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Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eyes' observation of the different colors and features of images. We propose a multi-layer hybrid system for deep learning using the unsupervised CAE architecture and using the color clustering of the K-mean algorithm to compress images and determine their size and color intensity. The system is implemented using Kodak and Challenge on Learned Image Compression (CLIC) dataset for deep learning. Experimental results show that our proposed method is superior to the traditional compression methods of the autoencoder, and the proposed work has better performance in terms of performance speed and quality measures Peak Signal To Noise Ratio (PSNR) and Structural Similarity Index (SSIM) where the results achieved better performance and high efficiency With high compression bit rates and low Mean Squared Error (MSE) rate the results recorded the highest compression ratios that ranged between (0.7117 to 0.8707) for the Kodak dataset and (0.7191 to 0.9930) for CLIC dataset. The system achieved high accuracy and quality in comparison to the error coefficient, which was recorded (0.0126 to reach 0.0003) below, and this system is onsidered the most quality and accurate compared to the methods of deep learning compared to the deep learning methods of the autoencoder

Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Sun Sep 03 2023
Journal Name
Wireless Personal Communications
Application of Healthcare Management Technologies for COVID-19 Pandemic Using Internet of Things and Machine Learning Algorithms
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and Evaluation of Oral Disintegrating Tablets of Ketoprofen by Dirct Compression
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Ketoprofen is a non-steroidal anti-inflammatory (NSAID) drug with analgesic, anti-inflammatory, and antipyretic effects. It is widely used in the treatment of inflammation and pain associated with rheumatic disorders such as rheumatoid arthritis, osteoarthritis, and in soft tissue injury. The purpose of this study was to prepare an  oral disintegrating tablets of ketoprofen by simple method. The tablets were prepared by direct compression method and different ratios of various subliming agents or superdisintegrants were incorporated. Then these tablets were evaluated for hardness, friability, weight variation, water absorption ratio, disintegrating time and dissolution time. The results showed that Formula F11 batch had short disint

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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
Experimental Evaluation of Thermal Performance of Solar Assisted Vapor Compression Heat Pump
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The thermal performance of indirect expansion solar assisted heat pump, IX-SAHP, was investigated experimentally under Iraqi climate. An Indirect-Solar Assisted Heat Pump system was designed, built, instrumented and tested. Experimental tests were conducted by varying the controlling parameters to investigate their effects on the thermal performance of the IX-SAHP such as cooling water flow rate, heating water flow rate, ambient temperature and solar radiation intensity. The investigation covered values of cooling water flow rate of (2, 3, 4, 5 l/min) and heating water flow rate of (2, 3, 4, 5 l/min) under meteorological condition of Baghdad from November 2014 to January 2015.

The results indicated that the performance of the IX-

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Behavior of Reinforced Concrete Deep Beams Strengthened with Carbon Fiber Reinforced Polymer Strips
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This research is concerned to investigate the behavior of reinforced concrete (RC) deep beams strengthened with carbon fiber reinforced polymer (CFRP) strips. The experimental part of this research is carried out by testing seven RC deep beams having the same dimensions and steel reinforcement which have been divided into two groups according to the strengthening schemes. Group one was consisted of three deep beams strengthened with vertical U-wrapped CFRP strips. While, Group two was consisted of three deep beams strengthened with inclined CFRP strips oriented by 45o with the longitudinal axis of the beam. The remaining beam is kept unstrengthening as a reference beam. For each group, the variable considered

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Publication Date
Wed Jun 01 2011
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Blind Color Image Steganography in Spatial Domain
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WA Shukur, FA Abdullatif, Ibn Al-Haitham Journal For Pure and Applied Sciences, 2011 With wide spread of internet, and increase the price of information, steganography become very important to communication. Over many years used different types of digital cover to hide information as a cover channel, image from important digital cover used in steganography because widely use in internet without suspicious.

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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Blind Color Image Steganography in Spatial Domain
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   With wide spread of internet, and increase the price of information, steganography become very important to communication. Over many years used different types of digital cover to hide information as a cover channel, image from important digital cover used in steganography  because widely use in internet without suspicious.     Since image is frequently compressed for storing and transmission, so steganography must counter the variations caused by loss compression algorithm.     This paper describes a robust blind image steganography, the proposed method embeds the secret message without altering the quality by spraying theme on the blocks in the high order bits in color channel s

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Publication Date
Tue Jun 01 2021
Journal Name
2021 Ieee/cvf Conference On Computer Vision And Pattern Recognition Workshops (cvprw)
Alps: Adaptive Quantization of Deep Neural Networks with GeneraLized PositS
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Publication Date
Wed Nov 28 2018
Journal Name
International Journal Of Engineering & Technology
Modified Strut Effectiveness Factor for FRP-Reinforced Concrete Deep Beams
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A few examinations have endeavored to assess a definitive shear quality of a fiber fortified polymer (FRP)- strengthened solid shallow shafts. Be that as it may, need data announced for examining the solid profound pillars strengthened with FRP bars. The majority of these investigations don't think about the blend of the rigidity of both FRP support and cement. This examination builds up a basic swagger adequacy factor model to evaluate the referenced issue. Two sorts of disappointment modes; concrete part and pulverizing disappointment modes were examined. Protection from corner to corner part is chiefly given by the longitudinal FRP support, steel shear fortification, and cement rigidity. The proposed model has been confirmed util

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