This study aims to recognize the most common thinking styles and level of the need for cognitive university students , the relation between thinking styles and the need for cognitive, and there are differences according to gender .The sample consists of (250) males and females university students for the academic year (2013-2014), and the researcher uses two scales;" thinking styles scale (Harison &Bramson, 1986), and the need for cognitive scale" (Cacioppo, Petty & Kao , 1996).
The results show that there is difference in the range of the prevalence of the thinking styles among university students , the scientific thinking style is the most common , the students have got the arrange level of the need for cognitive , and there

The research aims to identify the level of selective visual attention among students of the faculties of education at the University of Mosul. To achieve the goal of the research, the researchers chose a stratified random sample of students from the faculties of education at the University of Mosul for the academic year (2020-2021). The sample size was (652) students from the scientific and humanitarian specializations, the second and fourth stages. The researchers developed a test of multiple-choice to measure the selective visual attention, which consisted of (42) items. The results revealed that the students of the faculties of education for human sciences have an appropriate level of selective visual attention. There are statisticall

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d

This research aimed to identify the structural model of the relationship between emotional creativity and self-efficacy among male and female students of the preparatory year at Tabuk University. The current study adopted the descriptive correlational approach, as it is appropriate to the nature of the study. The study tools contained (60) items that measure the relationship between emotional creativity and self-efficacy among the male and female students of the preparatory year at Tabuk University. The study sample was chosen by the stratified random method of the study community, where the study sample reached (183) male and female students of the preparatory year at the University of Tabuk. The results of the study showed that there a

<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation