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Study of NOx Emissions of S.I. Engine Fueled with Different Kinds of Hydrocarbon Fuels and Hydrogen
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      Liquefied petroleum gas (LPG), Natural gas (NG) and hydrogen were used to operate spark ignition internal combustion engine Ricardo E6, to compare NOx emissions emitted from the engine, with that emitted from engine fueled with gasoline as a fuel.

      The study was done when engine operated at HUCR for gasoline, compared with its operation at HUCR for each fuel. Compression ratio, equivalence ratio and spark timing were studied at constant speed 25rps.

The results appeared that NOx concentrations will be at maximum value in the lean side near the stoichiometric ratio, and reduced with moving away from this ratio for mixture at both sides, these concentrations were at its highest value when hydrogen used at CR=8:1, and got near to each other for the three hydrocarbon fuels used in the study, when the engine operated at HUCR for each fuel, but still hydrogen had maximum value, the main variable affect these concentrations was spark timing.

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Composites For Construction
Near-Surface-Mounted CFRP for Strengthening Concavely Curved Soffit RC Beams: Experimental and Analytical Investigation
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Publication Date
Tue Oct 15 2024
Journal Name
Mongolian Journal Of Chemistry
Using activated and modified adsorbent surfaces from banana peels to remove the green Janus dye:
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In order for the process of removing pollutants, including dyes, from the aquatic environment to be effective, plant wastes such as banana peels were used as adsorbent surfaces by thermally activating them (ABP) and modifying them with iron oxide nanoparticles (MABP), which were characterized using Fourier transform infrared (FT-IR) and X-ray diffraction (XRD) techniques. They were applied in the field of Janus green (JG) dye adsorption for the batch system and studied the effect of several factors (adsorbent weight, contact time, initial concentration, and temperature). Their data were analyzed kinetically using first- and second-order kinetic models and they were found to follow the second order. Their data were also analyzed thro

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Publication Date
Tue Nov 19 2024
Journal Name
Discover Sustainability
Groundwater quality assessment and pollution sources identification using statistical analyses at Missan Governorate, Southeast Iraq
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The shortage in surface water quantities led to a shift in dependence on the groundwater as an alternative water source in southern parts of Iraq. The groundwater is decreasing in quantity and water quality is degrading due to different factors. Therefore, it is important to assess the groundwater quality of the Missan Governorate of the country by analyzing the physicochemical parameters and distinguishing the probable sources of contaminants in the area. The present study used water quality diagrams and statistical methods such as factor analysis and agglomerative cluster analysis to determine the sources of chemical ions in the forty-four groundwater samples collected from wells in the study area. In addition, the Water Quality Index (WQ

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
The Suggested Reciprocal Relationship between Maximum, Minimum and Optimum Usable Frequency Parameters Over Iraqi Zone
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In this work, the relationship between the ionospheric parameters (Maximum Usable Frequency (MUF), Lowest Usable Frequency (LUF) and Optimum working Frequency (OWF)) has been studied for the ionosphere layer over the Iraqi zone. The capital Baghdad (44.42oE, 33.32oN) has been selected to represent the transmitter station and many other cities that spread over Iraqi region have represented as receiver stations. The REC533 communication model considered as one of the modern radio broadcasting version of ITU has been used to calculate the LUF parameter, while the MUF and OWF ionospheric parameters have been generated using ASAPS international communication model which represents one of the most advanced  and accurate HF sky wave prop

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Publication Date
Wed Sep 17 2025
Journal Name
Molecular Biology Reports
Antibacterial effect and MexA efflux pump Inhibition by green-synthesized copper nanoparticles from Mentha piperita
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Publication Date
Tue May 23 2023
Journal Name
Journal Of Sensors
On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping
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Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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Publication Date
Wed Sep 20 2017
Journal Name
Mechanical Sciences
Comparative experimental investigation and gap flow simulation in electrical discharge drilling using new electrode geometry
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Abstract. This study presents experimental and numerical investigation on the effectiveness of electrode geometry on flushing and debris removal in Electrical Discharge Drilling (EDD) process. A new electrode geometry, namely side-cut electrode, was designed and manufactured based on circular electrode geometry. Several drilling operations were performed on stainless steel 304 using rotary tubular electrodes with circular and side-cut geometries. Drilling performance was characterized by Material Removal Rate (MRR), Electrode Wear Rate (EWR), and Tool Wear Ratio (TWR). Dimensional features and surface quality of drilled holes were evaluated based on Overcut (OC), Hole Depth (HD), and Surface Roughness (SR). Three-dimensional

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Publication Date
Mon Oct 12 2020
Journal Name
Molecules
Phase Change Process in a Zigzag Plate Latent Heat Storage System during Melting and Solidification
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Applying a well-performing heat exchanger is an efficient way to fortify the relatively low thermal response of phase-change materials (PCMs), which have broad application prospects in the fields of thermal management and energy storage. In this study, an improved PCM melting and solidification in corrugated (zigzag) plate heat exchanger are numerically examined compared with smooth (flat) plate heat exchanger in both horizontal and vertical positions. The effects of the channel width (0.5 W, W, and 2 W) and the airflow temperature (318 K, 323 K, and 328 K) are exclusively studied and reported. The results reveal the much better performance of the horizontal corrugated configuration compared with the smooth channel during both melti

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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