An analytical form of the ground state charge density distributions
for the low mass fp shell nuclei ( 40  A  56 ) is derived from a
simple method based on the use of the single particle wave functions
of the harmonic oscillator potential and the occupation numbers of
the states, which are determined from the comparison between theory
and experiment.
For investigating the inelastic longitudinal electron scattering form
factors, an expression for the transition charge density is studied
where the deformation in nuclear collective modes is taken into
consideration besides the shell model space transition density. The
core polarization transition density is evaluated by adopting the
shape of Tass

In our work present, the application of strong-Lensing observations for some gravitational lenses have been adopted to study the geometry of the universe and to explain the physics and the size of the quasars. The first procedure was to study the geometrical of the Lensing system to determine the relation between the redshift of the gravitational observations with its distances. The second procedure was to compare between the angular diameter distances "DA" calculated from the Euclidean case with that from the Freedman models, then evaluating the diameter of the system lens. The results concluded that the phenomena are restricted to the ratio of distance between lens and source with the diameter of the lens noticing.

An analytical form of the ground state charge density distributions
for the low mass fp shell nuclei ( 40  A  56 ) is derived from a
simple method based on the use of the single particle wave functions
of the harmonic oscillator potential and the occupation numbers of
the states, which are determined from the comparison between theory
and experiment.
For investigating the inelastic longitudinal electron scattering form
factors, an expression for the transition charge density is studied
where the deformation in nuclear collective modes is taken into
consideration besides the shell model space transition density. The
core polarization transition density is evaluated by adopting the
shape of Tassie mod

In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of ho

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

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

B3LYP/6-31G, DFT method was applied to hypothetical study the design of six carbon nanotube materials based on [8]circulene, through the use of cyclic polymerization of two and three molecules of [8]circulene. Optimized structures of [8]circulene have saddle-shaped. Design of six carbon nanotubes reactions were done by thermodynamically calculating (Δ S, Δ G and Δ H) and the stability of these hypothetical nanotubes depending on the value of HOMO energy level. Nanotubes obtained have the most efficient gap energy, making them potentially useful for solar cell applications.