Towards a Semantic Gas Source Localization under Uncertainty

Towards a Semantic Gas Source Localization under Uncertainty.Communications in Computer and Information Science book series (CCIS, volume 855), doi:10.1007/978-3-319-91479-4_42This work addresses the problem of efficiently and coherently locating a gas source in a domestic environment with a mobile robot, meaning efficiently the coverage of the shortest distance as possible and coherently the consideration of different gas sources explaining the gas presence. The main contribution is the exploitation, for the first time, of semantic relationships between the gases detected and the objects present in the environment to face this challenging issue. Our proposal also takes into account both the uncertainty inherent in the gas classification and object recognition processes. These uncertainties are combined through a probabilistic Bayesian framework to provide a priority-ordered list of (previously observed) objects to check. Moreover the proximity of the different candidates to the current robot location is also considered by a cost function, which output is used for planning the robot inspection path. We have conducted an initial demonstration of the suitability of our gas source localization approach by simulating this task within domestic environments for a variable number of objects, and comparing it with an greedy approach.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Strong pinning in the hole-doped pnictide superconductor La0.34_{0.34}Na0.66_{0.66}Fe2_2As2_2

We present magnetization studies as a function of time, temperature and magnetic field for $H$ $\parallel$ c-axis, in a hole-doped pnictide superconductor, La$_{0.34}$Na$_{0.66}$Fe$_2$As$_2$, with, $T_c$ $\approx$ 27 K. The obtained vortex phase-diagram shows that the magnetic irreversibility line is very close to the mean-field superconducting transition line, similar to the low $T_c$ superconductors, evidencing a strong pinning behavior. The irreversibility line does not follow a power law behavior with ($T_c$-$T$), however, it is well described using an expression developed in the literature considering the effect of disorder in the system. The critical current density estimated using the Bean's critical-state model is found to be of the order of 10$^5$ A/cm$^2$ below 12 K in the limit of zero magnetic field. A plot of the normalized pinning force density as a function of the reduced magnetic field at different temperatures shows a good scaling and the analysis suggests that the vortex pinning is due to normal point like pinning centers. The temperature dependence of the critical current density suggests that the pinning due to the variation in charge carrier mean free path alone is not sufficient to explain the experimental data. Magnetic relaxation rate as a function of temperature and magnetic field is also studied.Comment: 19 pages, 6 Figures, Accepted for Publication in the "Journal of Applied Physics 2019

Time-Optimal Adiabatic-Like Expansion of Bose-Einstein Condensates

In this paper we study the fast adiabatic-like expansion of a one-dimensional Bose-Einstein condensate (BEC) confined in a harmonic potential, using the theory of time-optimal control. We find that under reasonable assumptions suggested by the experimental setup, the minimum-time expansion occurs when the frequency of the potential changes in a bang-bang form between the permitted values. We calculate the necessary expansion time and show that it scales logarithmically with large values of the expansion factor. This work is expected to find applications in areas where the efficient manipulations of BEC is of utmost importance. As an example we present the field of atom interferometry with BEC, where the wavelike properties of atoms are used to perform interference experiments that measure with unprecedented precision small shifts induced by phenomena like rotation, acceleration, and gravity gradients.Comment: Submitted to 51st IEEE Conference on Decision and Contro

Nonrelativistic hydrogen type stability problems on nonparabolic 3-manifolds

We extend classical Euclidean stability theorems corresponding to the nonrelativistic Hamiltonians of ions with one electron to the setting of non parabolic Riemannian 3-manifolds.Comment: 20 pages; to appear in Annales Henri Poincar

A Relation-Centric Query Engine for the Foundational Model of Anatomy

The Foundational Model of Anatomy (FMA), a detailed representation of the structural organization of the human body, was constructed to support the development of software applications requiring knowledge of anatomy. The FMA's focus on the structural relationships between anatomical entities distinguishes it from other current anatomical knowledge sources. We developed Emily, a query engine for the FMA, to enable users to explore the richness and depth of these relationships. Preliminary analysis suggests that Emily is capable of correctly processing real world anatomical queries provided they have been translated into a constrained form suitable for processing by the query engine

Anti-phase synchronization of phase-reduced oscillators using open-loop control

In this letter, we present an elegant method to build and maintain an anti-phase configuration of two nonlinear oscillators with different natural frequencies and dynamics described by the sinusoidal phase-reduced model. The anti-phase synchronization is achieved using a common input that couples the oscillators and consists of a sequence of square pulses of appropriate amplitude and duration. This example provides a proof of principle that open-loop control can be used to create desired synchronization patterns for nonlinear oscillators, when feedback is expensive or impossible to obtain

Star Architecture as Socio-Material Assemblage

Taking inspiration from new materialism and assemblage, the chapter deals with star architects and iconic buildings as socio-material network effects that do not pre-exist action, but are enacted in practice, in the materiality of design crafting and city building. Star architects are here conceptualized as part of broader assemblages of actors and practices ‘making star architecture’ a reality, and the buildings they design are considered not just as unique and iconic objects, but dis-articulated as complex crafts mobilizing skills, technologies, materials, and forms of knowledge not necessarily ascribable to architecture. Overcoming narrow criticism focusing on the symbolic order of icons as unique creations and alienated repetitions of capitalist development, the chapter’s main aim is to widen the scope of critique by bridging culture and economy, symbolism and practicality, making star architecture available to a broad, fragmented arena of (potential) critics, unevenly equipped with critical tools and differentiated experiences

Realistic Standard Model Fermion Mass Relations in Generalized Minimal Supergravity (GmSUGRA)

Grand Unified Theories (GUTs) usually predict wrong Standard Model (SM) fermion mass relation m_e/m_{\mu} = m_d/m_s toward low energies. To solve this problem, we consider the Generalized Minimal Supergravity (GmSUGRA) models, which are GUTs with gravity mediated supersymmetry breaking and higher dimensional operators. Introducing non-renormalizable terms in the super- and K\"ahler potentials, we can obtain the correct SM fermion mass relations in the SU(5) model with GUT Higgs fields in the {\bf 24} and {\bf 75} representations, and in the SO(10) model. In the latter case the gauge symmetry is broken down to SU(3)_C X SU(2)_L X SU(2)_R X U(1)_{B-L}, to flipped SU(5)X U(1)_X, or to SU(3)_C X SU(2)_L X U(1)_1 X U(1)_2. Especially, for the first time we generate the realistic SM fermion mass relation in GUTs by considering the high-dimensional operators in the K\"ahler potential.Comment: JHEP style, 29 pages, no figure,references adde

Empirical modeling of the stellar spectrum of galaxies

An empirical method of modeling the stellar spectrum of galaxies is proposed, based on two successive applications of Principal Component Analysis (PCA). PCA is first applied to the newly available stellar library STELIB, supplemented by the J, H and K$_{s}$ magnitudes taken mainly from the 2 Micron All Sky Survey (2MASS). Next the resultant eigen-spectra are used to fit the observed spectra of a sample of 1016 galaxies selected from the Sloan Digital Sky Survey Data Release One (SDSS DR1). PCA is again applied, to the fitted spectra to construct the eigen-spectra of galaxies with zero velocity dispersion. The first 9 galactic eigen-spectra so obtained are then used to model the stellar spectrum of the galaxies in SDSS DR1, and synchronously to estimate the stellar velocity dispersion, the spectral type, the near-infrared SED, and the average reddening. Extensive tests show that the spectra of different type galaxies can be modeled quite accurately using these eigen-spectra. The method can yield stellar velocity dispersion with accuracies better than 10%, for the spectra of typical S/N ratios in SDSS DR1.Comment: 34 pages with 18 figures, submitted to A

Semantic Context Forests for Learning-Based Knee Cartilage Segmentation in 3D MR Images

The automatic segmentation of human knee cartilage from 3D MR images is a useful yet challenging task due to the thin sheet structure of the cartilage with diffuse boundaries and inhomogeneous intensities. In this paper, we present an iterative multi-class learning method to segment the femoral, tibial and patellar cartilage simultaneously, which effectively exploits the spatial contextual constraints between bone and cartilage, and also between different cartilages. First, based on the fact that the cartilage grows in only certain area of the corresponding bone surface, we extract the distance features of not only to the surface of the bone, but more informatively, to the densely registered anatomical landmarks on the bone surface. Second, we introduce a set of iterative discriminative classifiers that at each iteration, probability comparison features are constructed from the class confidence maps derived by previously learned classifiers. These features automatically embed the semantic context information between different cartilages of interest. Validated on a total of 176 volumes from the Osteoarthritis Initiative (OAI) dataset, the proposed approach demonstrates high robustness and accuracy of segmentation in comparison with existing state-of-the-art MR cartilage segmentation methods.Comment: MICCAI 2013: Workshop on Medical Computer Visio