Ontology-Driven Cross-Domain Transfer Learning.

The aim of transfer learning is to reuse learnt knowledge across different contexts. In the particular case of cross-domain transfer (also known as domain adaptation), reuse happens across different but related knowledge domains. While there have been promising first results in combining learning with symbolic knowledge to improve cross-domain transfer results, the singular ability of ontologies for providing classificatory knowledge has not been fully exploited so far by the machine learning community. We show that ontologies, if properly designed, are able to support transfer learning by improving generalization and discrimination across classes. We propose an architecture based on direct attribute prediction for combining ontologies with a transfer learning framework, as well as an ontology-based solution for cross-domain generalization based on the integration of top-level and domain ontologies. We validate the solution on an experiment over an image classification task, demonstrating the system's improved classification performance

Ages of massive galaxies at 0.5<z<2.00.5 < z < 2.0 from 3D-HST rest-frame optical spectroscopy

We present low-resolution near-infrared stacked spectra from the 3D-HST survey up to $z=2.0$ and fit them with commonly used stellar population synthesis models: BC03 (Bruzual & Charlot, 2003), FSPS10 (Flexible Stellar Population Synthesis, Conroy & Gunn 2010), and FSPS-C3K (Conroy, Kurucz, Cargile, Castelli, in prep). The accuracy of the grism redshifts allows the unambiguous detection of many emission and absorption features, and thus a first systematic exploration of the rest-frame optical spectra of galaxies up to $z=2$. We select massive galaxies ($\rm log(M_{*} / M_{\odot}) > 10.8$), we divide them into quiescent and star-forming via a rest-frame color-color technique, and we median-stack the samples in 3 redshift bins between $z=0.5$ and $z=2.0$. We find that stellar population models fit the observations well at wavelengths below $\rm 6500 \AA$ rest-frame, but show systematic residuals at redder wavelengths. The FSPS-C3K model generally provides the best fits (evaluated with a $\chi^2_{red}$ statistics) for quiescent galaxies, while BC03 performs the best for star-forming galaxies. The stellar ages of quiescent galaxies implied by the models, assuming solar metallicity, vary from 4 Gyr at $z \sim 0.75$ to 1.5 Gyr at $z \sim 1.75$, with an uncertainty of a factor of 2 caused by the unknown metallicity. On average the stellar ages are half the age of the Universe at these redshifts. We show that the inferred evolution of ages of quiescent galaxies is in agreement with fundamental plane measurements, assuming an 8 Gyr age for local galaxies. For star-forming galaxies the inferred ages depend strongly on the stellar population model and the shape of the assumed star-formation history.Comment: 13 pages, 15 figures, accepted for publication in Ap

Quiescent Galaxies in the 3D-HST Survey: Spectroscopic Confirmation of a Large Number of Galaxies with Relatively Old Stellar Populations at z~2

Quiescent galaxies at z~2 have been identified in large numbers based on rest-frame colors, but only a small number of these galaxies have been spectroscopically confirmed to show that their rest-frame optical spectra show either strong Balmer or metal absorption lines. Here, we median stack the rest-frame optical spectra for 171 photometrically-quiescent galaxies at 1.4 < z < 2.2 from the 3D-HST grism survey. In addition to Hbeta (4861A), we unambiguously identify metal absorption lines in the stacked spectrum, including the G-band (4304A), Mg I (5175A), and Na I (5894A). This finding demonstrates that galaxies with relatively old stellar populations already existed when the universe was ~3 Gyr old, and that rest-frame color selection techniques can efficiently select them. We find an average age of 1.3^0.1_0.3 Gyr when fitting a simple stellar population to the entire stack. We confirm our previous result from medium-band photometry that the stellar age varies with the colors of quiescent galaxies: the reddest 80% of galaxies are dominated by metal lines and have a relatively old mean age of 1.6^0.5_0.4 Gyr, whereas the bluest (and brightest) galaxies have strong Balmer lines and a spectroscopic age of 0.9^0.2_0.1 Gyr. Although the spectrum is dominated by an evolved stellar population, we also find [OIII] and Hbeta emission. Interestingly, this emission is more centrally concentrated than the continuum with L_[OIII] = 1.7 +/- 0.3 x 10^40 erg s^-1, indicating residual central star formation or nuclear activity.Comment: 6 pages, 4 figures, accepted for publication in the Astrophysical Journal Letter

Integrating 3D City Data through Knowledge Graphs

CityGML is a widely adopted standard by the Open Geospatial Consortium (OGC) for representing and exchanging 3D city models. The representation of semantic and topological properties in CityGML makes it possible to query such 3D city data to perform analysis in various applications, e.g., security management and emergency response, energy consumption and estimation, and occupancy measurement. However, the potential of querying CityGML data has not been fully exploited. The official GML/XML encoding of CityGML is only intended as an exchange format but is not suitable for query answering. The most common way of dealing with CityGML data is to store them in the 3DCityDB system as relational tables and then query them with the standard SQL query language. Nevertheless, for end users, it remains a challenging task to formulate queries over 3DCityDB directly for their ad-hoc analytical tasks, because there is a gap between the conceptual semantics of CityGML and the relational schema adopted in 3DCityDB. In fact, the semantics of CityGML itself can be modeled as a suitable ontology. The technology of Knowledge Graphs (KGs), where an ontology is at the core, is a good solution to bridge such a gap. Moreover, embracing KGs makes it easier to integrate with other spatial data sources, e.g., OpenStreetMap and existing (Geo)KGs (e.g., Wikidata, DBPedia, and GeoNames), and to perform queries combining information from multiple data sources. In this work, we describe a CityGML KG framework to populate the concepts in the CityGML ontology using declarative mappings to 3DCityDB, thus exposing the CityGML data therein as a KG. To demonstrate the feasibility of our approach, we use CityGML data from the city of Munich as test data and integrate OpenStreeMap data in the same area

Direct measurements of dust attenuation in z~1.5 star-forming galaxies from 3D-HST: Implications for dust geometry and star formation rates

The nature of dust in distant galaxies is not well understood, and until recently few direct dust measurements have been possible. We investigate dust in distant star-forming galaxies using near-infrared grism spectra of the 3D-HST survey combined with archival multi-wavelength photometry. These data allow us to make a direct comparison between dust around star-forming regions ($A_{V,\mathrm{HII}}$) and the integrated dust content ($A_{V,\mathrm{star}}$). We select a sample of 163 galaxies between $1.36\le{}z\le1.5$ with H$\alpha$ signal-to-noise ratio $\ge5$ and measure Balmer decrements from stacked spectra to calculate $A_{V,\mathrm{HII}}$. First, we stack spectra in bins of $A_{V,\mathrm{star}}$, and find that $A_{V,\mathrm{HII}}=1.86\,A_{V,\mathrm{star}}$, with a significance of $\sigma=1.7$. Our result is consistent with the two-component dust model, in which galaxies contain both diffuse and stellar birth cloud dust. Next, we stack spectra in bins of specific star formation rate ($\log\,\mathrm{SSFR}$), star formation rate ($\log\,\mathrm{SFR}$), and stellar mass ($\log{}M_*$). We find that on average $A_{V,\mathrm{HII}}$ increases with SFR and mass, but decreases with increasing SSFR. Interestingly, the data hint that the amount of extra attenuation decreases with increasing SSFR. This trend is expected from the two-component model, as the extra attenuation will increase once older stars outside the star-forming regions become more dominant in the galaxy spectrum. Finally, using Balmer decrements we derive dust-corrected H$\alpha$ SFRs, and find that stellar population modeling produces incorrect SFRs if rapidly declining star formation histories are included in the explored parameter space.Comment: Accepted for publication in the Astrophysical Journal (13 pages, 9 figures