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
The present research was conducted to synthesis Y-Zeolite by sol-gel technique using MWCNT (multiwalled carbon nanotubes) as crystallization medium to get a narrow range of particle size distribution with small average size compared with ordinary methods. The phase pattern, chemical structure, particle size, and surface area were detected by XRD, FTIR, BET and AFM, respectively. Results shown that the average size of Zeolite with and without using MWCNT were (92.39) nm and (55.17) nm respectively .Particle size range reduced from (150-55) nm to (130-30) nm. The surface area enhanced to be (558) m2/g with slightly large pore volume (0.231) km3/g was obtained. Meanwhile, degree of crystallization decrease
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The aim of this work was to estimate the concentrations of natural and artificial nuclides in some fertilized and unfertilized plant samples. These samples were collected and prepared in a petri dish for the measurements using gamma spectroscopy. The average values of 238U, 232Th, 40K, and 137Cs for the unfertilized plant samples were (11.964 ± 3.226, 8.273 ± 2.639, 402.436 ± 18.099, and 2.761 ± 1.613) respectively, and for the fertilized plant samples were (30.434 ± 5.282, 22.584 ± 4.620, 711.332 ± 25.806, and 6.986 ± 2.542) respectively. The average values of radiological hazard indices, Raeq, D, D for 137Cs, (AEDE)in, (AEDE)out, Iγ, Hin, and Hout for the unfertilized plant samples were (54.782 ± 7.216, 27.306, 0.469, 0.
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Background: Determination of local bone mineral density (BMD) immediately after implant insertion play an important role in implant success rate, may offer comprehensive description of the bone, and give enough information to the surgeon prior to implant insertion and at follow up status. The aim of the present study is to evaluate the changes of local bone density in the dental implant recipient sites by using computerized tomography. Material and method: The sample consisted of (20) dental implants recipient sites, bone density assessment was done twice, immediately after implants insertion and after six months. Results: The mean HU of the bone around the implant insertion site, immediately after implant placement was 552.28 HU, and inc
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Depletion of fossil fuel is one of the main reasons why the bioethanol has become popular. It is a renewable energy source. In order to meet the great demand of bioethanol, it is best that the bioethanol production is from cheap raw materials. Since the golden shower fruit is not being utilized and is considered as waste material, hence, this study was conducted to make use of the large volume of the residue as feedstock to test its potential for bioethanol extraction.The main goal of this study is to obtain the most volume of bioethanol from the golden shower fruit liquid residue by the factors, days of fermentation (3, 5, and 7 days) and sugar concentration (15, 20 and 25 brix) of the liquid residue. Also, part of the study is to compu
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The present study aimed to investigate the acetamiprid effects on biochemical aspects in albino mice. Thirty albino mice at the age of 6-8 weeks and average weight 25±5 g were divided into three groups each having ten (10) healthy mice. The first group was orally administrated with distilled water while the second and third groups were orally administrated with 50 mg/mL and 100 mg/mL respectively of acetamprid (0.1 mL) daily for one week. LD50 of acetamiprid was measured and found to be 200 mg/kg. The parameters of evaluations included liver function using Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT) and Alkaline Phosphatase (ALP). Lipid profile was anal
... Show MoreThe physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t
... Show MoreTo improve the efficiency of a processor in recent multiprocessor systems to deal with data, cache memories are used to access data instead of main memory which reduces the latency of delay time. In such systems, when installing different caches in different processors in shared memory architecture, the difficulties appear when there is a need to maintain consistency between the cache memories of different processors. So, cache coherency protocol is very important in such kinds of system. MSI, MESI, MOSI, MOESI, etc. are the famous protocols to solve cache coherency problem. We have proposed in this research integrating two states of MESI's cache coherence protocol which are Exclusive and Modified, which responds to a request from reading
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This research aims to develop new spectrophotometric analytical method to determine drug compound Salbutamol by reaction it with ferric chloride in presence potassium ferricyanide in acid median to formation of Prussian blue complex to determine it by uv-vis spectrophotmetric at wavelengths rang(700-750)nm . Study the optimal experimental condition for determination drug and found the follows: 1- Volume of(10M) H2SO4 to determine of drug is 1.5 ml . 2- Volume and concentration of K3Fe(CN)6 is 1.5 ml ,0.2% . 3- Volume and concentration of FeCl3 is 2.5ml , 0.2%. 4- Temperature has been found 80 . 5- Reaction time is 15 minute . 6- Order of addition is (drug + K3Fe(CN)6+ FeCl3 + acid) . Concentration rang (0.025-5 ppm) , limit detecti
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