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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
Sat Jan 10 2015
Journal Name
British Journal Of Mathematics & Computer Science
The Use of Gradient Based Features for Woven Fabric Images Classification
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Publication Date
Wed Sep 29 2021
Journal Name
Biomass Conversion And Biorefinery
Encapsulated deep eutectic solvent for esterification of free fatty acid
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A novel encapsulated deep eutectic solvent (DES) was introduced for biodiesel production via a two-step process. The DES was encapsulated in medical capsules and were used to reduce the free fatty acid (FFA) content of acidic crude palm oil (ACPO) to the minimum acceptable level (< 1%). The DES was synthesized from methyltriphenylphosphonium bromide (MTPB) and p-toluenesulfonic acid (PTSA). The effects pertaining to different operating conditions such as capsule dosage, reaction time, molar ratio, and reaction temperature were optimized. The FFA content of ACPO was reduced from existing 9.61% to less than 1% under optimum operating conditions. This indicated that encapsulated MTPB-DES performed high catalytic activity in FFA esterificatio

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Publication Date
Mon Sep 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Volumetric Mass Transfer Capacity Coefficient in the RTL Extractor
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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Fri Jan 01 2021
Journal Name
دراسات قانونية
The Legal Nature of the Build-Operate- transfer-Ownership Contract (B.O.T.)
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The legal nature of the Build-Operate-Transfer-Ownership Contract (B.O.T) The Build, Operate, and Transfer of Ownership Contract (BOT) has emerged as the most successful and safest method for involving the private sector in public sector services. The major infrastructure projects that are built through the BOT contract are no longer financed by the state and its budget, but the private sector has played a major role in financing These projects, especially developing countries that need to establish infrastructure or modernize their existing infrastructure, especially in the areas of transport, communications, services, electricity, water ..... and other public utilities.

Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Mechanical Engineering Research And Developments
Effect of Circular Turbulators on Heat Transfer in A Square Duct
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Publication Date
Mon Jun 01 2020
Journal Name
Case Studies In Thermal Engineering
Al2O3-water nanofluid heat transfer enhancement of a twin impingement jet
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Publication Date
Tue Jul 21 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Numerical Study of the Heat Transfer Behavior in Helical Microcoil Tube
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Publication Date
Fri Jul 01 2022
Journal Name
Journal Of Engineering
Conjugate Heat Transfer of Laminar Air Flow in Rectangular Mini Channel
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Conjugate heat transfer has significant implications on heat transfer characteristics, particularly in thick wall applications and small diameter pipes. In this study, a three-dimensional numerical investigation was carried out using commercial CFD software “ANSYS FLUENT” to study the influence of conjugate heat transfer of laminar flow in mini channels at constant heat flux wall conditions. Two parameters were studied and analyzed: the wall thickness and thermal conductivity and their effect on heat transfer characteristics such as temperature profile and Nusselt number. Thermal conductivity of (0.25, 10, 202, and 387) W/m2C and wall thickness of (1, 5, and 50) mm were used for a channel of (1*2) mm cross

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Publication Date
Fri Nov 15 2019
Journal Name
Journal Of Materials And Applications
Load Transfer Stiffness of Two-layer Roller Compacted Concrete for Pavements
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Roller compacted concrete (RCC) is a form of plain concrete pavement (JPCP). RCC is a zero-slump concrete consisting of well-graded aggregate, cement and water. RCC has many advantages over other pavement types, particularly cost and speed of construction. Recently, RCC has undergone many developments mostly directed towards improving quality, including smoothness and durability. RCC now has the potential to combine the performance of concrete with the low cost of asphalt installation. A two-layer system of RCC with different aggregate types and sizes was utilized in this study. This paper presents the determination of load transfer stiffness across induced joints in a two-layer RCC system based on a cyclic shear test. The test was

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