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
Abstract The aim of this study is preparing an intellectual map according to the feedback (verbally and writhingly ) in order to learn some skills of floor exercises in the women's artistic gymnastics , In addition to that the aim of this study defines on the impacts of intellectual map according to the feedback approach, and to identify the best group between the three groups study in the learning of skills approach in this study, the researchers used the experimental method, the subject of the study included on students second class in physical education and sport sciences , Baghdad University (2014-2015) , and divided into three groups for teaching skills which was under studied .The species used the specific manner by lot for selection
... Show MoreIn the hybrid coolingsolar systems , a solar collectoris used to convertsolar energy intoheat sourcein order to super heat therefrigerant leave thecompressor,andthisprocess helpsin the transformation ofrefrigerant state from gaseous statetothe liquid statein upper two-thirdsof thecondenserinstead of the lower two-thirdssuchas in thetraditional air-conditioning systems and this willreduce theenergyneeded torun the process ofcooling.In this research two hybrid air-conditioning system with an evacuated tube solar collector were used, therefrigerant was R22 and the capacity was 2 tons each.The tilt angle of the evacuated tube solar collector was changed and the solar collector fluid was replaced into oil instead of water.A comparison wasi
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Semiconductor quantum dots (QDs) have attracted tremendous attentions for their unique characteristics for solid-state lighting and thin-film display applications. A simple chemical method was used to synthesis quantum dots (QDs) of zinc sulfide (ZnS) with low cost. The XRD) shows cubic phase of the prepared ZnS with an average particles size of (3-29) nm. In UV-Vis. spectra observed a large blue shift over 38 nm. The band gaps energy (Eg) was 3.8 eV and 3.37eV from the absorption and photoluminescence (PL) respectively which larger than the Eg for bulk. QDs-LED hybrid devices were fabricated using ITO/ PEDOT: PSS/ Poly-TPD/ ZnS-QDs/ with different electron transport layers and cathode of LiF/Al layers. The EL spectrum reveals a bro
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The research is dealing with the absorption and fluorescence spectra for the hybrid of an Epoxy Resin doped with organic dye Rhodamine (R6G) of different concentrations (5*10-6, 5*10-5, 1*10-5, 1*10-4, 5*10-4) Mol/ℓ at room temperature. The Quantum efficiency Qfm, the rate of fluorescence emission Kfm (s-1), the non-radiative lifetime τfm (s), fluorescence lifetime τf and the Stokes shift were calculated. Also the energy gap (Eg) for each dye concentration was evaluated. The results showed that the maximum quantum effi
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Ensuring security, integrity, and reliability of the election process consider as the main challenges in the electronic voting system. This paper describes the e-voting system by integrating the biometric authentication, advanced encryption, and watermarking techniques towards meeting such challenges. The system employs the fingerprint authentication by utilizing the Scale-Invariant Feature Transform (SIFT) for verifying the identity of the voter to ensure genuineness and non-repudiation of the service. The vote will be encrypted with the AES-GCM technique to be employed in securing the voting process, thus ensuring both data privacy and integrity. Hybrid Blind Watermarking employs the technique of Discrete Wavelet Transform (DWT) a
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe
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A bolted–welded hybrid demountable shear connector for use in deconstructable steel–concrete composite buildings and bridges was proposed. The hybrid connector consisted of a partially threaded stud, which was welded on the flange of a steel section, and a machined steel tube with compatible geometry, which was bolted on the stud. Four standard pushout tests according to Eurocode 4 were carried out to assess the shear performance of the hybrid connector. The experimental results show that the initial stiffness, shear resistance, and slip capacity of the proposed connector were higher than those of traditional welded studs. The hybrid connector was a ductile connector, according to Eurocode 4, with slip capacity higher than 6 mm. A nonli
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