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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 Sep 29 2023
Journal Name
Pakistan Journal Of Ophthalmology
Corneal Parameters Measurement in Healthy Subjects Using Scheimpflug and Anterior Segment Optical Coherence Tomography
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Purpose:  To compare the central corneal thickness (CCT),minimum corneal thickness (MCT) and corneal power measured using theScheimpflug-Placido device and optical coherence tomography (OCT) in healthy eyes. Study Design:  Descriptive observational. Place and Duration of Study:  Al-Kindy college of medicine/university of Baghdad, from June 2021 to April 2022. Methods:  A total of 200 eyes of 200 individuals were enrolled in this study. CCT and MCT measurements were carried out using spectral-domain optical coherence tomography (Optovue) and a Scheimpflug-Placido topographer (Sirius).The agreement between the two approaches was assessed using Bland-Altman analysis in this study. Results:  Mean age was 28.54 ± 6.6 years, me

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Publication Date
Wed Jun 11 2003
Journal Name
Iraqi Journal Of Laser
Microdrop Size Measurement in a Mixing Unit Using Laser Technique
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One of the troublesome duties in chemical industrial units is determining the instantaneous drop size distribution, which is created between two immiscible liquids within such units. In this work a complete system for measuring instantaneous droplet size is constructed. It consists of laser detection system (1mW He-Ne laser), drop generation system (turbine mixer unit), and microphotography system. Two immiscible liquids, water and kerosene were mixed together with different low volume fractions (0.0025, 0.02) of kerosene (as a dispersed phase) in water (as a continuous phase). The experiments were carried out at different rotational speed (1180- 2090 r.p.m) of the turbine mixer. The Sauter mean diameter of the drops was determined by la

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
A Survey on Arabic Text Classification Using Deep and Machine Learning Algorithms
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    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Tue May 16 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Comparative Study of Anemia Classification Algorithms for International and Newly CBC Datasets
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Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

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Publication Date
Thu Oct 01 2020
Journal Name
Iraqi Journal Of Biotechnology,
Isolation and Identification of Multidrug Resistance Among Clinical and Environmental Pseudomonas aeruginosa Isolates
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Pseudomonas aeruginosa is the most common opportunistic pathogen causing morbidity and mortality in hospitalized patients due to its multiple resistance mechanisms. Therefore, as a therapeutic option becomes restricted, the search for a new agent is a preference. So P. aeruginosa is an extremely versatile Gram-negative bacterium capable of thriving in a broad spectrum of environments, and this performs main problems to workers in the field of health. One hundred and fifty samples were collected from different sources from Baghdad hospitals, divided into two main groups: clinical (100) specimens and (50) samples as an environmental, collected from October 2019 to the March 2020. All of these samples were cultured by specific and differential

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Publication Date
Mon Jan 28 2019
Journal Name
Journal Of The College Of Education For Women
Physical and chemical properties of soil in the Karkh district
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The study area soils suffer from several problems appear as tkhesvat and cracks in the roads and waterlogging which reduces the susceptibility of soil to withstand pressure, this study was conducted on the soil of the Karkh district based on field study that included (6) samples of soil physical analyses contain different ratios of (mud, sand, silt) as percentages (52%, 45%, 3 #) respectively, and liquidity limit rate (39%) Stroke rate plasticity was (20.6%) The rate coefficient of plasticity total (19.2%)0

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Publication Date
Sun Nov 01 2020
Journal Name
Chemosphere
Sorption and degradation of ranitidine in soil: Leaching potential assessment
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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Strength and Compressibility of Screw Piles Constructed in Gypseous Soil
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Abstract<p>The present work deals with the performance of screw piles constructed in gypseous soil of medium relative density; such piles are extensively used in piles foundations supported structures subjected to axial forces. The carrying capacity and settlement of a single screw pile model of several diameters (20, 30, and 40) mm inserted in gypseous soil is investigated in the present study. The gypsum content of soil used in tests was 40%. The bedding soil used in tests was prepared by raining technique with a relative density of 40%. A physical model was manufactured to demonstrate the tests in the laboratory. The model of screw pile has been manufactured of steel with a total length of 50</p> ... Show More
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Publication Date
Thu Mar 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks
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Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

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