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.
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Modern automation robotics have replaced many human workers in industrial factories around the globe. The robotic arms are used for several manufacturing applications, and their responses required optimal control. In this paper, a robust approach of optimal position control for a DC motor in the robotic arm system is proposed. The general component of the automation system is first introduced. The mathematical model and the corresponding transfer functions of a DC motor in the robotic arm system are presented. The investigations of using DC motor in the robotic arm system without controller lead to poor system performance. Therefore, the analysis and design of a Proportional plus Integration plus Divertive (PID) controller is illustrated.
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The issue of insurance against unlawful risks raises a jurisprudential and judicial debate between two opposing trends: the first considers coverage of these risks invalid due to their impact on public order or morals, while the second—which this research analyses—calls for the possibility of covering these risks in specific circumstances, based on contractual considerations in accordance with the principle that the contract is the law of the contracting parties, and based on the obligation to compensate the harmed third party—the victim—who has no connection to the unlawful act. In this context, our research highlights that contractual considerations can justify coverage of some unlawful risks, provided that the goal is to achieve
... Show MoreThis study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
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This study is targeting the new developed materials and techniques and how they were affected by the scientific and technological developments that contributed to revelated new and varied developed materials and techniques. And from the artist’s formulation by using the materials and techniques and through its embodiment and sensor the values, artistic and aesthetic standards by breaking from the familiar in aesthetic contemporary way.
The studies on questioning what’s the role of The New Developed Materials and Techniques in exposing the aesthetic of the art work?
This study is to show the aesthetic of the art work through the new developed materials and techniques. Which was based on descriptive analyzing method and hig
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