Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

Objective: To identify barriers to healthcare access, to assess the health literacy levels of the foreign-born Arabic speaking population in Iowa, USA and to measure their prevalence of seeking preventive healthcare services. Methods: A cross-sectional study of native Arabic speaking adults involved a focus group and an anonymous paper-based survey. The focus group and the Andersen Model were used to develop the survey questionnaire. The survey participants were customers at Arabic grocery stores, worshippers at the city mosque and patients at free University Clinic. Chi-square test was used to measure the relationship between the characteristics of survey participants and preventive healthcare services. Thematic analysis was

The world is currently facing a medical crisis. The epidemic has affected millions of people around the world since its appearance. This situation needs an urgent solution. Most countries have used different solutions to stop the spread of the epidemic. The World Health Organization has imposed some rules that people should adhere. The rules are such, wearing masks, quarantining infected people and social distancing. Social distancing is one of the most important solutions that have given good results to confront the emerging virus. Several systems have been developed that use artificial intelligence and deep learning to track social distancing. In this study, a system based on deep learning has been proposed. The system includes monitor

The current research aimed to identify the tasks performed by the internal auditors when developing a business continuity plan to face the COVID-19 crisis. It also aims to identify the recovery and resuming plan to the business environment. The research followed the descriptive survey to find out the views of 34 internal auditors at various functional levels in the Kingdom of Saudi Arabia. Spreadsheets (Excel) were used to analyze the data collected by a questionnaire which composed of 43 statements, covering the tasks that the internal auditors can perform to face the COVID-19 crisis. Results revealed that the tasks performed by the internal auditors when developing a business continuity plan to face the COVID-19 crisis is to en

There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input Multiple-Output (MIMO) channels by combining chaos modulation with a suitable Space Time Block Code (STBC). It is well known that the use of Chaotic Modulation techniques can enhance communication security. However, the performance of systems using Chaos modulation has been observed to be inferior in BER performance as compared to conventional communication

Abstract  

This research aims to study and improve the passivating specifications of rubber resistant to  vibration. In this paper, seven different rubber recipes were prepared based on mixtures of natural rubber(NR)  as an essential part in addition to the synthetic rubber (IIR, BR_cis, SBR, CR)with different rates. Mechanical tests such as tensile strength, hardness, friction, resistance to compression, fatigue and creep testing in addition to the rheological test were performed. Furthermore, scanning electron microscopy (SEM)test was used to examine the structure morphology of rubber. After studying and analyzing the results, we found that, recipe containing (BRcis) of 40% from th

This 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

Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

This paper aims to evaluate the reliability analysis for steel beam which represented by the probability of Failure and reliability index. Monte Carlo Simulation Method (MCSM) and First Order Reliability Method (FORM) will be used to achieve this issue. These methods need two samples for each behavior that want to study; the first sample for resistance (carrying capacity R), and second for load effect (Q) which are parameters for a limit state function. Monte Carlo method has been adopted to generate these samples dependent on the randomness and uncertainties in variables. The variables that consider are beam cross-section dimensions, material property, beam length, yield stress, and applied loads. Matlab software has be