In the digital age, protecting intellectual property and sensitive information against unauthorized access is of paramount importance. While encryption helps keep data private and steganography hides the fact that data are present, using both together makes the security much stronger. This paper introduces a new way to hide encrypted text inside color images by integrating discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD), along with AES-GCM encryption, to guarantee data integrity and authenticity. The proposed method operates in the YCbCr color space, targeting the luminance (Y) channel to preserve perceptual quality. Embedding is performed within the HL subband obtained from DWT decomposition via SVD coefficients extracted from DCT-transformed images in the midfrequency band. A content-aware strategy combining Gaussian blurring, Canny edge detection, and zigzag scanning is employed to increase robustness against image processing attacks. The experimental results demonstrate the effectiveness of the proposed approach, which achieves up to a 10.4% improvement in PSNR, an SSIM score of 0.996, and a 0.10% increase in NCC over those of previous methods, which mostly rely on grayscale images. These results reflect the ability of the system to maintain high visual quality while offering strong resilience and security for embedded data in full-color images.
There are many varied studies that dealt with the dramatic construction, especially books and studies that addressed drama in its construction and the method of writing it, that no textbook or a general cultural content is void of tackling the dramatic text in its construction and how the dramatic action develops in it. Therefore, a question occurs to the mind about the feasibility of dealing with the dramatic construction in this time, where many contemporary studies of dramatology and its relation and the contemporary critical directions are accumulating. This question many have two realistic aspects, yet the novelty and originality that this research shows lie in addressing a refined linguistic text in its style and connotations, such
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Background: The accuracy of fitness of any dental casting is imperative for the success of any prosthodontic treatment. From the time that dental casting was first introduced, efforts have been made to produce more accurate and better fitted castings with minimal marginal discrepancy. The aim of this in vitro study was to evaluate the effects of three different investing and burnout techniques on the vertical marginal discrepancies ofceramometalcopings invested with two types of phosphate- bonded investments. Materials and methods: Sixty wax patterns were fabricated on a standardized prepared brass die representing an upper central incisor by the aid of a custom-made split mold. Three different investing and burnout techniques were applied
... Show MoreThe article describes a study on the role of vitamin C as a protective agent for the teeth, gum, and implants using quantum chemical calculations and polarization tests. The Density Functional Theory (DFT) at 6-311G (d, p) basis set is used to estimate the ability of vitamin C to inhibit the corrosion of the abovementioned parts. The experimental study was performed in a at human body media simulator (Hank’s balanced salt solution) at a temperature of 37°C. The compound was optimized for its ground state, physical properties, and corrosion parameters. Further, HOMO, LUMO, energy gap, dipole moment, and other parameters were used to predict the inhibitor’s efficiency. Gaussian 09, UCA-FUKUI, MGL tools, DSV, and LigPlus software was used
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Background: Ideal root canal obturation depends on many factors; one of them is good sealing of root canal without pores. The aim of this study was to determine the radiographic density of GuttaFlow® 2 with different obturation techniques using spiral computed tomography. Materials and Methods: Forty palatal roots of permanent maxillary first molar were used in this study. Following working length determination, root canal was prepared using rotary PROTAPER universal system. They were randomly divided into four groups of 10 roots each, the groups are Conventional lateral condensation with Apexit Plus sealer, Conventional lateral condensation with GuttaFlow® 2 as a sealer, Soft Core Regular with GuttaFlow® 2 as a sealer and singl
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Most vegetation’s are Land cover (LC) for the globe, and there is an increased attention to plants since they represent an element of balance to natural ecology and maintain the natural balance of rapid changes due to systematic and random human uses, including the subject of the current study (Bassia eriophora ) Which represent an essential part of the United Nations system for land cover classification (LCCS), developed by the World Food Organization (FAO) and the world Organization for environmental program (UNEP), to observe basic environmental elements with modern techniques. Although this plant is distributed all over Iraq, we found that this plant exists primarily in the middle
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Abstract The aim of this research is to show the grade of implementation of ISO 26000 (Social Responsibility Standard), specifically which related in clause sex (consumer issues), this study was achieved in Market Research and Consumer Protection Center (MRCPC) / University of Baghdad. The seven consumer issues of ISO 26000 was analyzed to show the extent of its implementation in MRCPC depending of using a check list as a principle instrument to collect research data and information. Results analysis was achieved by percentages and mean average. The research was leaded some of results and the most importance one was that the grade of implementation of the center in related to consumer issues given in the standard was medium
General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k
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