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Predicting Wetting Patterns in Soil from a Single Subsurface Drip Irrigation System

Soil wetted pattern from a subsurface drip plays great importance in the design of subsurface drip irrigation (SDI) system for delivering the required water directly to the roots of the plant. An equation to estimate the dimensions of the wetted area in soil are taking into account water uptake by roots is simulated numerically using HYDRUS (2D/3D) software. In this paper, three soil textures namely loamy sand, sandy loam, and loam soil were used with three different types of crops tomato, pepper, and cucumber, respectively, and different values of drip discharge, drip depth, and initial soil moisture content were proposed. The soil wetting patterns were obtained at every thirty minutes for a total time of irrigation equal to three hours. Equations for wetted width and depth were predicted and evaluated by utilizing the statistical parameters (model efficiency (EF), and root mean square error (RMSE)). The model efficiency was more than 95%, and RMSE did not exceed 0.64 cm for three soils. This shows that evolved formula can be utilized to describe the soil wetting pattern from SDI system with good accuracy.    

 

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Publication Date
Sun Jul 03 2016
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Hemostatic parameters in Thalassemia patients; a single institute experience

Background: Changes of coagulation profile have been described in patients with B-Thalassemia major. Prolongation of prothrombin time and partial thromboplastin time and reduced levels of coagulation factors and natural anticoagulants have been variously described though the mechanisms involved in the thrombotic tendency seen in some Thalassemia patients have not been fully clarified.
Objectives: To investigate changes in the coagulation profile in patients with B-Thalassemia according to the available hemostatic parameters in Thalassemia patients in Al-Karama Teaching Hospital in Wasit governorate.
Methods: Hemostatic variables were studied in pre-transfusion blood samples from 50 transfusion-dependent children with Beta Thalassem

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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Publication Date
Wed Apr 01 2009
Journal Name
International Journal Of Applied Environmental Sciences
An expert System for Predicting the Effects of Noise Pollution on Grass Trimming Task Using Fuzzy Modeling

Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents

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Publication Date
Wed Jun 01 2022
Journal Name
International Dental Journal
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Scoping Review of Machine Learning Techniques and Their Utilisation in Predicting Heart Diseases

Heart diseases are diverse, common, and dangerous diseases that affect the heart's function. They appear as a result of genetic factors or unhealthy practices. Furthermore, they are the leading cause of mortalities in the world. Cardiovascular diseases seriously concern the health and activity of the heart by narrowing the arteries and reducing the amount of blood received by the heart, which leads to high blood pressure and high cholesterol. In addition, healthcare workers and physicians need intelligent technologies that help them analyze and predict based on patients’ data for early detection of heart diseases to find the appropriate treatment for them because these diseases appear on the patient without pain or noticeable symptoms,

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index

Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

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Publication Date
Tue Jun 30 2020
Journal Name
Membranes
Experimental and Theoretical Analysis of Lead Pb2+ and Cd2+ Retention from a Single Salt Using a Hollow Fiber PES Membrane

The present work reports the performance of three types of polyethersulfone (PES) membrane in the removal of highly polluting and toxic lead Pb2+ and cadmium Cd2+ ions from a single salt. This study investigated the effect of operating variables, including pH, types of PES membrane, and feed concentration, on the separation process. The transport parameters and mass transfer coefficient (k) of the membranes were estimated using the combined film theory-solution-diffusion (CFSD), combined film theory-Spiegler-Kedem (CFSK), and combined film theory-finely-porous (CFFP) membrane transport models. Various parameters were used to estimate the enrichment factors, concentration polarization modulus, and Péclet number. The pH values signif

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Publication Date
Mon Nov 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
A study of Irrigation Water Pollution By Some Heavy Metals in Baghdad Governorate
Abstract<p>A study of irrigation water was conducted Baghdad city to find out extent of its pollution by some heavy metals (Pb, Cd, Ni, Co, CU, Cr, Zn and Fe). Water samples were collected randomly from different sources (river, well and stream). Results showed that the concentration of studied heavy metals were as follows: Lead between 0.43-11.75 mg L<sup>-1</sup>, Cadmium between 0.01-0.95 mg L<sup>-1</sup>, Nickel between 0.008-0.46 mg L<sup>-1</sup>, Cobalt between Nil - 0.185 mg L<sup>-1</sup>, Copper is between 0.326 - 1.58 mg L<sup>-1</sup>, Chromium is between Nil-0.068 mg L<sup>-1</sup>, Zinc 0.398-1.182 mg L<sup>-1</sup>, as for Iro</p> ... Show More
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