Low–lying band states are one of the most fundamental excitation modes in the energy spectra of deformed nuclei. This paper presents a theoretical analysis of the properties of a deformed nuclei within the phenomenological model [1]. The normalization of the wave functions of low –lying excited band states are also calculated.IIUM Engineerin g

The dynamics of relative motion in a perturbed orbital environment are exploited based on Gauss’ and Cowell’s variational equations. The inertial coordinate frame and relative coordinate frame (Hill frame) are used, and a linear high fidelity model is developed to describe the relative motion. This model takes into account the primary gravitati

Urban Heat Island (UHI) phenomenon gives negative impacts towards urban climate changes, energy use and rises on the temperature of cities. One of the factors that contribute to the rising of temperature in urban area is the significant amount of impervious surfaces. The use of impervious surfaces is mostly found in parking lots which could create

The recent global financial crisis that began in the US and spread sporadically to other parts of the world has been a sort of awakening that financial stability of financial institutions should be on check from time to time. This scenario has called for a concerted effort that may possibly be geared towards introducing a framework or policy that t

In this paper, the autonomous in-orbit-self-assembly of multiple satellites is exploited in close proximity operations. Guidance and control algorithms are developed based on the closed-form analytical solution of relative motion equations that is completely explicit in time in a general Keplerian orbit. The guidance algorithm is based on a modifie

Preparation of Polypropylene ternary nanocomposites (PPTN) was accomplished by blending multiwall carbon nanotube (MWCNT) in polypropylene/clay binary system using a melt intercalation method. The effects of MWCNT loadings (A), melting temperature (B) and mixing speed (C) were investigated and optimized using central composite design. The analysis

Researchers are getting great benefits of big data as information gathered from social media like Facebook, Twitter and being used to perceive the lot from family planning to predicting postpartum depression. Detecting behavioral changes in social networks represents an exciting new area of this progression that is used to counter organizational be

Time Series Forecasting is vital for wide range of domains such as financial market forecasting, earthquake forecasting, weather forecasting, electric power demand forecasting and etc. The past 25 years of time series forecasting research that has been reviewed in (Tinbergen Institute Discussion Paper: International Journal of Forecasting) for the

This study utilized a random forest model for monthly temperature forecasting of KL by using historical time series data of (2000 to 2012). Random Forest is an ensemble learning method that generates many regression trees (CART) and aggregates their results. The model operates on patterns of the time series seasonal cycles which simplifies the fore

Introduction: Lower Urinary Tract Symptoms (LUTS) is a worldwide problem that is highly prevalent and varies by age, geography and culture. It influences the quality of life with a myriad of social implications. Objective: To estimate the prevalence of LUTS among patients attending the gynaecology clinic. We also assessed its severity and associate