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A Novel Technique for Secure Data Cryptosystem Based on Chaotic Key Image Generation
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The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given control parameters, which is then processed by converting the fractional parts of them through a function into a set of non-repeating numbers that leads to a vast number of unpredicted probabilities (the factorial of rows times columns). Double layers of rows and columns permutation are made to the values of numbers for a specified number of stages. Then, XOR is performed between the key matrix and the original image, which represent an active resolve for data encryption for any type of files (text, image, audio, video, … etc). The results proved that the proposed encryption technique is very promising when tested on more than 500 image samples according to security measurements where the histograms of cipher images are very flatten compared with that for original images, while the averages of Mean Square Error is very high (10115.4) and Peak Signal to Noise Ratio is very low (8.17), besides Correlation near zero and Entropy close to 8 (7.9975).

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Publication Date
Fri Dec 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Performance Analysis for Hybrid Massive MIMO FSO/RF Links Based on Efficient Channel Codes
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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm
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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
WOAIP: Wireless Optimization Algorithm for Indoor Placement Based on Binary Particle Swarm Optimization (BPSO)
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Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received s

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Materials Research And Technology
Immobilization of l-asparaginase on gold nanoparticles for novel drug delivery approach as anti-cancer agent against human breast carcinoma cells
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Publication Date
Thu Feb 13 2020
Journal Name
International Journal Of Environmental Research
Synthesis of a Novel Composite Sorbent Coated with Siderite Nanoparticles and its Application for Remediation of Water Contaminated with Congo Red Dye
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Abstract

Re-use of the byproduct wastes resulting from different municipal and industrial activities in the reclamation of contaminated water is real application for green projects and sustainability concepts. In this direction, the synthesis of composite sorbent from the mixing of waterworks and sewage sludge coated with new nanoparticles named “siderite” (WSSS) is the novelty of this study. These particles can be precipitated from the iron(II) nitrate using waterworks sludge as alkaline agent and source of carbonate. Characterization tests using X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) mapping revealed that the coating process was c

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Publication Date
Thu Jan 25 2024
Journal Name
Biomedical Materials
Enhancing the therapeutic potential of curcumin: a novel nanoformulation for targeted anticancer therapy to colorectal cancer with reduced miR20a and miR21 expression
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Abstract<p>Curcumin (Cur) possesses remarkable pharmacological properties, including cardioprotective, neuroprotective, antimicrobial, and anticancer activities. However, the utilization of Cur in pharmaceuticals faces constraints owing to its inadequate water solubility and limited bioavailability. To overcome these hurdles, there has been notable focus on exploring innovative formulations, with nanobiotechnology emerging as a promising avenue to enhance the therapeutic effectiveness of these complex compounds. We report a novel safe, effective method for improving the incorporation of anticancer curcumin to induce apoptosis by reducing the expression levels of miR20a and miR21. The established</p> ... Show More
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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Sat Jan 25 2020
Journal Name
Indian Journal Of Forensic Medicine &amp; Toxicology
Color Stability of Different Aesthetic Resin Composite Materials: A Digital Image Analysis
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Publication Date
Wed Jan 01 2020
Journal Name
Indian Journal Of Forensic Medicine And Toxicology
Color stability of different aesthetic resin composite materials: A digital image analysis
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