535 research outputs found
A feasibility cachaca type recognition using computer vision and pattern recognition
Brazilian rum (also known as cachaça) is the third most commonly consumed distilled alcoholic drink in the world, with approximately 2.5 billion liters produced each year. It is a traditional drink with refined features and a delicate aroma that is produced mainly in Brazil but consumed in many countries. It can be aged in various types of wood for 1-3 years, which adds aroma and a distinctive flavor with different characteristics that affect the price. A research challenge is to develop a cheap automatic recognition system that inspects the finished product for the wood type and the aging time of its production. Some classical methods use chemical analysis, but this approach requires relatively expensive laboratory equipment. By contrast, the system proposed in this paper captures image signals from samples and uses an intelligent classification technique to recognize the wood type and the aging time. The classification system uses an ensemble of classifiers obtained from different wavelet decompositions. Each classifier is obtained with different wavelet transform settings. We compared the proposed approach with classical methods based on chemical features. We analyzed 105 samples that had been aged for 3 years and we showed that the proposed solution could automatically recognize wood types and the aging time with an accuracy up to 100.00% and 85.71% respectively, and our method is also cheaper.info:eu-repo/semantics/publishedVersio
QUANTIFICATION OF THE POPULATION AND PHAGOCYTARY ACTIVITY OF HEMOCYTES OF RESISTANT AND SUSCEPTIBLE STRAINS OF Biomphalaria glabrata AND Biomphalaria tenagophila INFECTED WITH Schistosoma mansoni
Fitting the integrated Spectral Energy Distributions of Galaxies
Fitting the spectral energy distributions (SEDs) of galaxies is an almost
universally used technique that has matured significantly in the last decade.
Model predictions and fitting procedures have improved significantly over this
time, attempting to keep up with the vastly increased volume and quality of
available data. We review here the field of SED fitting, describing the
modelling of ultraviolet to infrared galaxy SEDs, the creation of
multiwavelength data sets, and the methods used to fit model SEDs to observed
galaxy data sets. We touch upon the achievements and challenges in the major
ingredients of SED fitting, with a special emphasis on describing the interplay
between the quality of the available data, the quality of the available models,
and the best fitting technique to use in order to obtain a realistic
measurement as well as realistic uncertainties. We conclude that SED fitting
can be used effectively to derive a range of physical properties of galaxies,
such as redshift, stellar masses, star formation rates, dust masses, and
metallicities, with care taken not to over-interpret the available data. Yet
there still exist many issues such as estimating the age of the oldest stars in
a galaxy, finer details ofdust properties and dust-star geometry, and the
influences of poorly understood, luminous stellar types and phases. The
challenge for the coming years will be to improve both the models and the
observational data sets to resolve these uncertainties. The present review will
be made available on an interactive, moderated web page (sedfitting.org), where
the community can access and change the text. The intention is to expand the
text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics &
Space Scienc
Pharmacotherapy review: a proposal to improve medication adherence among hypertensive patients
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Simulating maize yield in sub-tropical conditions of southern Brazil using Glam model
The objective of this work was to evaluate the feasibility of simulating maize yield in a sub‑tropical
region of southern Brazil using the general large area model (Glam). A 16‑year time series of daily weather data
were used. The model was adjusted and tested as an alternative for simulating maize yield at small and large
spatial scales. Simulated and observed grain yields were highly correlated (r above 0.8; p<0.01) at large scales
(greater than 100,000 km2), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small
spatial scales (lower than 10,000 km2). Large area models can contribute to monitoring or forecasting regional
patterns of variability in maize production in the region, providing a basis for agricultural decision making, and
Glam‑Maize is one of the alternatives
Measurement systems of soil water matric potential and evaluation of soil moisture under different irrigation depths
The effects of parturition season and suckling mode on the puerperium of Santa Ines ewes and on the weight gain of lambs
Uptake and distribution of N, P and heavy metals in three dominant salt marsh macrophytes from Yangtze River estuary, China
Consumo e fermentação ruminal de proteínas em função de suplementação alimentar energética e protéica em novilhos
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