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Mapping Paddy Rice Fields Using Landsat and Sentinel Radar Images in Urban Areas for Agriculture Planning
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     This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being conducted to analyze and understand the strengths and weakness of the proposed new method. This research shows that spectral indices are easy and accurate tool for rapid mapping of paddy rice fields in complicated environment where urban features are dominated. The outcomes of this research could help mapping and decision makers to progress their productivity and strategic plans for better management of rice fields.

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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
Greening Existing Buildings in Contemporary Iraqi Urban Reality/ Virtual Model
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The approach of greening existing buildings, is an urgent necessity, because the greening operation provides the speed and optimal efficiency in the environmental performance, as well as keeping up with the global green architecture revolution. Therefore, greening existing buildings in Iraq is important for trends towards renewable energies, because of what the country went through economic conditions and crises and wars which kept the country away from what took place globally in this issue. The research problem is: insufficient knowledge about the importance and the mechanism of the greening of existing buildings, including its environmental and economic dimensions, by rationalization of energy consumption and preservi

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
The Spatial Analysis for Bassia eriophora (Schrad.) Asch. Plant Distributed in all IRAQ by Using RS & GIS Techniques
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        Most vegetation’s are Land cover (LC) for the globe, and there is an increased attention to plants since they represent an element of balance to natural ecology and maintain the natural balance of rapid changes due to systematic and random human uses, including the subject of the current study (Bassia eriophora ) Which represent an essential part of the United Nations system for land cover classification (LCCS), developed by the World Food Organization (FAO) and the world Organization for environmental program (UNEP), to observe basic environmental elements with modern techniques. Although this plant is distributed all over Iraq, we found that this plant exists primarily in the middle

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Hepatocellular Carcinoma Prediction and early Diagnosis of Hepatitis B and C viral infection using miR-122 and miR-223 in a sample of Iraqi patients.
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Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death. Therefore, it is critical for researchers to understand molecular biology in greater depth.  In several diseases including cancer, abnormal miRNA expression has been linked to apoptosis, proliferation, differentiation, and metastasis. Many miRNAs have been studied in relation to cancer, including miR-122, miR-223, and others. Hepatitis B and C viruses are the most important global risk factors for HCC. This study is intended to test whether serum miRNAs serve as a potential biomarker for both HCC and viral infections HBV and C. The expression of miRNA in 64 serum samples was analyzed by RT-qPCR. Compared to healthy volunteers, HCC patients' sera expre

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Wed Jan 15 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The responsibility of the administration in compliance with the going concern assumption during the preparation for their financial statements: Research practically at muster of companies
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This research aims to demonstrate the impact of the going concern assumption in different accounting applications to provide a realistic look and more accurate result of activity and financial situation, as well as determining the responsibility of the Company's administration in compliance with the going concern assumption during the preparation for their financial statements, and to clarify the concept of integration between internal audit and external audit about going concern assumption, besides its importance and usefulness on the work of both of the internal auditor and the external auditor, as well as on the company under auditing process.This research purports preparing an internal audit program, including a set of auditing actio

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Some Estimation methods for the two models SPSEM and SPSAR for spatially dependent data
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ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Nonlinear Ritz Approximation for the Camassa-Holm Equation by Using the Modify Lyapunov-Schmidt method
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          In this work, the modified Lyapunov-Schmidt reduction is used to find a nonlinear Ritz approximation of Fredholm functional defined by the nonhomogeneous Camassa-Holm equation and Benjamin-Bona-Mahony. We introduced the modified Lyapunov-Schmidt reduction for nonhomogeneous problems when the dimension of the null space is equal to two.  The nonlinear Ritz approximation for the nonhomogeneous Camassa-Holm equation has been found as a function of codimension twenty-four.

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Educational And Psychological Researches
الشخصية العراقية في سياق تكامل الاسرة الحضرية
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From the above can be placed in a summary of the Iraqi personal to the subject in the context of urban family Integration: As personal so hard and durable organization to some extent on the nature of the individual temperament, his mind and his body structure Vhoalve determines the unique environment compatibility.
Valchksah not inherited However, the inherited components, building of the body of the individual and the way they complement each other and members of Trivhalta functions performed by temperament and preparations all in compliance with Vchksath become a product of the interaction between the possibility of nature and the environment.
From here we can say that the family a big role in the personal configuration,

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Speech Compression Using Multecirculerletet Transform
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Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

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Publication Date
Sun Jun 21 2020
Journal Name
Baghdad Science Journal
Spectrophotometer Determination of Cefixime in pure form and pharmaceutical preparation by Using Cloud point Extraction
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Two simple methods spectrophotometric were suggested for the determination of Cefixime (CFX) in pure form and pharmaceutical preparation. The first method is based without cloud point (CPE) on diazotization of the Cefixime drug by sodium nitrite at 5Cº followed by coupling with ortho nitro phenol in basic medium to form orange colour. The product was stabilized and measured 400 nm. Beer’s law was obeyed in the concentration range of (10-160) μg∙mL-1 Sandell’s sensitivity was 0.0888μg∙cm-1, the detection limit was 0.07896μg∙mL-1, and the limit of Quantitation was 0.085389μg∙mL-1.The second method was cloud point extraction (CPE) with using  Trtion X-114 as surfactant. Beer

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