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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 Dec 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Wear Behavior Performance of Polymeric Matrix Composites Using Taguchi Experiments
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This research estimates the effect of independent factors like filler  (3%, 6%, 9%, 11% weight fraction), normal load (5N, 10N, 15N), and time sliding (5,7 , 9 minutes) on wear behavior of unsaturated polyester resin reinforced with jute fiber and waste eggshell and, rice husk powder composites by utilizing a statistical approach. The specimens polymeric composite prepared from resin unsaturated polyester filled with (4% weight fraction) jute fiber, and (3%, 6%, 9%, 11% weight fraction) eggshell, and rice husk by utilizing (hand lay-up) molding. Dry sliding wear experiments were carried utilizing a standard (pin on disc test setup) following a well designed empirical schedule that depends on Taguchi’s experimental design L9 (MINIT

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
A Study on Transportation Models in Their Minimum and Maximum Values with Applications of Real Data
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The purpose of this paper is to apply different transportation models in their minimum and maximum values by finding starting basic feasible solution and finding the optimal solution. The requirements of transportation models were presented with one of their applications in the case of minimizing the objective function, which was conducted by the researcher as real data, which took place one month in 2015, in one of the poultry farms for the production of eggs

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Publication Date
Sat Oct 18 2025
Journal Name
Pattern Recognition And Artificial Intelligence
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation Through a Hybrid Methodology
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This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

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Publication Date
Mon Jan 07 2019
Journal Name
Arab Science Heritage Journal
تعيين عنصر الزئبق السام بتراكيز نزرة في نماذج غذائية ومائية مختلفة باستخدام منظومة بخار الزئبق البارد المرتبطة مع جهاز الامتصاص الذري اللهبي
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الخلاصة

     يتضمن البحث تعيين عنصر الزئبق السام بتراكيزنزرة عالية الدقة (نانوغرام) باستخدام منظومة يخار الزئبق البارد لنماذج غذائية (لحوم حمراء ، لحوم بيضاء ) مختلفة ونماذج مائية (ماء النهر، مياه صناعية ، ماء الشرب) وربط المنظومة بتقنية الامتصاص الذري اللهبي.

     ان عنصر الزئبق من اشد العناصر سمية وان التراكيز المسموح بها عالميا لايتعدى جزء واحد

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Publication Date
Sun Mar 12 2017
Journal Name
مجلة كلية مدينة العلم الجامعة
تخطيط اوقات انجاز الهيئات الرقابية لدائرة تدقيق نشاط التمويل والتوزيع في ديوان الرقابة المالية الاتحادي باستخدام إنموذج التخصيص العام مع تطبيق عملي
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تم في هذه الدراسة أعادة التخطيط لتوزيع الهيئات الرقابية على االدارات الخاضعة لتدقيقها لدائرة تدقيق نشاط التمويل والتوزيع في ديوان الرقـابة المالية االتحادي ، وتم بناء أنموذج التخصيص العـام اعتمادا"على لسنة أنجاز أعمال الهيئات الرقابية لالدارات الخاضعة (2016 (أوقـات,حيث أنـه تـم بنـاء أنموذج ريـاضي لتدقيقهاللمجموعة االولى لهيئات هـذه الدائرة وذلك للحصول علىالتخصيص األمثل للهيئات الـرقـابية على االدارات وي

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Publication Date
Sun Mar 08 2015
Journal Name
All Days
Distribution of New Horizontal Wells by the Use of Artificial Neural Network Algorithm
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Abstract<p>It is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporatin</p> ... Show More
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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Fabrication and Characterization of Nanofibers Membranes using Electrospinning Technology for Oil Removal
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Oily wastewater is one of the most challenging streams to deal with especially if the oil exists in emulsified form. In this study, electrospinning method was used to prepare nanofiberous polyvinylidene fluoride (PVDF) membranes and study their performance in oil removal. Graphene particles were embedded in the electrospun PVDF membrane to enhance the efficiency of the membranes. The prepared membranes were characterized using a scanning electron microscopy (SEM) to verify the graphene stabilization on the surface of the membrane homogeneously; while FTIR was used to detect the functional groups on the membrane surface. The membrane wettability was assessed by measuring the contact angle. The PVDF and PVDF / Graphene membranes efficiency

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Publication Date
Wed Sep 15 2021
Journal Name
Al-academy
The impact of e-learning on the cognitive level in the Corona crisis: أسماء غازي عبد
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E-learning is a necessity imposed by the Corona pandemic, which has disrupted various educational institutions in the world, but some of these institutions have not been affected and education has continued with them, due to their flexible educational system that was able to employ technology in the continuity of the educational process in the so-called e-learning, because It has characteristics that make it the most suitable alternative to avoid the consequences of the Corona pandemic and its damage to the educational process, as e-learning is one of the modern methods that contribute to enhancing the effectiveness of the learner, and enabling him to assume greater responsibility compared to traditional education, so the learner becomes

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Some Estimation Methods Of GM(1,1) Model With Missing Data and Practical Application
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This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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