Search results for "Bay"
showing 10 items of 1187 documents
Particle Group Metropolis Methods for Tracking the Leaf Area Index
2020
Monte Carlo (MC) algorithms are widely used for Bayesian inference in statistics, signal processing, and machine learning. In this work, we introduce an Markov Chain Monte Carlo (MCMC) technique driven by a particle filter. The resulting scheme is a generalization of the so-called Particle Metropolis-Hastings (PMH) method, where a suitable Markov chain of sets of weighted samples is generated. We also introduce a marginal version for the goal of jointly inferring dynamic and static variables. The proposed algorithms outperform the corresponding standard PMH schemes, as shown by numerical experiments.
A probabilistic compressive sensing framework with applications to ultrasound signal processing
2019
Abstract The field of Compressive Sensing (CS) has provided algorithms to reconstruct signals from a much lower number of measurements than specified by the Nyquist-Shannon theorem. There are two fundamental concepts underpinning the field of CS. The first is the use of random transformations to project high-dimensional measurements onto a much lower-dimensional domain. The second is the use of sparse regression to reconstruct the original signal. This assumes that a sparse representation exists for this signal in some known domain, manifested by a dictionary. The original formulation for CS specifies the use of an l 1 penalised regression method, the Lasso. Whilst this has worked well in l…
Methods of spatial cluster detection in rare childhood cancers: Benchmarking data and results from a simulation study on nephroblastoma
2021
Abstract The potential existence of spatial clusters in childhood cancer incidence is a debated topic. Identification of rare disease clusters in general may help to better understand disease etiology and develop preventive strategies against such entities. The incidence of newly diagnosed childhood malignancies under 15 years of age is 140/1,000,000. In this context, the subgroup of nephroblastoma represents an extremely rare entity with an annual incidence of 7/1,000,000. We evaluated widely used statistical approaches for spatial cluster detection in childhood cancer (Ref. [22] Schundeln et al., 2021, Cancer Epidemiology). For the simulation study, random high risk clusters of 1 to 50 ad…
StalAge – An algorithm designed for construction of speleothem age models
2011
Abstract Here we present a new algorithm ( StalAge ), which is designed to construct speleothem age models. The algorithm uses U-series ages and their corresponding age uncertainty for modelling and also includes stratigraphic information in order to further constrain and improve the age model. StalAge is applicable to problematic datasets that include outliers, age inversions, hiatuses and large changes in growth rate. Manual selection of potentially inaccurate ages prior to application is not required. StalAge can be applied by the general, non-expert user and has no adjustable free parameters. This offers the highest degree of reproducibility and comparability of speleothem records from …
Predictors of school students’ leisure-time physical activity : An extended trans-contextual model using Bayesian path analysis
2021
Abstract Background:The trans-contextual model (TCM) has been applied to identify the determinants of leisure-time physical activity participation in secondary school students. In the current study, the TCM was extended to include additional constructs that represent non-conscious, implicit processes that lead to leisure-time physical activity participation alongside the motivational and social cognition constructs from the TCM. The current study used baseline and follow-up data from an intervention study to test the extended TCM.Methods:The current study adopted a two-wave prospective design. Secondary-school students (N = 502) completed measures of perceived autonomy support from physical…
Contribution of Multi-Agent Systems and Fuzzy logic to support tutors in Learning Communities
2016
The growing importance of online training has put emphasis on the role of remote tutoring. A whole new area of research, dedicated to environment for human learning (EHL), is emerging. We are concerned with this field. More specifically, we will focus on the monitoring of learners.The instrumentation and observation of learners activities by exploiting interaction traces in the EHL and the development of indicators can help tutors to monitor activities of learners and support them in their collaborative learning process. Indeed, in a learning situation, the teacher needs to observe the behavior of learners in order to build an idea about their involvement, preferences and learning styles so…
The covariation between parental and expert evaluations of early language skills
2013
This study investigated the potential interrelationship between parental (maternal) and expert assessments of the expressive and receptive language skills of 12- to 18-month-old children. The language activities of 27 children were monitored by their mothers (MCDI scale: Lyytinen, 2000. Varhaisen kommunikaation ja kielen kehityksen arviointimenetelma. Jyvaskylan yliopiston lapsitutkimuskeskus ja Niilo Maki Instituutti. Jyvaskyla: Yliopistopaino. [An assessment tool for early communication and language development] Jyvaskyla: University Press) and trained researchers (Bayley Scales III: Bayley, 2006. Bayley III Scales of Infant Development. Administration Manual. San Antonio, TX: Psychologic…
Phylogenetic analysis in the clinical risk management of an outbreak of hepatitis C virus infection among transfused thalassaemia patients in Italy
2021
Background: Occurrence of hepatitis C virus (HCV) infection is reduced by effective risk management procedures, but patient-to-patient transmission continues to be reported in healthcare settings. Aim: To report the use of phylogenetic analysis in the clinical risk management of an HCV outbreak among 128 thalassaemia outpatients followed at a thalassaemia centre of an Italian hospital. Methods: Epidemiological investigation and root-cause analysis were performed. All patients with acute hepatitis and known chronic infection were tested for HCV RNA, HCV genotyping, and NS3, NS5A, and NS5B HCV genomic region sequencing. To identify transmission clusters, phylogenetic trees were built for each…
Surface soil water content estimation based on thermal inertia and Bayesian smoothing
2014
Soil water content plays a critical role in agro-hydrology since it regulates the rainfall partition between surface runoff and infiltration and, the energy partition between sensible and latent heat fluxes. Current thermal inertia models characterize the spatial and temporal variability of water content by assuming a sinusoidal behavior of the land surface temperature between subsequent acquisitions. Such behavior implicitly supposes clear sky during the whole interval between the thermal acquisitions; but, since this assumption is not necessarily verified even if sky is clear at the exact epoch of acquisition, , the accuracy of the model may be questioned due to spatial and temporal varia…
Comparing data mining and deterministic pedology to assess the frequency of WRB reference soil groups in the legend of small scale maps
2015
Abstract The assessment of class frequency in soil map legends is affected by uncertainty, especially at small scales where generalization is greater. The aim of this study was to test the hypothesis that data mining techniques provide better estimation of class frequency than traditional deterministic pedology in a national soil map. In the 1:5,000,000 map of Italian soil regions, the soil classes are the WRB reference soil groups (RSGs). Different data mining techniques, namely neural networks, random forests, boosted tree, classification and regression tree, and supported vector machine (SVM), were tested and the last one gave the best RSG predictions using selected auxiliary variables a…