Indian Institute of Technology Indore

About: Indian Institute of Technology Indore is a education organization based out in Indore, Madhya Pradesh, India. It is known for research contribution in the topics: Fading & Support vector machine. The organization has 1606 authors who have published 4803 publications receiving 66500 citations.

Air quality modelling using long short-term memory (LSTM) over NCT-Delhi, India

Abstract: Nowadays, monitoring and prediction of air quality parameters are becoming significantly important research topics in the context of increasing urbanization and industrialization. Therefore, efficient modelling of air quality parameters is essential because such an approach would enable to identify the existing and forthcoming implication of air pollution. In recent years, sharp rise in air pollution levels in Indian National Capital Territory of Delhi (NCT-Delhi) has made it the most polluted city of the world. Machine learning approaches are considered as an efficient and cost-effective method to model the air quality parameters and are widely used. However, current methods fail to incorporate long-term dependencies arising due to complex interaction of natural and anthropogenic factors. The present study is mainly aimed at predicting O3, PM2.5, NOx, and CO concentrations at a location in NCT-Delhi using the long short-term memory (LSTM) approach, which is considered as more efficient over other deep learning methods. Factors and parameters such as vehicular emissions, meteorological conditions, traffic data, and pollutant levels are employed in five different combinations. Performance evaluation of LSTM algorithms for hourly concentration prediction is carried out during 2008–2010, and it is found that LSTM models efficiently deal with the complexities and is immensely effective in ambient air quality forecasting. This paper can be considered as a significant motivation for carrying research on urban air pollution using latest LSTMs and helping the government and policymakers a better forecasting methodology for planning measures to curb ill impacts of degrading air quality.

TiO2–Co3O4 Core–Shell Nanorods: Bifunctional Role in Better Energy Storage and Electrochromism

Abstract: A suitably designed heterostructured TiO2–Co3O4 core–shell nanorod array has been found to exhibit improved supercapacitive as well as electrochromic properties as compared to the nanowires of either of the oxides when used individually The core–shell nanostructures have been grown on an FTO coated glass substrate by preparing TiO2 nanorods through hydrothermal reaction followed by growing a Co3O4 shell layer by electrodeposition The core–shell electrode shows high specific and areal capacitance of ∼342 F/g and ∼140 mF/cm2 (at scan rate of 100 mV/s), respectively Such an improvement in supercapacitive behavior, as compared to the behavior of the existing ones, is likely due to increased surface area and modified charge dynamics within the core–shell heterojunction Additionally, these core–shells also exhibit stable and power efficient bias induced color change between transparent (sky blue) and opaque (dark brown) states with coloration efficiency of ∼91 cm2/C Porous morphology and strong adhesion to