Zobrazeno 1 - 10
of 59 041
pro vyhledávání: '"Zaki, A."'
Sub-millisecond electric field sensing with an individual rare-earth doped ferroelectric nanocrystal
Autor:
Muraleedharan, Athulya, Zou, Jingye, Vallet, Maxime, Zaki, Abdelali, Bogicevic, Christine, Paillard, Charles, Perronet, Karen, Treussart, François
Understanding the dynamics of electrical signals within neuronal assemblies is crucial to unraveling complex brain function. Despite recent advances in employing optically active nanostructures in transmembrane potential sensing, there remains room f
Externí odkaz:
http://arxiv.org/abs/2407.02000
As of 2022, about 2.78 billion people in developing countries do not have access to the Internet. Lack of Internet access hinders economic growth, educational opportunities, and access to information and services. Recent initiatives to ``connect the
Externí odkaz:
http://arxiv.org/abs/2407.01738
We present the angular distribution of the four-fold $B\to\rho (\to\pi\pi)\mu^{+}\mu^{-}$ and $B\to a_{1}(\to\rho_{\parallel, \perp}\pi)\mu^{+}\mu^{-}$ decays both in the Standard Model and the family non-universal $Z^{\prime}$ model. At the quark le
Externí odkaz:
http://arxiv.org/abs/2407.00520
Autor:
Praquin, Matthieu, Lienhard, Vincent, Giraudo, Anthony, Vanselow, Aron, Leghtas, Zaki, Campagne-Ibarcq, Philippe
Light waves do not interact in vacuum, but may mix through various parametric processes when traveling in a nonlinear medium. In particular, a high-amplitude wave can be leveraged to frequency convert a low-amplitude signal, as long as the overall en
Externí odkaz:
http://arxiv.org/abs/2406.19751
Autor:
Yang, Chih-Hsuan, Feuer, Benjamin, Jubery, Zaki, Deng, Zi K., Nakkab, Andre, Hasan, Md Zahid, Chiranjeevi, Shivani, Marshall, Kelly, Baishnab, Nirmal, Singh, Asheesh K, Singh, Arti, Sarkar, Soumik, Merchant, Nirav, Hegde, Chinmay, Ganapathysubramanian, Baskar
We introduce Arboretum, the largest publicly accessible dataset designed to advance AI for biodiversity applications. This dataset, curated from the iNaturalist community science platform and vetted by domain experts to ensure accuracy, includes 134.
Externí odkaz:
http://arxiv.org/abs/2406.17720
Autor:
Saleem, Nasla, Balu, Aditya, Jubery, Talukder Zaki, Singh, Arti, Singh, Asheesh K., Sarkar, Soumik, Ganapathysubramanian, Baskar
Data augmentation is a powerful tool for improving deep learning-based image classifiers for plant stress identification and classification. However, selecting an effective set of augmentations from a large pool of candidates remains a key challenge,
Externí odkaz:
http://arxiv.org/abs/2406.13081
Large language models (LLMs) demonstrate impressive zero-shot and few-shot reasoning capabilities. Some propose that such capabilities can be improved through self-reflection, i.e., letting LLMs reflect on their own output to identify and correct mis
Externí odkaz:
http://arxiv.org/abs/2406.10400
Process mining extracts valuable insights from event data to help organizations improve their business processes, which is essential for their growth and success. By leveraging process mining techniques, organizations gain a comprehensive understandi
Externí odkaz:
http://arxiv.org/abs/2406.08530
Autor:
Zaki, Osama F.
In this paper I present a practical approach for coupling machine learning (ML) algorithms with knowledge bases (KB) ontology formalism. The lack of availability of prior knowledge in dynamic scenarios is without doubt a major barrier for scalable ma
Externí odkaz:
http://arxiv.org/abs/2407.02500
Task offloading in Vehicular Edge Computing (VEC) can advance cooperative perception (CP) to improve traffic awareness in Autonomous Vehicles. In this paper, we propose the Quality-aware Cooperative Perception Task Offloading (QCPTO) scheme. Q-CPTO i
Externí odkaz:
http://arxiv.org/abs/2405.20587