2,257 research outputs found
RankMerging: A supervised learning-to-rank framework to predict links in large social network
Uncovering unknown or missing links in social networks is a difficult task
because of their sparsity and because links may represent different types of
relationships, characterized by different structural patterns. In this paper,
we define a simple yet efficient supervised learning-to-rank framework, called
RankMerging, which aims at combining information provided by various
unsupervised rankings. We illustrate our method on three different kinds of
social networks and show that it substantially improves the performances of
unsupervised metrics of ranking. We also compare it to other combination
strategies based on standard methods. Finally, we explore various aspects of
RankMerging, such as feature selection and parameter estimation and discuss its
area of relevance: the prediction of an adjustable number of links on large
networks.Comment: 43 pages, published in Machine Learning Journa
Benchmarking some Portuguese S&T system research units: 2nd Edition
The increasing use of productivity and impact metrics for evaluation and
comparison, not only of individual researchers but also of institutions,
universities and even countries, has prompted the development of bibliometrics.
Currently, metrics are becoming widely accepted as an easy and balanced way to
assist the peer review and evaluation of scientists and/or research units,
provided they have adequate precision and recall.
This paper presents a benchmarking study of a selected list of representative
Portuguese research units, based on a fairly complete set of parameters:
bibliometric parameters, number of competitive projects and number of PhDs
produced. The study aimed at collecting productivity and impact data from the
selected research units in comparable conditions i.e., using objective metrics
based on public information, retrievable on-line and/or from official sources
and thus verifiable and repeatable. The study has thus focused on the activity
of the 2003-06 period, where such data was available from the latest official
evaluation.
The main advantage of our study was the application of automatic tools,
achieving relevant results at a reduced cost. Moreover, the results over the
selected units suggest that this kind of analyses will be very useful to
benchmark scientific productivity and impact, and assist peer review.Comment: 26 pages, 20 figures F. Couto, D. Faria, B. Tavares, P.
Gon\c{c}alves, and P. Verissimo, Benchmarking some portuguese S\&T system
research units: 2nd edition, DI/FCUL TR 13-03, Department of Informatics,
University of Lisbon, February 201
The fiscal forecasting track record of the European Commission and Portugal
Mestrado em Monetary and Financial EconomicsThis study aims at explaining the deviation between the budget balance ratio forecasts and the outcomes in the Portuguese official forecasts and in the European Commission (EC) vintage forecasts. Therefore, we used data from the EC for the period 1969-2011 and also the Portuguese official forecasts for 1977-2011. We explain the deviation of the budget balance-to-GDP through econometric estimations and present statistical decomposition about budget balance, revenue and spending-to-GDP deviations. The statistical significance of real GDP and inflation deviations reveals the effect of automatic stabilizers and the imperfect tax indexation system. The European panel reveals statistical significance (no significance) of investment (unemployment) deviation in the budget-to-GDP ratio. Countries with better fiscal rules seem to present favourable deviations (in the absence of fixed effects). In Portugal, there is evidence of unfavourable errors about the budget balance in nominal currency in most years, which has been offset (totally or partially) by a favourable nominal GDP effect deviation
Complexity in small-scale dwarf spheroidal galaxies
Our knowledge about the dynamics, the chemical abundances and the
evolutionary histories of the more luminous dwarf spheroidal (dSph) galaxies is
constantly growing. However, very little is known about the enrichment of the
ultra-faint systems recently discovered in large numbers in large sky surveys.
Current low-resolution spectroscopy and photometric data indicate that these
galaxies are highly dark matter dominated and predominantly metal poor. On the
other hand, recent high-resolution abundance analyses indicate that some dwarf
galaxies experienced highly inhomogenous chemical enrichment, where star
formation proceeds locally on small scales. In this article, I will review the
kinematic and chemical abundance information of the Milky Way satellite dSphs
that is presently available from low- and high resolution spectroscopy.
Moreover, some of the most peculiar element and inhomogeneous enrichment
patterns will be discussed and related to the question of to what extent the
faintest dSph candidates could have contributed to the Galactic halo, compared
to more luminous systems.Comment: 34 pages, 8 figures; Ludwig-Biermann Award Lecture 2008, to appear in
Reviews in Modern Astronomy, 21,
STRENGTHS AND LIMITATIONS OF QUALITATIVE AND QUANTITATIVE RESEARCH METHODS
Scientific research adopts qualitative and quantitative methodologies in the modeling and analysis of numerous phenomena. The qualitative methodology intends to understand a complex reality and the meaning of actions in a given context. On the other hand, the quantitative methodology seeks to obtain accurate and reliable measurements that allow a statistical analysis. Both methodologies offer a set of methods, potentialities and limitations that must be explored and known by researchers. This paper concisely maps a total of seven qualitative methods and five quantitative methods. A comparative analysis of the most relevant and adopted methods is done to understand the main strengths and limitations of them. Additionally, the work developed intends to be a fundamental reference for the accomplishment of a research study, in which the researcher intends to adopt a qualitative or quantitative methodology. Through the analysis of the advantages and disadvantages of each method, it becomes possible to formulate a more accurate, informed and complete choice. Article visualizations
Synergistic Smart Morphing Aileron
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106472/1/AIAA2013-1512.pd
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