This paper discusses estimating the two scale parameters of Exponential-Rayleigh distribution for singly type one censored data which is one of the most important Rights censored data, using the maximum likelihood estimation method (MLEM) which is one of the most popular and widely used classic methods, based on an iterative procedure such as the Newton-Raphson to find estimated values for these two scale parameters by using real data for COVID-19 was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. The duration of the study was in the interval 4/5/2020 until 31/8/2020 equivalent to 120 days, where the number of patients who entered the (study) hospital with sample size is (n=785). The number of patients who died during the period of study was (m=88). And the number of patients who survived during the study period was (n-m=697), then utilized one of the most important non-parametric tests which is the Chi-square test to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). then, after estimating the parameters of ER distribution for singly type-I censoring data, compute the survival function, hazard function, and probability density function.
The Catharanthus roseus plant was extracted and converted to nanoparticles in this work. The Soxhlet method extracted alkaloid compounds from the plant Catharanthus roseus and converted them to the nanoscale. Chitosan polymer was used as a linking material and converted to Chitosan nanoparticles using Sodium TriPolyPhosphate (STPP). The extracted alkaloids were linked with Chitosan nanoparticles CSNPs by maleic anhydride to get the final product (CSNPs- Linker- alkaloids). The synthesized (CSNPs- Linker- alkaloids) was characterized using SEM spectroscopy UV–Vis., Zeta Potential, and HPLC High-Performance Liquid Chromatography. Scanning electron microscope (SEM) analysis shows that the Chitosan nanoparticles (CSNPs) have small dim
... Show MoreThis study investigated the bioethanol production from green algae Chlorella vulgaris depending on its carbohydrate-enriched biomass. Four different phosphorous concentrations were employed to stimulate bioethanol production from Chlorella vulgaris. The impact of various phosphorous values on Chlorella vulgaris growth rate as well as primary product (carbohydrate) were evaluated. High performance liquid chromatography was utilized in this work. The stationary phase was identified as day 14, 12, 10 and 6 in treatments 6, 4, 2 and g/L, respectively. The findings suggest that the treatment without phosphorous addition had the highest record of carbohydrate content (22.64% dry weight) as well as the highest bioethanol yield (20.66% dry weight).
... Show MoreMass customization under the internet of things
This research aims to identify the level of extension administration performance under comprehensive quality standards from the perspective of the working staff in agricultural extension at the level of the general extension body and agricultural directorates and agricultural division.this was to identify the extension administration performance under comprehensive quality standards from the perspective of vegetables growers , random sample was selected from the central region governorates Baghdad , Diyala , Babel , karbala and Al-Najaf , a random sample from the workers in the general body numbered 56 employee , sample of staff working in agricultural extension was selected at the level of agricultural directorates in proportion
... Show MoreThe goal of this study was to investigate the protein peroxidation role by measuring serum levels of advanced oxidation protein products (AOPP) in type 2 diabetic patients with or without retinopathy and comparing them to controls to see if circulating AOPP levels can be used as a detection biomarker for DR. And see which of the two widely used antidiabetic treatment groups had the most impact on this oxidative stress marker. The groups were divided into two subgroups: 1) 70 type 2 diabetic patients (36 male, 34 female), 35 with diabetic retinopathy (DR) and 35 with no evidence of DR, and 2) non-diabetic controls (11 male, 9 female) were chosen from Ibn AL-Haitham Hospital for Ophthalmology and a Specialized Center for Endocrinology and Dia
... Show MoreThis Paper aims to plan the production of the electrical distribution converter (400 KV/11) for one month at Diyala Public Company and with more than one goal for the decision-maker in a fuzzy environment. The fuzzy demand was forecasting using the fuzzy time series model. The fuzzy lead time for raw materials involved in the production of the electrical distribution converter (400 KV/11) was addressed using the fuzzy inference matrix through the application of the matrix in Matlab, and since the decision-maker has more than one goal, so a mathematical model of goal programming was create, which aims to achieve two goals, the first is to reduce the total production costs of the electrical distribution converter (400 KV/11) and th
... Show MoreA 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 others
... Show MoreUse of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)
In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation) structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of these procedures and compare them using generated data.