Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

the shear strength parameters of the treated and untreated gypsum soil under the effect of four soaking and drying cycles has studied in this paper, moreover examined the effect of wetting and drying cycles on the collapse potential of the soil and comparing between the behavior of the treated and untreated gypsum soil under the effect of the two conditions. Gypsum soil sample brought from Sawa lake in Al Muthana governorate with the content of gypsum 65.5%, the polyurethane polymer (PP) was used with different percentages 3, 6, and 10% to enhance the mechanical properties of gypsum soil, model was prepared to achieve four soaking and drying cycle to the samples before testing, this model consists of an Aluminum plate base with dimensions 7

This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

The aim of the research is to determine the impact of profit management practices on the quality of profits through the use of flexibility in determining accounting methods and practices profit information is one of the most important information that concerns current users in general and observing users in particular. Some corporations managements manipulate the results of the company's profit or loss (income statement) and financial position statement with multiple reasons, including capital market motivations to raise their share prices in the stock market and attract investors, and on the other hand the motives of funding and borrowing loans, and the use of the flexibility in accounting policies and estimates to change the in

  The purpose of the study is to analyze the extent of the impact of liquidity as an independent variable on profitability as an intermediate variable and the value of banks listed in the Iraq Stock Exchange as a dependent variable, as the research problem is summarized by the fact that most banks focus on profitability as a phased goal without focusing on maximizing its value as a strategic goal by enhancing the wealth of owners and shareholders. On the long term, the research community is represented by the banks listed on the Iraq Stock Exchange, while the research sample was deliberately chosen, which included three private banks such as Baghdad Commercial Bank, the Iraqi Commercial Bank and the Iraqi Investment Bank, an

The aim of this study is to compare and contrast the science process skills (SPS) included in the 10th-12th grade physics textbooks content utilized in Yemeni schools. The study revealed weaknesses and strengths in the textbooks’ content. For instance, a number of science process skills (SPS), such as measuring, predicting and hypothesizing, have been neglected in the 11th grade textbook. For all three textbooks content, the maximum percentage of basic science process skills (BSPS) was devoted to observation. However, the maximum percentage of integrated science process skills (ISPS) was different for each grade: experimenting had the highest percentage for 10th grade, interpreting data for 11th grade, and operational definitions for 12th

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de