Browsing by Author "Mahapatro, S.R."

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3D-Printing Technology: A Review
(Institute of Electrical and Electronics Engineers Inc., 2024) Mahapatra, R.K.; Kaliyath, Y.; Shet, N.S.V.; Satapathi, G.S.; Mahapatro, S.R.; Lakshmu Naidu, M.L.
The process of digital fabrication, commonly known as 3D printing, involves gradually adding materials to a geometric representation to produce actual items. The advantages of 3D printing for industrial use include little material waste, simple manufacturing, minimal human participation, minimal post-processing, and energy efficiency. In this study, we provide insights on the development of 3D printing, its history, current state, uses, and potential future directions. There is a detailed explanation of various materials that work with each sort of 3D printing procedure. Â© 2024 IEEE.
A survey on wireless sensor network (applications and architecture)
(Inderscience Publishers, 2024) Mahapatra, R.K.; Kaliyath, Y.; Shet, N.S.V.; Mahapatro, S.R.; Satapathi, G.S.; Prusty, S.B.; Patro, B.S.
Proliferation of the wireless sensor network is due to the advancement in wireless networks, information technologies, miniaturisation of sensors as well as convergence of MEMS technology, wireless communication and digital electronics. These wireless networks interface the physical world to the computing (virtual) world. In recent years, the availability of smaller, cheaper and intelligent sensors on a large scale has motivated the deployment of sensors in various applications such as smart city, smart home, smart grid, automated vehicles, etc. The sensor plays an important role in internet of things. This survey reports current research activities, applications, characteristics, architecture and case study of WSNs. In addition to this open research issues/problems are discussed. The aim is to present a comprehensive study of the literature on several aspects of wireless sensor network such as application and architecture. © 2024 Inderscience Enterprises Ltd.
Critical Review on Heart Disease Prediction: A Machine Learning Approach
(Institute of Electrical and Electronics Engineers Inc., 2023) Mahapatro, S.R.; Mahapatra, R.K.; Shet, N.S.V.; Prusty, S.B.; Satapathi, G.S.; Manjukiran, B.; Reddy, G.; Chandana, O.; Divya, N.; DImri, P.
The heart is the second-most significant organ in the human body after the brain, which is the most significant organ. All of the body's organs are nourished and the blood is circulated. In the medical field, it might be difficult to anticipate the development of heart diseases. Data analytics is crucial for developing predictions based on new information, and it helps hospitals predict diseases. Every year, cardiovascular diseases account for more than 31 % of all fatalities globally. Different Machine learning algorithms are in this paper to predict heart disease. It presents a general overview of the previous work and offers insight into the current algorithm. Â© 2023 IEEE.