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pro vyhledávání: '"Barati A"'
L2AI: lightweight three-factor authentication and authorization in IOMT blockchain-based environment
Medical Internet of Things (IoMT) is the next frontier in the digital revolution and is utilized in healthcare. In this context, IoT enables individuals to remotely manage their essential activities with minimal interaction. However, the limitations
Externí odkaz:
http://arxiv.org/abs/2407.12187
Autor:
Graves, Reid, Farimani, Amir Barati
The design of aerodynamic shapes, such as airfoils, has traditionally required significant computational resources and relied on predefined design parameters, which limit the potential for novel shape synthesis. In this work, we introduce a data-driv
Externí odkaz:
http://arxiv.org/abs/2408.15898
Industry 4.0 has revolutionized manufacturing by driving digitalization and shifting the paradigm toward additive manufacturing (AM). Fused Deposition Modeling (FDM), a key AM technology, enables the creation of highly customized, cost-effective prod
Externí odkaz:
http://arxiv.org/abs/2408.14307
Autor:
Shu, Dule, Farimani, Amir Barati
The success of diffusion probabilistic models in generative tasks, such as text-to-image generation, has motivated the exploration of their application to regression problems commonly encountered in scientific computing and various other domains. In
Externí odkaz:
http://arxiv.org/abs/2408.04718
There has recently been increasing attention towards developing foundational neural Partial Differential Equation (PDE) solvers and neural operators through large-scale pretraining. However, unlike vision and language models that make use of abundant
Externí odkaz:
http://arxiv.org/abs/2407.17616
We use semiclassical Boltzmann transport theory to analytically study the electronic contribution to the linear thermoelectric response of anisotropic two-dimensional materials subjected to a perpendicular magnetic field. Conventional methods, such a
Externí odkaz:
http://arxiv.org/abs/2407.15074
Peptides are essential in biological processes and therapeutics. In this study, we introduce Multi-Peptide, an innovative approach that combines transformer-based language models with Graph Neural Networks (GNNs) to predict peptide properties. We com
Externí odkaz:
http://arxiv.org/abs/2407.03380
Tactile perception is a critical component of solving real-world manipulation tasks, but tactile sensors for manipulation have barriers to use such as fragility and cost. In this work, we engage a robust, low-cost tactile sensor, BeadSight, as an alt
Externí odkaz:
http://arxiv.org/abs/2406.15639
Autor:
Zhao, Meng, Barati, Masoud
Alternative current optimal power flow (ACOPF) problems have been studied for over fifty years, and yet the development of an optimal algorithm to solve them remains a hot and challenging topic for researchers because of their nonlinear and nonconvex
Externí odkaz:
http://arxiv.org/abs/2406.10428
Autor:
Barati, Masoud
This paper presents a new method for enhancing Alternating Current Power Flow (ACPF) analysis. The method integrates the Newton-Raphson (NR) method with Enhanced-Gradient Descent (GD) and computational graphs. The integration of renewable energy sour
Externí odkaz:
http://arxiv.org/abs/2406.10390