Conference Papers

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    Compact wideband microstrip circular patch antenna for 6G application
    (Institute of Electrical and Electronics Engineers Inc., 2023) Mahapatra, R.K.; Shet, N.S.V.; Satapathi, G.S.; Manjukiran, B.; DImri, P.; Shetty, A.N.; Shettigar, S.; Patro, B.S.; Senapati, A.; Srichandan, R.
    In order to create an antenna with a wide band range, the work provided in this paper displays the parametric analysis for the circular patch antenna designs. Microstrip line in the 50 ohm range is used in the developed antenna. To achieve it, three proposed designs were put forth, out of which design2 achieves a broadband of below -10dB return loss range from 20.33 to 47.11 GHz with a bandwidth of 26.78 GHz towards 6G. The HFSS (High Frequency Structure Simulator) is used on intel core i5, 8 GB RAM, Windows 11 to simulate the suggested antenna designs. © 2023 IEEE.
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    Design and Analysis of Microstrip Wideband Filter
    (Institute of Electrical and Electronics Engineers Inc., 2023) Mahapatra, R.K.; Kaliyath, Y.; Shet, N.S.V.; Satapathi, G.S.; Manjukiran, B.; DImri, P.; Shetty, A.N.; Srichandan, R.; Patro, B.S.; Senapati, A.
    This paper deals with the study on conventional wideband bandpass filter (BPF) and the bandpass filter designed using the split ring resonator structure. The proposed design using the SRR consists of 3 SRR on which the filter is mounted. This is designed using the HFSS software. The material with in the dielectric constant of 4.36 and the loss tangent of 0.01 is used for the substrate material. The substrate height is varied with the dimension of 4.9 x 2.9 kept constant. The result observed for the BPF on SRR with increase substrate height has shown better results better return loss characteristics as compared to the other design. © 2023 IEEE.
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    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. © 2023 IEEE.