The separation of fluid-fluid mixtures is a major issue in various sectors. The liquid-liquid hydro-cyclone has a wide range of applications in various sectors due to its great efficiency in separating fluid mixtures, ease of installation, and low cost. In crude oil production, high water is consumed following the degrading of production quality, high processing costs, costs, and environmental impacts. Axial hydro cyclone is a tool for Downhole Oil/Water Separation (DOWS) in the petroleum production industry, but it has limitations. The main purpose of this work is to simulate the effect of compacting the conventional inline hydro cyclone with a converging-diverging nozzle on the oil/water dynamic flow and the separation process to

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

This research aims to choose the appropriate  probability ‎ distribution  ‎‏‎ to the reliability‎        analysis‎ for  an   item through ‎ collected data for operating and stoppage  time of  the case  study.

    Appropriate choice for .probability distribution   is when  the data look to be on or  close the form fitting line for probability plot and test the data  for  goodness of fit .

     Minitab’s 17 software  was used ‎  for this  purpose after  arranging collected data and setting it in the the program‎.

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The cinematographer mediates through the means of cinema and television a set of elements complementing each other in the light of developments in various sciences, culture and arts for the purpose of conveying the meaning to the recipient and achieve aesthetic taste. Despite the diversity of cinematographic media with its multiple forms, The researcher started from the principle of definition and knowledge of a technical phenomenon that emerged in the cinematographic medium through the treatment of dramatic events through the solutions of the exit line depends on the narrative of events in one place contributes to attract Mam spectator since this interesting phenomenon in the mediator, there .van question arises the adoption of that vis

Nanoparticle has pulled in expanding consideration with the developing enthusiasm for nanotechnology which hold potential as essential segments for development applications. In the present work, a copper nanoparticle is manufactured as a suspension in distilled water by beating a bulk copper target with laser source (532 nm wavelength, 10 ns pulse duration and 10 Hz repletion rate) via method. UV- visible absorption spectra and AFM analysis has been done to observe the effect of repetition rate for the pulsation of laser. Copper nanoparticles (Cu-NPs) were successfully synthesized with green color. The Cu- NPs have very high purity because the preparation was managed in aqueous media to eliminate ambient contaminations.  Absorption

Background: The excess mortality associated with
rheumatoid arthritis is largely due to
cardiovascular disease. Rheumatoid arthritis is of
primary importance in atherogenesis. The intimamedia thickness of extracranial carotid arteries is a
measurable index of the presence of
atherosclerosis.
Objective: To assess carotid intima-media
thickness in rheumatoid arthritis by Doppler
ultrasound.
Methods: Fifty two Iraqi patients with rheumatoid
arthritis were studied and compared with another
fifty two, healthy individuals matched for age and
sex as a control group. Full history was taken and
complete clinical examination was done for all
individuals in both groups. Rheumatoid arthritis
diagnosis was

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardw