Many of researchers have written about social responsibility and business strategy and competitive advantage, and they have given particular attention to the relationship between economic and social responsibility , but what is missing in this aspect is how the economic units that use their core competencies to advance social responsibility initiatives so that they can achieve a significant competitive advantage and create value for it ?

The current research aims to verify the view that "the economic and social objectives in the long term is not contradictory in nature but complementary objectives essential", as well as make sure that the s

The objective of the research is to determine the nature of the strategic direction of the institution and its impact on enhancing the indicators of institutional performance. The strategic direction is the main purpose for which it was found. Therefore, it is the main engine for all activities and tasks that the institution can carry out to achieve its objectives within the environment in which it operates. The promotion of corporate performance indicators is one of the major challenges that senior management must address in order to help the organization invest its human resources in the best possible way.

The research problem was determined by means of the intentional sample, consisting of (33) members

In this paper, Nordhaus-Gaddum type relations on open support independence number of some derived graphs of path related graphs under addition and multiplication are studied.

This study aimed at identifying how children express the emerging coronavirus in general and according to their age groups (4-13 years) by analyzing 91 of their drawings published online, using the descriptive content analytical approach. The results showed that children's artistic expression of the virus came according to the concepts and ideas they carried about the virus for the age groups of (4-7 years) and (7-9 years), while it came according to visual perception for age groups (9-11 years), and from (11-13) years. Also, most children were aware about the presence of the virus and its widespread around the world, but (99%) of them do not realize the seriousness of the virus. It was confirmed that between (25-34%) of children were su

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

The permeability estimates for the uncored wells and a porosity function adopting a modified flow zone index-permeability crossplot are given in this work. The issues with implementing that approach were mostly crossplots, due to the influence of geological heterogeneity, did not show a clear connection (scatter data). Carbonate reservoir flow units may now be identified and characterized using a new approach, which has been formally confirmed. Due to the comparable distribution and flow of clastic and carbonate rock fluids, this zoning method is most effective for reservoirs with significant primary and secondary porosity. The equations and correlations here are more generalizable since they connect these variables by combining cor

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Research Summary


The research revolves around the collection of pending hadiths on Abdullah bin Amr bin Al-Aas, may God be pleased with them, and it is required in these hadiths that they be among those in which there is no room for diligence, such as telling about unseen matters, signs of the Hour, or a statement of virtue and reward for obedience, or punishment for disobedience.

The research consists of an introduction, two topics, and a conclusion of the first topic in the translation of Abdullah bin Amr bin Al-Aas, and the second topic, the pending hadiths of Abdullah bin Amr bin Al-Aas, may God be pleased with them, in which there is no room for diligence in collecting and studying

At the end of this rese

A Destructive Parenthood : The Problematic Motherhood in Selected Poems by Salvia Plath