Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Classifying behavioural traits of small-scale farmers: Use of a novel artificial neural network (ANN) classifier(Institute of Electrical and Electronics Engineers Inc., 2016) Jena, P.R.; Majhi, R.This paper develops and employs a novel artificial neural network (ANN) model to study farmers' behaviour towards decision making on maize production in Kenya. The paper has compared the accuracy level of ANN based model and the statistical model and found out that the ANN model has achieved higher accuracy and efficiency. The findings from the study reveal that the farmers are mostly influenced by their demographic and food security for decision making. Further to examine the relative importance of different demographic and food security characteristics, an ANOVA test is undertaken. The results found that education and food security indices are instrumental in influencing farmers' decision making. © 2016 IEEE.Item Deep Learning for Stock Index Tracking: Bank Sector Case(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2021) Arjun, R.; Suprabha, K.R.; Majhi, R.The current study explores the efficacy of deep learning models in stock market prediction specific to banking sector. The secondary data of major fundamental indicators and technical variables during 2004–2019 periods of two banking indices, BSE BANKEX and NIFTY Bank of Bombay stock exchange and National stock exchange, respectively, are collected. The factors impacting market index prices were analyzed using nonlinear autoregressive neural network. Preliminary findings contradict the general random walk hypothesis theory and model improvement over previous studies. The implications from practical and theoretical perspective for stakeholders are discussed. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Estimating the impact of news on Indian government decisions to contain the spread of COVID-19 in India(American Institute of Physics Inc., 2023) Bhatnagar, V.; Majhi, B.; Majhi, R.Corona-Virus or COVID-19 has adversely affected human life. A large number of human deaths and infected cases were recorded. India has also severely affected and recorded many deaths and infected cases. Understanding the criticality of the situation, the Indian government had taken decisions on lockdown and unlocking of the state to stop spreading of this deadly virus. It is evident from the information theory that more pieces of information eventually help a decision maker to make sound and well-informed decisions. News is considered as an important source of information around the world. This study is an attempt towards finding the impact of news on decisions taken by the Indian government. Sentiment analysis and Chi-square testing methods have been employed in the present investigation. Results obtained from the analysis are in line with the people opinion and the sentiments expressed by news articles towards the decisions made by the Indian government. © 2023 Author(s).Item Robust Machine Learning Methods for Prediction of Childhood Anemia - A Case of the Empowered Action Group States of India(Institute of Electrical and Electronics Engineers Inc., 2024) Gurudatha, S.; Majhi, R.Anemia is a major undernutrition concern in developing countries. Anemia in early childhood leads to lower immunity and diminished cognitive development and is one of the major causes of early childhood mortality. In India, the major burden of anemia is seen in the Empowered Action Group (EAG) states. Concerted efforts are needed to reduce the burden of anemia. This study uses machine learning (ML) models to predict anemia among children aged six to fifty-nine months using data from the fifth round of the Indian Demographic and Health Survey (DHS), also known as the National Family Health Survey - 5 (NFHS - 5) in the EAG states. The dataset had 85,189 rows. The random oversampling method was used to balance the dataset as there was a class-imbalance issue. Four ML models, namely conditional inference (CI) tree, random forest (RF), extreme gradient boosting (XGB), and k-nearest neighbors (KNN), were developed for prediction. The models were compared based on metrics such as accuracy, sensitivity, specificity, precision, and F1 score. The RF model had the best overall accuracy of 64%. The RF and XGB models had the best sensitivity of 0.75 and 0.7, respectively. The CI tree model had the highest specificity of 0.59. The RF and XGB models had the best F1 scores of 0.74 and 0.72, respectively. The RF model pointed out that the mother's nutritional status is the most important factor in predicting childhood anemia. Children were more likely to be anemic if their mothers had low Body Mass Index (BMI). This study contributes to the body of literature using ML techniques to study anemia in children. © 2024 IEEE.Item Segmenting Indian Alcohol Consumers: Analyzing Sustainable Trends Using K-Means Clustering(Institute of Electrical and Electronics Engineers Inc., 2024) Sukumaran, L.; Majhi, R.Wine has become increasingly popular in India, with projections indicating an annual growth rate of 7% through 2029. This rise in popularity is partly attributed to the perception of wine as a healthier alternative to stronger spirits such as rum and brandy. This paper employs K-Means clustering to segment Indian millennial alcohol consumers and explores whether the increase in wine consumption is mainly driven by health and sustainability considerations. The findings reveal a correlation between wine consumption and the health and sustainability attributes valued by consumers. Four distinct clusters of Indian alcohol consumers were identified. Among these, two clusters exhibit an intention-behavior gap. One cluster primarily consumes strong spirits but is actively seeking healthier options, while the other shows little interest in strong spirits yet remains open to considering wine. Thus wine presents an opportunity for strong spirit drinkers to make healthier choices and may serve as a potential entry point for non-drinkers to begin consuming alcohol. © 2024 IEEE.