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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 Jun 01 2014
Journal Name
Baghdad Science Journal
Classification of fetal abnormalities based on CTG signal
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The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Preparation, Spectroscopy, Biological Activities and Thermodynamic Studies of New Complexes of Some Metal Ions with 2-[5-(2-Hydroxy-Phenyl)- 1,3,4-Thiadiazol-2-Ylimino]-Methyl-Naphthalen-1-Ol]
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This study describes the preparation of new series of tetra-dentate N2O2 dinuclear complexes (Cr3+, Co2+, Cu2+) of the Schiff base derived from condensation of 1-Hydroxy-naphthalene-2-carbaldehyde with 2-amino-5-(2-hydroxy-phenyl)-1,3,4-thiadiazole. The structures of the ligands were identified using IR, UV-Vis , mass,  elemental analysis and 1H-NMR techniques. All prepared complexes have been characterized by conductance measurement, magnetic susceptibility, electronic spectra, infrared spectrum, theromgravimatric analysis (TGA) and metal analysis by atomic absorption. From stoichiometry of metal to ligand and all measurements show a octahedral geometry proposed for all complexes of the (Cr3+, Co2+, Cu2+). conductivity measurement shows t

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Preparation, Spectroscopy, Biological Activities and Thermodynamic Studies of New Complexes of Some Metal Ions with 2-[5-(2-Hydroxy-Phenyl)- 1,3,4-Thiadiazol-2-Ylimino]-Methyl-Naphthalen-1-Ol]
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This study describes the preparation of new series of tetra-dentate N2O2 dinuclear complexes (Cr3+, Co2+, Cu2+) of the Schiff base derived from condensation of 1-Hydroxy-naphthalene-2-carbaldehyde with 2-amino-5-(2-hydroxy-phenyl)-1,3,4-thiadiazole. The structures of the ligands were identified using IR, UV-Vis , mass,  elemental analysis and 1H-NMR techniques. All prepared complexes have been characterized by conductance measurement, magnetic susceptibility, electronic spectra, infrared spectrum, theromgravimatric analysis (TGA) and metal analysis by atomic absorption. From stoichiometry of metal to ligand and all measurements show a octahedral geometry proposed for all

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Evaluating the Distance Learning Experience in light of the Spread of the Corona Pandemic - Covid 19 from the Teachers' Point of View in Islamic Science Institutes in the Sultanate of Oman
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The study aimed to evaluate the distance learning experience in light of the spread of the Corona pandemic - Covid19 - from the teachers' point of view in Islamic Science Institutes in the Sultanate of Oman, which was applied during the second semester of the 2019/2020 academic year. The study sample consisted of (77) teachers from The Islamic Science Institutes of The Sultan Qaboos Higher Center for Culture and Science. The researchers prepared a questionnaire to evaluate the reality of the experience. The study results  revealed, the followings: The Department of Educational Affairs and Training at The Sultan Qaboos Higher Center for Culture and Science was able to a moderate degree in the rapid transition to a distance learning s

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
E-Learning (Benefits and management systems)
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E-learning seeks to create an interactive learning environment between the teacher and the learner through electronic media conveying in more than one direction, regardless of how the environment and its variables are identified. It also develops skills necessary to deal with technology in order to be able to take into account the individual differences between them and helps e-learning teacher and learner to achieve the goals set in advance and identify educational objectives in a clear manner. The research aims to identify e-learning in its benefits and management systems. It has three sections dealt with in the current research. Chapter II concentrates on the research Methodology, which consisted of three sections: The first s

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Thu Apr 13 2023
Journal Name
International Journal Of Research In Social Sciences And Humanities
Subject Review: The Effectiveness Of Integrating E-Learning On Learning Outcome And Student Perceptions In Tertiary Education
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The literature shows conflicting outcomes, making it difficult to determine how e-learning affects the performance of students in higher education. The effect of e-learning was studied and data has been gathered with the utilization of a variety of qualitative and quantitative methods, especially in relation to students' academic achievements and perceptions in higher education, according to literature review that has been drawn from articles published in the past two decades (2000-2020). The development of a sense of community in the on-line environment has been identified to be one of the main difficulties in e-learning education across this whole review. In order to create an efficient online learning community, it could be claim

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Sat Oct 22 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Classification of Different Shoulder Girdle Motions for Prosthesis Control Using a Time-Domain Feature Extraction Technique
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Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w

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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
The role of organizational learning ability to improve the performance of hospital organizations under the accumulation of intellectual capital Study hospital enterprise sector in Algeria
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        This study aims to identify the amount of the effect of the ability to learn the individuals within the organization on the accumulation of intellectual capital and the role it plays in improving the performance of the organization, and to achieve that, the researcher designed a questionnaire to collect data and information from the surveyed respondents and analyzed using SPSS software, the study concluded after testing hypotheses to have a direct impact between the capacity for organizational learning and the accumulation of intellectual capital, which in turn affects the accumulation of intellectual capital as a positive and direct impact on the performance of the organization, al

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