Since the Internet has been more widely used and more people have access to multimedia content, copyright hacking, and piracy have risen. By the use of watermarking techniques, security, asset protection, and authentication have all been made possible. In this paper, a comparison between fragile and robust watermarking techniques has been presented to benefit them in recent studies to increase the level of security of critical media. A new technique has been suggested when adding an embedded value (129) to each pixel of the cover image and representing it as a key to thwart the attacker, increase security, rise imperceptibility, and make the system faster in detecting the tamper from unauthorized users. Using the two watermarking ty

This paper presents the implementation of a complex fractional order proportional integral derivative (CPID) and a real fractional order PID (RPID) controllers. The analysis and design of both controllers were carried out in a previous work done by the author, where the design specifications were classified into easy (case 1) and hard (case 2) design specifications. The main contribution of this paper is combining CRONE approximation and linear phase CRONE approximation to implement the CPID controller. The designed controllers-RPID and CPID-are implemented to control flowing water with low pressure circuit, which is a first order plus dead time system. Simulation results demonstrate that while the implemented RPID controller fails to stabi

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This research introduce a study with application on Principal Component Regression obtained from some of the explainatory variables to limitate Multicollinearity problem among these variables and gain staibilty in their estimations more than those which yield from Ordinary Least Squares. But the cost that we pay in the other hand losing a little power of the estimation of the predictive regression function in explaining the essential variations. A suggested numerical formula has been proposed and applied by the researchers as optimal solution, and vererifing the its efficiency by a program written by the researchers themselves for this porpuse through some creterions: Cumulative Percentage Variance, Coefficient of Determination, Variance

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Tight reservoirs have attracted the interest of the oil industry in recent years according to its significant impact on the global oil product. Several challenges are present when producing from these reservoirs due to its low to extra low permeability and very narrow pore throat radius. Development strategy selection for these reservoirs such as horizontal well placement, hydraulic fracture design, well completion, and smart production program, wellbore stability all need accurate characterizations of geomechanical parameters for these reservoirs. Geomechanical properties, including uniaxial compressive strength (UCS), static Young’s modulus (Es), and Poisson’s ratio (υs), were measured experimentally using both static and dynamic met