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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
Mon Jan 11 2021
Journal Name
Earth And Environmental Science
Impact Resistance of Limestone Cement Self Compacting Concrete Reinforced by Locally Available Grids
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Impact strength of self-compacted concrete is a field of interest, mostly when the concrete is produced from sustainable materials. This research's main objective is to clarify the ability to use two types of Portland limestone cement (Karasta and Tasluja) in self compacted concrete under impact loading, further to the economic and environmental benefits of the limestone cement. The impact loading was applied by a low-speed test, using the drop ball on concrete. Moreover, the study reveals the resistance of the grids reinforced concrete to impact loading by using polymer grid, and steel grid reinforced concrete slabs. Mixes reinforced by steel mesh had the highest results, indicating that the steel mesh was more robust because it had

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
A Modified Approach by Using Prediction to Build a Best Threshold in ARX Model with Practical Application
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The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

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Publication Date
Wed Oct 21 2015
Journal Name
Integrated Journal Of Engineering Research And Technology
A HYBRID CUCKOO SEARCH AND BACK-PROPAGATION ALGORITHMS WITH DYNAMIC LEARNING RATE TO SPEED UP THE CONVERGENCE (SUBPL) ALGORITHM
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
Bacterial Causes Tonsillitis in Children, Study the Resistance to Antimicrobials and the Effect of Clove Extracts on Selected Isolated Bacteria.
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In this study Isolated Pathogenic bacteria which causes Tonsillitis in Children with ages between 3-17 years. They are admitted to Central Children Hospital (Al-Karch) and Ebn-Albalady Hospital (Al-Rusafa). 200 cases were collected which include 120 Male and 80 Female. The result of the recent study shows that the isolation percentage was 40% from Male and 35% from Female. In this study Fifty six isolated were Identified, 20 were ?-hemolytic Streptococcus which was Streptococcus pyogenes, formed (36%) from all isolated.6 Pathogenic bacteria were ?- hemolytic Streptococcus which was Streptococcus pneumoniae formed (11%). The number of Moraxella catarrhalis bacteria was 12 formed (21%), the number of Haemophilus influenzae was 1

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering
Load-settlement Behavior of Steel Piles in Different Sandy Soil Configurations
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In the case where a shallow foundation does not satisfy with design requirements alone, the addition of a pile may be suitable to improve the performance of the foundation design. The lack of in-situ data and the complexity of the issues caused by lagging in the research area of pile foundations are notable. In this study, different types of piles were used under the same geometric conditions to determine the load-settlement relationships with various sandy soil relative densities. The ultimate pile capacity for each selected pile is obtained from a modified California Bearing Ratio (CBR) machine to be suitable for axial pile loading. Based on the results, the values of Qu for close-ended square pile were increased by 15

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Publication Date
Sun Jan 21 2018
Journal Name
The Iraqi Geological Journal
GEOCHEMICAL PARTITIONING OF HEAVY METALS IN THE URBAN SOIL, KIRKUK, IRAQ
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This work focused on anthropogenic influences of the trace metals distribution in the soils of Kirkuk city. Sequential extraction technique was used to determine the distribution of the chemical fractions of Ag, Cd, Co, Cu, Ni, Pb, Zn, As, Cr and V in soil of Kirkuk city. This area is affected mainly by burning oil trash. Results show that these heavy metals were primarily restricted to surface horizons and mostly associated with the residual fraction (28.8 – 50%). The remnant fractions (13.8 – 33.1%) linked to the organic matter, 7.9 – 27.2% was bound to Fe-Mn oxide, 0.7 – 27.9 was bound to carbonate. Only a small amount of the total metals in the soil is exchangeable (0.5 – 4.2%) and water soluble (0 – 4.1%) fractions.

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Publication Date
Thu Jan 01 2015
Journal Name
Mj Journal On Applied Mathematics
Mathematical models for estimation the concentration of heavy metals in soil
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Publication Date
Fri Jan 01 2016
Journal Name
Lap Lambert Academic Publishing
New Technique to Estimate the concentration of Heavy Metals in soil
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There are many aims of this book: The first aim is to develop a model equation that describes the spread of contamination through soils which can be used to determine the rate of environmental contamination by estimate the concentration of heavy metals (HMs) in soil. The developed model equation can be considered as a good representation for a problem of environmental contamination. The second aim of this work is to design two feed forward neural networks (FFNN) as an alternative accurate technique to determine the rate of environmental contamination which can be used to solve the model equation. The first network is to simulate the soil parameters which can be used as input data in the second suggested network, while the second network sim

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Publication Date
Tue Oct 08 2019
Journal Name
Asa-cssa-sssa International Annual Meeting
Cover Crop Effects on Soil Health in Organic High Tunnels (2019).
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High tunnels, or unheated plastic greenhouses, are becoming increasingly popular among organic vegetable growers across the United States. However, the intensive production typical of these systems presents soil health challenges, including salinization due to high fertilizer or compost inputs coupled with lack of rainfall to leach salts. Legume cover crops may improve soil health in high tunnels by reducing the need for external inputs, while adding organic matter. We tested the soil health effects of a winter hairy vetch (Vicia villosa Roth) cover crop used to replace fertilizer N in an organic tomato cropping system in high tunnels. Studies were replicated across three sites differing in climate and soil type (Kansas, Kentucky, and Minne

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
Effect of Cyanobacteria Isolates on Rice Seeds Germination in Saline Soil
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Cyanobacteria are prokaryotic photosynthetic communities which are used in biofertilization of many plants especially rice plant. Cyanobacteria play a vital role to increase the plant's ability for salinity tolerance. Salinity is a worldwide problem which affects the growth and productivity of crops. In this work three cyanobacteria strains (Nostoc calcicola, Anabaena variabilis, and Nostoc linkia) were isolated from saline soil at Kafr El-Sheikh Governorate; North Egypt. The propagated cyanobacteria strains were used to withstand salinity of the soil and increase rice plant growth (Giza 178). The length of roots and shoot seedlings was measured for seven and forty days of cultivation, respectively. The results of this investigation showed

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