http://repository.iitr.ac.in/handle/123456789/19834
Title: | MM Big Data Applications: Statistical Resultant Analysis of Psychosomatic Survey on Various Human Personality Indicators |
Authors: | Rastogi R. Chaturvedi D.K. Satya S. Arora, Navneet Trivedi P. Gupta M. Singhal P. Gulati M. Sahana S.K. Bhattacharjee V. |
Published in: | Advances in Intelligent Systems and Computing Proceedings of 2nd International Conference on Computational Intelligence, ICCI 2018 |
Abstract: | Machines are getting intelligent day by day. Nowadays, the human being is so much complex that nobody can do any concrete or accurate behavioural or action-related predictions. The mood swing has been also an epidemic in modern India and all metro cities of the developed countries. We have grown rich in terms of money and physical facilities; modern science has gifted us many boons, but simultaneously the mental, physical and spiritual disorders have surprisingly disturbed the smile, peace and definite attitude and life style of individual and all human beings. The 3 M—Mobile, Money and Marriage are essential in one’s life, but the over addiction and misuse of resources, facilities and lack of right understanding with selfishness and ungrateful conduct have changed all the social parameters. So, presently the stress has been the biggest challenge against mankind like nuclear weapons, global warming and epidemics. It leads towards tension, frustration and depression and ultimately in extreme cases towards the self-suicide or the murder of innocents. The happiness index, safety of individual, living parameters have been drastically challenged us, and India specially has pathetic situation among global quality of life (QoL) index. The present paper is an effort to define a simulated model and framework for the subjective quality of stress into quantitative parameters and mathematically analysing it with the help of popular machine learning tools and applied methods. With the help of machine intelligence, authors are trying to establish a framework which may work as an expert system and may help the individual to grow self as a better human being. |
Citation: | Advances in Intelligent Systems and Computing, 2020, 303- 325 |
URI: | https://doi.org/10.1007/978-981-13-8222-2_25 http://repository.iitr.ac.in/handle/123456789/19834 |
Issue Date: | 2020 |
Publisher: | Springer Verlag |
Keywords: | Anaconda Machine learning Multinomial logistic regression Pycham Python Stress Use case Variance Big data Expert systems Global warming Learning systems Machine learning Stresses Anaconda Multinomial logistic regression Pycham Python Variance Nuclear weapons |
ISBN: | 9.78981E+12 |
ISSN: | 21945357 |
Author Scopus IDs: | 57192103103 12809516500 55897679400 15130971300 57210121940 57209260997 57213963786 57209249944 |
Author Affiliations: | Rastogi, R., Department of Computer Science and Engineering, ABESEC, Ghaziabad, India Chaturvedi, D.K., Department of Electrical Engineering, DEI, Agra, India Satya, S., Department of Rural Development, IIT-Delhi, New Delhi, India Arora, N., Department |
Corresponding Author: | Rastogi, R.; Department of Computer Science and Engineering, India; email: rohit.rastogi@abes.ac.in |
Appears in Collections: | Conference Publications [ME] |
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