The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

BACKGROUND: Vaccine hesitancy and reluctant had an important obstacle in achieving protection and population immunity against coronavirus disease 19 (COVID-19). It is essential to achieve high COVID-19 vaccination acceptance rates among medical students and health care workers to provide recommendations and counseling vaccine hesitant population. AIM: This study aims to identify level of COVID-19 hesitancy, attitude, knowledge, and factors that affect vaccination decision. MATERIALS AND METHODS: A cross-sectional study was done among medical students in Al-Kindy College of Medicine, University of Baghdad, Baghdad, Iraq. Data collection was done through an online Google Forms questionnaire during 2021 from 810 medical students.

The research aims to how to deal with certain situation to ensure the continuous competitive excellence of business market under the situation of covid-19, especially how to deal with major challenges, identifying the capabilities of tourism industry, investigating the ability of tourism agencies to resist the dynamic change of both internal as well as external environment to ensure their sustainability.

The important here as the paper notice, is how to be efficient and trying to find solutions in order to grow and survive through choosing certain strategies that aligned the critical issues.

Thus to achieve this level, many scenarios planed that could adopt in case of such pande

        This paper aims to identify the contents of the advertisements of the (Take the Vaccine .. to Protect Yourself) campaign that was carried out by the Iraqi Ministry of Health for the period from (11/19/2020) to (4/1/2022), to raise awareness of the anti-Covid 19 virus vaccines, which it published on its official page on Facebook. The researcher used a comprehensive inventory method for the research community, and used the content analysis tool.                                                                             

Arabic text classification is a challenging task because of the complex morphology of the language, the existence of different writing forms and a multitude of dialects, which can result in sparser common text representations. While transformer models such as AraBERT have obtained superior results on many Arabic NLP tasks, their high computational requirements make them difficult to deploy in environments with limited hardware resources. In some cases this can also make the model less practical for researchers working with basic computer systems. This study focuses on a more practical issue: how much accuracy a simple classifier may lose when the amount of required computation is reduced. We use a combined TF-IDF representation based on bo

This study examines the analysis of the contents of the international public relations campaign in confronting the Covid-19 virus, which was taken from the (Your Health is a Trust) campaign for the World Health Organization, Iraq office.The research problem revolves around a main question that is, what are the axes of the campaign (Your Health is a Trust) established by the World Health Organization (Iraq office) in the prevention of Covid 19 virus?From this main question, several sub-questions emerged that this study answered on their Facebook page, and the communication activities of the Covid-19 awareness campaign. In the content analysis form, as this form included a number of main themes and main categoriesthat were adopted in analyzin

To assess the impact of COVID‐19 on oral hygiene (OH) awareness, attitude towards dental treatment, fear of infection and economic impact in the Middle East.

An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter