In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The performance of the proposed algorithm is evaluated using detection
techniques such as Peak Signal- to- Noise Ratio (PSNR) to measure the distortion,
Similarity Correlation between the cover-image and watermarked image, and Bit
Error Rate (BER) is used to measure the robustness. The sensitivity against attacks on
the watermarked image is investigated. The types of attacks applied are: Laplacian
sharpening, Median filtering, Salt & Peppers Noise and Rotating attack. The results
show that the proposed algorithm can resist Laplacain sharpening with any sharpening
parameter k, besides laplacian good result according to some other types of attacks is
achieved.
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Metal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limit
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Lasmiditan (LAS) is a recently developed antimigraine drug and was approved in October, 2019 for the treatment of acute migraines; however, it suffers from low oral bioavailability, which is around 40%.
This study aimed to improve the LAS bioavailability via formulation as nanoemulsionbased in situ gel (NEIG) given intranasally and then compare the traditional aqueous-LASsuspension (AQS) with the two successful intranasal prepared formulations (NEIG 2 and NEIG 5) in order to determine its relative bioavailability (F-relative) via using rabbits.
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Background: The study's objective was to estimate the effects of radiation on testosterone-related hormones and blood components in prostate cancer patients. N Materials and Method: This study aims to investigate the effects of radiation on 20 male prostate cancer patients at the Middle Euphrates Oncology Centre. Blood samples were collected before and after radiation treatment, with a total dose of 60- 70 Gy, The blood parameters were analyzed. The hospital laboratory conducted the blood analysis using an analyzer (Diagon D-cell5D) to test blood components before and after radiation. Hormonal examinations included testosterone levels, using the VIDASR 30 for Multiparametric immunoassay system Results: The study assessed the socio-demogra
... Show MoreFace recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
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Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers. In this research, we pr
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