Using watermarking techniques and digital signatures can better solve the problems of digital images transmitted on the Internet like forgery, tampering, altering, etc. In this paper we proposed invisible fragile watermark and MD-5 based algorithm for digital image authenticating and tampers detecting in the Discrete Wavelet Transform DWT domain. The digital image is decomposed using 2-level DWT and the middle and high frequency sub-bands are used for watermark and digital signature embedding. The authentication data are embedded in number of the coefficients of these sub-bands according to the adaptive threshold based on the watermark length and the coefficients of each DWT level. These sub-bands are used because they a

The proliferation of manipulated multimedia content poses a significant threat in an era heavily reliant on social networks as primary information sources. Despite numerous countermeasures targeting specific attack types, the seamless nature of image manipulation challenges the differentiation between authentic and altered visuals. This study aims to detect fake images generated by StyleGAN2-ADA using watermark analysis and image content analysis techniques. The first experiment evaluates the performance of watermarking techniques in the spatial (Least Significant Bit (LSB)) and frequency (Discrete Cosine Transform (DCT)) domains using real-life imagery. Then, watermarked images are used as input to the StyleGAN2-ADA model to genera

Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi

An electrochemical sensor based on an amino-functionalized iron NH2-MIL-101(Fe) metal-organic framework (MOF)/Pd nanoparticles (NPs) composite-modified screen-printed elec­trode (SPE) is prepared for the simultaneous determination of norepinephrine (NEPI) and acetaminophen (ACP). The NH2-MIL-101(Fe) MOF/Pd NPs/SPE electrochemical sensor shows a significant enhancement in the response peak current of NEPI, as compared to bare SPE. This suggests that the unique features of NH2-MIL-101(Fe) MOF/Pd NPs composite-mo­di­fied SPE improve the electro­catalytic oxidation of NEPI. Such a synergistic effect bet­ween NH2-MIL-101(Fe) MOF and Pd NPs results in a significant enhancement in the res­pon­se, where the MOF's high surface area co

Background:Open reduction and internal fixation (ORIF) of using miniplates and screws is the treatment of choice of mandibular fractures. It is important to know both: the region where the bone providesafirm anchorage, andthe topography of the dental apices and inferior alveolar nerve to avoiddamaging them when inserting the screw. The aim of this study is to determine the thickness of buccal cortical plate and that of buccal bone at the parasymphysis and mandibular body, thereby determining the area that provide afirm anchorage and the maximum length of mono-cortical screws that can be safely placed in these regions without injuring the tooth roots or mandibular nerve. Materials and Methods:The sample of the present study was 110 Iraqi sub

The aim of the current study is to create special norms of the second edition of Minnesota multi faces personality inventory, and the fifth edition of the sixteen personality factor questionnaire of catel. To this end, the researcher applied the Minnesota multi faces personality inventory over a sample of (1646) secondary and university students as well as plenty of disorders. She also applied the sixteen personality factor questionnaire of catel on (4700) secondary and university students. SPSS tools were used to process data.  

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

In this study, the kinematic analysis including the forward and inverse kinematic developed for a 5 degree of freedom robotic arm. The forward kinematic is elaborated using Denavit-Hartenberg (DH) convention. Inverse Kinematic is established using Deep Neural Network (DNN) model with five hidden layer each contain 50 neurons fully connected using ReLu activation. A data of inputs and outputs are created and trained. The inputs are the end-effector position and orientation. The outputs are the joint angles of the manipulator. The data is generated by the forward kinematics, where a set of joint angles that limited by their corresponding ranges are inserted to the forward kinematic equations to result the end-effector positions and or