Social Capital’s Impact on Civic Engagement: An Empirical Study on Pakistani Youth

The aim of this research is to assess the impact of social capital on civic engagement. The quantitative method was applied to measure impact of independent variables on dependent variable. The survey instrument was applied to collected data from undergraduate student of four general Universities of Pakistan. The partial least squares structural equation modeling (PLS-SEM) approach was applied to measure impact of bridging, bonding social capital and trust on civic engagement. Results indicate that bonding social capital and trust have strong association with civic engagement, however, association between bridging social capital and civic engagement was found insignificant. The analyses indicate that it is a basic requirement to bring immediately policy reforms in context of youth development and create more opportunities for youth to engage in the social and structural development of society.

Estimation of Wind Energy in Meteorologically Unobserved Area of Sindh, Pakistan and its Impacts

Generation of electricity by wind energy is playing an important role to reduce environmental pollution; comparatively low cost with unlimited source of energy makes it more attractive. Present research work has been carried out considering these aspects which have serious negative impacts on environment and economy. This study presents mapping of wind speed over the province of Sindh (Pakistan) using spatial interpolation of wind speed data. Spatial distribution of monthly wind speed was found largely influenced by topography. It is to be noted that there is no research recorded relative to the interpolation methods in wind speed data of Sindh region. The purpose of this study is to predict the wind potential for meteorologically unobserved area of Sindh( Pakistan) to predict the feasibility of electricity generation. In the present research, for modeling nineteen different locations were selected. Four year wind speed data for Sindh, recorded by meteorological department of Pakistan, is used in this study. This study emphasized on deriving a gridded dataset of monthly wind speed from wind station observations with deeper analysis of the influence of topography on wind speed in Sindh. Three interpolation methods have been compared, that is Inverse Distance weighting (IDW), Radial Basis Function (RBF) and Residual Kriging (RK). A detailed study of relation between wind speed and different topographical factors, such as elevation, slope, latitude and longitude, it was revealed that, the correlation between latitude, longitude and wind speed is most appropriate. Regression model is used to remove the trend in spatial distribution of wind speed. The residuals are then interpolated onto a regular grid using, Kriging. Error analysis is performed by cross-validation. The residual Kriging procedure is found to be an excellent method compared to IDW or RBF methods, with RMSE error) and R 2 (root mean squared (correlation coefficient) values showing outstanding results. The Residual Kriging was chosen to interpolate the monthly wind speed in unobserved areas of Sindh. All the work has been done in GIS(Geographic information systems) and interpolation techniques . In order to test the applicability and benefit of the model, a case study has been discussed with three main issues, that is, the energy generation, environmental benefits and economical aspects.This research has provided a valuable information to decide best available interpolation method as well as most suitable site for wind farmind.