National Institute of Technology Calicut

About: National Institute of Technology Calicut is a education organization based out in Kozhikode, Kerala, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 3627 authors who have published 4638 publications receiving 50830 citations. The organization is also known as: Calicut Regional Engineering College & NIT Calicut.

Vehicular Emission Modeling at Toll Plaza Using Performance Box Data

Abstract: Delay occurring on any facility causes an extra amount of fuel consumption, leading to extra emissions. Toll plazas are the points laid on the highways for toll transaction that act as bot...

Investigations on Performance and Emission Characteristics of Vegetable Oil Biodiesels as Fuels in a Single Cylinder Direct Injection Diesel Engine

Abstract: Neat vegetable oils having high viscosity and low volatility could result in incomplete combustion in engine operation. The remedy for this is conversion of vegetable oils into biodiesels in order to reduce viscosity and increase volatility, thereby improving the performance in a CI engine. Biodiesel is methyl ester derived from vegetable oils (edible and non edible oils) or animal fats. Biodiesel can be used in pure form or as a blended form with diesel fuel and tested in CI engines with little or no modifications. This article presents the results of investigations carried out on a single cylinder, four stroke, and direct injection diesel engine operated with biodiesels of coconut oil, palm oil, and rubber seed oil. Comparative analysis in terms of brake power, brake thermal efficiency, brake specific fuel consumption, CO, HC, and NO x are discussed. The brake thermal efficiency of palm oil biodiesel is found higher and lower brake specific fuel consumption compared to biodiesels of coconut oil...

Tensor based approach for inpainting of video containing sparse text

Abstract: Videos received from certain sources may contain irrelevant contents which might reduce the amount of information conveyed by it. This paper proposes an effective tensor based video inpainting approach to improve the quality of these videos by removing and replacing unwanted contents with relevant information. The proposed method employs reweighted tensor decomposition technique to identify and discard the inappropriate sparse components of the video data. These sparse components are substituted with proper contents by utilising spatio-temporal consistency through reweighted tensor completion. The replacement is carried out in such a way that the resulting video possesses superior temporal consistency and visual credibility. The proposed method is applied to sparse text removal of videos having dynamic content in various extents and is found that our method outperforms its counterparts.