640 research outputs found
A Framework for Indoor Positioning Including Building Topology
In many application domains, position information is of fundamental importance. However, unlike the case of outdoor positioning, producing an accurate position estimation in the indoor setting turns out to be quite difficult. One of the most common localisation strategies makes use of fingerprinting. Research in this area has been faced with a number of challenges, leading to the proposal of a number of localisation algorithms, sampling strategies, benchmark datasets, and representations of building information. This proliferation made the modeling of the indoor positioning domain quite hard from both a theoretical and a practical point of view. In this paper, we propose a general and extensible framework, based on a relational database, that pairs fingerprints with building information. We show how the proposed system successfully deals with a number of problems that affect indoor positioning, supporting a large set of relevant tasks. The source code of the framework is available online, as well as an implementation of it, that provides an interactive open repository of indoor positioning data
Monitors that Learn from Failures: Pairing STL and Genetic Programming
In several domains, systems generate continuous streams of data during their execution, including meaningful telemetry information, that can be used to perform tasks like preemptive failure detection. Deep learning models have been exploited for these tasks with increasing success, but they hardly provide guarantees over their execution, a problem which is exacerbated by their lack of interpretability. In many critical contexts, formal methods, which ensure the correct behaviour of a system, are thus necessary. However, specifying in advance all the relevant properties and building a complete model of the system against which to check them is often out of reach in real-world scenarios. To overcome these limitations, we design a framework that resorts to monitoring, a lightweight runtime verification technique that does not require an explicit model specification, and pairs it with machine learning. Its goal is to automatically derive relevant properties, related to a bad behaviour of the considered system, encoded by means of formulas of Signal Temporal Logic (STL). Results based on experiments performed on well-known benchmark datasets show that the proposed framework is able to effectively anticipate critical system behaviours in an online setting, providing human-interpretable results
Lymnaea stagnalis as model for translational neuroscience research: from pond to bench
The purpose of this review is to illustrate how a reductionistic, but sophisticated, approach based on the use of a simple model system such as the pond snail Lymnaea stagnalis (L. stagnalis), might be useful to address fundamental questions in learning and memory. L. stagnalis, as a model, provides an interesting platform to investigate the dialog between the synapse and the nucleus and vice versa during memory and learning. More importantly, the "molecular actors" of the memory dialogue are well-conserved both across phylogenetic groups and learning paradigms, involving single- or multi-trials, aversion or reward, operant or classical conditioning. At the same time, this model could help to study how, where and when the memory dialog is impaired in stressful conditions and during aging and neurodegeneration in humans and thus offers new insights and targets in order to develop innovative therapies and technology for the treatment of a range of neurological and neurodegenerative disorders
Experimental observation of the Bogoliubov transformation for a Bose-Einstein condensed gas
Phonons with wavevector were optically imprinted into a
Bose-Einstein condensate. Their momentum distribution was analyzed using Bragg
spectroscopy with a high momentum transfer. The wavefunction of the phonons was
shown to be a superposition of +q and -q free particle momentum states, in
agreement with the Bogoliubov quasiparticle picture.Comment: 4 pages, 3 figures, please take postscript version for the best
version of Fig
The Excitation Spectrum of a Bose-Einstein Condensate
We report the first measurement of the excitation spectrum and the static
structure factor of a Bose-Einstein condensate. The excitation spectrum
displays a linear phonon regime, as well as a parabolic single-particle regime.
The linear regime provides an upper limit for the superfluid critical velocity,
by the Landau criterion. The excitation spectrum agrees well with the
Bogoliubov spectrum, in the local density approximation. This agreement
continues even for excitations close to the long-wavelength limit of the region
of applicability of the approximation. Feynman's relation between the
excitation spectrum and the static structure factor is verified, within an
overall constant
How to measure the Bogoliubov quasiparticle amplitudes in a trapped condensate
We propose an experiment, based on two consecutive Bragg pulses, to measure
the momentum distribution of quasiparticle excitations in a trapped Bose gas at
low temperature. With the first pulse one generates a bunch of excitations
carrying momentum , whose Doppler line is measured by the second pulse. We
show that this experiment can provide direct access to the amplitudes
and characterizing the Bogoliubov transformations from particles to
quasiparticles. We simulate the behavior of the nonuniform gas by numerically
solving the time dependent Gross-Pitaevskii equation.Comment: 12 pages, 4 figures include
Bogoliubov spectrum and Bragg spectroscopy of elongated Bose-Einstein condensates
The behavior of the momentum transferred to a trapped Bose-Einstein
condensate by a two-photon Bragg pulse reflects the structure of the underlying
Bogoliubov spectrum. In elongated condensates, axial phonons with different
number of radial nodes give rise to a multibranch spectrum which can be
resolved in Bragg spectroscopy, as shown by Steinhauer {\it et al.} [Phys. Rev.
Lett. {\bf 90}, 060404 (2003)]. Here we present a detailed theoretical analysis
of this process. We calculate the momentum transferred by numerically solving
the time dependent Gross-Pitaevskii equation. In the case of a cylindrical
condensate, we compare the results with those obtained by linearizing the
Gross-Pitaevskii equation and using a quasiparticle projection method. This
analysis shows how the axial-phonon branches affect the momentum transfer, in
agreement with our previous interpretation of the observed data. We also
discuss the applicability of this type of spectroscopy to typical available
condensates, as well as the role of nonlinear effects.Comment: 8 pages, 7 figures, minor changes, typos correcte
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