Improving the Hough Transform gathering process for affine transformations

In this paper, we show that significant wrong evidence can be generated when the Hough Transform (HT) is used to extract arbitrary shapes under rigid transformations. In order to reduce the amount of wrong evidence, we consider two types of constraints. First, we define constraints by considering invariant features. Secondly, we consider constraints defined via gradient direction information. Our results show that these constraints can significantly improve the gathering strategy, leading to identification of the correct parameters. The presented formulation is valid for any rigid transformations represented by affine mappings

Early Dust Formation and a Massive Progenitor for SN 2011ja?

SN 2011ja was a bright (I = -18.3) Type II supernova occurring in the nearby edge on spiral galaxy NGC 4945. Flat-topped and multi-peaked H-alpha and H-beta spectral emission lines appear between 64 - 84 days post-explosion, indicating interaction with a disc-like circumstellar medium inclined 30-45 degrees from edge-on. After day 84 an increase in the H- and K-band flux along with heavy attenuation of the red wing of the emission lines are strong indications of early dust formation, likely located in the cool dense shell created between the forward shock of the SN ejecta and the reverse shock created as the ejecta plows into the existing CSM. Radiative transfer modeling reveals both ~1.5 x 10^-4 Msun of pre-existing dust located ~ 10^16.7 cm away and ~ 5 x 10^-5 Msun of newly formed dust. Spectral observations after 1.5 years reveal the possibility that the fading SN is located within a young (3-6 Myr) massive stellar cluster, which when combined with tentative 56Ni mass estimates of 0.2 Msun may indicate a massive (> 25 Msun) progenitor for SN 2011ja.Comment: 13 pages, 8 figures, submitted to MNRAS awaiting final referee repor

Building the legal knowledge graph for smart compliance services in multilingual Europe

This position paper describes the vision, objectives and methodology of the LYNX project. The aim of Lynx is to create services to better manage compliance, based on a legal knowledge graph which integrates and links heterogeneous compliance data sources including legislation, case law and standards

Aggregation of Robust Regularization with Dynamic Filtration for Enhanced Radar Imaging

The paper suggest a novel approach to the problem of high-resolution array radar/SAR imaging as an ill-conditioned inverse spatial spectrum pattern (SSP) estimation problem with model uncertainties. We explain the theory recently developed by the authors of this presentation that addresses a new fused Bayesian-regularization paradigm for radar/SAR image formation/reconstruction. We show how this theory leads to new adaptive and robustified computational methods that enable one to derive efficient and consistent estimates of the SSP via unifying the Bayesian minimum risk estimation strategy with the ME randomized a priori image model and other projection-type regularization constraints imposed on the solution. We detail such fused Bayesian-regularization (FBR) paradigm and analyze some efficient numerical schemes for computational implementation of the relevant FBR-based methods. Also, we present the results of extended simulation study of the family of the radar image (RI) formation algorithms that employ the proposed FBR paradigm for high-resolution reconstruction of the SSP of the wavefield sources distributed in the remotely sensed environment. The last issue that we address as a perspective innovation is a paradigm of incorporating the concept of dynamic computing into the FBR-based technique to enable the latter to reconstruct the desired environmental remote sensing signatures (RSS) extracted from the enhanced imagery taking into account their dynamical behaviour. This provides a background for understanding the future trends in development of intelligent dynamic RS imaging and resource management techniques. The advantages of the well designed RI experiments (that employ the FBR-based methods) over the cases of poorer designed experiments (that employ the matched spatial filtering as well as the constrained least squares estimators) are investigated trough the simulation study.ITESO, A.C

Enriching Ontologies with Multilingual Information

This paper presents a novel approach to ontology localization with the objective of obtaining multilingual ontologies. Within the ontology development process, ontology localization has been defined as the activity of adapting an ontology to a concrete linguistic and cultural community. Depending on the ontology layers – terminological and/or conceptual – involved in the ontology localization activity, three heterogeneous multilingual ontology metamodels have been identified, of which we propose one of them. Our proposal consists in associating the ontology metamodel to an external model for representing and structuring lexical and terminological data in different natural languages. Our model has been called Linguistic Information Repository (LIR). The main advantages of this modelling modality rely on its flexibility by allowing (1) the enrichment of any ontology element with as much linguistic information as needed by the final application, and (2) the establishment of links among linguistic elements within and across different natural languages. The LIR model has been designed as an ontology of linguistic elements and is currently available in Web Ontology Language (OWL). The set of lexical and terminological data that it provides to ontology elements enables the localization of any ontology to a certain linguistic and cultural universe. The LIR has been evaluated against the multilingual requirements of the Food and Agriculture Organization of the United Nations in the framework of the NeOn project. It has proven to solve multilingual representation problems related to the establishment of well-defined relations among lexicalizations within and across languages, as well as conceptualization mismatches among different languages. Finally, we present an extension to the Ontology Metadata Vocabulary, the so-called LexOMV, with the aim of reporting on multilinguality at the ontology metadata level. By adding this contribution to the LIR model, we account for multilinguality at the three levels of an ontology: data level, knowledge representation level and metadata level

Remote Sensing Signature Fields Reconstruction via Robust Regularization of Bayesian Minimum Risk Technique

The robust numerical technique for high-resolution reconstructive imaging and scene analysis is developed as required for enhanced remote sensing with large scale sensor array radar/synthetic aperture radar. The problem- oriented modification of the previously proposed fused Bayesian-regularization (FBR) enhanced radar imaging method is performed to enable it to reconstruct remote sensing signatures (RSS) of interest alleviating problem ill- poseness due to system-level and model-level uncertainties. We report some simulation results of hydrological RSS reconstruction from enhanced real-world environmental images indicative of the efficiency of the developed method.Cinvesta