The research aims to reveal the impact of media policy in Iraqi media outlets on the level of objectivity in these outlets. A study from the communicators’ point of view where the researcher used a survey method on the communicators in media outlets to reveal the extent of media policies knowledge as well as the pressures exerted by this policy on communicators in media outlets. It also reveals the extent of their commitment to objectivity, neutrality in dealing with information and the way used to transfer it.
The research sample included (179) respondents from communicators in a range of Media outlets such as (Press, Radio, and Television), The researcher was careful with the diversity of the sample, and

Given that the Crimean and Congo hemorrhagic fever is one of the deadly viral diseases that occur seasonally due to the activity of the carrier “tick,” studying and developing a mathematical model simulating this illness are crucial. Due to the delay in the disease’s incubation time in the sick individual, the paper involved the development of a mathematical model modeling the transmission of the disease from the carrier to humans and its spread among them. The major objective is to comprehend the dynamics of illness transmission so that it may be controlled, as well as how time delay affects this. The discussion of every one of the solution’s qualitative attributes is included. According to the established basic reproductio

This paper presents an analytical study for the magnetohydrodynamic (MHD) flow of a generalized Burgers’ fluid in an annular pipe. Closed from solutions for velocity is obtained by using finite Hankel transform and discrete Laplace transform of the sequential fractional derivatives. Finally, the figures are plotted to show the effects of different parameters on the velocity profile.

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

thin films of se:2.5% as were deposited on a glass substates by thermal coevaporation techniqi=ue under high vacuum at different thikness

Sports commentary improves the audience’s engagement while delivering a real-time description and analysis of sporting events. However, sometimes the fast-paced nature leads to occasional linguistic errors which includes grammatical inconsistencies, lexical inaccuracies, and discourse level ambiguities. This study will categorize these errors and evaluate various NLP models for detection and processing. The data set of 100 h of transcribed football basketball and tennis commentary was preprocessed and annotated. Several NLP rule-based models such as languageTool and Hunspell, machine learning models such as SpaCy and Stanford NLP, and deep learning models such as AraBERT and GPT-4 Fine-Tuned we’re all assessed based on their precision,