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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 Jan 01 2016
Journal Name
Journal Of Engineering
Improve the Performance of PID Controller by Two Algorithms for Controlling the DC Servo Motor
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The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

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Publication Date
Mon Dec 01 2025
Journal Name
Case Studies In Construction Materials
Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia

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Publication Date
Thu Jun 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Marginal Discrepancy and Fracture Resistance of CAD/CAM Ceramill Sintron Metal Copings with Different Porcelain Materials
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Background: This study was performed to compare the marginal fit changes and facture resistance of metal ceramic crowns constructed from Ceramill Sintron metal coping veneered with three different porcelain veneering materials (Vita Master Koromikos VMK, Willi Geller Creation CC and GC initial MC), also to evaluate the influence of thermocycling on load at fracture. Materials and Methods: Master brass die was scanned ,then metal coping was designed and milled from Ceramill Sintron blank to get 60 metal copings, then divided randomly into three groups(20 sample), then veneered with porcelain: VITA, Creation or GC. The marginal gaps were measured before and after porcelain veneering then marginal fit changes was calculated. Fracture resist

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Publication Date
Sun Jul 01 2012
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
OCCURRENCE OF ENTOMOPATHOGENIC AND OTHER OPPORTUNISTIC FUNGI IN SOIL COLLECTED FROM INSECT HIBERNATION SITES AND EVALUATION OF THEIR ENTOMOPATHOGENIC POTENTIAL
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A survey of entomopathogenic and other opportunistic fungi isolated from soil samples collected from insect hibernation sites in different habitats in Kurdistan region of Iraq was carried out during October to December 2009. By using dilution plate method, two entomopathogenic species (Beauveria bassiana (Bals.) Vuill.and Isaria javanica (Friedrichs & Bally) Samson & Hywel-Jones) were detected with isolation percentage (38.46%) each. Other opportunistic fungi such as Alternaria alternata, Aspergillus flavus, A.niger, Penicillium glabrum, P. digitatum, Rhizopus stolonifer and Syncephalastratum racemosum

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Effect of different levels and sizes of walnut seed residues on phosphorus availability and alkaline phosphatase activity in calcareous soil
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A laboratory experiment has been carried out in the College of Science-University of Salahaddin to study the effect of different levels (0,5,10 and 15%) and sizes(250 and 1000µm) of walnut seeds residues and (160mg.kg-1) phosphorus fertilization on the concentration of phosphorus availability and alkaline phosphatase activity in calcareous soil during 15 and 30 days period of incubation, the experimental design in factorial complet randomize design (C.R.D) with three replications. The results indicated that the application of different levels of walnut seed residues decreases the concentration of phosphorus availability and alkaline phosphatase activity, however the results revealed that combination between levels and sizes o

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Impact of eccentricity and depth-to-breadth ratio on the behavior of skirt foundation rested on dry gypseous soil
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Abstract<p>Gypseous soils are considered one of the most problematic soils. The skirted foundation is an alternative technology that works to improve the bearing capacity and reduce settlement. This paper investigates the use of square skirted foundations resting on gypseous soil subjected to concentric and eccentric vertical load with eccentricity values of 4, 8, and 17 mm in 16 experimental model tests. To obtain the results by using this type of foundation, a small-scale physical model was designed to obtain the load–settlement behavior of the square skirted foundation; the dimension of the square footing is 100 mm × 100 mm with 1 mm thickness, the skirt depth (<italic>D</italic></p> ... Show More
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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Engineering
Influence of Nanomaterial Modifiers on Fatigue Resistance of Asphalt Concrete Mixtures: A Review Paper
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Enhancing fatigue resistance in asphalt binders and mixtures is crucial for prolonging pavement lifespan and improving road performance. Recent advancements in nanotechnology have introduced various nanomaterials such as alumina (NA), carbon nanotubes (CNTs), and silica (NS) as potential asphalt modifiers. These materials possess unique properties that address challenges related to asphalt fatigue. However, their effectiveness depends on proper dispersion and mixing techniques. This review examines the mixing methods used for each nanomaterial to ensure uniform distribution within the asphalt matrix and maximize performance benefits. Recent research findings are synthesized to elucidate how these nanomaterials and their mixing proce

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Publication Date
Tue Dec 19 2017
Journal Name
Al-khwarizmi Engineering Journal
Improve Wear Resistance on Al 332 Alloy Matrix- Micro -Nano Al2O3 Particles Reinforced Composite
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The wear behavior of alumina particulate reinforced A332 aluminium alloy composites produced by a stir casting process technique were investigated. A pin-on-disc type apparatus was employed for determining the sliding wear rate in composite samples at different grain size (1 µm, 12µm, 50 nm) and different weight percentage (0.05-0.1-0.5-1) wt% of alumina respectively. Mechanical properties characterization which strongly depends on microstructure properties of reinforcement revealed that the presence of ( nano , micro) alumina particulates lead to simultaneous increase in hardness, ultimate tensile stress (UTS), wear resistances. The results revealed that UTS, Hardness, Wear resistances increases with the increase in the percentage of

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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Prediction of Biodegradability Possibility for Sewage of the Dairy Industry
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he dairy industry is one of the industrial activities classified within the food industries in all phases of the dairy industry, which leads to an increase in the amount of wastewater discharged from this industry. The study was conducted in the Abu Ghraib dairy factory, classified as one of the central factories in Iraq, located in the west of Baghdad governorate, with a design capacity of 22,815 tons of dairy products. The characteristics of the liquid waste generated from the factory were determined for the following parameters biological oxygen demand (BOD5), Chemical oxygen demand (COD), total suspended solids (TSS), pH, nitrate, phosphate, chloride, and sulfate with an average value of (1079, 1945, 323, 9.2, 24, 2

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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