Abstract : This research is a field study of international cities that hosted various events of which (Sports, Exhibitions, Scientific, Cultural) and other events, these positive impacts on the city driven by such hosts were identified. The research goal was to support hosting events to improve the hostess city and to draw future plans for further developments and to invest event’s hosting to strengthen the city’s value according to a strategic vision that looks for the future the most important conclusions are Entering events hosting is a part of urban development strategies and The most important recommendations are coordination between hosting event activities and its facilities with the infrastructure structure of the host city, its

The world is currently challenging the serious effects of the pandemic of the Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). Data on pediatric COVID are rare and scattered in the literature. In this article, we presented the updated knowledge on the pediatric COVID-19 from different aspects. We hope it will increase the awareness of the pediatricians and health care professionals on this pandemic.

The problem of noise in the Baghdad airport has been examined in this study; and noise measurement and survey studies have been carried out at four high noise level (operation, training and development, quality system, and information and technology) zones located in this region. Noise exposure is a common hazard to workforce in general although at varying degrees depending on the occupation, as many workers are exposed for long periods of time to potentially hazardous noise. A questionnaire was completed by 122 workers during this study in order to determine the physical, physiological, and psycho-social impacts of the noise on workers and to specify what kind of measurements have been taken both by the employers and workers for protection

The problem of noise in the Baghdad airport has been examined in this study; and noise measurement and survey studies have been carried out at four high noise level (operation, training and development, quality system, and information and technology) zones located in this region. Noise exposure is a common hazard to workforce in general although at varying degrees depending on the occupation, as many workers are exposed for long periods of time to potentially hazardous noise. A questionnaire was completed by 122 workers during this study in order to determine the physical, physiological, and psycho-social impacts of the noise on workers and to specify what kind of measurements have been taken both by the employers and workers for protection

In this paper, we introduce a DCT based steganographic method for gray scale images. The embedding approach is designed to reach efficient tradeoff among the three conflicting goals; maximizing the amount of hidden message, minimizing distortion between the cover image and stego-image,and maximizing the robustness of embedding. The main idea of the method is to create a safe embedding area in the middle and high frequency region of the DCT domain using a magnitude modulation technique. The magnitude modulation is applied using uniform quantization with magnitude Adder/Subtractor modules. The conducted test results indicated that the proposed method satisfy high capacity, high preservation of perceptual and statistical properties of the steg

The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model

Antimicrobial resistance is one of the most significant threats to public health worldwide. As opposed to using traditional antibiotics, which are effective against diseases that are multidrug-resistant, it is vital to concentrate on the most innovative antibacterial compounds. These innate bacterial arsenals under the term «bacteriocins» refer to low-molecularweight, heat-stable, membrane-active, proteolytically degradable, and pore-forming cationic peptides. Due to their ability to attack bacteria, viruses, fungi, and biofilm, bacteriocins appear to be the most promising, currently accessible alternative for addressing the antimicrobial resistance (AMR) problem and minimizing the negative effects of antibiotics on the host’s m

Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM