Zobrazeno 1 - 10
of 5 184
pro vyhledávání: '"KUMAR, PRASHANT"'
In many-body systems with U(1) global symmetry, the charge fluctuations in a subregion reveal important insights into entanglement and other global properties. For subregions with sharp corners, bipartite fluctuations have been predicted to exhibit a
Externí odkaz:
http://arxiv.org/abs/2408.16057
PhisNet is a cutting-edge web application designed to detect phishing websites using advanced machine learning. It aims to help individuals and organizations identify and prevent phishing attacks through a robust AI framework. PhisNet utilizes Python
Externí odkaz:
http://arxiv.org/abs/2407.04732
Autor:
Cao, Yupeng, Chen, Zhi, Pei, Qingyun, Dimino, Fabrizio, Ausiello, Lorenzo, Kumar, Prashant, Subbalakshmi, K. P., Ndiaye, Papa Momar
The integration of Artificial Intelligence (AI) techniques, particularly large language models (LLMs), in finance has garnered increasing academic attention. Despite progress, existing studies predominantly focus on tasks like financial text summariz
Externí odkaz:
http://arxiv.org/abs/2404.07452
In this study, the impact of turbulent diffusion on mixing of biochemical reaction models is explored by implementing and validating different models. An original codebase called CHAD (Coupled Hydrodynamics and Anaerobic Digestion) is extended to inc
Externí odkaz:
http://arxiv.org/abs/2403.04457
Sparse LiDAR point clouds cause severe loss of detail of static structures and reduce the density of static points available for navigation. Reduced density can be detrimental to navigation under several scenarios. We observe that despite high sparsi
Externí odkaz:
http://arxiv.org/abs/2312.00068
Standard methods for modeling anaerobic digestion processes assume homogeneous conditions inside the tank and thus suffer from the negligence of hydrodynamics. In this work, we present the software toolbox Coupled Hydrodynamics and Anaerobic Digestio
Externí odkaz:
http://arxiv.org/abs/2311.08927
Autor:
Kumar, Prashant, Sharma, Puneet
In this paper, we investigate the dynamical behavior of a two dimensional shift $X_G$ (generated by a two dimensional graph $G=(\mathcal{H},\mathcal{V})$) using the adjacency matrices of the generating graph $G$. In particular, we investigate propert
Externí odkaz:
http://arxiv.org/abs/2311.01123
Autor:
Kumar, Prashant
This dissertation investigates the fundamental behavior of multifunctional materials for energy conversion. Multifunctional materials exhibit two or more functional properties, such as electrical, thermal, magnetic etc. In this dissertation, the emph
Externí odkaz:
http://hdl.handle.net/10919/100111
Autor:
Kumar, Prashant, Vattikonda, Dheeraj, Nadkarni, Vedang Bhupesh Shenvi, Dong, Erqun, Sahoo, Sabyasachi
We investigate a new paradigm that uses differentiable SLAM architectures in a self-supervised manner to train end-to-end deep learning models in various LiDAR based applications. To the best of our knowledge there does not exist any work that levera
Externí odkaz:
http://arxiv.org/abs/2309.09206
A volume penalization-based immersed boundary technique is developed and thoroughly validated for fluid flow problems, specifically flow over bluff bodies. The proposed algorithm has been implemented in an Open Source Field Operation and Manipulation
Externí odkaz:
http://arxiv.org/abs/2309.08882