206 research outputs found
Local Popularity and Time in top-N Recommendation
Items popularity is a strong signal in recommendation algorithms. It strongly
affects collaborative filtering approaches and it has been proven to be a very
good baseline in terms of results accuracy. Even though we miss an actual
personalization, global popularity can be effectively used to recommend items
to users. In this paper we introduce the idea of a time-aware personalized
popularity in recommender systems by considering both items popularity among
neighbors and how it changes over time. An experimental evaluation shows a
highly competitive behavior of the proposed approach, compared to state of the
art model-based collaborative approaches, in terms of results accuracy.Comment: ECIR short paper, 7 page
Monitoring the impact of desert dust outbreaks for air quality for health studies
We review the major features of desert dust outbreaks that are relevant to the assessment of dust impacts upon human health. Our ultimate goal is to provide scientific guidance for the acquisition of relevant population exposure information for epidemiological studies tackling the short and long term health effects of desert dust. We first describe the source regions and the typical levels of dust particles in regions close and far away from the source areas, along with their size, composition, and bio-aerosol load. We then describe the processes by which dust may become mixed with anthropogenic particulate matter (PM) and/or alter its load in receptor areas. Short term health effects are found during desert dust episodes in different regions of the world, but in a number of cases the results differ when it comes to associate the effects to the bulk PM, the desert dust-PM, or non-desert dust-PM. These differences are likely due to the different monitoring strategies applied in the epidemiological studies, and to the differences on atmospheric and emission (natural and anthropogenic) patterns of desert dust around the world. We finally propose methods to allow the discrimination of health effects by PM fraction during dust outbreaks, and a strategy to implement desert dust alert and monitoring systems for health studies and air quality management.The systematic review was funded by WHO with as part of a Grant Agreement with Ministry of Foreign Affairs, Norway. Thanks are also given to the Spanish Ministry for the Ecological Transition for long term support in the last 2 decades to our projects on African dust effects on air quality over Spain; to the Spanish Ministry of Science, Innovation and Universities and FEDER Funds for the HOUSE project (CGL2016-78594-R), and to the Generalitat de Catalunya (AGAUR 2017 SGR41). Carlos Pérez García-Pando acknowledges long-term support from the AXA Research Fund, as well as the support received through the Ramón y Cajal program (grant RYC-2015-18690) of the Spanish Ministry of Science, Innovation and Universities.Peer ReviewedPostprint (published version
The influence of quantum dot size on the sub-bandgap intraband photocurrent in intermediate band solar cells
The effect of quantum dot (QD) size on the performance of quantum dot intermediate band solar cells is investigated. A numerical model is used to calculate the bound state energy levels and the absorption coefficient of transitions from the ground state to all other states in the conduction band. Comparing with the current state of the art, strong absorption enhancements are found for smaller quantum dots, as well as a better positioning of the energy levels, which is expected to reduce thermal carrier escape. It is concluded that reducing the quantum dot size can increase sub-bandgap photocurrent and improve voltage preservation
Proximal nested sampling with data-driven priors for physical scientists
Proximal nested sampling was introduced recently to open up Bayesian model
selection for high-dimensional problems such as computational imaging. The
framework is suitable for models with a log-convex likelihood, which are
ubiquitous in the imaging sciences. The purpose of this article is two-fold.
First, we review proximal nested sampling in a pedagogical manner in an attempt
to elucidate the framework for physical scientists. Second, we show how
proximal nested sampling can be extended in an empirical Bayes setting to
support data-driven priors, such as deep neural networks learned from training
data.Comment: 9 pages, 4 figure
Application of tobit regression models in modelling censored epidemiological variables.
[ES] Muchas variables en estudios epidemiológicos corresponden a medidas continuas obtenidas mediante aparatos de medición con determinados límites de detección, produciendo distribuciones censuradas. La censura, a diferencia del truncamiento, se produce por un defecto de los datos de la muestra. La distribución de una variable censurada es una mezcla entre una distribución continua y otra discreta. En este caso, no es adecuado utilizar el modelo de regresión lineal estimado para mínimos cuadrados ordinarios, ya que proporciona estimaciones sesgadas. Con un único punto de censura debe utilizarse el modelo de regresión censurado (modelo tobit), mientras que cuando hay varios puntos de censura se utiliza la generalización de este modelo. La ilustración de estos modelos se presenta a través del análisis de las concentraciones de mercurio medidas en orina, correspondientes al estudio sobre los efectos para la salud de las emisiones de la incineradora de residuos sólidos de Mataró.
[EN] Many variables in epidemiological studies are continuous measures obtained by means of measurement equipments with detection limits, generating censored distributions. The censorship, opposite to the trucation, takes place for a defect of the data of the sample. The distribution of a censored variable is a mixture between a continuous and a categorical distributions. In this case, results from lineal regression models, by means of ordinary least squares, will provide biased estimates. With one only censorhip point the tobit model must be used, while with several censorship points this model's generalization should also be used. The illustration of these models is presented through the analysis of the levels of mercury measured in urine in the study about health effects of a municipal solid-waste incinerator in the county of Mataró (Spain).S
Light intensity enhancement by diffracting structures in solar cells
A simplified three-dimensional study is presented of the light confinement, that is, of the enhancement of the Poynting vector of the electromagnetic radiation of the light inside a solar cell absorbing the light weakly when diffracting structures are used. The model is based on the theory of periodic radiation arrays and is easily applied to one- and two-dimensional diffraction gratings. Realistically wide illumination bundles are considered. The extended nature of illumination severely limits the enhancement capabilities of diffraction structures. Results are compared to those of the more widely used Lambertian light confinement
Realistic performance prediction in nanostructured solar cells as a function of nanostructure dimensionality and density
The behavior of quantum dot, quantum wire, and quantum well InAs/GaAs solar cells is studied with a very simplified model based on experimental results in order to assess their performance as a function of the low bandgap material volume fraction fLOW. The efficiency of structured devices is found to exceed the efficiency of a non-structured GaAs cell, in particular under concentration, when fLOW is high; this condition is easier to achieve with quantum wells. If three different quasi Fermi levels appear with quantum dots the efficiency can be much higher
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