Beta Distribution

Abstract

             Gamma and Beta Distributions has very important in practice in various areas of statistical and applications reliability and quality control of production. and There are a number of methods to generate data behave on according to these distribution. and These methods bassic primarily on the shape parameters of each distribution and the relationship between these distributions and their relationship with some other probability distributions.    &nb

n this work, the effect of gamma rays on blood thinning drugs was studied using the drug (Aspirin), where gamma rays were spread with the drug using a radioactive source (Co60), and 15,000 grams of Aspirin were placed in the device (gamma chamber 900). The drug was subjected to different irradiation doses (5 KGy, 10 KGy, 15 KGy) and the amount of absorption of the drug was observed in the gamma for different doses and the study of x-rays. After confirming the absorption of the drug to radiation, the effect of the drug on blood thinning was calculated using the rat model and compared with the same drug and the same dose but without exposing the drug to radiation and comparing all results with the control group. The way drugs absorbed radiati

The Local manufacturing scanning gamma system designed in Tuwaitha site for nondestructive assay method of radioactive waste drums, where it consist of two main parts with their belongings for controlling the of detector and drum movements up-down and rotation respectively. The volume of the used drum is 220 L with 85 cm height. The drum filled with Portland cement. Six cylindrical holes were made within cement drum and distributed in radial arrangement.The152Eu source inserted in these holes individually, to measure the average angular count rate of gamma radiation. The full energy efficiency value for geometry of drum and detector is computed for thirteen photo peaks. The average efficiency represented by the curve of these peaks indic

<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

Nano gamma alumina was prepared by double hydrolysis process using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, hydroxyle poly acid and CTAB (cetyltrimethylammonium bromide) as templates. Different crystallization temperatures (120, 140, 160, and 180) ⁰C and calcinations temperatures (500, 550, 600, and 650) ⁰C were applied. All the batches were prepared at PH equals to 9. XRD diffraction technique and infrared Fourier transform spectroscopy were used to investigate the phase formation and the optical properties of the nano gamma alumina. N₂ adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the particle size and the

The purpose of the current work was to evaluate the effect of Radiation of Gamma on the superconducting characteristics of the compound PbBr2Ca1.9Sb0.1Cu3O8+δ utilizing a 137Cs source at doses of 10, 15, and 20MRad. Solid state reaction technology was used to prepare the samples. Before and after irradiation, X-ray diffraction (XRD) and superconductor properties were examined. Results indicated that the tetragonal structure of our chemical corresponds to the Pb-1223 phase with an increase in the ratio c/a as a result of gamma irradiation. (Tc (onset) ) and on set temperature Tc (offset)) were also dropping from 113 to the 85.6 K and 129.5 to 97 K, respectively, for a transition temperatu

An investigation was conducted for the determination of the effects of the forming conditions in the production of Gamma Alumina catalyst support on the crushing strength property. Eight variables were studied , they are ;binder content which is the sodium silicate , Solvent content which is the water, speed of mixing , time of mixing, drying temperature , drying time , calcinations temperature and the calcinations time
Design of the experiments was made by using the response Surface method in Minitab 15 software which supply us 90 experiments .
The results of this investigation show that the crushing strength for the dried Gamma alumina extrudate was affected by the drying temperature and the drying time only and there is no inter

In this research a study process to calculate the factor accumulation of gamma rays for aluminum and exporters cobalt 60 Mika Atktron volts and actively radiation Vdrh 1.406 Mika Bq been studying the effect of the angle of reimbursement and the distance between the shield and detector In measurements factor accumulation Adhrt results in line with the theoretical results published