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pro vyhledávání: '"Pachori A"'
Autor:
Sidhant Kumar Sahoo, Dipanjan Bhattacharjee, Roshan V Khanande, Hariom Pachori, Sourav Khanra, Basudeb Das
Publikováno v:
Indian Journal of Psychiatry, Vol 66, Iss 9, Pp 805-813 (2024)
Background: Individuals experiencing alcohol dependence syndrome (ADS) may struggle with relapse due to various factors, even after receiving successful inpatient treatment. While motivation enhancement therapy (MET) and pharmacotherapy are commonly
Externí odkaz:
https://doaj.org/article/e804b1d6b3b043318f3fd2d763f2a85c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract This paper considers the problem of estimation of the population total under probability proportional to size (PPS) sampling scheme when complete data is not available due to the presence of missing observations or non-response. The suggeste
Externí odkaz:
https://doaj.org/article/4f875e4cf2414ca2b48e8e1b50882012
Publikováno v:
In Biomedical Signal Processing and Control September 2024 95 Part A
Autor:
Jyoti, Kumari, Yadav, Saurabh, Patel, Chandrabhan, Dubey, Mayank, Kumar Chaudhary, Pradeep, Bilas Pachori, Ram, Mukherjee, Shaibal
Publikováno v:
In Biomedical Signal Processing and Control February 2025 100 Part C
Publikováno v:
In Biomedical Signal Processing and Control February 2025 100 Part C
Autor:
Rana, Debaraj, Pratik, Shreerudra, Balabantaray, Bunil Kumar, Peesapati, Rangababu, Pachori, Ram Bilas
Publikováno v:
In Biomedical Signal Processing and Control February 2025 100 Part A
Publikováno v:
In Digital Signal Processing January 2025 156 Part B
Publikováno v:
IEEE Access, Vol 12, Pp 103606-103625 (2024)
Electroencephalogram (EEG) signal-based emotion classification is vital in the ever-growing human-computer interface (HCI) applications. However, the chaotic, non-stationary, and person-dependent nature of EEG signals often limits such practical appl
Externí odkaz:
https://doaj.org/article/7daec66915ac4ad4b58693e56c828227
Autor:
Vardhan Paliwal, Kritiprasanna Das, Sam M. Doesburg, George Medvedev, Pengcheng Xi, Urs Ribary, Ram Bilas Pachori, Vasily A. Vakorin
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 2038-2048 (2024)
Electroencephalogram (EEG) is widely used in basic and clinical neuroscience to explore neural states in various populations, and classifying these EEG recordings is a fundamental challenge. While machine learning shows promising results in classifyi
Externí odkaz:
https://doaj.org/article/a9cd60afbcfd47d2b623585907981b66
Publikováno v:
In Sustainable Energy Technologies and Assessments June 2024 66