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DYNAMIC MODELING OF TIME-VARYING ESTIMATION FOR DISCRETE SURVIVAL ANALYSIS FOR DIALYSIS PATIENTS IN BASRAH, IRAQ
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Survival analysis is widely applied to data that described by the length of time until the occurrence of an event under interest such as death or other important events. The purpose of this paper is to use the dynamic methodology which provides a flexible method, especially in the analysis of discrete survival time, to estimate the effect of covariate variables through time in the survival analysis on dialysis patients with kidney failure until death occurs. Where the estimations process is completely based on the Bayes approach by using two estimation methods: the maximum A Posterior (MAP) involved with Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation Maximization (EM) algorithm. While the other method was represented by the Hybrid Markov Chain Monte Carlo method (HMCMC). Moreover, two hazard function models were considered in the comparison: the Logistic model and the discrete Cox model. Two criteria were used for comparisons Average Mean Square Error: AMSE and Cross Entropy Error: CEE. All these four combinations of methods were clarified via the discussion of the numerical results with their explanations. It can be noticed the superiority of HMCMC method through the two hazard models.

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
The spatial analysis for Greenhouses in province Baghdad
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Greenhouses are provide that produce of vegetable in non times seasons production by controlling the various environmental factors that appropriate atmosphere in temperature and humidity for the growth of plants in the plastic houses and owner plastic.
The objective of this research is to study of the most important natural and human factors affecting the Greenhouses in the province of Baghdad and study geographic distribution for the Greenhouses in the province.
Some properties on curriculum geographical descriptive analytical that used in describe and analysis of data and information that could be available from Directorate of agriculture in Baghdad to 2014. As it turns out that district of Mahmudiya acquired (45.3%) of the total

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Publication Date
Mon Dec 30 2013
Journal Name
Journal Of Genetic And Environmental Resources Conservation
Estimation of immunoglobulins levels in the sera of patients infected with liver hydatid cysts
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This study included 46 patients with liver hydatid cyst diagnosed clinically and surgically, control group consist of 22 were naïve from infection had been confirmed by specialist. The patients were divided according to the size of the cysts into more and less than 5 cm diameter size, were 33 and 13 respectively. Also it divided into primary and secondary hydatid cyst infection which were 30 and 16 respectively. The role of immunological response against hydatid cyst parasite, showed a significant increased in humoral immunoglobulins (IgG, IgA, IgM and IgE) which were significantly higher in the hydatid cyst infection than control. Also significant increased in immunoglobulins in secondary infection than primary infection, beside significa

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Publication Date
Sun Mar 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Simulation of five methods for parameter estimation and functionExponential distribution reliability
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The estimation process is one of the pillars of the statistical inference process as well as the hypothesis test, and the assessment is based on the collection of information and conclusions about the teacher or the community's teachers on the basis of the result
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Publication Date
Thu Jan 16 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison of some reliability estimation methods for Laplace distribution using simulations
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In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Revolution In Science And Humanity
Nonparametric Estimation of Failure Periods for Log Normal Distribution Using Bootstra
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A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental Estimation of Critical Buckling Velocities for Conservative Pipes Conveying Fluid
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Conservative pipes conveying fluid such as pinned-pinned (p-p), clamped–pinned (c-p) pipes and clamped-clamped (c-c) lose their stability by buckling at certain critical fluid velocities. In order to experimentally evaluate these velocities, high flow-rate pumps that demand complicated fluid circuits must be used.

     This paper studies a new experimental approach based on estimating the critical velocities from the measurement of several fundamental natural frequencies .In this approach low flow-rate pumps and simple fluid circuit can be used.

Experiments were carried out on two pipe models at three different boundary conditions. The results showed that the present approach is more accurate for est

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Publication Date
Fri Jan 01 2021
Journal Name
Environment Asia 14(1) 2021 13-22
Synoptic analysis of dust storm in Iraq
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In this study, the synoptic analysis of dust storm for spring and summertime in Iraq were investigated. The images for dust provided by NASA are used to emphasize the dust storm days, while the composite maps of wind vector and geopotential 850hPa are mapped to investigate the pressure and wind direction patterns appearing with the dust condition in the same days. Spring has more dust frequency than summertime, especially in May. The frontal type of dust storm is dominant on spring, the cold air pushes the warm air that picking up the sand to the air through the vertical wind, but the southwestern high-speed wind and drought condition were controlled on the dust in summer. The northwestern wind is the main factor that carries the dust for l

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Scopus Crossref
Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Mathematical Modeling for the Clarifier Units and Turbidity Parameters in AL-KARAMA Treatment Plant
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The high cost of chemical analysis of water has necessitated various researches into finding alternative method of determining portable water quality. This paper is aimed at modelling the turbidity value as a water quality parameter. Mathematical models for turbidity removal were developed based on the relationships between water turbidity and other water criteria. Results showed that the turbidity of water is the cumulative effect of the individual parameters/factors affecting the system. A model equation for the evaluation and prediction of a clarifier’s performance was developed:

Model: T = T0(-1.36729 + 0.037101∙10λpH + 0.048928t + 0.00741387∙alk)

The developed model will aid the predictiv

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Publication Date
Mon Sep 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimal Design of Cylinderical Ectrode Using Neural Network Modeling for Electrochemical Finishing
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The finishing operation of the electrochemical finishing technology (ECF) for tube of steel was investigated In this study. Experimental procedures included qualitative
and quantitative analyses for surface roughness and material removal. Qualitative analyses utilized finishing optimization of a specific specimen in various design and operating conditions; value of gap from 0.2 to 10mm, flow rate of electrolytes from 5 to 15liter/min, finishing time from 1 to 4min and the applied voltage from 6 to 12v, to find out the value of surface roughness and material removal at each electrochemical state. From the measured material removal for each process state was used to verify the relationship with finishing time of work piece. Electrochemi

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