Abstract

Objectives: The main objective of this study is to find the influence level of nursing incivility on psychological well-being among nurses in southeastern Iraq.

Methods: In this descriptive correlational study, a convenience sample of 250 nurses working in three government hospitals in Missan province in the south of Iraq were surveyed using the nursing incivility scale (NIS) and Ryff's psychological well-being scale (PWB) from November 2021, to July 2022. A multivariate multiple regression analysis was done to analyze the multivariate effect of workplace incivility on the psychological well-being of nurses.

Results: The study results show a

Criticism is inherently impolite and a face-threatening act generally leading to conflicts among interlocutors. It is equally challenging for both native and non-native speakers, and needs pre-planning before performing it. The current research examines the production of non-institutional criticism by Iraqi EFL university learners and American native speakers. More specifically, it explores to what extent Iraqi EFL learners and American native speakers vary in (i) performing criticism, (ii) mitigating criticism, and (iii) their pragmatic choices according to the contextual variables of power and distance. To collect data, a discourse-completion task was used to elicit written data from 20 Iraqi EFL learners and 20 American native speaker

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

Boltzmann mach ine neural network bas been used to recognize the Arabic speech.  Fast Fourier transl(>lmation algorithm has been used t() extract speciral 'features from an a caustic signal .

The  spectral  feature size is reduced by series of operations in

order to make it salable as input for a neural network which is used as a recogni zer by Boltzmann Machine Neural  network which has been used as a recognizer for phonemes . A training set consist of a number of Arabic phoneme repesentations, is used to train lhe neuntl network.

The neural network recognized Arabic. After Boltzmann Machine Neura l    network   training  the  system   with 

Cryptography is a method used to mask text based on any encryption method, and the authorized user only can decrypt and read this message. An intruder tried to attack in many manners to access the communication channel, like impersonating, non-repudiation, denial of services, modification of data, threatening confidentiality and breaking availability of services. The high electronic communications between people need to ensure that transactions remain confidential. Cryptography methods give the best solution to this problem. This paper proposed a new cryptography method based on Arabic words; this method is done based on two steps. Where the first step is binary encoding generation used t

Personification in Arab poetry is not confined to the abstract items in nature: it trespasses them to include more than that. We found after reviewing the anthologies of the poets tens of the personified items are full of human attributes - via personification- such as speaking, moving, feeling human feelings.. Personification formed a remarkable feature in the relationship between poets and war, which was clear in the Pre-Islamic poetry, because it occupied the minds of the ancient Arab mindset. The poets have envisioned war as ugly as a force that brings destruction and devastation. The paper aims at stating the position in which poets personified war with female tributes. Thus, it is impregnated, conceived, and produced birth like a w

In this work , a hybrid scheme tor Arabic speech for the recognition

of  the speaker  verification  is presented  . The scheme is hybrid as utilizes the traditional digi tal signal processi ng and neural network . Kohonen neural  network has been used as a recognizer  tor speaker verification after extract spectral  features from an acoustic signal  by Fast Fourier Transformation Algorithm(FFT) .

The system was im plemented using a PENTIUM  processor , I000

MHZ compatible and MS-dos 6.2 .