Zobrazeno 1 - 10
of 241
pro vyhledávání: '"Gupta Amarnath"'
Autor:
Dwivedi Shatkratu, Gupta Amarnath, Das Abhijit, Dubey Shubhra, Kumar Rohit Bhupendra, Dwivedi Sudeept
Publikováno v:
Global Journal of Medicine and Public Health, Vol 11, Iss 5 (2024)
Background Considering college students' food consumption habits and the importance of consumers' comprehension and awareness of food labels in healthy food choices, our study primarily aims to assess the knowledge, attitude and practices (KAP) about
Externí odkaz:
https://doaj.org/article/0c4496ba1c4f47abbfa3ec25ab603bf5
Autor:
Richard Kwasi Bannor, Gupta Amarnath Krishna Kumar, Helena Oppong-Kyeremeh, Camillus Abawiera Wongnaa
Publikováno v:
Rice Science, Vol 27, Iss 1, Pp 56-66 (2020)
The factors affecting the adoption of modern varieties (MVs) of rice and impact on poverty in Odisha, India were discussed. A total of 363 households from Cuttack and Sambalpur districts of Odisha via multistage sampling technique participated in the
Externí odkaz:
https://doaj.org/article/04e31fda93894d91995a6e216b2eea37
Bridging eResearch Infrastructure and Experimental Materials Science Process in the Quantum Data Hub
Autor:
Gupta, Amarnath, Purawat, Shweta, Dasgupta, Subhasis, Karmakar, Pratyush, Chi, Elaine, Altintas, Ilkay
Experimental materials science is experiencing significant growth due to automated experimentation and AI techniques. Integrated autonomous platforms are emerging, combining generative models, robotics, simulations, and automated systems for material
Externí odkaz:
http://arxiv.org/abs/2405.19706
Data science applications increasingly rely on heterogeneous data sources and analytics. This has led to growing interest in polystore systems, especially analytical polystores. In this work, we focus on a class of emerging multi-data model analytics
Externí odkaz:
http://arxiv.org/abs/2305.14391
Temporal information extraction plays a critical role in natural language understanding. Previous systems have incorporated advanced neural language models and have successfully enhanced the accuracy of temporal information extraction tasks. However,
Externí odkaz:
http://arxiv.org/abs/2201.06125
Modern data science applications increasingly use heterogeneous data sources and analytics. This has led to growing interest in polystore systems, especially analytical polystores. In this work, we focus on emerging multi-data model analytics workloa
Externí odkaz:
http://arxiv.org/abs/2112.00833
Knowledge analysis is an important application of knowledge graphs. In this paper, we present a complex knowledge analysis problem that discovers the gaps in the technology areas of interest to an organization. Our knowledge graph is developed on a h
Externí odkaz:
http://arxiv.org/abs/2109.05142
Hashtag annotation for microblog posts has been recently formulated as a sequence generation problem to handle emerging hashtags that are unseen in the training set. The state-of-the-art method leverages conversations initiated by posts to enrich con
Externí odkaz:
http://arxiv.org/abs/2104.08723
Autor:
Dasgupta, Subhasis, Gupta, Amarnath
Social media data are often modeled as heterogeneous graphs with multiple types of nodes and edges. We present a discovery algorithm that first chooses a "background" graph based on a user's analytical interest and then automatically discovers subgra
Externí odkaz:
http://arxiv.org/abs/2102.09120