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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
Thu Sep 01 2016
Journal Name
Applied Thermal Engineering
Solidification of a PCM with nanoparticles in triplex-tube thermal energy storage system
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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Diversity Operators-based Artificial Fish Swarm Algorithm to Solve Flexible Job Shop Scheduling Problem
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Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex

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Publication Date
Sun Jun 28 2026
Journal Name
Journal Of Physical Education
The Learning Gap between Classroom Education and Artificial Intelligence-Based Education in Curriculum Design among Students of the College of Physical Education and Sports Sciences from the Students' Perspective
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       The present study aimed to identify the learning gap between classroom-based education and artificial intelligence (AI)-based education among students of Colleges of Physical Education and Sports Sciences. It also sought to determine the effectiveness of classroom education and AI-based education in reducing the learning gap among these students. The research problem addressed the following questions: Are there statistically significant differences in the learning gap between students who learn through traditional classroom education and those who learn through AI-based education in Colleges of Physical Education and Sports Sciences? What is the nature of the learning gap between classroom education and AI-based educati

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Publication Date
Sat Oct 08 2022
Journal Name
Journal Of Computational Design And Engineering
Twisted-fin parametric study to enhance the solidification performance of phase-change material in a shell-and-tube latent heat thermal energy storage system
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Abstract<p>Phase change material (PCM) is considered as one of the most effective thermal energy storage (TES) systems to balance energy supply and demand. A key challenge in designing efficient PCM-based TES systems lies in the enhancement of heat transmission during phase transition. This study numerically examines the privilege of employing twisted-fin arrays inside a shell-and-tube latent heat storage unit to improve the solidification performance. The presence of twisted fins contributes to the dominating role of heat conduction by their curved shapes, which restricts the role of natural convection but largely aids the overall heat-transfer process during solidification. The heat-discharge </p> ... Show More
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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Influence of non-thermal argon plasma needle on blood coagulation
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Non-thermal argon plasma needle at atmospheric pressure was
constructed. The experimental setup was based on a simple and low
cost electric component that generates a sufficiently high electric
field at the electrodes to ionize the argon gas which flow at
atmospheric pressure. A high AC power supply was used with 1.1
kV and 19.57 kHz. Non-thermal Argon plasma used on blood
samples to show the ability of non-thermal plasma to promote blood
coagulation. Three tests have been done to show the ability of plasma
to coagulate both normal and anti-coagulant blood. Each blood
sample has been treated for varying time from 20sec. to 180sec. at
different distances. The results of the current study showed that the
co

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Publication Date
Fri Dec 01 2023
Journal Name
Environmental Processes
Removal of Dyes from Aqueous Solutions using Non-Thermal Plasma
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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Journal Of Science
Oxidative Desulfurization of Model Fuel by Non-Thermal Plasma Technology
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     The Non-thermal plasma has a wide range of applications in different areas. In this study, the oxidation of a model fuel containing organo-sulfur compounds (benzothiophene and dibenzothiophene) was investigated using plasma. The process involved ozone generation through dielectric barrier discharge, followed by extraction using acetonitrile. The results demonstrated the efficient oxidation and removal of dibenzothiophene and benzothiophene by non-thermal plasma. The desulfurization efficiency reached 93.78% under the optimum conditions, including a voltage of 11Kv, temperature of 50ºC, duration of 4 hours, and a flow rate of 75 ml/min.

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Publication Date
Wed Apr 20 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Text image secret sharing with hiding based on color feature
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Publication Date
Sun Aug 23 2026
Journal Name
Journal Of Food Science And Technology (iran)
Effect of Replacing Vegetable Oil with Anhydrous Milk Fat on the Quality Properties of Laboratory-Produced Nutella
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This study aimed to prepare a healthy Nutella rich in specific fatty acids (e.g., oleic, palmitic, and stearic acids) and fat-soluble vitamins (A, E, K, and D) by replacing sunflower oil with anhydrous milk fat (ghee) at substitution levels of 10%, 20%, and 30%. The effect of this substitution on the physicochemical and sensory properties of the laboratoryproduced Nutella was investigated. The chemical composition analysis revealed significant differences (p < 0.05) in fatty acid profiles and vitamin content among the treatments, while some other compositional parameters showed no significant differences. The percentages of oleic, palmitic, stearic, and linolenic fatty acids increased significantly with increasing substitution levels of anh

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