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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
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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Publication Date
Fri Dec 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Airborne Computer System Based Collision-Free Flight Path Finding Strategy Design for Drone Model
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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
High Order Sliding Mode Observer-Based Output Feedback Controller Design For Electro-Hydraulic System
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A perturbed linear system with property of strong observability ensures that there is a sliding mode observer to estimate the unknown form inputs together with states estimation. In the case of the electro-hydraulic system with piston position measured output, the above property is not met. In this paper, the output and its derivatives estimation were used to build a dynamic structure that satisfy the condition of strongly observable. A high order sliding mode observer (HOSMO) was used to estimate both the resulting unknown perturbation term and the output derivatives. Thereafter with one signal from the whole system (piton position), the piston position make tracking to desire one with a simple linear output feedback controller after ca

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Publication Date
Thu Feb 01 2024
Journal Name
International Journal Of Biological Macromolecules
A novel designed nanofibrous mat based on hydroxypropyl methyl cellulose incorporating mango peel extract for potential use in wound care system
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Publication Date
Tue Mar 01 2022
Journal Name
Iraqi Journal Of Physics
The Confinement Profile Effect on the Optical Properties in Different Inverse-shaped Single InGaN/GaN Quantum Wells
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In this work, the effects of size, and temperature on the linear and nonlinear optical properties in InGaN/GaN inverse parabolic and triangular quantum wells (IPQW and ITQW) for different concentrations at the well center were theoretically investigated. The indium concentrations at the barriers were fixed to be always xmax = 0.2. The energy levels and their associated wave functions are computed within the effective mass approximation. The expressions of optical properties are obtained analytically by using the compact density-matrix approach. The linear, nonlinear, and total absorption coefficients depending on the In concentrations at the well center are investigated as a function of the incident photon energy for different

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Synthesis, Characterizations, and Recent Applications of the Silica-based Mobil Composition of Mesoporous Material: A Review
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Silica-based mesoporous materials are a class of porous materials with unique characteristics such as ordered pore structure, large surface area, and large pore volume. This review covers the different types of porous material (zeolite and mesoporous) and the physical properties of mesoporous materials that make them valuable in industry. Mesoporous materials can be divided into two groups: silica-based mesoporous materials and non-silica-based mesoporous materials. The most well-known family of silica-based mesoporous materials is the Mesoporous Molecular Sieves family, which attracts attention because of its beneficial properties. The family includes three members that are differentiated based on their pore arrangement. In this review,

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Publication Date
Thu Jun 04 2020
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
User authentication system based specified brain waves
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A security system can be defined as a method of providing a form of protection to any type of data. A sequential process must be performed in most of the security systems in order to achieve good protection. Authentication can be defined as a part of such sequential processes, which is utilized in order to verify the user permission to entree and utilize the system. There are several kinds of methods utilized, including knowledge, and biometric features. The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field. EEG has five major wave patterns, which are Delta, Theta, Alpha, Beta and Gamma. Every wave has five features which are amplitude, wavelength, period, speed and frequency. The linear

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
A Real-Time Fuzzy Load Flow and Contingency Analysis Based on Gaussian Distribution System
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Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

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Publication Date
Tue Jun 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
A new pseudorandom bits generator based on a 2D-chaotic system and diffusion property
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A remarkable correlation between chaotic systems and cryptography has been established with sensitivity to initial states, unpredictability, and complex behaviors. In one development, stages of a chaotic stream cipher are applied to a discrete chaotic dynamic system for the generation of pseudorandom bits. Some of these generators are based on 1D chaotic map and others on 2D ones. In the current study, a pseudorandom bit generator (PRBG) based on a new 2D chaotic logistic map is proposed that runs side-by-side and commences from random independent initial states. The structure of the proposed model consists of the three components of a mouse input device, the proposed 2D chaotic system, and an initial permutation (IP) table. Statist

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Transmitter Zigbee System based on Wireless Sensor Network of IEEE 802.15.4 Standard
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Abstract

 

Zigbee is considered to be one of the wireless sensor networks (WSNs) designed for short-range communications applications. It follows IEEE 802.15.4 specifications that aim to design networks with lowest cost and power consuming in addition to the minimum possible data rate. In this paper, a transmitter Zigbee system is designed based on PHY layer specifications of this standard. The modulation technique applied in this design is the offset quadrature phase shift keying (OQPSK) with half sine pulse-shaping for achieving a minimum possible amount of phase transitions. In addition, the applied spreading technique is direct sequence spread spectrum (DSSS) technique, which has

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