Search results

The purpose of this study is to propose an alternative efficient 3D emotion recognition model for variable-length electroencephalogram (EEG) data.

Classical AMIGOS data set which comprises of multimodal records of varying lengths on mood, personality and other physiological aspects on emotional response is used for empirical assessment of the proposed overlapping sliding window (OSW) modelling framework. Two features are extracted using Fourier and Wavelet transforms: normalised band power (NBP) and normalised wavelet energy (NWE), respectively. The arousal, valence and dominance (AVD) emotions are predicted using one-dimension (1D) and two-dimensional (2D) convolution neural network (CNN) for both single and combined features.

The two-dimensional convolution neural network (2D CNN) outcomes on EEG signals of AMIGOS data set are observed to yield the highest accuracy, that is 96.63%, 95.87% and 96.30% for AVD, respectively, which is evidenced to be at least 6% higher as compared to the other available competitive approaches.

The present work is focussed on the less explored, complex AMIGOS (2018) data set which is imbalanced and of variable length. EEG emotion recognition-based work is widely available on simpler data sets. The following are the challenges of the AMIGOS data set addressed in the present work: handling of tensor form data; proposing an efficient method for generating sufficient equal-length samples corresponding to imbalanced and variable-length data.; selecting a suitable machine learning/deep learning model; improving the accuracy of the applied model.

The present world is crippled with the pandemic coronavirus (Covid-19). The pandemic that originated in Wuhan city of China has sent every country in the world in an unprecedented situation that has social and economic impacts. This paper aims to explore whether epidemics and pandemics have any impact on consumption patterns among rural and urban consumers in India. Taking pandemic Covid-19 as a case study, it was explored how this pandemic impacted the consumption pattern of consumers in India; what are the similarities and/or differences between rural and urban consumers that are found in their consumption habits in the wake of Covid-19 pandemic.

The required data was collected through questionnaires sent to respondents. Approximately 500 respondents were contacted through the mail to fill in the survey questionnaire. Despite the sincere efforts, a total of 175 complete survey questionnaires were filled in by respondents. The study used SPSS Statistics version 25 software for the analysis of data.

It was found that epidemics and pandemics have a profound impact on the pattern of consumption in India. The study reveals that consumers resort to panic buying in the initial stages of epidemics and pandemics. It was found that consumption habits of consumers went a sea change and they were spending largely on essentials only. The study also reveals that the majority of consumers would like to continue in the same consumption habits as that of during COVID-19. The consumption pattern of urban consumers witnessed more change than the consumption pattern of rural consumers. It is due to the closure of eateries and restaurants, shopping malls, movie theatres, etc., in urban areas that forced the change in the consumption pattern of urban consumers.

The research has a limitation of using a less sample size. For the generalizations, more robust studies can be conducted with more data.

The findings of the study will give marketers an insight for framing their policies in the wake of epidemics and pandemics.

The research adds to the existing body of knowledge. There are plenty of studies on the behaviour of consumers. However, there are no major studies that focus on the behaviour of consumers during the outbreak of a pandemic. So, this study fills this gap in the existing body of knowledge.