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Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our cameras system to capture the images and upload them to the Amazon Simple Storage Service (AWS S3) cloud. Then two detectors were running, Haar cascade and multitask cascaded convolutional neural networks (MTCNN), at the Amazon Elastic Compute (AWS EC2) cloud, after that the output results of these two detectors are compared using accuracy and execution time. Then the classified non-permission images are uploaded to the AWS S3 cloud. The validation accuracy of the offline augmentation face detection classification model reached 98.81%, and the loss and mean square error were decreased to 0.0176 and 0.0064, respectively. The execution time of all AWS cloud systems for one image when using Haar cascade and MTCNN detectors reached three and seven seconds, respectively.

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Publication Date
Tue Sep 27 2022
Journal Name
Journal Of Positive School Psychology .
The Explosive Capacity Of The Muscles Of The Two Men And Their Relationship To The Scoring Of Football Halls
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The research dealt with its forefront a definition of the aspects of the study and its variables, the explosive capacity and its relationship to the scoring of football for the halls and highlights the importance of these variables, and the problem of the research consisted that some players fail to score Amie because of the weak power of shots or the slow scoring, so the researchers saw studying this problem and knowing the extent of the influence of the explosive strength During the performance of the skill of scoring with five football, the study aimed to identify the relationship between the explosive strength and the skill of scoring with five football. Researchers assume that there is a statistically significant relationship between t

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Ten Years of OpenStreetMap Project: Have We Addressed Data Quality Appropriately? – Review Paper
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It has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlight

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Publication Date
Tue Jan 01 2019
Journal Name
Advances In Materials Physics And Chemistry
The Role of Cooling Condition on the Superconducting Properties of Tl<sub>2-x</sub>Hg<sub>x</sub>Sr<sub>2</sub>Ca<sub>2</sub>Cu<sub>3</sub>O<sub>10+δ</sub> System
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Publication Date
Wed Dec 08 2021
Journal Name
J. Inf. Hiding Multim. Signal Process.
Predication of Most Significant Features in Medical Image by Utilized CNN and Heatmap.
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The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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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
Sun Dec 16 2018
Journal Name
Al-academy
Deconstruction the Theatrical Time in the Expressionist Doctrine
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Time affects all elements of the intellectual scene or the theatrical scene. It came along with the theatrical doctrines according to the conditions of those doctrines and their conceptual ideas or the method of their mechanisms in the application. While it is classically or realistically integrated, we see it in the expressionist doctrine inconsistent and its inconsistency makes it responsive for the deconstruction strategy. Hence the researcher entitled his study (deconstruction the theatrical time in the expressionist doctrine) so that deconstruction would be a field for his study.   The study starts with an introduction presenting the research problem, importance and objective. The theoretical framework consisted of three s

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Publication Date
Fri Dec 15 2023
Journal Name
Al-academy
The Philosophy of time in contemporary arts
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Fine art represents part of society's culture. The development of art was accompanied by the penetration of new worlds known as the fourth dimension. After art entered the boundaries of geometry and reduction; He began to break into the absurd, and the form and philosophy of art changed, moving from modernity to what came after it to contemporary. Transforming from a formal form into a symbolic form with philosophical implications linked to the light, audio and kinetic effects as they embody time, the concept became the master of the idea. The research aims to identify the concept of time and its types, then the philosophical concept of time and its reflection on contemporary art, through the analytical study of a selection of contempora

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Publication Date
Sun Oct 02 2016
Journal Name
Journal Of Educational And Psychological Researches
The relationship between Intrinsic Motivation Academy and Time Management among University students
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study aimed to recognize The relationship between Intrinsic Motivation Academy and Time Management among University students and measure Intrinsic Motivation Academy And Time Management for sample and Balancing Degrees of Basic Research on the two scales According to the Variable genders and Specialization, The sample consisted (350) students by (230) female (120) male , and the sample  responded scales of Intrinsic Motivation Academy for (Alwan & Attaat2009) and Time Management (Building tool), The Results of this study show that: There are statistically significant differences according to gender variable in Intrinsic Motivation Academy and Time Management in favor of the male, and there are statistica

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Publication Date
Sun Jan 04 2015
Journal Name
Journal Of Educational And Psychological Researches
The Skills of Time Management and Causes of Wasting The Time of Heads of Department at University of Baghdad From The Staffers’ Point of View
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            Time is very important in educational institutions. It is also one of our contemporary problem ‚as time is a clear – cut and limited factor‚ it demands that administrators should monitor it by administering and monitoring the principles of time.

Hence‚ the researcher attempts to identify the skills of administrating time and the reasons that cause the waste of time of the Heads of Departments at university of Baghdad.

Significance  of the research:

Time is very important to all educational administrators and one of them is the institutions of Higher education. One of the

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