A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

Objective: The present study aims to assess the stressful life events for patients with substance abuse in Baghdad city.
Methodology: A descriptive study was carried out at (Baghdad teaching hospital and Ibn-Rushed Psychiatric hospital).
Starting from 1
st of December 2012 to 3
rd of July 2013, A non-probability (purposive) sample of 64 patients that
diagnosed with substance abuse, the data were collected through the use of semi-structured interview by
questionnaire, which consists of three parts sociodemographic data, medical information, and Life events scale
consists of 49-items distributed to six domains including, family and social domain, health domain, security, legal and
criminal domain, work and school do

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

The objective of this research is to know the economic feasibility of hydroponics technology by estimating the expected demand for green forage for the years 2021-2031 as well as Identify and analyze project data and information in a way that helps the investor make the appropriate investment decision in addition to preparing a detailed technical preliminary study for the cultivar barley project focusing on the commercial and financing aspects and the criteria that take into account the risks and uncertainties . that indicating the economic feasibility of the project to produce green forage using hydroponics technology. Cultured barley as a product falls within the blue ocean strategy. Accordingly, the research recommends the necess

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Objectives: To determine the (QoL) for patients with permanent pacemaker and to find-out the relationship between
these patients’ (QoL) and their sociodemographic characteristics such as age, gender, level of education, and
occupation.
Methodology: ٨ purposive non-probability” sample of (62) patient with permanent pacemaker was involved in this
study. The developed questionnaire consists of (4) parts which include !.demographic data form, 2.disease-related
information form, 3.socioeconomic data form, and 4.Permanent pacemaker patient’s quality of life questionnaire data
form. The validity and reliability of the questionnaire were determined through the application of a pilot study. ٨
descriptive statistical a

The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E