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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 Jun 01 2008
Journal Name
Baghdad Science Journal
Tamper Detection in Text Document
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Although text document images authentication is difficult due to the binary nature and clear separation between the background and foreground but it is getting higher demand for many applications. Most previous researches in this field depend on insertion watermark in the document, the drawback in these techniques lie in the fact that changing pixel values in a binary document could introduce irregularities that are very visually noticeable. In this paper, a new method is proposed for object-based text document authentication, in which I propose a different approach where a text document is signed by shifting individual words slightly left or right from their original positions to make the center of gravity for each line fall in with the m

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Publication Date
Sun Aug 28 2016
Journal Name
World Journal Of Pharmacy And Pharmaceutical Sciences
AN INSIGHT ON THE IDENTIFICATION OF CANCER STEM CELLS USING NOVEL IMMUNOLOGICAL AND MOLECULAR STRATEGIES
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Cancer stem cells (CSCs) are defined as a population of cells present in tumours, which can undergo self-renewal and differentiation. Identification and isolation of these CSCs using putative surface markers have been a priority of research in cancer. With this background we selected pancreatic normal and tumor cells for this study and passaged them into animal tissue culture medium. Further staining was done using alkaline phosphatase and heamatoxilin staining. Blue to purple colored zones in undifferentiated pluripotent stem cells and clear coloration in the chromatin material indicated pancreatic cells. Further studies on the cell surface marker CD 44 were done using ELISA. For this, the protein was extracted from cultivated normal and t

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Publication Date
Thu Sep 01 2016
Journal Name
2016 8th Computer Science And Electronic Engineering (ceec)
Class-specific pre-trained sparse autoencoders for learning effective features for document classification
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Publication Date
Wed Aug 12 2020
Journal Name
International Journal On Advanced Science, Engineering And Information Technology
Developing of a 3D Printer to Produce Parts Using Powder Metal
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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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Publication Date
Mon Jul 01 2019
Journal Name
Applied Mathematical Modelling
Potential flow of fluid from an elevated, two-dimensional source
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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials & Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of forensic accounting in resolving banking disputes: an applied research on a sample of private banks listed in the Iraq Stock Exchange
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This study aims to identify the role of forensic accounting in resolving banking disputes in the Iraqi environment, and to achieve this goal, the fiel

d survey method was used, as it is the most appropriate for studying the phenomenon in question and achieving its objectives. A sample of (50) male and female employees was selected, distributed among five banks listed on the Iraq Stock Exchange in the Baghdad governorate. The questionnaire tool prepared for this purpose was applied to them, which consisted of two main axes. The first axis included paragraphs of questions related to the importance of forensic accounting. The second axis relates to disputes At the end of the research, we reached a set of conclusions, the most import

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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Mon Aug 01 2011
Journal Name
International Journal Of Research And Reviews In Computer Science
Detection of the photon number splitting attack by using decoy states quantum key distribution system
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The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.