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Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
New algorithms to Enhanced Fused Images from Auto-Focus Images
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Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
A New Hybrid Meta-Heuristics Algorithms to Solve APP Problems
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Abstract<p>In this paper, a new hybrid algorithm for linear programming model based on Aggregate production planning problems is proposed. The new hybrid algorithm of a simulated annealing (SA) and particle swarm optimization (PSO) algorithms. PSO algorithm employed for a good balance between exploration and exploitation in SA in order to be effective and efficient (speed and quality) for solving linear programming model. Finding results show that the proposed approach is achieving within a reasonable computational time comparing with PSO and SA algorithms.</p>
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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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Publication Date
Mon Mar 31 2025
Journal Name
The Iraqi Geological Journal
Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Thu Oct 17 2024
Journal Name
مجلة ميسان لعلوم التربية البدنية
A historical study of the origins of the sport of polo and its development from the royal court to the stadiums of modern times
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The sport of polo, the game of kings and sultans, is one of the traditional sports that has defied time throughout its long history. It has preserved its historical roots and been able to adapt to contemporary requirements, societal transformations, and temporal and spatial variables. It has moved from an aristocratic sport practiced as a form of entertainment to a professional competitive sport. It attracts many players and millions of viewers, so it is a living model of how sports develop and transform from a local tradition into global sports with organized rules managed by international institutions and with many championships worldwide. Through this, the research objectives were formulated, including exploring sports' origins. Polo in

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Publication Date
Wed Jan 01 2020
Journal Name
Route Educational And Social Science Journal
SURVIVAL IN TIMES OF PANDEMICS: THE PROPHETIC VISION OF JACK LONDON
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Publication Date
Wed May 01 2013
Journal Name
2013 Fourth International Conference On E-learning "best Practices In Management, Design And Development Of E-courses: Standards Of Excellence And Creativity"
Students' Perspectives in Adopting Mobile Learning at University of Bahrain
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Publication Date
Sun Apr 01 2012
Journal Name
Journal Of Educational And Psychological Researches
Effectiveness of at site electronic learning/teaching in educational development
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 This study investigated three aims for the extent of effectiveness of the two systems in educational development of educators. To achieve this, statistical analysis was performed between the two groups that consisted of (26) participants of the electronic teaching method and (38) participants who underwent teaching by the conventional electronic lecture. The results indicated the effectiveness of the “electronic teaching method” and the “electronic lecture method” for learning of the participants in educational development. Also, it indicated the level of equivalence from the aspect of effectiveness of the two methods and at a confidence level of (0.05). This study reached several conclusions, recommendations, and suggestio

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Publication Date
Fri Aug 13 2021
Journal Name
Neural Computing And Applications
Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction
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