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Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Sun Jun 09 2019
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Status of CHADS2 and CHA2DS2-VASc Scores in Predicting Risk of Stroke and its Prevention in Iraqi Patients with Atrial Fibrillation
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Atrial fibrillation is associates with elevated risk of stroke. The simplest stroke risk assessment schemes are CHADS2 and CHA2DS2-VASc score. Aspirin and oral anticoagulants are recommended for stroke prevention in such patients.

The aim of this study was to  assess status of CHADS2 and CHA2DS2-VASc scores in Iraqi atrial fibrillation patients and to report current status of stroke prevention in these patients with either warfarin or aspirin in relation to these scores.

This prospective cross-sectional study was carried out at Tikrit, Samarra, Sharqat, Baquba, and AL-Numaan hospitals from July 2017 to October 2017. CHADS2

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Publication Date
Wed May 01 2024
Journal Name
Scientific Visualization
Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

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Publication Date
Thu Sep 15 2022
Journal Name
Knowledge And Information Systems
Multiresolution hierarchical support vector machine for classification of large datasets
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Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

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Publication Date
Sat Oct 31 2020
Journal Name
Eastern-european Journal Of Enterprise Technologies
Design and development of high-accuracy machine for wire bending
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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Influence of behavioural implication of information on the selection of accounting methods and their reflection on investor's decisions field study on Iraq stock exchange
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The research aims to highlight on the behavioural approach in accounting, and clarify the behavioural implications of the main activities of accounting, and clarify the concept of information inductance within the framework of the behavioural approach and its impact on preparing financial statements. And that the impact of financial information on the behaviour of investment decision-makers, and to achieve the goals of the research, the researcher prepared a questionnaire according to Likert five-step scale, and he took into consideration in preparing it in line with the characteristics of the study community, and that the target community for this questionnaire is the investors in the Iraq Stock Exchange. The researcher reached

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using a hybrid SARIMA-NARNN Model to Forecast the Numbers of Infected with (COVID-19) in Iraq
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Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

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Publication Date
Wed Jan 01 2025
Journal Name
Kuwait Journal Of Science
Detection of the most frequent sources of dust storms in Iraq during 2020–2023 using space tools
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Dust storms are typical in arid and semi-arid regions such as the Middle East; the frequency and severity of dust storms have grown dramatically in Iraq in recent years. This paper identifies the dust storm sources in Iraq using remotely sensed data from Meteosat-spinning enhanced visible and infrared imager (SEVIRI) bands. Extracted combined satellite images and simulated frontal dust storm trajectories, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, are used to identify the most influential sources in the Middle East and Iraq. Out of 132 dust storms in Iraq during 2020–2023, the most frequent occurred in the spring and summer. A dust source frequency percentage map (DSFPM) is generated using ArcGIS so

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Publication Date
Fri Sep 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluate the effect of surface treatments on shear bond strength between lithium disilicate ceramic and dentin.
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Purpose: To evaluate the effect of different surface treatments on shear bond strength between dentin and IPS e.max lithium disilicate glass-ceramic. Materials and Methods: Eighteen extracted third molars were embeded in epoxy resin. The tooth was sectioned vertically in mesiodistal direction using a low speed hard tissue microtome. The buccal and lingual surfaces of each section were ground flat using 600 grit Silicone carbide paper. Eighteen ceramic discs consisted of lithium disilicate glass-ceramic were prepared with a diameter of 4.7mm and height of 2.2mm. The discs were divided in two groups (n=10): (1) IPS e.max treated with hydrofluoric acid and Monobond Plus (MBP) and (2) IPS e.max treated with Monobond Etch &Prime (MBEP). The toot

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Publication Date
Sat Aug 21 2021
Journal Name
Engineering, Technology &amp; Applied Science Research
The Impact of Hybrid Fibers on Punching Shear Strength of Concrete Flat Plates Exposed to Fire
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This study presents an investigation about the effect of fire flame on the punching shear strength of hybrid fiber reinforced concrete flat plates. The main considered parameters are the fiber type (steel or glass) and the burning steady-state temperatures (500 and 600°C). A total of 9 half-scale flat plate specimens of dimensions 1500mm×1500mm×100mm and 1.5% fiber volume fraction were cast and divided into 3 groups. Each group consisted of 3 specimens that were identical to those in the other groups. The specimens of the second and the third groups were subjected to fire flame influence for 1 hour and steady-state temperature of 500 and 600°C respectively. Regarding the cooling process, water sprinkling was applied directly aft

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