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
Polyacrylamide Solutions of different concentrations (0.2, 0.4, 0.6, 0.8, 1.0 %) of Ag nanoparticles and ZnO nanoparticles were prepared, the viscosities and surface tension were measured for all solutions, where measurements indicated an increase in these properties with increased concentration, where the relative viscosity of polyacrylamide/zinc nanoparticles increased from 1.275 to 2.243, and the relative viscosity of polyacrylamide/silver nanoparticles increased from 1.178 to 1.934. Viscosity is significant parameters during electrospinning process. While the surface tension of the polyacrylamide/zinc nanoparticles has changed from 0.0343 Nm-1 to .0.0.0 Nm-1 and changed from .0.000Nm-1 to.0.0.0 Nm-1. Also the constants KH and KK were
... Show More
(1)
This study compared the effects of citric acid (CA) derived from microbial fermentation using Aspergillus niger (400 mg kg-1) and natural extraction from Citrus limon (400 mg kg1) in albino mice. Parameters assessed included cytogenetic damage via the micronucleus (MN) assay, immunological response through immunoglobulin (IgA, IgG, IgM) titers, and hepatoprotective activity based on liver enzyme levels (AST, ALT, ALP) and histopathological inves tigation. Mice were divided into six groups (n=10/group) as follows: (1) negative control, (2) carbon tetrachloride (CCl₄ 0.02%), (3) lemon CA, (4) A. niger, (5) CCl₄ + lemon CA, and (6) CCl₄ + A. niger CA. The CCl4 group exhibited a significantly higher MN frequency (0.06 ± 0.008) compa
... Show More
(6)
(6)
Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
... Show More
(24)
(18)
(9)
(8)
Soft red winter wheat (SRW) is characterized by high yield and relatively low protein content. In Kentucky, there is growing demand from local artisan bread bakers for regionally produced flour, requiring production of grain with increased protein content and/or strength. The objective of this two-year field experiment was to evaluate the effect of nitrogen (N) management on five cultivars of winter wheat on yield and bread baking quality traits of modern and landrace SRW cultivars (Triticum aestivum L.). All five cultivars were evaluated using two N application rates in conventional and organic production systems. All traits measured were significantly affected by the agricultural production system and N rate, although plant height
... Show More
(6)
(7)
One of the most important parameters determining structural members' durability and strength is the fire flame's influence and hazard. Some engineers have advocated using advanced analytical models to predict fire spread impact within a compartment and considering finite element models of structural components to estimate the temperatures within a component using heat transfer analysis. This paper presented a numerical simulation for a reinforced concrete beam’s structural response in a case containing Water Absorbing Polymer Spheres (WAPS) subjected to fire flame effect. The commercial finite element package ABAQUS was considered. The relevant geometrical and material parameters of the reinforced concrete beam model a
... Show More
(4)
(3)
(9)
Two experiments were carried out, the first at the College of Agriculture - University of Baghdad during spring season 2017 Everest cv. class (Elite) was used to study the effect of foliar application of calcium and magnesium and addition of humic acid to the soil on potato growth and yield, The layout of the experiment was factorial within RCBD design using three replicates. Calcium and Magnesium sprayed with concentrations (0, 500, 1000 mg.L-1), while the humic acid was added to the soil with (0, 0.75 gm.m2), The second experiment included storage of tubers produced from the spring season, with to study the effect of field treatments on improving the storability of the tubers. The results showed that the treatment of calci
... Show More
(10)
(2)
Fifty-Four paddy samples, 45 soil samples, and nine irrigation water samples of some paddy fields at Alfurat Alawsat Area, Iraq were collected to investigate the microbial quality including total count bacteria (TCB), molds and yeast, total coliform (TC), and E. coli bacteria. Paddy samples were processed at the laboratory level to produce rice at 32 and 36 whiteness, and the microbial quality of the produced rice was conducted too. The results showed that all irrigation water samples were overpassed the FDA limit for E. coli. All paddy samples were exceeded the good limit of TCB, but no sample exceeded the acceptable limit. Most paddy samples were exceeded the FDA limit for molds and yeast, and few paddy samples exc
... Show More
(2)