8,518 research outputs found
Towards a novel wave-extraction method for numerical relativity
We present the recent results of a research project aimed at constructing a
robust wave extraction technique for numerical relativity. Our procedure makes
use of Weyl scalars to achieve wave extraction. It is well known that, with a
correct choice of null tetrad, Weyl scalars are directly associated to physical
properties of the space-time under analysis in some well understood way. In
particular it is possible to associate with the outgoing gravitational
radiation degrees of freedom, thus making it a promising tool for numerical
wave--extraction. The right choice of the tetrad is, however, the problem to be
addressed. We have made progress towards identifying a general procedure for
choosing this tetrad, by looking at transverse tetrads where .
As a direct application of these concepts, we present a numerical study of
the evolution of a non-linearly disturbed black hole described by the
Bondi--Sachs metric. This particular scenario allows us to compare the results
coming from Weyl scalars with the results coming from the news function which,
in this particular case, is directly associated with the radiative degrees of
freedom. We show that, if we did not take particular care in choosing the right
tetrad, we would end up with incorrect results.Comment: 6 pages, 1 figure, to appear in the Proceedings of the Albert
Einstein Century International Conference, Paris, France, 200
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Adaptive routing in active networks
New conceptual ideas on network architectures have been proposed in the recent past. Current store-andforward
routers are replaced by active intermediate systems,
which are able to perform computations on transient packets,
in a way that results very helpful for developing and
deploying new protocols in a short time. This paper introduces a new routing algorithm, based on a congestion
metric, and inspired by the behavior of ants in nature. The
use of the Active Networks paradigm associated with a cooperative learning environment produces a robust, decentralized algorithm capable of adapting quickly to changing conditions
GPU-powered Simulation Methodologies for Biological Systems
The study of biological systems witnessed a pervasive cross-fertilization
between experimental investigation and computational methods. This gave rise to
the development of new methodologies, able to tackle the complexity of
biological systems in a quantitative manner. Computer algorithms allow to
faithfully reproduce the dynamics of the corresponding biological system, and,
at the price of a large number of simulations, it is possible to extensively
investigate the system functioning across a wide spectrum of natural
conditions. To enable multiple analysis in parallel, using cheap, diffused and
highly efficient multi-core devices we developed GPU-powered simulation
algorithms for stochastic, deterministic and hybrid modeling approaches, so
that also users with no knowledge of GPUs hardware and programming can easily
access the computing power of graphics engines.Comment: In Proceedings Wivace 2013, arXiv:1309.712
SMCP: a Secure Mobile Crowdsensing Protocol for fog-based applications
The possibility of performing complex data analysis through sets of cooperating personal smart devices has recently encouraged the definition of new distributed computing paradigms. The general idea behind these approaches is to move early analysis towards the edge of the network, while relying on other intermediate (fog) or remote (cloud) devices for computations of increasing complexity. Unfortunately, because both of their distributed nature and high degree of modularity, edge-fog-cloud computing systems are particularly prone to cyber security attacks that can be performed against every element of the infrastructure. In order to address this issue, in this paper we present SMCP, a Secure Mobile Crowdsensing Protocol for fog-based applications that exploit lightweight encryption techniques that are particularly suited for low-power mobile edge devices. In order to assess the performance of the proposed security mechanisms, we consider as case study a distributed human activity recognition scenario in which machine learning algorithms are performed by users’ personal smart devices at the edge and fog layers. The functionalities provided by SMCP have been directly compared with two state-of-the-art security protocols. Results show that our approach allows to achieve a higher degree of security while maintaining a low computational cost
High Dynamic Optimized Carrier Loop Improvement for Tracking Doppler Rates
Mathematical analysis and optimization of a carrier tracking loop are presented. Due to fast changing of the carrier frequency in some satellite systems, such as Low Earth Orbit (LEO) or Global Positioning System (GPS), or some planes like Unmanned Aerial Vehicles (UAVs), high dynamic tracking loops play a very important role. In this paper an optimized tracking loop consisting of a third-order Phase Locked Loop (PLL) assisted by a second-order Frequency Locked Loop (FLL) for UAVs is proposed and discussed. Based on this structure an optimal loop has been designed. The main advantages of this approach are the reduction of the computation complexity and smaller phase error. The paper shows the simulation results, comparing them with a previous work
Your Friends Mention It. What About Visiting It? A Mobile Social-Based Sightseeing Application
In this short poster paper, we present an application for suggesting attractions to be visited by users, based on social signal processing technique
Hardware design of LIF with Latency neuron model with memristive STDP synapses
In this paper, the hardware implementation of a neuromorphic system is
presented. This system is composed of a Leaky Integrate-and-Fire with Latency
(LIFL) neuron and a Spike-Timing Dependent Plasticity (STDP) synapse. LIFL
neuron model allows to encode more information than the common
Integrate-and-Fire models, typically considered for neuromorphic
implementations. In our system LIFL neuron is implemented using CMOS circuits
while memristor is used for the implementation of the STDP synapse. A
description of the entire circuit is provided. Finally, the capabilities of the
proposed architecture have been evaluated by simulating a motif composed of
three neurons and two synapses. The simulation results confirm the validity of
the proposed system and its suitability for the design of more complex spiking
neural network
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