Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Mixed ligand metal complexes of CrIII, FeIII,II, NiII and CuII have been synthesized using 5-chlorosalicylic acid (5-CSA) as a primary ligand and L-Valine (L-Val) as secondary ligand. The metal complexes have been characterized by elemental analysis, electrical conductance, magnetic susceptibility measurements and spectral studies. The electrical conductance studies of the complexes indicate their electrolytic nature. Magnetic susceptibility measurements revealed paramagnetic nature of the all complexes. Bonding of the metal ion through –OHand –COOgroups of bidentate to the 5-chlorosalicylic acid and through –NH2 and –COOgroups of bidentate to the L-valine by FT-IR studies . The agar diffusion method has been used to study the antib

Cancer stem cells (CSCs) are defined as a population of cells present in tumours, which can undergo self-renewal and differentiation. Identification and isolation of these CSCs using putative surface markers have been a priority of research in cancer. With this background we selected pancreatic normal and tumor cells for this study and passaged them into animal tissue culture medium. Further staining was done using alkaline phosphatase and heamatoxilin staining. Blue to purple colored zones in undifferentiated pluripotent stem cells and clear coloration in the chromatin material indicated pancreatic cells. Further studies on the cell surface marker CD 44 were done using ELISA. For this, the protein was extracted from cultivated normal and t

The main aim of this study was to molecular identification and determine the antagonistic impact of rhizosphere Trichoderma spp. against some phytopathogenic fungi, including (Magnaporthe grisea) pyricularia oryzae, Rhizoctonia solani and Macrophomina phasolina. Four Trichoderma isolates were isolated from rhizosphere soils of the different host plants in different locations of Egyptian governorates. The morphological characterization of isolated Trichoderma as well as using of (ITS1-5.8S-ITS2) ribosomal gene sequence acquisition and data analyses. By comparing the results of DNA sequences of ITS region, the fungi represented one isolate were positively identified as T. asperellum (1 isolate T1) and one as T. longibrachiatum (1 isolate T2)

Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene

Background: One of the unique prosthesis for tooth or teeth replacement is the dental implant. Our attempt is using a biomaterial system that is easily obtained and applicable and has the ability to provoke osteoinductive growth factor to enhance bone formation at the site of application. One of these natural polymers is hyaluronic acid. Material and methods: Sixty machined surface implants from commercially pure titanium rod inserted in thirty NewZealand rabbits. Two implants placed in both tibia of each rabbit. The animals scarified at 1, 2 and 4 weeks after implantation (10 rabbits for each interval). For all of animals the right tibia’s implant was control (uncoated) and the left one was experimental (coated with 0.1ml Hyaluro