The energy expectation values for Li and Li-like ions ( , and ) have been calculated and examined within the ground state and the excited state in position space. The partitioning technique of Hartree-Fock (H-F) has been used for existing wave functions.

Collective C2 transitions in 32S are discussed for higher
energy configurations by comparing the calculations of transition
strength B(CJ  )with the experimental data. These configurations
are taken into account through a microscopic theory including
excitations from the core orbits and the model space orbits with nħω
excitations.
Excitations up to n=10 are considered. However n=6 seems to
be large enough for a sufficient convergence. The calculations
include the lowest seven 2+0 states of 32S.

The purpose of the present work is to calculate the expectation value of potential energy for different spin states (??? ? ???,??? ? ???) and compared it with spin states (??? , ??? ) for lithium excited state (1s2s3s) and Li- like ions (Be+,B+2) using Hartree-Fock wave function by partitioning techanique .The result of inter particle expectation value shows linear behaviour with atomic number and for each atom and ion the shows the trend ??? < ??? < ??? < ???

One of the most important techniques for preparing nanoparticle material is Pulsed Laser Ablation in Liquid technique (PLAL). Carbon nanoparticles were prepared using PLAL, and the carbon target was immersed in Ultrapure water (UPW) then irradiated with Q-switched Nd:YAG laser (1064 nm) and six ns pulse duration. In this process, an Nd:YAG laser beam was focused near the carbon surface. Nanoparticles synthesized using laser irradiation were studied by observing the effects of varying incident laser pulse intensities (250, 500, 750, 1000) mJ on the particle size (20.52, 36.97, 48.72, and 61.53) nm, respectively. In addition, nanoparticles were characterized by means of the Atomic Force Microscopy (AFM) test, pH easurement

     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.

This article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the bat algorithm (BAT) to solve a single-objective optimization problem. It first runs GSA, followed by BAT as the second step. The proposed approach relies on a parameter between 0 and 1 to address the problem of falling into local research because the lack of a local search mechanism increases intensity search, whereas diversity remains high and easily falls into the local optimum. The improvement is equivalent to the speed of the original BAT. Access speed is increased for the best solution. All solutions in the population are updated before the end of the operation of the proposed algorithm. The diversification f