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Newton-Kantorovich Method for Solving One of the Non-Linear Sturm-Liouville Problems
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Due to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of applying this method
to solve these problems, a comparison is made in this paper between the Newton-Kantorovich method and the
Adomian decomposition method applied to the same non-linear Sturm-Liouville problems under consideration
in this work. As a result of this comparison, the results of the Newton-Kantorovich method agreed with the
results obtained by applying Adomian’s decomposition method.

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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Iraq and Rockffler Institution for Charity 1929 – 1944
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The thirties and the early forties and the at end of the World War II of the last century
witnessed several attempts carried out by the Public Health Directorate and by the Iraqi
Ministry of Foreign Affairs to persuade the Rockefeller Foundation to fund Iraq with its
health program which is carried out in several regions in the world to promote the health and
social situations since Iraq during that period in history was badly in need to such plans and
programs because of this lack of financial and technical possibilities necessary for the
advancement of health and social dire situation.
The details of these attempts are deposited in the documents of the diplomatic mail
records of the United States of America , an

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Publication Date
Mon May 01 2017
Journal Name
2017 Second International Conference On Fog And Mobile Edge Computing (fmec)
Smart Virtual eNB (SVeNB) for 5G mobile communication
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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi Geological Journal
Reservoir modeling for mishrif formation in Nasiriyah oilfield
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Publication Date
Wed Jan 01 2020
Journal Name
Arab Journal Of Basic And Applied Sciences
Reliable iterative methods for 1D Swift–Hohenberg equation
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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
Tue Dec 13 2022
Journal Name
Lecture Notes In Networks And Systems
Single-Bit Architecture for Low Power IoT Applications
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Publication Date
Sun Dec 04 2011
Journal Name
Baghdad Science Journal
Rotation Effect in Morse Potential For K2 Molecule
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The rotation effect upon Morse potential had been studied and the values of the effective potential in potential curves had been calculated for electronic states (X2?+g , B ?u ) K2 molecule. The calculation had been computed for rotational quantum number (J = 5). Also, drawing potential curves for these systems had been done using Herzberg and Gaydon equations. It was found that the values of the dissociation energy which resulting from using Herzberg equation greater than that of Gaydon equation. Besides, it was found that the rotation effect for (X and B) electronic states in Morse potential is very small and in this case may negligible.

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Publication Date
Mon Feb 19 2018
Journal Name
Al-academy
Dynamic Knowledge Athenaeum for Parametricism in Interior Design
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Over the last few years, the interior designer has been given the ability to access many innovative tools for new forms of unprecedented diversity and efficiency. Some design experts have described the new parametric procedures they are introducing to create new interior projects as a radical transformation that carries all the elements of a qualitative shift in interior design. The best of these parametric procedures is the technical capabilities offered by us to create new forms that are different from what has been discussed in everything that has been produced by designers and architects since modernity and even before it to the present time, which returns our design products through a series of computer programs that perform the pro

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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
Mon Apr 17 2023
Journal Name
Wireless Communications And Mobile Computing
A Double Clustering Approach for Color Image Segmentation
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One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

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