Abstract This study explores the extent to which public relations (PR) departments within Traqj governmental institutions are integrating artificial intelligence (AI) applications into their communication activities. The research adresses the growing importanc of AI in enhancing administrative efficieney, communication transparency, and stakeholder engagement. Adopting a descriptive research design, the study relied on an electtonic questionnaire distributed to PR profesionals across various ministries and government bodies, collecting 100 valid responses. The indings reveal that while younger PR practitioners are actively embracing AI, older employees show limited engagement. Most participants acquired AI-related skills through self- learn

Population density represents an important indicator for determining the growth of the size of urban areas. Population density has a direct impact on the quality of life, and its excessive rise may lead to the deterioration of basic service facilities. The problem of the research is that the increase in the total population densities of the residential neighborhood may reflect negatively on the nature of the services provided to the residents in these shops, and thus the failure to achieve sustainability in the residential locality. The research assumes that the increase in population densities negatively affects the achievement of sustainability in the residential neighborhood.

  In Iraq,  government contributions to the public companies have become a very important aspect which contributes to the survival and sustainability of these institutions as it consider  one of the main sources of funding, if not it consider the basis of funding.

  According to  the vital roles assigned to these institutions to follow up, which usually  include important activities in the national economy, the research focused on studying the field reality of the method used in evaluating the stock of total production and purchases of goods for the purpose of selling the strategic commodities of the General Company for Grain Trade.  As a result, the aim of this study came to came to highlight&n

Background: Cardiovascular disease (CVD) is the number one cause of death worldwide. Objective: To determine of coronary care unit nurses' knowledge regarding patient rehabilitation after myocardial infarction. Methodology: A cross- sectional study was designed in the Cardiac Care Unit of Al-Diwaniyah Teaching Hospital and the Specialized Center for Cardiac Surgery and Catheterization for the period from (November 7, 2022) to (May 12, 2023). A non-probability (purposive) sample consisting of (75 nurses) working in the above-mentioned study site. To determination of coronary care unit Nurses' knowledge regarding patient rehabilitation after myocardial infarction, the researcher used a tool that consists of two parts: The first part:

Chilled ceilings systems offer potential for overall capital savings. The main aim of the present research is to investigate the thermal performance of the indirect contact closed circuit cooling tower, ICCCCT used with chilled ceiling, to gain a deeper knowledge in this important field of engineering which has been traditionally used in various industrial & HVAC systems. To achieve this study, experimental work were implemented for the ICCCCT use with chilled ceiling. In this study the thermal performances of closed wet cooling tower use with chilled ceiling is experimentally and theoretically investigated. Different experimental tests were conducted by varying the controlling parameters to investigate their effects

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an