The research problem lies in the ambiguity of the usage of propaganda contents by two main media outlets (the Russian RT and American Alhurra) in their news coverage of the Syrian crisis through their websites and the methods used by them to convince users taking into account the mutual propaganda conflict between the United States and Russia in the war against Syria. The objectives of the research can be represented by the following: investigating the contents of American and Russian electronic propaganda towards Syrian crisis.
• Identifying the contents that received most of the coverage in the Syrian crisis by the two news outlets.
• Identifying the terms and phrases that have been most used by the websites of RT and Alhurr
This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi
... Show MoreThis research is addressing the effect of different ferrocene concentration (0.00, 2.15x10-3, 4.30x10-3, 8.60x10-3, and 12.9x10-3) on the bulk free radical polymerization of methyl methacrylate monomer in benzene using benzoyl peroxide as initiator. The polymerization was conducted at 60º C under free oxygen atmosphere. The resulting polymers were characterized by FTIR. The results were compared with the presence and absence of ferrocene at 10% conversion. The %conversion was 3.04% with no ferrocene present in the polymerization medium and its increase to 9.06 with a first lowest ferrocene concentration added, i.e. 2.15 x10-3mol/l. This was positively reflected on the poly(methyl methacrylate) molecular weight measured by viscosity techniq
... Show MoreThis research aims to clarify the conceptual framework of social entrepreneurship shows the importance of the development of social entrepreneurship according to the contextual aspects and the social value achieved from these works. It also identifies the degree of level of a sample of women entrepreneurs in Iraq for the extent of the relationship between social entrepreneurship and women's empowerment. It also explains the impact of entrepreneurial work in empowering women and the extent to which there are individual differences between the average scores of the sample members’ estimation of the level of social entrepreneurship according to social status, age group, educational qualification, and specialization according to the s
... Show MoreBackground
Respiratory tract aspergillosis is a pulmonary disease cause by aspergillus species which are opportunistic fungi that mainly infect immuno-compromised patients .
Objective(s)
The present study aimed to detect the frequency of pulmonary aspergillosis among clinically suspected and under follow up tuberculosis patients conducted at Tropical Diseases Teaching Hospital, Omdurman, Khartoum State , Sudan during the period from December 2019 to November 2020.
Materials and Methods
One hundred and fifty sputum samples were collected from suspected cases of pulmonary tuberculosis and under follow up tuberculosis patients. All specimens were examined using 20% KOH and cultured on two
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