Abstract

In light of the great technological development and the emergence of globalization has increased global competition, where it became competitive exercise pressure on all sectors. In light of this companies mast enviorment depend on the means that keeps them on the competitive position through access to information about competitors in order to help them to draw a strategy that will achieve a competitive edge either through excellence or reduce the costs of their products and this means intelligence competitive and reverse engineering that help to gain information on competitors analyze and put of the decision-maker From this point formed the idea of ​​research in the statement of the role of

This research aims to address the most recent international standard in the field of insurance contracts, the International Financial Reporting Standard (IFRS17) and the theoretical framework of the standard in addition to the most important characteristics of the standard (IFRS17), as well as to identify the paragraphs of the modern standard, with the challenges its application in general and the use of the approach (inputs - operations - outputs) to present the challenges of its application in the Iraqi environment and specifically in the environment of Iraqi insurance sector companies (government), the research is based on the main premise that the identification of the requirements for the application of the International Fin

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

The current research aims to verify the role of strategic intelligence as an explanatory variable in organizational success as a respondent variable in the colleges of the University of Fallujah, the research community. (Dean, Associate Dean, Section Head, Division Officer, Unit Officer), The researcher used the questionnaire as the main tool to collect data that included (50) items, in addition to using personal interviews and field observations as aids in data collection. The researcher relied on statistical programs (SPSS V.25; Excel V (16) In the treatment and analysis of data through the use of the most appropriate statistical methods (arithmetic mean, standard deviation, difference coefficient, determinatio

Background: Thalassemias are a group of heterogeneous genetic disorders, in which the rate of production of hemoglobin is partially or completely suppressed due to reduced rate of synthesis of α or β- chain

Objectives: to estimate the prevalence of Hepatitis C infection among B thalassemia patients attending Ibn-AL-Baladi center of blood diseases in AL-Sader city, in AL-Resafa Quarter of Baghdad and to determine the possible risk factors.

Type of the study: Cross- sectional study.

Methods: A cross sectional study conducted on B Thalassemia patients attending the blood diseases center in Ibn-AL-Baladi hospital during the period from 1^st

The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w

Abstract

The research aims to identify the logical intelligence of distinguished students and to identify the extent of the contribution of the fields of logical intelligence to the sensitivity of students' sensory processing in distinguished schools. The research sample consisted of (400) male and female students selected by the stratified random method with the proportional method. The scale that was prepared according to the theoretical framework and the adopted theory was applied after being subject to the psychometric properties of validity and reliability, Logical thinking (observation, interpretation, mathematical and arithmetic operations) contributed to sensory processing. The results showed that disting