Search results for "ToP"
showing 10 items of 17685 documents
Estudio multidisciplinar de la Muerte Súbita e Inesperada del Lactante en la Comunidad Valenciana. 2006-2017. Estrategia de análisis y prevención
2020
El síndrome de la muerte súbita del lactante (SMSL) define la muerte súbita de un niño menor de un año de edad, que ocurre aparentemente durante el sueño y que permanece sin explicación después de la realización de una minuciosa investigación postmortem, que incluye la autopsia completa, la investigación de las circunstancias de la muerte y la revisión de la historia clínica. La etiopatogenia del SMSL se ha entendido a través de la hipótesis del triple riesgo. Las tasas de incidencia del SMSL, han ido descendiendo drásticamente situándose en la actualidad en 0,2 -0,5 por mil nacimientos vivos, manteniéndose estable en los últimos años. Los factores de riesgo relacionados con el sueño del la…
Fault-proneness of open source software: Exploring its relations to internal software quality and maintenance process
2013
The goal of this study is to explore how fault-proneness of open source software (OSS) could be explained in terms of internal quality attributes and maintenance process metrics. We reviewed earlier studies and performed a multiple case study of eight Java-based projects based on data available in the Source Forge repository. Overall, we studied 342 re- leases of those systems. As is usual, software quality was regarded as a set of internal and external quality attributes. A to- tal of 76 internal quality attributes were measured from the source code of the selected systems via the tool SoftCalc. Two external quality attributes contributing to fault-proneness were in turn obtained from the …
Interface Detection Using a Quenched-Noise Version of the Edwards-Wilkinson Equation
2015
We report here a multipurpose dynamic-interface-based segmentation tool, suitable for segmenting planar, cylindrical, and spherical surfaces in 3D. The method is fast enough to be used conveniently even for large images. Its implementation is straightforward and can be easily realized in many environments. Its memory consumption is low, and the set of parameters is small and easy to understand. The method is based on the Edwards-Wilkinson equation, which is traditionally used to model the equilibrium fluctuations of a propagating interface under the influence of temporally and spatially varying noise. We report here an adaptation of this equation into multidimensional image segmentation, an…
A New Augmented Lagrangian Approach for $L^1$-mean Curvature Image Denoising
2015
Variational methods are commonly used to solve noise removal problems. In this paper, we present an augmented Lagrangian-based approach that uses a discrete form of the L1-norm of the mean curvature of the graph of the image as a regularizer, discretization being achieved via a finite element method. When a particular alternating direction method of multipliers is applied to the solution of the resulting saddle-point problem, this solution reduces to an iterative sequential solution of four subproblems. These subproblems are solved using Newton’s method, the conjugate gradient method, and a partial solution variant of the cyclic reduction method. The approach considered here differs from ex…
Social Collaborative Viewpoint Regression with Explainable Recommendations
2017
A recommendation is called explainable if it not only predicts a numerical rating for an item, but also generates explanations for users' preferences. Most existing methods for explainable recommendation apply topic models to analyze user reviews to provide descriptions along with the recommendations they produce. So far, such methods have neglected user opinions and influences from social relations as a source of information for recommendations, even though these are known to improve the rating prediction. In this paper, we propose a latent variable model, called social collaborative viewpoint regression (sCVR), for predicting item ratings based on user opinions and social relations. To th…
Biased graph walks for RDF graph embeddings
2017
Knowledge Graphs have been recognized as a valuable source for background information in many data mining, information retrieval, natural language processing, and knowledge extraction tasks. However, obtaining a suitable feature vector representation from RDF graphs is a challenging task. In this paper, we extend the RDF2Vec approach, which leverages language modeling techniques for unsupervised feature extraction from sequences of entities. We generate sequences by exploiting local information from graph substructures, harvested by graph walks, and learn latent numerical representations of entities in RDF graphs. We extend the way we compute feature vector representations by comparing twel…
Supporting Institutional Awareness and Academic Advising using Clustered Study Profiles
2017
The purpose of academic advising is to help students with developing educational plans that support their academic career and personal goals, and to provide information and guidance on studies. Planning and management of the students’ study path is the main joint activity in advising. Based on a study log of passed courses, we propose to use robust, prototype-based clustering to identify a set of actual study path profiles. Such profiles identify groups of students with similar progress of studies, whose analysis and interpretation can be used for better institutional awareness and to support evidence-based academic advising. A model of automated academic advising system utilizing the possi…
Determining the number of sources in high-density EEG recordings of event-related potentials by model order selection
2011
To high-density electroencephalography (EEG) recordings, determining the number of sources to separate the signal and the noise subspace is very important. A mostly used criterion is that percentage of variance of raw data explained by the selected principal components composing the signal space should be over 90%. Recently, a model order selection method named as GAP has been proposed. We investigated the two methods by performing independent component analysis (ICA) on the estimated signal subspace, assuming the number of selected principal components composing the signal subspace is equal to the number of sources of brain activities. Through examining wavelet-filtered EEG recordings (128…
Delayed and In-beam Spectroscopy on Francium and Astatine Nuclei at the Proton Drip Line
2011
Delayed and in‐beam spectroscopy on francium and astatine nuclei at and beyond the proton drip line has been performed. In neutron deficient astatine nuclei a shift to deformed shapes as a function of decreasing neutron has been obtained. In neutron deficient francium isotope the same shift is evident.
Methane-oxidizing and photoautotrophic bacteria are major producers in a humic lake with large anoxic hypolimnion
2011
Heterotrophic processes are considered to prevail in lakes with high terrestrial loading and a high content of dissolved organic carbon. However, previous studies have shown abundant methanotrophic bacteria (MOB) and photoautotrophic green sulphur bacteria (GSB) in some boreal lakes. We used genetic and lipid biomarkers to follow the seasonal succession of the abundance and carbon biomass of the major bacterial groups in Lake Mekkojarvi, a small Finnish polyhumic lake with a large anoxic hypolimnion. Biomarkers were based on length heterogeneity analysis of 16S rRNA gene amplification by polymerase chain reaction (PCR) (LH-PCR) and on phospholipid fatty acid (PLFA) analysis. Representative …