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Access Control Security Review: Concepts and Models
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HS Saeed, SS Abdul-Jabbar, SG Mohammed, EA Abed, HS Ibrahem, Solid State Technology, 2020

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Publication Date
Fri Feb 19 2021
Journal Name
Journal Of Pure And Applied Microbiology
Biological Control of Phytopathogenic Fungi by Kluyveromyces marxianus and Torulaspora delbrueckii Isolated from Iraqi Date Vinegar
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Yeasts are distributed in all environments and have been reported as potential biocontrol agents against various phytopathogenic fungi. To investigate their enzymatic and biological activities, 32 yeasts were isolated from 15 date vinegar samples. Evaluation of the antagonistic activities of isolated yeasts against the plant pathogens Fusarium oxysporium, Sclerotinia sclerotiorum, and Macrophomina phaseolina indicated that there are two yeasts had the highest inhibitory effect against plant pathogens, these yeasts identified as Kluyveromyces marxianus and Torulaspora delbrueckii using traditional and molecular methods. These yeast isolates were tested for fungal cell wall degrading enzymes (in vitro), and results indicated that the

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Publication Date
Mon Jan 16 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Dependence Severity, Locus of Control, and Readiness to Change in Male Alcoholic Clients: A Correlational Study
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Objectives: To assess the level of dependence severity, locus of control, and readiness to change in male alcohol clients and measure the correlation between dependence with a locus of control and readiness to change.

Methodology: A descriptive correlational design was conducted in the substance use rehabilitation centers at psychiatric teaching hospitals in Baghdad city from November /2021 to May 2022. The instrument of the study was designed by using sociodemographic, the clinical characteristics of the client, the Short-form Alcohol Dependence Data Questionnaire (SADD), Drinking Related Internal-External Locus of Control Scale: (DRIE), and the Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES). The data was co

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Model of Wind Turbine Power Control System with Fuzzy Regulation by Mamdani and Larsen Algorithms
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Abstract 

     The aim of this work is to create a power control system for wind turbines based on fuzzy logic. Three power control loop was considered including: changing the pitch angle of  the blade, changing the length of the blade and turning the nacelle. The stochastic law was given for changes and instant inaccurate assessment of wind conditions changes. Two different algorithms were used for fuzzy inference in the control loop, the Mamdani and Larsen algorithms. These two different algorithms are materialized and developed in this study in Matlab-Fuzzy logic toolbox which has been practically implemented using necessary intelligent control system in electrical engineerin

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Publication Date
Wed Aug 08 2012
Journal Name
Arabian Journal Of Geosciences
Chemical and physical control processes on the development of caves in the Injana Formation, Central Iraq
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Publication Date
Thu Oct 10 2019
Journal Name
Journal Of The College Of Education For Women
Constitutional Review of 1992 and 1996 and the role of the Party of Progress and Socialism
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Constitutional Review of 1992 and 1996 and the role of the Party of Progress and Socialism

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison between the estimated of nonparametric methods by using the methodology of quantile regression models
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This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

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Publication Date
Sat Jun 21 1930
Journal Name
College Of Islamic Sciences
Quelques raisons du total et son impact sur l'interprétation du Coran: Study of explanatory models
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The reasons for the totality are varied and multiple, some of which are attributed to the methods of the Arabic language as the participant
Verbal and omnipotent differences in the oud of conscience, which are comprehensive reasons for language in all
And some of these reasons are due to the sciences of the Qur'an, such as cessation and initiation
The explanation of the explanation for the multiplicity of words and differences in them, which necessarily led to a dispute jurisprudence
Linked to the origin of disagreement in the interpretation of the totality and its orientation and understanding and to summarize this subject and diverge
Parts and vocabulary did not receive the necessary care and did not absorb the lesson an

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region
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Publication Date
Sat Dec 21 2024
Journal Name
Edelweiss Applied Science And Technology
Using count regression models to investigate the most important economic factors affecting divorce in Iraq
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The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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