Neural networks and spectra feature selection for retrival of hot gases temperature profiles

Proceeding of: International Conference on Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, Vienna, Austria 28-30 Nov. 2005Neural networks appear to be a promising tool to solve the so-called inverse problems focused to obtain a retrieval of certain physical properties related to the radiative transference of energy. In this paper the capability of neural networks to retrieve the temperature profile in a combustion environment is proposed. Temperature profile retrieval will be obtained from the measurement of the spectral distribution of energy radiated by the hot gases (combustion products) at wavelengths corresponding to the infrared region. High spectral resolution is usually needed to gain a certain accuracy in the retrieval process. However, this great amount of information makes mandatory a reduction of the dimensionality of the problem. In this sense a careful selection of wavelengths in the spectrum must be performed. With this purpose principal component analysis technique is used to automatically determine those wavelengths in the spectrum that carry relevant information on temperature distribution. A multilayer perceptron will be trained with the different energies associated to the selected wavelengths. The results presented show that multilayer perceptron combined with principal component analysis is a suitable alternative in this field.Publicad

An infrared study of galactic OH/IR stars. I. An optical/near-IR atlas of the Arecibo sample

In this paper we present optical and near-infrared finding charts, accurate astrometry (~1") and single-epoch near-infrared photometry for 371 IRAS sources, 96% of those included in the so-called Arecibo sample of OH/IR stars (Eder et al. 1988; Lewis et al. 1990a; Chengalur et al. 1993). The main photometric properties of the stars in the sample are presented and discussed as well as the problems found during the process of identification of the optical/near-infrared counterparts. In addition, we also identify suitable reference stars in each field to be used for differential photometry purposes in the future. We find that 39% of the sources (144 in number) have no optical counterpart, 8 of them being invisible even at near infrared wavelengths. The relative distribution of sources with and without optical counterpart in the IRAS two-colour diagram and their characteristic near infrared colours are interpreted as the consequence of the increasing thickness of their circumstellar shells. Among the objects not detected at near infrared wavelengths four non-variable sources are proposed to be heavily obscured post-AGB stars which have just very recently left the AGB. Eight additional objects with unusually bright and/or blue near-infrared colours are identified as candidate post-AGB stars and/or proto-planetary nebulae.Comment: 28 pages, 9 figures, for associated finding charts see: http://www.edpsciences.org/articles/aa/full/2005/08/aa1709/FINDING_CHARTS/are cibo_index.htm

A Coreference Service for Enterprise Application Integration using Linked Data

The use of semantic and Linked Data technologies for Enterprise Application Integration (EAI) is increasing in recent years. Linked Data and Semantic Web technologies such as the Resource Description Framework (RDF) data model provide several key advantages over the current de-facto Web Service and XML based integration approaches. The flexibility provided by representing the data in a more versatile RDF model using ontologies enables avoiding complex schema transformations and makes data more accessible using Web standards, preventing the formation of data silos. These three benefits represent an edge for Linked Data-based EAI. However, work still has to be performed so that these technologies can cope with the particularities of the EAI scenarios in different terms, such as data control, ownership, consistency, or accuracy. The first part of the paper provides an introduction to Enterprise Application Integration using Linked Data and the requirements imposed by EAI to Linked Data technologies focusing on one of the problems that arise in this scenario, the coreference problem, and presents a coreference service that supports the use of Linked Data in EAI systems. The proposed solution introduces the use of a context that aggregates a set of related identities and mappings from the identities to different resources that reside in distinct applications and provide different views or aspects of the same entity. A detailed architecture of the Coreference Service is presented explaining how it can be used to manage the contexts, identities, resources, and applications which they relate to. The paper shows how the proposed service can be utilized in an EAI scenario using an example involving a dashboard that integrates data from different systems and the proposed workflow for registering and resolving identities. As most enterprise applications are driven by business processes and involve legacy data, the proposed approach can be easily incorporated into enterprise applications

An Ontology Model to Support the Automated Evaluation of Software

Even though previous research has tried to model Software Engineering knowledge, focusing either on the entire discipline or on parts of it, we lack an integrated conceptual model for representing software evaluations, and we also lack the information related to them that supports their definition and enables their automation and reproducibility. This paper presents an extensible ontology model for representing software evaluations and evaluation campaigns, i.e., worldwide activities where a group of tools is evaluated according to a certain evaluation specification using common test data. During the development of the ontologies, we have reused current standards and models and have linked these ontologies with some renowned ones

Carbon and oxygen abundances from recombination lines in low-metallicity star-forming galaxies. Implications for chemical evolution

We present deep echelle spectrophotometry of the brightest emission-line knots of the star-forming galaxies He 2-10, Mkn 1271, NGC 3125, NGC 5408, POX 4, SDSS J1253-0312, Tol 1457-262, Tol 1924-416 and the HII region Hubble V in the Local Group dwarf irregular galaxy NGC 6822. The data have been taken with the Very Large Telescope Ultraviolet-Visual Echelle Spectrograph in the 3100-10420 {\AA} range. We determine electron densities and temperatures of the ionized gas from several emission-line intensity ratios for all the objects. We derive the ionic abundances of C$^{2+}$ and/or O$^{2+}$ from faint pure recombination lines (RLs) in several of the objects, permitting to derive their C/H and C/O ratios. We have explored the chemical evolution at low metallicities analysing the C/O vs. O/H, C/O vs. N/O and C/N vs. O/H relations for Galactic and extragalactic HII regions and comparing with results for halo stars and DLAs. We find that HII regions in star-forming dwarf galaxies occupy a different locus in the C/O vs. O/H diagram than those belonging to the inner discs of spiral galaxies, indicating their different chemical evolution histories, and that the bulk of C in the most metal-poor extragalactic HII regions should have the same origin than in halo stars. The comparison between the C/O ratios in HII regions and in stars of the Galactic thick and thin discs seems to give arguments to support the merging scenario for the origin of the Galactic thick disc. Finally, we find an apparent coupling between C and N enrichment at the usual metallicities determined for HII regions and that this coupling breaks in very low-metallicity objects.Comment: 27 pages, 12 figures, Accepted for publication in Monthly Notices of the Royal Astronomical Societ

Ontology Access in Grid Environments with WS-DAIOnt and the RDF(S) Realization

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Executing Evaluations over Semantic Technologies using the SEALS Platform

The SEALS European project aims to develop an infrastructure for the evaluation of semantic technologies. This paper presents in detail the approach followed to automate the execution of these evaluations in the infrastructure. To materialize this approach, we have dened the entities managed by the infrastructure and their life cycle, the process followed to execute evaluations, the management of the computing resources that form the execution infrastructure, and how tools can be integrated with the infrastructure

Towards an Infrastructure for the Evaluation of Semantic Technologies

This paper presents and discusses the current development status of the SEALS Platform, a lasting reference infrastructure for semantic technology evaluation. It describes the different entities managed by the platform and the ontology-based model that has been defined to represent them; it also provides an overview of the platform architecture. In addition, it presents the different challenges faced during the development of the SEALS Platform and a use scenario of the platform that supports the execution of evaluation campaigns over semantic technologies