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pro vyhledávání: '"Gill, P. Singh"'
Considering radio-interferometric observations, we present a fast and efficient estimator to compute the binned angular bispectrum (ABS) from gridded visibility data. The estimator makes use of Fast Fourier Transform (FFT) techniques to compute the b
Externí odkaz:
http://arxiv.org/abs/2412.02246
The following contribution introduces a concept that employs Large Language Models (LLMs) and a chatbot interface to enhance SPARQL query generation for ontologies, thereby facilitating intuitive access to formalized knowledge. Utilizing natural lang
Externí odkaz:
http://arxiv.org/abs/2408.00800
Autor:
Golec, Muhammed, Gill, Sukhpal Singh
Publikováno v:
Published in Proceedings of the 21st International Conference on Smart Business Technologies, ICSBT 2024, Dijon, France, July 9 11, 2024
The Internet and computer commercialization have transformed the computing systems area over the past sixty years, affecting society. Computer systems have evolved to meet diverse social needs thanks to technological advances. The Internet of Things
Externí odkaz:
http://arxiv.org/abs/2407.12558
Autor:
Wen, Linfeng, Xu, Minxian, Gill, Sukhpal Singh, Hilman, Muhammad Hafizhuddin, Srirama, Satish Narayana, Ye, Kejiang, Xu, Chengzhong
Publikováno v:
ACM Transactions on Autonomous and Adaptive Systems, 2024
Microservice architecture has transformed traditional monolithic applications into lightweight components. Scaling these lightweight microservices is more efficient than scaling servers. However, scaling microservices still faces the challenges resul
Externí odkaz:
http://arxiv.org/abs/2407.10173
In the following contribution, a method is introduced that integrates domain expert-centric ontology design with the Cross-Industry Standard Process for Data Mining (CRISP-DM). This approach aims to efficiently build an application-specific ontology
Externí odkaz:
http://arxiv.org/abs/2407.06930
Autor:
Gill, Sukhpal Singh, Golec, Muhammed, Hu, Jianmin, Xu, Minxian, Du, Junhui, Wu, Huaming, Walia, Guneet Kaur, Murugesan, Subramaniam Subramanian, Ali, Babar, Kumar, Mohit, Ye, Kejiang, Verma, Prabal, Kumar, Surendra, Cuadrado, Felix, Uhlig, Steve
Publikováno v:
Springer Cluster Computing, Volume 28, article number 18, pages 11953 - 11981, (2025)
Edge Artificial Intelligence (AI) incorporates a network of interconnected systems and devices that receive, cache, process, and analyze data in close communication with the location where the data is captured with AI technology. Recent advancements
Externí odkaz:
http://arxiv.org/abs/2407.04053
The anisotropy of the redshift space bispectrum depends upon the orientation of the triangles formed by three $\vec{k}$ modes with respect to the line of sight. For a triangle of fixed size ($k_1$) and shape ($\mu,t$), this orientation dependence can
Externí odkaz:
http://arxiv.org/abs/2405.14513
Autor:
Golec, Muhammed, Hatay, Emir Sahin, Golec, Mustafa, Uyar, Murat, Golec, Merve, Gill, Sukhpal Singh
Publikováno v:
Journal of Economy and Technology, Elsevier, Volume 2 , November 2024, Pages 190-199
Quantum computing (QC) is a new paradigm that will revolutionize various areas of computing, especially cloud computing. QC, still in its infancy, is a costly technology capable of operating in highly isolated environments due to its rapid response t
Externí odkaz:
http://arxiv.org/abs/2404.19612
Autor:
Gill, Sukhpal Singh, Cetinkaya, Oktay, Marrone, Stefano, Claudino, Daniel, Haunschild, David, Schlote, Leon, Wu, Huaming, Ottaviani, Carlo, Liu, Xiaoyuan, Machupalli, Sree Pragna, Kaur, Kamalpreet, Arora, Priyansh, Liu, Ji, Farouk, Ahmed, Song, Houbing Herbert, Uhlig, Steve, Ramamohanarao, Kotagiri
The recent development of quantum computing, which uses entanglement, superposition, and other quantum fundamental concepts, can provide substantial processing advantages over traditional computing. These quantum features help solve many complex prob
Externí odkaz:
http://arxiv.org/abs/2403.02240
Autor:
Nandi, Anindita, Gill, Sukhdeep Singh, Sarkar, Debanjan, Shaw, Abinash Kumar, Pandey, Biswajit, Bharadwaj, Somnath
We have measured the spherically averaged bispectrum of the SDSS DR17 main galaxy sample, considering a volume-limited $[273\, \rm Mpc]^3$ data cube with mean galaxy number density $1.76 \times 10^{-3} \, {\rm Mpc}^{-3}$ and median redshift $0.093$.
Externí odkaz:
http://arxiv.org/abs/2401.15958