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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 Aug 01 2019
Journal Name
The Journal Of Solid Waste Technology And Management
Recycling of Waste Compact Discs in Concrete Mix: Lab Investigations and Artificial Neural Networks Modeling
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This study aimed to investigate the incorporation of recycled waste compact discs (WCDs) powder in concrete mixes to replace the fine aggregate by 5%, 10%, 15% and 20%. Compared to the reference concrete mix, results revealed that using WCDs powder in concrete mixes improved the workability and the dry density. The results demonstrated that the compressive, flexural, and split tensile strengths values for the WCDs-modified concrete mixes showed tendency to increase above the reference mix. However, at 28 days curing age, the strengths values for WCDs-modified concrete mixes were comparable to those for the reference mix. The leaching test revealed that none of the WCDs constituents was detected in the leachant after 180 days. The

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Utilizing Artificial Intelligence Tools in Enhancing Training of Trainers (ToT) Programs: Modern Approaches and Practical Applications
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This study specifically contributes to the urgent need for novel methods in Training of Trainers (ToT) programs which can be more effective and efficient through incorporation of AI tools. By exploring scenarios in which AI could be used to dramatically advance trainer preparation, knowledge-sharing, and skill-building across sectors, the research aims to understand the possibility. This study uses a mixed-methods approach, it surveys 500 trainers and conducts in-depth interviews with a further 50 ToT program directors across diverse industries to evaluate the impact of AI-enhanced ToT programs. The results showcase that the use of AI has a substantial positive effect on trainer performance and program outcomes. AI-enhanced ToT programs, fo

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Utilizing Artificial Intelligence Tools in Enhancing Training of Trainers (ToT) Programs: Modern Approaches and Practical Applications
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Publication Date
Thu Feb 13 2025
Journal Name
Technology In Agronomy
Challenges and innovations in potato harvester design: the role of artificial intelligence in improving crop sorting
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As population growth increases the demand for crops increases and their quality improves, and it becomes necessary to find innovative and modern solutions to enhance production. In this context, artificial intelligence plays a pivotal role in developing new technologies to improve crop sorting and increase agricultural yields. The present review discusses the main differences between manual and mechanical potato harvesting, explaining the advantages and disadvantages of each method. Manual harvesting is highlighted as a traditional method that allows for greater precision in handling the crop, but it requires more time and effort. In contrast, mechanical harvesting provides greater efficiency and speed in the process, but it may damage some

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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 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 Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Integration Balanced Scorecard and technology( TDABC) technology to achieve competitive advantage
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Abstract

That the reduction of costs for products and services provided by economic units is one of the main concerns at the present time to keep pace with competition in the markets, economic units are always striving to stay competitive in a modern business environment and achieve a competitive advantage, (TDABC) in the General Company for Electrical and Electronic Industries / Air cooler engine plant to reduce the costs facing the economic units under the circumstances of the Iraqi environment, especially the industrial, and the need for development events in traditional methods (TDABC) as a technology for reducing costs by relying on time guidelines. The research also concluded that the financial and non-financ

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Publication Date
Sun Dec 20 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Suggested Model to audit the oil companies to achieve environmental control
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Oil sector is one of the most important sectors affecting the ecological balance, as activity contributes to the oil companies to influence their working environment, both during the oil exploration and extraction process or during transfer from one place to another process. We will try through this research put an environmental audit program proposal takes into account all the financial aspects, commitment and performance, according to the laws and regulations and agreements as well as relevant international standards, was based on research on the premise that the development of an environmental proposal auditing program that includes environmental controls on oil industry phases which helps reduce or minimize environmental pollutants B

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Publication Date
Wed Jan 26 2022
Journal Name
Nanomaterials
Improved Melting of Latent Heat Storage Using Fin Arrays with Non-Uniform Dimensions and Distinct Patterns
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Employing phase-change materials (PCM) is considered a very efficient and cost-effective option for addressing the mismatch between the energy supply and the demand. The high storage density, little temperature degradation, and ease of material processing register the PCM as a key candidate for the thermal energy storage system. However, the sluggish response rates during their melting and solidification processes limit their applications and consequently require the inclusion of heat transfer enhancers. This research aims to investigate the potential enhancement of circular fins on intensifying the PCM thermal response in a vertical triple-tube casing. Fin arrays of non-uniform dimensions and distinct distribution patterns were des

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