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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 Dec 28 2025
Journal Name
مجلة جامعة صنعاء للعلوم التطبيقية والتكنولوجيا
From Algorithms to Applications: A Review of AI-Based Face Recognition and Identity Verification
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Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Modeling and Simulating NOMA Performance for Next Generations
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Non-orthogonal Multiple Access (NOMA) is a multiple-access technique allowing multiusers to share the same communication resources, increasing spectral efficiency and throughput. NOMA has been shown to provide significant performance gains over orthogonal multiple access (OMA) regarding spectral efficiency and throughput. In this paper, two scenarios of NOMA are analyzed and simulated, involving two users and multiple users (four users) to evaluate NOMA's performance. The simulated results indicate that the achievable sum rate for the two users’ scenarios is 16.7 (bps/Hz), while for the multi-users scenario is 20.69 (bps/Hz) at transmitted power of 25 dBm. The BER for two users’ scenarios is 0.004202 and 0.001564 for

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Publication Date
Sat Jan 15 2011
Journal Name
International Journal Of Poultry Science
Influence of Source of Oil Added to Diet on Egg Quality Traits of Laying Quail
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This experiment was performed to investigate the influence of different oils in the diets of laying quail on their egg quality characteristics. One hundred and twenty 7-week-old Japanese quails (Coturnix coturnix japonica) were allocated to four groups with three replicates containing 10 quail each (30 quail per treatment group). They were fed for 13 weeks (including one week of adaptation period) on diets containing 3% oil from different sources, viz., sunflower (T1), linseed (T2), maize (T3), or fish oil (T4). Inclusion of the diet of laying quail with fish oil (T4) and maize oil (T2) resulted in a significant increase with respect to egg weight, yolk weight, albumen weight, yolk diameter, yolk height, albumen diameter, albumen height, sh

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Publication Date
Sat Jan 15 2011
Journal Name
International Journal Of Poultry Science
Influence of Source of Oil Added to Diet on Egg Quality Traits of Laying Quail
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This experiment was performed to investigate the influence of different oils in the diets of laying quail on their egg quality characteristics. One hundred and twenty 7-wk old Japanese quails (Coturnix coturnix japonica) were allocated to four groups with three replicates containing 10 quail each (30 quail per each treatment group). They were fed for 13 weeks (including one week of adaptation period) on diets containing 3% oil from different sources, viz. either sunflower (T1), linseed (T2), maize (T3), or fish oil (T4). Inclusion the diet of laying quail with fish oil (T4) and maize oil (T2) resulted in significant increase with respect to egg weight, yolk weight, albumen weight, yolk diameter, yolk height, albumen diameter, albumen height

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Publication Date
Fri Jan 01 2016
Journal Name
Iraqi National Journal Of Chemistry
Novel Biomarker in Polycystic Ovary Syndrome (PCOS) Infertile Females With Diabetes Mellitus Prone to Atherosclerosis
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The study aimed to evaluate Glucagon-Like Peptide-1 levels in Polycystic ovary syndrome (PCOS) infertile female with Diabetes Mellitus (DM) and compare the results with control group, also, to find the correlation for GLP-1 with Luteinizing hormone (LH), Follicle stimulating hormone (FSH) and LH/FSH ratio that may be used in prediction atherosclerosis in these patients. The study included nineteen women with age ranged (30-40) years and BMI ranged between (30-35) Kg/m 2. Subjects were divided into two groups: group (1) consist of (45) females as a healthy control and group (2) consist of (45) infertile females with PCOS and DM as complication. Fasting serum glucose was determined by using commercial kits (Biolabo SA-France); LH, FSH, prolac

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
A Novel Approach to Improving Brain Image Classification Using Mutual Information-Accelerated Singular Value Decomposition
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Publication Date
Sun Oct 31 2021
Journal Name
Eastern-european Journal Of Enterprise Technologies
Distinguishing of different tissue types using K-Means clustering of color segmentation
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Millions of lives might be saved if stained tissues could be detected quickly. Image classification algorithms may be used to detect the shape of cancerous cells, which is crucial in determining the severity of the disease. With the rapid advancement of digital technology, digital images now play a critical role in the current day, with rapid applications in the medical and visualization fields. Tissue segmentation in whole-slide photographs is a crucial task in digital pathology, as it is necessary for fast and accurate computer-aided diagnoses. When a tissue picture is stained with eosin and hematoxylin, precise tissue segmentation is especially important for a successful diagnosis. This kind of staining aids pathologists in disti

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Publication Date
Fri Mar 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
The Dental Caries Experience in Relation to Salivary Flow Rate, SIgA and Mutans Streptococci Bacteria in Smoker and Non-Smoker Patients
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Background: Dental caries is a localized, progressive destructive, largely irreversible microbial based disease of multifactorial nature; these factors include (host, microbes and food) they influence differently on the initiation and progression of dental caries. The aims of the study: was to evaluate the effect of smoking on salivary flow rate, secretory immunoglobulin (SIgA) level and viable count of mutans streptococci (M.S) bacteria in oral cavity and their relation to dental caries experience. Material and method: The samples were collected from 80 male students ranging in ages from 18-22 years old. Where they divided in to two groups, 40 non-smokers (control group) and 40 smokers (study group). Unstimulated salivary samples were c

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Collection, Storage and Protein Extraction Method of Gingival Crevicular Fluid for Proteomic Analysis
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Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft

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Publication Date
Wed Jul 22 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Salivary microRNAs (hsa-miR-200a, hsa-miR-125a and hsa- miR-93) in relation to age, gender and histopathological parameters.
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Background: MicroRNAs (miRNAs) are small noncoding RNAs that post‐transcriptionally regulate gene expression by targeting specific mRNAs. The main objective of this study was measure the level of salivary (hsa-miR-200a, hsa-miR-125a and hsa- miR-93) in both oral squamous cell carcinoma and healthy controls to asses the association of them with age, gender and tumor grade materials and methods The level of three salivary microRNAs namely hsa-miR-200a, hsa-miR-125a and hsa- miR-93 were measured in saliva of patients with oral squamous cell carcinoma and healthy controls by using reveres transcription, preamplification and quantitative PCR also the general information from each patient including the age, sex and tumor grade were record

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