Browsing Data Science (DS) by Title
Now showing items 137156 of 165

Regularized optimization methods for convex MINLP problems
(TOP, 20160101)We propose regularized cuttingplane methods for solving mixedinteger nonlinear programming problems with nonsmooth convex objective and constraint functions. The given methods iteratively search for trial points in certain ... 
Resourcesharing in a single server with timevarying capacity
(2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011, 20111231)We investigate the problem of sharing the resources of a single server with timevarying capacity with the objective of minimizing the mean delay. We formulate the resource allocation problem as a Markov Decision Process. ... 
A review on distance based time series classification
(Data Mining and Knowledge Discovery,, 20181101)Time series classification is an increasing research topic due to the vast amount of time series data that is being created over a wide variety of fields. The particularity of the data makes it a challenging task and ... 
Robust combination of the Morris and Sobol methods in complex multidimensional models
(Environmental Modelling and Software, 2019)Conducting global sensitivity analysis using variance decomposition methods in complex simulation models with many input factors is usually unaffordable. An alternative is to first apply a screening method to reduce the ... 
Sample size impact on the categorisation of continuous variables in clinical prediction
(Trends in Mathematics. Research Perspectives CRM Barcelona. Extended Abstracts Fall 2015. Biomedical Big Data; Statistics for Low Dose Radiation Research, 201712)Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous predictor ... 
Scheduling of users with Markovian timevarying transmission rates
(Performance Evaluation Review, 20131231)We address the problem of developing a wellperforming and implementable scheduler of users with wireless connection to the base station. The main feature of such reallife systems is that the quality conditions of the ... 
Sentiment analysis with genetically evolved Gaussian kernels
(GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference, 2019)Sentiment analysis consists of evaluating opinions or statements based on text analysis. Among the methods used to estimate the degree to which a text expresses a certain sentiment are those based on Gaussian Processes. ... 
A simple Bayesian linear excess relative risk model
(20170711)A new Bayesian Poisson relative risk model is proposed for displaying the excess relative risk associated to a unique exposure as a probability distribution in a closed form. The background risk can be modelled by a unique ... 
Smooth additive mixed models for predicting aboveground biomass
(Journal of Agricultural, Biological and Environmental Statistics, 20161201)Aboveground biomass estimation in shortrotation forestry plantations is an essential step in the development of crop management strategies as well as allowing the economic viability of the crop to be determined prior to ... 
Soft information for localizationofthings
(Proceeding of the IEEE, 20191101)Location awareness is vital for emerging Internetof Things applications and opens a new era for Localizationof Things. This paper first reviews the classical localization techniques based on singlevalue metrics, such ... 
Soft range information for network localization
(IEEE Transactions on Signal Processing, 20180615)The demand for accurate localization in complex environments continues to increase despite the difficulty in extracting positional information from measurements. Conventional rangebased localization approaches rely on ... 
Spacecraft Trajectory Optimization: A review of Models, Objectives, Approaches and Solutions
(Progress in Aerospace Sciences, 2018)This article is a survey paper on solving spacecraft trajectory optimization problems. The solving process is decomposed into four key steps of mathematical modeling of the problem, defining the objective functions, ... 
Spatial Models for Field Trials
(20160901)An important aim of the analysis of agricultural field trials is to obtain good predictions for genotypic performance, by correcting for spatial effects. In practice these corrections turn out to be complicated, since there ... 
Spatiotemporal adaptive penalized splines with application to Neuroscience
(20161230)Data analysed here derive from experiments conducted to study neurons' activity in the visual cortex of behaving monkeys. We consider a spatiotemporal adaptive penalized spline (Pspline) approach for modelling the firing ... 
Spatiotemporal functional data analysis for wireless sensor networks data
(Environmetrics, 20150505)A new methodology is proposed for the analysis, modeling, and forecasting of data collected from a wireless sensor network. Our approach is considered in the framework of a functional dataanalysis paradigm where observed ... 
Spatiotemporal information coupling in network navigation
(IEEE Transactions on Information Theory, 201812)Network navigation, encompassing both spatial and temporal cooperation to locate mobile agents, is a key enabler for numerous emerging locationbased applications. In such cooperative networks, the positional information ... 
Stability and asymptotic optimality of opportunistic schedulers in wireless systems
(VALUETOOLS 2011  5th International ICST Conference on Performance Evaluation Methodologies and Tools, 20111231)We investigate the scheduling of a common resource between several concurrent users when the feasible transmission rate of each user varies randomly over time. Time is slotted and users arrive and depart upon service ... 
A statistical framework for radiation dose estimation with uncertainty quantification from the γH2AX assay
(PLoS ONE, 20181128)Over the last decade, the γ–H2AX focus assay, which exploits the phosphorylation of the H2AX histone following DNA double–strand–breaks, has made considerable progress towards acceptance as a reliable biomarker for exposure ... 
Suggestion of reduced cancer risks following cardiac xray exposures is unconvincing
(European Journal of Epidemiology, 20180331) 
Supervised nonparametric discretization based on Kernel density estimation
(Pattern Recognition Letters, 20191219)Nowadays, machine learning algorithms can be found in many applications where the classifiers play a key role. In this context, discretizing continuous attributes is a common step previous to classification tasks, the main ...