This research aims to identify and measure the role of TQM in the process of developing  the financial  performance of  Diyala State Company and show the reality and obstacles, after applying the company's management to the requirements of ISO 9001: 2008 and compare it with its performance before applying this standard, The researcher measured the financial performance by conducting financial analysis of the financial statements and conducting a number of interviews at the company's headquarters, Diyala State Company (one of the Iraqi Ministry of Industry and Minerals formations) was sele

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

The aim of this study was to know the inhibition activity of squeezed grape waste extract on Bacillus stearpthermophilus by using three different tempretures degree 40, 60 and 80c, in order to reduce the time exposure of food for preservation. This study include two branchs: First: isolation and identification of Bacillus stearothermophilus from soil, 5 sample were collected from the soil of the college agriculture/Baghdad university. Samples were cultured on nutrient agar, microscopic and culturing tests were conducted and many biochemical tests were done. The isolates were cultivated at 55 c and 65 c for differentiate it from Bacillus coagulans which is can^'t grow at 65 c^o. The c

This study aimed at examining the role played by the media outlets during the coverage
of the presidential election campaigns 2020 of the United States of America.
The analytical study used through a partial inventory of the research community
for almost three months from the announcement of the candidates’ names by
the major parties on August 13 to November 6، which is the official election day in
the U.S. National Public Radio Station (NPR) to achieve the objectives of the study.
The study reached a number of conclusions related to the contents، methods and
sources of media coverage of the election campaigns of the 2020 U.S. at the mentioned
station، where the researcher proposed a number of recommendations

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

This article aim to estimate the Return Stock Rate of the private banking sector, with two banks, by adopting a Partial Linear Model based on the Arbitrage Pricing Model (APT) theory, using Wavelet and Kernel Smoothers. The results have proved that the wavelet method is the best. Also, the results of the market portfolio impact and inflation rate have proved an adversely effectiveness on the rate of return, and direct impact of the money supply.

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation