The city suffers from the weakness of the civil defense to provide services where there are clusters of residential Guy covered services for that requires the study of the geographic distribution of the civil defense centers in Baghdad care great because they take care of Protect the population and their own property and protect state institutions. Through a review of the problems faced it is expected that this study will help decision-makers to take appropriate steps to develop this service core

Abstract

Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance.  This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H₂/H_∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS).  Simulatio

The ground state proton, neutron and matter densities of exotic ¹¹Be and ¹⁵C nuclei are studied by means of the TFSM and BCM. In TFSM, the calculations are based on using different model spaces for the core and the valence (halo) neutron. Besides single particle harmonic oscillator wave functions are employed with two different size parameters  B_c and B_v.  In BCM, the halo nucleus is considered as a composite projectile consisting of core and valence clusters bounded in a state of relative motion. The internal densities of the clusters are described by single particle Gaussian wave functions.

 Elastic electron scattering proton f

A new distribution, the Epsilon Skew Gamma (ESΓ ) distribution, which was first introduced by Abdulah [1], is used on a near Gamma data. We first redefine the ESΓ distribution, its properties, and characteristics, and then we estimate its parameters using the maximum likelihood and moment estimators. We finally use these estimators to fit the data with the ESΓ distribution

A land magnetic survey was carried out along regional profile, which is located at the north part of the Iraqi western desert. It starts from al –Qaam City (at north) toward Rutba City (at south) with a total length of 238km. The survey was carried out along the paved road between the two cities, About 113 measuring points were done with inter-station distance of 2 km (for 198 km) and 2 to 5km (for 40km). Two proton magnetometers were used in this survey. One of them is used for base station monitoring, which was fixed as of Salah Aldin field (Akkas). Its readings were used for diurnal corrections. All magnetic measurements were corrected for normal and topographic corrections. The readings were reduced to a certain base level. The resu

The recent development in statistics has made statistical distributions the focus of researchers in the process of compensating for some distribution parameters with fixed values and obtaining a new distribution, in this study, the distribution of Kumaraswamy was studied from the constant distributions of the two parameters. The characteristics of the distribution were discussed through the presentation of the probability density function (p.d.f), the cumulative distribution function (c.d.f.), the ratio of r, the reliability function and the hazard function. The parameters of the Kumaraswamy distribution were estimated using MLE, ME, LSEE by using the simulation method for different sampling sizes and using preli

In this paper a new idea was introduced which is finding a new distribution from other distributions using mixing parameters; w_i  where  0 < w_i < 1 ­and . Therefore we can get many mixture distributions with a number of parameters. In this paper I introduced the idea of a mixture Weibull distribution which is produced from mixing two Weibull distributions; the first with two parameters, the scale parameter , and the shape parameter,  and the second also has the scale parameter , and the shape parameter,  in addition to the location parameter, . These two distributions were mixed using a new parameter which is the mixing parameter w which represents the proportion