9,979 research outputs found
Fleet Prognosis with Physics-informed Recurrent Neural Networks
Services and warranties of large fleets of engineering assets is a very
profitable business. The success of companies in that area is often related to
predictive maintenance driven by advanced analytics. Therefore, accurate
modeling, as a way to understand how the complex interactions between operating
conditions and component capability define useful life, is key for services
profitability. Unfortunately, building prognosis models for large fleets is a
daunting task as factors such as duty cycle variation, harsh environments,
inadequate maintenance, and problems with mass production can lead to large
discrepancies between designed and observed useful lives. This paper introduces
a novel physics-informed neural network approach to prognosis by extending
recurrent neural networks to cumulative damage models. We propose a new
recurrent neural network cell designed to merge physics-informed and
data-driven layers. With that, engineers and scientists have the chance to use
physics-informed layers to model parts that are well understood (e.g., fatigue
crack growth) and use data-driven layers to model parts that are poorly
characterized (e.g., internal loads). A simple numerical experiment is used to
present the main features of the proposed physics-informed recurrent neural
network for damage accumulation. The test problem consist of predicting fatigue
crack length for a synthetic fleet of airplanes subject to different mission
mixes. The model is trained using full observation inputs (far-field loads) and
very limited observation of outputs (crack length at inspection for only a
portion of the fleet). The results demonstrate that our proposed hybrid
physics-informed recurrent neural network is able to accurately model fatigue
crack growth even when the observed distribution of crack length does not match
with the (unobservable) fleet distribution.Comment: Data and codes (including our implementation for both the multi-layer
perceptron, the stress intensity and Paris law layers, the cumulative damage
cell, as well as python driver scripts) used in this manuscript are publicly
available on GitHub at https://github.com/PML-UCF/pinn. The data and code are
released under the MIT Licens
A coherent state approach to effective potential in noncommutative D=(2+1) models
In this work we study the effective potential in noncommutative
three-dimensional models where the noncommutativity is introduced through the
coherent state approach. We discuss some important characteristics that seem to
be typical to this approach, specially the behavior of the quantum corrections
in the small noncommutativity limit.Comment: revtex4, 8 pages, 2 figures
A Fault Analytic Method against HB+
The search for lightweight authentication protocols suitable for low-cost
RFID tags constitutes an active and challenging research area. In this context,
a family of protocols based on the LPN problem has been proposed: the so-called
HB-family. Despite the rich literature regarding the cryptanalysis of these
protocols, there are no published results about the impact of fault analysis
over them. The purpose of this paper is to fill this gap by presenting a fault
analytic method against a prominent member of the HB-family: HB+ protocol. We
demonstrate that the fault analysis model can lead to a flexible and effective
attack against HB-like protocols, posing a serious threat over them
Commitment and Oblivious Transfer in the Bounded Storage Model with Errors
The bounded storage model restricts the memory of an adversary in a
cryptographic protocol, rather than restricting its computational power, making
information theoretically secure protocols feasible. We present the first
protocols for commitment and oblivious transfer in the bounded storage model
with errors, i.e., the model where the public random sources available to the
two parties are not exactly the same, but instead are only required to have a
small Hamming distance between themselves. Commitment and oblivious transfer
protocols were known previously only for the error-free variant of the bounded
storage model, which is harder to realize
On the Commitment Capacity of Unfair Noisy Channels
Noisy channels are a valuable resource from a cryptographic point of view.
They can be used for exchanging secret-keys as well as realizing other
cryptographic primitives such as commitment and oblivious transfer. To be
really useful, noisy channels have to be consider in the scenario where a
cheating party has some degree of control over the channel characteristics.
Damg\r{a}rd et al. (EUROCRYPT 1999) proposed a more realistic model where such
level of control is permitted to an adversary, the so called unfair noisy
channels, and proved that they can be used to obtain commitment and oblivious
transfer protocols. Given that noisy channels are a precious resource for
cryptographic purposes, one important question is determining the optimal rate
in which they can be used. The commitment capacity has already been determined
for the cases of discrete memoryless channels and Gaussian channels. In this
work we address the problem of determining the commitment capacity of unfair
noisy channels. We compute a single-letter characterization of the commitment
capacity of unfair noisy channels. In the case where an adversary has no
control over the channel (the fair case) our capacity reduces to the well-known
capacity of a discrete memoryless binary symmetric channel
Two novel evolutionary formulations of the graph coloring problem
We introduce two novel evolutionary formulations of the problem of coloring
the nodes of a graph. The first formulation is based on the relationship that
exists between a graph's chromatic number and its acyclic orientations. It
views such orientations as individuals and evolves them with the aid of
evolutionary operators that are very heavily based on the structure of the
graph and its acyclic orientations. The second formulation, unlike the first
one, does not tackle one graph at a time, but rather aims at evolving a
`program' to color all graphs belonging to a class whose members all have the
same number of nodes and other common attributes. The heuristics that result
from these formulations have been tested on some of the Second DIMACS
Implementation Challenge benchmark graphs, and have been found to be
competitive when compared to the several other heuristics that have also been
tested on those graphs.Comment: To appear in Journal of Combinatorial Optimizatio
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