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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
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Wed May 01 2024
Journal Name
Scientific Visualization
Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

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Publication Date
Sun Sep 03 2023
Journal Name
Iraqi Journal Of Computers, Communications, Control & Systems Engineering (ijccce)
Efficient Iris Image Recognition System Based on Machine Learning Approach
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HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

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Publication Date
Wed Jan 01 2025
Journal Name
Fusion: Practice And Applications
Enhanced EEG Signal Classification Using Machine Learning and Optimization Algorithm
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This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

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Publication Date
Tue Jul 01 2014
Journal Name
International Journal Of Artificial Intelligence And Mechatronics
Machining Polylines and Ellipses using Three-Axis CNC Milling Machine
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CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Local Search Algorithms for Multi-criteria Single Machine Scheduling Problem
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   Real life scheduling problems require the decision maker to consider a number of criteria before arriving at any decision. In this paper, we consider the multi-criteria scheduling problem of n jobs on single machine to minimize a function of five criteria denoted by total completion times (∑), total tardiness (∑), total earliness (∑), maximum tardiness () and maximum earliness (). The single machine total tardiness problem and total earliness problem are already NP-hard, so the considered problem is strongly NP-hard.

We apply two local search algorithms (LSAs) descent method (DM) and simulated annealing method (SM) for the 1// (∑∑∑

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Publication Date
Sat Jan 19 2019
Journal Name
Artificial Intelligence Review
Survey on supervised machine learning techniques for automatic text classification
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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Identifying the Phenomenon of monopoly according to the vision of Accounting
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The research seeks to identify the factors affecting the monopoly and the possibility of measuring the phenomenon of economic ( monopolistic profit) accounted for and that the importance of research topic arising from the transformation of the majority of developing countries to the market economy, which represents the image of the capitalist economy, which is a monopoly, a stages that economy in its various forms, whether Market Worldwide sales monopoly or monopoly, which generates absolute monopolistic profits, which more or less affect on the overall economy of those countries than they should study the phenomenon of monopoly and its impact on the economies of those countries that still love to find her site reinforces its pos

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Publication Date
Sat Jun 01 2013
Journal Name
Int. J. Nanoelectronics And Materials
The response of a window glass to the frequencies of sound
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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Isolation and Identification of Fungi from Clinical Samples of Diabetic Patients and Studying the Anti-Fungal Activity of Some Natural Oils on Isolated Fungi
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Isolation of fungi was performed from February to July, 2019. One hundred clinical specimens were collected from King Abdullah Hospital (KAH) Bisha, Saudi Arabia. Samples were collected from twenty patients of different ages (30 - 70 years old) ten males and ten females. The samples were collected from patients with the two types of diabetics. Specimens included blood, hair, nail, oral swabs and skin.  Specimens were inoculated on Sabourauds Dextrose agar containing chloramphenicol. Thirteen fungal species were isolated and identified. The isolated species were: Aspergillus flavus, A. niger, A. terrus, A. nidulans, A. fumigatus, Candida albicans, C. krusei, C. parapsilosis, C. Tropicalis, Curvularia lunata, Fusarium solani, Penicill

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