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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 Nov 01 2019
Journal Name
Journal Of Engineering
Prediction of Heat Transfer Coefficient and Pressure Drop in Wire Heat Exchanger Working with R-134a and R-600a
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An experimental and theoretical works were carried out to model the wire condenser in the domestic refrigerator by calculating the heat transfer coefficient and pressure drop and finding the optimum performance. The two methods were used for calculation, zone method, and an integral method. The work was conducted by using two wire condensers with equal length but different in tube diameters, two refrigerants, R-134a and R-600a, and two different compressors matching the refrigerant type. In the experimental work, the optimum charge was found for the refrigerator according to ASHRAE recommendation. Then, the tests were done at 32˚C ambient temperature in a closed room with dimension (2m*2m*3m). The results showed that th

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Prediction Using Artificial Neural Network of Bed Porosity and Solid Holdup in Viscous 3-Phase Inverse Fluidization
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In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid

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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Rigid Trunk Sewer Deterioration Prediction Models using Multiple Discriminant and Neural Network Models in Baghdad City, Iraq
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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Engineering
Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
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The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Multiphase Flow Behavior Prediction and Optimal Correlation Selection for Vertical Lift Performance in Faihaa Oil Field, Iraq
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In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
The Prediction of the Electromagnetic Properties and the ?(E2/M1) of 110-116Cd-Isotopes in IBM Model
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The Nuclear structure of 110-116Cd isotopes was studied theoretically in the framework of the interacting boson model of IBM-l and IBM-2. The properties of the lowest mixed symmetry states such as the 1+, 2+ and 3+ levels produced by the IBM-2 model in the vibrational-limit U(5) of Cd - isotopes are studied in details. This analysis shows that the character of mixed symmetry of 2+ is shared between and states in 110-114Cd – isotopes, the large shar goes to s, while in isotope, the state is declared as a mixed symmetry state without sharing. This identification is confirmed by the percentage of F-spin contribution. The electromagnetic properties of E2 and Ml operators were investigated and the results were analyzed. Various

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
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Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation stretching. In SPIF process, the research is concentrate on the development of predict models for estimate the product quality. Using simulated annealing algorithm (SAA), Surface quality in SPIF has been modeled. In the development of this predictive model, spindle speed, feed rate and step depth have been considered as model parameters. Maximum peak height (Rz) and Arithmetic mean surface roughness (Ra) are used as response parameter to assess th

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Publication Date
Thu Dec 20 2018
Journal Name
مجلة العلوم الاجتماعية والتربوية (ريس)
The acquisition of the concepts of nanotechnology by the students of chemistry in the college of Education for pure Sciences/ibn Al-Haytham and it`s relation to their technological
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One of the scientific education aims, preparing a student able to keep up with the scientific developments and innovations around him and make him contribute, adapt, investment and continue development. The concepts of nanotechnology from scientific innovation open up an important area of thinking and intervention in the field of chemistry applications in daily life, the technological changes lead to social, political and economic changes which result that the students to have the knowledge, understanding, awareness, appreciation and sense in applications of modern technology for their use optimally, in order to cope with these scientific and technological changes. The research aims at finding out the correlation between the acquisi

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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Heave Behavior of Granular Pile Anchor-Foundation System (GPA-Foundation System) in Expansive Soil
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Granular  Pile  Anchor  (GPA)  is  one  of  the  innovative  foundation  techniques,  devised  for mitigating heave of footing resulting from the expansive soils. This research attempts to study the heave behavior of (GPA-Foundation System) in expansive soil. Laboratory tests have been conducted on an experimental model in addition to a series of numerical modeling and analysis using the finite element package PLAXIS software. The effects of different parameters, such as (GPA) length (L) and diameter (D), footing diameter (B), expansive clay layer thickness (H) and presence of non-expansive clay are studied. The results proved the efficiency of (GPA) in reducing the heave of exp

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