Zobrazeno 1 - 10
of 33 742
pro vyhledávání: '"Hari, P"'
Autor:
Marcato, Agnese, Santos, Javier E., Pachalieva, Aleksandra, Gao, Kai, Hill, Ryley, Rougier, Esteban, Kang, Qinjun, Hyman, Jeffrey, Hunter, Abigail, Chua, Janel, Lawrence, Earl, Viswanathan, Hari, O'Malley, Daniel
Understanding material failure is critical for designing stronger and lighter structures by identifying weaknesses that could be mitigated. Existing full-physics numerical simulation techniques involve trade-offs between speed, accuracy, and the abil
Externí odkaz:
http://arxiv.org/abs/2411.08354
Autor:
Naik, Hemal, Yang, Junran, Das, Dipin, Crofoot, Margaret C, Rathore, Akanksha, Sridhar, Vivek Hari
Understanding animal behaviour is central to predicting, understanding, and mitigating impacts of natural and anthropogenic changes on animal populations and ecosystems. However, the challenges of acquiring and processing long-term, ecologically rele
Externí odkaz:
http://arxiv.org/abs/2411.06896
Autor:
Dirza, Risvan, Varadarajan, Hari Prasad, Aas, Vegard, Skogestad, Sigurd, Krishnamoorthy, Dinesh
This paper considers the problem of steady-state real-time optimization (RTO) of interconnected systems with a common constraint that couples several units, for example, a shared resource. Such problems are often studied under the context of distribu
Externí odkaz:
http://arxiv.org/abs/2411.04676
Autor:
Price, Brandon, Adleberg, Jason, Thomas, Kaesha, Zaiman, Zach, Mansuri, Aawez, Brown-Mulry, Beatrice, Okecheukwu, Chima, Gichoya, Judy, Trivedi, Hari
The Emory Knee Radiograph (MRKR) dataset is a large, demographically diverse collection of 503,261 knee radiographs from 83,011 patients, 40% of which are African American. This dataset provides imaging data in DICOM format along with detailed clinic
Externí odkaz:
http://arxiv.org/abs/2411.00866
The rapid growth of end-user AI applications, such as computer vision and generative AI, has led to immense data and processing demands often exceeding user devices' capabilities. Edge AI addresses this by offloading computation to the network edge,
Externí odkaz:
http://arxiv.org/abs/2411.00859
Autor:
Koshy, Vinay, Choi, Frederick, Chiang, Yi-Shyuan, Sundaram, Hari, Chandrasekharan, Eshwar, Karahalios, Karrie
Research into community content moderation often assumes that moderation teams govern with a single, unified voice. However, recent work has found that moderators disagree with one another at modest, but concerning rates. The problem is not the root
Externí odkaz:
http://arxiv.org/abs/2410.23448
The industrial landscape is rapidly evolving with the advent of 6G applications, which demand massive connectivity, high computational capacity, and ultra-low latency. These requirements present new challenges, which can no longer be efficiently addr
Externí odkaz:
http://arxiv.org/abs/2410.23086
Privacy is essential to fully enjoying the benefits of social media. While fear around privacy risks can sometimes motivate privacy management, the negative impact of such fear, particularly when it is perceived as unaddressable (i.e., "dysfunctional
Externí odkaz:
http://arxiv.org/abs/2410.16137
Reconfigurable holographic surfaces (RHS) are intrinsically amalgamated with reconfigurable intelligent surfaces (RIS), for beneficially ameliorating the signal propagation environment. This potent architecture significantly improves the system perfo
Externí odkaz:
http://arxiv.org/abs/2410.15995
Autor:
Hayagreevan, Hari, Khamaru, Souvik
This whitepaper highlights the dual importance of securing generative AI (genAI) platforms and leveraging genAI for cybersecurity. As genAI technologies proliferate, their misuse poses significant risks, including data breaches, model tampering, and
Externí odkaz:
http://arxiv.org/abs/2410.13899