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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
Fri Jun 01 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Performance assessment of biological treatment of sequencing batch reactor using artificial neural network technique.
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Artificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Synthesis and Biological Effectiveness of Some new Azo Compounds as Derivatives of Nitrogen Bases
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In this study the new azo compounds (3compounds) for nitrogen bases (Adenine and Cytosine) are synthesized through two reaction steps (formation of diazonium salt and coupling reaction). The compounds have been characterized by FTIR, melting point, and ultra-violate (UV) spectra. All synthesized compounds have been estimated in vitro for their antimicrobial activities against two species of bacteria(E.coli, S.aureus)and one kind of fungi ( Aspergillus flavus) .The results show that these compounds have very good antibacterial and antifungal activities especially compounds 1 and 3.To study the effect of these compounds were making some physiological tests on rats are made ,the results of hematological study showed decreasing level of

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Publication Date
Thu Nov 25 2021
Journal Name
Engineering And Technology Journal
Pentacene Based Organic Field Effect Transistor Using Different Gate Dielectric
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This paper presents the electrical behavior of the top contact/ bottom gate of an organic field-effect transistor (OFET) utilizing Pentacene as a semiconductor layer with two distinctive gate dielectric materials Polyvinylpyrrolidone (PVP) and Zirconium oxide (ZrO2) were chosen. The influence of the monolayer and bilayer gates insulator on OFET performance was investigated. MATLAB software was used to simulate and determine the electrical characteristics of a device. The output and transfer characteristics were studied for ZrO2, PVP and ZrO2/PVP as an organic gate insulator layer. Both characteristics show a high drain current at the gate dielectric ZrO2/PVP equal to -0.0031A and -0.0015A for output and transfer characteristics respectively

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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Temperature Effect on Power Drop of Different Photovoltaic Modules
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Solar module operating temperature is the second major factor affects the performance of solar photovoltaic panels after the amount of solar radiation. This paper presents a performance comparison of mono-crystalline Silicon (mc-Si), poly-crystalline Silicon (pc-Si), amorphous Silicon (a-Si) and Cupper Indium Gallium di-selenide (CIGS) photovoltaic technologies under Climate Conditions of Baghdad city. Temperature influence on the solar modules electric output parameters was investigated experimentally and their temperature coefficients was calculated. These temperature coefficients are important for all systems design and sizing. The experimental results revealed that the pc-Si module showed a decrease in open circuit v

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Publication Date
Sun Jan 01 2017
Journal Name
International Mathematical Forum
On mildly-regular space
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In this paper mildly-regular topological space was introduced via the concept of mildly g-open sets. Many properties of mildly - regular space are investigated and the interactions between mildly-regular space and certain types of topological spaces are considered. Also the concept of strong mildly-regular space was introduced and a main theorem on this space was proved.

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Publication Date
Fri Feb 28 2020
Journal Name
Iraqi Journal Of Agricultural Sciences (ijas)
PHYTOTOXICITY TEST OF KEROSENE-CONTAMINATED SOIL USING BARLEY
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This study was aimed to determine a phytotoxicity experiment with kerosene as a model of a total petroleum hydrocarbon (TPHs) as Kerosene pollutant at different concentrations (1% and 6%) with aeration rate (0 and 1 L/min) and retention time (7, 14, 21, 28 and 42 days), was carried out in a subsurface flow system (SSF) on the Barley wetland. It was noted that greatest elimination 95.7% recorded at 1% kerosene levels and aeration rate 1L / min after a period of 42 days of exposure; whereas it was 47% in the control test without plants. Furthermore, the percent of elimination efficiencies of hydrocarbons from the soil was ranged between 34.155%-95.7% for all TPHs (Kerosene) concentrations at aeration rate (0 and 1 L/min). The Barley c

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Publication Date
Tue Jul 01 2025
Journal Name
Journal Of Ecological Engineering
Enhancement of <i>Chlorella vulgaris</i> bioethanol production by optimizing phosphorus concentrations
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This 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).

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Publication Date
Fri Jan 31 2025
Journal Name
Joiv : International Journal On Informatics Visualization
RC5 Performance Enhancement Based on Parallel Computing
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This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti

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Publication Date
Fri Sep 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Real Time Wireless Monitoring and Controlling of 3-D Single Point Incremental Tool
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Maintenance of machine tools can be improved significantly by analyzing the operating of manufacturing process with the real-time monitoring system for 3-D single point deformation measurements. Therefore, the process of manufacturing could be optimized with less cost. Recently, wireless technology and internet of things (IOT) applied on intelligent machine has witnessed a significant advance with augmented virtuality, the analysis and the process certainly would contribute to enhance the intelligence of that machine. This paper presents a group of the wireless sensors and 3D animation technologies for data monitoring and analyzing. Three degree of freedom robotic hand structure has been selected as a prototype to be form the process of the

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

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