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jcoeduw-1361
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.

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Publication Date
Wed Jan 01 2020
Journal Name
Communications In Computer And Information Science
Performance Evaluation for Four Supervised Classifiers in Internet Traffic Classification
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Publication Date
Thu Aug 31 2023
Journal Name
Iraqi Geological Journal
Mineral Inversion Approach to Improve Ahdeb Oil Field's Mineral Classification
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Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Parametric Study of Mixed Convective Radiative Heat Transfer in an Inclined Annulus
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The steady state laminar mixed convection and radiation through inclined rectangular duct with an interior circular tube is investigated numerically for a thermally and hydrodynamicaly fully developed flow. The two heat transfer mechanisms of convection and radiation are treated independently and simultaneously. The governing equations which used are continuity, momentum and energy equations. These equations are normalized and solved using the Vorticity-Stream function and the Body Fitted Coordinates (B.F.C) methods. The finite difference approach with the Line Successive Over-Relaxation (LSOR) method is used to obtain all the computational results. The (B.F.C) method is used to generate the grid of the problem. A computer program (Fortran

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Publication Date
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Mass Transfer Coefficient During Cathodic Protection of Low Carbon Steel in Seawater
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The aim of this research is to calculate mass transfer coefficient, kd, during cathodic protection of low carbon steel in neutral seawater (3.5% W/V NaCl in distilled water with pH = 7). Two types of cathodic protection were used:

First: Sacrificial anode cathodic protection (SACP) were a pipeline of steel carrying seawater  using zinc as a sacrificial anode and with variable temperatures ranged (0 – 45oC) and volumetric flow rate ranged (5 – 900 lit/hr). It was found that the kd increases with increasing temperature and volumetric flow rate of seawater, where kd ranged (0.24×10-6 – 41.6×10-6 m/s).

Second: Impressed current cathodic pr

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Publication Date
Mon Jan 01 2018
Journal Name
Aip Conference Proceedings
Theoretical study of electronic transfer current rate at dye-sensitized solar cells
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Publication Date
Tue Feb 17 2026
Journal Name
Sustainable Engineering And Innovation
Morlet wavelet–based olfactory-evoked EEG features for random forest classification of normal, aMCI, and Alzheimer’s disease
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Olfactory impairment and abnormal frontal EEG oscillations are recognized as early markers of Alzheimer’s disease (AD). Using a publicly available olfactory EEG dataset of 35 subjects spanning normal cognition, amnestic mild cognitive impairment (aMCI), and AD, each with MMSE scores and demographics, stimulus-locked epochs from four electrodes (Fp1, Fz, Cz, Pz) were processed with wavelet-based time–frequency analysis. Band-limited power ratios (delta, theta, alpha, beta) were computed as log-transformed post-odor/baseline values and aggregated to subject-level features. Statistical analyses revealed graded attenuation of odor-evoked frontal (Fp1) band-power ratios across groups, with significant differences in several band–od

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Useing the Hierarchical Cluster Analysis and Fuzzy Cluster Analysis Methods for Classification of Some Hospitals in Basra
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In general, the importance of cluster analysis is that one can evaluate elements by clustering multiple homogeneous data; the main objective of this analysis is to collect the elements of a single, homogeneous group into different divisions, depending on many variables. This method of analysis is used to reduce data, generate hypotheses and test them, as well as predict and match models. The research aims to evaluate the fuzzy cluster analysis, which is a special case of cluster analysis, as well as to compare the two methods—classical and fuzzy cluster analysis. The research topic has been allocated to the government and private hospitals. The sampling for this research was comprised of 288 patients being treated in 10 hospitals. As t

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Publication Date
Sat Dec 03 2022
Journal Name
Al-kut University College Of Humanities
Deep understanding skills in chemistry among middle school students
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Publication Date
Mon Feb 25 2019
Journal Name
Iraqi Journal Of Physics
The distance variation due to mass transfer and mass loss in (13.6+8) Mand (13+10) M binary star systems
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In this research the change in the distance of the two stars in two binary star systems (13.6+8)M8and (13+10)M8 was studied, through the calculations the value  (rate of mass transfer) of the two phases of dynamical stages of mass which are mass loss and mass transfer has been extracted in its own way ,by extracting the value of  the value of (the distance variation between the two stars) has been found only in the mass transfer stage by using mathematical model ,in mass loss stage  and   were calculated from the change and the difference between the values of each at different times of binary star system evolution ,it was found that  the maximum values of  and  are in ma

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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