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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
Fri Nov 01 2019
Journal Name
Journal Of Physics: Conference Series
Data Processing, Storage, and Analysis: Applying Computational Procedures to the Case of a Falling Weight Deflectomer (FWD)
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In the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assum

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Solution for Multi-Objective Optimisation Master Production Scheduling Problems Based on Swarm Intelligence Algorithms
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The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), T

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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Publication Date
Wed Jan 01 2025
Journal Name
Transactions Of The Chinese Society Of Agricultural Machinery
Evaluating Tillage Quality under Varying Speed and Depth Using YOLOv7-Based Image Analysis
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Soil tillage is a critical agricultural practice that creates favorable conditions for seedbed preparation and plant growth. This study presents an innovative application of artificial intelligence (AI) in agriculture by employing the YOLOv7 algorithm to classify and assess post-tillage soil surface conditions, a domain underexplored in current research. The integration of mechanical operation parameters with AI-based image classification enables optimization of tillage quality and mitigation of soil compaction, highlighting the novelty of this approach. The study aims to improve the efficiency of moldboard plow operations by examining the effects of tillage speed and depth on soil clod distribution, fuel consumption, and power requ

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Day to Day variation of Ionosphere Electron and Ion Temperature during Great and Severe Geomagnetic Storms
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The ionospheric characteristics exhibit significant variations with the solar cycle, geomagnetic conditions, seasons, latitudes and even local time. Representation of this research focused on global distribution of electron (Te) and ion temperatures (Ti) during great and severe geomagnetic storms (GMS), their daily and seasonally variation for years (2001-2013), variations of electron and ion temperature during GMS with plasma velocity and geographic latitudes. Finally comparison between observed and predicted Te and Ti get from IRI model during the two kinds of storm selected. Data from satellite Defense Meteorological Satellite Program (DMSP) 850 km altitude are taken for Te, Ti and plasma velocity for different latitudes during great

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Publication Date
Sun Sep 01 2019
Journal Name
2019 11th Computer Science And Electronic Engineering (ceec)
ANN based Measurement for No-Reference Video Quality of Experience Metric
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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modified Grid Clustering Technique to Predict Heat Transfer Coefficient in a Duct of Arbitrary Cross Section Area
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A simple straightforward mathematical method has been developed to cluster grid nodes on a boundary segment of an arbitrary geometry that can be fitted by a relevant polynomial. The method of solution is accomplished in two steps. At the first step, the length of the boundary segment is evaluated by using the mean value theorem, then grids are clustered as desired, using relevant linear clustering functions. At the second step, as the coordinates cell nodes have been computed and the incremental distance between each two nodes has been evaluated, the original coordinate of each node is then computed utilizing the same fitted polynomial with the mean value theorem but reversibly.

The method is utilized to predict

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Publication Date
Sun Nov 02 2025
Journal Name
African Arguments
From Non‑Intervention to Non‑Indifference: What the African Union Has Really Learned about Crisis Management
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Two decades after replacing the OAU, the AU’s record is best measured not by communiqués but by how fast it converts rules into results on the ground. In March 2022, the African Union’s Peace and Security Council (PSC) authorised the transition from AMISOM to ATMIS in Somalia — a reminder that, two decades after the African Union (AU) replaced the Organisation of African Unity (OAU), the Union’s rules are judged by execution, not intent. This article argues that the AU’s legal and institutional redesign shortened the warning‑to‑decision cycle and raised the credibility of enforcement, but performance still hinges on finance, logistics and political will. Where mandates are matched with money, enabling capabilities and enforc

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Publication Date
Tue Aug 19 2025
Journal Name
Scientific Reports
Predictive modeling of asthma drug properties using machine learning and topological indices in a MATLAB based QSPR study
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Publication Date
Tue Dec 11 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Contribution of Some Managerial Accounting Techniques to Achieve Market Share Requirements / Applied researchin the Al-Muthanna Cement Company
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The research aims to achieve market share requirements and reach the targeted competitive price through the application of management accounting techniques represented by continuous improvement technique and target costing under an Activity Based Cost (ABC) system and Activity Based Management (ABM), In Muthanna Cement Company to reach the rationalization of the cost of the product and maintain the required quality and improve the profitability of the company.

The problem of research has emerged in the inability of local firms to enter into effective competition with other companies operating in the same economic sector, Because of the high cost of its products, Which led to the sale of the product at prices below its cost, and t

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