Search results for " selection"
showing 10 items of 1271 documents
Artificial intelligence for affective computing : an emotion recognition case study.
2020
This chapter provides an introduction on the benefits of artificial intelligence (Al) techniques for the field of affective computing, through a case study about emotion recognition via brain (electroencephalography EEG) signals. Readers are first pro-vided with a general description of the field, followed by the main models of human affect, with special emphasis to Russell's circumplex model and the pleasur-arousal-dominance (PAD) model. Finally, an AI-based method for the detection of affect elicited via multimedia stimuli is presented. The method combines both connectivity-and channel-based EEG features with a selection method that considerably reduces the dimensionality of the data and …
Stochastic models for wind speed forecasting
2011
Abstract This paper is concerned with the problem of developing a general class of stochastic models for hourly average wind speed time series. The proposed approach has been applied to the time series recorded during 4 years in two sites of Sicily, a region of Italy, and it has attained valuable results in terms both of modelling and forecasting. Moreover, the 24 h predictions obtained employing only 1-month time series are quite similar to those provided by a feed-forward artificial neural network trained on 2 years data.
Stability-Based Model Selection for High Throughput Genomic Data: An Algorithmic Paradigm
2012
Clustering is one of the most well known activities in scien- tific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is the model selection problem, i.e., the identifi- cation of the correct number of clusters in a dataset. In the last decade, a few novel techniques for model selection, representing a sharp departure from previous ones in statistics, have been proposed and gained promi- nence for microarray data analysis. Among those, the stability-based methods are the most robust and best performing in terms of predic- tion, but the slowest in terms of time. Unfortunately…
Relaxation for a Class of Control Systems with Unilateral Constraints
2019
We consider a nonlinear control system involving a maximal monotone map and with a priori feedback. We assume that the control constraint multifunction $U(t,x)$ is nonconvex valued and only lsc in the $x \in \mathbb{R}^{N}$ variable. Using the Q-regularization (in the sense of Cesari) of $U(t,\cdot )$, we introduce a relaxed system. We show that this relaxation process is admissible.
Variability of Classification Results in Data with High Dimensionality and Small Sample Size
2021
The study focuses on the analysis of biological data containing information on the number of genome sequences of intestinal microbiome bacteria before and after antibiotic use. The data have high dimensionality (bacterial taxa) and a small number of records, which is typical of bioinformatics data. Classification models induced on data sets like this usually are not stable and the accuracy metrics have high variance. The aim of the study is to create a preprocessing workflow and a classification model that can perform the most accurate classification of the microbiome into groups before and after the use of antibiotics and lessen the variability of accuracy measures of the classifier. To ev…
Classroom management practices and their associations with children’s mathematics skills in two cultural groups
2014
The aim of the study was to examine the extent to which contextual factors predict children’s mathematics skills in different cognitive domains. The sample consisted of 1734 students from 26 Estonian- and 17 Russian-language schools in Estonia. Mathematics and non-verbal reasoning tests were carried out at the beginning of the third grade. In addition, teachers were asked about their classroom management practices. The results of multilevel modelling showed that applying supportive practices in the classroom contributes to higher achievement in mathematics. Teachers from Estonian- and Russian-language schools were also found to differ with regard to their management practices, and these pra…
Positive selection in development and growth rate regulation genes involved in species divergence of the genus Radix
2015
AbstractBackgroundLife history traits like developmental time, age and size at maturity are directly related to fitness in all organisms and play a major role in adaptive evolution and speciation processes. Comparative genomic or transcriptomic approaches to identify positively selected genes involved in species divergence can help to generate hypotheses on the driving forces behind speciation. Here we use a bottom-up approach to investigate this hypothesis by comparative analysis of orthologous transcripts of four closely related EuropeanRadixspecies.ResultsSnails of the genusRadixoccupy species specific distribution ranges with distinct climatic niches, indicating a potential for natural …
Factors influencing inclusion in digestive cancer clinical trials: A population-based study
2015
Inclusion in a randomized therapeutic trial represents an optimal therapeutic strategy.To determine the influence of demographic characteristics and deprivation on the enrolment of patients in digestive cancer clinical trials.Between 2004 and 2010, 4632 patients were recorded by the Burgundy Digestive Cancer Registry. According to a balancing score, the 136 patients included in a clinical trial were matched with 272 patients who met the eligibility criteria for trials. Deprivation was measured by the ecological European deprivation index. A conditional multivariate logistic regression was performed.Patients aged over 75 years were significantly less likely to be included in clinical trials …
Bayesian versus data driven model selection for microarray data
2014
Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is a particular instance of the model selection problem, i.e., the identification of the correct number of clusters in a dataset. In what follows, for ease of reference, we refer to that instance still as model selection. It is an important part of any statistical analysis. The techniques used for solving it are mainly either Bayesian or data-driven, and are both based on internal knowledge. That is, they use information obtained by processing the input data. A…
Genome-wide detection of signatures of selection in three Valdostana cattle populations
2020
International audience; The Valdostana is a local dual purpose cattle breed developed in Italy. Three populations are recognized within this breed, based on coat colour, production level, morphology and temperament: Valdostana Red Pied (VPR), Valdostana Black Pied (VPN) and Valdostana Chestnut (VCA). Here, we investigated putative genomic regions under selection among these three populations using the Bovine 50K SNP array by combining three different statistical methods based either on allele frequencies (F-ST) or extended haplotype homozygosity (iHS and Rsb). In total, 8, 5 and 8 chromosomes harbouring 13, 13 and 16 genomic regions potentially under selection were identified by at least tw…