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Identifying the leading sector in the Iraqi economy through the interrelationships between sectors - applied research
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   Analyzing the size of the interrelationships between the main economic sectors in the Iraqi economy is an important necessity to know the impact of each sector on other economic sectors on the basis of the interrelationships and reciprocity between them, and what these relationships have achieved in terms of enhancing development and increasing the gross domestic product. To achieve the objectives of the study, we relied on mathematical (quantitative) analysis using user-product tables. Issued by the Ministry of Planning / Central Bureau of Statistics and Research (Directorate of National Accounts) for the economic sectors that make up the Iraqi economy. The study concluded that there are weak interdependence relations between economic sectors, which indicates the weak contribution of these sectors in creating the gross domestic product and the tendency of the Iraqi economy towards structural disintegration and dependence on exports from outside the country and deepening the phenomenon of a rentier economy. Likewise, the electricity, gas and water sector is the leading sector and one of the sectors most interconnected with the rest of the sectors, and accordingly the study recommended the necessity of strengthening interdependence relations between it and the economic sectors by adopting an industrialization strategy that works on a package of economic reform programs and restructuring the components of the gross domestic product. And giving a role in deepening development processes and strengthening networking

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Publication Date
Sun Sep 29 2019
Journal Name
Iraqi Journal Of Science
A Design of a Hybrid Algorithm for Optical Character Recognition of Online Hand-Written Arabic Alphabets
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     The growing relevance of printed and digitalized hand-written characters has necessitated the need for convalescent automatic recognition of characters in Optical Character Recognition (OCR). Among the handwritten characters, Arabic is one of those with special attention due to its distinctive nature, and the inherent challenges in its recognition systems. This distinctiveness of Arabic characters, with the difference in personal writing styles and proficiency, are complicating the effectiveness of its online handwritten recognition systems. This research, based on limitations and scope of previous related studies, studied the recognition of Arabic isolated characters through the identification o

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Publication Date
Sun Feb 27 2022
Journal Name
Iraqi Journal Of Science
Plants Leaf Diseases Detection Using Deep Learning
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     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
Diagnosis of Malaria Infected Blood Cell Digital Images using Deep Convolutional Neural Networks
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     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
الازمة المالية العالمية
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كنا ولا نزال نقرأ عن انهيار اسهم بورصة وول ستريت في نيويورك عام 1929 لكننا لم نعايش ذلك الحدث الاقتصادي الكبير، اما الان فإننا نرى ونسمع ونحس بتداعيات هذه الازمة المالية بل الاقتصادية العالمية الحالية.

وهذه الشرارة التي كانت بدأت قبل حوالي 80 عاماً ها هي تعيد نفسها اليوم وتبدأ من نفس المكان- بورصة وول ستريت في نيويورك.

واذا كنا قرأنا عن انهيار نظام برتن- وودز بعد الحرب العالمية الث

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Publication Date
Mon Oct 01 2007
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Management of Gastrointestinal Cutaneous Fistulae.
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Background: -Gastrointestinal cutaneous fistula G.I.C.F. occur either postoperative or spontaneous, it is a major complication to patients & surgeons together,, still have significance incidence of morbidity’ & mortality.& it needs specific management.
Ainu-To study the causes of the fistula, to study the methods of treatment either medical or surgical with or without the use of total parenteral nutrition. T.P.N.
Patients& methods: -a prospective study done on 61 patients, divided into male &female, patients. G.I.C.F.were divided into high output & low output fistulae, then an attempt to find the causes of the fistulae & the type of treatment both conservative &surgical treatment, also to study the

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Publication Date
Sat Aug 20 2022
Journal Name
Journal Of Legal Sciences
Jurisprudence and its controls : A Comparative study
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    Judicial jurisprudence is one of the important legal solutions to address the shortcomings of legislation. Throughout its long history, human societies have known many cases in which the judge finds himself facing a legislative vacuum in addition to civil legal texts that are difficult for the judge to implement due to ambiguity or contradiction, which requires diligence. To rule on resolving disputes before him in order not to deny justice, but the judge in his jurisprudence was not absolute, but rather bound by certain controls represented by observing the wisdom of legislation on the one hand and taking into account the nature of the texts on the other side, and from here this research came to shed light on the juri

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Publication Date
Sat Oct 01 2022
Journal Name
Environmental Advances
Stability and performance studies of emulsion liquid membrane on pesticides removal using mixture of Fe3O4Â nanoparticles and span80
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Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Calculation of FC F for Be9C l35 molecules
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Franck-Condon factors (FCF), which are proportional to peak intensities, were calculated as the square of the overlap between the initial and final state wavefunctions in order to calculate of molecule Be9Cl35 their overlap using numerical Integration for the vibrational band (′v =0 - 4) to (v″=0 –4) of the electronic transition A 2Π - Χ 2 Σ and by using an appropriate Potential for each of them .for vibrational ground and first excited states.this new vibrational level must be instantaneously compatible with the nuclear positions and momenta of the vibrational level of the molecule in the originating electronic state. In the semiclassical picture of vibrations (oscillations) of a simple harmonic oscillator, the necessary condit

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Material Recognition of Foreign Object Debris using Deep Learning
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     Foreign Object Debris (FOD) is defined as one of the major problems in the airline maintenance industry, reducing the levels of safety. A foreign object which may result in causing serious damage to an airplane, including engine problems and personal safety risks. Therefore, it is critical to detect FOD in place to guarantee the safety of airplanes flying. FOD detection systems in the past lacked an effective method for automatic material recognition as well as high speed and accuracy in detecting materials. This paper proposes the FOD model using a variety of feature extraction approaches like Gray-level Co-occurrence Matrix (GLCM) and Linear Discriminant Analysis (LDA) to extract features and Deep Learning (DL) for classifi

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Publication Date
Thu Jun 28 2018
Journal Name
2018 4th International Conference On Computer And Technology Applications (iccta)
Improving accuracy of CADx system by hybrid PCA and backpropagation
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—Medical images have recently played a significant role in the diagnosis and detection of various diseases. Medical imaging can provide a means of direct visualization to observe through the human body and notice the small anatomical change and biological processes associated by different biological and physical parameters. To achieve a more accurate and reliable diagnosis, nowadays, varieties of computer aided detection (CAD) and computer-aided diagnosis (CADx) approaches have been established to help interpretation of the medical images. The CAD has become among the many major research subjects in diagnostic radiology and medical imaging. In this work we study the improvement in accuracy of detection of CAD system when comb

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