In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

The study aims (objective ) to clarify the concept of comprehensive income and its usefulness for users, as the study aims to clarify the relationship between the concept of comprehensive income and market value of the company where the measurement of comprehensive income after accounting for net income and by measuring the unrealized gains or losses in the value of securities available for sale, and measurement the unrealized gains or losses on futures contracts, which are financial derivatives, and measurement the unrealized gains or losses from the settlement of foreign currency translation (conversions), and measurement the impact on the market value of companies and of the present study to rise or fall of return on the stock

   The research aims to measure the accounting conservatism practice of listed companies in the Iraq stock exchange using Basu model to measure the degree of accounting conservatism in a sample of companies of (21) companies for the period from 2007 to 2011, the researcher found that most of the listed companies in the market exercised accounting conservatism when measurement and disclosure of the result of the activity and financial position and there is a variation in the degree of accounting conservatism between economic sectors , which included banking , investment , insurance , industry , agriculture , tourism and hotels.

   Because the practice of accounting conservatism properly

This research study examines the impact of information technology on firm profitability and stock returns. Using a comprehensive dataset of firms across various industries, this research employs rigorous statistical analysis techniques to investigate the relationship between IT investments, firm profitability metrics, and stock returns. The study focuses at how IT investments affect financial performance measures including return on assets (ROA) and return on equity (ROE), with P-values of 0.34 and 0.12, respectively. Furthermore, the study investigates the influence of IT on stock returns, taking into account market capitalization, industry trends, and macroeconomic variables. This study's conclusions center on the beneficial assoc

The study seeks to determine the levels of credit structure (independent variable) depending on its components (loans, credit disseminate, other facilities) To get the eight patterns of the structure of bank credit for the purpose of assessing the relationship between changes in levels of each style of structure credit (increase or decrease) and reflected in maximizing the value of the Bank(The adopted a measured variable depending on the approximate equation of simple Tobin's Q) to determine the style that achieves the highest value of the Bank, to take advantage of it in management, planning and control by knowing the strengths and weaknesses of the historical distribution of the facilities . the sample of the

Joints are among the most widespread geologic structures as they are found in most each exposure of rock. They differ greatly in appearance, dimensions, and arrangement, besides they occur in quite different tectonic environments. This study is important because joints provide evidence on what kind of stress produced them (history of deformation) and also because they change the characteristics of the rocks in which they occur. The Measured data of joints from the studied area which are located in the high folded zone – Northeast of Iraq, were classified according to their relationship with the tectonic axes by projecting them stereographically using Schmidt net in GEOrient ver.9.5.0 software. The joint systems revealed the orientation of

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col