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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
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Quality of internal audit and its impact on nature, timing and procedures of external audit An investigative study of a sample of external auditors Iraqi Solidary Companies for Auditing.
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           The study aims at investigating the quality of internal auditing and its impact on nature, timing, and procedures of external audit, based on international auditing standards, in particular ISA (610). The standard ISA (610) requires the external auditors to assess independence, the scope of internal audit unit, competence, and due professional care of internal auditors as indicators that reflect the quality of internal audit performance before deciding to rely on internal auditors.

The sample of this study consisted of external auditors in Iraqi Solidary Companies for Auditing. A questionnaire was distributed to them via e-mail

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Publication Date
Sun Dec 31 2023
Journal Name
Iraqi Geological Journal
Advanced Geostatistical Techniques for Building 3D Geological Modeling: A Case Study from Cretaceous Reservoir in Bai Hassan Oil Field
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A 3D Geological model was generated using an advanced geostatistical method for the Cretaceous reservoir in the Bai Hassan oil field. In this study, a 3D geological model was built based on data from four wells for the petrophysical property distribution of permeability, porosity, water saturation, and NTG by using Petrel 2021 software. The geological model was divided into a structural model and a property model. The geological structures of the cretaceous reservoir in the Bai Hassan oil field represent elongated anticline folds with two faults, which had been clarified in the 3D Structural model. Thirteen formations represent the Cretaceous reservoir which includes (Shiranish, Mashurah, U.kometan, Kometan Shale, L. Kometan, Gulnen

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Statistical Sciences
Use the robust RFCH method with a polychoric correlation matrix in structural equation modeling When you are ordinal data
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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Evaluating Educational Programs in Combating Indecent Behaviors Among University Students Using Structural Equation Modeling (Field study: Northern Border University)
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The study aimed to evaluate educational programs efficiency in applying the best educational practices to educate students from the dangers of indecent behaviors, in line with higher education policy and the appropriateness of educational program dimensions to spread awareness among students to not fall into the indecent behaviors clutches. The study adopted the inductive exploratory approach through structural equation modeling and the descriptive analysis of the collected data from randomly selected sample (n=385) from educational academics at Northern Border University in the Saudi Arabia using a specially designed survey tool to meet study purposes to evaluate dimensions of teaching methods, evaluation tools, training courses, course

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Applying some hybrid models for modeling bivariate time series assuming different distributions for random error with a practical application
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Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

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Publication Date
Mon Dec 03 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Condition assessment and rehabilitation for trunk sewer deterioration based on Semi-Markov model
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An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
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Publication Date
Fri Dec 01 2017
Journal Name
2017 11th Asian Control Conference (ascc)
ESO-based repetitive control for rejecting periodic and aperiodic disturbances in piezoelectric actuators
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This paper presents the Extended State Observer (ESO) based repetitive control (RC) for piezoelectric actuator (PEA) based nano-positioning systems. The system stability is proved using Linear Matrix Inequalities (LMIs), which guarantees the asymptotic stability of the system. The ESObased RC used in this paper has the ability to eliminate periodic disturbances, aperiodic disturbances and model uncertainties. Moreover, ESO can be tuned using only two parameters and the model free approach of ESO-based RC, makes it an ideal solution to overcome the challenges of nano-positioning system control. Different types of periodic and aperiodic disturbances are used in simulation to demonstrate the effectiveness of the algorithm. The comparison studi

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Publication Date
Wed Sep 26 2018
Journal Name
Communications In Computer And Information Science
A New RGB Image Encryption Based on DNA Encoding and Multi-chaotic Maps
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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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