This study examines the news values employed by regional news agencies in the selection and dissemination of news concerning Iraqi affairs. Content analysis was conducted on a purposive sample of 596 news articles sourced from official websites of news agencies, including Iraqi, Turkish, and Iranian agencies. The research aims to identify the underlying criteria used by these agencies in determining news suitability for publication.

The present paper addresses one of the most challenging topics in translation; namely legal translation in the framework of two different approaches; the classical (formal) and the more recent (functional). The latter approach is the outcome of the process of simplifying legal language known technically as Plain Language Movement. The advent of this movement dates back to the 1950s, in response to the widely-held complain about the awkwardness of the legal register. Within this framework, the salient features of legal language, at the various linguistic and textual levels, underwent reconsideration in favor of more publicly digested expressions. The paper then subjects two translations of a lease contract to analysis in the ligh

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

La condicionalidad en árabe, supongo como en otras lenguas, constituye una noción amplia que puede expresarse mediante diferentes construcciones sintácticas. La mayor parte de los especialistas coinciden en señalar que las estructuras condicionales son, probablemente, la clase más compleja de expresión compuesta en árabe. Se utilizan para expresar una condición de la que depende la realización de lo expuesto en la oración principal. Las estructuras condicionales son una de las principales vías lingüísticas de las que dispone el individuo para expresar su capacidad de imaginar situaciones diferentes a las reales; de crear mundos posibles; de soñar con situaciones pasadas que podrían haber sido diferentes; de ocultar lo fact

Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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

Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi