Zobrazeno 1 - 10
of 15 955
pro vyhledávání: '"Arunkumar, AS"'
Achieving superior polymeric components through additive manufacturing (AM) relies on precise control of rheology. One key rheological property particularly relevant to AM is melt viscosity ($\eta$). Melt viscosity is influenced by polymer chemistry,
Externí odkaz:
http://arxiv.org/abs/2409.05240
User experience in data visualization is typically assessed through post-viewing self-reports, but these overlook the dynamic cognitive processes during interaction. This study explores the use of mind wandering -- a phenomenon where attention sponta
Externí odkaz:
http://arxiv.org/abs/2408.03576
Autor:
Martinez, Alejandra, Tovar, Laura, Amparan, Carla Irigoyen, Gonzalez, Karen, Edayath, Prajina, Pennathur, Priyadarshini, Pennathur, Arunkumar
Occupational exoskeletons promise to alleviate musculoskeletal injuries among industrial workers. Knowledge of the usability of the exoskeleton designs with respect to the user device interaction points, and the problems in design features, functions
Externí odkaz:
http://arxiv.org/abs/2408.02852
Let A be a graph type and B an equivalence relation on a group $G$. Let $[g]$ be the equivalence class of $g$ with respect to the equivalence relation B. The B superA graph of $G$ is an undirected graph whose vertex set is $G$ and two distinct vertic
Externí odkaz:
http://arxiv.org/abs/2408.00390
Autor:
Singh, Anuj Kumar, Bupathy, Arunkumar, Thongam, Jenis, Bianchi, Emanuela, Kahl, Gerhard, Banerjee, Varsha
We investigate the two-dimensional behavior of colloidal patchy ellipsoids specifically designed to follow a two-step assembly process from the monomer state to mesoscopic liquid-crystal phases, via the formation of so-called bent-core units at the i
Externí odkaz:
http://arxiv.org/abs/2407.21171
We introduce Diffusion Augmented Agents (DAAG), a novel framework that leverages large language models, vision language models, and diffusion models to improve sample efficiency and transfer learning in reinforcement learning for embodied agents. DAA
Externí odkaz:
http://arxiv.org/abs/2407.20798
Autor:
Martinez, Alejandra, Tovar, Laura, Amparan, Carla Irigoyen, Gonzalez, Karen, Edayath, Prajina, Pennathur, Priyadarshini, Pennathur, Arunkumar
Occupational exoskeletons promise to reduce the incidence of musculoskeletal injuries; however, we do not know if their designs allow universal use by all workers. We also do not know how easy the tasks of assembling, donning, doffing, and disassembl
Externí odkaz:
http://arxiv.org/abs/2405.20819
Autor:
Cubero-Cascante, José, Vaidyanathan, Arunkumar, Pelke, Rebecca, Pfeifer, Lorenzo, Leupers, Rainer, Joseph, Jan Moritz
The surge in AI usage demands innovative power reduction strategies. Novel Compute-in-Memory (CIM) architectures, leveraging advanced memory technologies, hold the potential for significantly lowering energy consumption by integrating storage with pa
Externí odkaz:
http://arxiv.org/abs/2405.04326
Autor:
Pennathur, Priyadarshini R., Boksa, Valerie, Pennathur, Arunkumar, Kusiak, Andrew, Livingston, Beth
The U.S. Bureau of Labor Statistics projects that by the year 2029, the United States will lose a million jobs in the office and administrative support occupations because technology, automation, and artificial intelligence (AI) have the potential to
Externí odkaz:
http://arxiv.org/abs/2405.03808
Autor:
Tirumala, Dhruva, Wulfmeier, Markus, Moran, Ben, Huang, Sandy, Humplik, Jan, Lever, Guy, Haarnoja, Tuomas, Hasenclever, Leonard, Byravan, Arunkumar, Batchelor, Nathan, Sreendra, Neil, Patel, Kushal, Gwira, Marlon, Nori, Francesco, Riedmiller, Martin, Heess, Nicolas
We apply multi-agent deep reinforcement learning (RL) to train end-to-end robot soccer policies with fully onboard computation and sensing via egocentric RGB vision. This setting reflects many challenges of real-world robotics, including active perce
Externí odkaz:
http://arxiv.org/abs/2405.02425