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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
Tue Oct 06 2020
Journal Name
College Of Islamic Sciences
Difficulties in learning and teaching Arabic to non-native speakers in the Kurdistan Region Types and solutions
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This research is a study of the difficulties of learning the Arabic language that faces Arabic language learners in the Kurdistan Region, by revealing its types and forms, which can be classified into two categories:

The first type has difficulties related to the educational system, the source of which is the Arabic language itself, the Arabic teacher or the learner studying the Arabic language or the educational curriculum, i.e. educational materials, or the educational process, i.e. the method used in teaching.

The second type: general difficulties related to the political aspect, the source of which is the policy of the Kurdistan Regional Government in marginalizing the Arabic language and replacing the forefront of th

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
The Simulation Technique to Estimate the Parameters of Generalized Exponential Rayleigh Model
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     The paper shows how to estimate the three parameters of the generalized exponential Rayleigh distribution by utilizing the three estimation methods, namely, the moment employing estimation method (MEM), ordinary least squares estimation method (OLSEM),  and maximum entropy estimation method (MEEM). The simulation technique is used for all these estimation methods to find the parameters for the generalized exponential Rayleigh distribution. In order to find the best method, we use the mean squares error criterion. Finally, in order to extract the experimental results, one of object oriented programming languages visual basic. net was used

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Thu Sep 15 2022
Journal Name
Gsc Biological And Pharmaceutical Sciences
Survey and revision of storage insects from several localities of Iraq
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Publication Date
Sun Jul 21 2024
Journal Name
Journal Of Clinical Medicine
Microbiological and Salivary Biomarkers Successfully Predict Site-Specific and Whole-Mouth Outcomes of Nonsurgical Periodontal Treatment
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Background/Objectives: Nonsurgical periodontal treatment (NSPT) is the gold-standard technique for treating periodontitis. However, an individual’s susceptibility or the inadequate removal of subgingival biofilms could lead to unfavorable responses to NSPT. This study aimed to assess the potential of salivary and microbiological biomarkers in predicting the site-specific and whole-mouth outcomes of NSPT. Methods: A total of 68 periodontitis patients exhibiting 1111 periodontal pockets 4 to 6 mm in depth completed the active phase of periodontal treatment. Clinical periodontal parameters, saliva, and subgingival biofilm samples were collected from each patient at baseline and three months after NSPT. A quantitative PCR assay was us

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Publication Date
Mon Sep 13 2021
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis
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The objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response w

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Publication Date
Sat Jun 01 2024
Journal Name
Alexandria Engineering Journal
U-Net for genomic sequencing: A novel approach to DNA sequence classification
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The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

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Publication Date
Sun Dec 02 2018
Journal Name
Journal Of The College Of Education For Women
Nutritional and Evaluation properties of natural orange juice enriched by coconut milk as kids' nutritional drink
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Coconut milk is considered as a natural drink that enhances the immunity and it is enriched by calcium, iron, magnesium and vitamin (C) and it is also safe drink for kids and bacterial anti-oxdant, and it may be used in the natural juices instead of the whole milk (cow milk) which is added to some juices. This study aimed to determine the nutritrnal value and the sensory evaluation properties of the natural orange juice enriched by canned coconut milk                                                 &nb

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Publication Date
Sun Mar 01 2015
Journal Name
Baghdad Science Journal
Detection of Cronobacter sakazakii (Enterobacter sakazakii) in powdered food infants (PIF) and raw milk in Iraq
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This study was conducted to detect C.sakazakii PIF and raw milk. Two hundred samples of PIF were taken from the infected hospital infants who used this type of milk and from the local markets in addition to 16 sample of raw milk were collected. The study is the first to report the isolation of C. sakazakii and Enterobacter spp. from raw milk in Iraq. The distribution of C.sakazakii and Enterobacter spp. among the presumptive isolates using Vitek-GN2 system gave 1/16(6.25%) isolates of C.sakazakii and 4/16 (25%) isolates of Enterobacter spp. Enterobacter spp. isolates include (E.cloacae ssp. cloacae and E.cloacae ssp. dissolvens, E.hormaechei, and E.ludwigii) that isolate from raw milk Differences in between percentages of each isolate perse

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
A Comparative Study of Heavy Metals and Trace Elements Concentration in Milk Samples Consumed in Iraq
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The measurements of major and trace elements in different brands of milk powder selected from the Iraqis market via the X-ray fluorescence (XRF) Technique have been studied in the present work. The result of the measurements reveals the high concentrations of sodium, phosphorus, sulfur, chlorine, potassium, calcium and magnesium. Furthermore, low concentrations of aluminum, silicon, iron, bromine, molybdenum, iodine, barium, titanium, manganese, cobalt, chrome, nickel, copper, zinc and lead were detected. Neutron activation analysis (NAA) and Kjeldahl technique were also employed to determine the concentrations of nitrogen. It was found that the nitrogen concentration was in the range of (1.96 - 3.23) % which is within the permissible li

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