Motilal Nehru National Institute of Technology Allahabad

About: Motilal Nehru National Institute of Technology Allahabad is a education organization based out in Allahabad, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 2475 authors who have published 5067 publications receiving 61891 citations. The organization is also known as: NIT Allahabad & Motilal Nehru Regional Engineering College.

Application of Mie theory and fractal models to determine the optical and surface roughness of Ag–Cu thin films

Abstract: Thin films of Ag/Cu were deposited by reactive DC magnetron sputtering on (001)-oriented Si and glass substrates for various deposition times (4–24 min). These films were characterized by atomic force microscopy (AFM), and a power law scaling was performed on the obtained micrographs to investigate the self-affine nature of the sample morphology, which is indicative of a fractal structure. We applied the Higuchi’s algorithm to the AFM data to determine the fractal dimension of each sample, and the Hurst exponents were computed. The deposition time dependences of these parameters and the grain size distributions estimated from the UV–visible spectra using the Mie theory, allowed us to describe a particle formation mechanism during the deposition process, in which the length of continuous paths of conductive particles increases as the deposition time is increased. In agreement with this explanation, the electrical resistance decreased with the increment of the deposition time.

Spatiotemporal mapping of Land Use/Land Cover dynamics using Remote Sensing and GIS approach: a case study of Prayagraj City, India (1988–2018)

Abstract: Prayagraj City is one the biggest cities in the State of Uttar Pradesh which has been selected as Smart City by Ministry of Housing and Urban Affairs, Government of India, in 2015. This city has rapidly evolved in the last three decades due to the urbanization process. This study has used multispectral imageries of Landsat Thematic Mapper and Operational Land Imager/Thermal Infrared Sensor of four different time points at the interval of ~ 10 years, i.e., 1988, 1997, 2008, and 2018. These images have been preprocessed and then classified through supervised classification using Maximum Likelihood Classifier in ERDAS IMAGINE version 2014. The overall accuracy achieved is more than 88% in all the four time points. The periodical change results have revealed that all land use/land cover (LU/LC) classes has altered in all periods, i.e., 1988–1997, 1997–2008, 2008–2018, and 1988–2018 with remarkable trends, patterns, and magnitudes. The growth of Built-up land is a major concern. The results of the change matrix (1988–2018) have indicated that the most expanded class was built-up land which has evolved into 64.52% at the cost of Agriculture land by 24.41%, Forest land by 10.56%, and Barren land by 6.01%. The above results of LU/LC dynamics can help in making planning and policy development for restoring and enhancing the carrying capacity of land and sustainability of the environment in a city landscape.