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

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

Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

This study is attempt to improve thermal isolation through measuring thermal conductivity composite of on polyester resin with fillers of (TiO2, ZnO, Acrylonitril, wood flour Coconut (Wf). The grain size of the fillers is 200 µm. The number of samples is (16) in addition to the virgin sample; these samples are prepared by cast molding method for polyester with filler volume fractions (5%, 10%, 15% and 20%). Shore hardness tests were used to measure the hardness and Lee disk method for thermal conductivity. The experimental results showed that the (20% ZnO) sample has the maximum value of thermal conductivity where (20% w.f) has minimum thermal conductivity .on the other hand (15% ZnO) sample give the maximum value of hardness where (20% w

Manganese dioxide rotating cylinder electrode prepared by anodic deposition on a graphite substrate using MnSO4 solution in the presence of 0.918 M of H2SO4. The influence of different operational parameters (MnSO4 concentration, current density, time, and rotation speed) on the structure, and morphology of MnO2 deposit film was examined widely. The structure and crystal size determined by X-ray diffraction (XRD), the morphology examined by scanning electron microscopy (SEM) and atomic force microscopy (AFM) techniques. The γ-MnO2 obtained as the main product of the deposition process. It found that the four parameters have a significant influence on the structure, morphology, and roughness of the prepared MnO2 deposit. The crystal size in

Background: To evaluate the ISO depth of cure of bulkfill composites and depth of cure which determined by Vickers microhardness test. Materials and Methods: Bulkfill resin composite specimens (n=150) were prepared of three bulkfill composite materials (TetricEvo Ceram, Quixfil and SDR) and light cured by Flash max p3 for 3, 10, 20 seconds and by wood pecker for 10, 20 seconds respectively, a mold was filled with one of the three bulkfill composites and light cured. The specimens removed from the mold and scraped by plastic spatula and the remaining length (absolute length) was measured which represent the ISO depth of cure. After that the specimens were returned into the mold and a microhardness indentation device applied on the specimen