Faculty Publications

Now showing 1 - 3 of 3

An Assessment of Municipal Solid Waste Management in Bengaluru: A Case Study
(L and H Scientific Publishing, LLC, 2022) Majhi, R.; Muhammad, A.
The challenges of solid waste are increasing every day as the population in the urban areas is increasing at a rapid pace. The challenge of solid waste such as landfilling is a major issue that requires urgent attention as it degrades the environment and causes adverse health hazards. The major legislation frameworks, policies, scientific handling related to municipal solid waste management (MSWM), and its effective implementation are essential to improve the state of MSWM. In this paper, various parameters of MSWM are evaluated along with the review ofMSW generation, collection, characterization of solid waste, treatment, and disposal ways practised in Bengaluru. This paper helps in understanding the scenario of solid waste in Bengaluru, the challenges it faces, and the opportunities it offers. Various issues like public-private partnerships, decentralization, rag-pickers role, local communities’ initiatives, etc. are discussed. The study concludes that it is the need of the hour to understand the various technological solutions that need to be implemented along with establishing recycling plants, biodigesters, and other solutions that are presented in this paper could help in generating energy and other resources, and improve the scenario of solid waste in the city © 2022. L&H Scientific Publishing, LLC. All rights reserved
Prediction of crop yield using climate variables in the south-western province of India: a functional artificial neural network modeling (FLANN) approach
(Springer Science and Business Media B.V., 2023) Jena, P.R.; Majhi, B.; Kalli, R.; Majhi, R.
To meet the demand of the growing population, there exists pressure on food production. In this context, appropriate prediction of crop yield helps in agricultural production planning. Given the inability of the traditional linear models to provide satisfactory prediction performance, there is a need to develop a crop yield prediction model that is simple in complexity, accurate in prediction, and less time-consuming during training and validation phases. Keeping these objectives in view, the present paper focuses on building an adaptive, low complexity, and accurate nonlinear model for the prediction of crop yield. A time series dataset for the period 1991–2012 of Karnataka, a southwestern state of India, is used for yield prediction. An empirical nonlinear relation between crop yield and the four independent attributes has been obtained from the proposed ANN model. The independent attributes employed are total rainfall, the cumulative distribution of temperature, the proportion of irrigated land, and the average amount of fertilizer used. It is demonstrated that the developed model exhibits better prediction accuracy, less root mean square error in the range of 0.07–0.14, less mean square error in the range of 0.01–0.04, and mean absolute error in the range of 0.07–0.15 compared to its corresponding linear regression model. It is recommended that the proposed ANN model can also be applied to predict other agricultural products of the same or other geographical regions of the globe. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.
An empirical investigation to understand mobile phone users’ behavioural intention to give their end-of-life mobile phones for formal recycling
(Elsevier Ltd, 2024) Prabhu N, S.; Majhi, R.
Mobile phones have turned into a highly essential device for numerous individuals. Swift innovation and decrease in in-use lifespan have increased the generation of end-of-life mobile phones (EOL-MPs). Lesser formal recycling of EOL-MPs has detrimental outcomes on the environment, human health, and circular economy. Therefore, this research was undertaken to investigate factors impacting mobile phone users’ behavioural intention to give their EOL-MPs for formal recycling. The conceptual model was developed by integrating the theory of planned behaviour, norm activation model, and value-belief-norm theory. Responses were collected from mobile phone users aged 18 and above residing in Bengaluru, Mangaluru, and Huballi-Dharvad cities of Karnataka state, India. 1135 responses were analysed by applying partial least squares structural equation modelling. Incentives was figured out to be the most positively impacting construct on behavioural intention. Followed by awareness of consequences, social media, past recycling experience, and recycling attitude. Whereas risk perception regarding information security and convenience of recycling negatively impacts behavioural intention. Personal norms get activated by awareness of consequences and ascription of responsibility. As a result, personal norms positively impact behavioural intention. In addition, biospheric values also positively impact personal norms. The outcomes of PLSpredict signify that the conceptual model has high out-of-sample predictive power. The outcomes of this research can be utilized by various stakeholders like e-waste collection organisations, e-waste recycling organisations, mobile phone manufacturing companies, city corporations, educational institutions, etc for improving sustainable end-of-life management of EOL-MPs. © 2024 Elsevier Ltd

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