Zobrazeno 1 - 10
of 10 534
pro vyhledávání: '"Pokhrel, A."'
Autor:
Pokhrel, Rishi, Dey, Tanay K.
In this work, we holographically study the hydrodynamical properties of strongly coupled $\mathcal{N} = 4$ SYM baryon rich thermal plasma with large number of flavour quarks. Specifically, we study the drag force acting on the moving heavy probe quar
Externí odkaz:
http://arxiv.org/abs/2410.14384
M2P2: A Multi-Modal Passive Perception Dataset for Off-Road Mobility in Extreme Low-Light Conditions
Autor:
Datar, Aniket, Pokhrel, Anuj, Nazeri, Mohammad, Rao, Madhan B., Pan, Chenhui, Zhang, Yufan, Harrison, Andre, Wigness, Maggie, Osteen, Philip R., Ye, Jinwei, Xiao, Xuesu
Long-duration, off-road, autonomous missions require robots to continuously perceive their surroundings regardless of the ambient lighting conditions. Most existing autonomy systems heavily rely on active sensing, e.g., LiDAR, RADAR, and Time-of-Flig
Externí odkaz:
http://arxiv.org/abs/2410.01105
Most traversability estimation techniques divide off-road terrain into traversable (e.g., pavement, gravel, and grass) and non-traversable (e.g., boulders, vegetation, and ditches) regions and then inform subsequent planners to produce trajectories o
Externí odkaz:
http://arxiv.org/abs/2409.17479
We present VertiEncoder, a self-supervised representation learning approach for robot mobility on vertically challenging terrain. Using the same pre-training process, VertiEncoder can handle four different downstream tasks, including forward kinodyna
Externí odkaz:
http://arxiv.org/abs/2409.11570
Autor:
Deur, A., Kuhn, S. E., Ripani, M., Zheng, X., Acar, A. G., Achenbach, P., Adhikari, K. P., Alvarado, J. S., Amaryan, M. J., Armstrong, W. R., Atac, H., Avakian, H., Baashen, L., Baltzell, N. A., Barion, L., Bashkanov, M., Battaglieri, M., Benkel, B., Benmokhtar, F., Bianconi, A., Biselli, A. S., Booth, W. A., ossu, F. B, Bosted, P., Boiarinov, S., Brinkmann, K. Th., Briscoe, W. J., Bueltmann, S., Burkert, V. D., Carman, D. S., Chatagnon, P., Chen, J. P., Ciullo, G., Cole, P. L., Contalbrigo, M., Crede, V., D'Angelo, A., Dashyan, N., De Vita, R., Defurne, M., Diehl, S., Djalali, C., Drozdov, V. A., Dupre, R., Egiyan, H., Alaoui, A. El, Fassi, L. El, Elouadrhiri, L., Eugenio, P., Faggert, J. C., Fegan, S., Fersch, R., Filippi, A., Gates, K., Gavalian, G., Gilfoyle, G. P., Gothe, R. W., Guo, L., Hakobyan, H., Hattawy, M., Hauenstein, F., Heddle, D., Hobart, A., Holtrop, M., Ireland, D. G., Isupov, E. L., Jiang, H., Jo, H. S., Joosten, S., Kang, H., Keith, C., Khandaker, M., Kim, W., Klein, F. J., Klimenko, V., Konczykowski, P., Kovacs, K., Kripko, A., Kubarovsky, V., Lanza, L., Lee, S., Lenisa, P., Li, X., Long, E., MacGregor, I. J. D., Marchand, D., Mascagna, V., Matamoros, D., McKinnon, B., Meekins, D., Migliorati, S., Mineeva, T., Mirazita, M., Mokeev, V., Munoz-Camacho, C., Nadel-Turonski, P., Nagorna, T., Neupane, K., Niccolai, S., Osipenko, M., Ostrovidov, A. I., Pandey, P., Paolone, M., Pappalardo, L. L., Paremuzyan, R., Pasyuk, E., Paul, S. J., Phelps, W., Phillips, S. K., Pierce, J., Pilleux, N., Pokhrel, M., Price, J. W., Prok, Y., Radic, A., Reed, T., Richards, J., Rosner, G., Rossi, P., Rusova, A. A., Salgado, C., Schmidt, A., Schumacher, R. A., Sharabian, Y. G., Shirokov, E. V., Shrestha, U., Sirca, S., Sparveris, N., Spreafico, M., Stepanyan, S., Strakovsky, I. I., Strauch, S., Sulkosky, V., Tan, J. A., Tenorio, M., Trotta, N., Tyson, R., Ungaro, M., Upton, D. W., Vallarino, S., Venturelli, L., Voskanyan, H., Voutier, E., Watts, D. P., Wei, X., Wood, M. H., Zachariou, N., Zhang, J., Zurek, M.
The spin structure functions of the proton and the deuteron were measured during the EG4 experiment at Jefferson Lab in 2006. Data were collected for longitudinally polarized electron scattering off longitudinally polarized NH$_3$ and ND$_3$ targets,
Externí odkaz:
http://arxiv.org/abs/2409.08365
Autor:
Dunham, Michael M., Stephens, Ian W., Myers, Philip C., Bourke, Tyler L., Arce, Héctor G., Pokhrel, Riwaj, Pineda, Jaime E., Vargas, Joseph
We use 1-4" (300-1200 au) resolution 12CO(2-1) data from the MASSES (Mass Assembly of Stellar Systems and their Evolution with the SMA) project to measure the projected opening angles of 46 protostellar outflows in the Perseus Molecular Cloud, 37 of
Externí odkaz:
http://arxiv.org/abs/2408.12788
Autor:
Pokhrel, Sandesh, Bhandari, Sanjay, Vazquez, Eduard, Lambrou, Tryphon, Gyawali, Prashnna, Bhattarai, Binod
Deep learning has significantly advanced the field of gastrointestinal vision, enhancing disease diagnosis capabilities. One major challenge in automating diagnosis within gastrointestinal settings is the detection of abnormal cases in endoscopic ima
Externí odkaz:
http://arxiv.org/abs/2407.14024
Publikováno v:
ACM SIGCOMM 2024 Sydney
This paper introduces a robust zero-trust architecture (ZTA) tailored for the decentralized system that empowers efficient remote work and collaboration within IoT networks. Using blockchain-based federated learning principles, our proposed framework
Externí odkaz:
http://arxiv.org/abs/2406.17172
Autor:
CLAS Collaboration, Hobart, A., Niccolai, S., Čuić, M., Kumerički, K., Achenbach, P., Alvarado, J. S., Armstrong, W. R., Atac, H., Avakian, H., Baashen, L., Baltzell, N. A., Barion, L., Bashkanov, M., Battaglieri, M., Benkel, B., Benmokhtar, F., Bianconi, A., Biselli, A. S., Boiarinov, S., Bondi, M., Booth, W. A., Bossù, F., Brinkmann, K. -Th., Briscoe, W. J., Brooks, W. K., Bueltmann, S., Burkert, V. D., Cao, T., Capobianco, R., Carman, D. S., Chatagnon, P., Ciullo, G., Cole, P. L., Contalbrigo, M., D'Angelo, A., Dashyan, N., De Vita, R., Defurne, M., Deur, A., Diehl, S., Dilks, C., Djalali, C., Dupre, R., Egiyan, H., Alaoui, A. El, Fassi, L. El, Elouadrhiri, L., Fegan, S., Filippi, A., Fogler, C., Gates, K., Gavalian, G., Gilfoyle, G. P., Glazier, D., Gothe, R. W., Gotra, Y., Guidal, M., Hafidi, K., Hakobyan, H., Hattawy, M., Hauenstein, F., Heddle, D., Holtrop, M., Ilieva, Y., Ireland, D. G., Isupov, E. L., Jiang, H., Jo, H. S., Joo, K., Kageya, T., Kim, A., Kim, W., Klimenko, V., Kripko, A., Kubarovsky, V., Kuhn, S. E., Lanza, L., Leali, M., Lee, S., Lenisa, P., Li, X., MacGregor, I. J. D., Marchand, D., Mascagna, V., Maynes, M., McKinnon, B., Meziani, Z. E., Migliorati, S., Milner, R. G., Mineeva, T., Mirazita, M., Mokeev, V., Camacho, C. Muñoz, Nadel-Turonski, P., Naidoo, P., Neupane, K., Niculescu, G., Osipenko, M., Pandey, P., Paolone, M., Pappalardo, L. L., Paremuzyan, R., Pasyuk, E., Paul, S. J., Phelps, W., Pilleux, N., Pokhrel, M., Rafael, S. Polcher, Poudel, J., Price, J. W., Prok, Y., Reed, T., Richards, J., Ripani, M., Ritman, J., Rossi, P., Golubenko, A. A., Salgado, C., Schadmand, S., Schmidt, A., Scott, Marshall B. C., Seroka, E. M., Sharabian, Y. G., Shirokov, E. V., Shrestha, U., Sparveris, N., Spreafico, M., Stepanyan, S., Strakovsky, I. I., Strauch, S., Tan, J. A., Trotta, N., Tyson, R., Ungaro, M., Vallarino, S., Venturelli, L., Tommaso, V., Voskanyan, H., Voutier, E., Watts, D. P, Wei, X., Williams, R., Wood, M. H., Xu, L., Zachariou, N., Zhang, J., Zhao, Z. W., Zurek, M.
Measuring Deeply Virtual Compton Scattering on the neutron is one of the necessary steps to understand the structure of the nucleon in terms of Generalized Parton Distributions (GPDs). Neutron targets play a complementary role to transversely polariz
Externí odkaz:
http://arxiv.org/abs/2406.15539
Autor:
Khanal, Sanjaya, Pokhrel, Shiva Raj
This research analyzes, models and develops a novel Digital Learning Environment (DLE) fortified by the innovative Private Learning Intelligence (PLI) framework. The proposed PLI framework leverages federated machine learning (FL) techniques to auton
Externí odkaz:
http://arxiv.org/abs/2405.10476