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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
Sun Jul 09 2023
Journal Name
Journal Of Engineering
An Investigation into Thermal Performance of Mist Water System and The Related Consumption Energy
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Experimental tests were conducted to investigate the thermal performance (cooling effect) of water mist system consisting of 5μm volume median diameter droplets in reducing the heat gain entering a room through the roof and the west wall by reducing the outside surface temperature due to the evaporative cooling effect during the hot dry summer of Baghdad/Iraq. The test period
was Fifty one days during the months May, June, and July 2012. The single test day consists of 16 test hours starting from 8:00 am to 12:00 pm. The results showed a reduction range of 1.71 to 15.5℃ of the roof outside surface temperature and 21.3 to 76.6% reduction in the daily heat flux entering the room through the roof compared with the case of not using w

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study of the Thermal Diffusivity and Heat Capacity Concerning Some Duplex Stainless Steel
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Abstract

In the present work, thermal diffusivity and heat capacity measurements have been investigated in temperature range between RT and 1473 K for different duplex stainless steel supplied by Outokumpu Stainless AB, Sweden. The purpose of this study is to get a reliable thermophysical data of these alloys and to study the effect of microstructure on the thermal diffusivity and heat capacity value. Results show the ferrite content in the duplex stainless steel increased with temperature at equilibrium state. On the other hand, ferrite content increased with increasing Cr/Ni ratio and there is no significant effect of ferrite content on the thermal diffusivity value at room temperature. Furthermore, the heat capacity of all sam

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Publication Date
Mon Sep 11 2023
Journal Name
University Of Anbar‎
Synthesis, ‎Characterization and ‎Thermal Study ‎of new aza-‎macrocyclic ligands with ‎some transition metals
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12 membered Schiff base macrocyclic ligands, 6,7,14,15-tetra phenyl-1,2,3,4, 4a,8a, 9,10, 11,12, 12a,16a-dodecahydro dibenzo [b,h] [1,4,7,10] tetraazacyclododecine L1, and 14 membered Schiff base macrocyclic ligands, 6,8,15,17-tetramethyl-1,2,3,4, 4a,7,9a, 10,11,12,13,13a,16,18a-tetra decahydro dibenzo[b,i] [1, 4,8,11] cyclotetradecine tetraaza L2, 7,16-bis(2,4- dichloro benz ylidene)-6,8,15,17-tetra methyl-1,2,3,4, 4a,7,9a, 10, 11,12, 13, 13a,16,18a-tetra deca hydro dibenzo [b,i] [1,4,8,11] tetra azacyclo tetra decine L3 and 6,8,15, 17-tetramethyl-1,2,3, 4,4a,9a,10, 11,12,13,13a,18a-dodecahydro dibenzo [b,i] [1,4,8, 11] tetraazacyclo tetradecine (7,16-diylidene) bis(methanylyli dene) bis (N,N-dimethylaniline) L4 were synthesized by condens

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Publication Date
Sat Aug 31 2019
Journal Name
Iraqi Journal Of Physics
Investigation the effect of post deposition thermal treatment on properties P3HT and P3HT:PCBM blend.
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  This work reports the study of heat treatment effect on the structural, morphological, optical and electrical properties of poly [3-hexylthiophene] and its blend with [6,6]-phenyl C61 butyric acid methyl ester ( P3HT:PC61BM). X-ray diffraction (XRD) measurements show that the crystallinity of the films increased with annealing. The evaluation of surface roughness and morphology was investigated using atomic force microscope (AFM), and field emission scanning microscope(FESEM). The optical properties were emphasized a strong optical absorption of P3HT compared with the blend. Hall effect measurement was used to study the electrical properties which revealed there is an increase in the electrical conductivity and Hall mobility of th

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Publication Date
Fri Jun 01 2018
Journal Name
Materials Science-poland
Thermal and electrical properties of polyimide/PANI nanofiber composites prepared via in situ polymerization
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Abstract<p> Polyimide/polyaniline nanofiber composites were prepared by in situ polymerization with various weight percentages of polyaniline (PANI) nanofibers. X-ray diffraction (XRD) and Fourier transform infrared spectra (FT-IR), proved the successful preparation of PANI nanofiber composite films. In addition, thermal stability of PI/PANI nanofiber composites was superior relative to PI, having 10 % gravimetric loss in the range of 623 °C to 671 °C and glass transition temperature of 289 °C to 297 °C. Furthermore, the values of the loss tangent tanδ and AC conductivity σAC of the nanocomposite films were notably higher than those of pure polyimide. The addition of 5 wt.% to 15 wt.% PANI</p> ... Show More
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Publication Date
Sun Jan 01 2012
Journal Name
Tikrit Journal For Dental Sciences
Microleakage Evaluation of a Silorane-Based and Methacrylate-Based Packable and Nanofill Posterior Composites (in vitro comparative study)
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This study compared in vitro the microleakage of a new low shrink silorane-based posterior composite (Filtek™ P90) and two methacrylate-based composites: a packable posterior composite (Filtek™ P60) and a nanofill composite (Filtek™ Supreme XT) through dye penetration test. Thirty sound human upper premolars were used in this study. Standardized class V cavities were prepared at the buccal surface of each tooth. The teeth were then divided into three groups of ten teeth each: (Group 1: restored with Filtek™ P90, Group 2: restored with Filtek™ P60, and Group 3: restored with Filtek™ Supreme XT). Each composite system was used according to the manufacturer's instructions with their corresponding adhesive systems. The teeth were th

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Publication Date
Wed May 15 2019
Journal Name
Al-khwarizmi Engineering Journal
Rheological and Thermal Properties of Lubricating Oil Enhanced by the Effect of CuO and TiO2 Nano-Additives
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The specifications of lubricating oil are fundamentally the final product of materials that have been added for producing the desired properties. In this research, spherical nanoparticles copper oxide (CuO) and titanium oxides (TiO2) are added to SAE 15W40 engine oil to study the thermal conductivity, stability, viscosity of nano-lubricants, which are prepared at different concentrations of 0.1%, 0.2%, 0.5%, and 1% by weight, and also their pour point, and flash point as five quality parameters. The obtained results show that CuO nanoparticles in all cases, give the best functionality and effect on engine oil with respect to TiO2. With 0.1 wt. % concentration, the thermal conductivity of CuO/oil and TiO2/

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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
Tue Jan 01 2019
Journal Name
Lambert
The concept of Evil in J.R.R.Tolkien Novel Lord of the Rings
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Evil pervades the narrative scene in Tolkien. Hence; his major themes in The Lord of the Rings are shown to be the Evil Nature of Power, the Tyranny of Technology and War as a Destructive Agent. Evil is not as powerful as good. The Boethian conception of evil comes through evil beings such as Melkor Morgoth in The Silmarillion or Sauron ,who cannot do good things but only pervert or mock things; In The Lord of the Rings; Tolkien seems to suggest that there is no absolute evil. The other conception of evil is the Manichaen, a conception which receives more emphasis in Tolkien's trilogy and which sees the world as a battle-ground for warring forces of good and evil. Tolkien frequently personifies the Ring as if it were acting with a will of i

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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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