The acceptance sampling plans for generalized exponential distribution, when life time experiment is truncated at a pre-determined time are provided in this article. The two parameters (α, λ), (Scale parameters and Shape parameters) are estimated by LSE, WLSE and the Best Estimator’s for various samples sizes are used to find the ratio of true mean time to a pre-determined, and are used to find the smallest possible sample size required to ensure the producer’s risks, with a pre-fixed probability (1 - P^*). The result of estimations and of sampling plans is provided in tables.

Key words: Generalized Exponential Distribution, Acceptance Sampling Plan, and Consumer’s and Producer Risks

This study deals with formation models of gypsum barrier, chemical temporal changes, and assessments of the Sawa Lake within the Al- Muthanna province, Southern Iraq, it is a very important issue to find the water quality and water assessments of this lake. Eleven water samples are collected from Sawa Lake. Many scientific concepts are used such as major cations (Ca2+, Mg2+, Na+ and K+), major anions (SO4=,Cl-,HCO3- and CO3=) with minor anions ( PO43-, NO3-) and H2S . Trace elements (Pb, Cd, Zn, As, Ni, Co, Cu, Mn, Fe, As, Sr And B) and bacterial test were analyzed in each sample. Total dissolved solids (TDS), electrical conductivity (EC), pH and temperature (T) were directly measured in the field. The equilibrium state between the conce

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

        In this research, an investigation for the compatibility of the IRI-2016 and ASAPS international models was conducted to evaluate their accuracy in predicting the ionospheric critical frequency parameter (f_oF2) for the years 2009 and 2014 that represent the minimum and maximum years of solar cycle 24. The calculations of the monthly average f_oF2 values were performed for three different selected stations distributed over the mid-latitude region. These stations are Athens - Greece (23.7^o E, 37.9 ^o N), El Arenosillo - Spain (-6.78 ^o E, 37.09 ^o N), and Je Ju - South Korea (124.53 ^o E, 33.6 ^o N). The calculated v

The present work aimed to make a comparative investigation between three different ionospheric models: IRI-2020, ASAPS and VOACAP. The purpose of the comparative study is to investigate the compatibility of predicting the Maximum Usable Frequency parameter (MUF) over mid-latitude region during the severe geomagnetic storm on 17 March 2015. Three stations distributed in the mid-latitudes were selected for study; these are (Athens (23.50o E, 38.00o N), Jeju (124.53o E, 33.6o N) and Pt. Arguello (239.50o W, 34.80o N). The daily MUF outcomes were calculated using the tested models for the three adopted sites, for a span of five-day (the day of the event and two days preceding and following the event day). The calculated datasets were co