977 research outputs found
Manage entropy in Architectural Projects: assuming commitments and ordering diversity
It was primary to transfer to the student the importance of his own responsibility on the project, transcending the usual condition of mere academic practice in the school. Their projects are already real actions to transform the reality from the
moment in which are the product of a responsible and critical thinking. To the regular development of the Subject of Architectural Projects with theoretical classes and collective corrections in Workshop of Projects, it was incorporated a
series of methodologies to activate the individual and collective learning.
The project critically acts on city model, proposes an architectural intervention with transformative will and the classroom becomes a social space where individual engagements and collective engagements are added. This dialectic with reality was concluded with the exhibition of projects, which the students explained to the neighbours as the end of the course, first in school and finally in their civic center.Fue primordial transferir al estudiante la importancia de su propia responsabilidad sobre el proyecto, trascendiendo la habitual condición de mera práctica escolar en la Escuela. Sus proyectos son ya verdaderas acciones para transformar la realidad desde el momento mismo en que son el producto de un pensamiento crítico y responsable. Al desarrollo habitual de la Asignatura de Proyectos Arquitectónicos con clases teóricas y correcciones colectivas en Taller de Proyectos se incorporan una serie de metodologías para activar individual y colectivamente el aprendizaje.
El proyecto actúa críticamente sobre el modelo de ciudad, propone una intervención arquitectónica con voluntad transformadora y el aula se convierte en un espacio social donde se suman compromisos individuales y compromisos
colectivos. Esta dialéctica con la realidad se concluyó con la exposición de los proyectos realizados, que los estudiantes explicaron ante los vecinos del barrio como final de curso, en la Escuela y en su Centro Cívico
Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models
[EN] This paper introduces the Group Linear Algorithm with Sparse Principal decomposition, an algorithm for supervised variable selection and clustering. Our approach extends the Sparse Group Lasso regularization to calculate clusters as part of the model fit. Therefore, unlike Sparse Group Lasso, our idea does not require prior specification of clusters between variables. To determine the clusters, we solve a particular case of sparse Singular Value Decomposition, with a regularization term that follows naturally from the Group Lasso penalty. Moreover, this paper proposes a unified implementation to deal with, but not limited to, linear regression, logistic regression, and proportional hazards models with right-censoring. Our methodology is evaluated using both biological and simulated data, and details of the implementation in R and hyperparameter search are discussed.Laria, JC.; Aguilera-Morillo, MC.; Lillo, RE. (2022). Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models. Statistical Papers. 64(1):227-253. https://doi.org/10.1007/s00362-022-01313-z227253641Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X et al (2000) Distinct types of diffuse large b-cell lymphoma identified by gene expression profiling. Nature 403(6769):503–511Bair E, Hastie T, Paul D, Tibshirani R (2006) Prediction by supervised principal components. J Am Stat Assoc 101(473):119–137Beck A, Teboulle M (2009) A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J Imag Sci 2(1):183–202Beisser D, Klau GW, Dandekar T, Müller T, Dittrich MT (2010) Bionet: an r-package for the functional analysis of biological networks. Bioinformatics 26(8):1129–1130Bergstra J, Bengio Y (2012) Random search for hyper-parameter optimization. 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J Stat Softw 33(1):1Kuhn M (2020) tune: Tidy Tuning Tools. https://CRAN.R-project.org/package=tune, r package version 0.1.0Kuhn M, Vaughan D (2020) parsnip: a Common API to Modeling and Analysis Functions. https://CRAN.R-project.org/package=parsnip, r package version 0.0.5Laria JC, Carmen Aguilera-Morillo M, Lillo RE (2019) An iterative sparse-group lasso. J Comput Graph Stat 28(3):722–731Luo S, Chen Z (2020) Feature selection by canonical correlation search in high-dimensional multiresponse models with complex group structures. J Am Stat Assoc 115(531):1227–1235Moore DF (2016) Applied survival analysis using R. Springer, New YorkNdiaye E, Fercoq O, Gramfort A, Salmon J (2016) Gap safe screening rules for sparse-group lasso. In: Advances in Neural Information Processing Systems, pp 388–396Price BS, Sherwood B (2017) A cluster elastic net for multivariate regression. J Mach Learn Res 18(1):8685–8723Rand WM (1971) Objective criteria for the evaluation of clustering methods. J Am Stat Assoc 66(336):846–850Ren S, Kang EL, Lu JL (2020) Mcen: a method of simultaneous variable selection and clustering for high-dimensional multinomial regression. Stat Comput 30(2):291–304Rosenwald A, Wright G, Chan WC, Connors JM, Campo E, Fisher RI, Gascoyne RD, Muller-Hermelink HK, Smeland EB, Giltnane JM et al (2002) The use of molecular profiling to predict survival after chemotherapy for diffuse large-b-cell lymphoma. N Engl J Med 346(25):1937–1947Shen H, Huang JZ (2008) Sparse principal component analysis via regularized low rank matrix approximation. J Multivar Anal 99(6):1015–1034Simon N, Friedman J, Hastie T, Tibshirani R (2013) A sparse-group lasso. J Comput Graph Stat 22(2):231–245Snoek J, Larochelle H, Adams RP (2012) Practical bayesian optimization of machine learning algorithms. 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Math Program 179(1):223–263Zhao H, Wu Q, Li G, Sun J (2019) Simultaneous estimation and variable selection for interval-censored data with broken adaptive ridge regression. J Am Stat Assoc 1–13Zhou N, Zhu J (2010) Group variable selection via a hierarchical lasso and its oracle property. Stat Interface 3:557–574Zou H, Hastie T (2005) Regularization and variable selection via the elastic net. J R Stat Soc Ser B 67(2):301–32
Adaptive sparse group LASSO in quantile regression
[EN] This paper studies the introduction of sparse group LASSO (SGL) to the quantile regression framework. Additionally, a more flexible version, an adaptive SGL is proposed based on the adaptive idea, this is, the usage of adaptive weights in the penalization. Adaptive estimators are usually focused on the study of the oracle property under asymptotic and double asymptotic frameworks. A key step on the demonstration of this property is to consider adaptive weights based on a initial root n-consistent estimator. In practice this implies the usage of a non penalized estimator that limits the adaptive solutions to low dimensional scenarios. In this work, several solutions, based on dimension reduction techniques PCA and PLS, are studied for the calculation of these weights in high dimensional frameworks. The benefits of this proposal are studied both in synthetic and real datasets.We appreciate the work of the referees that has contributed to substantially improve the scientific contributions of this work. In this research we have made use of Uranus, a supercomputer cluster located at University Carlos III of Madrid and funded jointly by EU-FEDER funds and by the Spanish Government via the National Projects No. UNC313-4E-2361, No. ENE2009-12213- C03-03, No. ENE2012-33219 and No. ENE2015-68265-P. This research was partially supported by research grants and Project ECO2015-66593-P from Ministerio de Economia, Industria y Competitividad, Project MTM2017-88708-P from Ministerio de Economia y Competitividad, FEDER funds and Project IJCI-2017-34038 from Agencia Estatal de Investigacion, Ministerio de Ciencia, Innovacion y Universidades.Mendez-Civieta, A.; Aguilera-Morillo, MC.; Lillo, RE. (2021). Adaptive sparse group LASSO in quantile regression. 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A low-voltage low-power front-end for wearable EEG systems
A low-voltage and low-power front-end for miniaturized, wearable EEG systems is presented. The instrumentation amplifier, which removes the electrode drift and conditions the signal for a 10-bit A/D converter, combines a chopping strategy with quasi-FGMOS (QFG) transistors to minimize low frequency noise whilst enabling operation at 1 V supply. QFG devices are also key to the A/D converter operating at 1.2 V with 70dB of SNR and an oversampling ratio of 64. The whole system consumes less than 2uW at 1.2V.Published versio
Comparative effects of several cyclodextrins on the extraction of PAHs from a real contaminated soil
Polycyclic aromatic hydrocarbons (PAHs) are persistent organic pollutants (POPs) attracting extensive attention worldwide. Soils from many sites, such as areas of coal storage, coke oven plants, manufactured gas plants and areas of coal tar spillage present a high contamination level by PAHs. Due to their low solubility in water, the presence of PAHs in the soil matrix constitutes a long-term source of groundwater contamination, and their toxic, mutagenic and carcinogenic properties are responsible that the remediation of PAH-contaminated soil becomes a major environmental concern. In order to enhance the desorption rate of organic pollutants, various extracting agents have been used. Recently, cyclodextrins (CDs) have been proposed as an alternative agent to enhance the water solubility of hydrophobic compounds and thus their availability for biodegradation. The objectives of the present work were: to identify the level of PAHs of an aged-contaminated soil sample from a former chemical industry plant and to evaluate the ability of a natural cyclodextrin (ß-cyclodextrin, BCD) and three chemically modified cyclodextrins: 2-hydroxypropyl-ß-cyclodextrin (HPBCD), partially methylated-ß-cyclodextrin (PMBCD), and hydroxypropyl-¿-cyclodextrin (HPGCD) to extract the sixteen PAHs considered as priority pollutants by US-EPA.
A real contaminated soil from the surrounding area of a deserted chemical industry situated in Asturias (North of Spain) was analyzed exhaustively in order to know its PAHs content. Then extraction experiments using Ca(NO3)2 solution or three types of different cyclodextrins solutions were carried out about the same soil.
The results presented in this study show that according to Spanish legislation the analyzed soil had to be considered as contaminated soil. Its total PAHs content was about 1068.77±100.81 mg Kg-1, being phenanthrene, anthracene and naphthalene the most abundant compounds (25.3, 24.7 and 17.1 % of the total PAHs content of the soil, respectively). After the extractions experiments using CDs solutions, it was observed that the percentages of PAHs obtained were always higher than when an aqueous solution was used, although the three chemically modified cyclodextrins achieved higher extractions percentages than the natural cyclodextrin (BCD). From the sixteen selected PAHs, the highest extraction percentages was always obtained for the 3-rings PAHs, what is related with the more appropriated size and shape of this compounds with respect to the CDs cavity dimensions
A Framework to Evaluate Software Developer’s Productivity The VALORTIA Project
Currently, there is a lack in companies developing software in relation to assessing their staff’s productivity
before executing software projects, with the aim of improving effectiveness and efficiency. QuEF (Quality
Evaluation Framework) is a framework that allows defining quality management tasks based on a model.
The main purpose of this framework is twofold: improve an entity’s continuous quality, and given a context,
decide between a set of entity’s instances on the most appropriate one. Thus, the aim of this paper is to
make this framework available to evaluate productivity of professionals along software development and
select the most appropriate experts to implement the suggested project. For this goal, Valortia platform,
capable of carrying out this task by following the QuEF framework guidelines, is designed. Valortia is a
platform to certify users' knowledge on a specific area and centralize all certification management in its
model by means of providing protocols and methods for a suitable management, improving efficiency and
effectiveness, reducing cost and ensuring continuous quality.Ministerio de Ciencia e Innovación TIN2013-46928-C3-3-
Tuning the program transformers from LCC to PDL
This work proposes an alternative definition of the so-called program transformers used to obtain reduction axioms in the Logic of Communication and Change (LCC). Our proposal uses an elegant matrix treatment of Brzozowski’s equational method instead of Kleene’s translation from finite automata to regular expressions. The two alternatives are shown to be equivalent, with Brzozowski’s method having the advantage of generating smaller expressions for models with average connectivity
Gain in Stochastic Resonance: Precise Numerics versus Linear Response Theory beyond the Two-Mode Approximation
In the context of the phenomenon of Stochastic Resonance (SR) we study the
correlation function, the signal-to-noise ratio (SNR) and the ratio of output
over input SNR, i.e. the gain, which is associated to the nonlinear response of
a bistable system driven by time-periodic forces and white Gaussian noise.
These quantifiers for SR are evaluated using the techniques of Linear Response
Theory (LRT) beyond the usually employed two-mode approximation scheme. We
analytically demonstrate within such an extended LRT description that the gain
can indeed not exceed unity. We implement an efficient algorithm, based on work
by Greenside and Helfand (detailed in the Appendix), to integrate the driven
Langevin equation over a wide range of parameter values. The predictions of LRT
are carefully tested against the results obtained from numerical solutions of
the corresponding Langevin equation over a wide range of parameter values. We
further present an accurate procedure to evaluate the distinct contributions of
the coherent and incoherent parts of the correlation function to the SNR and
the gain. As a main result we show for subthreshold driving that both, the
correlation function and the SNR can deviate substantially from the predictions
of LRT and yet, the gain can be either larger or smaller than unity. In
particular, we find that the gain can exceed unity in the strongly nonlinear
regime which is characterized by weak noise and very slow multifrequency
subthreshold input signals with a small duty cycle. This latter result is in
agreement with recent analogue simulation results by Gingl et al. in Refs. [18,
19].Comment: 22 pages, 5 eps figures, submitted to PR
Unidimensional model of the ad-atom diffusion on a substrate submitted to a standing acoustic wave I. Derivation of the ad-atom motion equation
The effect of a standing acoustic wave on the diffusion of an ad-atom on a
crystalline surface is theoretically studied. We used an unidimensional space
model to study the ad-atom+substrate system. The dynamic equation of the
ad-atom, a Generalized Langevin equation, is analytically derived from the full
Hamiltonian of the ad-atom+substrate system submitted to the acoustic wave. A
detailed analysis of each term of this equation, as well as of their
properties, is presented. Special attention is devoted to the expression of the
effective force induced by the wave on the ad-atom. It has essentially the same
spatial and time dependences as its parent standing acoustic wave
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