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Technological Advances in Soil Penetration Resistance Measurement and Prediction Algorithms
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Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use machine learning algorithms to determine the above relationship. Algorithms include multiple linear regression (MLR), k-nearest neighbors (KNN), support vector regression (SVR), cubist, random forest (RF), and artificial neural networks (ANN). Machine learning made it possible to predict soil penetration resistance from huge sets of environmental data obtained from onboard sensors on satellites and other sources to produce digital soil maps based on classification and slope, but whose output must be verified if they are to be trusted. This review presents soil penetration resistance measurement systems, new technological developments in measurement systems, and the contribution of precision agriculture techniques and machine learning algorithms to soil penetration resistance measurement and prediction.

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Publication Date
Fri Jul 12 2024
Journal Name
World Water Policy
The effect of natural factors on changing soil uses in the marshes: An experimental study using Landsat satellite data
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The study aimed to analyze the effect of meteorological factors (rainfall rate and temperature) on the change in land use in the marshes of the Al‐Majar Al‐Kabir region in southern Iraq. Satellite images from Landsat 7 for 2012 and Landsat 8 for 2022 were used to monitor changes in the land coverings, the images taken from the Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) sensors of the Landsat satellite. Geometric correction was used to convert images into a format with precise geographic coordinates using ArcMap 10.5. The maximum likelihood classification method was used to examine satellite image data using a supervised approach, and the data were analyzed statistically. We obtained clear images of the area,

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Publication Date
Fri Sep 05 2014
Journal Name
Engineering And Technology Journal
New Method to Increase the Ability of the Water for Dissolving Total Salts in Soil by Using the Magnetism
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Publication Date
Sun Mar 19 2023
Journal Name
Journal Of Educational And Psychological Researches
Standard Characteristics of (Philip Carter) Tests of Mental Agility Estimated According To the Classical Measurement Theory among University Students
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Abstract

The aim of the current research is to extract the psychometric properties of Philip Carter's tests (for mental agility) according to the classical measurement theory. To achieve these goals, the researcher took a number of scientific steps to analyze Philip Carter's tests (for mental agility) according to the classical measurement theory. The researcher translated Philip Carter's (mental agility) tests from English into Arabic and then he translated them conversely. For the purpose of statistical analysis of paragraphs of the Philip Carter tests (mental agility) to extract the psychometric properties, the tests were applied to a sample of (1000) male and female students who were selected by cluster sampl

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Publication Date
Thu Apr 25 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY OF THE SYNERGISTIC EFFECT OF BACTERIOCIN PRODUCED FROM Leuconostoc mesenteroides ssp. cremoris With Antibiotics Against Multi Resistance Diarrheal Bacteria: STUDY OF THE SYNERGISTIC EFFECT OF BACTERIOCIN PRODUCED FROM Leuconostoc mesenteroides ssp. cremoris With Antibiotics Against Multi Resistance Diarrheal Bacteria
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The study included the collection of samples of raw cow milk to isolate Leuconostoc bacteria, samples were sub cultured on De-Man Rogosa Sharpe-Vancomycin medium, the pure colonies were selected and subjected to the cultural and microscopically tests, according to that 25 cocci bacterial isolates were obtained, then isolates were subjected to biochemical tests. Result of tests showed that 12 isolates belong to the genus Leuconostoc out of 25 cocci bacterial isolates, Vitek2 system was used as a supplementary step. Results of final identification showed that 3 sub species were obtained included Leuconostoc mesenteroides ssp. cremoris 9 out of 12 isolates, while it was 2 isolates of Leuconostoc mesenteroides ssp. mesenteroides and one isol

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Publication Date
Fri Mar 12 2021
Journal Name
Medico Legal Update
A Comparative Study about Knowledge, Attitude, Practice of Antibiotic Use and Perceptions of the Possible Causes of Resistance between Final Year Undergraduate Students and Postgraduate Pharmacy Students
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Background: Antibiotic resistance is a problem leading to difficulty in treating microbial infections thatmay occur due to many causes. For the important pharmacist role as a reference for the information and theability to access to medications, they are vital members in lowering the development of antibiotic resistance,and also they support the proper use and control of antibioticsmisuse. Our goal is comparing the knowledge,attitude, practice of undergraduate and postgraduate pharmacy students and their perceptions about thecausing factors of antibiotic resistance in Iraq.Method: A cross sectional study was conducted involving the final year bachelor and postgraduate (masterand Philosophical doctor) students from different private

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Mon Dec 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction of Un-Cored Intervals Using FZI Method and Matrix Density Grouping Method: A Case Study of Abughirab Field/Asmari FM., Iraq
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Knowledge of permeability is critical for developing an effective reservoir description. Permeability data may be calculated from well tests, cores and logs. Normally, using well log data to derive estimates of permeability is the lowest cost method. This paper will focus on the evaluation of formation permeability in un-cored intervals for Abughirab field/Asmari reservoir in Iraq from core and well log data. Hydraulic flow unit (HFU) concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir quality index (RQI). Both measures are based on porosity and permeability of cores. It is assumed that samples with similar FZI values belong to the same HFU. A generated method is also used to calculate permea

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Hydrology
Boosted artificial intelligence model using improved alpha-guided grey wolf optimizer for groundwater level prediction: Comparative study and insight for federated learning technology
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Publication Date
Tue Apr 22 2014
Journal Name
International Journal Of Advanced Research
Effect of tillage system and deficit irrigation on consumptive use, some soil physical properties, growth and yield of potato Solanum tuberosum L.
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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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