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An Enhanced Document Source Identification System for Printer Forensic Applications based on the Boosted Quantum KNN Classifier
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Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing characteristics effectively. This study proposes leveraging quantum-inspired computing to improve KNN classifiers for printer source identification, offering better accuracy even with noisy or variable printing conditions. The proposed approach uses the Gray Level Co-occurrence Matrix (GLCM) for feature extraction, which is resilient to changes in rotation and scale, making it well-suited for texture analysis. Experimental results show that the quantum-inspired KNN classifier captures subtle printing artifacts, leading to improved classification accuracy despite noise and variability.

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Publication Date
Sun Mar 01 2020
Journal Name
Materials Research Express
Spray pyrolysis of graphene oxide based composite for optical and wettability applications
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Abstract<p>In this study, silica-graphene oxide nano–composites were prepared by sol-gel technique and deposited by spray pyrolysis method on glass substrate. The effect of changing the graphene/silica ratio on the optical properties and wetting of these nano–structures has been investigated. The structural and morphological properties of the thin films have been studied by x-ray diffraction spectroscopy (XRD), field emission scanning electron microscope (FESEM), energy dispersive x-ray spectroscopy (EDS) and atomic force microscope (AFM). XRD results show that silica structures present in the synthesized films exhibit amorphous character and there is a poor arrangement in graphene plates al</p> ... Show More
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials &amp; Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Sun Nov 27 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
open-source enterprise resource planning system Odoo roll in rationalizing the costs of the Ishtar Sheraton Hotel/ applied research
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The Accommodation industry in Iraq suffers from many problems, especially after 2003, when the Accommodation industry was exposed to many crises due to the security and political situation in Iraq, which negatively affected the administrative operations inside the industry and created many problems, the most important of which are deterioration, high costs and poor performance, so some hotel administrations sought To find alternative solutions that help in the advancement of hotels, one of the proposals is to go to technology, as technology is currently one of the most important solutions to solve large complex problems, as the world has turned to automation to solve complex problems such as increasing production, reducing costs, and rai

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Publication Date
Mon Jan 01 2024
Journal Name
Studies In Systems, Decision And Control
The Effect of Using an Accounting Information System Based on Artificial Intelligence in Detecting Earnings Management to Enhance the Sustainability of Economic Units
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This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Real-Time Cloth Simulation on Virtual Human Character Using Enhanced Position Based Dynamic Framework Technique
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     Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit

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Publication Date
Tue Oct 01 2024
Journal Name
Analytical And Bioanalytical Electrochemistry
New Electrochemical Sensors for Determination of Tamoxifen Based on Enhanced Polymer Nano Composite Deep Eutectic Solvent and Water Mixture as Ionophores
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Publication Date
Tue Oct 30 2018
Journal Name
Iraqi Journal Of Physics
N3, N749 dyes effect on the TiO2 for optoelectronic applications
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The present work aimed to study effect of (N749 & N3) dyes on TiO2 optical and electrical properties for optoelectronic application. The TiO2 paste prepared by using a doctor blade method. The samples were UV-VIS specterophometricall analyzes of TiO2 before and after immersed in dyes (N749 & N3). The results showed absorption spectra shift toward the visible region due to the adsorption of dye molecules on the surface of oxide nanoparticles. It is seen that the Eg determined to give a value of 3.3eV for TiO2 before immersing in dyes, and immersing in dyes (N749 & N3) are (1.4 &1.6 eV) respectively. The structural properties (XRD), (FTIR) and (SEM) for the sample prepared were investigated and (J-V) characteristics was stu

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Pose Invariant Palm Vein Identification System using Convolutional Neural Network
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Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
The Energy Spectra and Heat Capacity of GaAs Gaussian Quantum Dot in an External Magnetic Field
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In this paper, a theoretical study of the energy spectra and the heat capacity of one electron quantum dot with Gaussian Confinement in an external magnetic field are presented. Using the exact diagonalization technique, the Hamiltonian of the Gaussian Quantum Dot (GQD) including the electron spin is solved. All the elements in the energy matrix are found in closed form. The eigenenergies of the electron were displayed as a function of magnetic field, Gaussian confinement potential depth and quantum dot size. Explanations to the behavior of the quantum dot heat capacity curve, as a function of external applied magnetic field and temperature, are presented.

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