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Artificial intelligence‐based modeling of novel non‐thermal milk pasteurization to achieve desirable color and predict quality parameters during storage
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Abstract<sec><label></label><p>This study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (<italic>p</italic> > 0.05) for lightness (<italic>L</italic>*), redness‐greenness (<italic>a</italic>*), yellowness‐blueness (<italic>b</italic>*), total color differences (∆<italic>E</italic>), hue angle (<italic>h</italic>), chroma (<italic>C</italic>), whiteness (WI), yellowness (YI), and browning index (BI). ANFIS well‐predicted milk fat and moisture content using quadratic and two‐factor interaction models with mean errors of .00858–.01260 and correlation coefficient of .8051–.8205. Stability tests showed <italic>L</italic>* and WI reduced while <italic>a</italic>*, <italic>b</italic>*, Δ<italic>E</italic>, <italic>h</italic>, <italic>C</italic>, YI, and BI increased during the storage. NP milk had 77.21% higher half‐life than CP, as predicted by ANFIS modeling. Findings indicated milk quality characteristics could be estimated based on physical parameters (e.g., color components), contributing to sustainable food production.</p></sec><sec><title>Practical applications

The findings offer practical applications of artificial intelligence (AI) as an innovative monitoring and prediction technique to enhance food quality and sustainability. The proposed methodology makes the real‐time prediction of milk quality feasible by leveraging AI and physical parameters. An adaptive neuro‐fuzzy inference system (ANFIS) accurately predicts moisture and fat contents according to color values, facilitating quality assessment. Stability tests during cold storage provide insights into milk quality changes over time, aiding in determining key parameters in predictive modeling. The proposed approach was found to be applicable to both conventional and non‐thermal pasteurized milk. This study also provides a step‐by‐step protocol, facilitating the implementation of emerging technologies in the food industry.

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Engineering
Seismic Effects and Static Analysis for the Artificial Damped Outrigger Systems in Tall R.C Buildings
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This paper studies the combination fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. It works by connecting the central core, comprising either shear walls or braced frames, to the outer perimeter columns.

     The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model, and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximum lateral load at the top of the building is calculated, and  this load  w

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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Publication Date
Tue Jul 17 2018
Journal Name
International Journal Of Adaptive Control And Signal Processing
Single channel informed signal separation using artificial-stereophonic mixtures and exemplar-guided matrix factor deconvolution
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Publication Date
Mon Nov 01 2021
Journal Name
Energies
Solidification Enhancement in a Triple-Tube Latent Heat Energy Storage System Using Twisted Fins
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This work evaluates the influence of combining twisted fins in a triple-tube heat exchanger utilised for latent heat thermal energy storage (LHTES) in three-dimensional numerical simulation and comparing the outcome with the cases of the straight fins and no fins. The phase change material (PCM) is in the annulus between the inner and the outer tube, these tubes include a cold fluid that flows in the counter current path, to solidify the PCM and release the heat storage energy. The performance of the unit was assessed based on the liquid fraction and temperature profiles as well as solidification and the energy storage rate. This study aims to find suitable and efficient fins number and the optimum values of the Re and the inlet tem

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Publication Date
Sun Sep 01 2024
Journal Name
Journal Of Energy Storage
Nanofluid-assisted enhanced sealing security for efficient geological hydrogen storage in Saudi Arabian basalt
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The modification of hydrophobic rock surfaces to the water-wet state via nanofluid treatment has shown promise in enhancing their geological storage capabilities and the efficiency of carbon dioxide (CO2) and hydrogen (H2) containment. Despite this, the specific influence of silica (SiO2) nanoparticles on the interactions between H2, brine, and rock within basaltic formations remains underexplored. The present study focuses on the effect of SiO2 nanoparticles on the wettability of Saudi Arabian basalt (SAB) under downhole conditions (323 K and pressures ranging from 1 to 20 MPa) by using the tilted plate technique to measure the contact angles between H2/brine and the rock surfaces. The findings reveal that the SAB's hydrophobicity intensif

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Publication Date
Sun Dec 01 2019
Journal Name
Computers And Electronics In Agriculture
Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
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Publication Date
Sun Dec 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Comparison between the effects of Aloe vera and chlorhexidine on clinical periodontal parameters
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Background: Periodontal diseases are one of the major dental pathologies that affect human populations worldwide at high prevalence rates The term periodontal disease usually refers only to plaque related inflammatory disease of the dental supporting tissues. Mouth rinses which act as an anti-plaque agents mostly used as adjuncts to oral hygiene. Aims of the study: To Estimate and compare the effects of Aloe vera relative to chlorhexidine on the clinical periodontal parameters (plaque index, gingival index, bleeding on probing). Material and method: A total of 44 subjects with plaque-induced gingivitis, baseline of data were collected for (PLI, GI, and BOP) and underwent oral hygiene instruction, scaling and polishing, then divided into:

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Determination the dispersion parameters and urbach tail of iron chromate doped PMMA films
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Films of pure Poly (methyl methacrylate) PMMA and Iron chromate doped PMMA have been prepared using casting method. Transmission and absorptance spectra have been recorded in the wavelength range (300-900) nm, in order to calculate, single oscillator energy, dispersion energy proposed by Wemple - DiDomenico model, average oscillator strength, average oscillator wavelength. The refractive index data at infinite wavelength which was found to obey single oscillator model which was found to increase from 2.27-2.56 as the doping percentage increase. The decreasing in the optical energy gap which was found according to Tauc model were (3.74-3.63) eV , is in good agreement with that obtained by wimple-DiDomenico model. The inverse behavior comp

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Publication Date
Mon Jul 31 2023
Journal Name
Iraqi Geological Journal
Estimation of the Fracturing Parameters and Reservoir Permeability Using Diagnostic Fracturing Injection Test
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The term "tight reservoir" is commonly used to refer to reservoirs with low permeability. Tight oil reservoirs have caused worry owing to its considerable influence upon oil output throughout the petroleum sector. As a result of its low permeability, producing from tight reservoirs presents numerous challenges. Because of their low permeability, producing from tight reservoirs is faced with a variety of difficulties. The research aim is to performing hydraulic fracturing treatment in single vertical well in order to study the possibility of fracking in the Saady reservoir. Iraq's Halfaya oil field's Saady B reservoir is the most important tight reservoir. The diagnostic fracture injection test is determined for HF55using GOHFER soft

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Publication Date
Sat Sep 01 2018
Journal Name
Journal Of Pharmaceutical Sciences And Research
Evaluation of some biochemical and immunological parameters changes in Iraq male with toxoplasmosis
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A total of 33 Iraq male positive for Toxoplasmosis and Iraq male negative for Toxoplasmosis (controls) were studies to Evaluation of some biochemical and immunological parameters changes.The parameters included lipid profile such as (Cholesterol(C), Triglycerides(TG), High-Density Lipoprotein (HDL), Low-Density Lipoprotein (LDL) and very Low-Density Lipoprotein (VLDL) and complement component C3 and C4. The results revealed significant decrease in the total cholesterol, Triglycerides, LDL and non-significant in vLDL (129.96±1.63, 130.69± 2.80, 87.19±1.97, 29.24± 0.83 mg/dl respectively) and non-significant increase in HDL(24.22 ±0.62) mg/dl compared with control group(152.07± 1.63, 156.48± 6.55, 99.26 ±1.39, 31.49± 1.30 and 21.31±

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