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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
Tue Jun 04 2024
Journal Name
Asian Journal Of Water, Environment And Pollution
Biodegradation of Two Textile Dyes by Bacillus Subtilis
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This study revealed the efficiency of Bacillus subtilisin degrading two textile dyes (disperse red and disperse yellow), the rates of red dye removal when measured after 24, 48, 72 and 96 hours for the concentrations of 50 ppm were 51.67, 67.56, 84.67 and 95.33%, for the concentration 150 ppm were 41.67, 62.67, 80.67 and 89.67%, while for the concentration 300 ppm were 25.67, 42.67, 71.67 and 84.33%. The results of yellow dye removal showed that the concentration of 50 ppm were 49.67, 65.33, 83.33 and 92.67%, for the concentration of 150 ppm were 38.33, 60.33, 77.33 and 87.33%, and for the concentration, 300 ppm were 24, 36.67, 68.33 and 81.67%, when measured after 24, 48, 72 and 96 hours. Results recorded a slight decrease in pH valu

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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
Two side properties of EWMA control panels unilaterally
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This study, establishes two stochastic monotonicity results concerning the run length of an upper one –sided Exponentially Weighted Moving Average (EWMA) control charts, based on the logarithm of the sample variance, for monitoring a process standard deviation, these properties cast interesting light on the control chart performance, and their extension to other one –sided EWMA control charts.

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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Positive and Negative Aspects of Copaxone ( Glatiramer acetate) Action on TC, TG HbA1c and Iron Levels in The Sera of Iraqi Women with Multiple Sclerosis in Baghdad
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The aim of the present study is to highlight the role of total cholesterol (TC), triacylglycerol (TG), Glycated hemoglobin A1c and iron in Iraqi women with multiple sclerosis and also to examine the biochemical action of copaxone (which is the most widely used in the 21st century to treat multiple sclerosis) on these biochemical parameters. This is the first study in Iraq which deals copaxone action on TC , TG , HbA1c and iron. Ninety women in their fourth decade suffering from multiple sclerosis were enrolled in this study. They were divided into: the first (group B) composed of (30) women without any treatment related to multiple sclerosis or any treatment linked with chronic or inflammatory diseases. The second (group A1) included (30)

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Publication Date
Wed Jun 28 2023
Journal Name
Al–bahith Al–a'alami
The Impact of Iraqi Politicians' Use of Twitter on Public Political Awareness
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This research investigates the impact of Iraqi politicians' utilization of Twitter as an interactive media tool to communicate their positions and perspectives on political events. Twitter has become a significant platform for dialogue and interactive discussions. The survey method, specifically the descriptive approach, was employed to answer research questions and achieve objectives. A sample of 100 Iraqi Twitter users was selected, considering demographic variables such as gender, age, and educational background, during the period from September 15 to October 1, 2022.

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Publication Date
Sat Feb 01 2025
Journal Name
Saudi Medical Journal
Spectrum and classification of ATP7B variants with clinical correlation in children with Wilson disease
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Publication Date
Fri Feb 01 2019
Journal Name
Iraqi Journal Of Information & Communications Technology
Evaluation of DDoS attacks Detection in a New Intrusion Dataset Based on Classification Algorithms
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Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The classification of fetus gender based on fuzzy C-mean using a hybrid filter
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This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

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Publication Date
Tue Feb 05 2019
Journal Name
Journal Of The College Of Education For Women
African landlocked countries problems and outlets in the study and classification of geo-political
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Landlocked countries are displayed geopolitical new geo-political and intended to
countries that do not have sea views, a phenomenon present in four continents of the world
are: Africa, Europe, and Asia, and South America and the number arrived at the present time
to the (44) state the largest number of them in the continent it arrived in Africa (16) countries
in Asia (13) countries and Europe (13) In the State of South America two. This phenomenon
emerged due to the division of federations and empires and colonial treaties and others. But
the negative effects suffered by these countries may vary from one country to another, since
these countries in the continent of Europe, for example, is different from the same cou

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Classification of Fetus Gender Based on Fuzzy C-Mean Using a Hybrid Filter
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Abstract<p>This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT), (median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Lap</p> ... Show More
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Future Scenario of Global Climate Map change according to the Köppen -Geiger Climate Classification
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Earth’s climate changes rapidly due to the increases in human demands and rapid economic growth. These changes will affect the entire biosphere, mostly in negative ways. Predicting future changes will put us in a better position to minimize their catastrophic effects and to understand how humans can cope with the new changes beforehand. In this research, previous global climate data set observations from 1961-1990 have been used to predict the future climate change scenario for 2010-2039. The data were processed with Idrisi Andes software and the final Köppen-Geiger map was created with ArcGIS software. Based on Köppen climate classification, it was found that areas of Equator, Arid Steppes, and Snow will decrease by 3.9 %, 2.96%, an

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