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Experimental and Prediction Using Artificial Neural Network of Bed Porosity and Solid Holdup in Viscous 3-Phase Inverse Fluidization
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In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid velocities and liquid viscosity. Solid holdup with "low density particles" shows a higher numerical quantity "than that in the beds" with "high density". Levenberg-Marquardt back propagation of "artificial neural network (ANNs)" was utilized to predict the bed porosity and solid holdup. The expected values are in an excellent relationship with the experimental values, where the advanced model is high-fidelity and own a large capacity to predict bed porosity and solid holdup.

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Competitive Study Using UV and Ozone with H2O2 in Treatment of Oily Wastewater
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          In this study, ultraviolet (UV), ozone techniques with hydrogen peroxide oxidant were used to treat the wastewater which is produced from South Baghdad Power Station using lab-scale system. From UV-H2O2 experiments, it was shown that the optimum exposure time was 80 min. At this time, the highest removal percentages of oil, COD, and TOC were 84.69 %, 56.33 % and 50 % respectively. Effect of pH on the contaminants removing was studied in the range of (2-12). The best oil, COD, and TOC removal percentages (69.38 %, 70 % and 52 %) using H2O2/UV were at pH=12. H2O2/ozone experiments exhibited better performance compared to

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Publication Date
Wed Aug 28 2019
Journal Name
Journal Of Engineering
Evaluation of Heavy Metals Content in Simulated Solid Waste Food Compost
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Composting is one of the solid waste management (SWM) methods where the organic component decomposed biologically under controlled conditions. In this study, a 0.166 m3 bioreactor tank was designed to compose 59.2Kg of simulated common municipal solid food waste having a bulk density, organic matter, organic carbon, pH, nitrogen content, C/N and nitrification index (NH4-N/ NO3-N) of 536.62 kg/m3, 62.34%, 34.76%, 6.53, 1.86%, 23 and 0.34 respectively. The bioreactor operated aerobically for 30 days, and anaerobically for 70 days, until the end of the composting process. Results proved that the composting process could reduce the mass of the waste by 69%.  Nitrogen content,

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Publication Date
Wed Mar 23 2022
Journal Name
Modern Sport
Using Artificial intelligence to evaluate skill performance of some karate skills
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Human beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.

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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Wed Nov 06 2024
Journal Name
2024 17th International Conference On Development In Esystem Engineering (dese)
Improving Cardiovascular Prediction Performance Using Machine Learning Based Feature Selection
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Publication Date
Thu Apr 11 2024
Journal Name
Russian Journal Of Infection And Immunity
MATRIX METALLOPROTEINASES -3 (MMP-3) SERUM LEVEL AND GENETIC POLYMORPHISMS ASSOCIATED WITH RHEUMATOID ARTHRITIS
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Abstract Introduction: MMP3 plays a crucial role in the process of bone erosion in the pathomechanism of rheumatoid arthritis (RA). It acts by removing the outer osteoid layer, which allows the osteoclasts to tightly connect and carry out the subsequent damage to the underlying bone. MMP3 can trigger the production of other MMPs like MMP-1, MMP-7, and MMP-9, it plays a pivotal role in the remodeling of connective tissues. Aim of the study: to assess the influence of MMP-3 serum levels and single-nucleotide polymorphisms of rs679620 in the rheumatoid arthritis patients' group in comparison to the control group. Subjects: eighty eight samples, 45 rheumatoid arthritis patients after being referred by their treating physician for regular RA

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Publication Date
Tue Mar 01 2022
Journal Name
Iraqi Journal Of Physics
The Confinement Profile Effect on the Optical Properties in Different Inverse-shaped Single InGaN/GaN Quantum Wells
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In this work, the effects of size, and temperature on the linear and nonlinear optical properties in InGaN/GaN inverse parabolic and triangular quantum wells (IPQW and ITQW) for different concentrations at the well center were theoretically investigated. The indium concentrations at the barriers were fixed to be always xmax = 0.2. The energy levels and their associated wave functions are computed within the effective mass approximation. The expressions of optical properties are obtained analytically by using the compact density-matrix approach. The linear, nonlinear, and total absorption coefficients depending on the In concentrations at the well center are investigated as a function of the incident photon energy for different

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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
Experimental and Numerical Investigation of Creep Behavior In Isotropic Composites
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Creep testing is an important part of the characterization of composite materials. It is crucial to determine long-term deflection levels and time-to-failure for these advanced materials. The work is carried out to investigate creep behavior on isotropic composite columns. Isotropy property was obtained by making a new type of composite made from a paste of particles of carbon fibers mixed with epoxy resin and E-glass particles mixed with epoxy resin. This type of manufacturing process can be called the compression mold composite or the squeeze mold composite. Experimental work was carried out with changing the fiber concentration (30, 40 and 50% mass fraction), cross section shape, and type of composite. The creep results showed that th

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence to Enhance Digital Media Literacy Competencies and its Role in Shaping Media Students’ Awareness of Cybersecurity: A Survey Study
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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
Financial Variables and Their Effects on The Development of Bank Credit and Productive Sectors in Iraq Using a Path Analysis Model
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This study aims to measure and analyze the direct and indirect effects of the financial variables, namely (public spending, public revenues, internal debt, and external debt), on the non-oil productive sectors with and without bank credit as an intermediate variable, using quarterly data for the period (2004Q1–2021Q4), converted using Eviews 12. To measure the objective of the study, the path analysis method was used using IBM SPSS-AMOS. The study concluded that the direct and indirect effects of financial variables have a weak role in directing bank credit towards the productive sectors in Iraq, which amounted to (0.18), as a result of market risks or unstable expectations in the economy. In addition to the weak credit ratings of borr

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