moments method,as well proposed method (Differential Least Square Method)(DLSM).The comparison is done using simulation procedure, and all the results are explained in tables.

Recording an Electromyogram (EMG) signal is essential for diagnostic procedures like muscle health assessment and motor neurons control. The EMG signals have been used as a source of control for powered prosthetics to support people to accomplish their activities of daily living (ADLs). This work deals with studying different types of hand grips and finding their relationship with EMG activity. Five subjects carried out four functional movements (fine pinch, tripod grip and grip with the middle and thumb finger, as well as the power grip). Hand dynamometer has been used to record the EMG activity from three muscles namely; Flexor Carpi Radialis (FCR), Flexor Digitorum Superficialis (FDS), and Abductor Pollicis Brevis (ABP) with different

The main purpose of this investigation is to evaluate the concentrations of six essential metals (Na⁺, Mg²⁺, K⁺, Ca²⁺, Fe²⁺ and Zn²⁺) in saffron and a farm soil using the neutron activation analysis (NAA) as a nuclear spectrometry method. The stratified random sampling method was used here. The NAA results showed the well uptake of Mg²⁺, K⁺, Ca²⁺, Fe²⁺, and Zn²⁺ in saffron, which is lower than the toxicity range. Based on the contamination factor and geoaccumulation index, soil contamination levels were determined uncontaminated by Zn, moderately contaminated by Na⁺ and Fe²⁺, and strongly contamin

Ovako Working Postures Analyzing System (OWAS) is a widely used method for studying awkward working postures in workplaces. This study with OWAS, analyzed working postures for manual material handling of laminations at stacking workstation for water pump assembly line in Electrical Industrial Company (EICO) / Baghdad. A computer program, WinOWAS, was used for the study. In real life workstation was found that more than 26% of the working postures observed were classified as either AC2 (slightly harmful), AC3 (distinctly harmful). Postures that needed to be corrected soon (AC3) and corresponding tasks, were identified. The most stressful tasks observed were grasping, handling, and positioning of the laminations from workers. The construct

Abstract

The removal of water turbidity by using crumb rubber filter was investigated .The present study was conducted to evaluate the effect of variation of influent water turbidity (10, 25 and 50 NTU), media size (0.6and 1.14mm), filtration rate (25, 45 and 65 l/hr) and bed depth (30 and 60 cm) on the performance of mono crumb rubber filter in response to the effluent filtered water turbidity and head loss development, and compare it with that of conventional sand filter.Results revealed that 25 l/hr flow rate and 25 NTU influent turbidity were the best operating conditions.  smaller media size and higher bed depth gave the best removal efficiency while higher media size and small bed depth gave lower head

The 3-parameter Weibull distribution is used as a model for failure since this distribution is proper when the failure rate somewhat high in starting operation and these rates will be decreased with increasing time .

In practical side a comparison was made between (Shrinkage and Maximum likelihood) Estimators for parameter and reliability function using simulation , we conclude that the Shrinkage estimators for parameters are better than maximum likelihood estimators but the maximum likelihood estimator for reliability function is the better using statistical measures (MAPE)and (MSE) and for different sample sizes.

Note:- n_s : small sample ; n_m=median sample

     The research aims to analyze the impact of exchange rate fluctuations (EXM and EXN) and inflation (INF) on the gross domestic product (GDP) in Iraq for the period 1988-2020. The research is important by analyzing the magnitude of the macroeconomic and especially GDP effects of these variables, as well as the economic effects of exchange rates on economic activity. The results of the standard analysis using the ARDL model showed a long-term equilibrium relationship, according to the Bound Test methodology, from explanatory (independent) variables to the internal (dependent) variable, while the value of the error correction vector factor was negative and moral at a level less than (1%). The relationship bet

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c