Zobrazeno 1 - 10
of 303
pro vyhledávání: '"Ravinesh C. Deo"'
Publikováno v:
IEEE Access, Vol 12, Pp 72530-72543 (2024)
Atmospheric visibility and cloud ceiling forecasts are essential for the safety and efficiency of flight operations and the aviation industry. Routine hourly aviation meteorological observations are recorded at every airport. However, forecasts of th
Externí odkaz:
https://doaj.org/article/2a1c239623e94eabae5be1164bfca3eb
Autor:
Lionel P. Joseph, Ravinesh C. Deo, David Casillas-Perez, Ramendra Prasad, Nawin Raj, Sancho Salcedo-Sanz
Publikováno v:
IEEE Access, Vol 12, Pp 58750-58777 (2024)
Wind, being a clean and sustainable resource, boasts environmental advantages. However, its electricity generation faces challenges due to unpredictable variations in wind speed (WS). Accurate predictions of these variations would allow mixed grids t
Externí odkaz:
https://doaj.org/article/8c32f944f5c749a08ec15209e19e009b
Publikováno v:
Sensors, Vol 24, Iss 16, p 5271 (2024)
Low-Earth-orbit (LEO) satellites are widely acknowledged as a promising infrastructure solution for global Internet of Things (IoT) services. However, the Doppler effect presents a significant challenge in the context of long-range (LoRa) modulation
Externí odkaz:
https://doaj.org/article/ca245f1aa640421d86bcc5131433f999
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Abstract Transfer of processed data and parameters to ungauged catchments from the most similar gauged counterpart is a common technique in water quality modelling. But catchment similarities for Dissolved Inorganic Nitrogen (DIN) are ill posed, whic
Externí odkaz:
https://doaj.org/article/1310c04cd1d74145b85c2378629460c9
Autor:
Ravinesh Chand, Thong Nguyen-Huy, Ravinesh C. Deo, Sujan Ghimire, Mumtaz Ali, Afshin Ghahramani
Publikováno v:
Water, Vol 16, Iss 11, p 1560 (2024)
Floods are a common natural disaster whose severity in terms of duration, water resource volume, peak, and accumulated rainfall-based damage is likely to differ significantly for different geographical regions. In this paper, we first propose a novel
Externí odkaz:
https://doaj.org/article/9ff7946e53b74686a324da104867ee75
Publikováno v:
Sensors, Vol 24, Iss 10, p 2993 (2024)
In trainable wireless communications systems, the use of deep learning for over-the-air training aims to address the discontinuity in backpropagation learning caused by the channel environment. The primary methods supporting this learning procedure e
Externí odkaz:
https://doaj.org/article/89adc25e713e4787916766f289595179
Autor:
Sujan Ghimire, Thong Nguyen-Huy, Mohanad S. AL-Musaylh, Ravinesh C. Deo, David Casillas-Pérez, Sancho Salcedo-Sanz
Publikováno v:
Energy and AI, Vol 14, Iss , Pp 100302- (2023)
This paper develops a trustworthy deep learning model that considers electricity demand (G) and local climate conditions. The model utilises Multi-Head Self-Attention Transformer (TNET) to capture critical information from G, to attain reliable predi
Externí odkaz:
https://doaj.org/article/566f7cf083d94a8f914114d375c1b8c2
Autor:
Mahesh Anil Inamdar, U. Raghavendra, Anjan Gudigar, Sarvesh Bhandary, Massimo Salvi, Ravinesh C. Deo, Prabal Datta Barua, Edward J. Ciaccio, Filippo Molinari, U. Rajendra Acharya
Publikováno v:
IEEE Access, Vol 11, Pp 108982-108994 (2023)
One of the foremost causes of death in males worldwide is prostate cancer. The identification, detection and diagnosis of the same is very crucial in saving lives. In this paper, we present an efficient gland segmentation model using digital histopat
Externí odkaz:
https://doaj.org/article/db916f7b00a94123938ed171bfc3d4d8
Autor:
S. Janifer Jabin Jui, Ravinesh C. Deo, Prabal Datta Barua, Aruna Devi, Jeffrey Soar, U. Rajendra Acharya
Publikováno v:
IEEE Access, Vol 11, Pp 71905-71924 (2023)
An automated Neurological Disorder detection system can be considered as a cost-effective and resource efficient tool for medical and healthcare applications. In automated Neurological Disorder detection, electroencephalograms are commonly used, but
Externí odkaz:
https://doaj.org/article/6d4078e37a454d10bad9afa7042e84da
Autor:
Sagthitharan Karalasingham, Ravinesh C. Deo, David Casillas-Perez, Nawin Raj, Sancho Salcedo-Sanz
Publikováno v:
IEEE Access, Vol 11, Pp 5558-5577 (2023)
For bifacial solar photovoltaic panels, surface albedo plays a crucial role in estimating the radiant energy. Since land surfaces are heterogeneous, the actual albedo of the surface where the solar photovoltaic panel is placed can vary widely and its
Externí odkaz:
https://doaj.org/article/d54d837f645341d8849b9cf404fe960f