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An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recognition applications; the proposed method was evaluated for performance in terms of computational accuracy, convergence analysis, and cost.

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Tue Aug 02 2022
Journal Name
International Journal Of Research In Social Sciences & Humanities
The Making of a Heroine: A Female Character as Portrayed in The English Patient By Michael OndaatjE
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This article discusses how women have significant abilities to cope with the difficulties of war times. They are not the weak and vulnerable victims who are thought to be. On the contrary, they have the power to control over many-sided fronts, like participating in the battlefield as nurses or activists for peace, or even fighters, as well as through the tasks and responsibilities assigned to them to protect and support their families during wartime. The researcher will examine the impact of war upon women. Like men, women suffer during wartime. They are being injured, tortured and killed. Yet, they are able to give examples of love and courage even in the difficult times of war. Hana is one of those women who lived during wartimes,

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Publication Date
Mon May 25 2026
Journal Name
Journal Of Babylon Center For Humanities Studies
The reflection of the Arab character in Israeli children's literature in the years 1990 - 2015
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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Research In Social Sciences & Humanities
The House of Bernarda Alba: The Image of Repression and Female Rebellion Through the Character of Adela
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In the present work, the image and representation of Adela, the youngest daughter of the family of the Casa de Bernarda Alba, one of the most popular works of the Spanish author Federico García Lorca (1898-1936), will be analyzed. In this work, there are different themes, but what concerns us is to show the repression, oppression and rebellion of this character in a context of customs of the 1920s in Spain. They are revealing elements in that period in which women were relegated to the background, despite the fact that a feminist movement had already begun in Spain. By studying Adela, we seek to see how a single woman confronts her family and the society that surrounds her to fight for freedom, although its end is finally linked to

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Publication Date
Wed Mar 15 2023
Journal Name
Al-academy
Dramatic Dialogue And Its Effectiveness In Enhancing The Characteristics Of The Alienated Character In The Television Series
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Dialogue is one of the pillars of character building in the television series, through which it is possible to identify the most important characteristics and traits of the personality, in addition to its ability to reveal the most important problems at all levels. The following: (How does dialogue contribute to enhancing the traits of the alienated personality?). It therefore aims to identify the effectiveness of the dramatic dialogue in enhancing the traits of the alienated personality represented by (powerlessness, isolation, meaninglessness, objectification, non-standardization and rebellion). (The traits of the alienated character, and the second is the psychological function of the dramatic dialogue), to extract from them the main

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Geological Journal
Geological Model for Mauddud Reservoir Khabaz Oil Field
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The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

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Publication Date
Tue Jan 01 2019
Journal Name
Cpwr
Development of a workforce sustainability model for construction
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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Optimal Color Model for Information Hidingin Color Images
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In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Hydrology
Complementary data-intelligence model for river flow simulation
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