Semantic Object Parsing with Graph LSTM

By taking the semantic object parsing task as an exemplar application scenario, we propose the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of LSTM from sequential data or multi-dimensional data to general graph-structured data. Particularly, instead of evenly and fixedly dividing an image to pixels or patches in existing multi-dimensional LSTM structures (e.g., Row, Grid and Diagonal LSTMs), we take each arbitrary-shaped superpixel as a semantically consistent node, and adaptively construct an undirected graph for each image, where the spatial relations of the superpixels are naturally used as edges. Constructed on such an adaptive graph topology, the Graph LSTM is more naturally aligned with the visual patterns in the image (e.g., object boundaries or appearance similarities) and provides a more economical information propagation route. Furthermore, for each optimization step over Graph LSTM, we propose to use a confidence-driven scheme to update the hidden and memory states of nodes progressively till all nodes are updated. In addition, for each node, the forgets gates are adaptively learned to capture different degrees of semantic correlation with neighboring nodes. Comprehensive evaluations on four diverse semantic object parsing datasets well demonstrate the significant superiority of our Graph LSTM over other state-of-the-art solutions.Comment: 18 page

Lacunarity, predictability and predictive instability of the daily pluviometric regime in the Iberian Peninsula

The complexity of the daily pluviometric regime of the Iberian Peninsula is analysed from the point of view of its lacunarity, predictability and predictive instability. The database consists of daily pluviometric records obtained from 43 rain gauges in Spain and Portugal for the period 1950–1990. Five different series are generated for every rain gauge. The first series is constituted by the consecutive daily amounts. The other four consist of dry spell lengths with respect to daily amount thresholds of 0.1, 1.0, 5.0 and 10.0 mm/day. A dry spell length is defined as the number of consecutive days with rainfall amounts below one of these thresholds. The empirical lacunarity for every rain gauge is well reproduced by two power laws, the exponents varying notably from one gauge to another. The spatial distribution of the lacunarity is characterised by a north to south or southeast gradient, thus suggesting that this parameter can be a useful tool to distinguish between different pluviometric regimes. The predictability of the five series is quantified by means of the rescaled analysis and the interpretation of the Hurst exponent. Its patterns reveal that most part of the Iberian Peninsula shows signs of persistence for the daily rainfall and the dry spell series, although persistence is only clearly manifested in some small domains. The instability of possible predictive algorithms is analysed through the Lyapunov exponents. They are only computed for the series of daily amounts and for dry lengths respect to the threshold level of 0.1 mm/day due to the short number of dry spells for larger threshold levels. The series of daily amounts depict the highest instability along the Mediterranean coast. The series of dry spells show an increasing instability from NE to SW Spain, with a relevant nucleus of high Lyapunov values in the south-western Atlantic coast. As a summary, lacunarity and Hurst and Lyapunov exponents depict a relevant spatial variation, which is in agreement with well known patterns of the pluviometric regime, such as annual amount spatial distribution and return periods of dry spells

Predictability of the monthly North Atlantic Oscillation index based on fractal analyses and dynamic system theory

The predictability of the monthly North Atlantic Oscillation, NAO, index is analysed from the point of view of different fractal concepts and dynamic system theory such as lacunarity, rescaled analysis (Hurst exponent) and reconstruction theorem (embedding and correlation dimensions, Kolmogorov entropy and Lyapunov exponents). The main results point out evident signs of randomness and the necessity of stochastic models to represent time evolution of the NAO index. The results also show that the monthly NAO index behaves as a white-noise Gaussian process. The high minimum number of nonlinear equations needed to describe the physical process governing the NAO index fluctuations is evidence of its complexity. A notable predictive instability is indicated by the positive Lyapunov exponents. Besides corroborating the complex time behaviour of the NAO index, present results suggest that random Cantor sets would be an interesting tool to model lacunarity and time evolution of the NAO index

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Automatic chord-scale recognition using harmonic pitch class profiles

This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This study focuses on the application of different computational methods to carry out a”modal harmonic analysis” for Jazz improvisation performances by modeling the concept of chord-scales. The Chord-Scale Theory is a theoretical concept that explains the relationship between the harmonic context of a musical piece and possible scale types to be used for improvisation. This work proposes different computational approaches for the recognition of the chord-scale type in an improvised phrase given the harmonic context. We have curated a dataset to evaluate different chord-scale recognition approaches proposed in this study, where the dataset consists of around 40 minutes of improvised monophonic Jazz solo performances. The dataset is made publicly available and shared on freesound.org. To achieve the task of chord-scale type recognition, we propose one rule-based, one probabilistic and one supervised learning method. All proposed methods use Harmonic Pitch Class Profile (HPCP) features for classification. We observed an increase in the classification score when learned chord-scale models are filtered with predefined scale templates indicating that incorporating prior domain knowledge to learned models is beneficial. This study has its novelty in presenting a first computational analysis on chord-scales in the context of Jazz improvisation

Unexpected differences between thermal and photoinitiated cationic curing of a diglycidyl ether of bisphenol A modified with a multiarm star poly(styrene)-b-poly(ε-caprolactone) polymer

The effect of adding a multiarm star poly(styrene)-b-poly(ε-caprolactone) polymer on the cationic thermal and photoinitiated curing of diglycidyl ether of bisphenol A was studied. This star-polymer decelerated the thermal curing of diglycidyl ether of bisphenol A and modified the final structure of the epoxy matrix. The photocuring was influenced significantly by the addition of the multiarm star. When the proportion of this modifier added was 5%, much more time was necessary for complete photocuring (160 min at 40ºC). In the presence of 10% of modifier, the degree of photocuring reached was very low (0.196 at 120°C). A subsequent thermal post-curing was necessary to cure completely the system. During photocuring in presence of poly(styrene)-b-poly(ε-caprolactone), the formation of dormant species, which are reactivated when the temperature increases, takes places. The kinetics of the thermal curing and the photocuring was analyzed using an isoconversional method due to the complexity of the reactive process. Applying this method, it has been confirmed the dependence of activation energy on the degree of conversion. The fracture morphology analyzed by scanning electron microscopy exhibited a second phase originated during photocuring by the presence of the modifier

Submillimeter mapping and analysis of cold dust condensations in the Orion M42 star forming complex

We present here the continuum submillimeter maps of the molecular cloud around the M42 Nebula in the Orion region. These have been obtained in four wavelength bands (200, 260, 360 and 580 microns) with the ProNaOS two meter balloon-borne telescope. The area covered is 7 parsecs wide (50 arcmin at a distance of 470 pc) with a spatial resolution of about 0.4 parsec. Thanks to the high sensitivity to faint surface brightness gradients, we have found several cold condensations with temperatures ranging from 12 to 17 K, within 3 parsecs of the dense ridge. The statistical analysis of the temperature and spectral index spatial distribution shows an evidence of an inverse correlation between these two parameters. Being invisible in the IRAS 100 micron survey, some cold clouds are likely to be the seeds for future star formation activity going on in the complex. We estimate their masses and we show that two of them have masses higher than their Jeans masses, and may be gravitationally unstable.Comment: 4 figures, The Astrophysical Journal, Main Journal, in pres

Ophrys × castroviejoi (Orchidaceae), nuevo híbrido para España

Ophrys x castroviejoi is described and illustrated; it is a hybrid of O. scolopax and O. speculum, wich was obtained artificially in 1931 and named as O. x kelleriella, considered nomen nudum. It is offered its known distribution and current situation in Spain.Se describe e ilustra Ophrys × castroviejoi; híbrido de O. scolopax y O. speculum, obtenido de forma artificial en 1931 y nombrado O. × kelleriella, epíteto específico considerado nomen nudum. Se ofrece su distribución conocida y situación actual en España