The purpose of this research is to improve the organizational performance of the Oil Projects Company by adopting an approach to strategic change، and finding appropriate solutions to the problems facing the company. The researcher adopted in designing his research by conducting a survey of previous literature that dealt with approaches to strategic change، as the results of the survey showed that most researchers agree on the approach of renewal and modernization، Which formed a starting point for the researcher to identify the extent of the company's management interest in renewal and modernization to improve its level of performance، and the quality of the procedures followed on the ground that is related to

Background: Cardiopulmonary resuscitation (CPR) is a technique or procedure that combined chest compression and rescue breathing to maintain enough circulation that prevents brain damage until other essential steps are taken to control the main cause of cardiac and respiratory arrest. The health care personnel should be qualified in the performing of cardiopulmonary resuscitation (CPR) to improve the survival rate of the victims. Therefore; it is necessary to use new methods for learning [1]. Objectives: the study aims to compare the effectiveness of self-instructional teaching strategy and traditional teaching approach on student’s knowledge toward cardiopulmonary resuscitation. Methods: A randomized comparative trial (RCT) design was ca

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

The objectives of the study were to identify the incidence rate and characteristics of adverse drug events (ADEs) in nursing homes (NHs) using the ADE trigger tool and to evaluate the relationships between resident and facility work system factors and incidence of ADEs using the System Engineering Initiative for Patient Safety (SEIPS) model. The study used 2 observational quantitative methods, retrospective resident chart extraction, and surveys. The participating staff included Directors of nursing, registered nurses, certified nurse assistants (CNAs). Data were collected from fall 2016 to spring 2017 from 11 NHs in 9 cities in Iowa. Binary logistic regression with generalized estimated equations was used to measure the association

Pedagogical stylistics refers to the application of the tools of stylistics in the teaching of the English language as a foreign or a second language.  Teaching and learning poetry is challenging. Thus, pedagogical corpus stylistics (Henceforth, PCS) approach has been introduced to Iraqi undergraduate foreign language learners (EFL) to guide them to analyze poetic language.  The study aims to make students interact with authentic examples of poetic language and answer questions about it. The main objective of the study is to examine whether PCS tools enable the learners to provide linguistic evidence from the poetic texts they are exposed to. This in turn ensures objective poetic analyses. Moreover, it aims to enable EFL Iraqi stu

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

In this study, the optimum conditions for COD removal from petroleum refinery wastewater by using a combined electrocoagulation- electro-oxidation system were attained by Taguchi method. An orthogonal array experimental design (L18) which is of four controllable parameters including NaCl concentration, C.D. (current density), PH, and time (time of electrolysis) was employed. Chemical oxygen demand (COD) removal percentage was considered as the quality characteristics to be enhanced. Also, the value of turbidity and TDS (total dissolved solid) were estimated. The optimum levels of the studied parameters were determined precisely by implementing S/N analysis and analysis of variance (ANOVA). The optimum conditions were found to be NaCl = 2.5