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Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction
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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
Deep Learning Approach for Oil Pipeline Leakage Detection Using Image-Based Edge Detection Techniques
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Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

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Publication Date
Sun Jun 15 2025
Journal Name
Iraqi Journal Of Laser
Performance Enhancement of Metasurface Grating Polarizer Using Deep Learning for Quantum Key Distribution Systems
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Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Fri Feb 28 2025
Journal Name
International Journal Of Intelligent Engineering And Systems
MCNet: Mask Cell of Multi Class Deep Network for Blood Cells Detection and Classification
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Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

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Publication Date
Fri Aug 01 2025
Journal Name
Journal Of Communications
Deep Reinforcement Learning for Dynamic Routing, Modulation, and Spectrum Assignment in Elastic Optical Networks
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Publication Date
Mon Jun 30 2003
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Factors Affecting the Extraction Process
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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
With Solvent Extraction Method, and via new Organic Reagent 2-(Benzo thiazolyl azo)-4,5- Diphenyl Imidazole for Spectrophotometric Determination of Copper (II) in different Samples
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The new organic reagent 2-[Benzo thiazolyl azo]-4,5-diphenyl imidazole was prepared and used as complexing agent for separation and spectrophotometric determination of Cu2+ ion in some samples include plants, soil, water and human blood serum. Initially determined all factors effect on extraction method and the results show optimum pH was (pHex=9), optimum concentration was 40?g/5mLCu2+ and optimum shaking time was (15min.), as well stoichiometry study appears the complex structure was 1:1 Cu2+: BTADPI. Interferences effect of cations were studied. Synergism effect shows MIBK gave increasing in distribution ratio (D). Organic solvent effect appears there is no any linear relation between dielectric constant for organic solvent used and dis

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Publication Date
Fri Sep 24 2021
Journal Name
Indonesian Journal Of Chemistry
Molecular Imprinted of Nylon 6 for Selective Separation of Procaine by Solid-Phase Extraction
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The study is based on the selective binding ability of the drug compound procaine (PRO) on a surface imprinted with nylon 6 (N6) polymer. Physical characterization of the polymer template was performed by X-ray diffraction and DSC thermal analysis. The imprinted polymer showed a high adsorption capacity to trap procaine (237 µg/g) and excellent recognition ability with an imprinted factor equal to 3.2. The method was applied to an extraction column simulating a solid-phase extraction to separate the drug compound in the presence of tinoxicam and nucleosimide separately and in a mixture of them with a recovery rate more than the presence of tinoxicam and nucleosimide separately and in a mixture of them with a recovery rate of more t

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Publication Date
Tue Feb 12 2019
Journal Name
Iraqi Journal Of Physics
Lineament automatic extraction analysis for Galal Badra river basin using Landsat 8 satellite image
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This research including lineament automated extraction by using PCI Geomatica program, depending on satellite image and lineament analysis by using GIS program. Analysis included density analysis, length density analysis and intersection density analysis. When calculate the slope map for the study area, found the relationship between the slope and lineament density.
The lineament density increases in the regions that have high values for the slope, show that lineament play an important role in the classification process as it isolates the class for the other were observed in Iranian territory, clearly, also show that one of the lineament hit shoulders of Galal Badra dam and the surrounding areas dam. So should take into consideration

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Level of uric acid and its, relationship with lipid peroxidation in sera of patients with acute coronary syndrome
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Unstable angina pectoris often leads to acute myocardial infarction. Since uric acid is thought to be risk factor for cardiovascular disease and considered a major antioxidant in human blood .The level of uric acid and lipid peroxidation in the sera of patients with unstable angina and myocardial infarction were measured and compared to the healthy individuals. Twenty-nine patients with unstable angina and twenty-nine patients with myocardial infarction were studied and compared to twenty-five healthy individuals. Uric acid was measured by using Human Kit. Malondialdelyde (MDA) a lipid peroxidation marker, was measured by thiobarbituric acid method .Significant elevation of uric acid and MDA were observed in the sera of pati

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