Zobrazeno 1 - 10
of 55 108
pro vyhledávání: '"Shalini, A"'
Autor:
Inguva, Pavan K., Mukherjee, Saikat, Walker, Pierre J., Kanso, Mona A., Wang, Jie, Wu, Yanchen, Tenberg, Vico, Santra, Srimanta, Singh, Shalini, Kim, Shin Hyuk, Trout, Bernhardt L., Bazant, Martin Z., Myerson, Allan S., Braatz, Richard D.
Nucleic acids such as mRNA have emerged as a promising therapeutic modality with the capability of addressing a wide range of diseases. Lipid nanoparticles (LNPs) as a delivery platform for nucleic acids were used in the COVID-19 vaccines and have re
Externí odkaz:
http://arxiv.org/abs/2408.08577
The Virtual Experimental Research Assistant (VERA) is an inquiry-based learning environment that empowers a learner to build conceptual models of complex ecological systems and experiment with agent-based simulations of the models. This study investi
Externí odkaz:
http://arxiv.org/abs/2407.18335
Autor:
Tripathi, Shalini, Kundu, Chinmoy, Yadav, Animesh, Bansal, Ankur, Claussen, Holger, Ho, Lester
In this paper, we address the problem of joint allocation of transmit and jamming power at the source and destination, respectively, to enhance the long-term cumulative secrecy performance of an energy-harvesting wireless communication system until i
Externí odkaz:
http://arxiv.org/abs/2407.17435
Autor:
Lynch, Jason, Kumar, Pawan, Chen, Chen, Trainor, Nicholas, Kumari, Shalini, Peng, Tzu-Yu, Chen, Cindy Yueli, Lu, Yu-Jung, Redwing, Joan, Jariwala, Deep
Active metamaterials promise to enable arbitrary, temporal control over the propagation of wavefronts of light for applications such as beam steering, optical communication modulators, and holograms. This has been done in the past using patterned sil
Externí odkaz:
http://arxiv.org/abs/2407.09328
Autor:
Lin, Da, Lynch, Jason, Wang, Sudong, Hu, Zekun, Rai, Rajeev Kumar, Zhang, Huairuo, Chen, Chen, Kumari, Shalini, Stach, Eric, Davydov, Albert V., Redwing, Joan M., Jariwala, Deep
Broadband absorption in the visible spectrum is essential in optoelectronic applications that involve power conversion such as photovoltaics and photocatalysis. Most ultrathin broadband absorbers use parasitic plasmonic structures that maximize absor
Externí odkaz:
http://arxiv.org/abs/2407.05170
Autor:
Wang, Shengze, Li, Xueting, Liu, Chao, Chan, Matthew, Stengel, Michael, Spjut, Josef, Fuchs, Henry, De Mello, Shalini, Nagano, Koki
Recent breakthroughs in single-image 3D portrait reconstruction have enabled telepresence systems to stream 3D portrait videos from a single camera in real-time, potentially democratizing telepresence. However, per-frame 3D reconstruction exhibits te
Externí odkaz:
http://arxiv.org/abs/2405.00794
Table detection within document images is a crucial task in document processing, involving the identification and localization of tables. Recent strides in deep learning have substantially improved the accuracy of this task, but it still heavily reli
Externí odkaz:
http://arxiv.org/abs/2405.00187
Autor:
Liebel, Grischa, Klünder, Jil, Hebig, Regina, Lazik, Christopher, Nunes, Inês, Graßl, Isabella, Steghöfer, Jan-Philipp, Exelmans, Joeri, Oertel, Julian, Marquardt, Kai, Juhnke, Katharina, Schneider, Kurt, Gren, Lucas, Happe, Lucia, Herrmann, Marc, Wyrich, Marvin, Tichy, Matthias, Goulão, Miguel, Wohlrab, Rebekka, Kalantari, Reyhaneh, Heinrich, Robert, Greiner, Sandra, Rukmono, Satrio Adi, Chakraborty, Shalini, Abrahão, Silvia, Amaral, Vasco
Purpose: Software modelling and Model-Driven Engineering (MDE) is traditionally studied from a technical perspective. However, one of the core motivations behind the use of software models is inherently human-centred. Models aim to enable practitione
Externí odkaz:
http://arxiv.org/abs/2404.18682
Autor:
Saini, Shalini, Saxena, Nitesh
FemTech, a rising trend in mobile apps, empowers women to digitally manage their health and family planning. However, privacy and security vulnerabilities in period-tracking and fertility-monitoring apps present significant risks, such as unintended
Externí odkaz:
http://arxiv.org/abs/2404.05876
Autor:
Jain, Yash, Chan, David, Dheram, Pranav, Khare, Aparna, Shonibare, Olabanji, Ravichandran, Venkatesh, Ghosh, Shalini
Recent advances in machine learning have demonstrated that multi-modal pre-training can improve automatic speech recognition (ASR) performance compared to randomly initialized models, even when models are fine-tuned on uni-modal tasks. Existing multi
Externí odkaz:
http://arxiv.org/abs/2403.19822