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Bayesian methodology for spatial quantile autoregressive model estimation
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Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data problems caused by outliers. A simulation study was conducted using the Monte Carlo method, which is used to generate data according to the distribution and resample until the parameters of the used method converge. The Bayesian method was employed to estimate the model parameters due to its ability to achieve accurate parameter estimates and overcome the challenges faced by traditional estimation methods in this model. The results confirmed the importance of considering spatial aspects when analyzing data, as they significantly impact the model's accuracy. The simulation study was carried out using R software.

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Publication Date
Tue Jun 21 2022
Journal Name
Journal Of Planner And Development
Enviromental impact assessment of cement industry using Leopold Matrix
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The assessment of the environmental impact of the cement industry using the Leopold Matrix is ​​to determine the negative and positive impacts on the environment resulting from this industry, and what are the long-term and short-term effects, direct and indirect, and the amount of these effects and potential risks, and that this evaluation process is done through a number of methods, including Matrix method, including (Leopold).

 

The importance of the research because the cement occupies is of great importance in the world, especially in our country, Iraq, in the sector of construction and modernity, and the toxic emissions and solid waste produced by the production of this material. <

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Treatment of Dairy Wastewater by Electrocoagulation using Iron Filings Electrodes
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This study investigated the treatment of dairy wastewater using the electrocoagulation method with iron filings as electrodes. The study dealt with real samples collected from local factory for dairy products in Baghdad. The Response Surface Methodology (RSM) was used to optimize five experimental variables at six levels for each variable, for estimating chemical oxygen demand (COD) removal efficiency. These variables were the distance between electrodes, detention time, dosage of NaCl as electrolyte, initial COD concentration, and current density. RSM was investigated the direct and complex interaction effects between parameters to estimate the optimum values. The respective optimum value was 1 cm for the distance between electrodes, (6

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Fri Jun 30 2017
Journal Name
Journal Of Engineering
Aluminium Matrix Composites Fabricated by Friction Stir Processing A Review
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      Aluminum alloys widely use in production of the automobile and the aerospace because
they have low density, attractive mechanical properties with respect to their weight, better
corrosion and wear resistance, low thermal coefficient of expansion comparison with traditional
metals and alloys. Recently, researchers have shifted from single material to composite materials
to reduce weight and cost, improve quality, and high performance in structural materials.
Friction stir processing (FSP) has been successfully researched for manufacturing of metal
matrix composites (MMCs) and functional graded materials (FGMs), find out new possibilities
to chemically change the surfaces. It is shown th

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Publication Date
Tue Dec 19 2017
Journal Name
Al-khwarizmi Engineering Journal
Improve Wear Resistance on Al 332 Alloy Matrix- Micro -Nano Al2O3 Particles Reinforced Composite
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The wear behavior of alumina particulate reinforced A332 aluminium alloy composites produced by a stir casting process technique were investigated. A pin-on-disc type apparatus was employed for determining the sliding wear rate in composite samples at different grain size (1 µm, 12µm, 50 nm) and different weight percentage (0.05-0.1-0.5-1) wt% of alumina respectively. Mechanical properties characterization which strongly depends on microstructure properties of reinforcement revealed that the presence of ( nano , micro) alumina particulates lead to simultaneous increase in hardness, ultimate tensile stress (UTS), wear resistances. The results revealed that UTS, Hardness, Wear resistances increases with the increase in the percentage of

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Improving the Durability of Streak and Thermal Insulation of Petroleum Pipes by Using Polymeric Based Paint System: Polymer Matrix Composites have several and wide applications
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This research deals with increasing the hardening and insulating the petroleum pipes against the conditions and erosion of different environments. So, basic material of epoxy has been mixed with Ceramic Nano Zirconia reinforcement material 35 nm with the percentages  (0,1,2,3,4,5) %, whereas the paint basis of broken petroleum pipes was used  to paint on it, then it was cut into dimensions (2 cm. × 2 cm.) and 0.3cm high. After the paint and percentages are completed, the samples were immersed into the paint. Then, the micro-hardness was checked according to Vickers method and thermal inspection of paint, which contained (Thermal conduction, thermal flux and Thermal diffusivity), the density of the painted samples was calculate

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Publication Date
Wed Feb 01 2023
Journal Name
Chemical Data Collections
Removal of diclofenac from aqueous solution on apricot seeds activated carbon synthesized by pyro carbonic acid microwave
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Pharmaceuticals have been widely remaining contaminants in wastewater, and diclofenac is the most common pharmaceutical pollutant. Therefore, the removal of diclofenac from aqueous solutions using activated carbon produced by pyrocarbonic acid and microwaves was investigated in this research. Apricot seed powder and pyrophosphoric acid (45 wt%) were selected as raw material and activator respectively, and microwave irradiation technique was used to prepare the activated carbon. The raw material was impregnated in pyrophosphoric acid at 80◦C with an impregnation ratio of 1: 3 (apricot seeds to phosphoric acid), the impregnation time was 4 h, whereas the power of the microwave was 700 watts with a radiation time of 20 min. A series o

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Assessment of surface water quality using statistical analysis methods: Orontes River (Case study)
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The study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to w

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Publication Date
Sun Jun 25 2023
Journal Name
Iraqi Journal Of Agricultural Sciences
BREEDING POTENTIAL OF RICE GENOTYPES IN TWO AGROCLIMATIC CONDITIONS OF SULAIMANI - KURDISTAN REGION - IRAQ
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This study was aimed to investigate the genetic variability of 26 rice genotypes and evaluation at two locations in Sulaimani governorate, Gaba and Chawtan which were completely different in their environmental condition during the season of 2019. The performances of the genotypes were analyzed at both locations as well as the average of both. Simple coefficients of correlation were used to assess the grain yield components and their relationships. Path analysis was used to determine the direct and indirect effects of such components on grain yield plant-1. The genotypes were grouped based on the agro-morphological features using cluster analysis. Almost all of the traits at both locat

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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