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

AA Abbass, HL Hussein, WA Shukur, J Kaabi, R Tornai, Webology, 2022 Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The mai

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

This research deals with a unique and innovative topic, that is the study of complaint in the Quranic text. Despite its importance, it has never been studied before, because most of the complaint 's meanings in the Quranic text is: the in explicit complaint. The mentioned complaint's expressions in different contexts overlap with other purposes, in particular call method and its peripherals like mourn , ask for help , exclamation and others.
Moreover, expressions that reveal complaint are related to the complainant's emotional and psychological status, and the complaint's context.
This research deals with the topic into two sections: The first deals with the important expression of complaint such as: iff, ouah, mooing, crying. The

The rapid success and the field dilation of Daish organization in both Iraq and Syria make academic institutes and research centers to pay attention to its propaganda means to gain its public opinion, and to further investigation about new methods employed by this organization to disseminate its messages to the public, particularly young people in large areas of the world. This organization uses traditional propaganda techniques on psychological war and its levels, social network sites and platforms that are distributed online. This study seeks to expose more persuasive methods used by the organization to gain multiple classes of society and to disseminate its extremist ideological thoughts. It also studies the psychological operation an

The multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers  , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg