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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
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Wed Sep 30 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of Auditing Quality on the Earnings Quality: (An applied research in a sample of private joint stock companies listed on the Iraq Stock Exchange)
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The research aims to measure the impact of the quality of the audit on the Earnings Quality, for a sample of private joint stock companies listed on the Iraq Stock Exchange, as the research sample included (14) private and listed joint stock companies in issuing their financial statements for the period from (2010-2018), as well as companies The audit offices in charge of auditing these companies, which number (18) companies or an audit office, and the research relied on two main models for measurement, as the first model reflects the assumed relationship between independent variables represented in the characteristics of external audit quality and measuring the extent of its impact on the dependent variable represented in the Ea

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Publication Date
Fri Aug 30 2019
Journal Name
Environmental Engineering Research
Numerical modeling of two-dimensional simulation of groundwater protection from lead using different sorbents in permeable barriers
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This study is to investigate the possibility of using activated carbon prepared from Iraqi date-pits (ADP) which are produced from palm trees (Phoenix dactylifera L.) as low-cost reactive material in the permeable reactive barrier (PRB) for treating lead (Pb<sup>+2</sup>) from the contaminated groundwater, and then compare the results experimentally with other common reactive materials such as commercial activated carbon (CAC), zeolite pellets (ZP). Factors influencing sorption such as contact time, initial pH of the solution, sorbent dosage, agitation speed, and initial lead concentration has been studied. Two isotherm models were used for the description of sorption data (Langmuir and Freundlich). The maximum lead sorp

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Publication Date
Fri Dec 23 2022
Journal Name
Innovative Infrastructure Solutions
Experimental modeling of a single pile in liquefiable soil under the effect of coupled static-dynamic loads
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In this work, a single pile is physically modeled and embedded in an upper liquefiable loose sand layer overlying a non-liquefiable dense layer. A laminar soil container is adopted to simulate the coupled static-dynamic loading pile response during earthquake motions: Ali Algharbi, Halabjah, El-Centro, and Kobe earthquakes. During seismic events with combined loading, the rotation along the pile, the lateral and vertical displacements at the pile head as well as the pore pressure ratio in loose sandy soil were assessed. According to the experimental findings, combined loading that ranged from 50 to 100% of axial load would alter the pile reaction by reducing the pile head peak ground acceleration, rotation of the pile, and lateral displacem

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Study of weathering effect on the thermal conductivity of polyvinyl chloride before and after silicon carbide addition as packaging materials
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The work was carried out in two stages. The first stage concerned
with study of silicon carbide (SiC) ratio (1.5, 2.5, 3.5, and 4.5 wt%)
effect on the Thermal conductivity of polyvinyl chloride (PVC); and
the second stage concerned with the UV – weatherizing (25, 50, and
75 hr), thermal aging (40, 50, and 60 °C), and rain- weatherizing (1,
2.5, and 4 hr) effect on the samples involved. Thermal conductivity
results proved that there was slight increase in thermal conductivity
by (SiC) loading; it increased from 0.17 W/m.K for PVC to 0.19
W/m.K for 4.5% SiC/PVC; where as it was systematically decreased
by UV- weatherizing, thermal aging, and rain- weatherizing. This
property is in a good agreement with gene

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Publication Date
Wed Aug 04 2021
Journal Name
Ibn Al-haitham International Conference For Pure And Applied Science (ihicps)
Effect of Annealing on structural and optical properties of Indium Selenide (InSe) Thin films prepared by vacuum THERMAL EVAPORATION TECHNIQUE
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Publication Date
Sat Mar 01 2008
Journal Name
Al-khwarizmi Engineering Journal
Study the Effect of Carbon Fiber Volume Fraction and their Orientations on the Thermal Conductivity of the Polymer Composite Materials.
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      The effect of fiber volume fraction of the carbon fiber on the thermal conductivity of the polymer composite material was studied. Different percentages of carbon fibers were used (5%, 10%, 15%, 20%, and 25%). Specimens were made in two groups for unsaturated polyester as a matrix and carbon fibers, first group has parallel arrangement of fibers and the second group has perpendicular arrangement of fibers on the thermal flow, Lee's disk method was used for testing the specimens. This study showed that the values of the of thermal conductivity of the specimens when the fibers arranged in parallel direction was higher than that when the fibers arranged in the perpendicular direction  

 &nbsp

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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Study of the heat treatment effect on electrical and porosity of Cermet Coating layers (Zro2 – Y2O3) prepared by Thermal Spraying
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The technical of Flame Thermal Spray had been used in producing a cermet
composite based on powders of stabilized zirconium oxide containing amount of
Yatteria oxide (ZrO2- 8Y2O3) reiforced by minerals powders of bonding material
(Ni-Cr- Al- Y) in different rates of additions (25, 35, 50) on stainless steel base type
(304) after preparing it by the way of Grit Blasting.
Before heat treatment, the coated cermet layers were characterized for porosity
and electric resistivity. All samples were heat treated in vacuum furnace at different
temperature and times. The physical tests had been operated after heat treatment
and gave best results especially porosity, which found to be reduced dramatically
and producing hig

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of The College Of Basic Education
Effect of Annealing Temperature on the Structure and Optical Properties of CdS: Cu Thin Films Prepard By Thermal Vacuum Evaporation
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Publication Date
Fri Dec 30 2022
Journal Name
Journal Of Mathematics
Estimation of Parameters of Finite Mixture of Rayleigh Distribution by the Expectation-Maximization Algorithm
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In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T

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