Ultrasound imaging has some problems with image properties output. These affects the specialist decision. Ultrasound noise type is the speckle noise which has a grainy pattern depending on the signal. There are two parts of this study. The first part is the enhancing of images with adaptive Weiner, Lee, Gamma and Frost filters with 3x3, 5x5, and 7x7 sliding windows. The evaluated process was achieved using signal to noise ratio (SNR), peak signal to noise ratio (PSNR), mean square error (MSE), and maximum difference (MD) criteria. The second part consists of simulating noise in a standard image (Lina image) by adding different percentage of speckle noise from 0.01 to 0.06. The supervised classification based minimum distance method is used to evaluate the results depending on selecting four blocks located at different places on the image. Speckle noise was added with different percentage from 0.01 to 0.06 to calculate the coherent noise within the image. The coherent noise was concluded from the slope of the standard deviation with the mean for each noise. The results showed that the additive noise increased with the slide window size, while multiplicative noise did not change with the sliding window nor with increasing noise ratio. Wiener filter has the best results in enhancing the noise.
In the present work, Uranium (238U), Thorium (232Th) and Potassium (40K) specific activity concentration in (Bq/kg) was measured in five different types for wheat flours that are available in the Iraqi markets. The gamma spectrometry method with an NaI (Tl) detector has been used for radiometric measurements. Calculations of radium equivalent activity, annual effective dose equivalent, external hazard index (Hex), internal hazard index (Hin), representing gamma index and gamma dose rate in all flour samples were 17.98132 Bq/kg, 0.0100334, 0.04502, 0.04857, 0.06872, 0.125883 and 8.181244 respectively. It is found that the average of specific activity concentration of wheat flour sam
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreThe necessary optimality conditions with Lagrange multipliers are studied and derived for a new class that includes the system of Caputo–Katugampola fractional derivatives to the optimal control problems with considering the end time free. The formula for the integral by parts has been proven for the left Caputo–Katugampola fractional derivative that contributes to the finding and deriving the necessary optimality conditions. Also, three special cases are obtained, including the study of the necessary optimality conditions when both the final time and the final state are fixed. According to convexity assumptions prove that necessary optimality conditions are sufficient optimality conditions.
... Show MoreRock engineers widely use the uniaxial compressive strength (UCS) of rocks in designing
surface and underground structures. The procedure for measuring this rock strength has been
standardized by both the International Society for Rock Mechanics (ISRM) and American Society
for Testing and Materials (ASTM), Akram and Bakar(2007).
In this paper, an experimental study was performed to correlate of Point Load Index ( Is(50))
and Pulse Wave Velocity (Vp) to the Unconfined Compressive Strength (UCS) of Rocks. The effect
of several parameters was studied. Point load test, Unconfined Compressive Strength (UCS) and
Pulse Wave Velocity (Vp) were used for testing several rock samples with different diameters.
The predicted e
In the present work, the focusing was on the study of the x-ray diffraction, dielectric constant, loses dielectric coefficient, tangent angle, alter- natively conductivity and morphology of PET/BaTio3. The PET/BaTio3 composite was prepared for polyethylene terephthalate PET polymer composite containing 0, 10, 20, 30, 40, 50, and 60 wt. % from Barium titanate BaTi03 powder. The composite of two materials leads to form mixing solution and hot-pressing method. The effect of BaTio3 on the structure and dielectric properties with morphology was studied on PET matrix polymer using XRD, LCR meter and SEM.
The study was carried out by reinforcing the resin matrix material
which was (Epoxy- Ep828) by useing Kevlar fibers and glass fibers type (E-gl ass) both or them in the form of woven roving and poly propylene tlbcrs in the form chopped strand mats. wi th (30%) volume fraction. Some mechan i cal properties of the were prepared composite specimens U ltraviolet radiation were stuied after being subjected to different weathering conditi ons i ncluded. Compression and hardness testing were carried out using Briel! method so as to compare between composite behavior i n the environments previously mentioned .
<
... Show MoreFine aggregates used for concrete works in Sulaymaniyah city frequently fail to meet the standard requirements for gradation and fineness modulus in cement concrete. This paper aims to critically evaluate gradation, fineness modulus, and clay contents of various natural sands produced and used for concrete work in the region. Sixteen field sand samples were collected from various sites in Darbandikhan (5 samples), Qalat Dizah (5 samples), Koysinjaq (5 samples), and Piramagroon (1 sample) confirming to ASTM D75. The field samples were parted into test specimens based on ASTM C702. Then, sieve analysis was carried out on the oven-dry test specimens in compliance with ASTM C136. The test results of fine aggregates wer
... Show More