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

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

The importance of this research lies in shedding light on the concept of techno-strategy for information management from vital and important topics that showed response for change in all areas of life. As this necessitates the updating and changing of it in order to achieve its strategic goals and enhance its technological advantage. The research problem looked at the role of the information technology system (ITS) in enhancing risk management in general directorates for sports and school activity from the viewpoint of its department heads. The research aimed at the relationship of information techno-strategy in risk management and the ratios of the contribution of information techno-strategy in risk management from the viewpoint of heads o

The research problem is dedicated to investigate reservoirs irrational economic behavior adopted by the ruling elites in developing countries about the investment methodology of human capital and operating policies is based on the terms of reference of economic theory and standards governing the market, which led to a chronic structural imbalance in the workforce structure and lack of consistency with different production structure, in turn, which had a reported effects in the emergence of the phenomenon of unemployment and that they involved a certain privacy, as has become the issues of unemployment and employment in the various countries of the world are issues more important due to the presence of large numbers of the workforce in th

The present study was included the isolation of Keratinophilic fungi from water samples taken from 19 indoor public swimming pools in Baghdad during four season (summer ,fall ,spring ,and winter). Isolation period was September 2011and September 2012 . Samples were collected from different places in swimming pool . Sixteen keratinophilic fungal species, belonging to twenty –one genera were isolated using Surface Dilution Plating (SDP) and Hair Bait Technique (HBT) . Aspergillus genus was the most frequent and occurrence (19.84%), followed by Trichophyton (11.60%) and Fusarium (7.59% ) . The most common fungal infection occurred in summer season (42.16%) , and the most frequent month manifestation of species occurred in August

:Background: Many studies had stated that there are marked variations in the clinical presentation of depressive states between different cultures.Objectives: The main aim of the study is to identify the symptoms profile of patients with major depressive disorder living in Baghdad.Method: Ninety two patients with major depressive disorder consulting Ibn-Rushd psychiatric teaching hospital were studied thoroughly to identify the frequency of symptoms among them. The fifth edition of the Arabic version of the Mini-International Neuropsychiatric Interview (M.I.N.I) was used to identify the Diagnostic and Statistical Manual – fourth edition (DSM-IV) symptoms. A list of other symptoms, which were found to present variably in depression acco