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The effect of using Gaussian, Kurtosis and LogCosh as kernels in ICA on the satellite classification accuracy
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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.

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Publication Date
Wed Jan 01 2025
Journal Name
Fusion: Practice And Applications
Enhanced EEG Signal Classification Using Machine Learning and Optimization Algorithm
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This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

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Publication Date
Sun Jun 16 2019
Journal Name
Al–bahith Al–a'alami
The effectiveness of satellite channels in spreading the culture of volunteering among youth / applied study
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The study deals with the effectiveness of satellite channels in spreading the culture of volunteer work among young people. It is an applied study aimed at understanding the extent to which the sample understands the culture of volunteering, determining the type of relationship between the satellite channels programs and the perception of the sample of the culture of voluntary work and the relationship between the characteristics of the sample and the effect of satellite channels in their directions, And to identify the relationship between the demographic variables of the sample and to participate in voluntary work.
A sample study was conducted for students of faculties of the University of Baghdad, consisting of (150) single male an

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Study the Effect of Folic Acid as A supplement on Selected Oxidative Stress and Biochemical Parameters in First Trimester of Pregnancy
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Folic acid modulates several disorders in humans, pregnancy mostly because of the mitochondria-rich placenta, is a condition that favors oxidative stress.Transitional metals, especially iron, which are particularly abundant in the placenta, are important in the production of free radicals. Adenosine deaminase (ADA), an enzyme essential for the differentiation of lymphoid cells, has been used for monitoring diseases with altered immunity. In the present study we investigated the effect of regular and irregular administered folic acid in the first and second trimester of pregnancy to be compared with non-pregnant women ,and also the effect of regular and irregular using of folic acid  supplement on  oxidative stress parameters an

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Publication Date
Mon Nov 19 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison Study of the Effect of Erlotinib as a Tyrosine Kinase Inhibitor on Electrolyte Levels in Type2 Diabetic and Diabetic Nephropathy
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Diabetes mellitus can be defined as  a metabolic disorder disease .Complication  of diabetes  are due to diabetic nephropathy .This study was done in vitro to study the effect of different concentrations of erlotinib inhibitor ( tyrosine kinase inhibitor) on electrolyte levels (Mg⁺²,Ca⁺²,Na⁺) in sera of Iraqi patients with  newly diagnosis type2 diabetes and diabetic nephropathy in addition to find the best percentage inhibition for utilizing different concentrations from erlotinib (6.97x10⁻⁷, 9.30x10⁻⁷ ,1.16x10⁻⁶,1.39x10⁻⁶ ,1.62x10⁻⁵ )molar  on electrolyte levels . This study was conducted in The National Diabetes Ce

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Publication Date
Mon Feb 20 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Satellite Images Fusion Using Mapped Wavelet Transform Through PCA
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In this paper a new fusion method is proposed to fuse multiple satellite images that are acquired through different electromagnetic spectrum ranges to produce a single gray scale image. The proposed method based on desecrate wavelet transform using pyramid and packet bases, the fusion process preformed using two different fusion rules, where the low frequency part is remapped through the use of PCA analysis basing on covariance matrix and correlation matrix, and the high frequency part is fused using different fusion rules (adding, selecting the higher, replacement), then the restored image is obtained by applying the inverse desecrate wavelet transform. The experimental results show the validity of the proposed fusion method to fuse suc

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Publication Date
Wed May 31 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Satellite Image Mosaics Using Digital Cosine Transform (DCT) Descriptor
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In this research work, a modified DCT descriptor are presented to mosaics the satellite images based on Abdul Kareem [1] similarity criterion are presented, new method which is proposed to speed up the mosaics process is presented. The results of applying the modified DCT descriptor are compared with the mosaics method using RMSE similarity criterion which prove that the modified DCT descriptor to be fast and accurate mosaics method.

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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Mon Jan 01 2018
Journal Name
Lecture Notes Of The Institute For Computer Sciences, Social Informatics And Telecommunications Engineering
Sensor Data Classification for the Indication of Lameness in Sheep
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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
Diagnostic Accuracy of Different Radiological Investigations in the Diagnosis of Perforated Duodenal Ulcer
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Background; Perforated duodenal ulcer (PDU) is a common surgical emergency that is associated with high mortality and morbidity. Early diagnosis and prompt surgical treatment is required to prevent grave complications.
Objective; The study was designed to evaluate the diagnostic accuracy of different radiological investigations in the diagnosis of perforated duodenal ulcer.
Methods; A prospective study of 185 pts with PDU at al kindy teaching hospital, Baghdad, Iraq from June 2008- august 2010. patients were examined clinically and investigated by blood test, chest x ray, plain X ray of the abdomen. Ultrasonography (U/S) and CT scanning done for those patients with negative X- ray finding. Resuscitation by intravenous fluid and ant

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