Institution
Instituto Superior Técnico
About: Instituto Superior Técnico is a(n) based out in . It is known for research contribution in the topic(s): Catalysis & Finite element method. The organization has 10085 authors who have published 30226 publication(s) receiving 667524 citation(s). The organization is also known as: IST & Instituto Superior Tecnico.
Topics: Catalysis, Finite element method, Population, Black hole, Ionic liquid
Papers published on a yearly basis
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University of California, Berkeley1, Lawrence Berkeley National Laboratory2, Instituto Superior Técnico3, Pierre-and-Marie-Curie University4, Stockholm University5, European Southern Observatory6, Collège de France7, University of Cambridge8, University of Barcelona9, Yale University10, Space Telescope Science Institute11, European Space Agency12, University of New South Wales13
TL;DR: In this paper, the mass density, Omega_M, and cosmological-constant energy density of the universe were measured using the analysis of 42 Type Ia supernovae discovered by the Supernova Cosmology project.
Abstract: We report measurements of the mass density, Omega_M, and
cosmological-constant energy density, Omega_Lambda, of the universe based on
the analysis of 42 Type Ia supernovae discovered by the Supernova Cosmology
Project. The magnitude-redshift data for these SNe, at redshifts between 0.18
and 0.83, are fit jointly with a set of SNe from the Calan/Tololo Supernova
Survey, at redshifts below 0.1, to yield values for the cosmological
parameters. All SN peak magnitudes are standardized using a SN Ia lightcurve
width-luminosity relation. The measurement yields a joint probability
distribution of the cosmological parameters that is approximated by the
relation 0.8 Omega_M - 0.6 Omega_Lambda ~= -0.2 +/- 0.1 in the region of
interest (Omega_M <~ 1.5). For a flat (Omega_M + Omega_Lambda = 1) cosmology we
find Omega_M = 0.28{+0.09,-0.08} (1 sigma statistical) {+0.05,-0.04}
(identified systematics). The data are strongly inconsistent with a Lambda = 0
flat cosmology, the simplest inflationary universe model. An open, Lambda = 0
cosmology also does not fit the data well: the data indicate that the
cosmological constant is non-zero and positive, with a confidence of P(Lambda >
0) = 99%, including the identified systematic uncertainties. The best-fit age
of the universe relative to the Hubble time is t_0 = 14.9{+1.4,-1.1} (0.63/h)
Gyr for a flat cosmology. The size of our sample allows us to perform a variety
of statistical tests to check for possible systematic errors and biases. We
find no significant differences in either the host reddening distribution or
Malmquist bias between the low-redshift Calan/Tololo sample and our
high-redshift sample. The conclusions are robust whether or not a
width-luminosity relation is used to standardize the SN peak magnitudes.
15,392 citations
TL;DR: A new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA), which competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.
Abstract: Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.
2,090 citations
TL;DR: In this comprehensive survey, a large number of existing approaches to biclustering are analyzed, and they are classified in accordance with the type of biclusters they can find, the patterns of bIClusters that are discovered, the methods used to perform the search, the approaches used to evaluate the solution, and the target applications.
Abstract: A large number of clustering approaches have been proposed for the analysis of gene expression data obtained from microarray experiments. However, the results from the application of standard clustering methods to genes are limited. This limitation is imposed by the existence of a number of experimental conditions where the activity of genes is uncorrelated. A similar limitation exists when clustering of conditions is performed. For this reason, a number of algorithms that perform simultaneous clustering on the row and column dimensions of the data matrix has been proposed. The goal is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this paper, we refer to this class of algorithms as biclustering. Biclustering is also referred in the literature as coclustering and direct clustering, among others names, and has also been used in fields such as information retrieval and data mining. In this comprehensive survey, we analyze a large number of existing approaches to biclustering, and classify them in accordance with the type of biclusters they can find, the patterns of biclusters that are discovered, the methods used to perform the search, the approaches used to evaluate the solution, and the target applications.
2,027 citations
TL;DR: In this paper, the authors consider the evolution of a universe evolving from a phase dominated by nonrelativistic matter to a cosmological constant via an intermediate period where the effective equation of state is given by $p=\ensuremath{\alpha{-}A/{\ensemath{\rho}}^{\ensemblem{\alpha}},$ where A is a positive constant and $0l √ √ 1/ √ l 1/1.
Abstract: We consider the scenario emerging from the dynamics of a generalized Born-Infeld theory. The equation of state describing this system is given in terms of the energy density $\ensuremath{\rho}$ and pressure p by the relationship $p=\ensuremath{-}A/{\ensuremath{\rho}}^{\ensuremath{\alpha}},$ where A is a positive constant and $0l\ensuremath{\alpha}l~1.$ We discuss the conditions under which homogeneity arises and show that this equation of state describes the evolution of a universe evolving from a phase dominated by nonrelativistic matter to a phase dominated by a cosmological constant via an intermediate period where the effective equation of state is given by $p=\ensuremath{\alpha}\ensuremath{\rho}.$
1,760 citations
University of Chicago1, Pierre-and-Marie-Curie University2, Lawrence Berkeley National Laboratory3, University of Pennsylvania4, Argonne National Laboratory5, Fermilab6, University of Cape Town7, African Institute for Mathematical Sciences8, Texas A&M University9, University of Portsmouth10, University of Cambridge11, University of Toronto12, Wayne State University13, University of Colorado Boulder14, University of Tokyo15, California Institute of Technology16, University of Victoria17, University of California, Berkeley18, University of Illinois at Urbana–Champaign19, Autonomous University of Barcelona20, University of Chile21, Stockholm University22, University of Texas at Austin23, Princeton University24, University of Oxford25, Las Cumbres Observatory Global Telescope Network26, University of California, Santa Barbara27, Rutgers University28, University of Copenhagen29, Australian Astronomical Observatory30, Instituto Superior Técnico31, University of Utah32, Rochester Institute of Technology33, Johns Hopkins University34, Space Telescope Science Institute35, Pennsylvania State University36, University of the Western Cape37, University of Southampton38
TL;DR: In this article, the authors presented cosmological constraints from a joint analysis of type Ia supernova (SN Ia) observations obtained by the SDSS-II and SNLS collaborations.
Abstract: Aims. We present cosmological constraints from a joint analysis of type Ia supernova (SN Ia) observations obtained by the SDSS-II and SNLS collaborations. The dataset includes several low-redshift samples (z< 0.1), all three seasons from the SDSS-II (0.05
1,725 citations
Authors
Showing all 10085 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Joao Seixas | 153 | 1538 | 115070 |
| A. Gomes | 150 | 1862 | 113951 |
| Amartya Sen | 149 | 689 | 141907 |
| António Amorim | 136 | 1477 | 96519 |
| Joao Varela | 133 | 1411 | 92438 |
| Pietro Faccioli | 132 | 1378 | 89795 |
| João Carvalho | 126 | 1278 | 77017 |
| Pedro Jorge | 124 | 776 | 68658 |
| Pedro Silva | 124 | 961 | 74015 |
| A. De Angelis | 118 | 534 | 54469 |
| Hermine Katharina Wöhri | 116 | 629 | 55540 |
| Helena Santos | 114 | 1058 | 54286 |
| P. Conde Muiño | 109 | 558 | 56133 |
| Joao Saraiva | 107 | 519 | 53340 |
| J. N. Reddy | 106 | 926 | 66940 |