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
Medication safety is an important part of the comprehensive patient safety term. Medication safety is gaining more attention as the World Health Organization set the goal of decreasing medication harm by (50%) for the next 5 years when launching the third global challenge. Studying medication safety in the risk groups such as young ages, children are crucial to learn more about the effect of medicines in this risk group since they are not included in the clinical trials. Adverse drug reaction is defined as any harm resulted from the drug itself during medical process journey, while medication errors are any harm resulted from the treatment process rather than the drug or it is the result of the failure in a step of the treatment process
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very
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A true random TTL pulse generator was implemented and investigated for quantum key distribution systems. The random TTL signals are generated by low cost components available in the local markets. The TTL signals are obtained by using true random binary sequences based on registering photon arrival time difference registered in coincidence windows between two single – photon detectors. The true random TTL pulse generator performance was tested by using time to digital converters which gives accurate readings for photon arrival time. The proposed true random pulse TTL generator can be used in any quantum -key distribution system for random operation of the transmitters for these systems
Photonic crystal fiber interferometers (PCFIs) are widely used for sensing applications. This work presented solid core-PCFs based on Mach-Zehnder modal interferometer for sensing refractive index. The general structure of sensor was applied by splicing short lengths of PCF in both sides with conventional single mode fiber (SMF-28).To apply modal interferometer theory collapsing technique based on fusion splicing used to excite higher order modes (LP01 and LP11). A high sensitive optical spectrum analyzer (OSA) was used to monitor and record the transmitted wavelength. This work studied a Mach-Zahnder interferometer refractive index sensor based on splicing point tapered SMF-PCF-SMF. Relation between refractive index sensitivity and tape
... Show MoreA calamitic symmetric liquid crystalline consisting of an azo group containing 5H-Thiazolo[3,4-b][1,3,4]thiadiazole moiety compound[III] was synthesized via sequence reactions starting from reaction terephthaldehyde with mercaptoacetic acid and thiosemicarbazide in the presence of concentrated sulfuric acid to synthesized 5,5'-(1,4-phenylene)bis(5Hthiazolo[4,3-b][1,3,4]thiadiazol-2-amine)[I] then the azo compound [II] synthesized by coupling between diazonium salt of the compound [I] with phenol at (0-4) ̊C., after that the compound [III] was synthesized by the reaction of the compound [II] with methyl bromide in alkaline media. The compounds are characterized by melting points, FTIR and 1HNMR spectroscopy. The mesomorphic behavior was stu
... Show MorePhotonic Crystal Fiber Interferometers (PCFIs) are widely used for sensing applications. This work presents the fabrication and study the characterization of a relative humidity sensor based on a polymer-infiltrated photonic crystal fiber that operates in a Mach- Zehnder Interferometer (MZI) reflection mode. The fabrication of the sensor only involves splicing and cleaving Photonic Crystal Fiber (PCF) with Single Mode Fiber (SMF). A stub of (LMA-10) PCF spliced to SMF (Corning-28). In the splice regions. The PCFI sensor operation based on the adsorption and desorption of water vapour at the silica-air interface within the PCF. The sensor shows a high sensitivity to RH variations from (27% RH - 95% RH), with a change in its reflected powe
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Prediction of the formation of pore and fracture pressure before constructing a drilling wells program are a crucial since it helps to prevent several drilling operations issues including lost circulation, kick, pipe sticking, blowout, and other issues. IP (Interactive Petrophysics) software is used to calculate and measure pore and fracture pressure. Eaton method, Matthews and Kelly, Modified Eaton, and Barker and Wood equations are used to calculate fracture pressure, whereas only Eaton method is used to measure pore pressure. These approaches are based on log data obtained from six wells, three from the north dome; BUCN-52, BUCN-51, BUCN-43 and the other from the south dome; BUCS-49, BUCS-48, BUCS-47. Along with the overburden pressur
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Photonic Crystal Fiber Interferometers (PCFIs) are widely used for sensing applications. This work presents the fabrication and the characterization of a relative humidity sensor based on a polymer-coated photonic crystal fiber that operates in a Mach- Zehnder Interferometer (MZI) transmission mode. The fabrication of the sensor involved splicing a short (1 cm) length of Photonic Crystal Fiber (PCF) between two single-mode fibers (SMF). It was then coated with a layer of agarose solution. Experimental results showed that a high humidity sensitivity of 29.37 pm/%RH was achieved within a measurement range of 27–95%RH. The sensor also showed good repeatability, small size, measurement accuracy and wide humidity range. The RH sensitivity o
... Show MoreThe Atmospheric Infrared Sounder (AIRS) on EOS/Aqua satellite provides diverse measurements of Methane (CH4) distribution at different pressure levels in the Earth's atmosphere. The focus of this research is to analyze the vertical variations of (CH4) volume mixing ratio (VMR) time-series data at four Standard pressure levels SPL (925, 850, 600, and 300 hPa) in the troposphere above six cities in Iraq from January 2003 to September 2016. The analysis results of monthly average CH4VMR time-series data show a significant increase between 2003 and 2016, especially from 2009 to 2016; the minimum values of CH4 were in 2003 while the maximum values were in 2016. The vertical distribution of CH4<
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