Zobrazeno 1 - 10
of 22 365
pro vyhledávání: '"Savino, A."'
Autor:
Fu, Sal Wanying, Weisz, Daniel R., Starkenburg, Else, Martin, Nicolas, Collins, Michelle L. M., Savino, Alessandro, Boylan-Kolchin, Michael, Côté, Patrick, Dolphin, Andrew E., Longeard, Nicolas, Mateo, Mario L., Mercado, Francisco J., Sandford, Nathan R., Skillman, Evan D.
We present $\sim300$ stellar metallicity measurements in two faint M31 dwarf galaxies, Andromeda XVI ($M_V = -7.5$) and Andromeda XXVIII ($M_V = -8.8$) derived using metallicity-sensitive Calcium H & K narrow-band Hubble Space Telescope imaging. Thes
Externí odkaz:
http://arxiv.org/abs/2407.04698
The automotive industry has evolved significantly since the introduction of the Ford Model T in 1908. Today's vehicles are not merely mechanical constructs; they are integral components of a complex digital ecosystem, equipped with advanced connectiv
Externí odkaz:
http://arxiv.org/abs/2407.00483
This work evaluates how well hardware-based approaches detect stack buffer overflow (SBO) attacks in RISC-V systems. We conducted simulations on the PULP platform and examined micro-architecture events using semi-supervised anomaly detection techniqu
Externí odkaz:
http://arxiv.org/abs/2406.10282
Autor:
Kirdi, Sadek Misto, Scarano, Nicola, Oberti, Franco, Mannella, Luca, Di Carlo, Stefano, Savino, Alessandro
Modern vehicles are increasingly vulnerable to attacks that exploit network infrastructures, particularly the Controller Area Network (CAN) networks. To effectively counter such threats using contemporary tools like Intrusion Detection Systems (IDSs)
Externí odkaz:
http://arxiv.org/abs/2406.07125
Autor:
Eltaras, Tamer Ahmed, Malluhi, Qutaibah, Savino, Alessandro, Di Carlo, Stefano, Qayyum, Adnan, Qadir, Junaid
In the effort to learn from extensive collections of distributed data, federated learning has emerged as a promising approach for preserving privacy by using a gradient-sharing mechanism instead of exchanging raw data. However, recent studies show th
Externí odkaz:
http://arxiv.org/abs/2406.04227
Autor:
Savino, A., Gennaro, M., Dolphin, A. E., Weisz, D. R., Correnti, M., Anderson, J., Beaton, R., Boyer, M. L., Cohen, R. E., Cole, A. A., Durbin, M. J., Garling, C. T., Geha, M. C., Gilbert, K. M., Kalirai, J., Kallivayalil, N., McQuinn, K. B. W., Newman, M. J. B., Richstein, H., Skillman, E. D., Warfield, J. T., Williams, B. F.
We empirically assess estimates from v3.0 of the JWST NIRCam Exposure Time Calculator (ETC) using observations of resolved stars in Local Group targets taken as part of the Resolved Stellar Populations Early Release Science (ERS) Program. For bright
Externí odkaz:
http://arxiv.org/abs/2405.17547
Social networking services (SNS) have become integral to modern life to create and maintain meaningful relationships. Nevertheless, their historic growth of features has led to labyrinthine user interfaces (UIs) that often result in frustration among
Externí odkaz:
http://arxiv.org/abs/2405.07305
Autor:
Dequino, Alberto, Carpegna, Alessio, Nadalini, Davide, Savino, Alessandro, Benini, Luca, Di Carlo, Stefano, Conti, Francesco
Rehearsal-based Continual Learning (CL) has been intensely investigated in Deep Neural Networks (DNNs). However, its application in Spiking Neural Networks (SNNs) has not been explored in depth. In this paper we introduce the first memory-efficient i
Externí odkaz:
http://arxiv.org/abs/2407.03111
Autor:
El-Badry, Kareem, Rix, Hans-Walter, Latham, David W., Shahaf, Sahar, Mazeh, Tsevi, Bieryla, Allyson, Buchhave, Lars A., Andrae, René, Yamaguchi, Natsuko, Isaacson, Howard, Howard, Andrew W., Savino, Alessandro, Ilyin, Ilya V.
We report discovery and spectroscopic follow-up of 21 astrometric binaries containing solar-type stars and dark companions with masses near 1.4 $M_{\odot}$. The simplest interpretation is that the companions are dormant neutron stars (NSs), though ul
Externí odkaz:
http://arxiv.org/abs/2405.00089
One of today's main concerns is to bring Artificial Intelligence power to embedded systems for edge applications. The hardware resources and power consumption required by state-of-the-art models are incompatible with the constrained environments obse
Externí odkaz:
http://arxiv.org/abs/2404.03714