The two-frequency shell model approach is used to calculate the
ground state matter density distribution and the corresponding root
mean square radii of the two-proton¹⁷Ne halo nucleus with the
assumption that the model space of ¹⁵O core nucleus differ from the
model space of extra two loosely bound valence protons. Two
different size parameters bcore and bhalo of the single particle wave
functions of the harmonic oscillator potential are used. The
calculations are carried out for different configurations of the outer
halo protons in ¹⁷Ne nucleus and the structure of this halo nucleus
shows that the dominant configuration when the two halo protons in
the 1d_5/2 orbi

Throughout this paper R represents commutative ring with identity, and M is a unitary left R-module. The purpose of this paper is to study a new concept, (up to our knowledge), named a semi-extending modules, as generalization of extending modules, where an Rmodule M is called semi-extending if every sub module of M is a semi-essential in a direct summand of M. Various properties of semi-extending module are considered. Moreover, we investigate the relationships between semi-extending modules and other related concepts, such as CLS-modules and FI- extending modules.

     The Non-thermal plasma has a wide range of applications in different areas. In this study, the oxidation of a model fuel containing organo-sulfur compounds (benzothiophene and dibenzothiophene) was investigated using plasma. The process involved ozone generation through dielectric barrier discharge, followed by extraction using acetonitrile. The results demonstrated the efficient oxidation and removal of dibenzothiophene and benzothiophene by non-thermal plasma. The desulfurization efficiency reached 93.78% under the optimum conditions, including a voltage of 11Kv, temperature of 50ºC, duration of 4 hours, and a flow rate of 75 ml/min.

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to