In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end

Abstract:

     The research aims to shed light on the Corona pandemic and its repercussions on the global economy in general, and on the activities of Iraqi economic units in particular. It also aims to show the impact of the auditor’s reporting on the effects of the Corona pandemic on economic units and its reflection on the quality of his reporting. To achieve the objectives of the research, the researcher prepared a questionnaire according to the five-point Likert scale and took into account in its preparation compatibility with the characteristics of the study community, and that the target community for this questionnaire are the economic units listed in the Iraq Stock Exchange that have complet

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

The first known use of the term conspiracy theory dated back to the nineteenth century. It is defined as a theory that explains an event or set of circumstances as the result of a secret plot by usually powerful conspirators. It is commonly used, but by no means limited to, extreme political groups. Since the emergence of COVID-19 as a global pandemic in December 2019, the conspiracy theory was present at all stages of the pandemic.

The first known use of the term conspiracy theory dated back to the nineteenth century. It is defined as a theory that explains an event or set of circumstances as the result of a secret plot by usually powerful conspirators. It is commonly used, but by no means limited to, extreme political groups. Since the emergence of COVID-19 as a global pandemic in December 2019, the conspiracy theory was present at all stages of the pandemic.