370 research outputs found
A New Algorithm for Multivariate Genome Wide Association Studies Based on Differential Evolution and Extreme Learning Machines
Genome-wide association studies (GWAS) are observational studies of a large set of genetic variants, whose aim is to find those that are linked to a certain trait or illness. Due to the multivariate nature of these kinds of studies, machine learning methodologies have been already applied in them, showing good performance. This work presents a new methodology for GWAS that makes use of extreme learning machines and differential evolution. The proposed methodology was tested with the help of the genetic information (370,750 single-nucleotide polymorphisms) of 2049 individuals, 1076 of whom suffer from colorectal cancer. The possible relationship of 10 different pathways with this illness was tested. The results achieved showed that the proposed methodology is suitable for detecting relevant pathways for the trait under analysis with a lower computational cost than other machine learning methodologies previously proposed
Two planetary systems with transiting Earth-sized and super-Earth planets orbiting late-type dwarf stars
Experience with Artificial Neural Networks Applied in Multi-object Adaptive Optics
The use of artificial Intelligence techniques has become widespread in many fields of science, due to their ability to learn from real data and adjust to complex models with ease. These techniques have landed in the field of adaptive optics, and are being used to correct distortions caused by atmospheric turbulence in astronomical images obtained by ground-based telescopes. Advances for multi-object adaptive optics are considered here, focusing particularly on artificial neural networks, which have shown great performance and robustness when compared with other artificial intelligence techniques. The use of artificial neural networks has evolved to the extent of the creation of a reconstruction technique that is capable of estimating the wavefront of light after being deformed by the atmosphere. Based on this idea, different solutions have been proposed in recent years, including the use of new types of artificial neural networks. The results of techniques based on artificial neural networks have led to further applications in the field of adaptive optics, which are included in here, such as the development of new techniques for solar observation or their application in novel types of sensors
Multi-frequency point source detection with fully convolutional networks: Performance in realistic microwave sky simulations
Context. Point source (PS) detection is an important issue for future cosmic microwave background (CMB) experiments since they are one of the main contaminants to the recovery of CMB signal on small scales. Improving its multi-frequency detection would allow us to take into account valuable information otherwise neglected when extracting PS using a channel-by-channel approach.
Aims. We aim to develop an artificial intelligence method based on fully convolutional neural networks to detect PS in multi-frequency realistic simulations and compare its performance against one of the most popular multi-frequency PS detection methods, the matrix filters. The frequencies used in our analysis are 143, 217, and 353 GHz, and we imposed a Galactic cut of 30°.
Methods. We produced multi-frequency realistic simulations of the sky by adding contaminating signals to the PS maps as the CMB, the cosmic infrared background, the Galactic thermal emission, the thermal Sunyaev-Zel’dovich effect, and the instrumental and PS shot noises. These simulations were used to train two neural networks called flat and spectral MultiPoSeIDoNs. The first one considers PS with a flat spectrum, and the second one is more realistic and general because it takes into account the spectral behaviour of the PS. Then, we compared the performance on reliability, completeness, and flux density estimation accuracy for both MultiPoSeIDoNs and the matrix filters.
Results. Using a flux detection limit of 60 mJy, MultiPoSeIDoN successfully recovered PS reaching the 90% completeness level at 58 mJy for the flat case, and at 79, 71, and 60 mJy for the spectral case at 143, 217, and 353 GHz, respectively. The matrix filters reach the 90% completeness level at 84, 79, and 123 mJy. To reduce the number of spurious sources, we used a safer 4σ flux density detection limit for the matrix filters, the same as was used in the Planck catalogues, obtaining the 90% of completeness level at 113, 92, and 398 mJy. In all cases, MultiPoSeIDoN obtains a much lower number of spurious sources with respect to the filtering method. The recovering of the flux density of the detections, attending to the results on photometry, is better for the neural networks, which have a relative error of 10% above 100 mJy for the three frequencies, while the filter obtains a 10% relative error above 150 mJy for 143 and 217 GHz, and above 200 mJy for 353 GHz.
Conclusions. Based on the results, neural networks are the perfect candidates to substitute filtering methods to detect multi-frequency PS in future CMB experiments. Moreover, we show that a multi-frequency approach can detect sources with higher accuracy than single-frequency approaches also based on neural networks.We warmly thank the anonymous referee for the very useful comments on the original manuscript. J.M.C., J.G.N., L.B., M.M.C. and D.C. acknowledge financial support from the PGC 2018 project PGC2018-101948-B-I00 (MICINN, FEDER). DH acknowledges the Spanish MINECO and the Spanish Ministerio de Ciencia, Innovación y Universidades for partial financial support under project PGC2018-101814-B-I00. M.M.C. acknowledges PAPI-20-PF-23 (Universidad de Oviedo). J.D.C.J., M.L.S., S.L.S.G., J.D.S. and F.S.L. acknowledge financial support from the I+D 2017 project AYA2017-89121-P and support from the European Union’s Horizon 2020 research and innovation programme under the H2020-INFRAIA-2018-2020 grant agreement No 210489629. This research has made use of the python packages ipython (Pérez & Granger 2007), matplotlib (Hunter 2007), TensorFlow (Abadi et al. 2015), Numpy (Oliphant 2006) and Scipy (Jones et al. 2001), also the HEALPix (Górski et al. 2005) and healpy (Zonca et al. 2019) packages
University Issues. Year 3. Number 3. Journal of the Center for Research in Social Sciences and Arts
Las opiniones contenidas en los artíuclos de esta revista no vinvulan la institución sono que son exclusiva responsabilidad de los autores, dentro de los principios demacráticos de cátedar libre y libertad de expresión, consagrados en el artículo 3° Estatuto Genral de la Corporación Autónoma de Bucaramanga.Presentación. - 5
Investigación científica y tecnológica. - 8
Reflexión derivada de la investigación. -50
Anaquel. -120
Anexos. -122The opinions contained in the articles of this journal do not vindicate the institution but are the sole responsibility of the authors, within the democratic principles of free cattery and freedom of expression, enshrined in Article 3 General Statute of the Autonomous Corporation of Bucaramanga
una mirada desde las Ciencias de la Conducta
Este libro es el resultado de los trabajos presentados en el 1er Congreso Internacional "Convivencia y bienestar con sentido humanista para una cultura de paz"
POR UNA CULTURA DE PAZ: UNA MIRADA DESDE LAS CIENCIAS DE LA CONDUCTA
En
virtud
de
lo
anterior,
los
estudiosos
de
las
ciencias
de
la
conducta
de
la
Universidad
Autónoma
del
Estado
de
México,
ante
la
persistencia
y
proliferación
de
estos
hechos
en
diversas
partes
del
Mundo
y
de
nuestro
país
en
particular, se
convocó
a
los
estudiosos
interesados
y
a
la
sociedad
en
general
a
presentar
trabajos
para
analizar,
debatir
y
proponer
estrategias
de
acción
y
dirección,
que
fortalezcan
una
convivencia y bienestar con sentido humanista para una cultura de paz.
El
presente
texto
es
producto
de
esta convocatoria
que
recoge
los
trabajos
de
los
interesados
en
la
temática,
de
diferentes
países
(España,
Argentina,
Cuba,
Brasil,
Costa
Rica
y
México)
retomando
con
ello
sus
experiencias
relativas
al
estudio,
análisis,
comprensión
e
instrumentación
de
la
cultura
de
paz
en
los
distintos
ámbitos
institucionales
en
los
que
participan:
educativo,
salud,
penitenciario,
social,
laboral,
familia,
alimentario,
psicológico,
por
mencionar
algunos.
El
presente
libro,
propicia
un
espacio
de
reflexión,
diálogo
y
posicionamiento
de
las
ciencias
de
la
conducta
para
la
apropiación,
análisis,
debate
y
propuestas
que
fortalezcan
una
cultura
de
paz
a
través
de
la
convivencia
y
el
bienestar
social
con
sentido
humanista.
El
sistema
económico
neoliberal
y
el
proceso
de
globalización
han
contribuido
al
logro
de
avances
significativos
en
la
ciencia
y
la
tecnología,
pero
también
han
propiciado
la
polarización
de
las
sociedades
lo
que
ha
impactado
de
manera
negativa
a
la
sociedad
en
su
conjunto,
pero
en
mayor
medida
a
los grupos
vulnerables. Dicha
polarización
ha
traído
consigo
un
desarrollo
desigual
del
mundo
que
se
expresa
de
diferentes
maneras
tanto
en
países
desarrollados
como
en
los
llamados
del
tercer
mundo,
en
donde
no
están
satisfechas
las
necesidades
humanas
elementales
de
todos
los
sectores
de
la
población,
siempre
falta
algo.
Si
a
esto
le
sumamos
los
conflictos
internacionales por
diferentes
motivos
que
enfrentan
algunas
naciones,
una
insuficiente
cobertura
educativa
y
de
salud,
desempleo
y
pobreza
extrema,
entre
otras
cosas;
estamos
frente
a
retos
de
gran
envergadura
para
los
gobiernos,
para
los
estudiosos
y
para
la
sociedad
civil
en
general. Uno
de
los
intentos
para
frenar
y prevenir
la
agudización
de
estas
problemáticas
es
la
cultura
de
paz,
cuyo
estudio
y propuestas
han
ido
avanzando
en
diferentes
sentidos
y
de
manera
favorable,
el
tema
está
presente
en
diferentes
Organismos
Internacionales
como
la
ONU,
la
UNESCO,
la
OCDE,
El
Banco
Mundial,
entre
otros.
Pero
falta
mucho
por
hacer.Universidad Autónoma del Estado de Méxic
The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment
The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in
operation since July 2014. This paper describes the second data release from
this phase, and the fourteenth from SDSS overall (making this, Data Release
Fourteen or DR14). This release makes public data taken by SDSS-IV in its first
two years of operation (July 2014-2016). Like all previous SDSS releases, DR14
is cumulative, including the most recent reductions and calibrations of all
data taken by SDSS since the first phase began operations in 2000. New in DR14
is the first public release of data from the extended Baryon Oscillation
Spectroscopic Survey (eBOSS); the first data from the second phase of the
Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2),
including stellar parameter estimates from an innovative data driven machine
learning algorithm known as "The Cannon"; and almost twice as many data cubes
from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous
release (N = 2812 in total). This paper describes the location and format of
the publicly available data from SDSS-IV surveys. We provide references to the
important technical papers describing how these data have been taken (both
targeting and observation details) and processed for scientific use. The SDSS
website (www.sdss.org) has been updated for this release, and provides links to
data downloads, as well as tutorials and examples of data use. SDSS-IV is
planning to continue to collect astronomical data until 2020, and will be
followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14
happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov
2017 (this is the "post-print" and "post-proofs" version; minor corrections
only from v1, and most of errors found in proofs corrected
Espacio y territorios: razón, pasión e imaginarios
En este caleidoscopio de acercamientos hacia lo espacial y territorial, las visiones se mueven desde aquellas románticas y existencialistas, pasando por aquellas objetivistas y positivistas, hasta las estructuralistas y postestructuralistas. Por el espacio y el territorio se interesan con enfoques diversos numerosas disciplinas, desde la psicología, la etología o la literatura, y las ciencias naturales como la biología o la ecología, hasta las ciencias sociales y políticas, como la geografía, la antropología, la economía y la sociología. Este interés multidisciplinario demuestra la importancia y la complejidad del tema espacial y territorial, y reclama la necesidad de su estudio y comprensión interdisciplinarios, como se intenta con esta publicación
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