Zobrazeno 1 - 10
of 334
pro vyhledávání: '"A Takbiri"'
Autor:
Takbiri, Raziyeh, Daei, Sajad
This work is about recovering an analysis-sparse vector, i.e. sparse vector in some transform domain, from under-sampled measurements. In real-world applications, there often exist random analysis-sparse vectors whose distribution in the analysis dom
Externí odkaz:
http://arxiv.org/abs/2212.13582
Publikováno v:
صفه, Vol 34, Iss 1, Pp 69-89 (2024)
In research on vernacular architecture’s values, identifying architectural and construction patterns is increasingly attracting attention. It leads to documentation of the architectural heritage, which in turn helps in revitalisation and restoratio
Externí odkaz:
https://doaj.org/article/44929c48c1bb428cadccb57e0b1bf999
Publikováno v:
In Computers and Fluids 15 October 2023 264
User privacy can be compromised by matching user data traces to records of their previous behavior. The matching of the statistical characteristics of traces to prior user behavior has been widely studied. However, an adversary can also identify a us
Externí odkaz:
http://arxiv.org/abs/2108.12336
The Internet of Things (IoT) promises to improve user utility by tuning applications to user behavior, but revealing the characteristics of a user's behavior presents a significant privacy risk. Our previous work has established the challenging requi
Externí odkaz:
http://arxiv.org/abs/2007.06119
Akademický článek
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Publikováno v:
In Journal of Petroleum Science and Engineering April 2022 211
Autor:
Takbiri, Nazanin, Shejwalker, Virat, Houmansadr, Amir, Goeckel, Dennis L., Pishro-Nik, Hossein
The prevalence of mobile devices and Location-Based Services (LBS) necessitate the study of Location Privacy-Preserving Mechanisms (LPPM). However, LPPMs reduce the utility of LBS due to the noise they add to users' locations. Here, we consider the r
Externí odkaz:
http://arxiv.org/abs/1912.02209
Publikováno v:
57th Annual Allerton Conference on Communication, Control, and Computing 2019
The rapid growth of computer systems which generate graph data necessitates employing privacy-preserving mechanisms to protect users' identity. Since structure-based de-anonymization attacks can reveal users' identity's even when the graph is simply
Externí odkaz:
http://arxiv.org/abs/1910.08679
The objective for this work is to develop a data-driven proxy to high-fidelity numerical flow simulations using digital images. The proposed model can capture the flow field and permeability in a large verity of digital porous media based on solid gr
Externí odkaz:
http://arxiv.org/abs/1905.06327