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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
Tue Feb 01 2022
Journal Name
Archives Of Razi Institute
Imipenem Resistance in Gram-Negative Bacteria in the Central Pediatric Teaching Hospital in Baghdad, Iraq
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Antimicrobial resistance (AMR) is a serious challenge for infectious disease prevention and treatment, according to the World Health Organization. It is a worldwide problem caused primarily by inappropriate and insufficient therapy, misuse of antimicrobials without physician supervision, unnecessary hospital readmissions, and other factors. AMR has several consequences, including increased medical costs and mortality. The present study aimed to evaluate imipenem resistance in gram-negative bacteria in Central Pediatric Teaching Hospital in Baghdad, Iraq, and determine this bacteria resistance in different samples. Initially, a total of 100 different samples were collected from child patients from October 1, 2020, to August 31, 2021. Each is

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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Publication Date
Mon Jan 21 2019
Journal Name
International Journal Of Pharmaceutical Quality Assurance
Genetic Assessment of Antibiotic Resistance in Salmonella Enteric a Serovar Typhi in Kirkuk Province
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Around fifty isolates of Salmonella enterica serovar Typhi were isolated from blood specimens of patients referring to several hospitals in Kirkuk province, Iraq. The results revealed that all isolates developed resistance to trimethoprim-sulfamethoxazole and chloramphenicol. However, neither sul2 nor tem genes were detected. Moreover, only ten isolates were positive for catP. Our data suggested participation of other genes or mechanisms allow these multidrug isolates to resist the antibiotics in question.

Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Wed Jan 01 2020
Journal Name
Plant Archives
The effect of adding some organic and mineral substances to calcareous soil on adsorption and desorption of copper and its removal efficiency from soil
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Publication Date
Tue Jan 31 2017
Journal Name
Journal Of Engineering
Remediation of Contaminated Soil with Petroleum Industrial Wastewater
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The contamination of soil with the wastes of oil industry products that are complex mixtures of hydrocarbons increased recently due to the large development of oil industries in Iraq. This study deals with the remediation of low permeability contaminated clayey soil by using the enhanced electrokinetic technique (EK). The contaminated soil samples obtained from Thi-Qar oil refinery plant in Al-Nassyriah city, where the byproducts of refinery plant are disposed into that site. The byproduct contaminant treated as total petroleum hydrocarbons (TPH) to avoid dealing and complexity of treating the individual minerals and compounds consisting the contaminant. The initial concentrations of TPH were (702.7, 1168, 1235) ppm in the contaminated s

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
DESIGN, CONSTRUCTION AND TESTING OF LOW SPEED WIND TUNNEL WITH ITS MEASUREMENT AND INSPECTION DEVICES
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A low speed open circuit wind tunnel has been designed, manufactured and constructed at the
Mechanical Engineering Department at Baghdad University - College of Engineering. The work is one of
the pioneer projects adapted by the R & D Office at the Iraqi MOHESR. The present paper describes the
first part of the work; that is the design calculations, simulation and construction. It will be followed by a
second part that describes testing and calibration of the tunnel. The proposed wind tunnel has a test
section with cross sectional area of (0.7 x 0.7 m2) and length of (1.5 m). The maximum speed is about (70
m/s) with empty test section. The contraction ratio is (8.16). Three screens are used to minimize flow
distu

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Publication Date
Sat Sep 27 2025
Journal Name
Journal Of Engineering
DESIGN, CONSTRUCTION AND TESTING OF LOW SPEED WIND TUNNEL WITH ITS MEASUREMENT AND INSPECTION DEVICES
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A low speed open circuit wind tunnel has been designed, manufactured and constructed at the Mechanical Engineering Department at Baghdad University - College of Engineering. The work is one of the pioneer projects adapted by the R & D Office at the Iraqi MOHESR. The present paper describes the first part of the work; that is the design calculations, simulation and construction. It will be followed by a second part that describes testing and calibration of the tunnel. The proposed wind tunnel has a test section with cross sectional area of (0.7 x 0.7 m2) and length of (1.5 m). The maximum speed is about (70 m/s) with empty test section. The contraction ratio is (8.16). Three screens are used to minimize flow disturbances in the test section.

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Publication Date
Wed Aug 15 2018
Journal Name
Al-khwarizmi Engineering Journal
Bioremediation of Soil Contaminated with Diesel using Biopile system
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This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. The capability of mixed bacterial culture was examined to remediate the diesel-contaminated soil in bio piling system. For fast ex-situ treatment of diesel-contaminated soils, the bio pile system was selected. Two pilot scale bio piles (25 kg soil each) were constructed containing soils contaminated with approximately 2140 mg/kg total petroleum hydrocarbons (TPHs). The amended soil:

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Publication Date
Sun Jan 03 2021
Journal Name
Al-qadisiyah Journal For Engineering Sciences
Bearing Capacity of Square Footing Resting on Layered Soil
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The bearing capacity of layered soil studies was carried out with various approaches such as experimental, theoretical, numerical, and combination of them. This work is focused on the settlement and bearing capacity of shallow foundations subjected to the vertical load placed on the surface of layered soils. The experimental part was performed by manufacturing soil cubic container (570 mm x 570 mm x 570 mm).  A model square footing of width 60 mm was placed at the surface of the soil bed. The relative density of sand was constant at 60%, and the clay was prepared with a density of 19.2 (kN/m3) and water content of 14.6%. PLAXIS 3D FEM was used to simulate the experimental tests and performing a parametric study. The results showed

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