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
This study focuses on producing wood-plastic composites using unsaturated polyester resin reinforced with Pistacia vera shell particles and wood industry waste powder. Composites with reinforcement ratios of 0%, 20%, 30%, and 40% were prepared and tested for thermal conductivity, impact strength, hardness, and compressive strength. The results revealed that thermal conductivity increases with reinforcement, while maintaining good thermal insulation, reaching a peak value of 0.633453 W/m·K. Hardness decreased with increased reinforcement, reaching a minimum nominal hardness value of 0.9479. Meanwhile, impact strength and compressive strength improved, with peak values of 14.103 k/m² and 57.3864568 MPa, respectively. The main aim is to manu
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In this work the fabrication and characterization of poly(3-hexylthiophene) P3HT-metallic nanoparticles (Ag, Al). Pulsed Laser Ablation (PLA) technique was used to synthesis the nanoparticles in liquid. The Fourier Transformer Infrared (FTIR) for all samples indicate the chemical interaction between the polymer and the nanoparticles. Scanning Electron Microscopic (SEM) analysis showed the particle size for P3HT-AgNps samples between 44.50 nanometers as well the spherical structure. While for P3HT-AlNps samples was flakes shape. Energy Dispersive X-ray (EDX) spectra show the existing of amount of metallic nanoparticles.
Due to their attractive properties, silver nanowires (Ag-NWs) are newly used as nanoelectrodes in continuous wave (CW) THz photomixer. However, since these nanowires have small contact area, the nanowires fill factor in the photomixer active region is low, which leads to reduce the nanowires conductivity. In this work, we proposed to add graphene nanoantenna array as nanoelectrodes to the silver nanowires-based photomixer to improve the conductivity. In addition, the graphene nanoantenna array and the silver nanowires form new hybrid nanoelectrodes for the CW-THz photomixer leading to improve the device conversion efficiency by the plasmonic effect. Two types of graphene nanoantenna array are proposed in two separate photomixer conf
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Objective. Glass-ionomer and resin-modified glass-ionomer cements are versatile materials with the ability to form a direct bond with tooth tissues. The aim of this study was to formulate a novel class of dental bio-interactive restorative material (pRMGIC) based on resin-modified glass-ionomer cements via the inclusion of an organophosphorus monomer, ethylene glycol methacrylate phosphate, with a potential to improve the mechanical properties and also function as a reparative restorative material. Methods. pRMGIC was formulated with modification of the resin phase by forming mixes of ethylene glycol methacrylate phosphate (EGMP; 0–40%wt) and 2-hydroxyethyl methacrylate monomer into the liquid phase of a RMGIC (Fuji II LC, GC Corp.).
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The development of low profile gamma-ray detectors has encouraged the production of small field of view (SFOV) hand-held imaging devices for use at the patient bedside and in operating theatres. Early development of these SFOV cameras was focussed on a single modality—gamma ray imaging. Recently, a hybrid system—gamma plus optical imaging—has been developed. This combination of optical and gamma cameras enables high spatial resolution multi-modal imaging, giving a superimposed scintigraphic and optical image. Hybrid imaging offers new possibilities for assisting clinicians and surgeons in localising the site of uptake in procedures such as sentinel node detection. The hybrid camera concept can be extended to a multimodal detec
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The research aims mainly to the role of the statement style costs on the basis of activity based on performance (PFABC) to reduce production cost and improve the competitive advantage of economic units and industrial under the modern business environment dominated by a lot of developments and changes rapidly, which necessitates taking them and criticize them to ensure survival and continuity. The research problem is the inability of traditional cost methods of providing useful information to the departments of units to take many administrative decisions, particularly decisions related to the product and calculating the costs of the quality of the sound and the availability of the need and the ability to replace methods capa
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Many Iraqi students are reluctant to actively participate in the English
language classroom. This reluctance is attributed to a number of factors, above which
is students' lack of thinking skills necessary to express their points of view. This
eventually results in passive learning, a real problem in English language learning in
Iraq.
A need for educational reforms and innovations seems essential. These involve
developing relevant teaching materials, adopting learner-centered approach,
promoting learner autonomy, and enhancing critical thinking.
This study is hoped to assist teachers of English to initiate change and foster
the expansion of thinking, and adopt various new strategies to increase classroom
par