In this paper, some estimators of the unknown shape parameter and reliability function  of Basic Gompertz distribution (BGD) have been obtained, such as MLE, UMVUE, and MINMSE, in addition to estimating Bayesian estimators under Scale invariant squared error loss function assuming informative prior represented by Gamma distribution and non-informative prior by using Jefferys prior. Using Monte Carlo simulation method, these estimators of the shape parameter and R(t), have been compared based on mean squared errors and integrated mean squared, respectively

Hypertension is one of the leading causes of the global burden of disease, which causes serious health problems. The aim of this study is to investigate the lipid profile levels in sera of Iraqi hypertensive patients by measuring Total cholesterol (TC), triglyceride (TG) and low density lipoproteins (LDL) and kidney function levels by measuring uric acid, urea and creatinine. Seventy five individuals of Iraqi adults (Males) were divided into three groups: 25 hypertensive patients with duration of disease (1-10) year (group 1), 25 hypertensive patients with duration of disease (11-30) year (group 2) and 25 normal individuals as control group (group3). The findings indicate that serum (TC, TG and LDL) levels were significantly elevated (

Achieving reliable operation under the influence of deep-submicrometer noise sources including crosstalk noise at low voltage operation is a major challenge for network on chip links. In this paper, we propose a coding scheme that simultaneously addresses crosstalk effects on signal delay and detects up to seven random errors through wire duplication and simple parity checks calculated over the rows and columns of the two-dimensional data. This high error detection capability enables the reduction of operating voltage on the wire leading to energy saving. The results show that the proposed scheme reduces the energy consumption up to 53% as compared to other schemes at iso-reliability performance despite the increase in the overhead number o

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem

In today's world the role of leadership in the control factors of the organization different and advancement, and that the possession of the human ability to the development and creation and innovation varies from one individual to another depending on experience; and levels of performance and intellectual; and his mental and physical and other such factors can create a kind of differentiation between the built humans, and this distinction creates our leaders are able to influence others and have the wisdom and connect active individuals and organizations. as the need for organizations of all sizes and levels of leadership transformation is an urgent need to link the application of the various plans and strategies device which direction

In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

Background: The ideal force-delivery system must: provide optimal tooth moving forces that elicit the desired effects, be comfortable and hygienic for the patient, require minimal operator manipulation and patient cooperation and provide rapid tooth movement with minimal mobility during orthodontic therapy, the elastomeric chains have the greatest potential to fulfill these requirements. Materials and Methods: This in vitro study was designed to determine the effect of three different mechanisms for canine retraction : (6-3 , 6-5-3 and chain loop ) on the load relaxation behavior of three types of elastomeric chains : (maximum clear , maximum silver and extreme silver) from the same company (Ortho Technology company) with two different bran