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Studying of the Amount of Energy Required to Operate the Nursery Tray Planting Machine
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Abstract<p>A study was conducted at the University of Baghdad-College of Agricultural Engineering Sciences - Department of Agricultural Machinery and Equipment for the agricultural season 2023 with the aim of designing, manufacturing and testing a machine used to planting agricultural nursery tray with different types of vegetable or horticultural seeds or forest seeds of various forms, and using different agricultural media where they are conducted The planting process is by pulling the seeds with a negative pressure vacuum system, and then they are feding to the dishes in their right place to complete the planting process. The study included three factors: The speed of the main belt in three levels: 0.43, 0.66 and 0.90 m.sec<sup>−1</sup> and three types of agricultural media: Petmus, mix of Petmos and silt 1:1 and silt, and three types of seeds that were planted. A factorial experiment was carried out using a design (CRD) with three replications using the least significant difference and a probability level (LSD = 0.05) to compare the mean of the coefficients. Some performance indicators of the machine were studied, including: Consumed electrical power, electric power, the productivity of the machine, and the efficiency of the machine in picking seeds. The results indicated The peat moss medium excelled in recording the least consumed electric power, which amounted to 2075.8 watts, and the lowest electric power, which amounted to 0.007751 kWh. And the third speed of the conveyor belt excelled in achieving the highest productivity of dishes per hour, amounting to 105.08 dishes.hour<sup>−1</sup>, and the first speed achieved the least consumed power, amounting to 2047.3 watts, and the least consumed electrical energy at the third speed, which amounted to 0.007703 kWh.</p>
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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Studying Biomimetic Coated Niobium as an Alternative Dental Implant Material to Titanium (in vitro and in vivo study)
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Commercially pure titanium (cpTi) is widely used as dental implant material although it was found that titanium exhibited high modulus of elasticity and the lower corrosion tendency in oral environment. Niobium(Nb) was chosen for this study as an alternative to cpTi implant material due to its bioinert behavior and good elastic modulus and moderate cost in addition to corrosion resistance. This study was done to evaluate the effect of biomimetic coating on the surface properties of the commercially pure titanium and niobium implants by in vitro and in vivo experiments. The in vitro study was involved etching the samples of each material in HCl then soaking in 10M NaOH aqueous solution. These samples were then immersed in a 5 times concent

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Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
Studying Optical Properties of Quantum Dot Cylindrical Fresnel Lens
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An optical system including quantum dot cylindrical Fresnel lens (CFL) has been designed by using Zemax optical designing program. Quantum dot cylindrical Fresnel lens has a relatively small thickness compared to conventional lenses and high absorbance. It contains grooves in the form of parallel lines, and each groove represents an individual lens that works to change the path of light falling on it to a single focal line. (CFL) is characterized by its small focal length despite its large area and small thickness, due to the nature of its design that gives this feature, which is applied in many optical systems (imaging and non- imaging system). In this paper, the visual properties of the (CFL) were studied as it is one of the impor

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Publication Date
Sun Jun 01 2014
Journal Name
Soils And Foundations
Studying collapse potential of gypseous soil treated by grouting
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Publication Date
Tue Dec 15 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Studying properties of propagated transverse modes through optical fibers
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDYING THE EFFECT OF Proteinase K AND α-Amylase ON INHIBITION OF Staphylococcus aureus AND Klebsiella pneumoniae BIOFILM ISOLATE FROM URINARY TRACT INFECTION.: STUDYING THE EFFECT OF Proteinase K AND α-Amylase ON INHIBITION OF Staphylococcus aureus AND Klebsiella pneumoniae BIOFILM ISOLATE FROM URINARY TRACT INFECTION.
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The current study aimed to investigate the viability of biofilm formation klebsilla pneumoniae and Staphylococcus aureus. 440 urine samples were collected from patients suffering from urinary tract infection (UTI) from those who were admitted and visitors to Al-Ramadi Teaching Hospital, Al-Yarmouk Teaching Hospital, Al-Ramadi Teaching Hospital for women and children and , Teaching Laboratories in the Medical City for both genders for a period extended from 5 July, 2017 to 10 October, 2017. Samples were diagnosed by culturing them on a selective media and by biochemical testes , also, diagnosis was ensured by using VITEK-2 compact system. Results showed that K.pneumoniae isolation ratio was 17.1%(68) and S.aureus ratio was 13.1%(52). Thei

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Publication Date
Sun Mar 12 2023
Journal Name
Egyptian Journal Of Chemistry
Studying the Molecular Interactions for Potash Alum with Distilled Water and Aqueous Solution of Ethylene Glycol at Different Temperatures.
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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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