The Gaia-ESO Survey: Pre-Main Sequence Stars in the Young Open Cluster NGC 3293

The young open cluster NGC3293 is included in the observing program of the Gaia-ESO survey (GES). The radial velocity values provided have been used to assign cluster membership probabilities by means of a single-variable parametric analysis. These membership probabilities are compared to the results of the photometric membership assignment of NGC3293, based on UBV RI photometry. The agreement of the photometric and kinematic member samples amounts to 65%, and could increase to 70% as suggested by the analysis of the differences between both samples. A number of photometric PMS candidate members of spectral type F are found, which are confirmed by the results from VPHAS photometry and SED fitting for the stars in common with VPHAS and GES data sets. Excesses at mid- and near-infrared wavelengths, and signs of Hα emission, are investigated for them. Marginal presence of Hα emission or infilling is detected for the candidate members. Several of them exhibit moderate signs of U excess and weak excesses at mid-IR wavelengths. We suggest that these features originate from accretion disks in their last stages of evolution

The Gaia-ESO Survey: Pre-main-sequence stars in the young open cluster NGC 3293

© 2016 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.The young open cluster NGC3293 is included in the observing program of the Gaia-ESO survey (GES). The radial velocity values provided have been used to assign cluster membership probabilities by means of a single-variable parametric analysis. These membership probabilities are compared to the results of the photometric membership assignment of NGC3293, based on UBVRI photometry. The agreement of the photometric and kinematic member samples amounts to 65 per cent, and could increase to 70 per cent as suggested by the analysis of the differences between both samples. A number of photometric PMS candidate members of spectral type F are found, which are confirmed by the results from VPHAS photometry and SED fitting for the stars in common with VPHAS and GES data sets. Excesses at mid- and near-infrared wavelengths, and signs of Hα emission, are investigated for them. Marginal presence of Hα emission or infilling is detected for the candidate members. Several of them exhibit moderate signs of U excess and weak excesses at mid-IR wavelengths. We suggest that these features originate from accretion discs in their last stages of evolution

The Gaia-ESO Survey: pre-main-sequence stars in the young open cluster NGC 3293

The young open cluster NGC3293 is included in the observing program of the Gaia-ESO survey (GES). The radial velocity values provided have been used to assign cluster membership probabilities by means of a single-variable parametric analysis. These membership probabilities are compared to the results of the photometric membership assignment of NGC3293, based on UBVRI photometry. The agreement of the photometric and kinematic member samples amounts to 65 per cent, and could increase to 70 per cent as suggested by the analysis of the differences between both samples. A number of photometric PMS candidate members of spectral type F are found, which are confirmed by the results from VPHAS photometry and SED fitting for the stars in common with VPHAS and GES data sets. Excesses at mid- and near-infrared wavelengths, and signs of Hα emission, are investigated for them. Marginal presence of Hα emission or infilling is detected for the candidate members. Several of them exhibit moderate signs of U excess and weak excesses at mid-IR wavelengths. We suggest that these features originate from accretion discs in their last stages of evolution

Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis

In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent "imitate" teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments

Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership

A method for implicit variable selection in mixture-of-experts frameworks is proposed. We introduce a prior structure where information is taken from a set of independent covariates. Robust class membership predictors are identified using a normal gamma prior. The resulting model setup is used in a finite mixture of Bernoulli distributions to find homogenous clusters of women in Mozambique based on their information sources on HIV. Fully Bayesian inference is carried out via the implementation of a Gibbs sampler

On the posterior distribution of the number of components in a finite mixture

The posterior distribution of the number of components k in a finite mixture satisfies a set of inequality constraints. The result holds irrespective of the parametric form of the mixture components and under assumptions on the prior distribution weaker than those routinely made in the literature on Bayesian analysis of finite mixtures. The inequality constraints can be used to perform an ``internal'' consistency check of MCMC estimates of the posterior distribution of k and to provide improved estimates which are required to satisfy the constraints. Bounds on the posterior probability of k components are derived using the constraints. Implications on prior distribution specification and on the adequacy of the posterior distribution of k as a tool for selecting an adequate number of components in the mixture are also explored.Comment: Published at http://dx.doi.org/10.1214/009053604000000788 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Modelling airport and airline choice behaviour with the use of stated preference survey data

The majority of studies of air travel choice behavior make use of revealed preference (RP) data, generally in the form of survey data collected from departing passengers. While the use of RP data has certain methodological advantages over the use of stated preference (SP) data, major issues arise because of the often low quality of the data relating to the un-chosen alternatives, in terms of explanatory variables as well as availability. As such, studies using RP survey data often fail to recover a meaningful fare coefficient, and are generally not able to offer a treatment of the effects of airline allegiance. In this paper, we make use of SP data for airport and airline choice collected in the US in 2001. The analysis retrieves significant effects relating to factors such as airfare, access time, flight time and airline and airport allegiance, illustrating the advantages of SP data in this context. Additionally, the analysis explores the use of non-linear transforms of the explanatory variables, as well as the treatment of continuous variations in choice behavior across respondents

Spatial Guilds in the Serengeti Food Web Revealed by a Bayesian Group Model

Food webs, networks of feeding relationships among organisms, provide fundamental insights into mechanisms that determine ecosystem stability and persistence. Despite long-standing interest in the compartmental structure of food webs, past network analyses of food webs have been constrained by a standard definition of compartments, or modules, that requires many links within compartments and few links between them. Empirical analyses have been further limited by low-resolution data for primary producers. In this paper, we present a Bayesian computational method for identifying group structure in food webs using a flexible definition of a group that can describe both functional roles and standard compartments. The Serengeti ecosystem provides an opportunity to examine structure in a newly compiled food web that includes species-level resolution among plants, allowing us to address whether groups in the food web correspond to tightly-connected compartments or functional groups, and whether network structure reflects spatial or trophic organization, or a combination of the two. We have compiled the major mammalian and plant components of the Serengeti food web from published literature, and we infer its group structure using our method. We find that network structure corresponds to spatially distinct plant groups coupled at higher trophic levels by groups of herbivores, which are in turn coupled by carnivore groups. Thus the group structure of the Serengeti web represents a mixture of trophic guild structure and spatial patterns, in contrast to the standard compartments typically identified in ecological networks. From data consisting only of nodes and links, the group structure that emerges supports recent ideas on spatial coupling and energy channels in ecosystems that have been proposed as important for persistence.Comment: 28 pages, 6 figures (+ 3 supporting), 2 tables (+ 4 supporting