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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 Sep 01 2013
Journal Name
Baghdad Science Journal
Synthesis and characterization of novel metal complexes of (pentulose-?-lactone-2,3-enedibenzoate barbituric acid) with some metal ions
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New (pentulose-?-lactone-2,3-enedibenzoate barbituric acid) (L) have been synthesized by reaction of (5-C-dimethyl malonyl-pentulose-?-lactone-2,3-enedibenzoate) with urea in alkaline media (sodium methoxide). (Ca+2, Co+2, Ni+2, Cu+2, Zn+2, Cd+2 and Hg+2) complexes of (pentulose-?-lactone-2,3-enedibenzoate barbituric acid) (L) have been prepared and characterized by (1H and 13CNMR), FTIR, (U.V-Vis) spectroscopy, Atomic absorption spectrophotometer (A.A.S), Molar conductivity measurements and Magnetic moment measurements, and the following general formula has been given for the prepared complexes [MLCl2(H2O)].XH2O, where M = (Ca+2, Co+2, Ni+2, Cu+2, Zn+2, Cd+2, Hg+2), X = five molecules with (Cd+2) complex, L = (pentulose-?-lactone-2,3

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Publication Date
Fri Nov 15 2024
Journal Name
Azerbaijan Chemical Journal
EVALUATION OF ANTIOXIDANT ACTIVITY OF NOVEL ORGANOTIN COMPLEXES DERIVED FROM A NEWLY SYNTHESIZED LIGAND AND THEIR STRUCTURAL CHARACTERIZATION
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In this work, of New Ligand [(E)-5-hydroxy-4-(3-(4-methoxy phenyl) acryl amido) naphthalene -1- sulfonic acid] (ANS) was prepared by reflexing reaction of 4-amino-5-hydroxy naphthalene sulfonic acid with para methoxy cinnamic acid, this produced and described chemical was employed as ligand to prepare tri and di-organotin complexes by condensation reaction with the salts of organotin chloride (phenyl, butyl, and methyl tin chloride). Specialized methods, including elemental analysis, (tin and proton) magnetic resonance, and infrared spectra, were used to identify the complexes. DPPH (2,2-diphenyl-1-picrylhydrazyl) and CUPRAC (Cupric Reducing Antioxidant Capacity) are both commonly used methods for measuring antioxidant capacity in v

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Publication Date
Wed Jun 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of Artificial Aging Test on PEEK CAD/CAM Fabricated Orthodontic Fixed Lingual Retainer
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Background: The purpose of this study was to evaluate the effect of in vitro long-term simulation of oral conditions on the bond strength of PEEK CAD/CAM lingual retainers.

Material and methods: The sample consisted of 12 PEEK CAD/CAM retainers each composed of 2 centrally perforated 3x4mm pads joined by a connector. They were treated by 98% sulfuric acid for 1 minute and then conditioned with Single Bond Universal and bonded to the lingual surface of premolar teeth by 3M Transbond TM System. Half of the retainers were artificially aged using a 30-day water storage and 5000 thermocycling protocol before bond strength testing to compare with the non-aged specimens.

Results: The artificially aged retainers showed a marginally

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

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Publication Date
Sat May 09 2015
Journal Name
International Journal Of Innovations In Scientific Engineering
USING ARTIFICIAL NEURAL NETWORK TECHNIQUE FOR THE ESTIMATION OF CD CONCENTRATION IN CONTAMINATED SOILS
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The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

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Publication Date
Sat Jan 01 2022
Journal Name
International Middle Eastern Simulation And Modelling Conference 2022, Mesm 2022,
MECHANICS OF COMPOSITE PLATE STRUCTURE REINFORCED WITH HYBRID NANO MATERIALS USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Mathematical Modeling of a Hollow Fiber Module Used in Pressure-Retarded Osmosis Process
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   Pressure retarded osmosis (PRO) can be considered as one of the methods for utilizing osmotic power, which is a membrane-based technology. Mathematical modeling plays an essential part in the development and optimization of PRO energy-generating systems. In this research, a mathematical model was developed for the hollow fiber module to predict the power density and the permeate water flux theoretically. Sodium chloride solution was employed as the feed and draw solution. Different operating parameters, draw solution concentration (1 and 2 M), the flow rate of draw solution (2, 3, and 4 L/min), and applied hydraulic pressure difference (0 - 90 bar) was used to evaluate the performance of PRO process of a hollow fiber module. The eff

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Numerical Modeling of Water Movement from Buried Vertical Ceramic Pipes through Coarse Soils
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Problem of water scarcity is becoming common in many parts of the world.  Thus to overcome this problem proper management of water and an efficient irrigation systems are needed.  Irrigation with buried vertical ceramic pipe is known as a very effective in management of irrigation water.  The two- dimensional transient flow of water from a buried vertical ceramic pipe through homogenous porous media is simulated numerically using the software HYDRUS/2D to predict empirical formulas that describe the predicted results accurately.   Different values of pipe lengths and hydraulic conductivity were selected.  In addition, different values of initial volumetric soil water content were assumed in this simulation a

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Modeling of Mass Transfer Coefficient in Rotating Biological Contactor with Perforated Discs (RPBC)
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Abstract

 In order to make an improvement associated with rotating biological contactor (RBC), a new design of biofilm reactor called as Rotating perforated disc biological contactor (RPBC) was developed in which the rotating discs are perforated. The transfer of oxygen from air to wastewater was investigated. Mass-transfer coefficient (KLa)  in the liquid phase was determined by measuring  the rate transfer of oxygen.  A   laboratory scale of (RPBC) consisted of a semicircular trough was used with a working capacity of 40 liters capacity of liquid. Synthetic wastewater was used as a liquid phase, while air was used as a gas phase.

The effects of m

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