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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
Tue Oct 12 2021
Journal Name
Innovative Infrastructure Solutions
Facilitating claims settlement using building information modeling in the school building projects
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Publication Date
Thu Nov 29 2018
Journal Name
Al-khwarizmi Engineering Journal
Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
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Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Optimization of Cutting Parameters on Delamination of Drilling Glass-Polyester Composites
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This paper attempted to study the effect of cutting parameters (spindle speed and feed rate) on delamination phenomena during the drilling glass-polyester composites. Drilling process was done by CNC machine with 10 mm diameter of high-speed steel (HSS) drill bit. Taguchi technique with L16 orthogonal layout was used to analyze the effective parameters on delamination factor. The optimal experiment was no. 13 with spindle speed 1273 rpm and feed 0.05 mm/rev with minimum delamination factor 1.28.                                       &

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Publication Date
Fri Jun 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Improving of Design Parameters of an Industrial Continuous Catalytic Reforming Reactors
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Catalytic reforming of naphtha occupies an important issue in refineries for obtaining high octane gasoline and aromatic compounds, which are the basic materials of petrochemical industries. In this study, a novel of design parameters for industrial continuous catalytic reforming reactors of naphtha is proposed to increase the aromatics and hydrogen productions. Improving a rigorous mathematical model for industrial catalytic reactors of naphtha is studied here based on industrial data applying a new kinetic and deactivation model. The optimal design variables are obtained utilizing the optimization process in order to build the model with high accuracy and such design parameters are then applied to get the best configuration of this pro

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Publication Date
Sat Aug 12 2017
Journal Name
Journal Of Engineering
Influence of Temperature Upon Permanent Deformation Parameters of Asphalt Concrete Mixes
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        The performance of asphalt concrete pavement has affected by many factors, the temperature is the most important environmental one which has a large effect on the structural behavior of flexible pavement materials. The main cause of premature failure of pavement is the rutting, Due to the viscoelastic nature of the asphalt cement, rutting is more pronounced in hot climate areas because the viscosity of the asphalt binder which is
inversely related to rutting is significantly reduced with the increase in temperature resulting in a more rut susceptible paving mixtures. The objective of this study is to determine the effect of temperatures variations on the permanent deformation parameters (perm

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Publication Date
Fri Jul 28 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Effect of Benzene on Some haeMatological Parameters of Oil Station Workers
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  Benzene is a hydrocarbon chemical consisting of six atoms arranged in a ring structure. At normal ambient temperatures; it is a liquid, which evaporates rapidly at room temperature and is highly flammable. It has a characteristic of aromatic odor and is slightly soluble in water (1.5 g/liter at 20ºC) but miscible with most other organic solvents [1].           Long-term inhalation of benzene causes blood disorders. It specifically affects bone marrow [2]. And it may cause anemia, excessive bleeding, damage to the immune system and DNA [3, 4]. Increased incidence of leukemia (cancer of the tissues that form white blood cells) has been observed in people occupationally exposed to

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Publication Date
Sat Oct 01 2016
Journal Name
Arpn Journal Of Engineering And Applied Sciences
Numerical and experimental analysis of transient temperature and residual thermal stresses in friction stir welding of aluminum alloy 7020-T53
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Scopus
Publication Date
Sun Jul 23 2023
Journal Name
University Of Samarra
Synthesis, spectral characterization and thermal ‎study of complexes of ions of some metallic ‎elements with new cyclic ligands
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The purpose of my thesis is to prepare four new ligands (L1-L4) that have been ‎used to prepare a series of metal complexes by reacting them with metal ions:‎ ‎ M=(Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), Hg(II) ‎ ‎ Where succinyl chloride was used as a raw material for the preparation of ‎bi-dented ligands (L1-L4) by reacting it with potassium thiocyanate as a first ‎step and then reacting with (2-aminobenzothiazole, Benzylamine, 4-‎aminoantipyrine, Sulfamethoxazole) respectively as a second step with the use ‎of dry acetone as a solvent, the chemical formula of the four ligands prepared in ‎succession:‎ N1,N4-bis(benzo[d]thiazol-2-ylcarbamothioyl)succinamide (L1)‎ N1,N4-bis(benzylcarbamothioyl)succinami

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Publication Date
Fri Jun 14 2024
Journal Name
The Ukrainian Biochemical Journal
PREX proteins level correlation with insulin resistance markers and lipid profile in obese and overweight non-diabetic patients
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Metabolic dysregulation and obesity are associated with many metabolic alterations, including impairment of insulin sensitivity and dyslipidemia. Recent studies highlight the key role of phosphatidylinositol 3,4,5-triphosphate-dependent Rac exchange proteins (PREX proteins) in the pathogenesis of obesity, advocating further elucidation of their potential therapeutic implications. The present study aimed to estimate the serum level of PREX proteins and its potential association with insulin resistance markers and plasma lipids level in obese and overweight non-diabetic patients. The study included 30 persons classified as obese, 30 as overweight, and 30 healthy individuals of similar age and gender. The levels of PREX1 and PREX2 were

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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Application of Box-Behnken Method Based ANN-GA to Prediction of wt.% of Doping Elements for Incoloy 800H Coated by Aluminizing-Chromizing
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In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg

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