Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Seshathiri Dhanasekaran"'
Autor:
Prabhu Paramasivam, Mansoor Alruqi, Seshathiri Dhanasekaran, Fahad Albalawi, H.A. Hanafi, Waleed Saad
Publikováno v:
Case Studies in Thermal Engineering, Vol 61, Iss , Pp 105116- (2024)
In this study, waste biomass-derived biogas was employed as the main fuel while the biodiesel-diesel blend was used as pilot fuel. This paper describes the development of a Decision Tree and Response Surface methodology-based statistical framework fo
Externí odkaz:
https://doaj.org/article/19bd95ebb0fa42fa98d87fc55412f96d
Autor:
Pranjal Sarmah, Dipankar Das, Madhurjya Saikia, Virendra Kumar, Surendra Kumar Yadav, Prabhu Paramasivam, Seshathiri Dhanasekaran
Publikováno v:
ACS Omega, Vol 8, Iss 50, Pp 47897-47904 (2023)
Externí odkaz:
https://doaj.org/article/4f890114a6b04189ab9b3a15e22d9c12
Autor:
Natrayan Lakshmaiya, Raviteja Surakasi, V. Swamy Nadh, Chidurala Srinivas, Seniappan Kaliappan, Velmurugan Ganesan, Prabhu Paramasivam, Seshathiri Dhanasekaran
Publikováno v:
ACS Omega, Vol 8, Iss 42, Pp 39680-39689 (2023)
Externí odkaz:
https://doaj.org/article/a9bad57d8159468c9e825ee52e846469
Autor:
Abirami Annadurai, Vidhushavarshini Sureshkumar, Dhayanithi Jaganathan, Seshathiri Dhanasekaran
Publikováno v:
Fractal and Fractional, Vol 8, Iss 9, p 511 (2024)
In medical imaging, noise can significantly obscure critical details, complicating diagnosis and treatment. Traditional denoising techniques often struggle to maintain a balance between noise reduction and detail preservation. To address this challen
Externí odkaz:
https://doaj.org/article/92b3f7666f6d431ca08fed013eccef34
Publikováno v:
Computation, Vol 12, Iss 3, p 48 (2024)
In the field of heat and mass transfer applications, non-Newtonian fluids are potentially considered to play a very important role. This study examines the magnetohydrodynamic (MHD) bioconvective Eyring–Powell fluid flow on a permeable cone and pla
Externí odkaz:
https://doaj.org/article/5d7812fd8ae240b1af653e1021e30466
Publikováno v:
Frontiers in Materials, Vol 10 (2023)
This research aims to investigate the mechanical performance of the different weight proportions of nano-TiO2 combined with Kevlar fiber-based hybrid composites under cryogenic conditions. The following parameters were thus considered: (i) Kevlar fib
Externí odkaz:
https://doaj.org/article/afc4833d26244c2fa540a213c5b51b25
Autor:
Natrayan L, Raviteja Surakasi, Prabhu Paramasivam, Seshathiri Dhanasekaran, Kaliappan S., Pravin P. Patil
Publikováno v:
Frontiers in Materials, Vol 10 (2023)
Composite materials are increasingly replacing synthetic fiber combinations in various applications. However, certain extreme environments on Earth and in space require structures to operate under low temperatures, specifically cryogenic conditions,
Externí odkaz:
https://doaj.org/article/be8c253224924d26b926c52122072a33
Autor:
Anant Prakash Agrawal, Virendra Kumar, Jitendra Kumar, Prabhu Paramasivam, Seshathiri Dhanasekaran, Lalta Prasad
Publikováno v:
Heliyon, Vol 9, Iss 6, Pp e16531- (2023)
Additive manufacturing technology and its benefits have a significant impact on different industrial applications. The 3D printing technologies help manufacture lightweight intricate geometrical designs with enhanced strengths. The present study inve
Externí odkaz:
https://doaj.org/article/981dfc6ad1e84022a73c62a77e5bfae2
Autor:
Dhayanithi Jaganathan, Sathiyabhama Balasubramaniam, Vidhushavarshini Sureshkumar, Seshathiri Dhanasekaran
Publikováno v:
Diagnostics, Vol 14, Iss 4, p 422 (2024)
Breast cancer remains a significant global public health concern, emphasizing the critical role of accurate histopathological analysis in diagnosis and treatment planning. In recent years, the advent of deep learning techniques has showcased notable
Externí odkaz:
https://doaj.org/article/47edbc2446e44b4980bca7b9993bb035
Autor:
T.K. Revathi, Sathiyabhama Balasubramaniam, Vidhushavarshini Sureshkumar, Seshathiri Dhanasekaran
Publikováno v:
Diagnostics, Vol 14, Iss 3, p 239 (2024)
Cardiovascular diseases, prevalent as leading health concerns, demand early diagnosis for effective risk prevention. Despite numerous diagnostic models, challenges persist in network configuration and performance degradation, impacting model accuracy
Externí odkaz:
https://doaj.org/article/5082d967f4f9437a9f68bdf9899f3e9f