Zobrazeno 1 - 10
of 37 064
pro vyhledávání: '"AN. Tehrani"'
Autor:
Tehrani, Masoud Jamshidiyan, Kim, Jinhan, Foulefack, Rosmael Zidane Lekeufack, Marchetto, Alessandro, Tonella, Paolo
The advent of deep learning and its astonishing performance in perception tasks, such as object recognition and classification, has enabled its usage in complex systems, including autonomous vehicles. On the other hand, deep learning models are susce
Externí odkaz:
http://arxiv.org/abs/2412.04510
Assessing Vulnerability in Smart Contracts: The Role of Code Complexity Metrics in Security Analysis
Codes with specific characteristics are more exposed to security vulnerabilities. Studies have revealed that codes that do not adhere to best practices are more challenging to verify and maintain, increasing the likelihood of unnoticed or unintention
Externí odkaz:
http://arxiv.org/abs/2411.17343
Certification Authority Authentication (CAA) is a safeguard against illegitimate certificate issuance. We show how shortcomings in CAA concepts and operational aspects undermine its effectiveness in preventing certificate misissuance. Our discussion
Externí odkaz:
http://arxiv.org/abs/2411.07702
Nonlinear dynamics of fluid conveying pipe, rotating with constant velocity about its longitudinal axis is analyzed. Considering boundary conditions and internal damping, the nonlinear equation of motion is derived, and it is discretized via the Gale
Externí odkaz:
http://arxiv.org/abs/2410.23237
Autor:
Saeizadeh, Ali, Tehrani-Moayyed, Miead, Villa, Davide, Beattie Jr., J. Gordon, Wong, Ian C., Johari, Pedram, Anderson, Eric W., Basagni, Stefano, Melodia, Tommaso
Accurate channel modeling in real-time faces remarkable challenge due to the complexities of traditional methods such as ray tracing and field measurements. AI-based techniques have emerged to address these limitations, offering rapid, precise predic
Externí odkaz:
http://arxiv.org/abs/2410.22437
Autor:
Di Giovanni, Matteo, Leaci, Paola, Astone, Pia, Pra, Stefano Dal, D'Atonio, Sabrina, D'Onofrio, Luca, Frasca, Sergio, Muciaccia, Federico, Palomba, Cristiano, Pierini, Lorenzo, Tehrani, Francesco Safai
We present an improved method for vetoing candidates of continuous gravitational-wave sources during all-sky searches utilizing the Frequency Hough pipeline. This approach leverages linear correlations between source parameters induced by the Earth D
Externí odkaz:
http://arxiv.org/abs/2410.19420
Autor:
Sultanow, Eldar, Selimllari, Fation, Dutta, Siddhant, Reese, Barry D., Tehrani, Madjid, Buchanan, William J
Data poisoning attacks on machine learning models aim to manipulate the data used for model training such that the trained model behaves in the attacker's favor. In classical models such as deep neural networks, large chains of dot products do indeed
Externí odkaz:
http://arxiv.org/abs/2410.05145
This paper discusses the use case of energy saving and traffic steering in O-RAN, the mechanism of multi-vendor interoperability to make it work and depict its test methodology.
Comment: 6 pages, 8 figures
Comment: 6 pages, 8 figures
Externí odkaz:
http://arxiv.org/abs/2409.19807
Autor:
Lavrentiadis, Grigorios, Seylabi, Elnaz, Xia, Feiruo, Tehrani, Hesam, Asimaki, Domniki, McCallen, David
This study presents the development of two new sedimentary velocity models for the San Francisco Bay Area (SFBA) to improve the near-surface representation of shear-wave velocity ($V_S$) for large-scale, broadband numerical simulations, with the ulti
Externí odkaz:
http://arxiv.org/abs/2409.18856
Homodyned K-distribution (HK-distribution) parameter estimation in quantitative ultrasound (QUS) has been recently addressed using Bayesian Neural Networks (BNNs). BNNs have been shown to significantly reduce computational time in speckle statistics-
Externí odkaz:
http://arxiv.org/abs/2409.11583