Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

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Conducted the study of the experimental conditions of the interaction of glass the visual Alpmuth containing 15% Mall of zinc with phosphoric acid ????? various degrees of thermal and clip areas prone to interact different way turntable

This research aims to show the sight at the importance of the private banking sector in Iraq and its role in financing of the investment projects , of the ability of Central Bank's decision to increase the minimum limit of capital for private banks to provide support to the economic activity and the development in Iraq. In addition to illustrate the importance of the capital increase, with a, and taking into notice the most important determinants that can stand in front of these banks in the beginning of the decision implementation, which in turn can lead to the most important proceedings that can contribute in the support of banks to implementation the decision.  Also, the research has highlighted the most important ways through wh

Secured multimedia data has grown in importance over the last few decades to safeguard multimedia content from unwanted users. Generally speaking, a number of methods have been employed to hide important visual data from eavesdroppers, one of which is chaotic encryption. This review article will examine chaotic encryption methods currently in use, highlighting their benefits and drawbacks in terms of their applicability for picture security.

In this paper, tunable optical band-pass filters based on Polarization Maintaining Fiber –Mach Zehnder Interferometer presented. Tunability of the band-pass filter implemented by applying different mechanical forces N on the micro-cavities splicing regions (MCSRs). The micro-cavity formed by using three variable-lengths of single-mode polarization-maintaining fiber with (8, 16, 24) cm lengths, splice between two segments of (SMF-28) with (26, 13) cm lengths, using the fusion splicing technique.  Ellipsoidal shape micro-cavities experimentally achieved parallel to the propagation axis having dimensions between (12-24) μm of width and   (4-12) μm of length. A micro-cavity with width and length as high as 24 μm and 12 μ

The role of the ABC system in determining the costs of services in Iraqi banks

Background: In capturing a negative image, the digital impression secures a digital record for the purposeof designing and creating restorations. The introduction of scanning system presents a paradigm shift in the way of the dental impression procedure and encourages the accuracy of obtained restoration especially in the marginal area as a result of producing accurate final impression The digital system offers many advantages over the Conventional method.. The objective of this present in vitro study was to evaluate the marginal fitness of all ceramic crowns fabricated by direct digital scanning of the prepared tooth using two types of intra-oral cameras (Bluecam camera with strip light projection technique and Omnicam camera with video sa

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be