Physicians are infrequently selected to serve in the yearlong role of Jefferson Science Fellow (JSF) as senior science advisor for the US Department of State or the United States Agency for International Development. The authors discuss the role of a JSF in promoting “science diplomacy” from the perspective of one alumnus, who sites examples of ongoing, long-term collaborative projects including one focusing on medical education reform in Iraq that would not have been possible without the JSF program. More than 3 decades of political and social unrest, terrorism, the internal displacement of millions of Iraqi citizens, the arrival of Syrian refugees, international sanctions, and the effect of fluctuating oil prices that fund education i

   The oil sector in Iraq suffered from several difficulties led to the decline and reduction of oil production and the deterioration of refineries and transport pipeline status in addition to the weakness of the technology side and the prevalence of financial and administrative corruption besides the high costs of rehabilitation of the oil sector and also administrative and institutional problems still ongoing. 

 In spite of Iraq's possession of vast oil wealth allows him to play an important role in the international energy market، he is still under the level. The production of oil doesn'<

Abstract:

    The achievement of agricultural development provide food security and to form a basis for economic growth and comprehensive social, requires a number of actions to overcome the obstacles and problems facing the development of this economic sector, to make it able to achieve food security and operation of the workforce, and reduce dependence on the outside in the provision of food peripherals, and so it is only available through the highest degree of efficiency and economic mobilization of resources, so most of the developed and developing countries alike seek to achieve sustainable agricultural development tobacco meet the food requirements and good jobs for c

Iraq is considered one of the countries most susceptible to the negative impacts of climate change. According to international reports, it is classified as among the top five most affected by climate change in the world, leading to economic resource shortages and an increase in water scarcity, which exposes societal stability in Iraq to a threat.  This may result in social disintegration and civil conflicts, so climate changes are considered one of the most dangerous crises affecting societal stability in Iraq during this stage.  In this context, the research attempts to trace the causes of climate change and their effects on societal stability in Iraq and suggest some necessary measures to confront them in the future.  The resea

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

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

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

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