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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
Sun Apr 01 2012
Journal Name
Journal Of Educational And Psychological Researches
Effectiveness of at site electronic learning/teaching in educational development
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 This study investigated three aims for the extent of effectiveness of the two systems in educational development of educators. To achieve this, statistical analysis was performed between the two groups that consisted of (26) participants of the electronic teaching method and (38) participants who underwent teaching by the conventional electronic lecture. The results indicated the effectiveness of the “electronic teaching method” and the “electronic lecture method” for learning of the participants in educational development. Also, it indicated the level of equivalence from the aspect of effectiveness of the two methods and at a confidence level of (0.05). This study reached several conclusions, recommendations, and suggestio

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Wed Mar 20 2019
Journal Name
Al-khwarizmi Engineering Journal
Enhancement of Heat Exchanger Performance by Using Dimpled Tube
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The enhancement of heat exchanger performance was investigated using dimpled tubes tested at different Reynolds numbers, in the present work four types of dimpled tubes with a specified configuration manufactured, tested and then compared performance with the smooth tube and other passive techniques performance. Two dimpled arrangements along the tube were investigated, these are inline and staggered at constant pitch ratio X/d=4, the test results showed that Nusselts number (heat transfer) of the staggered array is higher than the inline array by 13%.  The effect of different depths of the dimple (14.5 mm and 18.5 mm) has been also investigated; a tube with large dimple diameter enhanced the Nusselts number by about 25% for the ran

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
solving linear fractional programming problems (LFP) by Using denominator function restriction method and compare it with linear transformations method
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Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac

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Publication Date
Sun May 08 2011
Journal Name
Journal Of Planner And Development
the best way to deal with the center of the ancient city of Najaf
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The historic cities in the Arab and Islamic world (including the cities of the holy shrines in Iraq) suffer from many and varied problems and most notably it is clear in its origin functional structure. It had been transformed from a basic place to live for a few thousand of the population to the center or part of the main center of large city populations of more than one million. Functional structure of the ancient city have been change with the beginning of the twentieth century and accelerated rate of change in the second half of the last century. The research aims to analyze the problems of the historic centers of holy cities and analyze the methods of dealing with these problems, leading to discrimination method could be the

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Publication Date
Mon Nov 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Treatability influence of municipal sewage effluent on surface water quality assessment based on Nemerow pollution index using an artificial neural network
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Abstract<p>Assessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem</p> ... Show More
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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Generalized Left Derivations with Identities on Near-Rings
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In this paper, new concepts which are called: left derivations and generalized left derivations in nearrings have been defined. Furthermore, the commutativity of the 3-prime near-ring which involves some
algebraic identities on generalized left derivation has been studied.

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Slice inverse regression with the principal components in reducing high-dimensions data by using simulation
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This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
identifying the reasons of electronic smoking spreading (VAPING) in the society with practical application using Analytical Factors
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We have investigated in this research, the contents of the electronic cigarette (Viber) and the emergence of the phenomenon of electronic smoking (vibing) were discussed, although the topic of smoking is one of the oldest topics on which many articles and research have been conducted, electronic smoking has not been studied according to statistical scientific research, we tried in this research to identify the concept of electronic smoking to sample the studied data and to deal with it in a scientific way. This research included conducting a statistical analysis using the factor analysis of a sample taken randomly from some colleges in Bab Al-medium in Baghdad with a size of (70) views where  (КМО) and a (bartlett) tests

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