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Predicate the Ability of Extracorporeal Shock Wave Lithotripsy (ESWL) to treat the Kidney Stones by used Combined Classifier
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Extracorporeal Shock Wave Lithotripsy (ESWL) is the most commonplace remedy for kidney stone. Shock waves from outside the body frame are centered at a kidney stone inflicting the stone to fragment. The success of the (ESWL) treatment is based on some variables such as age, sex, stone quantity stone period and so on. Thus, the prediction the success of remedy by this method is so important for professionals to make a decision to continue using (ESWL) or tousing another remedy technique. In this study, a prediction system for (ESWL) treatment by used three techniques of mixing classifiers, which is Product Rule (PR), Neural Network (NN) and the proposed classifier called Nested Combined Classifier (NCC). The samples had been taken from 2850 actual sufferers cases that had been treated at Urology and Nephrology center of Iraq. The results from three cases have been compared to actual treatment results of (ESWL) for trained and non-trained cases and compared the results of three models. The results show that (NCC) approach is the most accurate method in prediction the efficient of uses (ESWL) remedy in treatment the kidney stone.

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Publication Date
Thu Dec 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Shear Wave velocity for carbonate rocks
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In many oil fields only the BHC logs (borehole compensated sonic tool) are available to provide interval transit time (Δtp), the reciprocal of compressional wave velocity VP.

   To calculate the rock elastic or inelastic properties, to detect gas-bearing formations, the shear wave velocity VS is needed. Also VS is useful in fluid identification and matrix mineral identification.

   Because of the lack of wells with shear wave velocity data, so many empirical models have been developed to predict the shear wave velocity from compressional wave velocity. Some are mathematical models others used the multiple regression method and neural network technique.

   In this study a number of em

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Publication Date
Sun Jul 09 2017
Journal Name
Current Research In Microbiology And Biotechnology
The chronic effects of glucosamine sulfate (GS) on kidney in Albino Mice
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Publication Date
Fri Jun 08 2018
Journal Name
Advances In Intelligent Systems And Computing
Improve Memory for Alzheimer Patient by Employing Mind Wave on Virtual Reality with Deep Learning
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Evaluation of the one electron expectation values for different wave function of Be atom
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The aim of this work is to evaluate the one- electron expectation value from the radial electronic density function D(r1) for different wave function for the 2S state of Be atom . The wave function used were published in 1960,1974and 1993, respectavily. Using Hartree-Fock wave function as a Slater determinant has used the partitioning technique for the analysis open shell system of Be (1s22s2) state, the analyze Be atom for six-pairs electronic wave function , tow of these are for intra-shells (K,L) and the rest for inter-shells(KL) . The results are obtained numerically by using computer programs (Mathcad).

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
The Potential of Recycling Used Engine Oil for Biogas Generation by Co-Digestion with Animals’ Manure: Experimental and Kinetic Study
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This study investigates the potential of biogas recovery from used engine oil (UEO) by co-digestion with animals’ manure, including cow dung (CD), poultry manure (PM), and cattle manure (CM). The experimental work was carried out in anaerobic biodigesters at mesophilic conditions (37°C). Two groups of biodigesters were prepared. Each group consisted of 4 digesters. UEO was the main component in the first group of biodigesters with and without inoculum, whereby a mix of UEO and petroleum refinery oily sludge (ROS) was the component in the second group of biodigesters. The results revealed that for UEO-based biodigesters, maximum biogas production was 0.98, 1.23, 1.93, and 0 ml/g VS from UEO±CD, UEO±CM, UEO±PM, and U

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Publication Date
Mon Apr 23 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Investigate of the Ability of Cronobacter sakazakii Isolated from Clinical Samples of Children Under Two Years to Induce Swimming, Swarming and Biofilm
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      The study included 200 samples were collected   from   children  under two   years included (50 samples from each of Cerebrospinal fluid, Blood, Stool and Urine) from, Central Children Hospital and Children's Protections Educational Hospital. Isolates bacterial were obtained cultural, microscopic and biochemical examination and diagnosed to the species by using vitek2 system. The results showed there were contamination in 6.5% of clinical samples. The diagnosed colonies which gave pink color on the MacConkey agar , golden yellow color on the Trypton Soy agar and green color on the Birillent Enterobacter sakazakii agar and gave  a probability of 99% in the vit

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Publication Date
Wed Jul 01 2020
Journal Name
Plant Archives
INVESTIGATING THE ABILITY TO USE NATURAL IRAQI MATERIAL "CRUSHED PORCELANITE ROCKS" IN GREYWATER FILTRATION, AND COMPARE IT WITH SAND FILTER
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Publication Date
Wed Jul 01 2020
Journal Name
Plant Archives
Investigating the ability to use natural iraqi material ⇜crushed porcelanite rocks⇝ in greywater filtration, and compare it with sand filter
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Publication Date
Fri Jan 01 2021
Journal Name
Materials Today: Proceedings
Solving high sulfate content of sand used in concrete by magnetic water process
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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.