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Two-Stage Classification of Breast Tumor Biomarkers for Iraqi Women
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Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are further classified into either malignant or benign. The collected 20 breast cancer features are utilized to test the performance of the proposed classification system with Leave-One-Out (LOO) cross validation and Synthetic Minority Over-Sampling Technique (SMOTE) to balance the classes. Furthermore, correlation-based feature selection (CFS) was employed in an exploratory analysis to find the best features for the 2-stage classification system.

Results: Classification accuracy of 94% for stage-1 and 100% for stage-2was achieved with a Naïve Bayesclassifier which outperformed other three methods. In addition, CFS selected small subset of features as being the best five features out of the all 20 features for both stage-1 and stage-2.

Conclusion: We achieved a high classification accuracy which is promising to help improve the early diagnosis of breast tumor. The outcome of this study also shows the importance of CA15-3protein in saliva and blood as well as carcinoembryonic antigen level and total protein in blood, and Estrogen hormone level in saliva, for predicting breast tumors.

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Publication Date
Sun Jul 01 2018
Journal Name
Computers & Mathematics With Applications
Analytical and numerical solutions for the nonlinear Burgers and advection–diffusion equations by using a semi-analytical iterative method
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Sat Mar 20 2021
Journal Name
Psychology And Education
Analyzing the Mutual Impact between Accounting Profit and Stock returns for Joint Stock Companies Registered in Baghdad Stock Exchange
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The research aims to test the two characteristics of the relationship between accounting profits and the stock returns, to find out the suitability of both of them in explaining the relationship between accounting profits and stock returns for joint stock companies registered in the Baghdad Stock Exchange, also aims to reaching the most appropriate specification for the relationship between the two variables of the company’s stock dealing in the Baghdad Stock Exchange, and get a set of results, the most important of which are: the ability of changing for both of these variables in the profits share and the stock level of the profits does not explain more than 9,9% of the market returns of the Iraqi Joint Stock Companies registered i

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Publication Date
Mon Apr 01 2019
Journal Name
Applied Water Science
Hydrochemistry as a tool for interpreting brine origin and chemical equilibrium in oilfields: Zubair reservoir southern Iraq case study
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Publication Date
Wed Jun 01 2022
Journal Name
Applied Energy
Novel mathematical modeling, performance analysis, and design charts for the typical hybrid photovoltaic/phase-change material (PV/PCM) system
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Publication Date
Wed Oct 25 2023
Journal Name
Journal Of Optics
Integrated gallium phosphide-waveguide polarization rotator based on rotating a horizontal slot by 45 degree for 700 nm wavelength
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Polarization manipulation elements operating at visible wavelengths represent a critical component of quantum communication sub-systems, equivalent to their telecom wavelength counterparts. The method proposed involves rotating the optic axis of the polarized input light by an angle of 45 degree, thereby converting the fundamental transverse electric (TE0) mode to the fundamental transverse magnetic (TM0) mode. This paper outlines an integrated gallium phosphide-waveguide polarization rotator, which relies on the rotation of a horizontal slot by 45 degree at a wavelength of 700 nm. This will ultimately lead to the conception of a mode hybridization phenomenon in the waveguide. The simulation results demonstrate a polarization co

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
A Posteriori L_∞ (L_2 )+L_2 (H^1 )–Error Bounds in Discontinuous Galerkin Methods For Semidiscrete Semilinear Parabolic Interface Problems
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The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study Using the Passive Solar Chimney for Evaporative Cooling With PCM and CFM as a Thermal Energy Storage
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      In this work, a test room was built in Baghdad city, with (2*1.5*1.5) m3  in dimensions, while the solar chimneys (SC) were designed with aspect ratio (ar) bigger than 12. Test room was supplied by many solar collectors; vertical single side of air pass with ar equals 25, and tilted 45o double side of air passes with ar equals 50 for each pass, both collectors consist of flat thermal energy storage box collector (TESB) that covered by transparent clear acrylic sheet, third type of collector is array of evacuated tubular collectors with thermosyphon in 45o instelled  in the bottom of TESB of vertical SC. The TESB was

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Petrophysical Analysis Based on Well Logging Data for Tight Carbonate Reservoir: The SADI Formation Case in Halfaya Oil Field
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Carbonate reservoirs are an essential source of hydrocarbons worldwide, and their petrophysical properties play a crucial role in hydrocarbon production. Carbonate reservoirs' most critical petrophysical properties are porosity, permeability, and water saturation. A tight reservoir refers to a reservoir with low porosity and permeability, which means it is difficult for fluids to move from one side to another. This study's primary goal is to evaluate reservoir properties and lithological identification of the SADI Formation in the Halfaya oil field. It is considered one of Iraq's most significant oilfields, 35 km south of Amarah. The Sadi formation consists of four units: A, B1, B2, and B3. Sadi A was excluded as it was not filled with h

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Using Dates Leaves Midribs to Prepare Hierarchical Structures Incorporating Porous Carbon and Zeolite A Composites for Cesium137Cs Ion Exchange
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This study synthesized zeolite 4A, and hierarchical composite structure consisting of zeolite 4A- carbon were successfully prepared. Hydrothermal method was used to grow a layer of zeolite 4A over porous carbon surfaces to enhance mass transfer and increase surface area of zeolite. The products then were used to remove radioactive cesium137Cs from liquid wastewater. Iraqi dates leaves midribs (DM) were used as locally available agricultural waste to prepare low- cost porous carbon, using carbonization method in tubular furnace at 900C for two hours. Hierarchical porous structures including zeolite are prepared by mechanically activating the carbon surface via Ultrasonicating nanoparticles suspension of ground zeolite type 4A.F

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