Zobrazeno 1 - 10
of 8 967
pro vyhledávání: '"P. RaviKumar"'
Publikováno v:
Heliyon, Vol 10, Iss 15, Pp e35554- (2024)
Composite materials have become prominent in the aerospace, automotive, wind energy, biomedical, and machine tool industries. This has demanded the evaluation of the dynamic mechanical and tribological behaviour of composites to understand their perf
Externí odkaz:
https://doaj.org/article/cc014d2098d740e5bb61793c7494e8ab
Autor:
P. RaviKumar, G. Rajeshkumar, Jeganathan Prakash Maran, Naif Abdullah Al-Dhabi, Ponmurugan Karuppiah
Publikováno v:
Journal of Natural Fibers, Vol 19, Iss 13, Pp 6521-6533 (2022)
In this work, the influence of hybridizing jute and carbon fibers on the mechanical properties and water absorption behavior of polyester composites was evaluated. The composites were fabricated by using compression molding technique with discrete of
Externí odkaz:
https://doaj.org/article/35c0f058d6ae4541ad94c870c54b9720
Publikováno v:
Journal of Natural Fibers, Vol 19, Iss 8, Pp 2823-2835 (2022)
This research work focuses on the wear characteristics of hybrid composites prepared using Sisal fiber (SF) /Pineapple fiber (PF) and Pineapple fly ash (PA) in various wt.%. Linear reciprocating tribometer was used for determining the Specific Wear R
Externí odkaz:
https://doaj.org/article/52bf2520d7b44d74acbaaaab94972662
Publikováno v:
Journal of Natural Fibers, Vol 19, Iss 3, Pp 943-953 (2022)
In this work, the tribological performance of bidirectional jute/carbon fiber reinforced polyester composites was investigated using response surface methodology. The effects of three factors namely fiber weight fraction, load, and sliding velocity o
Externí odkaz:
https://doaj.org/article/d0391ee79e094f6da2a68f2005fe3ed3
Autor:
Dai, Shenghong, Sohn, Jy-yong, Chen, Yicong, Alam, S M Iftekharul, Balakrishnan, Ravikumar, Banerjee, Suman, Himayat, Nageen, Lee, Kangwook
Continual Federated Learning (CFL) is essential for enabling real-world applications where multiple decentralized clients adaptively learn from continuous data streams. A significant challenge in CFL is mitigating catastrophic forgetting, where model
Externí odkaz:
http://arxiv.org/abs/2409.01585
Computer vision models are increasingly capable of classifying ovarian epithelial cancer subtypes, but they differ from pathologists by processing small tissue patches at a single resolution. Multi-resolution graph models leverage the spatial relatio
Externí odkaz:
http://arxiv.org/abs/2407.18105
Autor:
Rao, Ravipudi Venkata, shah, Ravikumar
Two simple yet powerful optimization algorithms, named the Best-Mean-Random (BMR) and Best-Worst-Random (BWR) algorithms, are developed and presented in this paper to handle both constrained and unconstrained optimization problems. These algorithms a
Externí odkaz:
http://arxiv.org/abs/2407.11149
In this paper, we explore the properties of loss curvature with respect to input data in deep neural networks. Curvature of loss with respect to input (termed input loss curvature) is the trace of the Hessian of the loss with respect to the input. We
Externí odkaz:
http://arxiv.org/abs/2407.02747
Compressed video action recognition classifies video samples by leveraging the different modalities in compressed videos, namely motion vectors, residuals, and intra-frames. For this purpose, three neural networks are deployed, each dedicated to proc
Externí odkaz:
http://arxiv.org/abs/2407.02713
In this paper, we demonstrate a surprising capability of large language models (LLMs): given only input feature names and a description of a prediction task, they are capable of selecting the most predictive features, with performance rivaling the st
Externí odkaz:
http://arxiv.org/abs/2407.02694