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Articles by Kandarpa Kumar Sarma
DASTNet-X: an explainable dual-attention based spatio-temporal network for arrhythmia classification
Abstract Deep learning (DL) models have demonstrated strong performance in electrocardiography (ECG) arrhythmia classification. However, the criteria and processes for selecting ECG samples for analysis are often unclear. This lack of transparency, together with the challenge of interpreting the rationale behind model predictions, may limit clinical acceptance.
NOMA‐Based Satellite‐UAV‐Terrestrial Network With Partial Relay Selection and Imperfect CSI and SIC
Conflicts of Interest The authors declare no conflicts of interest. References 1, , , and , “What Should 6G Be?,” Nature Electronics 3, no. 1 (2020): 20–29. 2, , , and , “6G Wireless Communications: Vision and Potential Techniques,” IEEE Network 33, no. 4 (2019): 70–75. 3, , , , , and , “Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges,” IEEE Internet of Things Journal 8, no. 11 (2021): 8910–8934.
Considerations on Novel Network Edge Physical Nodes Architectures Leveraging A Bottom-Up Technology-Centric Approach Empowered by Micro/Nanotechnologies (MEMS/NEMS) and Federated Learning
Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 7 November 2024 / Approved: 8 November 2024 / Online: 8 November 2024 (10:15:04 CET) Iannacci, J.; Bhuyan, M.; Sarma, K. K.; Sharma, P.; Misra, A.; Misra, D. D.; Guha, K. Considerations on Novel Network Edge Physical Nodes Architectures Leveraging A Bottom-Up Technology-Centric Approach Empowered by Micro/Nanotechnologies (MEMS/NEMS) and Federated Learning. Preprints 2024, 2024110603.
Edge Computing for Smart-City Human Habitat: A Pandemic-Resilient, AI-Powered Framework
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
IoHT and Edge Computing Aided Pandemic-Compliant, Resilient and Perceptive Platform for Smart-City Human Habitat
Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 12 September 2024 / Approved: 12 September 2024 / Online: 13 September 2024 (08:40:12 CEST) ---, A. C.; Sarma, K. K.; Misra, D. D.; Guha, K.; Iannacci, J. IoHT and Edge Computing Aided Pandemic-Compliant, Resilient and Perceptive Platform for Smart-City Human Habitat. Preprints 2024, 2024091035. https://doi.org/10.20944/preprints202409.1035.v1 ---, A. C.; Sarma, K. K.; Misra, D. D.; Guha, K.; Iannacci, J.
Adaptive Hybrid Beamforming Codebook Design Using Multi-Agent Reinforcement Learning for Multiuser Multiple-Input-Multiple-Output Systems
1. Introduction MIMO systems employ multiple antennas at both the transmitter and receiver ends to enhance communication performance. MIMO technology leverages spatial diversity and multiplexing to increase data throughput and link reliability without requiring additional bandwidth or transmit power, making it fundamental in modern wireless communication systems, including 4G and 5G networks.
Adaptive Hybrid Beamforming Codebook Design using Multi-Agent Reinforcement Learning for Multiuser MIMO Systems
Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 14 July 2024 / Approved: 15 July 2024 / Online: 16 July 2024 (05:16:10 CEST) Bhuyan, M.; Sarma, K. K.; Misra, D. D.; Guha, K.; Iannacci, J. Adaptive Hybrid Beamforming Codebook Design using Multi-Agent Reinforcement Learning for Multiuser MIMO Systems. Preprints 2024, 2024071166. https://doi.org/10.20944/preprints202407.1166.v1 Bhuyan, M.; Sarma, K. K.; Misra, D. D.; Guha, K.; Iannacci, J.
linking academia, business and industry through research
Home Full-text access for editors Deep features-based dialect and mood recognition using Assamese telephonic speech by Mridusmita Sharma; Kandarpa Kumar Sarma International Journal of Information and Communication Technology (IJICT), Vol. 17, No. 4, 2020 Abstract: Learning aided methods are popular for designing automatic speech recognition (ASR) systems.
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