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

Photonic Crystal Fiber Interferometers (PCFIs) are greatly used
for sensing applications. This work presents the fabrication and
characterization of a relative humidity sensor based on Mach-
Zehnder Interferometer (MZI), which operates in reflection mode.
The humidity sensor operation based on the adsorption and
desorption of water vapour at the silica-air interface within the PCF.
The fabrication of this sensor is simple, it only includes splicing and
cleaving the PCF with SMF.PCF (LMA-10) with a certain length
spliced to SMF (Corning-28).
The spectrum of PCFI exhibits good sensitivity to humidity
variations. The PCFI response is observed for a range of humidity
values from (27% RH to 85% RH), the positi

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

The ligand 4-amino-N-(5-methylisoxazole-3-yl)-benzene-sulfonamide(L1) (as a chelating ligand) was treated with Pd(II),Pt (IV) and Au(III) ions in alcoholic medium in order to prepare a series of new metal complexes. Mixed ligand complexes of this primary ligand were prepared in alcoholic medium in presence of the co-ligand 4,4'-dimethyl-2,2'-bipyridyl(L2) with Cu(II) ,Pd(II) and Au(III) ions. The complexes were characterized in solid state using flame atomic absorption, elemental analysis C.H.N.S, FT-IR, UV-Vis Spectroscopy, conductivity and magnetic susceptibility measurements. The nature of some complexes formed in ethanolic solution has been studied following the molar ratio method, also stability constant was studied and the complexes f

School administration has an effective role in stimulating academic achievement, as it is the ideal regulation and activation of material and human power to achieve the goals of the educational process. This role has axes in the form of interests, aids, and specific procedures exercised by the school administration in improving the educational process, and assisting researchers in achieving the highest levels of academic achievement. This activation is achieved through stages of planning, organizing, coordinating, and evaluating.

To achieve the aims of this research, the researcher pursued the descriptive analytical approach, which is considered one of the most appropriate approaches to the nature of this type of research. The qu

This work deals with the effect of adding aluminum nanoparticles on the mechanical properties, micro-hardness and porosity of memory-shape alloys (Cu-Al-Ni). These alloys have wide applications in various industrial fields such as (high damping compounds and self-lubricating applications). The samples are manufactured using the powder metallurgy method, which involved pressing in only one direction and sintered in a furnace surrounded by an inert gas. Four percentages (0%, 5%, 10%, and 15%) of aluminum nanoparticles were fabricated, which depended on the weight of aluminum powder (13%) in the sample under study. To find out which phase is responsible for the reliability of the formation of this type of alloy and its porosity, X-ray diffr