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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 Mar 01 2014
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Alliance insurance companies with the banks to promote insurance services
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       Insurance companies seeking to develop programs to promote and market their services and to increase its customer through the use of modern technical marketing and reduce its dependence on agents and take advantage of work of the banks by alliances with them and including reinforcing get the parties to competitive advantages in the financial market , the insurance services intangible service stops marketed over the insurance awareness and   requires exceptional promotional efforts.                                   &nbs

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Simulation and Modelling of Electricity Usage Control and Monitoring System using ThingSpeak
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Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

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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
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
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Quality of Life in Schizophrenic Patients: The Relationship with Personal Characteristics
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Objectives: The study aims to identify the quality of life level in schizophrenic patients and to find out the
relationships between the quality of life and some of personal characteristics for those patients with
schizophrenia.
Methodology: A descriptive correlation analytic design was used by using the assessment technique on sample
of 100 schizophrenic outpatients, who were selected purposively (non-probability sample) during the period
10/ 3/2013 - 1/ 12 /2013. The study was conducted on the schizophrenic patients in an out patient psychiatric
clinics at Ibn-Rushd; and Al-Rashad Psychiatric Teaching Hospital; Baghdad Teaching Hospital, and Al-Kadhimya
Teaching Hospital. Self administrative questionnaire was used

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Developing and Sustaining a Multilevel Competitive Learning Organization – A Behavioral and Cognitive Approach
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To maintain a sustained competitive position in the contemporary environment of  knowledge  economy,  organizations  as an open social systems must have an ability to learn and know  how to adapt to rapid changes  in a proper fashion so that organizational objectives will be achieved efficiently and effectively.  A multilevel approach is adopted proposing that organizational learning suffers from the lack of interest about the strategic competitive performance of the organization. This remains implicit almost in all models of organizational learning and there is little focus on how learning organizations achieve sustainable competitive advantage . A dynamic model that captures t

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Use Of Some Parametric And Non parametric Methods For Analysis Of Factorial Experiments With Application
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summary

In this search, we examined the factorial experiments and the study of the significance of the main effects, the interaction of the factors and their simple effects by the F test (ANOVA) for analyze the data of the factorial experience. It is also known that the analysis of variance requires several assumptions to achieve them, Therefore, in case of violation of one of these conditions we conduct a transform to the data in order to match or achieve the conditions of analysis of variance, but it was noted that these transfers do not produce accurate results, so we resort to tests or non-parametric methods that work as a solution or alternative to the parametric tests , these method

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Software Security using Aspect-Oriented Software Development
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Aspect-Oriented Software Development (AOSD) is a technology that helps achieving
better Separation of Concern (SOC) by providing mechanisms to identify all relevant points
in a program at which aspectual adaptations need to take place. This paper introduces a
banking application using of AOSD with security concern in information hiding.

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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Index for the treated water from WTPs on Al-Karakh side of Baghdad City using Artificial Neural Network (ANN) technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Scopus (59)
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