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

Background: Poly propylene fibers with and without silane treatment have been used to reinforce heat cure denture base acrylic but, some mechanical properties like transverse strength, impact strength, tensile strength, hardness, wear resistance and wettability. Which are related to the clinical use of the prosthesis are not evaluated yet. The aim of the study is to identify the influence of incorporation of treated and untreated fibers on these properties Materials and methods: Eighty four heat cure acrylic specimens were constructed by conventional flasking technique. They were divided into six groups according to the tests and each group was subdivided into two subgroups control and experimental groups (seven samples for each subgroup

The research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.

      The impregnation method is used in test sample preparation, using molding by pressure presses.

      All samples were exposure to (Co⁶⁰) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.

      The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad

This work has been done with using of epoxy resin mixed with Granite powder were weighted by percent volume (5,10,15, and 20)%and then mixed with epoxy polymer to compose polymer composite. Hand lay-up technique is used in fabrication of the composite samples. Hardness test was carried out for the proper samples in both normal condition and after immersion in HCL (1 M and 2 M) solutions for periods ranging up to 10 weeks. After comparing the results between the polymer and their composite, the hardness increased with increasing Granite weight percent, it was found that Hardness were greater for the composites before immersion compared with their values after immersion.

The paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applie