In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.  

The research is a contemporary stylistic study of the text that expresses the psychological
meanings in Nahj Al-Balaghah.
The research is divided to three chapters.
The first chapter : characteristics of psychological text.
It is about the power to influence the addressee ,that is to say ,the text influence power
connects with vulnerability and emotions inside the addressee spirit and his response to
violent effects shaking his feelings and that is represented in outbreaking of words vitality and
homogeneously. The Imam's wrath , grief , love to rightness , hatred of falsehood and
deviation from Islam arouses the words and emotions through :
1. Reduction in words and expansion in meaning by means of inspiration

In this paper, the concept of a hyper structure KU-algebra is introduced and some related properties are investigated. Also, some types of hyper KU-algebras are studied and the relationship between them is stated. Then a hyper KU-ideal of a hyper structure KU-algebra is studied and a few properties are obtained. Furthermore, the notion of a homomorphism is discussed.

A significant challenge arises in the characterization of urban systems, especially regarding the intricate structures of Central Business Districts (CBDs). Conventional models seem insufficient, failing to comprehend the non-linear, network-oriented structure of the city's economic and social dynamics. This creates a disparity between the city's physical, geographical structure and the unseen processes occurring within it. The fundamental inquiry is thus configurational: how can we systematically examine the inherent spatial logic of the CBD to develop a more efficient and predictive planning model? This paper presents a theoretical and methodological model to explore this inquiry, which focuses on Lower Manhattan as the primary su

This research attempts to investigate narrative structure in oral narrative particularly in Oprah's Show from a sociolinguistic viewpoint. Narrative is said to be universal in the sense that it is found in all times and places. There is no society or culture without narrative. Oral narrative is organized in a specific order. The research aims at studying and analyzing this order. In addition to that, it highlights the importance of narrative in conveying some moral messages to people who are listening to the story. The study is divided into two parts; theoretical and practical. The theoretical part draws on presenting a survey of literature which includes definitions and explanations of some related terms. The practical part is concerned

In this paper we present the first ever measured experimental electron momentum density of Cu2Sb at an intermediate resolution (0.6 a.u.) using 59.54 keV 241Am Compton spectrometer. The measurements are compared with the theoretical Compton profiles using density function theory (DFT) within a linear combination of an atomic orbitals (LCAO) method. In DFT calculation, Perdew-Burke-Ernzerhof (PBE) scheme is employed to treat correlation whereas exchange is included by following the Becke scheme. It is seen that various approximations within LCAO-DFT show relatively better agreement with the experimental Compton data. Ionic model calculations for a number of configurations (Cu+x/2)2(Sb-x) (0.0≤x≤2.0) are also performed utilizing free a

The ground state proton, neutron and matter densities, the corresponding rms radii and charge form factors of a dripline nuclei 6He, 11Li, 12Be and 14Be have been studied via a three–body model of (Core + n + n). The core–neutron interaction takes the form of Woods-Saxon (WS) potential. The two valence neutrons of 6He, 11Li and 12Be interact by the realistic interaction of ZBMII while those of 14Be interact via the realistic interaction of VPNP. The core and valence (halo) density distributions are described by the single-particle wave functions of the WS potential. The calculated results are discussed and compared with the experimental data. The long tail performance is clearly noticed in the calculated neutron and matter density distr

The study is devoted to both static and earthquake response analysis of retaining structures acted upon by lateral earth pressure. Two main approaches were implemented in the analysis, namely, the Mononobe-Okabe analytical method and the numerical Finite element procedure as provided in the ready software ABAQUS with explicit dynamic method. A basic case study considered in the present work is the bridge approach retaining walls as a part of AL-Jadiriya bridge intersection to obtain the effects of the backfill and the ground water on the retaining wall response including displacement of the retaining structure in addition to the behavior of the fill material. Parametric studies were carried out to evaluate the effects of several factors

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T