This study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calculate the classification accuracy. Statistical analysis for the result of the classification of each scene is presented for each class .The study showed that the ICA transform makes the satellite image significantly increases the classification accuracy, as well as that the Gaussian kernel gives the highest classification accuracy than other kernels.
Glass Fiber Reinforced Polymer (GFRP) beams have gained attention due to their promising mechanical properties and potential for structural applications. Combining GFRP core and encasing materials creates a composite beam with superior mechanical properties. This paper describes the testing encased GFRP beams as composite Reinforced Concrete (RC) beams under low-velocity impact load. Theoretical analysis was used with practical results to simulate the tested beams' behavior and predict the generated energies during the impact loading. The impact response was investigated using repeated drops of 42.5 kg falling mass from various heights. An analysis was performed using accelerometer readings to calculate the generalized inertial load
... Show MoreTotal Electron Content measurements derived from Athens station ionograms (ITEC),
located near Iraq, during the ascending phase of solar cycle 24 (July 2009- April 2010),
according to availability of data, are compared with the latest version of the International
Reference Ionosphere model, IRI-2012 (IRI TEC), using two options (NeQuick, IRI01-
Corr) for topside electron density.
The results obtained from both (ITEC and IRI TEC) techniques were similar, where
correlation coefficients between them are very high. Generally, the IRI predictions
overestimate the ITEC values.
In this study, we investigated the ability of nanoliposomes preparation, as a nanoadjuvant, to entrap soluble Leismania donovani antigens (SLAs) and release in vitro. The parasite reactivation was carried out when inoculated into Rosewell park memorial institute media (RPMI) and incubated at 23 °C for 4 days. L. donovani promastigote inoculum (104 cell / ml) of 4 days was used to inoculate modified medium of Saline - Neopeptone and Blood agar 9 (SNB 9) to produce promastigote mass. SLAs were extracted from the promastigotes ghost membrane after fourth passages of subculturing in SNB. The membrane pellet obtained was suspended in 5 mM Tris buffer (pH 7.6) and sonicated three times at 4 °C and entrapped in freshly prepared nanoliposomes.
... Show MoreGlass Fiber Reinforced Polymer (GFRP) beams have gained attention due to their promising mechanical properties and potential for structural applications. Combining GFRP core and encasing materials creates a composite beam with superior mechanical properties. This paper describes the testing encased GFRP beams as composite Reinforced Concrete (RC) beams under low-velocity impact load. Theoretical analysis was used with practical results to simulate the tested beams' behavior and predict the generated energies during the impact loading. The impact response was investigated using repeated drops of 42.5 kg falling mass from various heights. An analysis was performed using accelerometer readings to calculate the generalized inertial load. The in
... Show MoreThis paper sheds the light on the vital role that fractional ordinary differential equations(FrODEs) play in the mathematical modeling and in real life, particularly in the physical conditions. Furthermore, if the problem is handled directly by using numerical method, it is a far more powerful and efficient numerical method in terms of computational time, number of function evaluations, and precision. In this paper, we concentrate on the derivation of the direct numerical methods for solving fifth-order FrODEs in one, two, and three stages. Additionally, it is important to note that the RKM-numerical methods with two- and three-stages for solving fifth-order ODEs are convenient, for solving class's fifth-order FrODEs. Numerical exa
... Show MoreThe species of Opilio kakunini Snegovaya, Cokendolpher & Mozaffarian, 2018 was recorded for the first time in Iraq; as well as to four species belonging to this order which were recorded previously. In this paper, we added a new species to the checklist of Iraqi opilionid fauna with a description of the most important characteristics, along with genitalia, for both males and females are presented with digital photographs. Specimens of males and females were collected from Al- Rifai district northern of Dhi-Qar Province, southern of Iraq.
In this paper, we present new algorithm for the solution of the second order nonlinear three-point boundary value problem with suitable multi boundary conditions. The algorithm is based on the semi-analytic technique and the solutions which are calculated in the form of a rapid convergent series. It is observed that the method gives more realistic series solution that converges very rapidly in physical problems. Illustrative examples are provided to demonstrate the efficiency and simplicity of the proposed method in solving this type of three point boundary value problems.
Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.
Hypothesis CO2 geological storage (CGS) involves different mechanisms which can store millions of tonnes of CO2 per year in depleted hydrocarbon reservoirs and deep saline aquifers. But their storage capacity is influenced by the presence of different carboxylic compounds in the reservoir. These molecules strongly affect the water wetness of the rock, which has a dramatic impact on storage capacities and containment security. However, precise understanding of how these carboxylic acids influence the rock’s CO2-wettability is lacking. Experiments We thus systematically analysed these relationships as a function of pressure, temperature, storage depth and organic acid concentrations. A particular focus was on identifying organic acid conce
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