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Edge detection for fast block-matching motion estimation to enhance Mean Predictive Block Matching algorithm
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Publication Date
Sat Mar 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Estimation of rock strength from sonic log for Buzurgan oil field: A Comparison study
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It is very difficult to obtain the value of a rock strength along the wellbore.  The value of Rock strength utilizing to perform different analysis, for example, preventing failure of the wellbore, deciding a completion design and, control the production of sand.  In this study, utilizing sonic log data from (Bu-50) and (BU-47) wells at Buzurgan oil field.  Five formations have been studied (Mishrif, Sadia, Middle lower Kirkuk, Upper Kirkuk, and Jaddala) Firstly, calculated unconfined compressive strength (UCS) for each formation, using a sonic log method.  Then, the derived confined compressive rock strengthens from (UCS) by entering the effect of bore and hydrostatic pressure for each formation.  Evaluations th

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some of Robust the Non-Parametric Methods for Semi-Parametric Regression Models Estimation
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In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then  these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.

The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the

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Publication Date
Wed May 01 2019
Journal Name
Reports Of Practical Oncology & Radiotherapy
Estimation of tumor and local tissue dose in gold nanoparticles radiotherapy for prostate cancer
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The objective of this research was to estimate the dose distribution delivered by radioactive gold nanoparticles (198 AuNPs or 199 AuNPs) to the tumor inside the human prostate as well as to normal tissues surrounding the tumor using the Monte-Carlo N-Particle code (MCNP-6.1. 1 code). Background Radioactive gold nanoparticles are emerging as promising agents for cancer therapy and are being investigated to treat prostate cancer in animals. In order to use them as a new therapeutic modality to treat human prostate cancer, accurate radiation dosimetry simulations are required to estimate the energy deposition in the tumor and surrounding tissue and to establish the course of therapy for the patient. Materials and methods A simple geometrical

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Publication Date
Sat May 09 2015
Journal Name
International Journal Of Innovations In Scientific Engineering
USING ARTIFICIAL NEURAL NETWORK TECHNIQUE FOR THE ESTIMATION OF CD CONCENTRATION IN CONTAMINATED SOILS
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The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Some Estimation for the Parameters and Hazard Function of Kummer Beta Generalized Normal Distribution
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Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr

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Publication Date
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
Enhancement of gas response of annealed ZnO film for hydrogen gas detection
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  The mechanism of hydrogen (H2) gas sensor in the range of 50-200 ppm of RF-sputtered annealed zinc oxide (ZnO) and without annealing was studied. The X-ray Diffraction( XRD) results showed that the Zn metal was completely converted to ZnO with a polycrystalline structure. The I–V characteristics of the device (PT/ZnO/Pt) measured at room temperature before and after annealing at 450 oC for4h, from which a linear relationship has been observed. The sensors had a maximum response to H2 at 350 oC for annealing ZnO and showed stable behavior for detecting H2 gases in the range of 50 to 200 ppm. The annealed film exhibited hig

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Publication Date
Sun Dec 04 2011
Journal Name
Baghdad Science Journal
Use of cefoxitin as indicator for detection of Methicillin Resistant Staphylococcus aureus
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Rapid and accurate identification of Methicillin Resistant Staphylococcus aureus is essential in limiting the spread of this bacterium. The aim of study is the detection of Methicillin Resistant Staphylococcus aureus (MRSA) and determining their susceptibility to some antimicrobial agent. A total of fifty clinical Staphylococcus aureus, isolated from the nose of health work staff in surgery unit of Kalar general hospital and from ear of patients attended to the same hospital. The susceptibilities of isolates were determined by the disc diffusion method with oxacillin (1 ?g) and cefoxitin (30 ?g), and by the mannitol salt agar supplemented with cefoxitin (MSA-CFOX), susceptibilities of isolates to other antimicrobial agent were determined b

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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