The radial wave functions of the Bear–Hodgson potential have been used to study the ground state features such as the proton, neutron and matter densities and the as- sociated rms radii of two neutrons halo 6He, 11Li, 14Be and 17B nuclei. These halo nuclei are treated as a three-body system composed of core and outer two-neutron (Core + n + n). The radial wave functions of the Bear–Hodgson potential are used to describe the core and halo density distributions. The interaction of core-neutron takes the Bear–Hodgson potential form. The outer two neutrons of 6He and 11Li interact by the realistic interaction REWIL whereas those of 14Be and 17B interact by the realistic interaction of HASP. The obtained results show that this model succee

Generally fossil based fuels are used in internal combustion engines as an energy source.
Excessive use of fossil based fuels diminishes present reserves and increases the air pollution in
urban areas. This enhances the importance of the effective use of present reserves and/or to develop
new alternative fuels, which are environment friendly. Use of alternative fuel is a way of emission
control. The term “Alternative Gaseous Fuels” relates to a wide range of fuels that are in the
gaseous state at ambient conditions, whether when used on their own or as components of mixtures
with other fuels.
In this study, a single cylinder diesel engine was modified to use LPG in dual fuel mode to study
the performance, emis

paper

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The