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Classification of the galaxy Milky Way using variable precision rough sets technique
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Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Physics: Conference Series
Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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Publication Date
Sat Jan 01 2022
Journal Name
Intelligent Automation & Soft Computing
A Novel Classification Method with Cubic Spline Interpolation
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Publication Date
Thu Jan 01 2026
Journal Name
Desalination And Water Treatment
Microplastics toxicity: Classification, sources, exposure routes, and experiments
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Microplastics (MPs), including polymers such as polyethylene, polyvinyl chloride (PVC), and polystyrene (PS), are widespread environmental contaminants detected in air, water, soil, and food. These particles originate from the breakdown of larger plastics and from direct industrial and consumer sources, including packaging, textiles, and personal care products. MPs enter the human body primarily through ingestion, inhalation, and dermal contact, with food, water, and air serving as major exposure pathways. Once internalized, MPs have been found in various human tissues and biological fluids, indicating their capacity for bioaccumulation. Toxicological studies in experimental models and occupational settings link MP exposure to oxidative str

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Publication Date
Thu Feb 24 2022
Journal Name
Journal Of Educational And Psychological Researches
Question Asking Skills: Levels, Conditions, Classification, and Types
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The research aims to know the question asking skills in terms of levels, conditions, classification, and types. The research limited to the literature that dealt with the importance of questioning for students and teachers. The most important term used in the research is the skill (Ryan defined it as "the ability to perform with great efficiency, accuracy, and ease). The results of the research are as follows: 1. the questions asked by the schoolteacher within the assessment of students' learning. 2. Teachers should focus on the lower levels of learning (remembering, understanding and comprehension) and then evaluating students at the higher levels (synthesis and evaluation). 3. Teacher with good knowledge can skillfully use the question

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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Index for the treated water from WTPs on Al-Karakh side of Baghdad City using Artificial Neural Network (ANN) technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Developing A Mathematical Model for Planning Repetitive Construction Projects By Using Support Vector Machine Technique
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Abstract<p>Each project management system aims to complete the project within its identified objectives: budget, time, and quality. It is achieving the project within the defined deadline that required careful scheduling, that be attained early. Due to the nature of unique repetitive construction projects, time contingency and project uncertainty are necessary for accurate scheduling. It should be integrated and flexible to accommodate the changes without adversely affecting the construction project’s total completion time. Repetitive planning and scheduling methods are more effective and essential. However, they need continuous development because of the evolution of execution methods, essent</p> ... Show More
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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Gingival Enlargement Management using Diode Laser 940 nm and Conventional Scalpel Technique (A Comparative Study)
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Diode lasers are becoming popular in periodontal surgery due to their highly absorption by pigments such as melanin and hemoglobin their weak absorption by water and hydroxyapatite makes them safe to be used around dental hard tissues. Objective: The aim of the present study was to evaluate the efficiency of diode laser in performing gingivectomy in comparison to conventional scalpel technique in patients with chronic inflammatory enlargement. Materials and methods: Thirty patients were selected for this study. All of them required surgical treatment of gingival enlargements and were randomly divided into two groups: Control group (treated by scalpel and include sixteen patients) and study group (treated with diode laser 940nm and includ

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Real-Time Cloth Simulation on Virtual Human Character Using Enhanced Position Based Dynamic Framework Technique
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     Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit

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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Studying the Classification of Texture Images by K-Means of Co-Occurrence Matrix and Confusion Matrix
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In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every

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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
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

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