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The Bayesian Estimation in Competing Risks Analysis for Discrete Survival Data under Dynamic Methodology with Application to Dialysis Patients in Basra/ Iraq
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Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete hazard function and the time-dependent parameters, two estimation methods have been used that depend on the Bayes method according to dynamic modeling: the Maximum A Posterior method (MAP) This method was done using numerical methods represented by a Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation maximization algorithm (EM), the other method is represented by the Hybrid Markov Chains Monte Carlo (HMCMC) method using the Metropolis Hasting algorithm (MH) and Gypsum sampling (GS). It was concluded that survival analysis by descretization the data into a set of intervals is more flexible and fluid, as this allows analyzing risks and diagnosing impacts that vary over time. The study was applied in the survival analysis on dialysis until either death occurred due to kidney failure or the competing event, represented by kidney transplantation. The most important variables affecting the patient’s cessation of dialysis were also identified for both events in this research.

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Publication Date
Tue Jan 01 2019
Journal Name
Sci.int.(lahore)
FILTER BASES AND SUPRA PERFECT FUNCTIONS
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We introduce some new generalizations of some definitions which are, supra closure converge to a point, supra closure directed toward a set, almost supra converges to a set, almost supra cluster point, a set supra H-closed relative, supra closure continuous functions, supra weakly continuous functions, supra compact functions, supra rigid a set, almost supra closed functions and supra perfect functions. And we state and prove several results concerning it

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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Adsorption of Congo Red Dye from Aqueous Solution onto Natural and Modified Bauxite Clays
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The adsorption behavior of congo red dye from its aqueous solutions was investigated onto natural and modified bauxite clays. Both bauxite and modified bauxite are primarily characterized by using, FTIR, SEM, AFM, and XRD. Several variables are studied as a function of adsorption including contact time, adsorbent weight, pH, ionic strength, particle size and temperature under batch adsorption technique. The absorbance of the solution before and after adsorption was measured spectrophotometrically. The equilibrium data fit with Langmuir model of adsorption and the linear regression coefficient R2 is found to be 0.9832 and 0.9630 for natural and modified bauxite respectively at 37.5°C which elucidate the best fitting isotherm model. The gene

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Sat Jul 15 2023
Journal Name
Journal Of Interdisciplinary Mathematics
Some games via semi-generalized regular spaces
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In this research, a new application has been developed for games by using the generalization of the separation axioms in topology, in particular regular, Sg-regular and SSg- regular spaces. The games under study consist of two players and the victory of the second player depends on the strategy and choice of the first player. Many regularity, Sg, SSg regularity theorems have been proven using this type of game, and many results and illustrative examples have been presented

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Publication Date
Mon Sep 20 2021
Journal Name
Key Engineering Materials
Effect of Partial Substitution of Sr by Ba on the Structural Properties of Tl&lt;sub&gt;0.8&lt;/sub&gt;Ni&lt;sub&gt;0.2&lt;/sub&gt;Sr&lt;sub&gt;2-x&lt;/sub&gt;Br&lt;sub&gt;x&lt;/sub&gt;Ca&lt;sub&gt;2&lt;/sub&gt;Cu&lt;sub&gt;3&lt;/sub&gt;O&lt;sub&gt;9-δ&lt;/sub&gt; System
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In this manuscript, the effect of substituting strontium with barium on the structural properties of Tl0.8Ni0.2Sr2-xBrxCa2Cu3O9-δcompound with x= 0, 0.2, 0.4, have been studied. Samples were prepared using solid state reaction technique, suitable oxides alternatives of Pb2O3, CaO, BaO and CuO with 99.99% purity as raw materials and then mixed. They were prepared in the form of discs with a diameter of 1.5 cm and a thickness of (0.2-0.3) cm under pressures 7 tons / cm2, and the samples were sintered at a constant temperature o

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Publication Date
Tue Apr 01 2025
Journal Name
Journal Of Economics And Administrative Sciences
Spatial Quantile Autoregressive Model: A Review
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This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Bridge Regression Model Estimating via Simulation
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      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

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Publication Date
Wed Sep 12 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On θ-Totally Disconnected and θ-Light Mappings
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        In our research, we introduced new concepts, namely *and **-light mappings, after we knew *and **-totally disconnected mappings through the use of -open sets.

Many examples, facts, relationships and results have been given to support our work.

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Publication Date
Mon Jan 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
CONVERGENCES VIA ẛـ PREـ gـ OPEN SET
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   The main aim of this paper is to use the notion  which was introduced in [1], to offered new classes of separation axioms in ideal spaces. So, we offered new type of notions of convergence in ideal spaces via the set. Relations among several types of separation axioms that offered were explained.

 

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Development Binary Search Algorithm
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There are many methods of searching large amount of data to find one particular piece of information. Such as find name of person in record of mobile. Certain methods of organizing data make the search process more efficient the objective of these methods is to find the element with least cost (least time). Binary search algorithm is faster than sequential and other commonly used search algorithms. This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. It consists of three locations (1-Top, 2-Left, and 3-Right) Binary search algorithm divide the search interval in half, this process makes the maximum number of comparisons (Average case com

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