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Improving Water Use Efficiency and Water Productivity for Okra Crop by using Subsurface Water Retention Technology
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Utilizing the modern technologies in agriculture such as subsurface water retention techniques were developed to improve water storage capacities in the root zone depth. Moreover, this technique was maximizing the reduction in irrigation losses and increasing the water use efficiency. In this paper, a polyethylene membrane was installed within the root zone of okra crop through the spring growing season 2017 inside the greenhouse to improve water use efficiency and water productivity of okra crop. The research work was conducted in the field located in the north of Babylon Governorate in Sadat Al Hindiya Township seventy-eight kilometers from Baghdad city. Three treatments plots were used for the comparison using surface trickle irrigation system: Polyethylene sheet (SWRT) was used in plot T1, controlled irrigation in plot T2 and uncontrolled irrigation in plot T3. Irrigation quantities, time of irrigation, soil water contents were measured for all treatments plots. The results indicated that water use efficiency for the three experimental plots, T1, T2, and T3 were: 2.43, 1.94 and 0.98 kg/m3, respectively.  The increasing value in water use efficiency of T1 plot compared with T2 and T3 plots were 25 and 148 %, respectively. Additionally, the water productivity of okra crop for T1, T2, and T3 plots was: 12800.9, 8744.8, and 4736.3 ID/m3, respectively. The increasing value of the water productivity of T1 compared with plots T2 and T3 was 46 and 170 %, respectively. From this study, the benefit of using membrane sheet below the soil surface resulted in an increase in the value of yield, water use efficiency and water productivity. Moreover, saving water and reduced the water losses by deep percolation were resulted.   

  

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Publication Date
Mon Jan 01 2024
Journal Name
Jordanian Journal Of Computers And Information Technology
BEYOND WORDS: HARNESSING SPEECH SOUND FOR SPEAKER AGE AND GENDER DETECTION USING 1D CNN ARCHITECTURE WITH SELF-ATTENTION MECHANISM
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Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio

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Publication Date
Fri Feb 20 2026
Journal Name
Modern Sport
The effect of Developing special endurance using multiple round periods on some physical and functional indicators for elite boxers
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Publication Date
Tue Dec 07 2021
Design and numerical verification of a polarization-independent grating coupler using a double-layer approach for visible wavelengths applications
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Publication Date
Sun Jan 13 2019
Journal Name
Iraqi Journal Of Physics
Measurements of radon, thoron and their progeny concentrations using twin cup dosimeter for indoor Al-Madaan city – Baghdad – Iraq
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In this study, the activity concentrations of indoor radon, thoron
and their progeny have been measured in air for 61 different
locations of Al-Maddan city using twin cup dosimeter. Furthermore,
some useful parameters concerning the health hazards have been
estimated; working level month (WLM), annual effective dose (Eff),
and excess lung cancer per million person per year (ELC).The results
show that the values of radon gas levels in the investigated districts
varied from 56.28 to 194.43Bq/m3with an overall average value
132.96Bq/m3, while 0.313 to 1.085 for WLM with an overall average
0.740, respectively. The value of Eff and ELC have been found to
vary from 1.420 to 4.918 mSv/y with an overall average valu

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study Using the Passive Solar Chimney for Evaporative Cooling With PCM and CFM as a Thermal Energy Storage
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      In this work, a test room was built in Baghdad city, with (2*1.5*1.5) m3  in dimensions, while the solar chimneys (SC) were designed with aspect ratio (ar) bigger than 12. Test room was supplied by many solar collectors; vertical single side of air pass with ar equals 25, and tilted 45o double side of air passes with ar equals 50 for each pass, both collectors consist of flat thermal energy storage box collector (TESB) that covered by transparent clear acrylic sheet, third type of collector is array of evacuated tubular collectors with thermosyphon in 45o instelled  in the bottom of TESB of vertical SC. The TESB was

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Publication Date
Wed Oct 30 2024
Journal Name
Internet Technology Letters
Using <scp>5G</scp> Standards for Smart Healthcare Applications and Designing an Artificial Intelligence‐Based Industry 4.0 Communication System
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ABSTRACT<p>The introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing </p> ... Show More
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Publication Date
Sun Oct 01 2023
Journal Name
Applied Sciences
Multiobjective Optimization of Stereolithography for Dental Bridge Based on a Simple Shape Model Using Taguchi and Response Surface Methods
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Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi me

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Publication Date
Sun Aug 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Online 3D path planning for Tri-copter drone using GWO-IBA algorithm
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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Petroleum Research And Studies
Modeling of Oil Viscosity for Southern Iraqi Reservoirs using Neural Network Method
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The calculation of the oil density is more complex due to a wide range of pressuresand temperatures, which are always determined by specific conditions, pressure andtemperature. Therefore, the calculations that depend on oil components are moreaccurate and easier in finding such kind of requirements. The analyses of twenty liveoil samples are utilized. The three parameters Peng Robinson equation of state istuned to get match between measured and calculated oil viscosity. The Lohrenz-Bray-Clark (LBC) viscosity calculation technique is adopted to calculate the viscosity of oilfrom the given composition, pressure and temperature for 20 samples. The tunedequation of state is used to generate oil viscosity values for a range of temperatu

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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