This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

         Language always conveys ideologies that represent an essential aspect of the world we live in. The beliefs and opinions of an individual or community can be organized, interacted with, and negotiated via the use of language. Recent researches have paid attention to bullying as a social issue. They have focused on the psychological aspect of bullying rather than the linguistic one. To bridge this gap, the current study is intended to investigate the ideology of bullying from a critical stylistic perspective. The researchers adopt Jeffries' (2010) critical stylistics model to analyze the data which is five extracts taken from Hunt’s Fish in a Tree (2015). The analysis demonstrates

Characterized Iraq, being one of the oldest countries where oil was discovered in the Middle East since 1927, and possess a vast oil reserves. In addition, the production and marketing of Iraqi oil continued since 1934 and until the present time. Over the past eight decades, the range of economic benefit of the financial Iraq’s oil resources varied according to the applicable forms of investments in the oil sector in Iraq.

This research included a study

Asbestos is a hazard pollutant to human health, exposure to asbestos cause serious health effects and wide range of asbestos-related diseases such as asbestosis, lung cancer and malignant mesothelioma and it has been classified as carcinogen by the World Health Organization WHO which cause a carcinogenic effects. Fibers of asbestos are mainly released from friction product in brakes and clutch linings and from reinforce agent in the asbestos cement industry. The aim of this was to evaluate the levels of asbestos fibers in surroundings air of some dense traffic points in Baghdad, through winter 2020. Materials and Methods: Samples of airs was carried out by directing air flow to a mixed cellulose ester membrane filter mounted on an open face

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Y Adnan, H Atiyah, IH Neamah…, International Development Planning Review, 2024

In this research, beam expander, BEX, is explained and designed for illuminating the
remote flying target. The BEX is optically designed to be suited for Nd:YAG laser of given
specifications. The BEX is modified to be zoom one to meet the conditions of preventing the
receiving unit; i.e the photodetector, from getting saturated at near and far laser tracking.
Decollimation could be achieved by automatic motor, which controls zoom lens of the BEX
according to the required expansion ratio of beam expander

In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho