Background: In healthcare settings, specialists from different fields may follow the most well-known, reliable, and easy-to-understand medical guidelines. This study aimed to determine Iraqi physicians' adherence to treatment guidelines, to specify which treatment guidelines are utilized for each disease and identify their barriers to follow the guidelines.

Methods: This was qualitative study including face-to-face and virtual semi-structured interviews with specialist physicians from different disciplines. The interviews were conducted between December 2021 and May 2022 in Kirkuk province, Iraq. The qualitative data generated through i

The research focuses on how to reach a mechanism that assists experts, engineers, and others in the architectural & engineering project to verify the co-existence of values and sustainability constituents in it. Research problem shows a clear lack, locally, in the interest to establish a value system and a list that cares about comprehending building components whether considering sustainable building criteria. Hypothesis shows that in order to head towards the applicable sustainable approach of buildings, then a local assessment system should be established to evaluate buildings during its life cycle, and from which buildings would be categorized as sustainable or not. Research aims at establishing main and general

Despite the vast areas occupied by deserts in the world, it is still far from the civilized development and development of the other regions, so they became semi-neglected areas that extend to the hand of urbanization only in specific places and for special purposes, due to the harsh natural conditions surrounding it and to the accuracy The ecological balance in it became the greatest enemy of human beings in the desert areas is the same person who paved the way for increased intervention in the exploitation of natural resources and increase the demand for them to drain seriously affect the impact and still on the environmental and climatic conditions and thus living for the inhabitants of these Areas. The main potential for deve

The educational service industry is one of the most negatively affected industries by the spread of the COVID-19 pandemic. Government agencies have taken many measures to slow its spread, and then restrict movement and gatherings and stop recreational activities. Furthermore, the repercussions of the curfew had a significant impact due to the interruption in actual attendance for students and employees, and the severity of the Covid-19 crisis and its (economic, social, security, humanitarian and behavioral) effects on all societies and work sectors is no secret to anyone. Iraq, like other countries, was also affected by the negative impact of Covid-19 pandemic in all fields of institutional work, especially public fields, and specifically t

Future generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m