A Bayesian Shrinkage Approach for AMMI Models.
da Silva, Carlos Pereira; de Oliveira, Luciano Antonio; Nuvunga, Joel Jorge; Pamplona, Andrezza Kéllen Alves; Balestre, Marcio
2015-01-01
Linear-bilinear models, especially the additive main effects and multiplicative interaction (AMMI) model, are widely applicable to genotype-by-environment interaction (GEI) studies in plant breeding programs. These models allow a parsimonious modeling of GE interactions, retaining a small number of principal components in the analysis. However, one aspect of the AMMI model that is still debated is the selection criteria for determining the number of multiplicative terms required to describe the GE interaction pattern. Shrinkage estimators have been proposed as selection criteria for the GE interaction components. In this study, a Bayesian approach was combined with the AMMI model with shrinkage estimators for the principal components. A total of 55 maize genotypes were evaluated in nine different environments using a complete blocks design with three replicates. The results show that the traditional Bayesian AMMI model produces low shrinkage of singular values but avoids the usual pitfalls in determining the credible intervals in the biplot. On the other hand, Bayesian shrinkage AMMI models have difficulty with the credible interval for model parameters, but produce stronger shrinkage of the principal components, converging to GE matrices that have more shrinkage than those obtained using mixed models. This characteristic allowed more parsimonious models to be chosen, and resulted in models being selected that were similar to those obtained by the Cornelius F-test (α = 0.05) in traditional AMMI models and cross validation based on leave-one-out. This characteristic allowed more parsimonious models to be chosen and more GEI pattern retained on the first two components. The resulting model chosen by posterior distribution of singular value was also similar to those produced by the cross-validation approach in traditional AMMI models. Our method enables the estimation of credible interval for AMMI biplot plus the choice of AMMI model based on direct posterior
A Bayesian Shrinkage Approach for AMMI Models.
Directory of Open Access Journals (Sweden)
Carlos Pereira da Silva
Full Text Available Linear-bilinear models, especially the additive main effects and multiplicative interaction (AMMI model, are widely applicable to genotype-by-environment interaction (GEI studies in plant breeding programs. These models allow a parsimonious modeling of GE interactions, retaining a small number of principal components in the analysis. However, one aspect of the AMMI model that is still debated is the selection criteria for determining the number of multiplicative terms required to describe the GE interaction pattern. Shrinkage estimators have been proposed as selection criteria for the GE interaction components. In this study, a Bayesian approach was combined with the AMMI model with shrinkage estimators for the principal components. A total of 55 maize genotypes were evaluated in nine different environments using a complete blocks design with three replicates. The results show that the traditional Bayesian AMMI model produces low shrinkage of singular values but avoids the usual pitfalls in determining the credible intervals in the biplot. On the other hand, Bayesian shrinkage AMMI models have difficulty with the credible interval for model parameters, but produce stronger shrinkage of the principal components, converging to GE matrices that have more shrinkage than those obtained using mixed models. This characteristic allowed more parsimonious models to be chosen, and resulted in models being selected that were similar to those obtained by the Cornelius F-test (α = 0.05 in traditional AMMI models and cross validation based on leave-one-out. This characteristic allowed more parsimonious models to be chosen and more GEI pattern retained on the first two components. The resulting model chosen by posterior distribution of singular value was also similar to those produced by the cross-validation approach in traditional AMMI models. Our method enables the estimation of credible interval for AMMI biplot plus the choice of AMMI model based on direct
An, Lihua; Fung, Karen Y; Krewski, Daniel
2010-09-01
Spontaneous adverse event reporting systems are widely used to identify adverse reactions to drugs following their introduction into the marketplace. In this article, a James-Stein type shrinkage estimation strategy was developed in a Bayesian logistic regression model to analyze pharmacovigilance data. This method is effective in detecting signals as it combines information and borrows strength across medically related adverse events. Computer simulation demonstrated that the shrinkage estimator is uniformly better than the maximum likelihood estimator in terms of mean squared error. This method was used to investigate the possible association of a series of diabetic drugs and the risk of cardiovascular events using data from the Canada Vigilance Online Database.
Bayesian-based Wavelet Shrinkage for SAR Image Despeckling Using Cycle Spinning
Institute of Scientific and Technical Information of China (English)
ZHANG De-xiang; GAO Qing-wei; CHEN Jun-ning
2006-01-01
A novel and efficient speckle noise reduction algorithm based on Bayesian wavelet shrinkage using cycle spinning is proposed. First, the sub-band decompositions of non-logarithmically transformed SAR images are shown. Then, a Bayesian wavelet shrinkage factor is applied to the decomposed data to estimate noise-free wavelet coefficients. The method is based on the Mixture Gaussian Distributed (MGD) modeling of sub-band coefficients. Finally, multi-resolution wavelet coefficients are reconstructed by wavelet-threshold using cycle spinning. Experimental results show that the proposed despeckling algorithm is possible to achieve an excellent balance between suppresses speckle effectively and preserves as many image details and sharpness as possible. The new method indicated its higher performance than the other speckle noise reduction techniques and minimizing the effect of pseudo-Gibbs phenomena.
Bayesian Inference with Optimal Maps
Moselhy, Tarek A El
2011-01-01
We present a new approach to Bayesian inference that entirely avoids Markov chain simulation, by constructing a map that pushes forward the prior measure to the posterior measure. Existence and uniqueness of a suitable measure-preserving map is established by formulating the problem in the context of optimal transport theory. We discuss various means of explicitly parameterizing the map and computing it efficiently through solution of an optimization problem, exploiting gradient information from the forward model when possible. The resulting algorithm overcomes many of the computational bottlenecks associated with Markov chain Monte Carlo. Advantages of a map-based representation of the posterior include analytical expressions for posterior moments and the ability to generate arbitrary numbers of independent posterior samples without additional likelihood evaluations or forward solves. The optimization approach also provides clear convergence criteria for posterior approximation and facilitates model selectio...
Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping
Directory of Open Access Journals (Sweden)
Xu Shizhong
2011-05-01
Full Text Available Abstract Background The Bayesian shrinkage technique has been applied to multiple quantitative trait loci (QTLs mapping to estimate the genetic effects of QTLs on quantitative traits from a very large set of possible effects including the main and epistatic effects of QTLs. Although the recently developed empirical Bayes (EB method significantly reduced computation comparing with the fully Bayesian approach, its speed and accuracy are limited by the fact that numerical optimization is required to estimate the variance components in the QTL model. Results We developed a fast empirical Bayesian LASSO (EBLASSO method for multiple QTL mapping. The fact that the EBLASSO can estimate the variance components in a closed form along with other algorithmic techniques render the EBLASSO method more efficient and accurate. Comparing with the EB method, our simulation study demonstrated that the EBLASSO method could substantially improve the computational speed and detect more QTL effects without increasing the false positive rate. Particularly, the EBLASSO algorithm running on a personal computer could easily handle a linear QTL model with more than 100,000 variables in our simulation study. Real data analysis also demonstrated that the EBLASSO method detected more reasonable effects than the EB method. Comparing with the LASSO, our simulation showed that the current version of the EBLASSO implemented in Matlab had similar speed as the LASSO implemented in Fortran, and that the EBLASSO detected the same number of true effects as the LASSO but a much smaller number of false positive effects. Conclusions The EBLASSO method can handle a large number of effects possibly including both the main and epistatic QTL effects, environmental effects and the effects of gene-environment interactions. It will be a very useful tool for multiple QTL mapping.
Bayesian and maximum likelihood estimation of genetic maps
DEFF Research Database (Denmark)
York, Thomas L.; Durrett, Richard T.; Tanksley, Steven;
2005-01-01
There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods...... that makes the Bayesian method applicable to large data sets. We present an extensive simulation study examining the statistical properties of the method and comparing it with the likelihood method implemented in Mapmaker. We show that the Maximum A Posteriori (MAP) estimator of the genetic distances...
Uncertainty Modeling Based on Bayesian Network in Ontology Mapping
Institute of Scientific and Technical Information of China (English)
LI Yuhua; LIU Tao; SUN Xiaolin
2006-01-01
How to deal with uncertainty is crucial in exact concept mapping between ontologies. This paper presents a new framework on modeling uncertainty in ontologies based on bayesian networks (BN). In our approach, ontology Web language (OWL) is extended to add probabilistic markups for attaching probability information, the source and target ontologies (expressed by patulous OWL) are translated into bayesian networks (BNs), the mapping between the two ontologies can be digged out by constructing the conditional probability tables (CPTs) of the BN using a improved algorithm named I-IPFP based on iterative proportional fitting procedure (IPFP). The basic idea of this framework and algorithm are validated by positive results from computer experiments.
Colombani, C; Legarra, A; Fritz, S; Guillaume, F; Croiseau, P; Ducrocq, V; Robert-Granié, C
2013-01-01
Recently, the amount of available single nucleotide polymorphism (SNP) marker data has considerably increased in dairy cattle breeds, both for research purposes and for application in commercial breeding and selection programs. Bayesian methods are currently used in the genomic evaluation of dairy cattle to handle very large sets of explanatory variables with a limited number of observations. In this study, we applied 2 bayesian methods, BayesCπ and bayesian least absolute shrinkage and selection operator (LASSO), to 2 genotyped and phenotyped reference populations consisting of 3,940 Holstein bulls and 1,172 Montbéliarde bulls with approximately 40,000 polymorphic SNP. We compared the accuracy of the bayesian methods for the prediction of 3 traits (milk yield, fat content, and conception rate) with pedigree-based BLUP, genomic BLUP, partial least squares (PLS) regression, and sparse PLS regression, a variable selection PLS variant. The results showed that the correlations between observed and predicted phenotypes were similar in BayesCπ (including or not pedigree information) and bayesian LASSO for most of the traits and whatever the breed. In the Holstein breed, bayesian methods led to higher correlations than other approaches for fat content and were similar to genomic BLUP for milk yield and to genomic BLUP and PLS regression for the conception rate. In the Montbéliarde breed, no method dominated the others, except BayesCπ for fat content. The better performances of the bayesian methods for fat content in Holstein and Montbéliarde breeds are probably due to the effect of the DGAT1 gene. The SNP identified by the BayesCπ, bayesian LASSO, and sparse PLS regression methods, based on their effect on the different traits of interest, were located at almost the same position on the genome. As the bayesian methods resulted in regressions of direct genomic values on daughter trait deviations closer to 1 than for the other methods tested in this study, bayesian
A Bayesian Algorithm for Functional Mapping of Dynamic Complex Traits
Directory of Open Access Journals (Sweden)
Rongling Wu
2009-04-01
Full Text Available Functional mapping of dynamic traits measured in a longitudinal study was originally derived within the maximum likelihood (ML context and implemented with the EM algorithm. Although ML-based functional mapping possesses many favorable statistical properties in parameter estimation, it may be computationally intractable for analyzing longitudinal data with high dimensions and high measurement errors. In this article, we derive a general functional mapping framework for quantitative trait locus mapping of dynamic traits within the Bayesian paradigm. Markov chain Monte Carlo techniques were implemented for functional mapping to estimate biologically and statistically sensible parameters that model the structures of time-dependent genetic effects and covariance matrix. The Bayesian approach is useful to handle difficulties in constructing confidence intervals as well as the identifiability problem, enhancing the statistical inference of functional mapping. We have undertaken simulation studies to investigate the statistical behavior of Bayesian-based functional mapping and used a real example with F2 mice to validate the utilization and usefulness of the model.
多QTL定位的压缩估计方法%Shrinkage Estimation Method for Mapping Multiple Quantitative Trait Loci
Institute of Scientific and Technical Information of China (English)
章元明
2006-01-01
本文综述了多标记分析和多QTL定位的压缩估计方法.对于前者,Xu(Genetics,2003,163:789-801)首先提出了Bayesian压缩估计方法.其关键在于让每个效应有一个特定的方差参数,而该方差又服从一定的先验分布,以致能从资料中估计之.由此,能够同时估计大量分子标记基因座的遗传效应,即使大多数标记的效应是可忽略的.然而,对于上位性遗传模型,其运算时间还是过长.为此,笔者将上述思想嵌入极大似然法,提出了惩罚最大似然方法.模拟研究显示:该方法能处理变量个数大于样本容量10倍左右的线性遗传模型.对于后者,本文详细介绍了基于固定区间和可变区间的Bayesian压缩估计方法.固定区间方法可处理中等密度的分子标记资料;可变区间方法则可分析高密度分子标记资料,甚至是上位性遗传模型.对于上位性检测,已介绍的惩罚最大似然方法和可变区间Bayesian压缩估计方法可供利用.应当指出,压缩估计方法在今后的eQTL和QTN定位以及基因互作网络分析等研究中也是有应用价值的.%In this article, shrinkage estimation method for multiple-marker analysis and for mapping multiple quantitative trait loci (QTL) was reviewed. For multiple-marker analysis, Xu (Genetics, 2003, 163:789-801) developed a Bayesian shrinkage estimation (BSE) method. The key to the success of this method is to allow each marker effect have its own variance parameter, which in turn has its own prior distribution so that the variance can be estimated from the data. Under this hierarchical model, a large number of markers can be handled although most of them may have negligible effects. Under epistatic genetic model, however, the running time is very long. To overcome this problem, a novel method of incorporating the idea described above into maximum likelihood,known as penalized likelihood method, was proposed. A simulated study showed that this method can
Learning Continuous Time Bayesian Network Classifiers Using MapReduce
Directory of Open Access Journals (Sweden)
Simone Villa
2014-12-01
Full Text Available Parameter and structural learning on continuous time Bayesian network classifiers are challenging tasks when you are dealing with big data. This paper describes an efficient scalable parallel algorithm for parameter and structural learning in the case of complete data using the MapReduce framework. Two popular instances of classifiers are analyzed, namely the continuous time naive Bayes and the continuous time tree augmented naive Bayes. Details of the proposed algorithm are presented using Hadoop, an open-source implementation of a distributed file system and the MapReduce framework for distributed data processing. Performance evaluation of the designed algorithm shows a robust parallel scaling.
MAP estimators and their consistency in Bayesian nonparametric inverse problems
Dashti, M.; Law, K. J. H.; Stuart, A. M.; Voss, J.
2013-09-01
We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map {G} applied to u. We adopt a Bayesian approach to the problem and work in a setting where the prior measure is specified as a Gaussian random field μ0. We work under a natural set of conditions on the likelihood which implies the existence of a well-posed posterior measure, μy. Under these conditions, we show that the maximum a posteriori (MAP) estimator is well defined as the minimizer of an Onsager-Machlup functional defined on the Cameron-Martin space of the prior; thus, we link a problem in probability with a problem in the calculus of variations. We then consider the case where the observational noise vanishes and establish a form of Bayesian posterior consistency for the MAP estimator. We also prove a similar result for the case where the observation of {G}(u) can be repeated as many times as desired with independent identically distributed noise. The theory is illustrated with examples from an inverse problem for the Navier-Stokes equation, motivated by problems arising in weather forecasting, and from the theory of conditioned diffusions, motivated by problems arising in molecular dynamics.
MAP estimators and their consistency in Bayesian nonparametric inverse problems
Dashti, M.
2013-09-01
We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map applied to u. We adopt a Bayesian approach to the problem and work in a setting where the prior measure is specified as a Gaussian random field μ0. We work under a natural set of conditions on the likelihood which implies the existence of a well-posed posterior measure, μy. Under these conditions, we show that the maximum a posteriori (MAP) estimator is well defined as the minimizer of an Onsager-Machlup functional defined on the Cameron-Martin space of the prior; thus, we link a problem in probability with a problem in the calculus of variations. We then consider the case where the observational noise vanishes and establish a form of Bayesian posterior consistency for the MAP estimator. We also prove a similar result for the case where the observation of can be repeated as many times as desired with independent identically distributed noise. The theory is illustrated with examples from an inverse problem for the Navier-Stokes equation, motivated by problems arising in weather forecasting, and from the theory of conditioned diffusions, motivated by problems arising in molecular dynamics. © 2013 IOP Publishing Ltd.
A Bayesian approach to traffic light detection and mapping
Hosseinyalamdary, Siavash; Yilmaz, Alper
2017-03-01
Automatic traffic light detection and mapping is an open research problem. The traffic lights vary in color, shape, geolocation, activation pattern, and installation which complicate their automated detection. In addition, the image of the traffic lights may be noisy, overexposed, underexposed, or occluded. In order to address this problem, we propose a Bayesian inference framework to detect and map traffic lights. In addition to the spatio-temporal consistency constraint, traffic light characteristics such as color, shape and height is shown to further improve the accuracy of the proposed approach. The proposed approach has been evaluated on two benchmark datasets and has been shown to outperform earlier studies. The results show that the precision and recall rates for the KITTI benchmark are 95.78 % and 92.95 % respectively and the precision and recall rates for the LARA benchmark are 98.66 % and 94.65 % .
Mapping malaria risk in Bangladesh using Bayesian geostatistical models.
Reid, Heidi; Haque, Ubydul; Clements, Archie C A; Tatem, Andrew J; Vallely, Andrew; Ahmed, Syed Masud; Islam, Akramul; Haque, Rashidul
2010-10-01
Background malaria-control programs are increasingly dependent on accurate risk maps to effectively guide the allocation of interventions and resources. Advances in model-based geostatistics and geographical information systems (GIS) have enabled researchers to better understand factors affecting malaria transmission and thus, more accurately determine the limits of malaria transmission globally and nationally. Here, we construct Plasmodium falciparum risk maps for Bangladesh for 2007 at a scale enabling the malaria-control bodies to more accurately define the needs of the program. A comprehensive malaria-prevalence survey (N = 9,750 individuals; N = 354 communities) was carried out in 2007 across the regions of Bangladesh known to be endemic for malaria. Data were corrected to a standard age range of 2 to less than 10 years. Bayesian geostatistical logistic regression models with environmental covariates were used to predict P. falciparum prevalence for 2- to 10-year-old children (PfPR(2-10)) across the endemic areas of Bangladesh. The predictions were combined with gridded population data to estimate the number of individuals living in different endemicity classes. Across the endemic areas, the average PfPR(2-10) was 3.8%. Environmental variables selected for prediction were vegetation cover, minimum temperature, and elevation. Model validation statistics revealed that the final Bayesian geostatistical model had good predictive ability. Risk maps generated from the model showed a heterogeneous distribution of PfPR(2-10) ranging from 0.5% to 50%; 3.1 million people were estimated to be living in areas with a PfPR(2-10) greater than 1%. Contemporary GIS and model-based geostatistics can be used to interpolate malaria risk in Bangladesh. Importantly, malaria risk was found to be highly varied across the endemic regions, necessitating the targeting of resources to reduce the burden in these areas.
Macnab, Ying C
2009-04-30
This paper presents Bayesian multivariate disease mapping and ecological regression models that take into account errors in covariates. Bayesian hierarchical formulations of multivariate disease models and covariate measurement models, with related methods of estimation and inference, are developed as an integral part of a Bayesian disability adjusted life years (DALYs) methodology for the analysis of multivariate disease or injury data and associated ecological risk factors and for small area DALYs estimation, inference, and mapping. The methodology facilitates the estimation of multivariate small area disease and injury rates and associated risk effects, evaluation of DALYs and 'preventable' DALYs, and identification of regions to which disease or injury prevention resources may be directed to reduce DALYs. The methodology interfaces and intersects the Bayesian disease mapping methodology and the global burden of disease framework such that the impact of disease, injury, and risk factors on population health may be evaluated to inform community health, health needs, and priority considerations for disease and injury prevention. A burden of injury study on road traffic accidents in local health areas in British Columbia, Canada, is presented as an illustrative example.
Energy Technology Data Exchange (ETDEWEB)
Terwilliger, Thomas C [Los Alamos National Laboratory; Adams, Paul D [LBNL; Read, Randy J [UNIV OF CAMBRIDGE; Mccoy, Airlie J [UNIV OF CAMBRIDGE
2008-01-01
Ten measures of experimental electron-density-map quality are examined and the skewness of electron density is found to be the best indicator of actual map quality. A Bayesian approach to estimating map quality is developed and used in the PHENIX AutoSol wizard to make decisions during automated structure solution.
GENERALIZED DOUBLE PARETO SHRINKAGE.
Armagan, Artin; Dunson, David B; Lee, Jaeyong
2013-01-01
We propose a generalized double Pareto prior for Bayesian shrinkage estimation and inferences in linear models. The prior can be obtained via a scale mixture of Laplace or normal distributions, forming a bridge between the Laplace and Normal-Jeffreys' priors. While it has a spike at zero like the Laplace density, it also has a Student's t-like tail behavior. Bayesian computation is straightforward via a simple Gibbs sampling algorithm. We investigate the properties of the maximum a posteriori estimator, as sparse estimation plays an important role in many problems, reveal connections with some well-established regularization procedures, and show some asymptotic results. The performance of the prior is tested through simulations and an application.
Detecting coevolving amino acid sites using Bayesian mutational mapping
DEFF Research Database (Denmark)
Dimmic, Matthew W.; Hubisz, Melissa J.; Bustamente, Carlos D.
2005-01-01
Motivation: The evolution of protein sequences is constrained by complex interactions between amino acid residues. Because harmful substitutions may be compensated for by other substitutions at neighboring sites, residues can coevolve. We describe a Bayesian phylogenetic approach to the detection...... sites in PGK resulted in a less discriminating test, yielding a marked increase in the number of reported positives at both contact and non-contact sites....
Brus, D.J.; Bogaert, P.; Heuvelink, G.B.M.
2008-01-01
Bayesian Maximum Entropy was used to estimate the probabilities of occurrence of soil categories in the Netherlands, and to simulate realizations from the associated multi-point pdf. Besides the hard observations (H) of the categories at 8369 locations, the soil map of the Netherlands 1:50 000 was u
Landslide hazards mapping using uncertain Naïve Bayesian classification method
Institute of Scientific and Technical Information of China (English)
毛伊敏; 张茂省; 王根龙; 孙萍萍
2015-01-01
Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naïve Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Naïve Bayesian classification method in Baota district of Yan’an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Naïve Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves (AUC) in NBU and Naïve Bayesian algorithm are 87.29%and 82.47%respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.
On Bayesian shared component disease mapping and ecological regression with errors in covariates.
MacNab, Ying C
2010-05-20
Recent literature on Bayesian disease mapping presents shared component models (SCMs) for joint spatial modeling of two or more diseases with common risk factors. In this study, Bayesian hierarchical formulations of shared component disease mapping and ecological models are explored and developed in the context of ecological regression, taking into consideration errors in covariates. A review of multivariate disease mapping models (MultiVMs) such as the multivariate conditional autoregressive models that are also part of the more recent Bayesian disease mapping literature is presented. Some insights into the connections and distinctions between the SCM and MultiVM procedures are communicated. Important issues surrounding (appropriate) formulation of shared- and disease-specific components, consideration/choice of spatial or non-spatial random effects priors, and identification of model parameters in SCMs are explored and discussed in the context of spatial and ecological analysis of small area multivariate disease or health outcome rates and associated ecological risk factors. The methods are illustrated through an in-depth analysis of four-variate road traffic accident injury (RTAI) data: gender-specific fatal and non-fatal RTAI rates in 84 local health areas in British Columbia (Canada). Fully Bayesian inference via Markov chain Monte Carlo simulations is presented.
Johnson, Eric D; Tubau, Elisabet
2016-09-27
Presenting natural frequencies facilitates Bayesian inferences relative to using percentages. Nevertheless, many people, including highly educated and skilled reasoners, still fail to provide Bayesian responses to these computationally simple problems. We show that the complexity of relational reasoning (e.g., the structural mapping between the presented and requested relations) can help explain the remaining difficulties. With a non-Bayesian inference that required identical arithmetic but afforded a more direct structural mapping, performance was universally high. Furthermore, reducing the relational demands of the task through questions that directed reasoners to use the presented statistics, as compared with questions that prompted the representation of a second, similar sample, also significantly improved reasoning. Distinct error patterns were also observed between these presented- and similar-sample scenarios, which suggested differences in relational-reasoning strategies. On the other hand, while higher numeracy was associated with better Bayesian reasoning, higher-numerate reasoners were not immune to the relational complexity of the task. Together, these findings validate the relational-reasoning view of Bayesian problem solving and highlight the importance of considering not only the presented task structure, but also the complexity of the structural alignment between the presented and requested relations.
Bayesian analysis of log Gaussian Cox processes for disease mapping
DEFF Research Database (Denmark)
Benes, Viktor; Bodlák, Karel; Møller, Jesper;
We consider a data set of locations where people in Central Bohemia have been infected by tick-borne encephalitis, and where population census data and covariates concerning vegetation and altitude are available. The aims are to estimate the risk map of the disease and to study the dependence...
Bayesian Localization and Mapping Using GNSS SNR Measurements
2014-05-01
are with Department of Electrical and Computer Engineering, University of Cal- ifornia, Santa Barbara {jtisaacs, andrewirish, madhow, hespanha...ece.ucsb.edu 2F. Quitin is with the School of Electrical and Electronic Engineering, Nanyang Technological University,fquitin@ntu.edu.sg NLOS Low SNR LOS...building. The proposed algorithm pushes the particles away from the building and back on the sidewalk near the true path. Additionally, the resulting map
Automated soil resources mapping based on decision tree and Bayesian predictive modeling
Institute of Scientific and Technical Information of China (English)
周斌; 张新刚; 王人潮
2004-01-01
This article presents two approaches for automated building of knowledge bases of soil resources mapping.These methods used decision tree and Bayesian predictive modeling, respectively to generate knowledge from training data.With these methods, building a knowledge base for automated soil mapping is easier than using the conventional knowledge acquisition approach. The knowledge bases built by these two methods were used by the knowledge classifier for soil type classification of the Longyou area, Zhejiang Province, China using TM hi-temporal imageries and GIS data. To evaluate the performance of the resultant knowledge bases, the classification results were compared to existing soil map based on field survey. The accuracy assessment and analysis of the resultant soil maps suggested that the knowledge bases built by these two methods were of good quality for mapping distribution model of soil classes over the study area.
Automated soil resources mapping based on decision tree and Bayesian predictive modeling
Institute of Scientific and Technical Information of China (English)
周斌; 张新刚; 王人潮
2004-01-01
This article presents two approaches for automated building of knowledge bases of soil resources mapping.These methods used decision tree and Bayesian predictive modeling,respectively to generate knowledge from training data.With these methods,building a knowledge base for automated soil mapping is easier than using the conventional knowledge acquisition approach.The knowledge bases built by these two methods were used by the knowledge classifier for soil type classification of the Longyou area,Zhejiang Province,China using TM bi-temporal imageries and GIS data.To evaluate the performance of the resultant knowledge bases,the classification results were compared to existing soil map based on field survey.The accuracy assessment and analysis of the resultant soil maps suggested that the knowledge bases built by these two methods were of good quality for mapping distribution model of soil classes over the study area.
Energy Technology Data Exchange (ETDEWEB)
Terwilliger, T. C.; Adams, P. D.; Read, R. J.; McCoy, A. J.; Moriarty, Nigel W.; Grosse-Kunstleve, R. W.; Afonine, P. V.; Zwart, P. H.; Hung, L.-W.
2009-03-01
Estimates of the quality of experimental maps are important in many stages of structure determination of macromolecules. Map quality is defined here as the correlation between a map and the map calculated based on a final refined model. Here we examine 10 different measures of experimental map quality using a set of 1359 maps calculated by reanalysis of 246 solved MAD, SAD, and MIR datasets. A simple Bayesian approach to estimation of map quality from one or more measures is presented. We find that a Bayesian estimator based on the skew of histograms of electron density is the most accurate of the 10 individual Bayesian estimators of map quality examined, with a correlation between estimated and actual map quality of 0.90. A combination of the skew of electron density with the local correlation of rms density gives a further improvement in estimating map quality, with an overall correlation coefficient of 0.92. The PHENIX AutoSol Wizard carries out automated structure solution based on any combination of SAD, MAD, SIR, or MIR datasets. The Wizard is based on tools from the PHENIX package and uses the Bayesian estimates of map quality described here to choose the highest-quality solutions after experimental phasing.
A hierarchical Bayesian-MAP approach to inverse problems in imaging
Raj, Raghu G.
2016-07-01
We present a novel approach to inverse problems in imaging based on a hierarchical Bayesian-MAP (HB-MAP) formulation. In this paper we specifically focus on the difficult and basic inverse problem of multi-sensor (tomographic) imaging wherein the source object of interest is viewed from multiple directions by independent sensors. Given the measurements recorded by these sensors, the problem is to reconstruct the image (of the object) with a high degree of fidelity. We employ a probabilistic graphical modeling extension of the compound Gaussian distribution as a global image prior into a hierarchical Bayesian inference procedure. Since the prior employed by our HB-MAP algorithm is general enough to subsume a wide class of priors including those typically employed in compressive sensing (CS) algorithms, HB-MAP algorithm offers a vehicle to extend the capabilities of current CS algorithms to include truly global priors. After rigorously deriving the regression algorithm for solving our inverse problem from first principles, we demonstrate the performance of the HB-MAP algorithm on Monte Carlo trials and on real empirical data (natural scenes). In all cases we find that our algorithm outperforms previous approaches in the literature including filtered back-projection and a variety of state-of-the-art CS algorithms. We conclude with directions of future research emanating from this work.
Institute of Scientific and Technical Information of China (English)
LIU; Jianfeng; ZHANG; Yuan; ZHANG; Qin; WANG; Lixian; ZHANG; Jigang
2006-01-01
It is a challenging issue to map Quantitative Trait Loci (QTL) underlying complex discrete traits, which usually show discontinuous distribution and less information, using conventional statistical methods. Bayesian-Markov chain Monte Carlo (Bayesian-MCMC) approach is the key procedure in mapping QTL for complex binary traits, which provides a complete posterior distribution for QTL parameters using all prior information. As a consequence, Bayesian estimates of all interested variables can be obtained straightforwardly basing on their posterior samples simulated by the MCMC algorithm. In our study, utilities of Bayesian-MCMC are demonstrated using simulated several animal outbred full-sib families with different family structures for a complex binary trait underlied by both a QTL and polygene. Under the Identity-by-Descent-Based variance component random model, three samplers basing on MCMC, including Gibbs sampling, Metropolis algorithm and reversible jump MCMC, were implemented to generate the joint posterior distribution of all unknowns so that the QTL parameters were obtained by Bayesian statistical inferring. The results showed that Bayesian-MCMC approach could work well and robust under different family structures and QTL effects. As family size increases and the number of family decreases, the accuracy of the parameter estimates will be improved. When the true QTL has a small effect, using outbred population experiment design with large family size is the optimal mapping strategy.
Compressed sensing recovery via nonconvex shrinkage penalties
Woodworth, Joseph; Chartrand, Rick
2016-07-01
The {{\\ell }}0 minimization of compressed sensing is often relaxed to {{\\ell }}1, which yields easy computation using the shrinkage mapping known as soft thresholding, and can be shown to recover the original solution under certain hypotheses. Recent work has derived a general class of shrinkages and associated nonconvex penalties that better approximate the original {{\\ell }}0 penalty and empirically can recover the original solution from fewer measurements. We specifically examine p-shrinkage and firm thresholding. In this work, we prove that given data and a measurement matrix from a broad class of matrices, one can choose parameters for these classes of shrinkages to guarantee exact recovery of the sparsest solution. We further prove convergence of the algorithm iterative p-shrinkage (IPS) for solving one such relaxed problem.
Segmentation of B-mode cardiac ultrasound data by Bayesian Probability Maps.
Hansson, Mattias; Brandt, Sami S; Lindström, Johan; Gudmundsson, Petri; Jujić, Amra; Malmgren, Andreas; Cheng, Yuanji
2014-10-01
In this paper we present a model for describing the position distribution of the endocardium in the two-chamber apical long-axis view of the heart in clinical B-mode ultrasound cycles. We propose a novel Bayesian formulation, including priors for spatial and temporal smoothness, and preferred shapes and position. The shape model takes into account both endocardium, atrial region and apex. The likelihood is built using a statistical signal model, which attempts to closely model a censored signal. In addition, the use of a censored Gamma mixture model with unknown censoring point, to handle artefacts resulting from left-censoring of the in US clinical B-mode, is to our knowledge novel. The posterior density is sampled by the Gibbs method to estimate the expected latent variable representation of the endocardium, which we call the Bayesian Probability Map; the map describes the probability of pixels being classified as being within the endocardium. The regularization parameters of the model are estimated by cross-validation, and the results are compared against the two-chamber apical model of Chen et al.
Institute of Scientific and Technical Information of China (English)
CHI Wen-xue; WANG Jin-feng; LI Xin-hu; ZHENG Xiao-ying; LIAO Yi-lan
2007-01-01
Objective: To estimate the prevalence rates of neural tube defects (NTDs) in Heshun County, Shanxi Province, China by Bayesian smoothing technique. Methods: A total of 80 infants in the study area who were diagnosed with NTDs were analyzed. Two mapping techniques were then used. Firstly, the GIS software ArcGIS was used to map the crude prevalence rates. Secondly,the data were smoothed by the method of empirical Bayes estimation. Results: The classical statistical approach produced an extremely dishomogeneous map, while the Bayesian map was much smoother and more interpretable. The maps produced by the Bayesian technique indicate the tendency of villages in the southeastern region to produce higher prevalence or risk values. Conclusions: The Bayesian smoothing technique addresses the issue of heterogeneity in the population at risk and it is therefore recommended for use in explorative mapping of birth defects. This approach provides procedures to identify spatial health risk levels and assists in generating hypothesis that will be investigated in further detail.
Institute of Scientific and Technical Information of China (English)
Farid Zayeri; Masoud Salehi; Hasan Pirhosseini
2011-01-01
Objective:To present the geographical map of malaria and identify some of the important environmental factors of this disease in Sistan and Baluchistan province, Iran.Methods:We used the registered malaria data to compute the standard incidence rates (SIRs) of malaria in different areas of Sistan and Baluchistan province for a nine-year period (from 2001 to 2009). Statistical analyses consisted of two different parts: geographical mapping of malaria incidence rates, and modeling the environmental factors. The empirical Bayesian estimates of malaria SIRs were utilized for geographical mapping of malaria and a Poisson random effects model was used for assessing the effect of environmental factors on malaria SIRs.Results:In general, 64 926 new cases of malaria were registered in Sistan and Baluchistan Province from 2001 to 2009. Among them, 42 695 patients (65.8%) were male and 22 231 patients (34.2%) were female. Modeling the environmental factors showed that malaria incidence rates had positive relationship with humidity, elevation, average minimum temperature and average maximum temperature, while rainfall had negative effect on malaria SIRs in this province.Conclusions:The results of the present study reveals that malaria is still a serious health problem in Sistan and Baluchistan province, Iran. Geographical map and related environmental factors of malaria can help the health policy makers to intervene in high risk areas more efficiently and allocate the resources in a proper manner.
Martínez-García, Eric E.; González-Lópezlira, Rosa A.; Magris C., Gladis; Bruzual A., Gustavo
2017-01-01
Stellar masses of galaxies are frequently obtained by fitting stellar population synthesis models to galaxy photometry or spectra. The state of the art method resolves spatial structures within a galaxy to assess the total stellar mass content. In comparison to unresolved studies, resolved methods yield, on average, higher fractions of stellar mass for galaxies. In this work we improve the current method in order to mitigate a bias related to the resolved spatial distribution derived for the mass. The bias consists in an apparent filamentary mass distribution and a spatial coincidence between mass structures and dust lanes near spiral arms. The improved method is based on iterative Bayesian marginalization, through a new algorithm we have named Bayesian Successive Priors (BSP). We have applied BSP to M51 and to a pilot sample of 90 spiral galaxies from the Ohio State University Bright Spiral Galaxy Survey. By quantitatively comparing both methods, we find that the average fraction of stellar mass missed by unresolved studies is only half what previously thought. In contrast with the previous method, the output BSP mass maps bear a better resemblance to near-infrared images.
Regularized brain reading with shrinkage and smoothing
Wehbe, Leila; Ramdas, Aaditya; Steorts, Rebecca C.; Shalizi, Cosma Rohilla
2014-01-01
Functional neuroimaging measures how the brain responds to complex stimuli. However, sample sizes are modest, noise is substantial, and stimuli are high dimensional. Hence, direct estimates are inherently imprecise and call for regularization. We compare a suite of approaches which regularize via shrinkage: ridge regression, the elastic net (a generalization of ridge regression and the lasso), and a hierarchical Bayesian model based on small area estimation (SAE). We contrast regularization w...
Alsing, Justin; Jaffe, Andrew H
2016-01-01
We apply two Bayesian hierarchical inference schemes to infer shear power spectra, shear maps and cosmological parameters from the CFHTLenS weak lensing survey - the first application of this method to data. In the first approach, we sample the joint posterior distribution of the shear maps and power spectra by Gibbs sampling, with minimal model assumptions. In the second approach, we sample the joint posterior of the shear maps and cosmological parameters, providing a new, accurate and principled approach to cosmological parameter inference from cosmic shear data. As a first demonstration on data we perform a 2-bin tomographic analysis to constrain cosmological parameters and investigate the possibility of photometric redshift bias in the CFHTLenS data. Under the baseline $\\Lambda$CDM model we constrain $S_8 = \\sigma_8(\\Omega_\\mathrm{m}/0.3)^{0.5} = 0.67 ^{\\scriptscriptstyle+ 0.03 }_{\\scriptscriptstyle- 0.03 }$ $(68\\%)$, consistent with previous CFHTLenS analysis but in tension with Planck. Adding neutrino m...
Directory of Open Access Journals (Sweden)
Chris Wallace
2015-06-01
Full Text Available Identification of candidate causal variants in regions associated with risk of common diseases is complicated by linkage disequilibrium (LD and multiple association signals. Nonetheless, accurate maps of these variants are needed, both to fully exploit detailed cell specific chromatin annotation data to highlight disease causal mechanisms and cells, and for design of the functional studies that will ultimately be required to confirm causal mechanisms. We adapted a Bayesian evolutionary stochastic search algorithm to the fine mapping problem, and demonstrated its improved performance over conventional stepwise and regularised regression through simulation studies. We then applied it to fine map the established multiple sclerosis (MS and type 1 diabetes (T1D associations in the IL-2RA (CD25 gene region. For T1D, both stepwise and stochastic search approaches identified four T1D association signals, with the major effect tagged by the single nucleotide polymorphism, rs12722496. In contrast, for MS, the stochastic search found two distinct competing models: a single candidate causal variant, tagged by rs2104286 and reported previously using stepwise analysis; and a more complex model with two association signals, one of which was tagged by the major T1D associated rs12722496 and the other by rs56382813. There is low to moderate LD between rs2104286 and both rs12722496 and rs56382813 (r2 ≃ 0:3 and our two SNP model could not be recovered through a forward stepwise search after conditioning on rs2104286. Both signals in the two variant model for MS affect CD25 expression on distinct subpopulations of CD4+ T cells, which are key cells in the autoimmune process. The results support a shared causal variant for T1D and MS. Our study illustrates the benefit of using a purposely designed model search strategy for fine mapping and the advantage of combining disease and protein expression data.
Bayesian mapping of HIV infection among women of reproductive age in Rwanda.
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François Niragire
Full Text Available HIV prevalence is rising and has been consistently higher among women in Rwanda whereas a decreasing national HIV prevalence rate in the adult population has stabilised since 2005. Factors explaining the increased vulnerability of women to HIV infection are not currently well understood. A statistical mapping at smaller geographic units and the identification of key HIV risk factors are crucial for pragmatic and more efficient interventions. The data used in this study were extracted from the 2010 Rwanda Demographic and Health Survey data for 6952 women. A full Bayesian geo-additive logistic regression model was fitted to data in order to assess the effect of key risk factors and map district-level spatial effects on the risk of HIV infection. The results showed that women who had STIs, concurrent sexual partners in the 12 months prior to the survey, a sex debut at earlier age than 19 years, were living in a woman-headed or high-economic status household were significantly associated with a higher risk of HIV infection. There was a protective effect of high HIV knowledge and perception. Women occupied in agriculture, and those residing in rural areas were also associated with lower risk of being infected. This study provides district-level maps of the variation of HIV infection among women of child-bearing age in Rwanda. The maps highlight areas where women are at a higher risk of infection; the aspect that proximate and distal factors alone could not uncover. There are distinctive geographic patterns, although statistically insignificant, of the risk of HIV infection suggesting potential effectiveness of district specific interventions. The results also suggest that changes in sexual behaviour can yield significant results in controlling HIV infection in Rwanda.
Liu, Zengkai; Liu, Yonghong; Wu, Xinlei; Yang, Dongwei; Cai, Baoping; Zheng, Chao
2016-09-01
Bayesian network (BN) is a widely used formalism for representing uncertainty in probabilistic systems and it has become a popular tool in reliability engineering. The GO-FLOW method is a success-oriented system analysis technique and capable of evaluating system reliability and risk. To overcome the limitations of GO-FLOW method and add new method for BN model development, this paper presents a novel approach on constructing a BN from GO-FLOW model. GO-FLOW model involves with several discrete time points and some signals change at different time points. But it is a static system at one time point, which can be described with BN. Therefore, the developed BN with the proposed method in this paper is equivalent to GO-FLOW model at one time point. The equivalent BNs of the fourteen basic operators in the GO-FLOW methodology are developed. Then, the existing GO-FLOW models can be mapped into equivalent BNs on basis of the developed BNs of operators. A case of auxiliary feedwater system of a pressurized water reactor is used to illustrate the method. The results demonstrate that the GO-FLOW chart can be successfully mapped into equivalent BNs.
Sánchez Gil, M. Carmen; Berihuete, Angel; Alfaro, Emilio J.; Pérez, Enrique; Sarro, Luis M.
2015-09-01
One of the fundamental goals of modern Astronomy is to estimate the physical parameters of galaxies from images in different spectral bands. We present a hierarchical Bayesian model for obtaining age maps from images in the Ha line (taken with Taurus Tunable Filter (TTF)), ultraviolet band (far UV or FUV, from GALEX) and infrared bands (24, 70 and 160 microns (μm), from Spitzer). As shown in [1], we present the burst ages for young stellar populations in the nearby and nearly face on galaxy M74. As it is shown in the previous work, the Hα to FUV flux ratio gives a good relative indicator of very recent star formation history (SFH). As a nascent star-forming region evolves, the Ha line emission declines earlier than the UV continuum, leading to a decrease in the HαFUV ratio. Through a specific star-forming galaxy model (Starburst 99, SB99), we can obtain the corresponding theoretical ratio Hα / FUV to compare with our observed flux ratios, and thus to estimate the ages of the observed regions. Due to the nature of the problem, it is necessary to propose a model of high complexity to take into account the mean uncertainties, and the interrelationship between parameters when the Hα / FUV flux ratio mentioned above is obtained. To address the complexity of the model, we propose a Bayesian hierarchical model, where a joint probability distribution is defined to determine the parameters (age, metallicity, IMF), from the observed data, in this case the observed flux ratios Hα / FUV. The joint distribution of the parameters is described through an i.i.d. (independent and identically distributed random variables), generated through MCMC (Markov Chain Monte Carlo) techniques.
A Bayesian and Physics-Based Ground Motion Parameters Map Generation System
Ramirez-Guzman, L.; Quiroz, A.; Sandoval, H.; Perez-Yanez, C.; Ruiz, A. L.; Delgado, R.; Macias, M. A.; Alcántara, L.
2014-12-01
We present the Ground Motion Parameters Map Generation (GMPMG) system developed by the Institute of Engineering at the National Autonomous University of Mexico (UNAM). The system delivers estimates of information associated with the social impact of earthquakes, engineering ground motion parameters (gmp), and macroseismic intensity maps. The gmp calculated are peak ground acceleration and velocity (pga and pgv) and response spectral acceleration (SA). The GMPMG relies on real-time data received from strong ground motion stations belonging to UNAM's networks throughout Mexico. Data are gathered via satellite and internet service providers, and managed with the data acquisition software Earthworm. The system is self-contained and can perform all calculations required for estimating gmp and intensity maps due to earthquakes, automatically or manually. An initial data processing, by baseline correcting and removing records containing glitches or low signal-to-noise ratio, is performed. The system then assigns a hypocentral location using first arrivals and a simplified 3D model, followed by a moment tensor inversion, which is performed using a pre-calculated Receiver Green's Tensors (RGT) database for a realistic 3D model of Mexico. A backup system to compute epicentral location and magnitude is in place. A Bayesian Kriging is employed to combine recorded values with grids of computed gmp. The latter are obtained by using appropriate ground motion prediction equations (for pgv, pga and SA with T=0.3, 0.5, 1 and 1.5 s ) and numerical simulations performed in real time, using the aforementioned RGT database (for SA with T=2, 2.5 and 3 s). Estimated intensity maps are then computed using SA(T=2S) to Modified Mercalli Intensity correlations derived for central Mexico. The maps are made available to the institutions in charge of the disaster prevention systems. In order to analyze the accuracy of the maps, we compare them against observations not considered in the
MacNab, Ying C
2007-11-20
This paper presents a Bayesian disability-adjusted life year (DALY) methodology for spatial and spatiotemporal analyses of disease and/or injury burden. A Bayesian disease mapping model framework, which blends together spatial modelling, shared-component modelling (SCM), temporal modelling, ecological modelling, and non-linear modelling, is developed for small-area DALY estimation and inference. In particular, we develop a model framework that enables SCM as well as multivariate CAR modelling of non-fatal and fatal disease or injury rates and facilitates spline smoothing for non-linear modelling of temporal rate and risk trends. Using British Columbia (Canada) hospital admission-separation data and vital statistics mortality data on non-fatal and fatal road traffic injuries to male population age 20-39 for year 1991-2000 and for 84 local health areas and 16 health service delivery areas, spatial and spatiotemporal estimation and inference on years of life lost due to premature death, years lived with disability, and DALYs are presented. Fully Bayesian estimation and inference, with Markov chain Monte Carlo implementation, are illustrated. We present a methodological framework within which the DALY and the Bayesian disease mapping methodologies interface and intersect. Its development brings the relative importance of premature mortality and disability into the assessment of community health and health needs in order to provide reliable information and evidence for community-based public health surveillance and evaluation, disease and injury prevention, and resource provision.
Directory of Open Access Journals (Sweden)
Gogarten J Peter
2002-02-01
Full Text Available Abstract Background Horizontal gene transfer (HGT played an important role in shaping microbial genomes. In addition to genes under sporadic selection, HGT also affects housekeeping genes and those involved in information processing, even ribosomal RNA encoding genes. Here we describe tools that provide an assessment and graphic illustration of the mosaic nature of microbial genomes. Results We adapted the Maximum Likelihood (ML mapping to the analyses of all detected quartets of orthologous genes found in four genomes. We have automated the assembly and analyses of these quartets of orthologs given the selection of four genomes. We compared the ML-mapping approach to more rigorous Bayesian probability and Bootstrap mapping techniques. The latter two approaches appear to be more conservative than the ML-mapping approach, but qualitatively all three approaches give equivalent results. All three tools were tested on mitochondrial genomes, which presumably were inherited as a single linkage group. Conclusions In some instances of interphylum relationships we find nearly equal numbers of quartets strongly supporting the three possible topologies. In contrast, our analyses of genome quartets containing the cyanobacterium Synechocystis sp. indicate that a large part of the cyanobacterial genome is related to that of low GC Gram positives. Other groups that had been suggested as sister groups to the cyanobacteria contain many fewer genes that group with the Synechocystis orthologs. Interdomain comparisons of genome quartets containing the archaeon Halobacterium sp. revealed that Halobacterium sp. shares more genes with Bacteria that live in the same environment than with Bacteria that are more closely related based on rRNA phylogeny . Many of these genes encode proteins involved in substrate transport and metabolism and in information storage and processing. The performed analyses demonstrate that relationships among prokaryotes cannot be accurately
Dutta, Ritaban; Cohn, Anthony G.; Muggleton, Jen M.
2013-05-01
The successful operation of buried infrastructure within urban environments is fundamental to the conservation of modern living standards. In this paper a novel multi-sensor image fusion framework has been proposed and investigated using dynamic Bayesian network for automatic detection of buried underworld infrastructure. Experimental multi-sensors images were acquired for a known buried plastic water pipe using Vibro-acoustic sensor based location methods and Ground Penetrating Radar imaging system. Computationally intelligent conventional image processing techniques were used to process three types of sensory images. Independently extracted depth and location information from different images regarding the target pipe were fused together using dynamic Bayesian network to predict the maximum probable location and depth of the pipe. The outcome from this study was very encouraging as it was able to detect the target pipe with high accuracy compared with the currently existing pipe survey map. The approach was also applied successfully to produce a best probable 3D buried asset map.
Gil, M Carmen Sánchez; Alfaro, Emilio J; Pérez, Enrique; Sarro, Luis M
2015-01-01
One of the fundamental goals of modern Astronomy is to estimate the physical parameters of galaxies from images in different spectral bands. We present a hierarchical Bayesian model for obtaining age maps from images in the \\Ha\\ line (taken with Taurus Tunable Filter (TTF)), ultraviolet band (far UV or FUV, from GALEX) and infrared bands (24, 70 and 160 microns ($\\mu$m), from Spitzer). As shown in S\\'anchez-Gil et al. (2011), we present the burst ages for young stellar populations in the nearby and nearly face on galaxy M74. As it is shown in the previous work, the \\Ha\\ to FUV flux ratio gives a good relative indicator of very recent star formation history (SFH). As a nascent star-forming region evolves, the \\Ha\\ line emission declines earlier than the UV continuum, leading to a decrease in the \\Ha\\/FUV ratio. Through a specific star-forming galaxy model (Starburst 99, SB99), we can obtain the corresponding theoretical ratio \\Ha\\ / FUV to compare with our observed flux ratios, and thus to estimate the ages of...
Bayesian model choice and search strategies for mapping interacting quantitative trait Loci.
Yi, Nengjun; Xu, Shizhong; Allison, David B
2003-01-01
Most complex traits of animals, plants, and humans are influenced by multiple genetic and environmental factors. Interactions among multiple genes play fundamental roles in the genetic control and evolution of complex traits. Statistical modeling of interaction effects in quantitative trait loci (QTL) analysis must accommodate a very large number of potential genetic effects, which presents a major challenge to determining the genetic model with respect to the number of QTL, their positions, and their genetic effects. In this study, we use the methodology of Bayesian model and variable selection to develop strategies for identifying multiple QTL with complex epistatic patterns in experimental designs with two segregating genotypes. Specifically, we develop a reversible jump Markov chain Monte Carlo algorithm to determine the number of QTL and to select main and epistatic effects. With the proposed method, we can jointly infer the genetic model of a complex trait and the associated genetic parameters, including the number, positions, and main and epistatic effects of the identified QTL. Our method can map a large number of QTL with any combination of main and epistatic effects. Utility and flexibility of the method are demonstrated using both simulated data and a real data set. Sensitivity of posterior inference to prior specifications of the number and genetic effects of QTL is investigated. PMID:14573494
A new approach for supply chain risk management: Mapping SCOR into Bayesian network
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Mahdi Abolghasemi
2015-01-01
Full Text Available Purpose: Increase of costs and complexities in organizations beside the increase of uncertainty and risks have led the managers to use the risk management in order to decrease risk taking and deviation from goals. SCRM has a close relationship with supply chain performance. During the years different methods have been used by researchers in order to manage supply chain risk but most of them are either qualitative or quantitative. Supply chain operation reference (SCOR is a standard model for SCP evaluation which have uncertainty in its metrics. In This paper by combining qualitative and quantitative metrics of SCOR, supply chain performance will be measured by Bayesian Networks. Design/methodology/approach: First qualitative assessment will be done by recognizing uncertain metrics of SCOR model and then by quantifying them, supply chain performance will be measured by Bayesian Networks (BNs and supply chain operations reference (SCOR in which making decision on uncertain variables will be done by predictive and diagnostic capabilities. Findings: After applying the proposed method in one of the biggest automotive companies in Iran, we identified key factors of supply chain performance based on SCOR model through predictive and diagnostic capability of Bayesian Networks. After sensitivity analysis, we find out that ‘Total cost’ and its criteria that include costs of labors, warranty, transportation and inventory have the widest range and most effect on supply chain performance. So, managers should take their importance into account for decision making. We can make decisions simply by running model in different situations. Research limitations/implications: A more precise model consisted of numerous factors but it is difficult and sometimes impossible to solve big models, if we insert all of them in a Bayesian model. We have adopted real world characteristics with our software and method abilities. On the other hand, fewer data exist for some
Wainwright, Haruko M; Seki, Akiyuki; Chen, Jinsong; Saito, Kimiaki
2017-02-01
This paper presents a multiscale data integration method to estimate the spatial distribution of air dose rates in the regional scale around the Fukushima Daiichi Nuclear Power Plant. We integrate various types of datasets, such as ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. The Bayesian method allows us to quantify the uncertainty in the estimates, and to provide the confidence intervals that are critical for robust decision-making. Although this approach is primarily data-driven, it has great flexibility to include mechanistic models for representing radiation transport or other complex correlations. We demonstrate our approach using three types of datasets collected at the same time over Fukushima City in Japan: (1) coarse-resolution airborne surveys covering the entire area, (2) car surveys along major roads, and (3) walk surveys in multiple neighborhoods. Results show that the method can successfully integrate three types of datasets and create an integrated map (including the confidence intervals) of air dose rates over the domain in high resolution. Moreover, this study provides us with various insights into the characteristics of each dataset, as well as radiocaesium distribution. In particular, the urban areas show high heterogeneity in the contaminant distribution due to human activities as well as large discrepancy among different surveys due to such heterogeneity.
Spontaneous shrinkage of vestibular schwannoma
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Rossana Romani
2016-01-01
Conclusion: Early WWR management can be associated with spontaneous shrinkage of VS over time. Prospective clinical study of larger numbers of such cases using the UK VS database may help to identify predictive factors for the spontaneous regression of VS.
Preparation of High Shrinkage Polypropylene
Institute of Scientific and Technical Information of China (English)
吕文军; 王华平; 李建梅; 张玉梅
2001-01-01
The common PP chips have been used to prepare high shrinkage PP fibers with shrinkage in boiling water higher than 50%. Meanwhile, the process conditions on fiber structure and properties have been discussed in detail. With the increase of drawing temperature, the shrinkage in boiling water of the fiber increases at first,and then decreases in the temperature range from 70℃ to 100℃. The better drawing temperature is from 75℃ to 85℃ according to the melt index of the PP material. The shrinkage in boiling water of PP fiber increases with the increase of pump delivery. The orientation factor and crystallinity increase with the increase of drawing temperature. With an increase in drawing temperature,unit-cell numbers and monomer unit numbers in every crystal nucleus tend to increase, but unit volume crystal nucleus tend to reduce.
Mapping brucellosis increases relative to elk density using hierarchical Bayesian models
Cross, Paul C.; Heisey, Dennis M.; Scurlock, Brandon M.; Edwards, William H.; Brennan, Angela; Ebinger, Michael R.
2010-01-01
The relationship between host density and parasite transmission is central to the effectiveness of many disease management strategies. Few studies, however, have empirically estimated this relationship particularly in large mammals. We applied hierarchical Bayesian methods to a 19-year dataset of over 6400 brucellosis tests of adult female elk (Cervus elaphus) in northwestern Wyoming. Management captures that occurred from January to March were over two times more likely to be seropositive than hunted elk that were killed in September to December, while accounting for site and year effects. Areas with supplemental feeding grounds for elk had higher seroprevalence in 1991 than other regions, but by 2009 many areas distant from the feeding grounds were of comparable seroprevalence. The increases in brucellosis seroprevalence were correlated with elk densities at the elk management unit, or hunt area, scale (mean 2070 km2; range = [95–10237]). The data, however, could not differentiate among linear and non-linear effects of host density. Therefore, control efforts that focus on reducing elk densities at a broad spatial scale were only weakly supported. Additional research on how a few, large groups within a region may be driving disease dynamics is needed for more targeted and effective management interventions. Brucellosis appears to be expanding its range into new regions and elk populations, which is likely to further complicate the United States brucellosis eradication program. This study is an example of how the dynamics of host populations can affect their ability to serve as disease reservoirs.
Mapping brucellosis increases relative to elk density using hierarchical Bayesian models.
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Paul C Cross
Full Text Available The relationship between host density and parasite transmission is central to the effectiveness of many disease management strategies. Few studies, however, have empirically estimated this relationship particularly in large mammals. We applied hierarchical Bayesian methods to a 19-year dataset of over 6400 brucellosis tests of adult female elk (Cervus elaphus in northwestern Wyoming. Management captures that occurred from January to March were over two times more likely to be seropositive than hunted elk that were killed in September to December, while accounting for site and year effects. Areas with supplemental feeding grounds for elk had higher seroprevalence in 1991 than other regions, but by 2009 many areas distant from the feeding grounds were of comparable seroprevalence. The increases in brucellosis seroprevalence were correlated with elk densities at the elk management unit, or hunt area, scale (mean 2070 km(2; range = [95-10237]. The data, however, could not differentiate among linear and non-linear effects of host density. Therefore, control efforts that focus on reducing elk densities at a broad spatial scale were only weakly supported. Additional research on how a few, large groups within a region may be driving disease dynamics is needed for more targeted and effective management interventions. Brucellosis appears to be expanding its range into new regions and elk populations, which is likely to further complicate the United States brucellosis eradication program. This study is an example of how the dynamics of host populations can affect their ability to serve as disease reservoirs.
Law, Jane; Quick, Matthew
2013-01-01
This paper adopts a Bayesian spatial modeling approach to investigate the distribution of young offender residences in York Region, Southern Ontario, Canada, at the census dissemination area level. Few geographic researches have analyzed offender (as opposed to offense) data at a large map scale (i.e., using a relatively small areal unit of analysis) to minimize aggregation effects. Providing context is the social disorganization theory, which hypothesizes that areas with economic deprivation, high population turnover, and high ethnic heterogeneity exhibit social disorganization and are expected to facilitate higher instances of young offenders. Non-spatial and spatial Poisson models indicate that spatial methods are superior to non-spatial models with respect to model fit and that index of ethnic heterogeneity, residential mobility (1 year moving rate), and percentage of residents receiving government transfer payments are, respectively, the most significant explanatory variables related to young offender location. These findings provide overwhelming support for social disorganization theory as it applies to offender location in York Region, Ontario. Targeting areas where prevalence of young offenders could or could not be explained by social disorganization through decomposing the estimated risk map are helpful for dealing with juvenile offenders in the region. Results prompt discussion into geographically targeted police services and young offender placement pertaining to risk of recidivism. We discuss possible reasons for differences and similarities between the previous findings (that analyzed offense data and/or were conducted at a smaller map scale) and our findings, limitations of our study, and practical outcomes of this research from a law enforcement perspective.
The soil reference shrinkage curve
Chertkov, V Y
2014-01-01
A recently proposed model showed how a clay shrinkage curve is transformed to the soil shrinkage curve at the soil clay content higher than a critical one. The objective of the present work was to generalize this model to the soil clay content lower a critical one. I investigated (i) the reference shrinkage curve, that is, one without cracks; (ii) the superficial layer of aggregates, with changed pore structure compared with the intraaggregate matrix; and (iii) soils with sufficiently low clay content where there are large pores inside the intraaggregate clay (so-called lacunar pores). The methodology is based on detail accounting for different contributions to the soil volume and water content during shrinkage. The key point is the calculation of the lacunar pore volume variance at shrinkage. The reference shrinkage curve is determined by eight physical soil parameters: (1) oven-dried specific volume; (2) maximum swelling water content; (3) mean solid density; (4) soil clay content; (5) oven-dried structural...
Accounting for PDMS shrinkage when replicating structures
DEFF Research Database (Denmark)
Madsen, Morten Hannibal; Feidenhans'l, Nikolaj Agentoft; Hansen, Poul-Erik
2014-01-01
are seldom applied to counteract the shrinkage of PDMS. Also, to perform metrological measurements using replica techniques one has to take the shrinkage into account. Thus we report a study of the shrinkage of PDMS with several different mixing ratios and curing temperatures. The shrinkage factor, with its...
DEFF Research Database (Denmark)
Ekpo, Uwem F.; Hürlimann, Eveline; Schur, Nadine
2013-01-01
Schistosomiasis prevalence data for Nigeria were extracted from peer-reviewed journals and reports, geo-referenced and collated in a nationwide geographical information system database for the generation of point prevalence maps. This exercise revealed that the disease is endemic in 35 of the cou......Schistosomiasis prevalence data for Nigeria were extracted from peer-reviewed journals and reports, geo-referenced and collated in a nationwide geographical information system database for the generation of point prevalence maps. This exercise revealed that the disease is endemic in 35......% confidence interval (CI): 22.8-23.1%). The model suggests that the mean temperature, annual precipitation and soil acidity significantly influence the spatial distribution. Prevalence estimates, adjusted for school-aged children in 2010, showed that the prevalence is...
Das, Kiranmoy; Li, Jiahan; Fu, Guifang; Wang, Zhong; Li, Runze; Wu, Rongling
2013-02-10
Many phenomena of fundamental importance to biology and biomedicine arise as a dynamic curve, such as organ growth and HIV dynamics. The genetic mapping of these traits is challenged by longitudinal variables measured at irregular and possibly subject-specific time points, in which case nonnegative definiteness of the estimated covariance matrix needs to be guaranteed. We present a semiparametric approach for genetic mapping within the mixture-model setting by jointly modeling mean and covariance structures for irregular longitudinal data. Penalized spline is used to model the mean functions of individual quantitative trait locus (QTL) genotypes as latent variables, whereas an extended generalized linear model is used to approximate the covariance matrix. The parameters for modeling the mean-covariances are estimated by MCMC, using the Gibbs sampler and the Metropolis-Hastings algorithm. We derive the full conditional distributions for the mean and covariance parameters and compute Bayes factors to test the hypothesis about the existence of significant QTLs. We used the model to screen the existence of specific QTLs for age-specific change of body mass index with a sparse longitudinal data set. The new model provides powerful means for broadening the application of genetic mapping to reveal the genetic control of dynamic traits.
Chu, Wei; Ghahramani, Zoubin; Podtelezhnikov, Alexei; Wild, David L
2006-01-01
In this paper, we develop a segmental semi-Markov model (SSMM) for protein secondary structure prediction which incorporates multiple sequence alignment profiles with the purpose of improving the predictive performance. The segmental model is a generalization of the hidden Markov model where a hidden state generates segments of various length and secondary structure type. A novel parameterized model is proposed for the likelihood function that explicitly represents multiple sequence alignment profiles to capture the segmental conformation. Numerical results on benchmark data sets show that incorporating the profiles results in substantial improvements and the generalization performance is promising. By incorporating the information from long range interactions in beta-sheets, this model is also capable of carrying out inference on contact maps. This is an important advantage of probabilistic generative models over the traditional discriminative approach to protein secondary structure prediction. The Web server of our algorithm and supplementary materials are available at http://public.kgi.edu/-wild/bsm.html.
Li, Yan-Rong; Ho, Luis C; Du, Pu; Bai, Jin-Ming
2013-01-01
This is the first paper in a series devoted to systematic study of the size and structure of the broad-line region (BLR) in active galactic nuclei (AGNs) using reverberation mapping (RM) data. We employ a recently developed Bayesian approach that statistically describes the variabibility as a damped random walk process and delineates the BLR structure using a flexible disk geometry that can account for a variety of shapes, including disks, rings, shells, and spheres. We allow for the possibility that the line emission may respond non-linearly to the continuum, and we detrend the light curves when there is clear evidence for secular variation. We use a Markov Chain Monte Carlo implementation based on Bayesian statistics to recover the parameters and uncertainties for the BLR model. The corresponding transfer function is obtained self-consistently. We tentatively constrain the virial factor used to estimate black hole masses; more accurate determinations will have to await velocity-resolved RM data. Application...
Directory of Open Access Journals (Sweden)
Sánchez, J. A.
1997-03-01
Full Text Available Nowadays, the methodology existing to measure the shrinkage in air, developed for paste and cement mortars, has serious problems to be applied to lime mortars, due to its different mechanism of hardening several modifications in Norms UNE 80-113-86 y 80-112-89 make possible the determination of the shrinkage in these traditional mortars.
La metodología existente en la actualidad para la medida de la retracción de secado, desarrollada para las pastas y los morteros de cemento, presenta serios problemas a la hora de su aplicación a los morteros de cal debido a su distinto mecanismo de endurecimiento. Algunas modificaciones de las normas UNE 80-113-86 y 80-112-89 hacen posible la determinación de la retracción en estos morteros tradicionales.
Image Shrinkage Based on Hot-Target Map and Featured Edge Preservation%基于Hot-Target图和特征边缘保持的图像收缩方法
Institute of Scientific and Technical Information of China (English)
梁云; 苏卓; 罗笑南; 王栋
2011-01-01
图像收缩是缩小高分辨率图像以适应不同纵横比小尺寸显示屏幕的过程,关键是收缩后能够凸显图像重要区域,保持连续,避免扭曲.提出一种新的图像收缩方法,该方法首先基于能量失真约束,迭代收缩覆盖图像的四边形网格至目标大小,然后映射,插值目标网格实现图像收缩.能量失真反映了对重要区域的凸显程度、结构的保持效果以及扭曲避免情况,失真越小,目标图像越理想.在该约束下,构成网格的子四边形非均匀收缩,重要度大的收缩小.为准确计算子四边形的重要度,根据图像显著度和边缘构建反映图像重要度的Hot-Target图.最后,通过保持图像直线边,称为特征边缘,避免非均匀收缩引起的边缘扭曲.为提高效率,降低复杂度,该方法由迭代求解线性方程实现.实验结果验证了方法的有效性.%Image shrinkage is the process of reducing image resolution to adapt to display screens with different aspect ratios and different sizes. Its key is to highlight important areas, keep continuity and avoid twists. This paper presents a novel image shrinking method. First, this paper iteratively shrinks the quad mesh covering the original image to the target size under the constraint of energy distortion. Then, this paper obtains the arget image by interpolating and mapping the target mesh. The energy distortion function reflects the effects of highlighting important regions, preserving structure and avoiding twists. Less distortion owns better result. Under the constraint of energy distortion, every sub quad of mesh shrinks non-uniformly. Quads with more importance shrink less. In order to accurately calculate quad's importance, this paper proposes a new method named as Hot-Target map to calculate image importance according to image saliency and edges. Finally, this paper avoids distortion by preserving image linear edges named as featured straight edge. To increase efficiency and
The influence of shrinkage reducing admixtures on plastic shrinkage
Directory of Open Access Journals (Sweden)
Mora, J.
2003-12-01
Full Text Available Shrinkage reducing admixtures (SRAs are viable alternatives for reducing plastic shrinkage cracking in concrete. The objective of the present paper is to study early age plastic shrinkage in restrained concrete elements, where three different SRAs have been used. The influence of the admixture is analyzed through the following measurements: capillary pressure, evaporation, temperature evolution, crack evolution and settlement. The tests for studying the cracking and deformation were made on two different configurations (i.e., restrained prisms with reduced cross-section and restrained panel, in a wind tunnel, with controlled wind temperature and velocity. The conclusions obtained indicate the viability of the use of this type of admixture and the usefulness of the test methods.
Los aditivos reductores de retracción (SRAs se plantean, hoy en día, como una alternativa viable para reducir la fisuración por retracción plástica. El objetivo del presente artículo es conocer mejor y predecir el comportamiento a primeras edades de la retracción plástica en elementos estructurales coaccionados, a los que se les ha añadido diversos aditivos reductores de retracción (tres tipos diferentes. Esta influencia se analiza a través de las siguientes propiedades: presión capilar, evaporación, evolución de temperaturas, evolución de fisuración, y deformaciones verticales de asentamiento. Los ensayos para estudiar la fisuración y las deformaciones se han realizado sobre diferentes configuraciones (prisma restringido con estrangulamiento y panel restringido, en un túnel de viento, con temperaturas y velocidades de viento controladas. Las conclusiones obtenidas señalan la viabilidad del empleo de este tipo de aditivos y la bondad de los métodos experimentales utilizados.
Shrinkage behavior of self-compacting concrete
Institute of Scientific and Technical Information of China (English)
Farhad ASLANI; Shami NEJADI
2012-01-01
In the structures where long-term behavior should be monitored and controlled,creep and shrinkage effects have to be included precisely in the analysis and design procedures.Shrinkage varies with the constituent and mixture proportions,and depends on the curing conditions and the work environment as well.Self-compacting concrete (SCC) contains combinations of various components,such as aggregate,cement,superplasticizer,water-reducing agent and other ingredients which affect the properties of the SCC including shrinkage.Hence,the realistic prediction shrinkage strains of SCC are an important requirement of the design process for this type of concrete structures.This study reviews the accuracy of the conventional concrete (CC) shrinkage prediction models proposed by the international codes of practice,including CEB-FIP (1990),ACI 209R (1997),Eurocode 2 (2001),JSCE (2002),AASHTO (2004; 2007) and AS 3600 (2009).Also,SCC shrinkage prediction models proposed by Poppe and De Schutter (2005),Larson (2007),Cordoba (2007) and Khayat and Long (2010) are reviewed.Further,a new shrinkage prediction model based on the comprehensive analysis on both of the available models,i.e.,the CC and the SCC is proposed.The predicted shrinkage strains are compared with the actual measured shrinkage strains in 165 mixtures of SCC and 21 mixtures of CC.
Tonini, Roberto; Sandri, Laura; Anne Thompson, Mary
2015-06-01
PyBetVH is a completely new, free, open-source and cross-platform software implementation of the Bayesian Event Tree for Volcanic Hazard (BET_VH), a tool for estimating the probability of any magmatic hazardous phenomenon occurring in a selected time frame, accounting for all the uncertainties. New capabilities of this implementation include the ability to calculate hazard curves which describe the distribution of the exceedance probability as a function of intensity (e.g., tephra load) on a grid of points covering the target area. The computed hazard curves are (i) absolute (accounting for the probability of eruption in a given time frame, and for all the possible vent locations and eruptive sizes) and (ii) Bayesian (computed at different percentiles, in order to quantify the epistemic uncertainty). Such curves allow representation of the full information contained in the probabilistic volcanic hazard assessment (PVHA) and are well suited to become a main input to quantitative risk analyses. PyBetVH allows for interactive visualization of both the computed hazard curves, and the corresponding Bayesian hazard/probability maps. PyBetVH is designed to minimize the efforts of end users, making PVHA results accessible to people who may be less experienced in probabilistic methodologies, e.g. decision makers. The broad compatibility of Python language has also allowed PyBetVH to be installed on the VHub cyber-infrastructure, where it can be run online or downloaded at no cost. PyBetVH can be used to assess any type of magmatic hazard from any volcano. Here we illustrate how to perform a PVHA through PyBetVH using the example of analyzing tephra fallout from the Okataina Volcanic Centre (OVC), New Zealand, and highlight the range of outputs that the tool can generate.
Bayesian LASSO, scale space and decision making in association genetics.
Directory of Open Access Journals (Sweden)
Leena Pasanen
Full Text Available LASSO is a penalized regression method that facilitates model fitting in situations where there are as many, or even more explanatory variables than observations, and only a few variables are relevant in explaining the data. We focus on the Bayesian version of LASSO and consider four problems that need special attention: (i controlling false positives, (ii multiple comparisons, (iii collinearity among explanatory variables, and (iv the choice of the tuning parameter that controls the amount of shrinkage and the sparsity of the estimates. The particular application considered is association genetics, where LASSO regression can be used to find links between chromosome locations and phenotypic traits in a biological organism. However, the proposed techniques are relevant also in other contexts where LASSO is used for variable selection.We separate the true associations from false positives using the posterior distribution of the effects (regression coefficients provided by Bayesian LASSO. We propose to solve the multiple comparisons problem by using simultaneous inference based on the joint posterior distribution of the effects. Bayesian LASSO also tends to distribute an effect among collinear variables, making detection of an association difficult. We propose to solve this problem by considering not only individual effects but also their functionals (i.e. sums and differences. Finally, whereas in Bayesian LASSO the tuning parameter is often regarded as a random variable, we adopt a scale space view and consider a whole range of fixed tuning parameters, instead. The effect estimates and the associated inference are considered for all tuning parameters in the selected range and the results are visualized with color maps that provide useful insights into data and the association problem considered. The methods are illustrated using two sets of artificial data and one real data set, all representing typical settings in association genetics.
Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro
2016-01-01
An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas.
Breast specimen shrinkage following formalin fixation
Directory of Open Access Journals (Sweden)
Horn CL
2014-02-01
Full Text Available Christopher L Horn, Christopher Naugler Department of Pathology and Laboratory Medicine, University of Calgary, and Calgary Laboratory Services, Calgary, AB, Canada Abstract: Accurate measurement of primary breast tumors and subsequent surgical margin assessment is critical for pathology reporting and resulting patient therapy. Anecdotal observations from pathology laboratory staff indicate possible shrinkage of breast cancer specimens due to the formalin fixation process. As a result, we conducted a prospective study to investigate the possible shrinkage effects of formalin fixation on breast cancer specimens. The results revealed no significant changes in tumor size, but there were significant changes in the distance to all surgical resection margins from the unfixed to fixed state. This shrinkage effect could interfere with the accuracy of determining distance to margin assessment and tumor-free margin assessment. Thus, changes in these measurements due to the formalin fixation process have the potential to alter treatment options for the patient. Keywords: breast margins, formalin, shrinkage, cancer
A Shrinkage Estimator for Combination of Bioassays
Institute of Scientific and Technical Information of China (English)
Jian Xiong; D.G. Chen; Zhen-hai Yang
2007-01-01
A shrinkage estimator and a maximum likelihood estimator are proposed in this paper for combination of bioassays. The shrinkage estimator is obtained in closed form which incorporates prior information just on the common log relative potency after the homogeneity test for combination of bioassays is accepted. It is a practical improvement over other estimators which require iterative procedure to obtain the estimator for the relative potency. A real data is also used to show the superiorities for the newly-proposed procedures.
Volumetric polymerization shrinkage of contemporary composite resins
Directory of Open Access Journals (Sweden)
Halim Nagem Filho
2007-10-01
Full Text Available The polymerization shrinkage of composite resins may affect negatively the clinical outcome of the restoration. Extensive research has been carried out to develop new formulations of composite resins in order to provide good handling characteristics and some dimensional stability during polymerization. The purpose of this study was to analyze, in vitro, the magnitude of the volumetric polymerization shrinkage of 7 contemporary composite resins (Definite, Suprafill, SureFil, Filtek Z250, Fill Magic, Alert, and Solitaire to determine whether there are differences among these materials. The tests were conducted with precision of 0.1 mg. The volumetric shrinkage was measured by hydrostatic weighing before and after polymerization and calculated by known mathematical equations. One-way ANOVA (a or = 0.05 was used to determine statistically significant differences in volumetric shrinkage among the tested composite resins. Suprafill (1.87±0.01 and Definite (1.89±0.01 shrank significantly less than the other composite resins. SureFil (2.01±0.06, Filtek Z250 (1.99±0.03, and Fill Magic (2.02±0.02 presented intermediate levels of polymerization shrinkage. Alert and Solitaire presented the highest degree of polymerization shrinkage. Knowing the polymerization shrinkage rates of the commercially available composite resins, the dentist would be able to choose between using composite resins with lower polymerization shrinkage rates or adopting technical or operational procedures to minimize the adverse effects deriving from resin contraction during light-activation.
Influence of Shrinkage-Reducing Admixtures on the Development of Plastic Shrinkage Cracks
DEFF Research Database (Denmark)
Lura, Pietro; Pease, Bradley Justin; Mazzotta, Guy;
2007-01-01
settlement of the concrete and tensile stress development in the surface of the concrete, which increase the potential for development of plastic shrinkage cracks. Specifically, this paper studies the development of plastic shrinkage cracks in mortars containing a commercially available shrinkage......-reducing admixture (SRA). Mortars containing SRA show fewer and narrower plastic shrinkage cracks than plain mortars when exposed to the same environmental conditions. It is proposed that the lower surface tension of the pore fluid in the mortars containing SRA results in less evaporation, reduced settlement......, reduced capillary tension, and lower crack-inducing stresses at the topmost layer of the mortar....
Development of novel low shrinkage dental nanocomposite
Sun, Yi; Wu, Xiaorong; Liu, Yanju; Xie, Weili; Sun, Shouhua
2009-07-01
It has been the focus to develop low shrinkage dental composite resins in recent ten years. A major difficulty in developing low shrinkage dental materials is their deficiency in mechanical properties to clinical use. This paper reviews the present investigations of low shrinkage dental composite resins and attempts to develop a novel system with multifunctional POSS incorporated. In this paper, it is especially interesting to evaluate the influences of shrinkage with different weight percentage of POSS (0~15wt%) incorporated in dental composite resins. Their double bond conversions are evaluated and their microstructures are characterized with Fourier-transform infra-red spectroscopy and X-ray diffraction. Their mechanical properties are also presented in this paper. The results show that the shrinkage of nanocomposites with POSS can be reduced effectively from 3.53% to 2.18%. The mechanical properties of this novel system, such as strength, hardness and toughness, are also enhanced greatly. Especially with 2wt%POSS incorporated, the best integrative improved effects are revealed. The mechanism of shrinkage is discussed.
Lesaffre, Emmanuel
2012-01-01
The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets. Through examples, exercises and a combination of introd
Fytilis, N.; Rizzo, D. M.
2012-12-01
Environmental managers are increasingly required to forecast the long-term effects and the resilience or vulnerability of biophysical systems to human-generated stresses. Mitigation strategies for hydrological and environmental systems need to be assessed in the presence of uncertainty. An important aspect of such complex systems is the assessment of variable uncertainty on the model response outputs. We develop a new classification tool that couples a Naïve Bayesian Classifier with a modified Kohonen Self-Organizing Map to tackle this challenge. For proof-of-concept, we use rapid geomorphic and reach-scale habitat assessments data from over 2500 Vermont stream reaches (~1371 stream miles) assessed by the Vermont Agency of Natural Resources (VTANR). In addition, the Vermont Department of Environmental Conservation (VTDEC) estimates stream habitat biodiversity indices (macro-invertebrates and fish) and a variety of water quality data. Our approach fully utilizes the existing VTANR and VTDEC data sets to improve classification of stream-reach habitat and biological integrity. The combined SOM-Naïve Bayesian architecture is sufficiently flexible to allow for continual updates and increased accuracy associated with acquiring new data. The Kohonen Self-Organizing Map (SOM) is an unsupervised artificial neural network that autonomously analyzes properties inherent in a given a set of data. It is typically used to cluster data vectors into similar categories when a priori classes do not exist. The ability of the SOM to convert nonlinear, high dimensional data to some user-defined lower dimension and mine large amounts of data types (i.e., discrete or continuous, biological or geomorphic data) makes it ideal for characterizing the sensitivity of river networks in a variety of contexts. The procedure is data-driven, and therefore does not require the development of site-specific, process-based classification stream models, or sets of if-then-else rules associated with
新家, 健精
2013-01-01
© 2012 Springer Science+Business Media, LLC. All rights reserved. Article Outline: Glossary Definition of the Subject and Introduction The Bayesian Statistical Paradigm Three Examples Comparison with the Frequentist Statistical Paradigm Future Directions Bibliography
Asmarian, Naeimehossadat; Jafari-Koshki, Tohid; Soleimani, Ali; Taghi Ayatollahi, Seyyed Mohammad
2016-10-01
Background: In many countries gastric cancer has the highest incidence among the gastrointestinal cancers and is the second most common cancer in Iran. The aim of this study was to identify and map high risk gastric cancer regions at the county-level in Iran. Methods: In this study we analyzed gastric cancer data for Iran in the years 2003-2010. Areato- area Poisson kriging and Besag, York and Mollie (BYM) spatial models were applied to smoothing the standardized incidence ratios of gastric cancer for the 373 counties surveyed in this study. The two methods were compared in term of accuracy and precision in identifying high risk regions. Result: The highest smoothed standardized incidence rate (SIR) according to area-to-area Poisson kriging was in Meshkinshahr county in Ardabil province in north-western Iran (2.4,SD=0.05), while the highest smoothed standardized incidence rate (SIR) according to the BYM model was in Ardabil, the capital of that province (2.9,SD=0.09). Conclusion: Both methods of mapping, ATA Poisson kriging and BYM, showed the gastric cancer incidence rate to be highest in north and north-west Iran. However, area-to-area Poisson kriging was more precise than the BYM model and required less smoothing. According to the results obtained, preventive measures and treatment programs should be focused on particular counties of Iran.
Bisschop, J.; Van Mier, J.C.M.
1999-01-01
In this paper a method is described to quantify shrinkage microcracking in young mortar by means of crack mapping. Visualisation of the microcracks is realised with two techniques: Fluorescence Light Microscopy (FLM) and Environmental Scanning Electron Microscopy (ESEM). The preliminary results obta
Denoising of Mechanical Vibration Signals Using Quantum-Inspired Adaptive Wavelet Shrinkage
Directory of Open Access Journals (Sweden)
Yan-long Chen
2014-01-01
Full Text Available The potential application of a quantum-inspired adaptive wavelet shrinkage (QAWS technique to mechanical vibration signals with a focus on noise reduction is studied in this paper. This quantum-inspired shrinkage algorithm combines three elements: an adaptive non-Gaussian statistical model of dual-tree complex wavelet transform (DTCWT coefficients proposed to improve practicability of prior information, the quantum superposition introduced to describe the interscale dependencies of DTCWT coefficients, and the quantum-inspired probability of noise defined to shrink wavelet coefficients in a Bayesian framework. By combining all these elements, this signal processing scheme incorporating the DTCWT with quantum theory can both reduce noise and preserve signal details. A practical vibration signal measured from a power-shift steering transmission is utilized to evaluate the denoising ability of QAWS. Application results demonstrate the effectiveness of the proposed method. Moreover, it achieves better performance than hard and soft thresholding.
Shrinkage Properties of Cement Stabilized Gravel
DEFF Research Database (Denmark)
Lund, Mia Schou Møller; Hansen, Kurt Kielsgaard
2014-01-01
Cement stabilized gravel is an attractive material in road construction because its strength prop-erties are accommodating the increasingly higher requirements to the bearing capacity of a base course. However, reflection cracking of cement stabilized gravel is a major concern. In this pa......-per the shrinkage properties of cement stabilized gravel have been documented under various temperature and relative humidity conditions. Two cement contents corresponding to a 28-days compressive strength of 6.2 MPa and 12.3 MPa have been tested and compared. It is found that the coefficient of linear expansion...... for the two cement contents is 9.9 × 10-6 ⁰C-1 and 11.3 × 10-6 ⁰C-1, respectively. Furthermore, it is found that reflecting cracking can mainly be explained by temperature dependent shrinkage rather than moisture dependent shrinkage....
Bernardo, Jose M
2000-01-01
This highly acclaimed text, now available in paperback, provides a thorough account of key concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts play a central role in the development of the theory, which provides, in particular, a detailed discussion of the problem of specification of so-called prior ignorance . The work is written from the authors s committed Bayesian perspective, but an overview of non-Bayesian theories is also provided, and each chapter contains a wide-ranging critica
Villalba, Jesús
2015-01-01
In this document we are going to derive the equations needed to implement a Variational Bayes estimation of the parameters of the simplified probabilistic linear discriminant analysis (SPLDA) model. This can be used to adapt SPLDA from one database to another with few development data or to implement the fully Bayesian recipe. Our approach is similar to Bishop's VB PPCA.
Physical Shrinkage Relationship in Soils of Dissimilar Lithologies in Central Southeastern Nigeria
Onweremadu, E. U.; Akamigbo, F. O. R.; Igwe, C. A.
This study investigated the relationship between volume shrinkage properties of soils derived from different parent materials in Central Southeastern Nigeria as they related to selected soil physical properties. Using a free survey technique and guided by a geological map of the area, field sampling was conducted in the early months of 2005. Routine analyses were done using collected soil samples. Results showed significant (pwaterholding capacity, Atterberg limits and Co-efficient Of Linear Extensibility (COLE) among the 6 studied soil groups. Volume shrinkage results indicated severe shrinkage (20-30%) rating for soils derived from Shale, moderate shrinkage (10-20%) for soils formed over Lower Coal Measures and Falsebedded Sandstones and slight shrinkage (0-10%) ratings for the rest. The COLE, used as an index of VS correlated significantly (pwaterholding capacity (WHC), Liquid Limit (LL), Plastic Limit (PL), Plasticity Index (PI) and clay content. A model was generated which expressed good predictive relationship between COLE and selected physical properties (R = 0.87; R2 = 0.75; 1-R2 = 0.25, RMSE = 0.01 and Bias = +0.00001), indicating high accuracy and little over-estimation by the model. More soil and soil related variables may further improve generated model (s), thus should be included in future studies.
Gutiérrez, J. M.; Natxiondo, A.; Nieves, J.; Zabala, A.; Sertucha, J.
2017-04-01
The study of shrinkage incidence variations in nodular cast irons is an important aspect of manufacturing processes. These variations change the feeding requirements on castings and the optimization of risers' size is consequently affected when avoiding the formation of shrinkage defects. The effect of a number of processing variables on the shrinkage size has been studied using a layout specifically designed for this purpose. The β parameter has been defined as the relative volume reduction from the pouring temperature up to the room temperature. It is observed that shrinkage size and β decrease as effective carbon content increases and when inoculant is added in the pouring stream. A similar effect is found when the parameters selected from cooling curves show high graphite nucleation during solidification of cast irons for a given inoculation level. Pearson statistical analysis has been used to analyze the correlations among all involved variables and a group of Bayesian networks have been subsequently built so as to get the best accurate model for predicting β as a function of the input processing variables. The developed models can be used in foundry plants to study the shrinkage incidence variations in the manufacturing process and to optimize the related costs.
Park, Jeong-Kil; Lee, Geun-Ho; Kim, Jong-Hwa; Park, Mi-Gyoung; Ko, Ching-Chang; Kim, Hyung-Il; Kwon, Yong Hoon
2014-01-01
This study evaluated the polymerization shrinkage, flexural and compressive properties of low-shrinkage resin composites. For the study, four methacrylate-based and one silorane-based resin composites were light cured using three different light-curing units (LCUs) and their polymerization shrinkage, flexural (strength (FS) and modulus (FM)) and compressive (strength (CS) and modulus (CM)) properties were evaluated. Data were statistically analyzed using ANOVA and a post-hoc Tukey test. The polymerization shrinkage ranged approximately 7.6-14.2 μm for 2-mm thick specimens depending on the resin product and LCU. Filtek LS showed the least shrinkage while the rest shrank approximately 13.2-14.2 μm. However, Filtek LS showed the greatest shrinkage difference for the used LCUs. FS and CS of the tested specimens ranged 96.2-152.1 MPa and 239.2-288.4 MPa, respectively, depending on the resin product and LCU. The highest and lowest FS and FM were recorded for the methacrylate-based resin composites. Among the specimens, Filtek LS showed the lowest CS and CM.
Hedlund, Jonas
2014-01-01
This paper introduces private sender information into a sender-receiver game of Bayesian persuasion with monotonic sender preferences. I derive properties of increasing differences related to the precision of signals and use these to fully characterize the set of equilibria robust to the intuitive criterion. In particular, all such equilibria are either separating, i.e., the sender's choice of signal reveals his private information to the receiver, or fully disclosing, i.e., the outcome of th...
Kirstein, Roland
2005-01-01
This paper presents a modification of the inspection game: The ?Bayesian Monitoring? model rests on the assumption that judges are interested in enforcing compliant behavior and making correct decisions. They may base their judgements on an informative but imperfect signal which can be generated costlessly. In the original inspection game, monitoring is costly and generates a perfectly informative signal. While the inspection game has only one mixed strategy equilibrium, three Perfect Bayesia...
Discrete multiscale wavelet shrinkage and integrodifferential equations
Didas, S.; Steidl, G.; Weickert, J.
2008-04-01
We investigate the relation between discrete wavelet shrinkage and integrodifferential equations in the context of simplification and denoising of one-dimensional signals. In the continuous setting, strong connections between these two approaches were discovered in 6 (see references). The key observation is that the wavelet transform can be understood as derivative operator after the convolution with a smoothing kernel. In this paper, we extend these ideas to the practically relevant discrete setting with both orthogonal and biorthogonal wavelets. In the discrete case, the behaviour of the smoothing kernels for different scales requires additional investigation. The results of discrete multiscale wavelet shrinkage and related discrete versions of integrodifferential equations are compared with respect to their denoising quality by numerical experiments.
Nearest shrunken centroids via alternative genewise shrinkages
Choi, Byeong Yeob; Bair, Eric; Lee, Jae Won
2017-01-01
Nearest shrunken centroids (NSC) is a popular classification method for microarray data. NSC calculates centroids for each class and “shrinks” the centroids toward 0 using soft thresholding. Future observations are then assigned to the class with the minimum distance between the observation and the (shrunken) centroid. Under certain conditions the soft shrinkage used by NSC is equivalent to a LASSO penalty. However, this penalty can produce biased estimates when the true coefficients are large. In addition, NSC ignores the fact that multiple measures of the same gene are likely to be related to one another. We consider several alternative genewise shrinkage methods to address the aforementioned shortcomings of NSC. Three alternative penalties were considered: the smoothly clipped absolute deviation (SCAD), the adaptive LASSO (ADA), and the minimax concave penalty (MCP). We also showed that NSC can be performed in a genewise manner. Classification methods were derived for each alternative shrinkage method or alternative genewise penalty, and the performance of each new classification method was compared with that of conventional NSC on several simulated and real microarray data sets. Moreover, we applied the geometric mean approach for the alternative penalty functions. In general the alternative (genewise) penalties required fewer genes than NSC. The geometric mean of the class-specific prediction accuracies was improved, as well as the overall predictive accuracy in some cases. These results indicate that these alternative penalties should be considered when using NSC. PMID:28199352
Comparative Study of Shrinkage and Non-Shrinkage Model of Food Drying
Shahari, N.; Jamil, N.; Rasmani, KA.
2016-08-01
A single phase heat and mass model has always been used to represent the moisture and temperature distribution during the drying of food. Several effects of the drying process, such as physical and structural changes, have been considered in order to increase understanding of the movement of water and temperature. However, the comparison between the heat and mass equation with and without structural change (in terms of shrinkage), which can affect the accuracy of the prediction model, has been little investigated. In this paper, two mathematical models to describe the heat and mass transfer in food, with and without the assumption of structural change, were analysed. The equations were solved using the finite difference method. The converted coordinate system was introduced within the numerical computations for the shrinkage model. The result shows that the temperature with shrinkage predicts a higher temperature at a specific time compared to that of the non-shrinkage model. Furthermore, the predicted moisture content decreased faster at a specific time when the shrinkage effect was included in the model.
Polymerization shrinkage assessment of dental resin composites: a literature review.
Kaisarly, Dalia; Gezawi, Moataz El
2016-09-01
Composite restorations are widely used worldwide, but the polymerization shrinkage is their main disadvantage that may lead to clinical failures and adverse consequences. This review reports, currently available in vitro techniques and methods used for assessing the polymerization shrinkage. The focus lies on recent methods employing three-dimensional micro-CT data for the evaluation of polymerization shrinkage: volumetric measurement and the shrinkage vector evaluation through tracing particles before and after polymerization. Original research articles reporting in vitro shrinkage measurements and shrinkage stresses were included in electronic and hand-search. Earlier methods are easier, faster and less expensive. The procedures of scanning the samples in the micro-CT and performing the shrinkage vector evaluation are time consuming and complicated. Moreover, the respective software is not commercially available and the various methods for shrinkage vector evaluation are based on different mathematical principles. Nevertheless, these methods provide clinically relevant information and give insight into the internal shrinkage behavior of composite applied in cavities and how boundary conditions affect the shrinkage vectors. The traditional methods give comparative information on polymerization shrinkage of resin composites, whereas using three-dimensional micro-CT data for volumetric shrinkage measurement and the shrinkage vector evaluation is a highly accurate method. The methods employing micro-CT data give the researchers knowledge related to the application method and the boundary conditions of restorations for visualizing the shrinkage effects that could not be seen otherwise. Consequently, this knowledge can be transferred to the clinical situation to optimize the material manipulation and application techniques for improved outcomes.
Bessiere, Pierre; Ahuactzin, Juan Manuel; Mekhnacha, Kamel
2013-01-01
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to email filtering, are incomplete or uncertain in nature. Probability theory and Bayesian computing together provide an alternative framework to deal with incomplete and uncertain data. Decision-Making Tools and Methods for Incomplete and Uncertain DataEmphasizing probability as an alternative to Boolean
DEFF Research Database (Denmark)
Dashab, Golam Reza; Kadri, Naveen Kumar; Mahdi Shariati, Mohammad;
2012-01-01
) Mixed model analysis (MMA), 2) Random haplotype model (RHM), 3) Genealogy-based mixed model (GENMIX), and 4) Bayesian variable selection (BVS). The data consisted of phenotypes of 2000 animals from 20 sire families and were genotyped with 9990 SNPs on five chromosomes. Results: Out of the eight...
Do low-shrink composites reduce polymerization shrinkage effects?
Tantbirojn, D; Pfeifer, C S; Braga, R R; Versluis, A
2011-05-01
Progress in polymer science has led to continuous reduction of polymerization shrinkage, exemplified by a new generation of "low-shrink composites". The common inference that shrinkage stress effects will be reduced in teeth restored with such restoratives with lower shrinkage was tested in extracted human premolars. Mesio-occluso-distal slot-shaped cavities were cut and restored with a conventional (SupremePlus) or low-shrink (RefleXions, Premise, Kalore, and LS) composite (N = 5). We digitized the coronal surfaces before and 10 min after restoration to determine cuspal deflection from the buccal and lingual volume change/area. We also determined the main properties involved (total shrinkage, post-gel shrinkage, degree of conversion, and elastic modulus), as well as microleakage, to verify adequate bonding. It was shown that, due to shrinkage stresses, buccal and lingual surfaces pulled inward after restoration (9-14 microns). Only Kalore and LS resulted in significantly lower tooth deformation (ANOVA/Student-Newman-Keuls post hoc, p = 0.05). The other two low-shrink composites, despite having the lowest and highest total shrinkage values, did not cause significant differences in cuspal deflection. Deflection seemed most related to the combination of post-gel shrinkage and elastic modulus. Therefore, even for significantly lower total shrinkage values, shrinkage stress is not necessarily reduced.
Reducing Shrinkage in Canned and Frozen Mushrooms
Gormley, T. R. (Thomas Ronan); Walshe, P.E.
1982-01-01
The process involving a preliminary soaking of the mushrooms in water for 20 min followed by a chill storage period followed by a further water soak for 2 hr, and known as the 3S process, gave a considerable reduction in total shrinkage in both brown and white strain canned mushrooms compared with the control samples. Water uptake by the mushrooms in the 3S process was greatest when the soaking water temperature was between 20 and 30°C and had a pH of 8. Citric acid in the blanch water enhanc...
Mechanical Self-shrinkage of Artillery Barrels
Directory of Open Access Journals (Sweden)
Ioan Ciorba
2012-09-01
Full Text Available Objective of this paper is to define what self-shrink artillery barrel is. She is considered to be a compound barrel like as a thick-walled tube (k>2, in his wall being introduced a state of stress and strain using specific technological proceeds. This type of treatment is aimed to increase the artillery barrel load capacity and wear resistance in operation. The experimental part was realized using an industrial plant at Mechanical Factory of Resita. This part presents a comparative study between mechanical self-shrinkage on artillery head barrel, first using a mandrel and seconds a ball.
Huadong sintering model about expansion and shrinkage
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
The whole sintering course from the beginning of heating to the end of heat preservation stage was studied by taking into account the influence of pressing. It was found that there exist expanding mechanism and shrinking mechanism in the sintering process, and the expanding mechanism is always acting before the shrinking mechanism. Whether the sintering body shrinks or expands depends on the interaction between the two mechanisms. And according to this, the Huadong sintering model in account of expansion and shrinkage mechanism was given.
Xu, Xu Steven; Yuan, Min; Yang, Haitao; Feng, Yan; Xu, Jinfeng; Pinheiro, Jose
2017-01-01
Covariate analysis based on population pharmacokinetics (PPK) is used to identify clinically relevant factors. The likelihood ratio test (LRT) based on nonlinear mixed effect model fits is currently recommended for covariate identification, whereas individual empirical Bayesian estimates (EBEs) are considered unreliable due to the presence of shrinkage. The objectives of this research were to investigate the type I error for LRT and EBE approaches, to confirm the similarity of power between the LRT and EBE approaches from a previous report and to explore the influence of shrinkage on LRT and EBE inferences. Using an oral one-compartment PK model with a single covariate impacting on clearance, we conducted a wide range of simulations according to a two-way factorial design. The results revealed that the EBE-based regression not only provided almost identical power for detecting a covariate effect, but also controlled the false positive rate better than the LRT approach. Shrinkage of EBEs is likely not the root cause for decrease in power or inflated false positive rate although the size of the covariate effect tends to be underestimated at high shrinkage. In summary, contrary to the current recommendations, EBEs may be a better choice for statistical tests in PPK covariate analysis compared to LRT. We proposed a three-step covariate modeling approach for population PK analysis to utilize the advantages of EBEs while overcoming their shortcomings, which allows not only markedly reducing the run time for population PK analysis, but also providing more accurate covariate tests.
Automatic Thesaurus Construction Using Bayesian Networks.
Park, Young C.; Choi, Key-Sun
1996-01-01
Discusses automatic thesaurus construction and characterizes the statistical behavior of terms by using an inference network. Highlights include low-frequency terms and data sparseness, Bayesian networks, collocation maps and term similarity, constructing a thesaurus from a collocation map, and experiments with test collections. (Author/LRW)
Towards a first classification of aerosol shrinkage events
Directory of Open Access Journals (Sweden)
E. Alonso-Blanco
2015-09-01
Full Text Available This work presents for the first time a classification of shrinkage events based on the aerosol processes that precede them. To this end, 3.5 years of continuous measurements (from 2009 to 2012 of aerosol size distributions, obtained with a Scanning Mobility Particle Sizer (SMPS at an urban background site in Southern Europe, have been interpreted. 48 shrinkage events were identified and analysed, all occurring during spring and summer when the atmospheric conditions are more favourable for their development. In this study the shrinkage events took place mostly towards the end of the day, and their occurrence could be associated to atmospheric dilution conditions and a reduction in photochemical activity. The shrinkage rate (SR varied between −1.0 and −11.1 nm h−1 (average value of −4.7 ± 2.6 nm h−1. Changes in particle concentrations corresponding to the nucleation and Aitken modes were detected, whereby an increase in the number of particles in the nucleation mode often coincided with a reduction in the Aitken mode. The accumulation mode did not undergo significant changes during these processes. In addition, in some cases, a dilution of the total particle number concentration in the ambient air was observed. Following the proposed methodology, three groups of events have been identified: Group I (NPF + shrinkage, Group II (aerosol growth process + shrinkage and Group III (pure shrinkage events. The largest number of shrinkage events has been observed in the absence of prior processes, i.e. pure shrinkage events, followed by Group I events and finally Group II events. Although this analysis has confirmed that the triggering of shrinkage events is clearly linked to the atmospheric situation and the characteristics of the measurement area, this classification may contribute to a better understanding of the processes involved and the features that characterize shrinkage events.
Introduction to Bayesian statistics
Bolstad, William M
2017-01-01
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...
Energy Technology Data Exchange (ETDEWEB)
Wyrzykowski, Mateusz, E-mail: mateusz.wyrzykowski@empa.ch [Empa, Swiss Federal Laboratories for Materials Science and Technology, Concrete and Construction Chemistry Laboratory, Dübendorf (Switzerland); Lodz University of Technology, Department of Building Physics and Building Materials, Lodz (Poland); Trtik, Pavel [Paul Scherrer Institute, Laboratory for Neutron Scattering and Imaging, Villigen (Switzerland); Empa, Swiss Federal Laboratories for Materials Science and Technology, Concrete and Construction Chemistry Laboratory, Dübendorf (Switzerland); Münch, Beat [Empa, Swiss Federal Laboratories for Materials Science and Technology, Concrete and Construction Chemistry Laboratory, Dübendorf (Switzerland); Weiss, Jason [Purdue University, School of Civil Engineering, West Lafayette (United States); Vontobel, Peter [Paul Scherrer Institute, Laboratory for Neutron Scattering and Imaging, Villigen (Switzerland); Lura, Pietro [Empa, Swiss Federal Laboratories for Materials Science and Technology, Concrete and Construction Chemistry Laboratory, Dübendorf (Switzerland); ETH Zurich, Institute for Building Materials (IfB), Zurich (Switzerland)
2015-07-15
Water transport in fresh, highly permeable concrete and rapid water evaporation from the concrete surface during the first few hours after placement are the key parameters influencing plastic shrinkage cracking. In this work, neutron tomography was used to determine both the water loss from the concrete surface due to evaporation and the redistribution of fluid that occurs in fresh mortars exposed to external drying. In addition to the reference mortar with a water to cement ratio (w/c) of 0.30, a mortar with the addition of pre-wetted lightweight aggregates (LWA) and a mortar with a shrinkage reducing admixture (SRA) were tested. The addition of SRA reduced the evaporation rate from the mortar at the initial stages of drying and reduced the total water loss. The pre-wetted LWA released a large part of the absorbed water as a consequence of capillary pressure developing in the fresh mortar due to evaporation.
Bayesian artificial intelligence
Korb, Kevin B
2003-01-01
As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.
Bayesian artificial intelligence
Korb, Kevin B
2010-01-01
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente
Directory of Open Access Journals (Sweden)
Mihaela Simionescu
2014-12-01
Full Text Available There are many types of econometric models used in predicting the inflation rate, but in this study we used a Bayesian shrinkage combination approach. This methodology is used in order to improve the predictions accuracy by including information that is not captured by the econometric models. Therefore, experts’ forecasts are utilized as prior information, for Romania these predictions being provided by Institute for Economic Forecasting (Dobrescu macromodel, National Commission for Prognosis and European Commission. The empirical results for Romanian inflation show the superiority of a fixed effects model compared to other types of econometric models like VAR, Bayesian VAR, simultaneous equations model, dynamic model, log-linear model. The Bayesian combinations that used experts’ predictions as priors, when the shrinkage parameter tends to infinite, improved the accuracy of all forecasts based on individual models, outperforming also zero and equal weights predictions and naïve forecasts.
Bayesian population finding with biomarkers in a randomized clinical trial.
Morita, Satoshi; Müller, Peter
2017-03-03
The identification of good predictive biomarkers allows investigators to optimize the target population for a new treatment. We propose a novel utility-based Bayesian population finding (BaPoFi) method to analyze data from a randomized clinical trial with the aim of finding a sensitive patient population. Our approach is based on casting the population finding process as a formal decision problem together with a flexible probability model, Bayesian additive regression trees (BART), to summarize observed data. The proposed method evaluates enhanced treatment effects in patient subpopulations based on counter-factual modeling of responses to new treatment and control for each patient. In extensive simulation studies, we examine the operating characteristics of the proposed method. We compare with a Bayesian regression-based method that implements shrinkage estimates of subgroup-specific treatment effects. For illustration, we apply the proposed method to data from a randomized clinical trial.
A Sparsity-Based InSAR Phase Denoising Algorithm Using Nonlocal Wavelet Shrinkage
Directory of Open Access Journals (Sweden)
Dongsheng Fang
2016-10-01
Full Text Available An interferometric synthetic aperture radar (InSAR phase denoising algorithm using the local sparsity of wavelet coefficients and nonlocal similarity of grouped blocks was developed. From the Bayesian perspective, the double- l 1 norm regularization model that enforces the local and nonlocal sparsity constraints was used. Taking advantages of coefficients of the nonlocal similarity between group blocks for the wavelet shrinkage, the proposed algorithm effectively filtered the phase noise. Applying the method to simulated and acquired InSAR data, we obtained satisfactory results. In comparison, the algorithm outperformed several widely-used InSAR phase denoising approaches in terms of the number of residues, root-mean-square errors and other edge preservation indexes.
Effective Expansion: Balance between Shrinkage and Hygroscopic Expansion.
Suiter, E A; Watson, L E; Tantbirojn, D; Lou, J S B; Versluis, A
2016-05-01
The purpose of this study was to investigate the relationship between hygroscopic expansion and polymerization shrinkage for compensation of polymerization shrinkage stresses in a restored tooth. One resin-modified glass-ionomer (RMGI) (Ketac Nano, 3M ESPE), 2 compomers (Dyract, Dentsply; Compoglass, Ivoclar), and a universal resin-based composite (Esthet•X HD, Dentsply) were tested. Volumetric change after polymerization ("total shrinkage") and during 4 wk of water storage at 37°C was measured using an optical method (n= 10). Post-gel shrinkage was measured during polymerization using a strain gauge method (n= 10). Extracted human molars with large mesio-occluso-distal slot preparations were restored with the tested restorative materials. Tooth surfaces at baseline (preparation), after restoration, and during 4 wk of 37°C water storage were scanned with an optical scanner to determine cuspal flexure (n= 8). Occlusal interface integrity was measured using dye penetration. Data were analyzed using analysis of variance and post hoc tests (significance level 0.05). All tested materials shrunk after polymerization. RMGI had the highest total shrinkage (4.65%) but lowest post-gel shrinkage (0.35%). Shrinkage values dropped significantly during storage in water but had not completely compensated polymerization shrinkage after 4 wk. All restored teeth initially exhibited inward (negative) cuspal flexure due to polymerization shrinkage. Cuspal flexure with the RMGI restoration was significantly less (-6.4 µm) than with the other materials (-12.1 to -14.1 µm). After 1 d, cuspal flexure reversed to +5.0 µm cuspal expansion with the RMGI and increased to +9.3 µm at 4 wk. After 4 wk, hygroscopic expansion compensated cuspal flexure in a compomer (Compoglass) and reduced flexure with Dyract and resin-based composite. Marginal integrity (93.7% intact restoration wall) was best for the Compoglass restorations and lowest (73.1%) for the RMGI restorations. Hygroscopic
Applied Bayesian Hierarchical Methods
Congdon, Peter D
2010-01-01
Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling specifications, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of hierarchical models.
Gelman, Andrew; Stern, Hal S; Dunson, David B; Vehtari, Aki; Rubin, Donald B
2013-01-01
FUNDAMENTALS OF BAYESIAN INFERENCEProbability and InferenceSingle-Parameter Models Introduction to Multiparameter Models Asymptotics and Connections to Non-Bayesian ApproachesHierarchical ModelsFUNDAMENTALS OF BAYESIAN DATA ANALYSISModel Checking Evaluating, Comparing, and Expanding ModelsModeling Accounting for Data Collection Decision AnalysisADVANCED COMPUTATION Introduction to Bayesian Computation Basics of Markov Chain Simulation Computationally Efficient Markov Chain Simulation Modal and Distributional ApproximationsREGRESSION MODELS Introduction to Regression Models Hierarchical Linear
Anisotropic shrinkage characteristics of tape cast alumina
Patwardhan, Jaideep Suresh
Dimensional control during sintering is a major issue in ceramics processing to avoid high post-sintering costs associated with machining of the fired ceramic part to desired tolerances and dimensions. Ceramic forming processes such as tape casting, injection molding, and extrusion involve shear of anisotropic particles resulting in preferential alignment of the particles in the green body. This preferential alignment causes directionality in mechanical, electrical, optical, and magnetic properties and most importantly warpage or distortion during sintering. A large effort has been devoted to synthesizing ceramic green bodies with minimal density gradients and uniform packing and modeling the sintering behavior evolution but little effort has been devoted to characterizing orientation of particles and the effect of preferential alignment on sintering shrinkage anisotropy. A systematic study was initiated to study the effect of processing variables such as shear rate, solids loading, temperature, and binder content on aqueous tape cast alumina. Three different alumina systems: A16-SG, Baikowski RC-UFX DBM and RC-LS DBM were investigated. Aqueous tapes of high solids loading alumina (56 vol. %) were tape cast at various speeds and thicknesses and assuming plane Couette flow a shear rate regime of 21--270 s-1 was investigated. Higher shear rates and high solids loading resulted in higher in-plane anisotropy whereas the anisotropy in the thickness direction was higher for low solids loading systems. The anisotropy was found to be fairly constant above a certain critical shear rate (˜100 s-1) irrespective of the temperature and the solids loading and this correlated with the viscosity-shear rate relationship of the cast slips. The higher shrinkage anisotropy in the thickness direction for the low solids loading systems (35 and 45 vol. %) was attributed to the higher amount of organics in the slip required to sustain the suitable viscosity for tape casting and
Li, Zitong; Sillanpää, Mikko J
2012-08-01
Quantitative trait loci (QTL)/association mapping aims at finding genomic loci associated with the phenotypes, whereas genomic selection focuses on breeding value prediction based on genomic data. Variable selection is a key to both of these tasks as it allows to (1) detect clear mapping signals of QTL activity, and (2) predict the genome-enhanced breeding values accurately. In this paper, we provide an overview of a statistical method called least absolute shrinkage and selection operator (LASSO) and two of its generalizations named elastic net and adaptive LASSO in the contexts of QTL mapping and genomic breeding value prediction in plants (or animals). We also briefly summarize the Bayesian interpretation of LASSO, and the inspired hierarchical Bayesian models. We illustrate the implementation and examine the performance of methods using three public data sets: (1) North American barley data with 127 individuals and 145 markers, (2) a simulated QTLMAS XII data with 5,865 individuals and 6,000 markers for both QTL mapping and genomic selection, and (3) a wheat data with 599 individuals and 1,279 markers only for genomic selection.
Cure shrinkage in epoxy grouts for grouted repairs
Shamsuddoha, Md.; Islam, Md. Mainul; Aravinthan, Thiru; Manalo, Allan; Lau, Kin-tak
2013-08-01
Structures can go through harsh environmental adversity and can experience material loss and cracks during their service lives. Infill material is used to ensure a supporting bed for a grouted repair. Epoxy grouts are used for repairing and rehabilitating structures, such as foundations, bridges, piers, transportation pipelines, etc., because they are resistant to typical chemicals and possess superior mechanical properties than other grouts. The resin based infill used inside the void or cracked space of the repair is vulnerable to shrinkage. When these filled grouts have high resin content, cracks can develop from residual stresses, which can affect the load transfer performance. It follows that interlayer separation and cracking of infill layer can occur in a grouted repair. In this study, volumetric shrinkage of two epoxy grouts was measured over 28 days using a Pycnometer. The highest volumetric shrinkage measured after 7 days was found to be 2.72%. The results suggest that the volumetric shrinkage can be reduced to 1.1% after 7 days, through the introduction of a coarse aggregate filler; a 2.5 times reduction in shrinkage. About 98% and 92% of the total shrinkage over the 28 day period, of the unfilled and filled grouts respectively, was found to occur within 7 days of mixing. The gel-time shrinkages were also calculated, to determine the "postgel" part of the curing contraction which subsequently produces residual stresses in the hardened grout systems.
Comparative Analysis of Measured and Predicted Shrinkage Strain in Concrete
Directory of Open Access Journals (Sweden)
Kossakowski P. G.
2014-06-01
Full Text Available The article discusses the issues related to concrete shrinkage. The basic information on the phenomenon is presented as well as the factors that determine the contraction are pointed out and the stages of the process are described. The guidance for estimating the shrinkage strain is given according to Eurocode standard PN-EN 1992-1-1:2008. The results of studies of the samples shrinkage strain of concrete C25/30 are presented with a comparative analysis of the results estimated by the guidelines of the standard according to PN-EN 1992-1- 1:2008
Olson, Rudolph Andrew, III
1998-12-01
The objective was to understand how the microstructure of cement paste influences its susceptibility to drying shrinkage. The strategy was to vary the microstructure via processing and relate the changes to the deformation behavior. There were many processing parameters to choose from that were capable of varying the microstructure, but one very effective way was through addition of mineral admixtures. Since the use of mineral admixtures also has the potential to address current economic, social, and environmental problems, achieving a better understanding of blended cement paste was an added benefit. Ground granulated blast furnace slag, fly ash, and silica fume were the mineral admixtures chosen for this study because they represent a wide range of reactivity. Blended cement pastes of various compositions and degrees of hydration were characterized. Calcium hydroxide, calcium silicate hydrate, pH, free water, and nitrogen surface area were the microstructural parameters chosen for analysis. Because calcium silicate hydrate is usually measured by indirect techniques which are not applicable to blended cements, a technique based on water adsorption was developed; results compared favorably with calculations from the Jennings-Tennis hydration model. The connectivity of the pore network was characterized using impedance spectroscopy. Drying shrinkage was analyzed on the macrolevel using bulk shrinkage measurements and the microstructural level using a deformation mapping technique. Several processing-microstructure-property relationships were developed. Mineral admixtures were found to significantly reduce the connectivity of the pore network and increase the nitrogen surface area of cement paste per gram of calcium silicate hydrate. The bulk drying shrinkage of blended cement pastes dried to 50% relative humidity was found to depend primarily on calcium hydroxide and calcium silicate hydrate content; shrinkage decreased with increasing amounts of calcium hydroxide
Shrinkage of Mt. Bogda Glaciers of Eastern Tian Shan in Central Asia during 1962-2006
Institute of Scientific and Technical Information of China (English)
Kaiming Li; Zhongqin Li; Cuiyun Wang; Baojuan Huai
2016-01-01
Many small mountain glaciers have been reported undergoing strong shrinkage, and it is therefore important to understand how they respond to climate change. The availability of topographic maps from 1962, Landsat TM imagery from 1990 and ASTER (Advanced Spaceborne Thermal Emission and Radiometer) imagery from 2006 and field investigation of some glaciers allow a comprehensive analysis of glacier change based on glacier size and topography on Mt. Bogda. Results include:(1) an overall loss of a glacierized area by 31.18±0.31 km2 or 21.6%from 1962 to 2006, (2) a marked dependence of glacier area shrinkage on initial size, with smaller glaciers experiencing higher shrinkage levels, (3) the disappearance of 12 small glaciers, (4) a striking difference in area loss between the southern and northern slopes of 25%and 17%, respectively. A subset of the investigated glaciers shows that the area 57.45±0.73 km2 in 1962 reduced to 54.79±0.561 km2 in 1990 and 48.88±0.49 km2 in 2006, with a relative area reduction of 4.6% during 1962–1990, and 10.8%during 1990–2006. The corresponding volume waste increased from 6.9%to 10.2%. Three reference glaciers were investigated in 1981 and revisited in 2009. Their terminus experienced a marked recession. Meteorological data from stations around Mt. Bogda reveals that glacier shrinkage is correlated with winter warming and an extension of the ablation period. Precipitation on the northwest side of the range shows a marked increase, with a slight increase on the southeast side.
Nanocavity Shrinkage and Preferential Amorphization during Irradiation in Silicon
Institute of Scientific and Technical Information of China (English)
ZHU Xian-Fang; WANG Zhan-Guo
2005-01-01
@@ We model the recent experimental results and demonstrate that the internal shrinkage of nanocavities in silicon is intrinsically associated with preferential amorphization as induced by self-ion irradiation.
Development of spraying agent for reducing drying shrinkage of mortar
Fujiwara, Hiromi; Maruoka, Masanori; Liu, Lingling
2017-02-01
Mortar used to repair is sometimes exposed to drying state in early ages after construction and a few days later water is sprayed frequently on the surface of the mortar in order to prevent cracks. This research studied on shrinkage characteristic of mortar subjected to drying conditions like this. The result showed that the water spraying on the mortar after initial drying did not have any effect to prevent shrinkage, but increased. And it also showed when various chemical agents are mixed and used in watersprayingit had the prevention effect on shrinkage. This report was to understand this kind of phenomenon and clarify the mechanism. In addition, based on the results, the new spraying agent was developed to reduce drying shrinkage.
Applying strain into graphene by SU-8 resist shrinkage
Takamura, Makoto; Hibino, Hiroki; Yamamoto, Hideki
2016-07-01
We investigated the use of the shrinkage of SU-8 resist caused by thermal annealing to apply strain into graphene grown by the chemical-vapor-deposition (CVD) method. We demonstrate that the shrinkage of resist deposited on top of graphene on a substrate induces a local tensile strain within a distance of 1-2 μm from the edge of the resist. The thermal shrinkage of SU-8 will allow us to design the local strain in graphene on substrates. We also show that the shrinkage induces a large tensile strain in graphene suspended between two bars of SU-8. We expect that a much larger strain can be induced by suppressing defects in CVD-grown graphene.
Fast shrinkage of tropical glaciers in Colombia
Ceballos, Jorge Luis; Euscátegui, Christian; Ramírez, Jair; Cañon, Marcela; Huggel, Christian; Haeberli, Wilfried; Machguth, Horst
As a consequence of ongoing atmospheric temperature rise, tropical glaciers belong to the unique and threatened ecosystems on Earth, as defined by the Intergovernmental Panel on Climate Change (Houghton and others, 2001). Worldwide glacier monitoring, especially as part of the Global Climate Observing System (GCOS), includes the systematic collection of data on such perennial surface ice masses. Several peaks in the sierras of Colombia have lost their glacier cover during recent decades. Today, high-altitude glaciers still exist in Sierra Nevada de Santa Marta, in Sierra Nevada del Cocuy and on the volcanoes of Nevados del Ruiz, de Santa Isabel, del Tolima and del Huila. Comparison of reconstructions of maximum glacier area extent during the Little Ice Age with more recent information from aerial photographs and satellite images clearly documents a fast-shrinking tendency and potential disappearance of the remaining glaciers within the next few decades. In the past 50 years, Colombian glaciers have lost 50% or more of their area. Glacier shrinkage has continued to be strong in the last 15 years, with a loss of 10-50% of the glacier area. The relationship between fast glacier retreat and local, regional and global climate change is now being investigated. Preliminary analyses indicate that the temperature rise of roughly 1° C in the last 30 years recorded at high-altitude meteorological stations exerts a primary control on glacier retreat. The investigations on the Colombian glaciers thus corroborate earlier findings concerning the high sensitivity of glaciers in the wet inner tropics to temperature rise. To improve understanding of fast glacier retreat in Colombia, a modern monitoring network has been established according to the multilevel strategy of the Global Terrestrial Network for Glaciers (GTN-G) within GCOS. The observations are also contributions to continued assessments of hazards from the glacier-covered volcanoes and to integrated global change
Method to determine factors contributing to thermoplastic sheet shrinkage
Rensch, Greg J.; Frye, Brad A.
A test method is presented for the determination of shrinkage behavior in vacuum-formed thermoplastic resin sheeting, as presently simulated for various resin lots, sheet-gage thicknesses, sheet orientations, and mold profiles. The thermoforming machine and vacuum-forming mold characteristics are discussed. It is established that the four variable factors exert statistically significant effects on the shrinkage response of three Declar resin lots, but that these are of no real practical significance for either engineering or manufacturing operations.
Accurate characterisation of post moulding shrinkage of polymer parts
DEFF Research Database (Denmark)
Neves, L. C.; De Chiffre, L.; González-Madruga, D.;
2015-01-01
The work deals with experimental determination of the shrinkage of polymer parts after injection moulding. A fixture for length measurements on 8 parts at the same time was designed and manufactured in Invar, mounted with 8 electronic gauges, and provided with 3 temperature sensors. The fixture...... of post moulding shrinkage of polymer parts was developed. Expanded uncertainties (k=2) of 3 μm were obtained....
Most frugal explanations in Bayesian networks
Kwisthout, J.H.P.
2015-01-01
Inferring the most probable explanation to a set of variables, given a partial observation of the remaining variables, is one of the canonical computational problems in Bayesian networks, with widespread applications in AI and beyond. This problem, known as MAP, is computationally intractable (NP-ha
Bayesian mixture models for partially verified data
DEFF Research Database (Denmark)
Kostoulas, Polychronis; Browne, William J.; Nielsen, Søren Saxmose;
2013-01-01
for some individuals, in order to minimize this loss in the discriminatory power. The distribution of the continuous antibody response against MAP has been obtained for healthy, MAP-infected and MAP-infectious cows of different age groups. The overall power of the milk-ELISA to discriminate between healthy......Bayesian mixture models can be used to discriminate between the distributions of continuous test responses for different infection stages. These models are particularly useful in case of chronic infections with a long latent period, like Mycobacterium avium subsp. paratuberculosis (MAP) infection...
Lopes, Lawrence Gonzaga; Franco, Eduardo Batista; Pereira, José Carlos; Mondelli, Rafael Francisco Lia
2008-01-01
The aim of this study was to evaluate the polymerization shrinkage and shrinkage stress of composites polymerized with a LED and a quartz tungsten halogen (QTH) light sources. The LED was used in a conventional mode (CM) and the QTH was used in both conventional and pulse-delay modes (PD). The composite resins used were Z100, A110, SureFil and Bisfil 2B (chemical-cured). Composite deformation upon polymerization was measured by the strain gauge method. The shrinkage stress was measured by photoelastic analysis. The polymerization shrinkage data were analyzed statistically using two-way ANOVA and Tukey test (p contraction and the stress values when compared to CM. LED generated the same stress as QTH in conventional mode. Regardless of the activation mode, SureFil produced lower contraction and stress values than the other light-cured resins. Conversely, Z100 and A110 produced the greatest contraction and stress values. As expected, the chemically cured resin generated lower shrinkage and stress than the light-cured resins. In conclusion, The PD mode effectively decreased contraction stress for Z100 and A110. Development of stress in light-cured resins depended on the shrinkage value.
Bayesian Games with Intentions
Directory of Open Access Journals (Sweden)
Adam Bjorndahl
2016-06-01
Full Text Available We show that standard Bayesian games cannot represent the full spectrum of belief-dependent preferences. However, by introducing a fundamental distinction between intended and actual strategies, we remove this limitation. We define Bayesian games with intentions, generalizing both Bayesian games and psychological games, and prove that Nash equilibria in psychological games correspond to a special class of equilibria as defined in our setting.
Bayesian statistics an introduction
Lee, Peter M
2012-01-01
Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as wel
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
Angelidou, Elisavet; Kostoulas, Polychronis; Leontides, Leonidas
2016-02-01
A total of 854 paired milk and blood samples were collected from ewes of a Greek flock and used to estimate the sensitivity and specificity of a commercial ELISA for detection of Mycobacterium avium subsp. paratuberculosis (MAP) specific antibodies in each stage of lactation. We implemented Bayesian mixture models to derive the distributions of the test response for the healthy and the infected ewes. In the colostrum period, early, mid and late lactation stage the median values of the area under the curves (AUC) were 0.61 (95% credible interval: 0.50; 0.84), 0.61 (0.51;0.84), 0.65 (0.51;0.91), 0.65(0.51;0.89) for the serum ELISA and and 0.60 (0.50; 0.84), 0.61 (0.50; 0.84), 0.67(0.51; 0.91), 0.66(0.50; 0.90) for the milk ELISA, respectively. Both serum and milk ELISA had low to average overall discriminatory ability as measured by the area under the curves and comparable sensitivities and specificities at the recommended cutoffs.
Bayesian and L$_\\mathbf{1}$ Approaches to Sparse Unsupervised Learning
Mohamed, Shakir; Ghahramani, Zoubin
2011-01-01
The use of $L_1$ regularisation for sparse learning has generated immense research interest, with successful application in such diverse areas as signal acquisition, image coding, genomics and collaborative filtering. While existing work highlights the many advantages of $L_1$ methods, in this paper we find that $L_1$ regularisation often dramatically underperforms in terms of predictive performance when compared with other methods for inferring sparsity. We focus on unsupervised latent variable models, and develop $L_1$ minimising factor models, Bayesian variants of "$L_1$", and Bayesian models with a stronger $L_0$-like sparsity induced through spike-and-slab distributions. These spike-and-slab Bayesian factor models encourage sparsity while accounting for uncertainty in a principled manner and avoiding unnecessary shrinkage of non-zero values. We demonstrate on a number of data sets that in practice spike-and-slab Bayesian methods outperform $L_1$ minimisation, even on a computational budget. We thus highl...
Plastic and free shrinkages cracking of blended white cement concrete
Energy Technology Data Exchange (ETDEWEB)
Rashad, A.M.; White, T.; Ariaratnam, S.; Knutson, K. [Housing and Building National Research Center, Cairo (Egypt)
2007-07-01
This paper presented the results of a study that investigated the plastic and free shrinkages of white portland cement concrete, concrete incorporating silica fume (SF) and concrete incorporating metakaolin (MK) compared to regular plain gray portland cement concrete. An experimental program was designed to investigate the plastic and free shrinkage of concrete containing gray and white blended cement. The paper discussed the experimental details including materials and cement types such as SF, MK, aggregate, and superplasticizer as well as concrete mixtures and specimen preparation including mixture proportions, preparation and curing of concrete specimens, and test specimens. It also presented the determination of concrete properties such as slump of fresh concrete, plastic shrinkage, and dry shrinkage. Test results and discussion of results were also provided. It was concluded that plain white portland cement concrete showed less number of plastic cracks but slightly higher average crack width compared to other concrete mixtures with MK or SF. In addition, free shrinkage behavior of plain white cement and plain gray cement matrix was comparable. 23 refs.
Geosynthetic clay liners shrinkage under simulated daily thermal cycles.
Sarabadani, Hamid; Rayhani, Mohammad T
2014-06-01
Geosynthetic clay liners are used as part of composite liner systems in municipal solid waste landfills and other applications to restrict the escape of contaminants into the surrounding environment. This is attainable provided that the geosynthetic clay liner panels continuously cover the subsoil. Previous case histories, however, have shown that some geosynthetic clay liner panels are prone to significant shrinkage and separation when an overlying geomembrane is exposed to solar radiation. Experimental models were initiated to evaluate the potential shrinkage of different geosynthetic clay liner products placed over sand and clay subsoils, subjected to simulated daily thermal cycles (60°C for 8 hours and 22°C for 16 hours) modelling field conditions in which the liner is exposed to solar radiation. The variation of geosynthetic clay liner shrinkage was evaluated at specified times by a photogrammetry technique. The manufacturing techniques, the initial moisture content, and the aspect ratio (ratio of length to width) of the geosynthetic clay liner were found to considerably affect the shrinkage of geosynthetic clay liners. The particle size distribution of the subsoil and the associated suction at the geosynthetic clay liner-subsoil interface was also found to have significant effects on the shrinkage of the geosynthetic clay liner.
Directory of Open Access Journals (Sweden)
Lawrence Gonzaga Lopes
2008-02-01
Full Text Available The aim of this study was to evaluate the polymerization shrinkage and shrinkage stress of composites polymerized with a LED and a quartz tungsten halogen (QTH light sources. The LED was used in a conventional mode (CM and the QTH was used in both conventional and pulse-delay modes (PD. The composite resins used were Z100, A110, SureFil and Bisfil 2B (chemical-cured. Composite deformation upon polymerization was measured by the strain gauge method. The shrinkage stress was measured by photoelastic analysis. The polymerization shrinkage data were analyzed statistically using two-way ANOVA and Tukey test (p<0.05, and the stress data were analyzed by one-way ANOVA and Tukey's test (p<0.05. Shrinkage and stress means of Bisfil 2B were statistically significant lower than those of Z100, A110 and SureFil. In general, the PD mode reduced the contraction and the stress values when compared to CM. LED generated the same stress as QTH in conventional mode. Regardless of the activation mode, SureFil produced lower contraction and stress values than the other light-cured resins. Conversely, Z100 and A110 produced the greatest contraction and stress values. As expected, the chemically cured resin generated lower shrinkage and stress than the light-cured resins. In conclusion, The PD mode effectively decreased contraction stress for Z100 and A110. Development of stress in light-cured resins depended on the shrinkage value.
Yuan, Ying; MacKinnon, David P.
2009-01-01
In this article, we propose Bayesian analysis of mediation effects. Compared with conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian…
Varadhan, Ravi; Wang, Sue-Jane
2016-01-01
Treatment effect heterogeneity is a well-recognized phenomenon in randomized controlled clinical trials. In this paper, we discuss subgroup analyses with prespecified subgroups of clinical or biological importance. We explore various alternatives to the naive (the traditional univariate) subgroup analyses to address the issues of multiplicity and confounding. Specifically, we consider a model-based Bayesian shrinkage (Bayes-DS) and a nonparametric, empirical Bayes shrinkage approach (Emp-Bayes) to temper the optimism of traditional univariate subgroup analyses; a standardization approach (standardization) that accounts for correlation between baseline covariates; and a model-based maximum likelihood estimation (MLE) approach. The Bayes-DS and Emp-Bayes methods model the variation in subgroup-specific treatment effect rather than testing the null hypothesis of no difference between subgroups. The standardization approach addresses the issue of confounding in subgroup analyses. The MLE approach is considered only for comparison in simulation studies as the "truth" since the data were generated from the same model. Using the characteristics of a hypothetical large outcome trial, we perform simulation studies and articulate the utilities and potential limitations of these estimators. Simulation results indicate that Bayes-DS and Emp-Bayes can protect against optimism present in the naïve approach. Due to its simplicity, the naïve approach should be the reference for reporting univariate subgroup-specific treatment effect estimates from exploratory subgroup analyses. Standardization, although it tends to have a larger variance, is suggested when it is important to address the confounding of univariate subgroup effects due to correlation between baseline covariates. The Bayes-DS approach is available as an R package (DSBayes).
Brain shrinkage and subdural effusion associated with ACTH administration.
Satoh, J; Takeshige, H; Hara, H; Fukuyama, Y
1982-01-01
Sequential computed tomographic (CT) studies of 11 patients (aged five months to seven years) with intractable epilepsy treated with synthetic ACTH-Z showed brain shrinkage in all cases. Brain shrinkage started to appear on daily ACTH injections for seven days, reached the maximum within four weeks of administration (14 injections every day and then 7 injections every other day), and almost returned to the original status in seven out of nine cases which were followed up for one to three months after the therapy. The subjects aged less than two years showed more remarkable brain shrinkage than did those aged more than five years. Furthermore, two other cases were complicated by subdural effusion after ACTH therapy. It is the authors' assumption that both of these phenomena are caused by the high concentration of corticosteroid through a change of the water and electrolyte contents in the brain.
von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo
2014-06-01
Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.
Shrinkage anisotropy characteristics from soil structure and initial sample/layer size
Chertkov, V Y
2014-01-01
The objective of this work is a physical prediction of such soil shrinkage anisotropy characteristics as variation with drying of (i) different sample/layer sizes and (ii) the shrinkage geometry factor. With that, a new presentation of the shrinkage anisotropy concept is suggested through the sample/layer size ratios. The work objective is reached in two steps. First, the relations are derived between the indicated soil shrinkage anisotropy characteristics and three different shrinkage curves of a soil relating to: small samples (without cracking at shrinkage), sufficiently large samples (with internal cracking), and layers of similar thickness. Then, the results of a recent work with respect to the physical prediction of the three shrinkage curves are used. These results connect the shrinkage curves with the initial sample size/layer thickness as well as characteristics of soil texture and structure (both inter- and intra-aggregate) as physical parameters. The parameters determining the reference shrinkage c...
Hydration of Portoguese cements, measurement and modelling of chemical shrinkage
DEFF Research Database (Denmark)
Maia, Lino; Geiker, Mette Rica; Figueiras, Joaquim A.
2008-01-01
form of the dispersion model. The development of hydration varied between the investigated cements; based on the measured data the degree of hydration after 24 h hydration at 20 C varied between 40 and 50%. This should be taken into account when comparing properties of concrete made from the different......Development of cement hydration was studied by measuring the chemical shrinkage of pastes. Five types of Portuguese Portland cement were used in cement pastes with . Chemical shrinkage was measured by gravimetry and dilatometry. In gravimeters results were recorded automatically during at least...
Optimal linear shrinkage corrections of sample LMMSE and MVDR estimators
2012-01-01
La proposició d'estimadors shrinkage òptims que corregeixen la degradació dels mètodes sample LMMSE i sample MUDR en el règim on el número de mostres és petit en comparació a la dimensió de les observacions. [ANGLÈS] This master thesis proposes optimal shrinkage estimators that counteract the performance degradation of the sample LMMSE and sample MVDR methods in the regime where the sample size is small compared to the observation dimension. [CASTELLÀ] Esta máster tesis propone estimado...
Konstruksi Bayesian Network Dengan Algoritma Bayesian Association Rule Mining Network
Octavian
2015-01-01
Beberapa tahun terakhir, Bayesian Network telah menjadi konsep yang populer digunakan dalam berbagai bidang kehidupan seperti dalam pengambilan sebuah keputusan dan menentukan peluang suatu kejadian dapat terjadi. Sayangnya, pengkonstruksian struktur dari Bayesian Network itu sendiri bukanlah hal yang sederhana. Oleh sebab itu, penelitian ini mencoba memperkenalkan algoritma Bayesian Association Rule Mining Network untuk memudahkan kita dalam mengkonstruksi Bayesian Network berdasarkan data ...
A geometric atlas to predict lung tumor shrinkage for radiotherapy treatment planning
Zhang, Pengpeng; Rimner, Andreas; Yorke, Ellen; Hu, Yu-Chi; Kuo, Licheng; Apte, Aditya; Lockney, Natalie; Jackson, Andrew; Mageras, Gig; Deasy, Joseph O.
2017-02-01
To develop a geometric atlas that can predict tumor shrinkage and guide treatment planning for non-small-cell lung cancer. To evaluate the impact of the shrinkage atlas on the ability of tumor dose escalation. The creation of a geometric atlas included twelve patients with lung cancer who underwent both planning CT and weekly CBCT for radiotherapy planning and delivery. The shrinkage pattern from the original pretreatment to the residual posttreatment tumor was modeled using a principal component analysis, and used for predicting the spatial distribution of the residual tumor. A predictive map was generated by unifying predictions from each individual patient in the atlas, followed by correction for the tumor’s surrounding tissue distribution. Sensitivity, specificity, and accuracy of the predictive model for classifying voxels inside the original gross tumor volume were evaluated. In addition, a retrospective study of predictive treatment planning (PTP) escalated dose to the predicted residual tumor while maintaining the same level of predicted complication rates for a clinical plan delivering uniform dose to the entire tumor. The effect of uncertainty on the predictive model’s ability to escalate dose was also evaluated. The sensitivity, specificity and accuracy of the predictive model were 0.73, 0.76, and 0.74, respectively. The area under the receiver operating characteristic curve for voxel classification was 0.87. The Dice coefficient and mean surface distance between the predicted and actual residual tumor averaged 0.75, and 1.6 mm, respectively. The PTP approach allowed elevation of PTV D95 and mean dose to the actual residual tumor by 6.5 Gy and 10.4 Gy, respectively, relative to the clinical uniform dose approach. A geometric atlas can provide useful information on the distribution of resistant tumors and effectively guide dose escalation to the tumor without compromising the organs at risk complications. The atlas can be further refined by using
Model Diagnostics for Bayesian Networks
Sinharay, Sandip
2006-01-01
Bayesian networks are frequently used in educational assessments primarily for learning about students' knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A…
Effect of processing conditions on shrinkage in injection molding
Jansen, K.M.B.; Dijk, van D.J.; Husselman, M.H.
1998-01-01
A systematic study on the effect of processing conditions on mold shrinkage was undertaken for seven common thermoplastic polymers. It turned out that the holding pressure was always the key parameter. The effect of the melt temperature is slightly less important. Injection velocity and mold tempera
SOMBI: Bayesian identification of parameter relations in unstructured cosmological data
Frank, Philipp; Enßlin, Torsten A
2016-01-01
This work describes the implementation and application of a correlation determination method based on Self Organizing Maps and Bayesian Inference (SOMBI). SOMBI aims to automatically identify relations between different observed parameters in unstructured cosmological or astrophysical surveys by automatically identifying data clusters in high-dimensional datasets via the Self Organizing Map neural network algorithm. Parameter relations are then revealed by means of a Bayesian inference within respective identified data clusters. Specifically such relations are assumed to be parametrized as a polynomial of unknown order. The Bayesian approach results in a posterior probability distribution function for respective polynomial coefficients. To decide which polynomial order suffices to describe correlation structures in data, we include a method for model selection, the Bayesian Information Criterion, to the analysis. The performance of the SOMBI algorithm is tested with mock data. As illustration we also provide ...
Exploratory disease mapping: kriging the spatial risk function from regional count data
Directory of Open Access Journals (Sweden)
Berke Olaf
2004-08-01
Full Text Available Abstract Background There is considerable interest in the literature on disease mapping to interpolate estimates of disease occurrence or risk of disease from a regional database onto a continuous surface. In addition to many interpolation techniques available the geostatistical method of kriging has been used but also criticised. Results To circumvent these critics one may use kriging along with already smoothed regional estimates, where smoothing is based on empirical Bayes estimates, also known as shrinkage estimates. The empirical Bayes step has the advantage of shrinking the unstable and often extreme estimates to the global or local mean, and also has a stabilising effect on variance by borrowing strength, as well. Negative interpolates are prevented by choice of the appropriate kriging method. The proposed mapping method is applied to the North Carolina SIDS data example as well as to an example data set from veterinary epidemiology. The SIDS data are modelled without spatial trend. And spatial interpolation is based on ordinary kriging. The second example is included to demonstrate the method when the phenomenon under study exhibits a spatial trend and interpolation is based on universal kriging. Conclusion Interpolation of the regional estimates overcomes the areal bias problem and the resulting isopleth maps are easier to read than choropleth maps. The empirical Bayesian estimate for smoothing is related to internal standardization in epidemiology. Therefore, the proposed concept is easily communicable to map users.
Cure shrinkage effects in epoxy and polycyanate matrix composites
Energy Technology Data Exchange (ETDEWEB)
Spellman, G.P.
1995-12-22
A relatively new advanced composite matrix, polycyanate ester, was evaluated for cure shrinkage. The chemical cure shrinkage of composites is difficult to model but a number of clever experimental techniques are available to the investigator. In this work the method of curing a prepreg layup on top of a previously cured laminate of identical ply composition is utilized. The polymeric matrices used in advanced composites have been primarily epoxies and therefore a common system of this type, Fiberite 3501-6, was used as a base case material. Three polycyanate matrix systems were selected for the study. These are: Fiberite 954-2A, YLA RS-3, and Bryte Technology BTCy-1. The first three of these systems were unidirectional prepreg with carbon fiber reinforcement. The Bryte Technology material was reinforced with E-glass fabric. The technique used to evaluate cure shrinkage results in distortion of the flatness of an otherwise symmetric laminate. The first laminate is cured in a conventional fashion. An identical layup is cured on this first laminate. During the second cure all constituents are exposed to the same thermal cycles. However, only the new portion of the laminate will experience volumetric changes associate with matrix cure. The additional strain of cure shrinkage results in an unsymmetric distribution of residual stresses and an associated warpage of the laminate. The baseline material, Fiberite 3501-6, exhibited cure shrinkage that was in accordance with expectations. Cure strains were {minus}4.5E-04. The YLA RS-3 material had cure strains somewhat lower at {minus}3.2E-04. The Fiberite 954-2A cure strain was {minus}1.5E-04 that is 70% lower than the baseline material. The glass fabric material with the Bryte BTCy-1 matrix did not result in meaningful results because the processing methods were not fully compatible with the material.
Bayesian Lensing Shear Measurement
Bernstein, Gary M
2013-01-01
We derive an estimator of weak gravitational lensing shear from background galaxy images that avoids noise-induced biases through a rigorous Bayesian treatment of the measurement. The Bayesian formalism requires a prior describing the (noiseless) distribution of the target galaxy population over some parameter space; this prior can be constructed from low-noise images of a subsample of the target population, attainable from long integrations of a fraction of the survey field. We find two ways to combine this exact treatment of noise with rigorous treatment of the effects of the instrumental point-spread function and sampling. The Bayesian model fitting (BMF) method assigns a likelihood of the pixel data to galaxy models (e.g. Sersic ellipses), and requires the unlensed distribution of galaxies over the model parameters as a prior. The Bayesian Fourier domain (BFD) method compresses galaxies to a small set of weighted moments calculated after PSF correction in Fourier space. It requires the unlensed distributi...
Fox, G.J.A.; Berg, van den S.M.; Veldkamp, B.P.; Irwing, P.; Booth, T.; Hughes, D.
2015-01-01
In educational and psychological studies, psychometric methods are involved in the measurement of constructs, and in constructing and validating measurement instruments. Assessment results are typically used to measure student proficiency levels and test characteristics. Recently, Bayesian item resp
Noncausal Bayesian Vector Autoregression
DEFF Research Database (Denmark)
Lanne, Markku; Luoto, Jani
We propose a Bayesian inferential procedure for the noncausal vector autoregressive (VAR) model that is capable of capturing nonlinearities and incorporating effects of missing variables. In particular, we devise a fast and reliable posterior simulator that yields the predictive distribution...
Granade, Christopher; Cory, D G
2015-01-01
In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of- the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we solve all three problems. First, we use modern statistical methods, as pioneered by Husz\\'ar and Houlsby and by Ferrie, to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first informative priors on quantum states and channels. Finally, we develop a method that allows online tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.
Bayesian phylogeography finds its roots.
Directory of Open Access Journals (Sweden)
Philippe Lemey
2009-09-01
Full Text Available As a key factor in endemic and epidemic dynamics, the geographical distribution of viruses has been frequently interpreted in the light of their genetic histories. Unfortunately, inference of historical dispersal or migration patterns of viruses has mainly been restricted to model-free heuristic approaches that provide little insight into the temporal setting of the spatial dynamics. The introduction of probabilistic models of evolution, however, offers unique opportunities to engage in this statistical endeavor. Here we introduce a Bayesian framework for inference, visualization and hypothesis testing of phylogeographic history. By implementing character mapping in a Bayesian software that samples time-scaled phylogenies, we enable the reconstruction of timed viral dispersal patterns while accommodating phylogenetic uncertainty. Standard Markov model inference is extended with a stochastic search variable selection procedure that identifies the parsimonious descriptions of the diffusion process. In addition, we propose priors that can incorporate geographical sampling distributions or characterize alternative hypotheses about the spatial dynamics. To visualize the spatial and temporal information, we summarize inferences using virtual globe software. We describe how Bayesian phylogeography compares with previous parsimony analysis in the investigation of the influenza A H5N1 origin and H5N1 epidemiological linkage among sampling localities. Analysis of rabies in West African dog populations reveals how virus diffusion may enable endemic maintenance through continuous epidemic cycles. From these analyses, we conclude that our phylogeographic framework will make an important asset in molecular epidemiology that can be easily generalized to infer biogeogeography from genetic data for many organisms.
Bayesian image reconstruction: Application to emission tomography
Energy Technology Data Exchange (ETDEWEB)
Nunez, J.; Llacer, J.
1989-02-01
In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.
A Monte Carlo Evaluation of Estimated Parameters of Five Shrinkage Estimate Formuli.
Newman, Isadore; And Others
1979-01-01
A Monte Carlo simulation was employed to determine the accuracy with which the shrinkage in R squared can be estimated by five different shrinkage formulas. The study dealt with the use of shrinkage formulas for various sample sizes, different R squared values, and different degrees of multicollinearity. (Author/JKS)
Study of ‘real’ shrinkage by ESEM observations and digital image analysis
Jankovic, D.
2007-01-01
Defining the 'real' shrinkage values of concrete is still a subject of much debate. In shrinkage experiments size effects are inherently present. Through an attempt to determine the real shrinkage of cement-based materials, these size effects have to be eliminated or at least reduced as much a possi
New particle growth and shrinkage observed in subtropical environments
Directory of Open Access Journals (Sweden)
L.-H. Young
2012-07-01
Full Text Available We present the first systematic analysis for new particle formation (NPF, growth and shrinkage of new particles observed at four different sites in subtropical Central Taiwan. A total of 14 NPF events were identified during 137 days of ambient measurements during a cold and warm season. The derived nucleation rates of 1 nm particles (J_{1} and growth rates were in the range of 39.6–252.9 cm^{−3} s^{−1} and 6.5–14.5 nm h^{−1}, respectively. The NPF events occurred on days either with low condensation sink (CS, increased morning traffic emissions and the breakup of nocturnal inversion layer (type A, or with high CS, minimum levels of primary traffic emissions and enhanced atmospheric dilution (type B. On non-event days, the particle number concentrations were mostly driven by traffic emissions. We have also observed shrinkage of new particles (type A-S and B-S, reversal of growth, during five out of the 14 NPF events. In intense shrinkage cases, the grown particles shrank back to the smallest measurable size of ~10 nm, thereby creating a unique "arch-like" shape in the size distribution contour plot. The particle shrinkage rates ranged from 5.1 to 7.6 nm h^{−1}. The ratios of shrinkage-to-growth rates were mostly in the range of 0.40–0.65, suggesting that a large fraction of the condensable species that contributed to growth were likely semi-volatile. The particle shrinkage was related to air masses with low CS due to atmospheric dilution, high ambient temperature and low relative humidity and such atmospheric conditions may have facilitated the evaporation of semi-volatile species from the particles to the gas phase. Our observations show that the new particle growth may be a~reversible process and the evaporating semi-volatile species are important for the growth of new particles to cloud condensation nuclei sizes.
Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm
Kyrillidis, Anastasios
2012-01-01
The least absolute shrinkage and selection operator (LASSO) for linear regression exploits the geometric interplay of the $\\ell_2$-data error objective and the $\\ell_1$-norm constraint to arbitrarily select sparse models. Guiding this uninformed selection process with sparsity models has been precisely the center of attention over the last decade in order to improve learning performance. To this end, we alter the selection process of LASSO to explicitly leverage combinatorial sparsity models (CSMs) via the combinatorial selection and least absolute shrinkage (CLASH) operator. We provide concrete guidelines how to leverage combinatorial constraints within CLASH, and characterize CLASH's guarantees as a function of the set restricted isometry constants of the sensing matrix. Finally, our experimental results show that CLASH can outperform both LASSO and model-based compressive sensing in sparse estimation.
Exploiting tumor shrinkage through temporal optimization of radiotherapy
Unkelbach, Jan; Hong, Theodore; Papp, David; Ramakrishnan, Jagdish; Salari, Ehsan; Wolfgang, John; Bortfeld, Thomas
2013-01-01
In multi-stage radiotherapy, a patient is treated in several stages separated by weeks or months. This regimen has been motivated mostly by radiobiological considerations, but also provides an approach to reduce normal tissue dose by exploiting tumor shrinkage. The paper considers the optimal design of multi-stage treatments, motivated by the clinical management of large liver tumors for which normal liver dose constraints prohibit the administration of an ablative radiation dose in a single treatment. We introduce a dynamic tumor model that incorporates three factors: radiation induced cell kill, tumor shrinkage, and tumor cell repopulation. The design of multi-stage radiotherapy is formulated as a mathematical optimization problem in which the total dose to the liver is minimized, subject to delivering the prescribed dose to the tumor. Based on the model, we gain insight into the optimal administration of radiation over time, i.e. the optimal treatment gaps and dose levels. We analyze treatments consisting ...
Analysis of Shrinkage on Thick Plate Part using Genetic Algorithm
Directory of Open Access Journals (Sweden)
Najihah S.N.
2016-01-01
Full Text Available Injection moulding is the most widely used processes in manufacturing plastic products. Since the quality of injection improves plastic parts are mostly influenced by process conditions, the method to determine the optimum process conditions becomes the key to improving the part quality. This paper presents a systematic methodology to analyse the shrinkage of the thick plate part during the injection moulding process. Genetic Algorithm (GA method was proposed to optimise the process parameters that would result in optimal solutions of optimisation goals. Using the GA, the shrinkage of the thick plate part was improved by 39.1% in parallel direction and 17.21% in the normal direction of melt flow.
Modelling of elastoplastic damage in concrete due to desiccation shrinkage
Bourgeois, F.; Burlion, N.; Shao, J. F.
2002-07-01
We present a numerical modelling of elastoplastic damage due to drying shrinkage of concrete in the framework of mechanics of partially saturated porous media. An elastoplastic model coupled with isotropic damage is first formulated. Two plastic flow mechanisms are involved, controlled by applied stress and suction, respectively. A general concept of net effective stress is used in take into account effects of capillary pressure and material damage on stress-controlled plastic deformation. Damage evolution depends both on elastic and plastic strains. The model's parameters are determined or chosen from relevant experimental data. Comparisons between numerical simulations and experimental data are presented to show the capacity of model to reproduce mains features of concrete behaviour under mechanical loading and during drying shrinkage of concrete. An example of application concerning drying of a concrete wall is finally presented. The results obtained allow to show potential capacity of proposed model for numerical modelling of complex coupling processes in concrete structures.
Reversible cerebral shrinkage in kwashiorkor: an MRI study.
Gunston, G D; Burkimsher, D; Malan, H; Sive, A A
1992-08-01
Protein energy malnutrition is associated with cerebral atrophy which may be detrimental to intellectual development. The aim of this study was to document the anatomical abnormalities which lead to the appearance of cerebral atrophy using magnetic resonance imaging (MRI) in the acute stage of kwashiorkor and to monitor changes during nutritional rehabilitation. Twelve children aged 6 to 37 months requiring admission to hospital for the treatment of kwashiorkor were studied. The children were evaluated clinically, biochemically, and by MRI of their brains on admission and 30 and 90 days later. Brain shrinkage was present in every child on admission. White and grey matter appeared equally affected and the myelination was normal for age. At 90 days, the cerebral changes had resolved in nine and improved substantially in the remainder, by which time serum proteins and weight for age were within the normal range. The findings of this study suggest that brain shrinkage associated with kwashiorkor reverses rapidly with nutritional rehabilitation.
Shrinkage and trajectory of the flat jet with inclination angle
Institute of Scientific and Technical Information of China (English)
Shufeng Ye; Yusheng Xie; Hongzhi Guo; Ye Huang; Shantong Jin
2003-01-01
The performance of the flat jet with an inclination angle was investigated by a water model. A mathematical model for theshrinkage and the trajectory of the flat jet with an inclination angle was derived theoretically and verified by experimental data of thewater model. The experimental results indicate that the inclination angle (α) has no influence on the shrinkage of the flat jet, theshrinkage of the flat jet along the width direction decreases with the increasing of the initial velocity at the exit (u0) and the initialthickness of the flat jet (t0). Enough bigger initial exit velocity (u0) and initial thickness can suppress the shrinkage of the flat jetalong the width direction and keep the flat jet stabilized. In addition, the trajectory of the flat jet with an inclination angle is parabolicand must be taking into consideration when to determine the striking distance.
New System of Shrinkage Measurement through Cement Mortars Drying
Morón, Carlos; Saiz, Pablo; Ferrández, Daniel; García-Fuentevilla, Luisa
2017-01-01
Cement mortar is used as a conglomerate in the majority of construction work. There are multiple variants of cement according to the type of aggregate used in its fabrication. One of the major problems that occurs while working with this type of material is the excessive loss of moisture during cement hydration (setting and hardening), known as shrinkage, which provokes a great number of construction pathologies that are difficult to repair. In this way, the design of a new sensor able to measure the moisture loss of mortars at different age levels is useful to establish long-term predictions concerning mortar mass volume loss. The purpose of this research is the design and fabrication of a new capacitive sensor able to measure the moisture of mortars and to relate it with the shrinkage. PMID:28272297
Autogenous Shrinkage of High Strength Lightweight Aggregate Concrete
Institute of Scientific and Technical Information of China (English)
DING Qingjun; TIAN Yaogang; WANG Fazhou; ZHANG Feng; HU Shuguang
2005-01-01
The characteristic of autogenous shrinkage ( AS ) and its effect on high strength lightweight aggregate concrete (HSLAC) were studied. The experimental results show that the main shrinkage of high strength concrete is AS and the amount of cement can affect the AS of HSLAC remarkably. At the early stage the AS of HSLAC is lower than that of high strength normal concrete, but it has a large growth at the later stage. The AS of high strength normal concrete becomes stable at 90d age, but HSLAC still has a high AS growth. It is found that adjusting the volume rate of lightweight aggregate, mixing with a proper dosage of fly ash and raising the water saturation degree of lightweight aggregate can markedly reduce the AS rate of HSLAC.
Research and Application of the Mathematic Model for the Washing Shrinkage of Woven Fabric
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Having analyzed the relationships between washing shrinkage and weaving technique, parameters, material properties of woven fabrics and studied the shrinkage mechanism and its mathematical model of the plain fabric,researchers set up a shrinkage model of the twills and satins and proposed a method for calculating the washing shrinkage based on weaving technique and parameters of fabrics. Shrinkage experiments of silk habotai, silk twill and silk satin fabrics were performed. The results were compared with those of the theoretical computations, and it has been proven that the theoretical method is reliable.
Polymerization shrinkage of flowable resin-based restorative materials
Stavridakis, Minos M; Dietschi, Didier; Krejci, Ivo
2005-01-01
This study measured the linear polymerization displacement and polymerization forces induced by polymerization shrinkage of a series of flowable resin-based restorative materials. The materials tested were 22 flowable resin-based restorative materials (Admira Flow, Aelite Flow, Aeliteflow LV, Aria, Crystal Essence, Definite Flow, Dyract Flow, Filtek Flow, FloRestore, Flow-it, Flow-Line, Freedom, Glacier, OmegaFlo, PermaFlo, Photo SC, Revolution 2, Star Flow, Synergy Flow, Tetric Flow, Ultrase...
Super-resolution optical telescopes with local light diffraction shrinkage
Changtao Wang; Dongliang Tang; Yanqin Wang; Zeyu Zhao; Jiong Wang; Mingbo Pu; Yudong Zhang; Wei Yan; Ping Gao; Xiangang Luo
2015-01-01
Suffering from giant size of objective lenses and infeasible manipulations of distant targets, telescopes could not seek helps from present super-resolution imaging, such as scanning near-field optical microscopy, perfect lens and stimulated emission depletion microscopy. In this paper, local light diffraction shrinkage associated with optical super-oscillatory phenomenon is proposed for real-time and optically restoring super-resolution imaging information in a telescope system. It is found ...
Evaluating plastic shrinkage and permeability of polypropylene fiber reinforced concrete
Directory of Open Access Journals (Sweden)
G.M. Sadiqul Islam
2016-12-01
Full Text Available Plastic concrete is susceptible to develop cracks due to shrinkage in dry and windy conditions. Addition of fibers could reduce propagation of this crack. On the other hand, permeability determines the durability properties of concrete. This study evaluated strength, plastic shrinkage and permeability (gas and water of concrete incorporating ‘polypropylene’ fiber (aspect ratio 300 in various proportions (viz. 0.10%, 0.15%, 0.2%, 0.25% and 0.3% by volume of concrete. Plane concrete samples were also prepared and tested for reference purpose. Inclusion of 0.1% fiber gave minor reduction (2% in compressive strength while the tensile strength increased by 39% with same fiber content compared to the plain concrete. A significant reduction in crack generation, appearance period of first crack and crack area between plane concrete and fiber reinforced concretes was found. The experimental result with inclusion of 0.1–0.3% fiber in concrete indicated that plastic shrinkage cracks were reduced by 50–99% compared to the plain concrete. For reference concrete (without fiber, test within the high temperature and controlled humidity chamber gave higher crack width than the acceptable limit (3 mm specified by the ACI 224. With the inclusion of 0.1% fiber reduced the crack width down to 1 mm and the trend was continued with the addition of more fibers. However, results showed that with the addition of polypropylene fiber both water and gas permeability coefficient was increased. Therefore, it is concluded that the fiber reinforced concrete would work better for plastic shrinkage susceptible structural elements (flat elements such as slab; however, it requires careful judgement while applying to a water retaining structures.
Bayesian Face Sketch Synthesis.
Wang, Nannan; Gao, Xinbo; Sun, Leiyu; Li, Jie
2017-03-01
Exemplar-based face sketch synthesis has been widely applied to both digital entertainment and law enforcement. In this paper, we propose a Bayesian framework for face sketch synthesis, which provides a systematic interpretation for understanding the common properties and intrinsic difference in different methods from the perspective of probabilistic graphical models. The proposed Bayesian framework consists of two parts: the neighbor selection model and the weight computation model. Within the proposed framework, we further propose a Bayesian face sketch synthesis method. The essential rationale behind the proposed Bayesian method is that we take the spatial neighboring constraint between adjacent image patches into consideration for both aforementioned models, while the state-of-the-art methods neglect the constraint either in the neighbor selection model or in the weight computation model. Extensive experiments on the Chinese University of Hong Kong face sketch database demonstrate that the proposed Bayesian method could achieve superior performance compared with the state-of-the-art methods in terms of both subjective perceptions and objective evaluations.
PREDIKSI SHRINKAGE UNTUK MENGHINDARI CACAT PRODUK PADA PLASTIC INJECTION
Directory of Open Access Journals (Sweden)
Agus Dwi Anggono
2015-05-01
Full Text Available Plastic injection merupakan proses manufactur untuk membuat produk dengan bahan dasar plastic atau dalam kesempatan ini polypropylene. Pada proses tersebut seringkali terjadi cacat produk seperti pengerutan, retak, dimensi tidak sesuai dan kerusakan saat produk keluar dari mould, sehingga banyak material yang terbuang percuma. Meskipun cacat produk tersebut dipengaruhi banyak factor, tetapi yang paling utama adalah masalah shrinkage, atau penyusutan material setelah terjadi pendinginan. Sangat penting untuk melakukan prediksi lebih awal terjadinya penyusutan setelah pendinginan untuk menghindari cacat produk. Dalam penelitian ini akan dilakukan prediksi shrinkage yang akan digunakan untuk material polypropylene dengan cara perhitungan standar. Pembuatan modeling dalam bentuk 3D (tiga dimensi injection molding baik cavity maupun corenya dengan menggunakan CATIA, kemudian dilakukan analisis dengan software MoldFlow untuk pembuatan mesh dan memberikan batasan panas pada komponen sehingga dapat diketahui mode penyusutannya. Analisis ini akan memberikan gambaran tentang distribusi panas pada mould dan memberikan tentang gambaran aliran fluida. Pada analisis tersebut dapat dilihat gejala terjadinya cacat produk, jika hal itu terjadi maka perlu dilakukan perubahan shrinkage, sampai diperoleh hasil analisis yang baik.
The physical effects of an intra-aggregate structure on soil shrinkage
Chertkov, V Y
2014-01-01
Clay and soil containing it have shrinkage curves that are qualitatively different in shape. The objective of this work is to qualitatively show with maximum simplicity, how a clay shrinkage curve turns into a soil shrinkage curve. Because of the crack volume the measured shrinkage curve is not the single-valued feature of a soil. We use a concept of the reference shrinkage curve that is only stipulated by soil shrinkage without cracking, single-valued, and qualitatively similar to an observed shrinkage curve. We also use new concepts of an intra-aggregate soil structure: (i) a rigid superficial layer of aggregates that loses water during shrinkage; and (ii) lacunar pores (micro-cracks) inside an intra-aggregate clay that change in volume during shrinkage. Then, through a series of consecutive steps, illustrating each step by a separate graphic presentation, we move from a clay shrinkage curve to a soil shrinkage curve with predicted qualitative features that coincide with those experimentally observed in num...
Bayesian least squares deconvolution
Asensio Ramos, A.; Petit, P.
2015-11-01
Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Hybrid Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2012-01-01
Bayesian Optimization aims at optimizing an unknown non-convex/concave function that is costly to evaluate. We are interested in application scenarios where concurrent function evaluations are possible. Under such a setting, BO could choose to either sequentially evaluate the function, one input at a time and wait for the output of the function before making the next selection, or evaluate the function at a batch of multiple inputs at once. These two different settings are commonly referred to as the sequential and batch settings of Bayesian Optimization. In general, the sequential setting leads to better optimization performance as each function evaluation is selected with more information, whereas the batch setting has an advantage in terms of the total experimental time (the number of iterations). In this work, our goal is to combine the strength of both settings. Specifically, we systematically analyze Bayesian optimization using Gaussian process as the posterior estimator and provide a hybrid algorithm t...
Bayesian least squares deconvolution
Ramos, A Asensio
2015-01-01
Aims. To develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods. We consider LSD under the Bayesian framework and we introduce a flexible Gaussian Process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results. We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Bayesian Exploratory Factor Analysis
DEFF Research Database (Denmark)
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.;
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corr......This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor......, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates...
Center, Julian L.; Knuth, Kevin H.
2011-03-01
Visual odometry refers to tracking the motion of a body using an onboard vision system. Practical visual odometry systems combine the complementary accuracy characteristics of vision and inertial measurement units. The Mars Exploration Rovers, Spirit and Opportunity, used this type of visual odometry. The visual odometry algorithms in Spirit and Opportunity were based on Bayesian methods, but a number of simplifying approximations were needed to deal with onboard computer limitations. Furthermore, the allowable motion of the rover had to be severely limited so that computations could keep up. Recent advances in computer technology make it feasible to implement a fully Bayesian approach to visual odometry. This approach combines dense stereo vision, dense optical flow, and inertial measurements. As with all true Bayesian methods, it also determines error bars for all estimates. This approach also offers the possibility of using Micro-Electro Mechanical Systems (MEMS) inertial components, which are more economical, weigh less, and consume less power than conventional inertial components.
Probabilistic Inferences in Bayesian Networks
Ding, Jianguo
2010-01-01
This chapter summarizes the popular inferences methods in Bayesian networks. The results demonstrates that the evidence can propagated across the Bayesian networks by any links, whatever it is forward or backward or intercausal style. The belief updating of Bayesian networks can be obtained by various available inference techniques. Theoretically, exact inferences in Bayesian networks is feasible and manageable. However, the computing and inference is NP-hard. That means, in applications, in ...
Bayesian multiple target tracking
Streit, Roy L
2013-01-01
This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements
Bayesian estimation of keyword confidence in Chinese continuous speech recognition
Institute of Scientific and Technical Information of China (English)
HAO Jie; LI Xing
2003-01-01
In a syllable-based speaker-independent Chinese continuous speech recognition system based on classical Hidden Markov Model (HMM), a Bayesian approach of keyword confidence estimation is studied, which utilizes both acoustic layer scores and syllable-based statistical language model (LM) score. The Maximum a posteriori (MAP) confidence measure is proposed, and the forward-backward algorithm calculating the MAP confidence scores is deduced. The performance of the MAP confidence measure is evaluated in keyword spotting application and the experiment results show that the MAP confidence scores provide high discriminability for keyword candidates. Furthermore, the MAP confidence measure can be applied to various speech recognition applications.
Bayesian methods for hackers probabilistic programming and Bayesian inference
Davidson-Pilon, Cameron
2016-01-01
Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples a...
DEFF Research Database (Denmark)
Jensen, Finn Verner; Nielsen, Thomas Dyhre
2016-01-01
and edges. The nodes represent variables, which may be either discrete or continuous. An edge between two nodes A and B indicates a direct influence between the state of A and the state of B, which in some domains can also be interpreted as a causal relation. The wide-spread use of Bayesian networks...
DEFF Research Database (Denmark)
Antoniou, Constantinos; Harrison, Glenn W.; Lau, Morten I.;
2015-01-01
A large literature suggests that many individuals do not apply Bayes’ Rule when making decisions that depend on them correctly pooling prior information and sample data. We replicate and extend a classic experimental study of Bayesian updating from psychology, employing the methods of experimental...
Bayesian modelling of geostatistical malaria risk data
Directory of Open Access Journals (Sweden)
L. Gosoniu
2006-11-01
Full Text Available Bayesian geostatistical models applied to malaria risk data quantify the environment-disease relations, identify significant environmental predictors of malaria transmission and provide model-based predictions of malaria risk together with their precision. These models are often based on the stationarity assumption which implies that spatial correlation is a function of distance between locations and independent of location. We relax this assumption and analyse malaria survey data in Mali using a Bayesian non-stationary model. Model fit and predictions are based on Markov chain Monte Carlo simulation methods. Model validation compares the predictive ability of the non-stationary model with the stationary analogue. Results indicate that the stationarity assumption is important because it influences the significance of environmental factors and the corresponding malaria risk maps.
Bayesian modelling of geostatistical malaria risk data.
Gosoniu, L; Vounatsou, P; Sogoba, N; Smith, T
2006-11-01
Bayesian geostatistical models applied to malaria risk data quantify the environment-disease relations, identify significant environmental predictors of malaria transmission and provide model-based predictions of malaria risk together with their precision. These models are often based on the stationarity assumption which implies that spatial correlation is a function of distance between locations and independent of location. We relax this assumption and analyse malaria survey data in Mali using a Bayesian non-stationary model. Model fit and predictions are based on Markov chain Monte Carlo simulation methods. Model validation compares the predictive ability of the non-stationary model with the stationary analogue. Results indicate that the stationarity assumption is important because it influences the significance of environmental factors and the corresponding malaria risk maps.
Bayesian Cosmological inference beyond statistical isotropy
Souradeep, Tarun; Das, Santanu; Wandelt, Benjamin
2016-10-01
With advent of rich data sets, computationally challenge of inference in cosmology has relied on stochastic sampling method. First, I review the widely used MCMC approach used to infer cosmological parameters and present a adaptive improved implementation SCoPE developed by our group. Next, I present a general method for Bayesian inference of the underlying covariance structure of random fields on a sphere. We employ the Bipolar Spherical Harmonic (BipoSH) representation of general covariance structure on the sphere. We illustrate the efficacy of the method with a principled approach to assess violation of statistical isotropy (SI) in the sky maps of Cosmic Microwave Background (CMB) fluctuations. The general, principled, approach to a Bayesian inference of the covariance structure in a random field on a sphere presented here has huge potential for application to other many aspects of cosmology and astronomy, as well as, more distant areas of research like geosciences and climate modelling.
Bayesian analysis of cosmic structures
Kitaura, Francisco-Shu
2011-01-01
We revise the Bayesian inference steps required to analyse the cosmological large-scale structure. Here we make special emphasis in the complications which arise due to the non-Gaussian character of the galaxy and matter distribution. In particular we investigate the advantages and limitations of the Poisson-lognormal model and discuss how to extend this work. With the lognormal prior using the Hamiltonian sampling technique and on scales of about 4 h^{-1} Mpc we find that the over-dense regions are excellent reconstructed, however, under-dense regions (void statistics) are quantitatively poorly recovered. Contrary to the maximum a posteriori (MAP) solution which was shown to over-estimate the density in the under-dense regions we obtain lower densities than in N-body simulations. This is due to the fact that the MAP solution is conservative whereas the full posterior yields samples which are consistent with the prior statistics. The lognormal prior is not able to capture the full non-linear regime at scales ...
Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding
Desmal, Abdulla
2015-04-13
A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.
Sonar target enhancement by shrinkage of incoherent wavelet coefficients.
Hunter, Alan J; van Vossen, Robbert
2014-01-01
Background reverberation can obscure useful features of the target echo response in broadband low-frequency sonar images, adversely affecting detection and classification performance. This paper describes a resolution and phase-preserving means of separating the target response from the background reverberation noise using a coherence-based wavelet shrinkage method proposed recently for de-noising magnetic resonance images. The algorithm weights the image wavelet coefficients in proportion to their coherence between different looks under the assumption that the target response is more coherent than the background. The algorithm is demonstrated successfully on experimental synthetic aperture sonar data from a broadband low-frequency sonar developed for buried object detection.
Photoelastic study of shrinkage fitted components for a gasturbine engine
Govindaraju, T. V.; Maheshappa, H.; Govindaraju, N.; Gargesa, G.
A 3D photoelastic model of shrink-fitted components of a gas turbine engine such as low-pressure main shaft and compressor adopter shaft (or hub) are used to perform a photo-elastic investigation of shrink-fitted components for different relative thickness ratio and different contact length ratio. The relative rigidity of the hub is found to increase as the relative thickness ratio increases, and the relative rigidity is found to increase as the contact length ratio decreases. An optimization of the geometry of the shrinkage-fitted components is also obtained.
Occupancy Grid Map Merging Using Feature Maps
2010-11-01
Gonzalez, “Toward a unified bayesian approach to hybrid metric-topological SLAM,” IEEE Transactions on Robotics , 24(2), April 2008, 259-270. [14] G...Risetti, C. Stachniss, and W. Burgard, “Improved Techniques for grid mapping with Rao-Blackwellized Particle Filter,” IEEE Transactions on Robotics , 23
DEFF Research Database (Denmark)
Snoeck, Didier; Jensen, Ole Mejlhede; De Belie, Nele
2016-01-01
A promising way to mitigate autogenous shrinkage in cementitious materials with a low water-to-binder ratio is internal curing by the use of superabsorbent polymers. Superabsorbent polymers are able to absorb multiple times their weight in water and can be applied as an internal water reservoir...... shrinkage in materials blended with fly ash or blast-furnace slag remain scarce, especially after one week of age. This paper focuses on the autogenous shrinkage by performing manual and automated shrinkage measurements up to one month of age. Without superabsorbent polymers, autogenous shrinkage...... was reduced in cement pastes with the supplementary cementitious materials versus Portland cement pastes. At later ages, the rate of autogenous shrinkage is higher due to the pozzolanic activity of the supplementary cementitious materials. Internal curing by means of superabsorbent polymers is successful...
Shrinkage and microstructural development during drying of organically modified silica xerogels
Energy Technology Data Exchange (ETDEWEB)
Raman, N.K. [New Mexico Univ., Albuquerque, NM (United States); Wallace, S. [Nanopore Corp., Albuquerque, NM (United States); Brinker, C.J. [New Mexico Univ., Albuquerque, NM (United States)]|[Sandia National Labs., Albuquerque, NM (United States)
1996-07-01
We have studied the different driving forces behind syneresis in MTES/TEOS gels by aging them in different H{sub 2}O/EtOH pore fluids. We show using shrinkage, density, contact angle, and N{sub 2} sorption measurements, the influence of gel/solvent interactions on the microstructural evolution during drying. Competing effects of syneresis (that occurs during aging) and drying shrinkage resulted in the overall linear shrinkage of the organically modified gels to be constant at {approximately}50%. Increasing the hydrophobicity of the gels caused the driving force for syneresis to change from primarily condensation reactions to a combination of condensation and solid/liquid interfacial energy. In addition the condensation driven shrinkage was observed to be irreversible, whereas the interfacial free energy driven shrinkage was observed to be partially reversible. Nitrogen sorption experiments show that xerogels with the same overall extent of shrinkage can have vastly different microstructures due to the effects of microphase separation.
Shrinkage and cracking behavior of high performance concretes containing chemical admixtures
Institute of Scientific and Technical Information of China (English)
亓萌; 李宗津; 马保国
2002-01-01
Modern concretes often incorporate several chemical admixtures to alter the properties of fresh or hardened concrete. In this work, the influences of three types of chemical admixtures, calcium nitrite inhibitor (CNI), retarder (D-17) and superplasticizer (W-19) on free shrinkage and restrained shrinkage cracking of high performance concrete were experimentally investigated. The test results showed that, with the same water to binder ratio (0.4), mixtures containing D-17 of 0.25 percent or higher ratio of W-19 (2.76 percent) all exhibited a reduction in free shrinkage and shrinkage cracking width. However, the incorporations of various ratios of CNI into mixtures led to an increase in free shrinkage and shrinkage cracking width as compared to control mixture. In order to study the influence of CNI, the microstructure of concrete mixture containing CNI were investigated by Mercury Intrusion Porosimetry as well as Scanning Electronic Microscopy(SEM) technique.
Institute of Scientific and Technical Information of China (English)
WUYi-qiang; HAYASHIKazuo; LIUYuan; CAIYing-chun; SUGIMORIMasatoshi; LUOJian-ju
2005-01-01
Collapse-type shrinkage is one of highly refractory drying defects in low-medium density plantation-grown eucalypt wood used as solid wood products. Basic density (BD), microfibril angle (MFA), double fibre cell wall thickness (DWT), proportion of ray parenchyma (RP), unit cell wall shrinkage, total shrinkage and residual collapse, which are associated with collapse-type shrinkage characteristics, were investigated by using simple regression method for three species of collapse-susceptible Eucalyptus urophyll, E. grandis and E.urophyllaxE.grandis, planted at Dong-Men Forest Farm in Guangxi autonomous region, China. The results indicated that : unit cell wall shrinkage had a extremely strong positive correlation with BD, moderately strong positive correlation with DWT, and a weakly or moderately negative correlation with RP and MFA; total shrinkage was positively correlated with BD, DWT and RP and negatively related to MFA, but not able to be predicted ideally by any examined factors alone owing to lower R2 value (R2≤0.5712); residual collapse was negatively correlated with BD and DWT, linearly positively correlated with MFA, and had strongly positive linear correlation with RP. It is concluded that BD can be used as single factor (R2≥0.9412) to predicate unit cell wall shrinkage and RP is the relatively sound indicator for predicting residual collapse
Impaired decision-making and brain shrinkage in alcoholism.
Le Berre, A-P; Rauchs, G; La Joie, R; Mézenge, F; Boudehent, C; Vabret, F; Segobin, S; Viader, F; Allain, P; Eustache, F; Pitel, A-L; Beaunieux, H
2014-03-01
Alcohol-dependent individuals usually favor instant gratification of alcohol use and ignore its long-term negative consequences, reflecting impaired decision-making. According to the somatic marker hypothesis, decision-making abilities are subtended by an extended brain network. As chronic alcohol consumption is known to be associated with brain shrinkage in this network, the present study investigated relationships between brain shrinkage and decision-making impairments in alcohol-dependent individuals early in abstinence using voxel-based morphometry. Thirty patients performed the Iowa Gambling Task and underwent a magnetic resonance imaging investigation (1.5T). Decision-making performances and brain data were compared with those of age-matched healthy controls. In the alcoholic group, a multiple regression analysis was conducted with two predictors (gray matter [GM] volume and decision-making measure) and two covariates (number of withdrawals and duration of alcoholism). Compared with controls, alcoholics had impaired decision-making and widespread reduced gray matter volume, especially in regions involved in decision-making. The regression analysis revealed links between high GM volume in the ventromedial prefrontal cortex, dorsal anterior cingulate cortex and right hippocampal formation, and high decision-making scores (Palcoholism may result from impairment of both emotional and cognitive networks.
Response Predicting LTCC Firing Shrinkage: A Response Surface Analysis Study
Energy Technology Data Exchange (ETDEWEB)
Girardi, Michael; Barner, Gregg; Lopez, Cristie; Duncan, Brent; Zawicki, Larry
2009-02-25
The Low Temperature Cofired Ceramic (LTCC) technology is used in a variety of applications including military/space electronics, wireless communication, MEMS, medical and automotive electronics. The use of LTCC is growing due to the low cost of investment, short development time, good electrical and mechanical properties, high reliability, and flexibility in design integration (3 dimensional (3D) microstructures with cavities are possible)). The dimensional accuracy of the resulting x/y shrinkage of LTCC substrates is responsible for component assembly problems with the tolerance effect that increases in relation to the substrate size. Response Surface Analysis was used to predict product shrinkage based on specific process inputs (metal loading, layer count, lamination pressure, and tape thickness) with the ultimate goal to optimize manufacturing outputs (NC files, stencils, and screens) in achieving the final product design the first time. Three (3) regression models were developed for the DuPont 951 tape system with DuPont 5734 gold metallization based on green tape thickness.
Physical Model of Drying Shrinkage of Recycled Aggregate Concrete
Institute of Scientific and Technical Information of China (English)
GUO Yuanchen; WANG Xue; QIAN Jueshi
2015-01-01
We prepared concretes (RC0, RC30, and RC100) with three different mixes. The pore-size distribution parameters of RAC were examined by high-precision mercury intrusion method (MIM) and nuclear magnetic resonance (NMR) imaging. A capillary-bundle physical model with random-distribution pores (improved model, IM) was established according to the parameters, and dry-shrinkage strain values were calculated and verified. Results show that in all pore types, capillary pores, and gel pores have the greatest impacts on concrete shrinkage, especially for pores 2.5-50 and 50-100 nm in size. The median radii are 34.2, 31, and 34 nm for RC0, RC30, and RC100, respectively. Moreover, the internal micropore size distribution of RC0 differs from that of RC30 and RC100, and the pore descriptions of MIM and NMR are consistent both in theory and in practice. Compared with the traditional capillary-bundle model, the calculated results of IM have higher accuracy as demonstrated by experimental veriifcation.
Design changes of device to investigation of alloys linear contraction and shrinkage stresses
Directory of Open Access Journals (Sweden)
J. Mutwil
2009-07-01
Full Text Available Some design changes in device elaborated by author to examination of linear contraction and shrinkage stresses progress of metals and alloys during– and after solidification have been described. The introduced changes have been focused on design of closing of shrinkage test rod mould. The introduced changes have been allowed to simplify a mounting procedure of thermocouples measuring a temperature of the shrinkage rod casting (in 6 points. Exemplary investigation results of linear contraction and shrinkage stresses development in Al-Si13.5% alloy have been presented.
Probability and Bayesian statistics
1987-01-01
This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
DEFF Research Database (Denmark)
Mørup, Morten; Schmidt, Mikkel N
2012-01-01
Many networks of scientific interest naturally decompose into clusters or communities with comparatively fewer external than internal links; however, current Bayesian models of network communities do not exert this intuitive notion of communities. We formulate a nonparametric Bayesian model...... consistent with ground truth, and on real networks, it outperforms existing approaches in predicting missing links. This suggests that community structure is an important structural property of networks that should be explicitly modeled....... for community detection consistent with an intuitive definition of communities and present a Markov chain Monte Carlo procedure for inferring the community structure. A Matlab toolbox with the proposed inference procedure is available for download. On synthetic and real networks, our model detects communities...
Bayesian Independent Component Analysis
DEFF Research Database (Denmark)
Winther, Ole; Petersen, Kaare Brandt
2007-01-01
In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...... in a Matlab toolbox, is demonstrated for non-negative decompositions and compared with non-negative matrix factorization....
Bayesian theory and applications
Dellaportas, Petros; Polson, Nicholas G; Stephens, David A
2013-01-01
The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and devel...
The effect of fibers on the loss of water by evaporation and shrinkage of concrete
Directory of Open Access Journals (Sweden)
N. M. P. Pillar
Full Text Available Shrinkage is one of the least desirable attributes in concrete. Large areas of exposed concrete surfaces , such as in shotcrete tunnel linings, where it is practically impossible to make a moist cure, are highly susceptible to plastic shrinkage at early ages. The autogenous and drying shrinkage can lead to states of greater than threshold strength, causing fracture, mechanical damage and lack of durability of concrete structures. The addition of fibers can greatly reduce plastic shrinkage, but has limited effect in mitigating autogenous and drying shrinkage. To evaluate the performance of polypropylene and steel fibers to understand their effect on shrinkage of concrete, a study was carried out to relate the loss of water from the paste and the shrinkage during the first 28 days of age, and compare it with a control mix without fiber. The loss of water was obtained by the weight loss of the specimens at different ages, since the only component that could contribute for the loss of weight was the water lost by the paste of the concrete. And the paste itself is the only source of shrinkage. Uniaxial compressive tests from very early ages enabled the determination of time when plastic shrinkage ended. It was observed that the control concrete mix lost three times more water and developed plastic and drying shrinkage 60 % higher than the fiber reinforced concrete mixes. It was possible to demonstrate that the reduced loss of water caused by the incorporation of fibers is related to the mitigation of plastic shrinkage. It was observed that the fibers are effective to restrain the movement of water through the cement paste in the plastic state, however such effect is limited after concrete starts the hardening state.
Creep and shrinkage effects on integral abutment bridges
Munuswamy, Sivakumar
Integral abutment bridges provide bridge engineers an economical design alternative to traditional bridges with expansion joints owing to the benefits, arising from elimination of expensive joints installation and reduced maintenance cost. The superstructure for integral abutment bridges is cast integrally with abutments. Time-dependent effects of creep, shrinkage of concrete, relaxation of prestressing steel, temperature gradient, restraints provided by abutment foundation and backfill and statical indeterminacy of the structure introduce time-dependent variations in the redundant forces. An analytical model and numerical procedure to predict instantaneous linear behavior and non-linear time dependent long-term behavior of continuous composite superstructure are developed in which the redundant forces in the integral abutment bridges are derived considering the time-dependent effects. The redistributions of moments due to time-dependent effects have been considered in the analysis. The analysis includes nonlinearity due to cracking of the concrete, as well as the time-dependent deformations. American Concrete Institute (ACI) and American Association of State Highway and Transportation Officials (AASHTO) models for creep and shrinkage are considered in modeling the time dependent material behavior. The variations in the material property of the cross-section corresponding to the constituent materials are incorporated and age-adjusted effective modulus method with relaxation procedure is followed to include the creep behavior of concrete. The partial restraint provided by the abutment-pile-soil system is modeled using discrete spring stiffness as translational and rotational degrees of freedom. Numerical simulation of the behavior is carried out on continuous composite integral abutment bridges and the deformations and stresses due to time-dependent effects due to typical sustained loads are computed. The results from the analytical model are compared with the
DEFF Research Database (Denmark)
Luo, Yangjun; Wang, Michael Yu; Zhou, Mingdong;
2015-01-01
To take into account the shrinkage effect in the early stage of Reinforced Concrete (RC) design, an effective continuum topology optimization method is presented in this paper. Based on the power-law interpolation, shrinkage of concrete is numerically simulated by introducing an additional design...
T.T. Tauböck; A.J. Feilzer; W. Buchalla; C.J. Kleverlaan; I. Krejci; T. Attin
2014-01-01
This study investigated the influence of modulated photo-activation on axial polymerization shrinkage, shrinkage force, and hardening of light- and dual-curing resin-based composites. Three light-curing resin composites (SDR bulk-fill, Esthet X flow, and Esthet X HD) and one dual-curing material (Re
1992-07-01
unidirectional composite micromechanics model The constituent fiber properties (constant), the resin properties and chemical shrinkage (cure dependent...during cure. Changes in the resin properties directly influence the mechanical properties in the composite, and chemical shrinkage represents a...xA (5) The expansion coefficients, otL and or, are based on the micromechanics model utilizing constant fiber properties. cure dependent resin
Modeling dental composite shrinkage by digital image correlation and finite element methods
Chen, Terry Yuan-Fang; Huang, Pin-Sheng; Chuang, Shu-Fen
2014-10-01
Dental composites are light-curable resin-based materials with an inherent defect of polymerization shrinkage which may cause tooth deflection and debonding of restorations. This study aimed to combine digital image correlation (DIC) and finite element analysis (FEA) to model the shrinkage behaviors under different light curing regimens. Extracted human molars were prepared with proximal cavities for composite restorations, and then divided into three groups to receive different light curing protocols: regular intensity, low intensity, and step-curing consisting of low and high intensities. For each tooth, the composite fillings were consecutively placed under both unbonded and bonded conditions. At first, the shrinkage of the unbonded restorations was analyzed by DIC and adopted as the setting of FEA. The simulated shrinkage behaviors obtained from FEA were further validated by the measurements in the bonded cases. The results showed that different light curing regimens affected the shrinkage in unbonded restorations, with regular intensity showing the greatest shrinkage strain on the top surface. The shrinkage centers in the bonded cases were located closer to the cavity floor than those in the unbonded cases, and were less affected by curing regimens. The FEA results showed that the stress was modulated by the accumulated light energy density, while step-curing may alleviate the tensile stress along the cavity walls. In this study, DIC provides a complete description of the polymerization shrinkage behaviors of dental composites, which may facilitate the stress analysis in the numerical investigation.
Shrinkage reduction of dental composites by addition of expandable zirconia filler
DEFF Research Database (Denmark)
Skovgaard, M.; Almdal, Kristoffer; Sørensen, Bent F.;
2011-01-01
A problem with dental resin composites is the polymerization shrinkage, which makes the filling loosen from the tooth or induces crack formation. We have developed an expandable metastable tetragonal zirconia filler, which upon reaction with water, is able to counter the polymer shrinkage...
Magnitude, modeling and significance of swelling and shrinkage processes in clay soils.
Bronswijk, J.J.B.
1991-01-01
The dynamic process of swelling and shrinkage in clay soils has significant practical consequences, such as the rapid transport of water and solutes via shrinkage cracks to the subsoil, and the destruction of buildings and roads on clay soils. In order to develop measuring methods and computer simul
Autogenous shrinkage in high-performance cement paste: An evaluation of basic mechanisms
DEFF Research Database (Denmark)
Lura, Pietro; Jensen, Ole Mejlhede; van Breugel, Klaas
2003-01-01
In this paper, various mechanisms Suggested to cause autogenous shrinkage are presented. The mechanisms are evaluated from the point of view of their soundness and applicability to quantitative modeling of autogenous shrinkage. The capillary tension approach is advantageous, because it has a soun...
Effect of cure cycle on enthalpy relaxation and post shrinkage in neat epoxy and epoxy composites
DEFF Research Database (Denmark)
Jensen, Martin; Jakobsen, Johnny
2016-01-01
. Enthalpy recovery is found to exert a minor impact on the sample dimension during reheating since a non-reversing shrinkage is observed during reheating. This shrinkage is ascribed to structural changes on molecular level in the specimen and it is inferred that samples with a high initial disorder only...
To develop a quantitative method for predicting shrinkage porosity in squeeze casting
Institute of Scientific and Technical Information of China (English)
Shaomin Li; Kenichiro Mine; Shinji Sanakanishi; Koichi Anzai
2009-01-01
In order to secure high strength and high elongation of suspension parts, it is critical to predict shrinkage porosity quantitatively. A new simulation method for quantitative predic'don of shrinkage porosity when replenishing molten metal has been proposed for squeeze casting process. To examine the accuracy of the calculation model, the proposed method was applied to a plate model.
Influence of ultra-fine fly ash on hydration shrinkage of cement paste
Institute of Scientific and Technical Information of China (English)
GAO Ying-li; ZHOU Shi-qiong
2005-01-01
Hydration shrinkage generated by cement hydration is the cause of autogenous shrinkage of high strength concrete. It may result in the volume change and even cracking of mortar and concrete. According to the data analysis in a series of experimental studies, the influence of ultra-fine fly ash on the hydration shrinkage of composite cementitious materials was investigated. It is found that ultra-fine fly ash can reduce the hydration shrinkage of cement paste effectively, and the more the ultra-fine fly ash, the less the hydration shrinkage. Compared with cement paste without the ultra-fine fly ash, the shrinkage ratio of cement paste reduces from 23.4% to 39.7% when the ultra-fine fly ash replaces cement from 20% to 50%. Moreover, the microscopic mechanism of the ultra-fine fly ash restraining the hydration shrinkage was also studied by scanning electron microscopy, X-ray diffraction and hydrated equations. The results show that the hydration shrinkage can be restrained to a certain degree because the ultra-fine fly ash does not participate in the hydration at the early stage and the secondary hydration products are different at the later stage.
Bayesian geostatistics in health cartography: the perspective of malaria.
Patil, Anand P; Gething, Peter W; Piel, Frédéric B; Hay, Simon I
2011-06-01
Maps of parasite prevalences and other aspects of infectious diseases that vary in space are widely used in parasitology. However, spatial parasitological datasets rarely, if ever, have sufficient coverage to allow exact determination of such maps. Bayesian geostatistics (BG) is a method for finding a large sample of maps that can explain a dataset, in which maps that do a better job of explaining the data are more likely to be represented. This sample represents the knowledge that the analyst has gained from the data about the unknown true map. BG provides a conceptually simple way to convert these samples to predictions of features of the unknown map, for example regional averages. These predictions account for each map in the sample, yielding an appropriate level of predictive precision.
Monitoring of collagen shrinkage by use of second harmonic generation microscopy
Lin, Sung-Jan; Chen, Jau-Shiuh; Lo, Wen; Sun, Yen; Chen, Wei-Liang; Chan, Jung-Yi; Tan, Hsin-Yuan; Lin, Wei-Chou; Hsu, Chih-Jung; Young, Tai-Horng; Jee, Shiou-Hwa; Dong, Chen-Yuan
2006-02-01
Thermal treatment induced collagen shrinkage has a great number of applications in medical practice. Clinically, the there is lack of reliable non-invasive methods to quantify the shrinkage. Overt treatment by heat application can lead to devastating results. We investigate the serial changes of collagen shrinkage by thermal treatment of rat tail tendons. The change in length is correlated with the finding in second harmonic generation microscopy and histology. Rat tail tendon shortens progressively during initial thermal treatment. After a certain point in time, the length then remains almost constant despite further thermal treatment. The intensity of second harmonic generation signals also progressively decreases initially and then remains merely detectable upon further thermal treatment. It prompts us to develop a mathematic model to quantify the dependence of collagen shrinkage on changes of SHG intensity. Our results show that SHG intensity can be used to predict the degree of collagen shrinkage during thermal treatment for biomedical applications.
DEFF Research Database (Denmark)
Hartelius, Karsten; Carstensen, Jens Michael
2003-01-01
A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which...... nodes and the arc prior models variations in row and column spacing across the grid. Grid matching is done by placing an initial rough grid over the image and applying an ensemble annealing scheme to maximize the posterior distribution of the grid. The method can be applied to noisy images with missing...
Congdon, Peter
2014-01-01
This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBU
Bayesian nonparametric data analysis
Müller, Peter; Jara, Alejandro; Hanson, Tim
2015-01-01
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.
Classification using Bayesian neural nets
J.C. Bioch (Cor); O. van der Meer; R. Potharst (Rob)
1995-01-01
textabstractRecently, Bayesian methods have been proposed for neural networks to solve regression and classification problems. These methods claim to overcome some difficulties encountered in the standard approach such as overfitting. However, an implementation of the full Bayesian approach to neura
Bayesian Intersubjectivity and Quantum Theory
Pérez-Suárez, Marcos; Santos, David J.
2005-02-01
Two of the major approaches to probability, namely, frequentism and (subjectivistic) Bayesian theory, are discussed, together with the replacement of frequentist objectivity for Bayesian intersubjectivity. This discussion is then expanded to Quantum Theory, as quantum states and operations can be seen as structural elements of a subjective nature.
Bayesian Approach for Inconsistent Information.
Stein, M; Beer, M; Kreinovich, V
2013-10-01
In engineering situations, we usually have a large amount of prior knowledge that needs to be taken into account when processing data. Traditionally, the Bayesian approach is used to process data in the presence of prior knowledge. Sometimes, when we apply the traditional Bayesian techniques to engineering data, we get inconsistencies between the data and prior knowledge. These inconsistencies are usually caused by the fact that in the traditional approach, we assume that we know the exact sample values, that the prior distribution is exactly known, etc. In reality, the data is imprecise due to measurement errors, the prior knowledge is only approximately known, etc. So, a natural way to deal with the seemingly inconsistent information is to take this imprecision into account in the Bayesian approach - e.g., by using fuzzy techniques. In this paper, we describe several possible scenarios for fuzzifying the Bayesian approach. Particular attention is paid to the interaction between the estimated imprecise parameters. In this paper, to implement the corresponding fuzzy versions of the Bayesian formulas, we use straightforward computations of the related expression - which makes our computations reasonably time-consuming. Computations in the traditional (non-fuzzy) Bayesian approach are much faster - because they use algorithmically efficient reformulations of the Bayesian formulas. We expect that similar reformulations of the fuzzy Bayesian formulas will also drastically decrease the computation time and thus, enhance the practical use of the proposed methods.
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael
2009-01-01
Since the 1980s, Bayesian Networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability-techniques (like fault trees...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk
Directory of Open Access Journals (Sweden)
Lewei Duan
2013-01-01
Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.
Sparse kernel learning with LASSO and Bayesian inference algorithm.
Gao, Junbin; Kwan, Paul W; Shi, Daming
2010-03-01
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers [Gao, J., Antolovich, M., & Kwan, P. H. (2008). L1 LASSO and its Bayesian inference. In W. Wobcke, & M. Zhang (Eds.), Lecture notes in computer science: Vol. 5360 (pp. 318-324); Wang, G., Yeung, D. Y., & Lochovsky, F. (2007). The kernel path in kernelized LASSO. In International conference on artificial intelligence and statistics (pp. 580-587). San Juan, Puerto Rico: MIT Press]. This paper is concerned with learning kernels under the LASSO formulation via adopting a generative Bayesian learning and inference approach. A new robust learning algorithm is proposed which produces a sparse kernel model with the capability of learning regularized parameters and kernel hyperparameters. A comparison with state-of-the-art methods for constructing sparse regression models such as the relevance vector machine (RVM) and the local regularization assisted orthogonal least squares regression (LROLS) is given. The new algorithm is also demonstrated to possess considerable computational advantages.
Bayesian Inference on Gravitational Waves
Directory of Open Access Journals (Sweden)
Asad Ali
2015-12-01
Full Text Available The Bayesian approach is increasingly becoming popular among the astrophysics data analysis communities. However, the Pakistan statistics communities are unaware of this fertile interaction between the two disciplines. Bayesian methods have been in use to address astronomical problems since the very birth of the Bayes probability in eighteenth century. Today the Bayesian methods for the detection and parameter estimation of gravitational waves have solid theoretical grounds with a strong promise for the realistic applications. This article aims to introduce the Pakistan statistics communities to the applications of Bayesian Monte Carlo methods in the analysis of gravitational wave data with an overview of the Bayesian signal detection and estimation methods and demonstration by a couple of simplified examples.
Gilbert, J L; Hasenwinkel, J M; Wixson, R L; Lautenschlager, E P
2000-10-01
A theoretical basis for understanding polymerization shrinkage of bone cement is presented based on density changes in converting monomer to polymer. Also, an experimental method, based on dilatometry and the Archimedes' principle is presented for highly precise and accurate measurement of unconstrained volumetric shrinkage of bone cement. Furthermore, a theoretical and experimental analysis of polymerization shrinkage in a constrained deformational state is presented to demonstrate that porosity can develop due to shrinkage. Six bone-cement conditions (Simplex-Ptrade mark vacuum and hand mixed, Endurancetrade mark vacuum mixed, and three two-solution experimental bone cements with higher initial monomer levels) were tested for volumetric shrinkage. It was found that shrinkage varied statistically (ptheory that they are the result of shrinkage. The results of this study show that shrinkage of bone cement under certain constrained conditions may result in the development of porosity at the implant-bone cement interface and elsewhere in the polymerizing cement mantle.
Approximate Bayesian computation.
Directory of Open Access Journals (Sweden)
Mikael Sunnåker
Full Text Available Approximate Bayesian computation (ABC constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology.
Borsboom, D.; Haig, B.D.
2013-01-01
Unlike most other statistical frameworks, Bayesian statistical inference is wedded to a particular approach in the philosophy of science (see Howson & Urbach, 2006); this approach is called Bayesianism. Rather than being concerned with model fitting, this position in the philosophy of science primar
Implementing Bayesian Vector Autoregressions Implementing Bayesian Vector Autoregressions
Directory of Open Access Journals (Sweden)
Richard M. Todd
1988-03-01
Full Text Available Implementing Bayesian Vector Autoregressions This paper discusses how the Bayesian approach can be used to construct a type of multivariate forecasting model known as a Bayesian vector autoregression (BVAR. In doing so, we mainly explain Doan, Littermann, and Sims (1984 propositions on how to estimate a BVAR based on a certain family of prior probability distributions. indexed by a fairly small set of hyperparameters. There is also a discussion on how to specify a BVAR and set up a BVAR database. A 4-variable model is used to iliustrate the BVAR approach.
Searching chemical space with the Bayesian Idea Generator.
van Hoorn, Willem P; Bell, Andrew S
2009-10-01
The Pfizer Global Virtual Library (PGVL) is defined as a set compounds that could be synthesized using validated protocols and monomers. However, it is too large (10(12) compounds) to search by brute-force methods for close analogues of a given input structure. In this paper the Bayesian Idea Generator is described which is based on a novel application of Bayesian statistics to narrow down the search space to a prioritized set of existing library arrays (the default is 16). For each of these libraries the 6 closest neighbors are retrieved from the existing compound file, resulting in a screenable hypothesis of 96 compounds. Using the Bayesian models for library space, the Pfizer file of singleton compounds has been mapped to library space and is optionally searched as well. The method is >99% accurate in retrieving known library provenance from an independent test set. The compounds retrieved strike a balance between similarity and diversity resulting in frequent scaffold hops. Four examples of how the Bayesian Idea Generator has been successfully used in drug discovery are provided. The methodology of the Bayesian Idea Generator can be used for any collection of compounds containing distinct clusters, and an example using compound vendor catalogues has been included.
Polymerisation shrinkage versus layer thickness of a dentine bonding resin: Method development
Directory of Open Access Journals (Sweden)
Jafarzadeh T
2002-07-01
Full Text Available Dentine bonding systems are usually unfilled, and so their shrinkage may be significant. High"nshrinkage may cause internal stress at the interface between resin-composite restoration and the dentine"nsubstrate. Failure of the adhesive interface may be observed due to the interna! stress. The aims of this"nstudy were:"nA To obtain a suitable method for measuring the kinetics of polymerisation shrinkage in unfilled resm at different thicknesses, particularly for thin films."nB Consideraing the effect of thickness on shrinkage."nScotchbond Multipurpose (3M adhesive bond resin was used. To overcome the particular challenges presented by thin films, a filled-ring measurement procedure was used. Also, a non-contact laser analogue displacement sensor system was developed and applied to measure polymerisation shrinkage. Regression analysis was performed on a complete data set. Non-linear regression analysis established a logarithmic relationship between polymerisation shrinkage and layer thickness. The method applied in this study was found to be sensitive and accurate procedure for determining photo-polymerisation shrinkage of thin films. Polymerisation shrinkage increased with logarithmic of the adhesive thickness.
Compositional Changes for Reduction of Polymerisation-Induced Shrinkage in Holographic Photopolymers
Directory of Open Access Journals (Sweden)
D. Cody
2016-01-01
Full Text Available Polymerisation-induced shrinkage is one of the main reasons why many photopolymer materials are not used for certain applications including holographic optical elements and holographic data storage. Here, two compositional changes for the reduction of shrinkage in an acrylamide-based photopolymer are reported. A holographic interferometric technique was used to study changes in the dynamics of the shrinkage processes occurring in the modified photopolymer during holographic recording in real time. Firstly, the effect of the replacement of the acrylamide monomer in the photopolymer composition with a larger monomer molecule, diacetone acrylamide, on polymerisation-induced shrinkage has been studied. A reduction in relative shrinkage of 10–15% is obtained using this compositional change. The second method tested for shrinkage reduction involved the incorporation of BEA-type zeolite nanoparticles in the acrylamide-based photopolymer. A reduction in relative shrinkage of 13% was observed for acrylamide photopolymer layers doped with 2.5% wt. BEA zeolites in comparison to the undoped photopolymer.
Effect of the key mixture parameters on shrinkage of reactive powder concrete.
Ahmad, Shamsad; Zubair, Ahmed; Maslehuddin, Mohammed
2014-01-01
Reactive powder concrete (RPC) mixtures are reported to have excellent mechanical and durability characteristics. However, such concrete mixtures having high amount of cementitious materials may have high early shrinkage causing cracking of concrete. In the present work, an attempt has been made to study the simultaneous effects of three key mixture parameters on shrinkage of the RPC mixtures. Considering three different levels of the three key mixture factors, a total of 27 mixtures of RPC were prepared according to 3(3) factorial experiment design. The specimens belonging to all 27 mixtures were monitored for shrinkage at different ages over a total period of 90 days. The test results were plotted to observe the variation of shrinkage with time and to see the effects of the key mixture factors. The experimental data pertaining to 90-day shrinkage were used to conduct analysis of variance to identify significance of each factor and to obtain an empirical equation correlating the shrinkage of RPC with the three key mixture factors. The rate of development of shrinkage at early ages was higher. The water to binder ratio was found to be the most prominent factor followed by cement content with the least effect of silica fume content.
Effect of the Key Mixture Parameters on Shrinkage of Reactive Powder Concrete
Directory of Open Access Journals (Sweden)
Shamsad Ahmad
2014-01-01
Full Text Available Reactive powder concrete (RPC mixtures are reported to have excellent mechanical and durability characteristics. However, such concrete mixtures having high amount of cementitious materials may have high early shrinkage causing cracking of concrete. In the present work, an attempt has been made to study the simultaneous effects of three key mixture parameters on shrinkage of the RPC mixtures. Considering three different levels of the three key mixture factors, a total of 27 mixtures of RPC were prepared according to 33 factorial experiment design. The specimens belonging to all 27 mixtures were monitored for shrinkage at different ages over a total period of 90 days. The test results were plotted to observe the variation of shrinkage with time and to see the effects of the key mixture factors. The experimental data pertaining to 90-day shrinkage were used to conduct analysis of variance to identify significance of each factor and to obtain an empirical equation correlating the shrinkage of RPC with the three key mixture factors. The rate of development of shrinkage at early ages was higher. The water to binder ratio was found to be the most prominent factor followed by cement content with the least effect of silica fume content.
Influence of fly ash fineness on water requirement and shrinkage of blended cement mortars
Directory of Open Access Journals (Sweden)
Vanissorn Vimonsatit
2015-12-01
Full Text Available In this paper, the influence of fly ash fineness on water requirement and shrinkage of blended cement mortar was studied. The results indicate that the water requirement and shrinkage characteristic of the blended cement mortar are dependent on fly ash fineness and replacement level. The use of coarse fly ash slightly reduces the water requirement but greatly reduced the drying and the autogenous shrinkage of the blended cement mortars and the reduction is more with an increase in the fly ash replacement level. The finer fly ashes further reduce the water requirement, but increase the drying and the autogenous shrinkages as compared with coarser fly ash. The incorporation of superplasticizer drastically reduces the water requirement, but the effect on the drying and autogenous shrinkages of the normal Portland cement mortar is small. However, for the fly ash mortar, the use of superplasticizer results in a decrease in drying shrinkage and in a substantial increase in the autogenous shrinkage particularly for the fine fly ash at a high replacement level.
Importance of shrinkage in empirical bayes estimates for diagnostics: problems and solutions.
Savic, Radojka M; Karlsson, Mats O
2009-09-01
Empirical Bayes ("post hoc") estimates (EBEs) of etas provide modelers with diagnostics: the EBEs themselves, individual prediction (IPRED), and residual errors (individual weighted residual (IWRES)). When data are uninformative at the individual level, the EBE distribution will shrink towards zero (eta-shrinkage, quantified as 1-SD(eta (EBE))/omega), IPREDs towards the corresponding observations, and IWRES towards zero (epsilon-shrinkage, quantified as 1-SD(IWRES)). These diagnostics are widely used in pharmacokinetic (PK) pharmacodynamic (PD) modeling; we investigate here their usefulness in the presence of shrinkage. Datasets were simulated from a range of PK PD models, EBEs estimated in non-linear mixed effects modeling based on the true or a misspecified model, and desired diagnostics evaluated both qualitatively and quantitatively. Identified consequences of eta-shrinkage on EBE-based model diagnostics include non-normal and/or asymmetric distribution of EBEs with their mean values ("ETABAR") significantly different from zero, even for a correctly specified model; EBE-EBE correlations and covariate relationships may be masked, falsely induced, or the shape of the true relationship distorted. Consequences of epsilon-shrinkage included low power of IPRED and IWRES to diagnose structural and residual error model misspecification, respectively. EBE-based diagnostics should be interpreted with caution whenever substantial eta- or epsilon-shrinkage exists (usually greater than 20% to 30%). Reporting the magnitude of eta- and epsilon-shrinkage will facilitate the informed use and interpretation of EBE-based diagnostics.
Directory of Open Access Journals (Sweden)
J. Mutwil
2009-07-01
Full Text Available Shrinkage phenomena during solidification and cooling of hypereutectic aluminium-silicon alloys (AlSi18, AlSi21 have been examined. A vertical shrinkage rod casting with circular cross-section (constant or fixed: tapered has been used as a test sample. Two type of experiments have been conducted: 1 on development of the test sample linear dimension changes (linear expansion/contraction, 2 on development of shrinkage stresses in the test sample. By the linear contraction experiments the linear dimension changes of the test sample and the metal test mould as well a temperature in six points of the test sample have been registered. By shrinkage stresses examination a shrinkage tension force and linear dimension changes of the test sample as well a temperature in three points of the test sample have been registered. Registered time dependences of the test bar and the test mould linear dimension changes have shown, that so-called pre-shrinkage extension has been mainly by mould thermal extension caused. The investigation results have shown that both: the linear contraction as well as the shrinkage stresses development are evident dependent on metal temperature in a warmest region the sample (thermal centre.
An integrated approach to soil structure, shrinkage, and cracking in samples and layers
Chertkov, V Y
2014-01-01
A recent model showed how a clay shrinkage curve is step-by-step transformed into the shrinkage curve of an aggregated soil at any clay content if it is measured on samples so small that cracks do not occur at shrinkage. Such a shrinkage curve was called a reference curve. The present work generalizes this model to any soil sample size or layer thickness, i.e., to any crack contribution to the shrinkage curve. The approach is based on: (i) recently suggested features of an intra-aggregate structure; (ii) detailed accounting for the contributions to the soil volume and water content during shrinkage; and (iii) new concepts of lacunar factor, crack factor, and critical sample size. The following input parameters are needed for the prediction: (i) all parameters determining the basic dependence of the reference shrinkage curve; (ii) parameters determining the critical sample size (structural porosity and minimum and maximum aggregate size at maximum swelling); and (iii) initial sample size or layer thickness. A ...
Book review: Bayesian analysis for population ecology
Link, William A.
2011-01-01
Brian Dennis described the field of ecology as “fertile, uncolonized ground for Bayesian ideas.” He continued: “The Bayesian propagule has arrived at the shore. Ecologists need to think long and hard about the consequences of a Bayesian ecology. The Bayesian outlook is a successful competitor, but is it a weed? I think so.” (Dennis 2004)
Ortega, Pedro A
2011-01-01
Discovering causal relationships is a hard task, often hindered by the need for intervention, and often requiring large amounts of data to resolve statistical uncertainty. However, humans quickly arrive at useful causal relationships. One possible reason is that humans use strong prior knowledge; and rather than encoding hard causal relationships, they encode beliefs over causal structures, allowing for sound generalization from the observations they obtain from directly acting in the world. In this work we propose a Bayesian approach to causal induction which allows modeling beliefs over multiple causal hypotheses and predicting the behavior of the world under causal interventions. We then illustrate how this method extracts causal information from data containing interventions and observations.
Blundell, Charles; Heller, Katherine A
2012-01-01
Hierarchical structure is ubiquitous in data across many domains. There are many hier- archical clustering methods, frequently used by domain experts, which strive to discover this structure. However, most of these meth- ods limit discoverable hierarchies to those with binary branching structure. This lim- itation, while computationally convenient, is often undesirable. In this paper we ex- plore a Bayesian hierarchical clustering algo- rithm that can produce trees with arbitrary branching structure at each node, known as rose trees. We interpret these trees as mixtures over partitions of a data set, and use a computationally efficient, greedy ag- glomerative algorithm to find the rose trees which have high marginal likelihood given the data. Lastly, we perform experiments which demonstrate that rose trees are better models of data than the typical binary trees returned by other hierarchical clustering algorithms.
Bayesian inference in geomagnetism
Backus, George E.
1988-01-01
The inverse problem in empirical geomagnetic modeling is investigated, with critical examination of recently published studies. Particular attention is given to the use of Bayesian inference (BI) to select the damping parameter lambda in the uniqueness portion of the inverse problem. The mathematical bases of BI and stochastic inversion are explored, with consideration of bound-softening problems and resolution in linear Gaussian BI. The problem of estimating the radial magnetic field B(r) at the earth core-mantle boundary from surface and satellite measurements is then analyzed in detail, with specific attention to the selection of lambda in the studies of Gubbins (1983) and Gubbins and Bloxham (1985). It is argued that the selection method is inappropriate and leads to lambda values much larger than those that would result if a reasonable bound on the heat flow at the CMB were assumed.
Flood control and shrinkage in the Haihe River Mouth
Institute of Scientific and Technical Information of China (English)
胡世雄; 王兆印; 李行伟
2001-01-01
Because of overusing water resources in the upper and middle reaches of the Haihe Basin, less and less water flows to the river mouth. The Haihe River flow is cut off in most time of the seasons, sediment deposited in the river mouth channel is rarely scoured away, and many of the river mouth channels have been shrinking quickly. The discharge capacity of the channel is consequently reduced greatly, which results in more and more serious flood hazard. Many tide gates have been built for storing fresh water and preventing the salty and turbid water. The channel downstream of the gate is silting up and people have to dredge the channel every year before the flood season. This paper studies the laws of the siltation and strategies controlling channel shrinkage. The strategies are digger dredging, trailer dredging, scouring with pumping water or storing tidal water, building double guiding dikes and building a new gate. Comparison of various strategies is performed, suggesting the most effective strategy con
An improved adaptive wavelet shrinkage for ultrasound despeckling
Indian Academy of Sciences (India)
P Nirmala Devi; R Asokan
2014-08-01
Ultrasound imaging is the most widely used medical diagnostic technique for clinical decision making, due to its ability to make real time imaging for moving structures, low cost and safety. However, its usefulness is degraded by the presence of signal dependent speckle noise. Several wavelet-based denoising schemes have been reported in the literature for the removal of speckle noise. This study proposes a new and improved adaptive wavelet shrinkage in the translational invariant domain. It exploits the knowledge of the correlation of the wavelet coefficients within and across the resolution scales. A preliminary coefficient classification representing useful image information and noise is performed with a novel inter-scale dependency measure. The spatial context adaptation of the wavelet coefficients within a subband is achieved by a local spatial adaptivity indicator, determined by using a truncation threshold. A weighted signal variance is estimated based on this measure and used in the determination of a subband adaptive threshold. The proposed thresholding function aims to reduce the fixed bias of the soft thresholding approach. Experiments conducted with the proposed filter are compared with the existing filtering algorithms in terms of Peak-Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity IndexMeasure (SSIM), Equivalent Number of Looks (ENL) and Edge Preservation Index (EPI). A comparison of the results shows that the proposed filter achieves an improvement in terms of quantitative measures and in terms of visual quality of the images.
Shrinkage/swelling of compacted clayey loose and dense soils
Nowamooz, Hossein; Masrouri, Farimah
2009-11-01
This Note presents an experimental study performed on expansive compacted loose and dense samples using osmotic oedometers. Several successive wetting and drying cycles were applied in a suction range between 0 and 8 MPa under different values of constant net vertical stress (15, 30, and 60 kPa). During the suction cycles, the dense samples showed cumulative swelling strains, while the loose samples showed volumetric shrinkage accumulation. At the end of the suction cycles, the volumetric strains converged to an equilibrium stage that indicated elastic behavior of the swelling soil for any further hydraulic variations. At this stage, the compression curves for the studied soil at the different imposed suctions (0, 2, and 8 MPa) converged towards the saturated state curve for the high applied vertical stresses. We defined this pressure as the saturation stress(P). The compression curves provided sufficient data to examine the soil mechanical behavior at the equilibrium stage. To cite this article: H. Nowamooz, F. Masrouri, C. R. Mecanique 337 (2009).
Shrinkage, abrasion, erosion and sorption of clay plasters
Directory of Open Access Journals (Sweden)
Minke, G.
2011-09-01
Full Text Available At the Buildung Research Institute (FEB, Faculty of Architecture, University of Kassel, Germany, in the last years several hundred tests were made to study the characteristics of different loam mortars in respect of their linear shrinkage, absorption of humidity and their resistance against abrasion and erosion. In order to get data about abrasion and erosion new test methods and special apparatusses were developed. The mortars tested, chosen from the market, showed extremely varying test results.
En el Laboratorio de Construcciones Experimentales (FEB de la Facultad de Arquitectura, Universidad de Kassel, Alemania, fueron testeados cientos de diferentes pruebas de revoque de barro para estudiar su contracción durante el secado, su absorción de humedad y su resistencia contra abrasión, erosión y absorción. Para recibir datos sobre abrasión y erosión, nuevas aparatos y metodos fueron desarrollados. Los resultados de los revoques comprados en el mercado muestran gran diferencias en los valores.
Super-resolution optical telescopes with local light diffraction shrinkage
Wang, Changtao; Tang, Dongliang; Wang, Yanqin; Zhao, Zeyu; Wang, Jiong; Pu, Mingbo; Zhang, Yudong; Yan, Wei; Gao, Ping; Luo, Xiangang
2015-12-01
Suffering from giant size of objective lenses and infeasible manipulations of distant targets, telescopes could not seek helps from present super-resolution imaging, such as scanning near-field optical microscopy, perfect lens and stimulated emission depletion microscopy. In this paper, local light diffraction shrinkage associated with optical super-oscillatory phenomenon is proposed for real-time and optically restoring super-resolution imaging information in a telescope system. It is found that fine target features concealed in diffraction-limited optical images of a telescope could be observed in a small local field of view, benefiting from a relayed metasurface-based super-oscillatory imaging optics in which some local Fourier components beyond the cut-off frequency of telescope could be restored. As experimental examples, a minimal resolution to 0.55 of Rayleigh criterion is obtained, and imaging complex targets and large targets by superimposing multiple local fields of views are demonstrated as well. This investigation provides an access for real-time, incoherent and super-resolution telescopes without the manipulation of distant targets. More importantly, it gives counterintuitive evidence to the common knowledge that relayed optics could not deliver more imaging details than objective systems.
An Iterative Shrinkage Approach to Total-Variation Image Restoration
Michailovich, Oleg
2009-01-01
The problem of restoration of digital images from their degraded measurements plays a central role in a multitude of practically important applications. A particularly challenging instance of this problem occurs in the case when the degradation phenomenon is modeled by an ill-conditioned operator. In such a case, the presence of noise makes it impossible to recover a valuable approximation of the image of interest without using some a priori information about its properties. Such a priori information is essential for image restoration, rendering it stable and robust to noise. Particularly, if the original image is known to be a piecewise smooth function, one of the standard priors used in this case is defined by the Rudin-Osher-Fatemi model, which results in total variation (TV) based image restoration. The current arsenal of algorithms for TV-based image restoration is vast. In the present paper, a different approach to the solution of the problem is proposed based on the method of iterative shrinkage (aka i...
Polymerization Shrinkage and Flexural Modulus of Flowable Dental Composites
Directory of Open Access Journals (Sweden)
Janaína Cavalcanti Xavier
2010-09-01
Full Text Available Linear polymerization shrinkage (LPS, flexural strength (FS and modulus of elasticity (ME of low-viscosity resin composites (Admira Flow™, Grandio Flow™/VOCO; Filtek Z350 Flow™/3M ESPE; Tetric Flow™/Ivoclar-Vivadent was evaluated using a well-established conventional micro-hybrid composite as a standard (Filtek Z250™/3M ESPE. For the measurement of LPS, composites were applied to a cylindrical metallic mould and polymerized (n = 8. The gap formed at the resin/mould interface was observed using SEM (1500×. For FS and ME, specimens were prepared according to the ISO 4049 specifications (n = 10. Statistical analysis of the data was performed with one-way ANOVA and the Tukey test. The conventional resin presented significantly lower LPS associated with high FS and ME, but only the ME values of the conventional resin differed significantly from the low-viscosity composites. The relationship between ME and LPS of low-viscosity resin composites when used as restorative material is a critical factor in contraction stress relief and marginal leakage.
INTER-GROUP IMAGE REGISTRATION BY HIERARCHICAL GRAPH SHRINKAGE.
Ying, Shihui; Wu, Guorong; Liao, Shu; Shen, Dinggang
2013-12-31
In this paper, we propose a novel inter-group image registration method to register different groups of images (e.g., young and elderly brains) simultaneously. Specifically, we use a hierarchical two-level graph to model the distribution of entire images on the manifold, with intra-graph representing the image distribution in each group and the inter-graph describing the relationship between two groups. Then the procedure of inter-group registration is formulated as a dynamic evolution of graph shrinkage. The advantage of our method is that the topology of entire image distribution is explored to guide the image registration. In this way, each image coordinates with its neighboring images on the manifold to deform towards the population center, by following the deformation pathway simultaneously optimized within the graph. Our proposed method has been also compared with other state-of-the-art inter-group registration methods, where our method achieves better registration results in terms of registration accuracy and robustness.
Laser-induced scleral shrinkage for refractive surgery
Ren, Qiushi; Simon, Gabriel; Parel, Jean-Marie A.; Shen, Jin-Hui
1994-06-01
We investigate the laser refractive scleroplasty (LRS) as a potential minimal-invasive method for correcting post-operative astigmatism. The scleral shrinkage near limbus was induced on 6 cadaver eyes using a 200 micrometers fiber optic probe coupled to a pulsed Ho:YAG laser. The diameter of the treatment spot was 0.8 mm. The output energy measured at tip was 60.2+/- 0.6 mJ. The treatments consisted of multiple sector patterns placed along the major axis of astigmatism parallel to the limbus, and round patterns placed along the limbus. Three treatment spots were applied on each side of the sector. The separation among sectors and limbus is 1 mm. Keratometry and topography of the cornea were measured after each sector or round pattern treatment. Effect of 5 and 10 pulses at each treatment spot were compared. Histology was performed to evaluate laser tissue damage. The major axis of astigmatism was shifted 90 degrees after the sector pattern treatment and amount of dioptric change increased when adding a new treatment or using more treatment pulses. However, the spherical equivalent of the eyes was essentially unchanged. The keratometry of the corneas remained the same after the round pattern treatment. Laser refractive scleroplasty may be applied for the correction of post-operative astigmatism.
CHANNEL SHRINKAGE AND ITS INSTABILITY IN THE LOWER YELLOW RIVER1
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
From the mid 1980s through the late 1990s, the channel of the lower Yellow River experienced serious shrinkage, which has decreased the flood conveyance of the channel and the sediment carrying capacity of the flow, raised the water levels of floods, and, thus, severely threatened the safety of flood control along the river. The completion of Xiaolangdi Dam in 1999 could help mitigate the channel shrinkage problem, but the situation has not changed yet. This paper analyses the characteristics, mechanisms, and conditions resulting in channel shrinkage, points out channel instabilities, and puts forward approaches of channel rehabilitation.
Current trends in Bayesian methodology with applications
Upadhyay, Satyanshu K; Dey, Dipak K; Loganathan, Appaia
2015-01-01
Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.Each chapter is self-contained and focuses on
Directory of Open Access Journals (Sweden)
Abel Palafox
2014-01-01
Full Text Available We address a prototype inverse scattering problem in the interface of applied mathematics, statistics, and scientific computing. We pose the acoustic inverse scattering problem in a Bayesian inference perspective and simulate from the posterior distribution using MCMC. The PDE forward map is implemented using high performance computing methods. We implement a standard Bayesian model selection method to estimate an effective number of Fourier coefficients that may be retrieved from noisy data within a standard formulation.
Irregular-Time Bayesian Networks
Ramati, Michael
2012-01-01
In many fields observations are performed irregularly along time, due to either measurement limitations or lack of a constant immanent rate. While discrete-time Markov models (as Dynamic Bayesian Networks) introduce either inefficient computation or an information loss to reasoning about such processes, continuous-time Markov models assume either a discrete state space (as Continuous-Time Bayesian Networks), or a flat continuous state space (as stochastic dif- ferential equations). To address these problems, we present a new modeling class called Irregular-Time Bayesian Networks (ITBNs), generalizing Dynamic Bayesian Networks, allowing substantially more compact representations, and increasing the expressivity of the temporal dynamics. In addition, a globally optimal solution is guaranteed when learning temporal systems, provided that they are fully observed at the same irregularly spaced time-points, and a semiparametric subclass of ITBNs is introduced to allow further adaptation to the irregular nature of t...
Bayesian Inference: with ecological applications
Link, William A.; Barker, Richard J.
2010-01-01
This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.
Bayesian Methods for Statistical Analysis
Puza, Borek
2015-01-01
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete c...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...
Tsujimoto, Akimasa; Barkmeier, Wayne W; Takamizawa, Toshiki; Latta, Mark A; Miyazaki, Masashi
2016-01-01
The mechanical properties, volumetric shrinkage and depth of cure of a short fiber-reinforced resin composite (SFRC) were investigated in this study and compared to both a bulk fill resin composite (BFRC) and conventional glass/ceramic-filled resin composite (CGRC). Fracture toughness, flexural properties, volumetric shrinkage and depth of cure of the SFRC, BFRC and CGRC were measured. SFRC had significantly higher fracture toughness than BFRCs and CGRCs. The flexural properties of SFRC were comparable with BFRCs and CGRCs. SFRC showed significantly lower volumetric shrinkage than the other tested resin composites. The depth of cure of the SFRC was similar to BFRCs and higher than CGRCs. The data from this laboratory investigation suggests that SFRC exhibits improvements in fracture toughness, volumetric shrinkage and depth of cure when compared with CGRC, but depth of cure of SFRC was similar to BFRC.
Experimental Research on the Autogenous Shrinkage of MK High Performance Concrete
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Calcine and mill kaolin were used under agreeable technological conditions to generate matakaolin (MK). The autogenous shrinkage performance of high performance concrete added with MK was researched. It is shown that MK has an effective inhibitory action to early autogenous shrinkage of cement concrete, and the inhibitory action increases with the increase of MK. The autogenous shrinkage values from 24 hours after placement to 56 days are all higher than those of the contrasted concrete, among which, the value of the concrete with 5% MK is the highest. But the total shrinkage values in 56 days are all less than those of the contrasted test pieces. The total contraction after 24 h of placement decreases as the increase of MK, moreover,it is greatly less than that of the contrasted ones.
Marginal adaptation of a low-shrinkage silorane-based composite: A SEM-analysis
DEFF Research Database (Denmark)
Schmidt, Malene; Bindslev, Preben Hørsted; Poulsen, Sven;
2012-01-01
shrinkage, has been marketed. Objective. To investigate whether reduced polymerization shrinkage improves the marginal adaptation of composite restorations. Material and methods. A total of 156 scanning electron microscopy (SEM) pictures (78 baseline, 78 follow-up) of the occlusal part of Class II......-casts of the restorations were used for SEM pictures at x 16 magnification. Pictures from baseline and follow-up (398 days, SD 29 days) were randomized and the examiner was blinded to the material and the age of the restoration. Stereologic measurements were used to calculate the length and the width of the marginal......Introduction. Shrinkage during polymerization of resin-based composite materials may lead to gap formation and hamper the marginal adaptaion of the restorations. To reduce the problem of polymerization shrinkage, a new composite material (Filtek™ Silorane, 3M-ESPE, Germany), with a reduced...
Shrinkage and Expansive Strain of Concrete with Fly Ash and Expansive Agent
Institute of Scientific and Technical Information of China (English)
GAO Peiwei; LU Xiaolin; TANG Mingshu
2009-01-01
The effects of fly ash and MgO-type expansive agent on the shrinkage and expan-sive strain of concrete with high magnesia cement were investigated. The results show that high volumes of fly ash may reduce the shrinkage strain of concrete and inhibit the expansive strain of concrete with MgO-type expansive agent, but can not eliminate the shrinkage of concrete. MgO-type expansive agent may produce expansive strain and compensate the shrinkage strain of concrete, re-lieve the cracking risk, but the hydration product of magnesia tends to get together in paste and pro-duce expansive cracking of concrete with high magnesia content according to SEM observation.
Directory of Open Access Journals (Sweden)
Vasková I.
2014-10-01
Full Text Available Ductile cast iron (GS has noticed great development in last decades and its boom has no analogue in history humankind. Ductile iron has broaden the use of castings from cast iron into areas, which where exclusively domains for steel castings. Mainly by castings, which weight is very high, is the propensity to shrinkage creation even higher. Shrinkage creation influences mainly material, construction of casting, gating system and mould. Therefore, the main realized experiment was to ascertain the influence of technological parameters of furane mixture on shrinkage creation in castings from ductile iron. Together was poured 12 testing items in 3 moulds forto determine and compare the impact of various technological parameters forms the propensity for shrinkage in the casting of LGG.
Directory of Open Access Journals (Sweden)
Jianjun Liu
2013-01-01
Full Text Available Most salt rock has interbed of mudstone in China. Owing to the enormous difference of mechanical properties between the mudstone interbed and salt rock, the stress-strain and creep behaviors of salt rock are significantly influenced by neighboring mudstone interbed. In order to identify the rules of wellbore shrinkage and casings equivalent stress in bedded salt rock stratum, three-dimensional finite difference models were established. The effects of thickness and elasticity modulus of mudstone interbed on the open wellbore shrinkage and equivalent stress of casing after cementing operation were studied, respectively. The results indicate that the shrinkage of open wellbore and equivalent stress of casings decreases with the increase of mudstone interbed thickness. The increasing of elasticity modulus will reduce the shrinkage of open wellbore and casing equivalent stress. Research results can provide the scientific basis for the design of mud density and casing strength.
Liu, Jianjun; Zhang, Linzhi; Zhao, Jinzhou
2013-01-01
Most salt rock has interbed of mudstone in China. Owing to the enormous difference of mechanical properties between the mudstone interbed and salt rock, the stress-strain and creep behaviors of salt rock are significantly influenced by neighboring mudstone interbed. In order to identify the rules of wellbore shrinkage and casings equivalent stress in bedded salt rock stratum, three-dimensional finite difference models were established. The effects of thickness and elasticity modulus of mudstone interbed on the open wellbore shrinkage and equivalent stress of casing after cementing operation were studied, respectively. The results indicate that the shrinkage of open wellbore and equivalent stress of casings decreases with the increase of mudstone interbed thickness. The increasing of elasticity modulus will reduce the shrinkage of open wellbore and casing equivalent stress. Research results can provide the scientific basis for the design of mud density and casing strength.
Strength and Drying Shrinkage of Alkali-Activated Slag Paste and Mortar
Directory of Open Access Journals (Sweden)
Mao-chieh Chi
2012-01-01
Full Text Available The aim of this study is to investigate the strengths and drying shrinkage of alkali-activated slag paste and mortar. Compressive strength, tensile strength, and drying shrinkage of alkali-activated slag paste and mortar were measured with various liquid/slag ratios, sand/slag ratios, curing ages, and curing temperatures. Experimental results show that the higher compressive strength and tensile strength have been observed in the higher curing temperature. At the age of 56 days, AAS mortars show higher compressive strength than Portland cement mortars and AAS mortars with liquid/slag ratio of 0.54 have the highest tensile strength in all AAS mortars. In addition, AAS pastes of the drying shrinkage are higher than AAS mortars. Meanwhile, higher drying shrinkage was observed in AAS mortars than that observed comparable Portland cement mortars.
Institute of Scientific and Technical Information of China (English)
谭罗荣; 孔令伟
2001-01-01
The swell-shrinking mineral of saturated and unsaturated expansive soil has important effect on engineering mechanical behavior. Based on the swelling-shrinkage change regularity of montmorillonite crystal in this paper, the actions between various interlayers of montmorillonite crystal are generally summarized as two kinds of action potentials-shrinkage potential and swelling potential. Moreover, through the experimental research and analysis, the expression formula for variations of the swelling potential and shrinkage potential with interlayer distance is presented, and the regularity of matric suction variations with interlayer distance is also obtained for unsaturated expansive soil. It may provide a new theoretical basis and research path for further research on the swelling-shrinkage mechanism of expansive soil and matric suction potential of unsaturated soil.
Measurement of composite shrinkage using a fibre optic Bragg grating sensor.
Milczewski, M S; Silva, J C C; Paterno, A S; Kuller, F; Kalinowski, H J
2007-01-01
Fibre Bragg grating is used to determine resin-based composite shrinkage. Two composite resins (Freedom from SDI and Z100 from 3M) were tested to determine the polymerization contraction behaviour. Each sample of resin was prepared with an embedded fibre Bragg grating. A LED activation unit with wavelength from 430 nm to 470 nm (Dabi Atlante) was used for resin polymerization. The wavelength position of the peak in the optical reflection spectra of the sensor was measured. The wavelength shift was related to the shrinkage deformation of the samples. Temperature and strain evolution during the curing phase of the material was monitored. The shrinkage in the longitudinal direction was 0.15 +/- 0.02% for resin Z100 (3M) and 0.06+/-0.01% for Freedom (SDI); two-thirds of shrinkage occurred after the first 50 s of illumination.
Teall, Oliver; Pilegis, Martins; Sweeney, John; Gough, Tim; Thompson, Glen; Jefferson, Anthony; Lark, Robert; Gardner, Diane
2017-04-01
The shrinkage force exerted by restrained shape memory polymers (SMPs) can potentially be used to close cracks in structural concrete. This paper describes the physical processing and experimental work undertaken to develop high shrinkage die-drawn polyethylene terephthalate (PET) SMP tendons for use within a crack closure system. The extrusion and die-drawing procedure used to manufacture a series of PET tendon samples is described. The results from a set of restrained shrinkage tests, undertaken at differing activation temperatures, are also presented along with the mechanical properties of the most promising samples. The stress developed within the tendons is found to be related to the activation temperature, the cross-sectional area and to the draw rate used during manufacture. Comparisons with commercially-available PET strip samples used in previous research are made, demonstrating an increase in restrained shrinkage stress by a factor of two for manufactured PET filament samples.
Tumor shrinkage by cyclopamine tartrate through inhibiting hedgehog signaling
Institute of Scientific and Technical Information of China (English)
Qipeng Fan; Arash Garrossian; Massoud Garrossian; Dale Gardner; Jingwu Xie; Dongsheng Gu; Miao He; Hailan Liu; Tao Sheng; Guorui Xie; Ching-xin Li; Xiaoli Zhang; Brandon Wainwright
2011-01-01
The link of hedgehog (Hh) signaling activation to human cancer and synthesis of a variety of Hh signaling inhibitors raise great expectation that inhibiting Hh signaling may be effective in human cancer treatment. Cyclopamine (Cyc), an alkaloid from the Veratrum plant, is a specific natural product inhibitor of the Hh pathway that acts by targeting smoothened (SMO) protein. However, its poor solubility, acid sensitivity, and weak potency relative to other Hh antagonists prevent the clinical development of Cyc as a therapeutic agent. Here, we report properties of cyclopamine tartrate salt (CycT) and its activities in Hh signaling-mediated cancer in vitro and in vivo. Unlike Cyc, CycT is water soluble (5-10 mg/mL). The median lethal dose (LD) of CycT was 62.5 mg/kg body weight compared to 43.5 mg/kg for Cyc, and the plasma half-life (T) of CycT was not significantly different from that of Cyc. We showed that CycT had a higher inhibitory activity for Hh signaling-dependent motor neuron differentiation than did Cyc (IC = 50nmol/L for CycT vs. 300 nmol/L for Cyc). We also tested the antitumor effectiveness of these Hh inhibitors using two mouse models of basal cell carcinomas (K14cre:Ptch1and K14cre:SmoM2). After topical application of CycT or Cyc daily for 21 days, we found that all CycT-treated mice had tumor shrinkage and decreased expression of Hh target genes. Taken together, we found that CycT is an effective inhibitor of Hh signaling-mediated carcinogenesis.
Influence of rare earths on shrinkage porosity in thin walled ductile cast iron
DEFF Research Database (Denmark)
Pedersen, Karl Martin; Tiedje, Niels Skat
2009-01-01
Ductile cast iron has been cast in test bars with thickness from 2 to 10 mm. The rare earth elements La and Ce have been added to some of the castings to evaluate their influence on microstructure and shrinkage tendency. Both La and Ce increased the graphite nodule count, especially for thickness...... the temperature T-1, which is controlled by the growth of off-eutectic austenite dendrites, increased the shrinkage tendency....
Study on a New Method of Reducing the Water Shrinkage of Rabbit Hair Knitted Fabrics
Institute of Scientific and Technical Information of China (English)
PAN Fu-kui; WANG Shan-yuan; LONG Min; YANG Guang-ming
2005-01-01
In order to reduce the water shrinkage of rabbit hair knitted fabrics, a new method is developed, which is blending rabbit hairs with a little bit of blaze. The sericin on the blaze which can swell and melt in hot and wet condition[1] can cohere the rabbit hairs through special processing. So the relative movement among fibers could be restricted. The testing results show that the water shrinkage of rabbit hair knitted fabrics can be greatly reduced after processed.
Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space
DEFF Research Database (Denmark)
Østby, Ivar; Øyehaug, Leiv; Einevoll, Gaute T;
2009-01-01
Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS) between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance and astr......Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS) between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance...
Pore Structure and Influence of Recycled Aggregate Concrete on Drying Shrinkage
Yuanchen Guo; Jueshi Qian; Xue Wang
2013-01-01
Pore structure plays an important role in the drying shrinkage of recycled aggregate concrete (RAC). High-precision mercury intrusion and water evaporation were utilized to study the pore structure of RAC, which has a different replacement rate of recycled concrete aggregate (RCA), and to analyze its influence on drying shrinkage. Finally, a fractal-dimension calculation model was established based on the principles of mercury intrusion and fractal-geometry theory. Calculations were performed...
Denoising of Mechanical Vibration Signals Using Quantum-Inspired Adaptive Wavelet Shrinkage
2014-01-01
The potential application of a quantum-inspired adaptive wavelet shrinkage (QAWS) technique to mechanical vibration signals with a focus on noise reduction is studied in this paper. This quantum-inspired shrinkage algorithm combines three elements: an adaptive non-Gaussian statistical model of dual-tree complex wavelet transform (DTCWT) coefficients proposed to improve practicability of prior information, the quantum superposition introduced to describe the interscale dependencies of DTCWT co...
Effect of the Key Mixture Parameters on Shrinkage of Reactive Powder Concrete
Shamsad Ahmad; Ahmed Zubair; Mohammed Maslehuddin
2014-01-01
Reactive powder concrete (RPC) mixtures are reported to have excellent mechanical and durability characteristics. However, such concrete mixtures having high amount of cementitious materials may have high early shrinkage causing cracking of concrete. In the present work, an attempt has been made to study the simultaneous effects of three key mixture parameters on shrinkage of the RPC mixtures. Considering three different levels of the three key mixture factors, a total of 27 mixtures of RPC w...
Polymerization Shrinkage of Dental Composites Registered by a Video-imaging Device. A pilot study
Afaag, Ali; Sandelin, Benjamin
2014-01-01
The use of composite materials for dental fillings has become more common due to demands for more esthetic filling materials and a national ban against using mercury-containing products, among others dental amalgam. However, one of the drawbacks with composites is their polymerization shrinkage. Filler particles are incorporated into composites among other things to minimize the shrinkage. The sizes of the filler particles have in recent years become smaller and most composites have nano-part...
A Hierarchical Bayesian Model for Crowd Emotions
Urizar, Oscar J.; Baig, Mirza S.; Barakova, Emilia I.; Regazzoni, Carlo S.; Marcenaro, Lucio; Rauterberg, Matthias
2016-01-01
Estimation of emotions is an essential aspect in developing intelligent systems intended for crowded environments. However, emotion estimation in crowds remains a challenging problem due to the complexity in which human emotions are manifested and the capability of a system to perceive them in such conditions. This paper proposes a hierarchical Bayesian model to learn in unsupervised manner the behavior of individuals and of the crowd as a single entity, and explore the relation between behavior and emotions to infer emotional states. Information about the motion patterns of individuals are described using a self-organizing map, and a hierarchical Bayesian network builds probabilistic models to identify behaviors and infer the emotional state of individuals and the crowd. This model is trained and tested using data produced from simulated scenarios that resemble real-life environments. The conducted experiments tested the efficiency of our method to learn, detect and associate behaviors with emotional states yielding accuracy levels of 74% for individuals and 81% for the crowd, similar in performance with existing methods for pedestrian behavior detection but with novel concepts regarding the analysis of crowds. PMID:27458366
A new method for chill and shrinkage control in ladle treated ductile iron
Institute of Scientific and Technical Information of China (English)
Torbj(o)rn Skaland
2006-01-01
The paper is undertaken with the objective of describing a new method for treating ductile cast iron in a ladle process, where the main objective is to minimize formation of eutectic carbides and shrinkage porosity during solidification. The suppression of carbide formation is associated with the nucleating properties of the nodularizer and inoculant alloys. By nucleating properties it is understood the number and potency of nuclei formed by an alloy addition. The nodularizer and inoculant additions also influence ductile iron solidification shrinkage. Some alloys may give good protection against shrinkage while others tend to promote more shrinkage.The use of vanous rare earth elements is found to have a pronounced impact on these conditions. It has been discovered that the use of pure lanthanum as the primary rare earth source in the magnesium ferrosilicon nodularizer surprisingly further improves the performance of the ductile iron ladle treatment method compared to similar methods using cerium or mishmetal bearing nodularizers. The nucleating properties are substantially improved and the risk for carbides (chill) and shrinkage formation in the sandwich or tundish ladle treated ductile iron is then minimized.The paper describes this new ladle treatment concept in detail, and gives examples from successful testing of the new nodularizing technology and how it simultaneously affects and minimizes critical ductile iron chill and shrinkage tendencies.
Energy Technology Data Exchange (ETDEWEB)
Togrul, Inci Turk; Ispir, Ayse [Firat University, Engineering Faculty, Department of Chemical Engineering, 23279 Elazig (Turkey)
2007-10-15
This article represents the results of the variation in density and shrinkage of apricots during its osmotic dehydration. Shrinkage was investigated by means of dimensionless volume, diameter and length. Various osmotic agents such as sucrose, glucose, fructose, maltodextrin and sorbitol were used. It was found that the shrinkage of apricots could be well correlated with the moisture content of the sample during osmotic dehydration. The relationship between dimensionless parameters and moisture content was investigated by using eight non-linear models for each osmotic agent. It was find that the following proposed model can be confidently use for explaining the effect of shrinkage during osmotic dehydration of apricots.V/V{sub 0},D/D{sub 0},L/L{sub 0},{rho}/{rho}{sub 0}=a+b. exp (cX)+d. exp (e.X{sup f})In addition, the osmotic dehydration kinetics of apricots with and without shrinkage was studied. The effective diffusivities calculated from the diffusional model with and without shrinkage varied from 10.342 x 10{sup -9} m{sup 2}/s to 5.139 x 10{sup -9} and from 1.755 x 10{sup -10} and 0.767 x 10{sup -10} m{sup 2}/s, respectively. (author)
Transient brain shrinkage in infantile spasms after ACTH treatment. Report of two cases.
Maekawa, K; Ohta, H; Tamai, I
1980-02-01
This is the report of two cases of infantile spasms, manifesting transient brain shrinkage in computerized tomography (CT) after ACTH treatment. ACTH was given for 8 weeks to a 8-months-old Japanese girl with infantile spasms. First CT performed at 2 weeks after the final ACTH injection, displayed moderate brain shrinkage. Second CT at 4 months showed marked diminution of the shrinkage. ACTH was also given for 8 weeks to a 14 months old Japanese boy with infantile spasms. First CT, just before ACTH treatment, showed mild cortical atrophy, the second at 7 days after the final ACTH injection revealed marked brain shrinkage and moderate ventricular dilatation, and the third at 2 months, disclosed mild improvement of the shrinkage. ACTH or corticoateroid has widespread effects on the developing nervous system. In animal experiments, ACTH or steroids interfere with brain growth of young rats. CT findings of transient brain shrinkage in a child with infantile spasms might suggest that intensive treatment with ACTH or steroids in infancy interferes with brain growth as seen in the results of animal experiments.
Institute of Scientific and Technical Information of China (English)
MA Bao-guo; WEN Xiao-dong; WANG Ming-yuan; YAN Jia-jia; Gao Xiao-jian
2007-01-01
Currently,deformations along the central axis of specimens were usually measured under fixed environmental conditions. Seldom were the effects of environmental factors on the drying-shrinkage deformation of cement-based material considered. For this paper, the drying-shrinkage deformation at different w/b ratios and different additions to mortars was investigated under different environments at a temperature of 20 ℃ and humidity ranging from 100% to 50%. The specimens were cured in water for 28 days before measurement. The results illustrate that mortar shows much less shrinkage under various drying conditions when a lower w/b ratio is adopted. With a decrease in relative humidity the speed of drying-shrinkage becomes gradually lower. The addition of silica fume reduces the drying-shrinkage of mortar under higher relative humidity, because the pore structure of mortar with silica fume becomes more refined. The addition of fly ash increases the total porosity and the volume of coarse pores in the mortar. The drying-shrinkage of mortar under different conditions increases with the addition of more of fly ash.
Sampaio, C S; Chiu, K-J; Farrokhmanesh, E; Janal, M; Puppin-Rontani, R M; Giannini, M; Bonfante, E A; Coelho, P G; Hirata, R
The present study aimed to characterize the pattern and volume of polymerization shrinkage of flowable resin composites, including one conventional, two bulk fill, and one self-adhesive. Standardized class I preparations (2.5 mm depth × 4 mm length × 4 mm wide) were performed in 24 caries-free human third molars that were randomly divided in four groups, according to the resin composite and adhesive system used: group 1 = Permaflo + Peak Universal Bond (PP); group 2 = Filtek Bulk Fill + Scotchbond Universal (FS); group 3 = Surefil SDR + XP Bond (SX); and group 4 = Vertise flow self-adhering (VE) (n=6). Each tooth was scanned three times using a microcomputed tomography (μCT) apparatus. The first scan was done after the cavity preparation, the second after cavity filling with the flowable resin composite before curing, and the third after it was cured. The μCT images were imported into three-dimensional rendering software, and volumetric polymerization shrinkage percentage was calculated for each sample. Data were submitted to one-way analysis of variance and post hoc comparisons. No significant difference was observed among PP, FS, and VE. SX bulk fill resin composite presented the lowest values of volumetric shrinkage. Shrinkage was mostly observed along the occlusal surface and part of the pulpal floor. In conclusion, polymerization shrinkage outcomes in a 2.5-mm deep class I cavity were material dependent, although most materials did not differ. The location of shrinkage was mainly at the occlusal surface.
The effect of mucosal cuff shrinkage around dental implants during healing abutment replacement.
Nissan, J; Zenziper, E; Rosner, O; Kolerman, R; Chaushu, L; Chaushu, G
2015-10-01
Soft tissue shrinkage during the course of restoring dental implants may result in biological and prosthodontic difficulties. This study was conducted to measure the continuous shrinkage of the mucosal cuff around dental implants following the removal of the healing abutment up to 60 s. Individuals treated with implant-supported fixed partial dentures were included. Implant data--location, type, length, diameter and healing abutments' dimensions--were recorded. Mucosal cuff shrinkage, following removal of the healing abutments, was measured in bucco-lingual direction at four time points--immediately after 20, 40 and 60 s. anova was used to for statistical analysis. Eighty-seven patients (49 women and 38 men) with a total of 311 implants were evaluated (120 maxilla; 191 mandible; 291 posterior segments; 20 anterior segments). Two-hundred and five (66%) implants displayed thick and 106 (34%) thin gingival biotype. Time was the sole statistically significant parameter affecting mucosal cuff shrinkage around dental implants (P < 0.001). From time 0 to 20, 40 and 60 s, the mean diameter changed from 4.1 to 4.07, 3.4 and 2.81 mm, respectively. The shrinkage was 1%, 17% and 31%, respectively. The gingival biotype had no statistically significant influence on mucosal cuff shrinkage (P = 0.672). Time required replacing a healing abutment with a prosthetic element should be minimised (up to 20/40 s), to avoid pain, discomfort and misfit.
Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations
Energy Technology Data Exchange (ETDEWEB)
Chen, Peng, E-mail: peng@ices.utexas.edu [The Institute for Computational Engineering and Sciences, The University of Texas at Austin, 201 East 24th Street, Stop C0200, Austin, TX 78712-1229 (United States); Schwab, Christoph, E-mail: christoph.schwab@sam.math.ethz.ch [Seminar für Angewandte Mathematik, Eidgenössische Technische Hochschule, Römistrasse 101, CH-8092 Zürich (Switzerland)
2016-07-01
We extend the reduced basis (RB) accelerated Bayesian inversion methods for affine-parametric, linear operator equations which are considered in [16,17] to non-affine, nonlinear parametric operator equations. We generalize the analysis of sparsity of parametric forward solution maps in [20] and of Bayesian inversion in [48,49] to the fully discrete setting, including Petrov–Galerkin high-fidelity (“HiFi”) discretization of the forward maps. We develop adaptive, stochastic collocation based reduction methods for the efficient computation of reduced bases on the parametric solution manifold. The nonaffinity and nonlinearity with respect to (w.r.t.) the distributed, uncertain parameters and the unknown solution is collocated; specifically, by the so-called Empirical Interpolation Method (EIM). For the corresponding Bayesian inversion problems, computational efficiency is enhanced in two ways: first, expectations w.r.t. the posterior are computed by adaptive quadratures with dimension-independent convergence rates proposed in [49]; the present work generalizes [49] to account for the impact of the PG discretization in the forward maps on the convergence rates of the Quantities of Interest (QoI for short). Second, we propose to perform the Bayesian estimation only w.r.t. a parsimonious, RB approximation of the posterior density. Based on the approximation results in [49], the infinite-dimensional parametric, deterministic forward map and operator admit N-term RB and EIM approximations which converge at rates which depend only on the sparsity of the parametric forward map. In several numerical experiments, the proposed algorithms exhibit dimension-independent convergence rates which equal, at least, the currently known rate estimates for N-term approximation. We propose to accelerate Bayesian estimation by first offline construction of reduced basis surrogates of the Bayesian posterior density. The parsimonious surrogates can then be employed for online data
Dynamic Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2011-01-01
Bayesian optimization (BO) algorithms try to optimize an unknown function that is expensive to evaluate using minimum number of evaluations/experiments. Most of the proposed algorithms in BO are sequential, where only one experiment is selected at each iteration. This method can be time inefficient when each experiment takes a long time and more than one experiment can be ran concurrently. On the other hand, requesting a fix-sized batch of experiments at each iteration causes performance inefficiency in BO compared to the sequential policies. In this paper, we present an algorithm that asks a batch of experiments at each time step t where the batch size p_t is dynamically determined in each step. Our algorithm is based on the observation that the sequence of experiments selected by the sequential policy can sometimes be almost independent from each other. Our algorithm identifies such scenarios and request those experiments at the same time without degrading the performance. We evaluate our proposed method us...
Bayesian seismic AVO inversion
Energy Technology Data Exchange (ETDEWEB)
Buland, Arild
2002-07-01
A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P-wave velocity, S-wave velocity and density. Distributions for other elastic parameters can also be assessed, for example acoustic impedance, shear impedance and P-wave to S-wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance, hence exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3-D dataset from the Sleipner Field. The results show good agreement with well logs but the uncertainty is high. The stochastic model includes uncertainties of both the elastic parameters, the wavelet and the seismic and well log data. The posterior distribution is explored by Markov chain Monte Carlo simulation using the Gibbs sampler algorithm. The inversion algorithm has been tested on a seismic line from the Heidrun Field with two wells located on the line. The uncertainty of the estimated wavelet is low. In the Heidrun examples the effect of including uncertainty of the wavelet and the noise level was marginal with respect to the AVO inversion results. We have developed a 3-D linearized AVO inversion method with spatially coupled model parameters where the objective is to obtain posterior distributions for P-wave velocity, S
Bayesian microsaccade detection
Mihali, Andra; van Opheusden, Bas; Ma, Wei Ji
2017-01-01
Microsaccades are high-velocity fixational eye movements, with special roles in perception and cognition. The default microsaccade detection method is to determine when the smoothed eye velocity exceeds a threshold. We have developed a new method, Bayesian microsaccade detection (BMD), which performs inference based on a simple statistical model of eye positions. In this model, a hidden state variable changes between drift and microsaccade states at random times. The eye position is a biased random walk with different velocity distributions for each state. BMD generates samples from the posterior probability distribution over the eye state time series given the eye position time series. Applied to simulated data, BMD recovers the “true” microsaccades with fewer errors than alternative algorithms, especially at high noise. Applied to EyeLink eye tracker data, BMD detects almost all the microsaccades detected by the default method, but also apparent microsaccades embedded in high noise—although these can also be interpreted as false positives. Next we apply the algorithms to data collected with a Dual Purkinje Image eye tracker, whose higher precision justifies defining the inferred microsaccades as ground truth. When we add artificial measurement noise, the inferences of all algorithms degrade; however, at noise levels comparable to EyeLink data, BMD recovers the “true” microsaccades with 54% fewer errors than the default algorithm. Though unsuitable for online detection, BMD has other advantages: It returns probabilities rather than binary judgments, and it can be straightforwardly adapted as the generative model is refined. We make our algorithm available as a software package. PMID:28114483
Maximum margin Bayesian network classifiers.
Pernkopf, Franz; Wohlmayr, Michael; Tschiatschek, Sebastian
2012-03-01
We present a maximum margin parameter learning algorithm for Bayesian network classifiers using a conjugate gradient (CG) method for optimization. In contrast to previous approaches, we maintain the normalization constraints on the parameters of the Bayesian network during optimization, i.e., the probabilistic interpretation of the model is not lost. This enables us to handle missing features in discriminatively optimized Bayesian networks. In experiments, we compare the classification performance of maximum margin parameter learning to conditional likelihood and maximum likelihood learning approaches. Discriminative parameter learning significantly outperforms generative maximum likelihood estimation for naive Bayes and tree augmented naive Bayes structures on all considered data sets. Furthermore, maximizing the margin dominates the conditional likelihood approach in terms of classification performance in most cases. We provide results for a recently proposed maximum margin optimization approach based on convex relaxation. While the classification results are highly similar, our CG-based optimization is computationally up to orders of magnitude faster. Margin-optimized Bayesian network classifiers achieve classification performance comparable to support vector machines (SVMs) using fewer parameters. Moreover, we show that unanticipated missing feature values during classification can be easily processed by discriminatively optimized Bayesian network classifiers, a case where discriminative classifiers usually require mechanisms to complete unknown feature values in the data first.
Masson, Jean-Baptiste; Salvatico, Charlotte; Renner, Marianne; Specht, Christian G; Triller, Antoine; Dahan, Maxime
2015-01-01
Protein mobility is conventionally analyzed in terms of an effective diffusion. Yet, this description often fails to properly distinguish and evaluate the physical parameters (such as the membrane friction) and the biochemical interactions governing the motion. Here, we present a method combining high-density single-molecule imaging and statistical inference to separately map the diffusion and energy landscapes of membrane proteins across the cell surface at ~100 nm resolution (with acquisition of a few minutes). When applying these analytical tools to glycine neurotransmitter receptors (GlyRs) at inhibitory synapses, we find that gephyrin scaffolds act as shallow energy traps (~3 kBT) for GlyRs, with a depth modulated by the biochemical properties of the receptor-gephyrin interaction loop. In turn, the inferred maps can be used to simulate the dynamics of proteins in the membrane, from the level of individual receptors to that of the population, and thereby, to model the stochastic fluctuations of physiologi...
Bayesian modeling using WinBUGS
Ntzoufras, Ioannis
2009-01-01
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic, offering readers a smooth introduction to the principles of Bayesian modeling with detailed guidance on the practical implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key topics, including: Markov Chain Monte Carlo algorithms in Bayesian inference Generalized linear models Bayesian hierarchical models Predictive distribution and model checking Bayesian model and variable evaluation Computational notes and screen captures illustrate the use of both WinBUGS as well as R software to apply the discussed techniques. Exercises at the end of each chapter allow readers to test their understanding of the presented concepts and all ...
Bayesian Methods and Universal Darwinism
Campbell, John
2010-01-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a 'copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that system...
Attention in a bayesian framework
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
The behavioral phenomena of sensory attention are thought to reflect the allocation of a limited processing resource, but there is little consensus on the nature of the resource or why it should be limited. Here we argue that a fundamental bottleneck emerges naturally within Bayesian models...... of perception, and use this observation to frame a new computational account of the need for, and action of, attention - unifying diverse attentional phenomena in a way that goes beyond previous inferential, probabilistic and Bayesian models. Attentional effects are most evident in cluttered environments......, and include both selective phenomena, where attention is invoked by cues that point to particular stimuli, and integrative phenomena, where attention is invoked dynamically by endogenous processing. However, most previous Bayesian accounts of attention have focused on describing relatively simple experimental...
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Bayesian Missile System Reliability from Point Estimates
2014-10-28
OCT 2014 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Bayesian Missile System Reliability from Point Estimates 5a. CONTRACT...Principle (MEP) to convert point estimates to probability distributions to be used as priors for Bayesian reliability analysis of missile data, and...illustrate this approach by applying the priors to a Bayesian reliability model of a missile system. 15. SUBJECT TERMS priors, Bayesian , missile
Perception, illusions and Bayesian inference.
Nour, Matthew M; Nour, Joseph M
2015-01-01
Descriptive psychopathology makes a distinction between veridical perception and illusory perception. In both cases a perception is tied to a sensory stimulus, but in illusions the perception is of a false object. This article re-examines this distinction in light of new work in theoretical and computational neurobiology, which views all perception as a form of Bayesian statistical inference that combines sensory signals with prior expectations. Bayesian perceptual inference can solve the 'inverse optics' problem of veridical perception and provides a biologically plausible account of a number of illusory phenomena, suggesting that veridical and illusory perceptions are generated by precisely the same inferential mechanisms.
Bayesian test and Kuhn's paradigm
Institute of Scientific and Technical Information of China (English)
Chen Xiaoping
2006-01-01
Kuhn's theory of paradigm reveals a pattern of scientific progress,in which normal science alternates with scientific revolution.But Kuhn underrated too much the function of scientific test in his pattern,because he focuses all his attention on the hypothetico-deductive schema instead of Bayesian schema.This paper employs Bayesian schema to re-examine Kuhn's theory of paradigm,to uncover its logical and rational components,and to illustrate the tensional structure of logic and belief,rationality and irrationality,in the process of scientific revolution.
3D Bayesian contextual classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
2000-01-01
We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....
Effects of Manufactured-sand on Dry Shrinkage and Creep of High-strength Concrete
Institute of Scientific and Technical Information of China (English)
ZHOU Mingkai; WANG Jiliang; ZHU Lide; HE Tusheng
2008-01-01
The influences of natural sand, manufactured-sand (MS) and stone-dust (SD) in the manufactured-sand on workability, compressive strength, elastic modulus, drying shrinkage and creep properties of high-strength concrete (HSC) were tested and compared. The results show that the reasonable content (7%-10.5%) of SD in MS will not deteriorate the workability of MS-HSC. It could even improve the workability. Moreover, the compressive strength increases gradually with the increasing SD content,and the MS-HSC with low SD content (smaller than 7%) has the elastic modulus which approaches that of the natural sand HSC, but the elastic modulus reduces when the SD content is high. The influence of the SD content on drying shrinkage performance of MS-HSC is closely related to the hydration age. The shrinkage rate of MS-HSC in the former 7 d age is higher than that of the natural sand HSC, but the difference of the shrinkage rate in the late age is not marked. Meanwhile the shrinkage rate reduces as the fly ash is added; the specific creep and creep coefficient of MS-HSC with 7% SD are close to those of the natural sand HSC.
Gholamhoseini, Alireza
2016-03-01
Relatively little research has been reported on the time-dependent in-service behavior of composite concrete slabs with profiled steel decking as permanent formwork and little guidance is available for calculating long-term deflections. The drying shrinkage profile through the thickness of a composite slab is greatly affected by the impermeable steel deck at the slab soffit, and this has only recently been quantified. This paper presents the results of long-term laboratory tests on composite slabs subjected to both drying shrinkage and sustained loads. Based on laboratory measurements, a design model for the shrinkage strain profile through the thickness of a slab is proposed. The design model is based on some modifications to an existing creep and shrinkage prediction model B3. In addition, an analytical model is developed to calculate the time-dependent deflection of composite slabs taking into account the time-dependent effects of creep and shrinkage. The calculated deflections are shown to be in good agreement with the experimental measurements.
Shrinkage modeling of concrete reinforced by palm fibres in hot dry environments
Akchiche, Hamida; Kriker, Abdelouahed
2017-02-01
The cement materials, such as concrete and conventional mortar present very little resistance to traction and cracking, these hydraulic materials which induces large withdrawals on materials and cracks in structures. The hot dry environments such as: the Saharan regions of Algeria, Indeed, concrete structures in these regions are very fragile, and present high shrinkage. Strengthening of these materials by fibers can provide technical solutions for improving the mechanical performance. The aim of this study is firstly, to reduce the shrinkage of conventional concrete with its reinforcement with date palm fibers. In fact, Algeria has an extraordinary resources in natural fibers (from Palm, Abaca, Hemp) but without valorization in practical areas, especially in building materials. Secondly, to model the shrinkage behavior of concrete was reinforced by date palm fibers. In the literature, several models for still fiber concrete were founded but few are offers for natural fiber concretes. To do so, a still fiber concretes model of YOUNG - CHERN was used. According to the results, a reduction of shrinkage with reinforcement by date palm fibers was showed. A good ability of molding of shrinkage of date palm reinforced concrete with YOUNG - CHERN Modified model was obtained. In fact, a good correlation between experimental data and the model data was recorded.
Directory of Open Access Journals (Sweden)
Amin Noushini
2014-01-01
Full Text Available The current study assesses the drying shrinkage behaviour of polyvinyl alcohol fibre reinforced concrete (PVA-FRC containing short-length (6 mm and long-length (12 mm uncoated monofilament PVA fibres at 0.125%, 0.25%, 0.375%, and 0.5% volumetric fractions. Fly ash is also used as a partial replacement of Portland cement in all mixes. PVA-FRC mixes have been compared to length change of control concrete (devoid of fibres at 3 storage intervals: early-age (0–7 days, short-term (0–28 days, and long-term (28–112 days intervals. The shrinkage results of FRC and control concrete up to 112 days indicated that all PVA-FRC mixes exhibited higher drying shrinkage than control. The shrinkage exhibited by PVA-FRC mixes ranged from 449 to 480 microstrain, where this value was only 427 microstrain in the case of control. In addition, the longer fibres exhibited higher mass loss, thus potentially contributing to higher shrinkage.
Pore Structure and Influence of Recycled Aggregate Concrete on Drying Shrinkage
Directory of Open Access Journals (Sweden)
Yuanchen Guo
2013-01-01
Full Text Available Pore structure plays an important role in the drying shrinkage of recycled aggregate concrete (RAC. High-precision mercury intrusion and water evaporation were utilized to study the pore structure of RAC, which has a different replacement rate of recycled concrete aggregate (RCA, and to analyze its influence on drying shrinkage. Finally, a fractal-dimension calculation model was established based on the principles of mercury intrusion and fractal-geometry theory. Calculations were performed to study the pore-structure fractal dimension of RAC. Results show the following. (1 With the increase in RCA content, the drying shrinkage values increase gradually. (2 Pores with the greatest impact on concrete shrinkage are those whose sizes ranging from 2.5 nm to 50 nm and from 50 nm to 100 nm. In the above two ranges, the proportions of RAC are greater than those of RC0 (natural aggregate concrete, NAC, which is the main reason the shrinkage values of RAC are greater than those of NAC. (3 The pore structure of RAC has good fractal feature, and the addition of RCA increases the complexity of the pore surface of concrete.
A Pore-Centric Model for Combined Shrinkage and Gas Porosity in Alloy Solidification
Khalajzadeh, Vahid; Carlson, Kent D.; Backman, Daniel G.; Beckermann, Christoph
2017-04-01
A unified model has been developed for combined gas- and shrinkage-induced pore formation during solidification of metal alloys. The model is based on a pore-centric approach, in which the temporal evolution of the pore radius is calculated as a function of cooling rate, thermal gradient, gas diffusion, and shrinkage. It accounts for the effect of porosity formation on the liquid velocity within the mushy zone. Simulations for an aluminum alloy show that the porosity transitions smoothly from shrinkage-induced to gas-induced as the Niyama value is increased. A Blake (cavitation) instability is observed to occur when the porosity is both gas- and shrinkage-driven. A revised dimensionless Niyama curve for pure shrinkage is presented. The experimentally observed gas porosity trend that the pore volume decreases with increasing cooling rate is well predicted. The pore-centric formulation allows the present model to be solved locally, at any point in a casting, during a regular casting simulation.
The effects of dimensional mould sizes on volumetric shrinkage strain of lateritic soil
Directory of Open Access Journals (Sweden)
John Engbonye SANI
2016-07-01
Full Text Available Dimensional influences of specimen size on the volumetric shrinkage strain values of a lateritic soil for waste containment system have not been researched upon. Therefore, this paper presents the result of a laboratory study on the volumetric shrinkage strain (VSS of lateritic soil at three different dimensional sizes of mould (split former mould, proctor mould and California bearing ratio mould at three energy levels; British standard light (BSL, West African standard (WAS and British standard heavy (BSH respectively. Compactions were done at different molding water content of -2% to +6% optimum moisture content (OMC. At -2% to +2% molding water content for the split former mould the volumetric shrinkage strain met the requirement of not more than 4% while at +4% and +6% only the WAS and BSH met the requirement. The proctor mould and the CBR mould on the other hand gave a lower value of volumetric shrinkage strain in all compactive effort and the values are lower than the 4% safe VSS suggested by Tay et al., (2001. Based on the VSS values obtained if the CBR mould can be used to model site condition it is recommended for use to simulate site condition for Volumetric shrinkage strain for all molding water content and compactive effort.
Perceptual shrinkage of a one-way motion path with high-speed motion.
Nakajima, Yutaka; Sakaguchi, Yutaka
2016-07-28
Back-and-forth motion induces perceptual shrinkage of the motion path, but such shrinkage is hardly perceived for one-way motion. If the shrinkage is caused by temporal averaging of stimulus position around the endpoints, it should also be induced for one-way motion at higher motion speeds. In psychophysical experiments with a high-speed projector, we tested this conjecture for a one-way motion stimulus at various speeds (4-100 deg/s) along a straight path. Results showed that perceptual shrinkage of the motion path was robustly observed in higher-speed motion (faster than 66.7 deg/s). In addition, the amount of the forwards shift at the onset position was larger than that of the backwards shift at the offset position. These results demonstrate that high-speed motion can induce shrinkage, even for a one-way motion path. This can be explained by the view that perceptual position is represented by the integration of the temporal average of instantaneous position and the motion representation.
Shrinkage and growth compensation in common sunflowers: refining estimates of damage
Sedgwick, James A.; Oldemeye, John L.; Swenson, Elizabeth L.
1986-01-01
Shrinkage and growth compensation of artificially damaged common sunflowers (Helianthus annuus) were studied in central North Dakota during 1981-1982 in an effort to increase accuracy of estimates of blackbird damage to sunflowers. In both years, as plants matured damaged areas on seedheads shrank at a greater rate than the sunflower heads themselves. This differential shrinkage resulted in an underestimation of the area damaged. Sunflower head and damaged-area shrinkage varied widely by time and degree of damage and by size of the seedhead damaged. Because variation in shrinkage by time of damage was so large, predicting when blackbird damage occurs may be the most important factor in estimating seed loss. Yield'occupied seed area was greater (P < 0.05) for damaged than undamaged heads and tended to increase as degree of damage inflicted increased, indicating growth compensation was occurring in response to lost seeds. Yields of undamaged seeds in seedheads damaged during early seed development were higher than those of heads damaged later. This suggested that there was a period of maximal response to damage when plants were best able to redirect growth to seeds remaining in the head. Sunflowers appear to be able to compensate for damage of ≤ 15% of the total hear area. Estimates of damage can be improved by applying empirical results of differential shrinkage and growth compensations.
Directory of Open Access Journals (Sweden)
Alain Pefferkorn
2012-01-01
Full Text Available The adsorption of polymethylmethacrylate polymer of different molecular weight at the aerosil/ethyleneglycol- or 1,3 butanediol-dimethacrylate interfaces was determined to provide microstructured networks. Their structural characteristics were determined to be controlled by the amount of polymer initially supplied to the system. The sediment (the settled phase characteristics, determined as a function of the polymer concentration and the rate of the polymerization shrinkage determined for composite resins, obtained by extrusion of the sediment after centrifugation, were found to be correlated. The specific role of the adsorbed polymer was found to be differently perturbed with the supplementary supply of dimethacrylate based monomer additives. Particularly, the bisphenol A dimethacrylate that generated crystals within the sediment was found to impede the shrinkage along the crystal lateral faces and strongly limit the shrinkage along its basal faces. Addition of ethyleneglycol- or polyethylene-glycoldimethacrylate monomers was determined to modify the sedimentation characteristics of the aerosil suspension and the shrinkage properties of the composites. Finally, the effects of stepwise light curing methods with prolonged lighting-off periods were investigated and found to modify the development and the final values of the composite shrinkage.
Maia, Rodrigo R.; Reis, Rodrigo S.; Moro, André F.V.; Perez, Cesar R.; Bárbara M. Pessôa; Dias, Katia R.H.C.
2015-01-01
Purpose. This study tested the null hypothesis that different classes of direct restorative dental materials: silorane-based resin, low-shrinkage and conventional (non-flowable and flowable) resin-based composite (RBC) do not differ from each other with regard to polymerization shrinkage, depth of cure or microhardness. Methods. 140 RBC samples were fabricated and tested by one calibrated operator. Polymerization shrinkage was measured using a gas pycnometer both before and immediately after ...
Crack development through plastic shrinkage in fresh concretes and mortars
Directory of Open Access Journals (Sweden)
Aguanell García, M.
1989-09-01
Full Text Available The rate of water evaporation in the exposed surfaces plays an important part in the development of cracks in fresh concretes and mortars before hardening is completed. This rate of evaporation depends on the drying power of the wind sweeping such surfaces as a function of the relative humidity, temperature and speed of the air.
After many studies and research work on the subject of plastic cracking, the following axiom has been established: "Plastic shrinkage and cracking of concrete surfaces take place when water evaporates from the surface quicker than it can be replaced through exudation".
Once the value of weather parameters are known, the extent of the risk of crack development can be known and preventive steps taken to overcome such risk. Obviously, such steps are all oriented to reducing or stopping evaporation and go from covering surfaces with wet sackcloth or plastic foil, through sprinkling water mists or lowering the concrete temperature, to using film-forming curing products.
Another additional measure can be the addition of polypropelene fibers to the concrete while in the mixer, at the rate of 0.9 kg fiber to 1 m^{3} of concrete.
En la formación de grietas en morteros y hormigones frescos, antes de finalizar el fraguado, tiene una primordial importancia la velocidad de evaporación del agua de las superficies expuestas al exterior, velocidad que depende del poder desecante de los vientos que barren estas superficies y que está en función de la humedad relativa del aire, de su temperatura y de su velocidad.
Después de los múltiples estudios e investigaciones sobre este tema de la formación de las grietas plásticas, se ha llegado a establecer el siguiente axioma: "La retracción plástica y las grietas se producen, en las superficies del hormigón, cuando el agua se evapora de ellas más rápidamente que la que puede ser reemplazada por exudación."
Conociendo el valor de los parámetros meteorol
A Bayesian Nonparametric Approach to Test Equating
Karabatsos, George; Walker, Stephen G.
2009-01-01
A Bayesian nonparametric model is introduced for score equating. It is applicable to all major equating designs, and has advantages over previous equating models. Unlike the previous models, the Bayesian model accounts for positive dependence between distributions of scores from two tests. The Bayesian model and the previous equating models are…
Bayesian Model Averaging for Propensity Score Analysis
Kaplan, David; Chen, Jianshen
2013-01-01
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
Bayesian networks and food security - An introduction
Stein, A.
2004-01-01
This paper gives an introduction to Bayesian networks. Networks are defined and put into a Bayesian context. Directed acyclical graphs play a crucial role here. Two simple examples from food security are addressed. Possible uses of Bayesian networks for implementation and further use in decision sup
Plug & Play object oriented Bayesian networks
DEFF Research Database (Denmark)
Bangsø, Olav; Flores, J.; Jensen, Finn Verner
2003-01-01
Object oriented Bayesian networks have proven themselves useful in recent years. The idea of applying an object oriented approach to Bayesian networks has extended their scope to larger domains that can be divided into autonomous but interrelated entities. Object oriented Bayesian networks have b...
A biological mechanism for Bayesian feature selection: Weight decay and raising the LASSO.
Connor, Patrick; Hollensen, Paul; Krigolson, Olav; Trappenberg, Thomas
2015-07-01
Biological systems are capable of learning that certain stimuli are valuable while ignoring the many that are not, and thus perform feature selection. In machine learning, one effective feature selection approach is the least absolute shrinkage and selection operator (LASSO) form of regularization, which is equivalent to assuming a Laplacian prior distribution on the parameters. We review how such Bayesian priors can be implemented in gradient descent as a form of weight decay, which is a biologically plausible mechanism for Bayesian feature selection. In particular, we describe a new prior that offsets or "raises" the Laplacian prior distribution. We evaluate this alongside the Gaussian and Cauchy priors in gradient descent using a generic regression task where there are few relevant and many irrelevant features. We find that raising the Laplacian leads to less prediction error because it is a better model of the underlying distribution. We also consider two biologically relevant online learning tasks, one synthetic and one modeled after the perceptual expertise task of Krigolson et al. (2009). Here, raising the Laplacian prior avoids the fast erosion of relevant parameters over the period following training because it only allows small weights to decay. This better matches the limited loss of association seen between days in the human data of the perceptual expertise task. Raising the Laplacian prior thus results in a biologically plausible form of Bayesian feature selection that is effective in biologically relevant contexts.
Bayesian geostatistical modeling of leishmaniasis incidence in Brazil.
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Dimitrios-Alexios Karagiannis-Voules
Full Text Available BACKGROUND: Leishmaniasis is endemic in 98 countries with an estimated 350 million people at risk and approximately 2 million cases annually. Brazil is one of the most severely affected countries. METHODOLOGY: We applied Bayesian geostatistical negative binomial models to analyze reported incidence data of cutaneous and visceral leishmaniasis in Brazil covering a 10-year period (2001-2010. Particular emphasis was placed on spatial and temporal patterns. The models were fitted using integrated nested Laplace approximations to perform fast approximate Bayesian inference. Bayesian variable selection was employed to determine the most important climatic, environmental, and socioeconomic predictors of cutaneous and visceral leishmaniasis. PRINCIPAL FINDINGS: For both types of leishmaniasis, precipitation and socioeconomic proxies were identified as important risk factors. The predicted number of cases in 2010 were 30,189 (standard deviation [SD]: 7,676 for cutaneous leishmaniasis and 4,889 (SD: 288 for visceral leishmaniasis. Our risk maps predicted the highest numbers of infected people in the states of Minas Gerais and Pará for visceral and cutaneous leishmaniasis, respectively. CONCLUSIONS/SIGNIFICANCE: Our spatially explicit, high-resolution incidence maps identified priority areas where leishmaniasis control efforts should be targeted with the ultimate goal to reduce disease incidence.
Pitel, Mark L
2013-09-01
Despite numerous advances in composite resin technology over the course of many decades, shrinkage behavior and the resultant stresses inherent to direct placed composite restorations continue to challenge clinicians. This overview of composite resins includes a review of their history and development along with a discussion of strategies for reducing polymerization shrinkage. An assessment of the clinical significance of these materials is also provided, including a discussion of the differences between polymerization shrinkage and stress, incremental layering versus bulk placement, and the emergence of lower shrinkage stress monomer chemistry.
Tani, Y; Nambu, T; Ishikawa, A; Katsuyama, S
1993-12-01
This study quantified the contraction force and polymerization shrinkage of composite resins with/without beta-Quartz Glass Ceramic Inserts (BQCI) as "Megafiller". The materials used for the determination included a chemically cured composite and five light-cured composites. The system for measuring contraction force consisted of a transparent teflon tube for preparing the specimen, a small load cell, a dynamic strain gauge and a pen-recorder. After the composite was packed into the teflon mold, a BQCI (Type R3) was inserted through the opening and the specimen was cured. Linear polymerization shrinkage of the composites was measured every 10 seconds from the start of mixing or irradiation to 90 minutes by the mercury bath method. Three pieces each of BQCI (Type T3) were inserted in each specimen. The results suggested that BQCI was markedly effective in reducing polymerization shrinkage, but was not always effective in reducing the contraction force during polymerization.
Ottevaere, H.; Tabak, M.; Chah, K.; Mégret, P.; Thienpont, H.
2012-04-01
Polymerization shrinkage of dental composite materials is recognized as one of the main reasons for the development of marginal leakage between a tooth and filling material. As an alternative to conventional measurement methods, we propose optical fiber Bragg grating (FBG) based sensors to perform real-time strain and shrinkage measurements during the curing process of dental resin cements. We introduce a fully automated set-up to measure the Bragg wavelength shift of the FBG strain sensors and to accurately monitor the linear strain and shrinkage of dental resins during curing. Three different dental resin materials were studied in this work: matrix-filled BisGMA-based resins, glass ionomers and organic modified ceramics.
Fast approach to infrared image restoration based on shrinkage functions calibration
Zhang, Chengshuo; Shi, Zelin; Xu, Baoshu; Feng, Bin
2016-05-01
High-quality image restoration in real time is a challenge for infrared imaging systems. We present a fast approach to infrared image restoration based on shrinkage functions calibration. Rather than directly modeling the prior of sharp images to obtain the shrinkage functions, we calibrate them for restoration directly by using the acquirable sharp and blurred image pairs from the same infrared imaging system. The calibration method is employed to minimize the sum of squared errors between sharp images and restored images from the blurred images. Our restoration algorithm is noniterative and its shrinkage functions are stored in the look-up tables, so an architecture solution of pipeline structure can work in real time. We demonstrate the effectiveness of our approach by testing its quantitative performance from simulation experiments and its qualitative performance from a developed wavefront coding infrared imaging system.
A cure shrinkage model for analyzing the stresses and strains in encapsulated assemblies
Chambers, R. S.; Lagasse, R. R.; Guess, T. R.; Plazek, D. J.; Bero, C.
Electrical component assemblies are encapsulated to provide delicate parts with voltage isolation and protection against damage caused by shock, vibration, and harsh atmospheric environments. During cure, thermosetting resins shrink and harden simultaneously. If the natural deformation of the resin is constrained by adhesion to the mold or to relatively stiff embedded components, cure shrinkage stresses are generated in the encapsulant. Subsequent cooling or thermal cycling produces additional stresses that are caused by the mismatches in thermal strains among the materials in the encapsulated assembly. Although cure shrinkage stresses frequently are neglected because they are considerably smaller than thermal stresses, cure shrinkage stresses can cause delamination or fractures in the encapsulant, since the partially cured resin is not as tough as the fully cured material. Cracks generated during cure can compromise performance (e.g., permit dielectric breakdown), degrade a component's protection, and grow under subsequent thermal cycling producing residual stresses that differ from those found in uncracked assemblies.
A cure shrinkage model for analyzing the stresses and strains in encapsulated assemblies
Energy Technology Data Exchange (ETDEWEB)
Chambers, R.S.; Lagasse, R.R.; Guess, T.R. [Sandia National Labs., Albuquerque, NM (United States); Plazek, D.J.; Bero, C. [Pittsburgh Univ., PA (United States). Dept. of Materials Science and Engineering
1992-12-31
Electrical component assemblies are encapsulated to provide delicate parts with voltage isolation and protection against damage caused by shock, vibration, and harsh atmospheric environments. During cure, thermosetting resins shrink and harden simultaneously. If the natural deformation of the resin is constrained by adhesion to the mold or to relatively stiff embedded components, cure shrinkage stresses are generated in the encapsulant. Subsequent cooling or thermal cycling produces additional stresses that are caused by the mismatches in thermal strains among the materials in the encapsulated assembly. Although cure shrinkage stresses frequently are neglected because they are considerably smaller than thermal stresses, cure shrinkage stresses can cause delamination or fractures in the encapsulant, since the partially cured resin is not as tough as the fully cured material. Cracks generated during cure can compromise performance (e. g., permit dielectric breakdown), degrade a component`s protection, and grow under subsequent thermal cycling producing residual stresses that differ from those found in uncracked assemblies. 3 refs., 11 figs.
Hormone replacement therapy and age-related brain shrinkage: regional effects.
Raz, Naftali; Rodrigue, Karen M; Kennedy, Kristen M; Acker, James D
2004-11-15
Neuroprotective properties of estrogen have been established in animal models, but clinical trials of hormone replacement therapy (HRT) produced contradictory results. We examined the impact of HRT on age-related regional changes in human brain volume. Six brain regions were measured twice, five years apart, in 12 healthy women who took HRT and in matched controls who did not. The controls showed a typical pattern of differential brain shrinkage in the association cortices and the hippocampus with no change in the primary visual cortex. In contrast, women who took HRT showed comparable shrinkage of the hippocampus but no significant shrinkage of the neocortex. Future large scale studies may benefit from applying regional rather than global measures in assessment of brain integrity.
Adaptive contourlet-wavelet iterative shrinkage/thresholding for remote sensing image restoration
Institute of Scientific and Technical Information of China (English)
Nu WEN; Shi-zhi YANG; Cheng-jie ZHU; Sheng-cheng CUI
2014-01-01
In this paper, we present an adaptive two-step contourlet-wavelet iterative shrinkage/thresholding (TcwIST) algorithm for remote sensing image restoration. This algorithm can be used to deal with various linear inverse problems (LIPs), including image deconvolution and reconstruction. This algorithm is a new version of the famous two-step iterative shrinkage/thresholding (TwIST) algorithm. First, we use the split Bregman Rudin-Osher-Fatemi (ROF) model, based on a sparse dictionary, to decom-pose the image into cartoon and texture parts, which are represented by wavelet and contourlet, respectively. Second, we use an adaptive method to estimate the regularization parameter and the shrinkage threshold. Finally, we use a linear search method to find a step length and a fast method to accelerate convergence. Results show that our method can achieve a signal-to-noise ratio improvement (ISNR) for image restoration and high convergence speed.
Cell shrinkage as a signal to apoptosis in NIH 3T3 fibroblasts
DEFF Research Database (Denmark)
Friis, Martin B; Friborg, Christel R; Schneider, Linda;
2005-01-01
Cell shrinkage is a hallmark of the apoptotic mode of programmed cell death, but it is as yet unclear whether a reduction in cell volume is a primary activation signal of apoptosis. Here we studied the effect of an acute elevation of osmolarity (NaCl or sucrose additions, final osmolarity 687...... mosmol l(-1)) on NIH 3T3 fibroblasts to identify components involved in the signal transduction from shrinkage to apoptosis. After 1.5 h the activity of caspase-3 started to increase followed after 3 h by the appearance of many apoptotic-like bodies. The caspase-3 activity increase was greatly enhanced...... in cells expressing a constitutively active G protein, Rac (RacV12A3 cell), indicating that Rac acts upstream to caspase-3 activation. The stress-activated protein kinase, p38, was significantly activated by phosphorylation within 30 min after induction of osmotic shrinkage, the phosphorylation being...
Physical modeling of the soil swelling curve vs. the shrinkage curve
Chertkov, V Y
2014-01-01
Physical understanding of the links between soil swelling, texture, structure, cracking, and sample size is of great interest for the physical understanding of many processes in the soil-air-water system and for applications in civil, agricultural, and environmental engineering. The background of this work is an available chain of interconnected physical shrinkage curve models for clay, intra-aggregate matrix, aggregated soil without cracks, and soil with cracks. The objective of the work is to generalize these models to the case of swelling, and to construct the physical-swelling-model chain with a step-by-step transition from clay to aggregated soil with cracks. The generalization is based on thorough accounting for the analogies and differences between shrinkage and swelling and the corresponding use, modification, or replacement of the soil shrinkage features. Two specific soil swelling features to be used are: (i) air entrapping in pores of the contributing clay; and (ii) aggregate destruction with the f...
Thermal assisted ion shrinkage (TAIS) of fluorinated polyimide for optical telecommunication devices
Trigaud, T.; Moliton, J. P.; Quillat, M.; Chiron, D.
1999-06-01
In the framework of the development of low cost optical devices for telecommunications, here is studied the shrinkage of 6FDA-ODA polyimide films by ion irradiation as a function of five parameters: the ion fluence, the ion fluence rate, the ion energy, the ion nature and the target temperature. In the 30-350 keV energy range for impinging ions, the shrinkage remains constant whatever the tested fluence rate is. An upper limit appears for fluences above 10 16 ions cm -2. The etching is linearly dependent on the ion beam energy and reaches a maximum around 1 μm by thermal assisted ion shrinkage (TAIS) with Na + irradiations.
Hormone-dependent shrinkage of a sphenoid wing meningioma after pregnancy: case report.
Kerschbaumer, Johannes; Freyschlag, Christian F; Stockhammer, Günter; Taucher, Susanne; Maier, Hans; Thomé, Claudius; Seiz-Rosenhagen, Marcel
2016-01-01
Meningiomas are known to be associated with female sex hormones. Worsening neurological symptoms or newly diagnosed meningiomas have been described in the context of elevated levels of sex hormones, for example, in pregnancy. To the authors' knowledge, tumor shrinkage after the normalization of hormones has not been described, even if it is known that neurological deficits due to meningioma compression may improve after giving birth. A 32-year-old female patient presented with severe headache and vision disturbances at the end of her second pregnancy. Magnetic resonance imaging revealed an extended mass at the lateral left-sided sphenoid wing that was suspected to be a meningioma. After delivery, the patient's symptoms improved, and MRI obtained 2 months postpartum showed significant shrinkage of the lesion. Significant tumor shrinkage can occur after pregnancy. Thus, repeat imaging is indicated in these patients.
Institute of Scientific and Technical Information of China (English)
李茂柏; 王慧; 张建明; 李丁鲁; 杨润清; 周宇琼; 朴钟泽
2009-01-01
Main QTL and epistasis interaction effects for phytic acid concentration in rice grain were investigated by using a F_2 population consisted of 172 lines derived from the cross between an indica rice LPA(the grain phytic acid concentration was 7.11 mg/g) and a japonica rice Zhonghua 11(the phytic acid concentration was 11.92 mg/g) with the Bayesian model selection. A genetic linkage map including 126 SSR and 4 STS markers was constructed with the F_2 population. Three main QTLs related to phytic acid concentration in rice grain were detected. They were located on chromosomes 3, 5, and 6, explaining 5.38%, 8.02%, and 4.62% of phenotypic variation, respectively. The three alleles for reducing the phytic aid concentration were from the parent LPA. Ten pairs of epistatic interaction were detected on chromosomes 1, 3, 5, 6, and 11, with the interaction effects from 1.69 to 5.18 and the percentages of phenotypic variance ranged from 8.67% to 24.73%.%利用水稻植酸含量差异较大的品种中花11(粳型)和LPA(籼型)为亲本杂交获得F_2群体的172个单株,构建了含126个SSR和4个STS标记的遗传连锁图谱,利用贝叶斯(Bayesian)法对水稻籽粒植酸含量性状进行了主效应QTL定位和上位性互作分析.共检测到 3 个与水稻籽粒植酸含量性状有关的主效QTL,分布在第3、5和6 染色体的相应区间内,表型贡献率分别为5.38%、8.02%和4.62%,降低籽粒植酸含量的等位基因均来自亲本LPA.检测到10对上位性互作影响籽粒植酸含量, 分布于水稻第1、3、5、6、11染色体上,互作效应值为1.69～5.18,其表型变异的解释率为8.67%～24.73%.
Bayesian stable isotope mixing models
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixtur...
Naive Bayesian for Email Filtering
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The paper presents a method of email filter based on Naive Bayesian theory that can effectively filter junk mail and illegal mail. Furthermore, the keys of implementation are discussed in detail. The filtering model is obtained from training set of email. The filtering can be done without the users specification of filtering rules.
Bayesian analysis of binary sequences
Torney, David C.
2005-03-01
This manuscript details Bayesian methodology for "learning by example", with binary n-sequences encoding the objects under consideration. Priors prove influential; conformable priors are described. Laplace approximation of Bayes integrals yields posterior likelihoods for all n-sequences. This involves the optimization of a definite function over a convex domain--efficiently effectuated by the sequential application of the quadratic program.
Bayesian NL interpretation and learning
Zeevat, H.
2011-01-01
Everyday natural language communication is normally successful, even though contemporary computational linguistics has shown that NL is characterised by very high degree of ambiguity and the results of stochastic methods are not good enough to explain the high success rate. Bayesian natural language
ANALYSIS OF BAYESIAN CLASSIFIER ACCURACY
Directory of Open Access Journals (Sweden)
Felipe Schneider Costa
2013-01-01
Full Text Available The naÃ¯ve Bayes classifier is considered one of the most effective classification algorithms today, competing with more modern and sophisticated classifiers. Despite being based on unrealistic (naÃ¯ve assumption that all variables are independent, given the output class, the classifier provides proper results. However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables, the network may not provide appropriate results. This study uses a process variable selection, using the chi-squared test to verify the existence of dependence between variables in the data model in order to identify the reasons which prevent a Bayesian network to provide good performance. A detailed analysis of the data is also proposed, unlike other existing work, as well as adjustments in case of limit values between two adjacent classes. Furthermore, variable weights are used in the calculation of a posteriori probabilities, calculated with mutual information function. Tests were applied in both a naÃ¯ve Bayesian network and a hierarchical Bayesian network. After testing, a significant reduction in error rate has been observed. The naÃ¯ve Bayesian network presented a drop in error rates from twenty five percent to five percent, considering the initial results of the classification process. In the hierarchical network, there was not only a drop in fifteen percent error rate, but also the final result came to zero.
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...
Bayesian Classification of Image Structures
DEFF Research Database (Denmark)
Goswami, Dibyendu; Kalkan, Sinan; Krüger, Norbert
2009-01-01
In this paper, we describe work on Bayesian classi ers for distinguishing between homogeneous structures, textures, edges and junctions. We build semi-local classiers from hand-labeled images to distinguish between these four different kinds of structures based on the concept of intrinsic dimensi...
3-D contextual Bayesian classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
In this paper we will consider extensions of a series of Bayesian 2-D contextual classification pocedures proposed by Owen (1984) Hjort & Mohn (1984) and Welch & Salter (1971) and Haslett (1985) to 3 spatial dimensions. It is evident that compared to classical pixelwise classification further...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis Linda
2006-01-01
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...
Bayesian Evidence and Model Selection
Knuth, Kevin H; Malakar, Nabin K; Mubeen, Asim M; Placek, Ben
2014-01-01
In this paper we review the concept of the Bayesian evidence and its application to model selection. The theory is presented along with a discussion of analytic, approximate and numerical techniques. Application to several practical examples within the context of signal processing are discussed.
Differentiated Bayesian Conjoint Choice Designs
Z. Sándor (Zsolt); M. Wedel (Michel)
2003-01-01
textabstractPrevious conjoint choice design construction procedures have produced a single design that is administered to all subjects. This paper proposes to construct a limited set of different designs. The designs are constructed in a Bayesian fashion, taking into account prior uncertainty about
Directory of Open Access Journals (Sweden)
Ricardo José Ferreira
2010-01-01
desired goals have been reached, suggest the adoption of more sophisticated formulae, such as Bayesian networks (BN rather than BSC. In the case of BN, the challenge becomes a proper quantification of its parameters, allowing reliable estimates from them. The objective of this work is to evaluate the performance of BN in handling a given real PHR problem by means of the comparison between its predictions and the respective observed results. The model has been developed from a BSC and subsequently quantified according to expert opinions, since no relevant empirical data was available. The BN was designed to support the deployment of strategies for scientific development and opening of markets for a given university course. The analyses carried out indicate the good performance of the model, emphasizing the adopted elicitation method in such a process.
Persson, N; Ghisletta, P; Dahle, C L; Bender, A R; Yang, Y; Yuan, P; Daugherty, A M; Raz, N
2014-12-01
We examined regional changes in brain volume in healthy adults (N=167, age 19-79years at baseline; N=90 at follow-up) over approximately two years. With latent change score models, we evaluated mean change and individual differences in rates of change in 10 anatomically-defined and manually-traced regions of interest (ROIs): lateral prefrontal cortex (LPFC), orbital frontal cortex (OF), prefrontal white matter (PFw), hippocampus (Hc), parahippocampal gyrus (PhG), caudate nucleus (Cd), putamen (Pt), insula (In), cerebellar hemispheres (CbH), and primary visual cortex (VC). Significant mean shrinkage was observed in the Hc, CbH, In, OF, and PhG, and individual differences in change were noted in all regions, except the OF. Pro-inflammatory genetic variants modified shrinkage in PhG and CbH. Carriers of two T alleles of interleukin-1β (IL-1β C-511T, rs16944) and a T allele of methylenetetrahydrofolate reductase (MTHFR C677T, rs1801133) polymorphisms showed increased PhG shrinkage. No effects of a pro-inflammatory polymorphism for C-reactive protein (CRP-286C>A>T, rs3091244) or apolipoprotein (APOE) ε4 allele were noted. These results replicate the pattern of brain shrinkage observed in previous studies, with a notable exception of the LPFC, thus casting doubt on the unique importance of prefrontal cortex in aging. Larger baseline volumes of CbH and In were associated with increased shrinkage, in conflict with the brain reserve hypothesis. Contrary to previous reports, we observed no significant linear effects of age and hypertension on regional brain shrinkage. Our findings warrant further investigation of the effects of neuroinflammation on structural brain change throughout the lifespan.
Bayesian Alternation During Tactile Augmentation
Directory of Open Access Journals (Sweden)
Caspar Mathias Goeke
2016-10-01
Full Text Available A large number of studies suggest that the integration of multisensory signals by humans is well described by Bayesian principles. However, there are very few reports about cue combination between a native and an augmented sense. In particular, we asked the question whether adult participants are able to integrate an augmented sensory cue with existing native sensory information. Hence for the purpose of this study we build a tactile augmentation device. Consequently, we compared different hypotheses of how untrained adult participants combine information from a native and an augmented sense. In a two-interval forced choice (2 IFC task, while subjects were blindfolded and seated on a rotating platform, our sensory augmentation device translated information on whole body yaw rotation to tactile stimulation. Three conditions were realized: tactile stimulation only (augmented condition, rotation only (native condition, and both augmented and native information (bimodal condition. Participants had to choose one out of two consecutive rotations with higher angular rotation. For the analysis, we fitted the participants’ responses with a probit model and calculated the just notable difference (JND. Then we compared several models for predicting bimodal from unimodal responses. An objective Bayesian alternation model yielded a better prediction (χred2 = 1.67 than the Bayesian integration model (χred2= 4.34. Slightly higher accuracy showed a non-Bayesian winner takes all model (χred2= 1.64, which either used only native or only augmented values per subject for prediction. However the performance of the Bayesian alternation model could be substantially improved (χred2= 1.09 utilizing subjective weights obtained by a questionnaire. As a result, the subjective Bayesian alternation model predicted bimodal performance most accurately among all tested models. These results suggest that information from augmented and existing sensory modalities in
Spatial Bayesian hierarchical modelling of extreme sea states
Clancy, Colm; O'Sullivan, John; Sweeney, Conor; Dias, Frédéric; Parnell, Andrew C.
2016-11-01
A Bayesian hierarchical framework is used to model extreme sea states, incorporating a latent spatial process to more effectively capture the spatial variation of the extremes. The model is applied to a 34-year hindcast of significant wave height off the west coast of Ireland. The generalised Pareto distribution is fitted to declustered peaks over a threshold given by the 99.8th percentile of the data. Return levels of significant wave height are computed and compared against those from a model based on the commonly-used maximum likelihood inference method. The Bayesian spatial model produces smoother maps of return levels. Furthermore, this approach greatly reduces the uncertainty in the estimates, thus providing information on extremes which is more useful for practical applications.
[A medical image semantic modeling based on hierarchical Bayesian networks].
Lin, Chunyi; Ma, Lihong; Yin, Junxun; Chen, Jianyu
2009-04-01
A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in allusion to characters of medical images. It used GMM (Gaussian mixture models) to map low-level image features into object semantics with probabilities, then it captured high-level semantics through fusing these object semantics using a Bayesian network, so that it built a multi-layer medical image semantic model, aiming to enable automatic image annotation and semantic retrieval by using various keywords at different semantic levels. As for the validity of this method, we have built a multi-level semantic model from a small set of astrocytoma MRI (magnetic resonance imaging) samples, in order to extract semantics of astrocytoma in malignant degree. Experiment results show that this is a superior approach.
Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method
Desmal, Abdulla
2014-07-01
A contrast-source inversion scheme is proposed for microwave imaging of domains with sparse content. The scheme uses inexact Newton and linear shrinkage methods to account for the nonlinearity and ill-posedness of the electromagnetic inverse scattering problem, respectively. Thresholded shrinkage iterations are accelerated using a preconditioning technique. Additionally, during Newton iterations, the weight of the penalty term is reduced consistently with the quadratic convergence of the Newton method to increase accuracy and efficiency. Numerical results demonstrate the applicability of the proposed method.
Method and application of wavelet shrinkage denoising based on genetic algorithm
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Genetic algorithm (GA) based on wavelet transform threshold shrinkage (WTS) and translation-invafiant threshold shrinkage (TIS) is introduced into the method of noise reduction, where parameters used in WTS and TIS, such as wavelet function,decomposition levels, hard or soft threshold and threshold can be selected automatically. This paper ends by comparing two noise reduction methods on the basis of their denoising performances, computation time, etc. The effectiveness of these methods introduced in this paper is validated by the results of analysis of the simulated and real signals.
Alcohol consumption and frontal lobe shrinkage: study of 1432 non-alcoholic subjects
Kubota, M.; Nakazaki, S.; Hirai, S.; Saeki, N; YAMAURA, A.; Kusaka, T
2001-01-01
OBJECTIVES—To evaluate the influences of chronic alcohol consumption on brain volume among social drinkers, as it is well known that alcohol misusers have a high risk of brain shrinkage. METHODS—Frontal lobe volumes on MRI were compared with the current alcohol habits of consecutive 1432 non-alcoholic subjects. RESULTS—After adjusting for other variables, age was found to be the most powerful promoting factor for the shrinkage with a odds ratio of 2.8 (95% confidence i...
DEFF Research Database (Denmark)
Yoon, G. H.; Kim, Y. Y.; Bendsøe, Martin P.;
2004-01-01
In topology optimization applications for the design of compliant mechanisms, the formation of hinges is typically encountered. Often such hinges are unphysical artifacts that appear due to the choice of discretization spaces for design and analysis. The objective of this work is to present a new...... in the multiscale design space. To imbed the shrinkage method implicitly in the optimization formulation and thus facilitate sensitivity analysis, the shrinkage method is made differentiable by means of differentiable versions of logical operators. The validity of the present method is confirmed by solving typical...... two-dimensional compliant mechanism design problems....
Bayesian analysis of rare events
Energy Technology Data Exchange (ETDEWEB)
Straub, Daniel, E-mail: straub@tum.de; Papaioannou, Iason; Betz, Wolfgang
2016-06-01
In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.
STATISTICAL BAYESIAN ANALYSIS OF EXPERIMENTAL DATA.
Directory of Open Access Journals (Sweden)
AHLAM LABDAOUI
2012-12-01
Full Text Available The Bayesian researcher should know the basic ideas underlying Bayesian methodology and the computational tools used in modern Bayesian econometrics. Some of the most important methods of posterior simulation are Monte Carlo integration, importance sampling, Gibbs sampling and the Metropolis- Hastings algorithm. The Bayesian should also be able to put the theory and computational tools together in the context of substantive empirical problems. We focus primarily on recent developments in Bayesian computation. Then we focus on particular models. Inevitably, we combine theory and computation in the context of particular models. Although we have tried to be reasonably complete in terms of covering the basic ideas of Bayesian theory and the computational tools most commonly used by the Bayesian, there is no way we can cover all the classes of models used in econometrics. We propose to the user of analysis of variance and linear regression model.
Bayesian methods for measures of agreement
Broemeling, Lyle D
2009-01-01
Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies. It focuses on agreement among the various players in the diagnostic process.The author employs a Bayesian approach to provide statistical inferences based on various models of intra- and interrater agreement. He presents many examples that illustrate the Bayesian mode of reasoning and explains elements of a Bayesian application, including prior information, experimental information, the likelihood function, posterior distribution, and predictive distribution. The appendices provide the necessary theoretical foundation to understand Bayesian methods as well as introduce the fundamentals of programming and executing the WinBUGS software.Taking a Bayesian approach to inference, this hands-on book explores numerous measures of agreement, including the Kappa coefficient, the G coefficient, and intraclass correlation...
SOMBI: Bayesian identification of parameter relations in unstructured cosmological data
Frank, Philipp; Jasche, Jens; Enßlin, Torsten A.
2016-11-01
This work describes the implementation and application of a correlation determination method based on self organizing maps and Bayesian inference (SOMBI). SOMBI aims to automatically identify relations between different observed parameters in unstructured cosmological or astrophysical surveys by automatically identifying data clusters in high-dimensional datasets via the self organizing map neural network algorithm. Parameter relations are then revealed by means of a Bayesian inference within respective identified data clusters. Specifically such relations are assumed to be parametrized as a polynomial of unknown order. The Bayesian approach results in a posterior probability distribution function for respective polynomial coefficients. To decide which polynomial order suffices to describe correlation structures in data, we include a method for model selection, the Bayesian information criterion, to the analysis. The performance of the SOMBI algorithm is tested with mock data. As illustration we also provide applications of our method to cosmological data. In particular, we present results of a correlation analysis between galaxy and active galactic nucleus (AGN) properties provided by the SDSS catalog with the cosmic large-scale-structure (LSS). The results indicate that the combined galaxy and LSS dataset indeed is clustered into several sub-samples of data with different average properties (for example different stellar masses or web-type classifications). The majority of data clusters appear to have a similar correlation structure between galaxy properties and the LSS. In particular we revealed a positive and linear dependency between the stellar mass, the absolute magnitude and the color of a galaxy with the corresponding cosmic density field. A remaining subset of data shows inverted correlations, which might be an artifact of non-linear redshift distortions.
Directory of Open Access Journals (Sweden)
Rodrigo R. Maia
2015-06-01
Full Text Available Purpose. This study tested the null hypothesis that different classes of direct restorative dental materials: silorane-based resin, low-shrinkage and conventional (non-flowable and flowable resin-based composite (RBC do not differ from each other with regard to polymerization shrinkage, depth of cure or microhardness.Methods. 140 RBC samples were fabricated and tested by one calibrated operator. Polymerization shrinkage was measured using a gas pycnometer both before and immediately after curing with 36 J/cm2 light energy density. Depth of cure was determined, using a penetrometer and the Knoop microhardness was tested from the top surface to a depth of 5 mm.Results. Considering polymerization shrinkage, the authors found significant differences (p < 0.05 between different materials: non-flowable RBCs showed lower values compared to flowable RBCs, with the silorane-based resin presenting the smallest shrinkage. The low shrinkage flowable composite performed similarly to non-flowable with significant statistical differences compared to the two other flowable RBCs. Regarding to depth of cure, low-shrinkage flowable RBC, were most effective compared to other groups. Microhardness was generally higher for the non-flowable vs. flowable RBCs (p < 0.05. However, the values for low-shrinkage flowable did not differ significantly from those of non-flowable, but were significantly higher than those of the other flowable RBCs.Clinical Significance. RBCs have undergone many modifications as they have evolved and represent the most relevant restorative materials in today’s dental practice. This study of low-shrinkage RBCs, conventional RBCs (non-flowable and flowable and silorane-based composite—by in vitro evaluation of volumetric shrinkage, depth of cure and microhardness—reveals that although filler content is an important determinant of polymerization shrinkage, it is not the only variable that affects properties of materials that were tested in
Comparison of Bayesian Land Surface Temperature algorithm performance with Terra MODIS observations
Morgan, J A
2009-01-01
An approach to land surface temperature (LST) estimation that relies upon Bayesian inference has been validated against multiband infrared radiometric imagery from the Terra MODIS instrument. Bayesian LST estimators are shown to reproduce standard MODIS product LST values starting from a parsimoniously chosen (hence, uninformative) range of prior band emissivity knowledge. Two estimation methods have been tested. The first is the iterative contraction mapping of joint expectation values for LST and surface emissivity described in a previous paper. In the second method, the Bayesian algorithm is reformulated as a Maximum \\emph{A-Posteriori} (MAP) search for the maximum joint \\emph{a-posteriori} probability for LST, given observed sensor aperture radiances and \\emph{a-priori} probabilities for LST and emissivity. Two MODIS data granules each for daytime and nighttime were used for the comparison. The granules were chosen to be largely cloud-free, with limited vertical relief in those portions of the granules fo...
Institute of Scientific and Technical Information of China (English)
Jian-ying LI; Andrew LAU; Alex S.L.FOK
2013-01-01
Objectives:Polymerization shrinkage of dental composites remains a major concern in restorative dentistry because it can lead to micro-cracking of the tooth and debonding at the tooth-restoration interface.The aim of this study was to measure the full-field polymerization shrinkage of dental composites using the optical digital image correlation (DIC) method and to evaluate how the measurement is influenced by the factors in experiment setup and image analysis.Methods:Four commercial dental composites,Premise Dentine,Z100,Z250 and Tetric EvoCeram,were tested.Composite was first placed into a slot mould to form a bar specimen with rectangular-section of 4 mm×2 mm,followed by the surface painting to create irregular speckles.Curing was then applied at one end of the specimen while the other part were covered against curing light for simulating the clinical curing condition of composite in dental cavity.The painted surface was recorded by a charge-coupled device (CCD) camera before and after curing.Subsequently,the volumetric shrinkage of the specimen was calculated with specialist DIC software based on image cross correlation.In addition,a few factors that may influence the measuring accuracy,including the subset window size,speckle size,illumination light and specimen length,were also evaluated.Results:The volumetric shrinkage of the specimen generally decreases with increasing distance from the irradiated surface with a conspicuous exception being the composite Premise Dentine as its maximum shrinkage occurred at a subsurface distance of about 1 mm instead of the irradiated surface.Zl00 had the greatest maximum shrinkage strain,followed by Z250,Tetric EvoCeram and then Premise Dentine.Larger subset window size made the shrinkage strain contour smoother.But the cost was that some details in the heterogeneity of the material were lost.Very small subset window size resulted in a lot of noise in the data,making it difficult to discern the general pattern in the strain
Bayesian versus 'plain-vanilla Bayesian' multitarget statistics
Mahler, Ronald P. S.
2004-08-01
Finite-set statistics (FISST) is a direct generalization of single-sensor, single-target Bayes statistics to the multisensor-multitarget realm, based on random set theory. Various aspects of FISST are being investigated by several research teams around the world. In recent years, however, a few partisans have claimed that a "plain-vanilla Bayesian approach" suffices as down-to-earth, "straightforward," and general "first principles" for multitarget problems. Therefore, FISST is mere mathematical "obfuscation." In this and a companion paper I demonstrate the speciousness of these claims. In this paper I summarize general Bayes statistics, what is required to use it in multisensor-multitarget problems, and why FISST is necessary to make it practical. Then I demonstrate that the "plain-vanilla Bayesian approach" is so heedlessly formulated that it is erroneous, not even Bayesian denigrates FISST concepts while unwittingly assuming them, and has resulted in a succession of algorithms afflicted by inherent -- but less than candidly acknowledged -- computational "logjams."
Bayesian inference on the sphere beyond statistical isotropy
Das, Santanu; Souradeep, Tarun
2015-01-01
We present a general method for Bayesian inference of the underlying covariance structure of random fields on a sphere. We employ the Bipolar Spherical Harmonic (BipoSH) representation of general covariance structure on the sphere. We illustrate the efficacy of the method as a principled approach to assess violation of statistical isotropy (SI) in the sky maps of Cosmic Microwave Background (CMB) fluctuations. SI violation in observed CMB maps arise due to known physical effects such as Doppler boost and weak lensing; yet unknown theoretical possibilities like cosmic topology and subtle violations of the cosmological principle, as well as, expected observational artefacts of scanning the sky with a non-circular beam, masking, foreground residuals, anisotropic noise, etc. We explicitly demonstrate the recovery of the input SI violation signals with their full statistics in simulated CMB maps. Our formalism easily adapts to exploring parametric physical models with non-SI covariance, as we illustrate for the in...
Institute of Scientific and Technical Information of China (English)
David González-Ballester
2016-01-01
Aim: One of the most important factors associated with recurrence rate and overall survival is the status of surgical margin of resection free of disease. However, sometimes, the margins measured intra-operatively at the time of surgery differ of those measured by the pathologist in the histopathologic analysis. Faced with this dilemma, a literature review of the best available evidence was conducted in an attempt to determine how the phenomenon of tissue shrinkage may influence on the surgical margin of resection in patients undergoing oral and oropharyngeal squamous cell carcinoma (SCC).Methods: An electronic and manual search was conducted by one reviewer. A combination of controlled Medical Subjects Headings and keywords were used as search strategy. Inclusion and exclusion criteria were established.Results: Finally, after an exhaustive selection process, four articles fulfilled the inclusion criteria and were analyzed. All articles reported a decrease of surgical margin after resection. The tumor site and tumor stage seem to influence in degree of margin shrinkage.Conclusion:Tissue shrinkage on surgical margins of resection in oral SCC is a tangible phenomenon. There is a significant discrepancy between margins measured intraoperatively previous to resection and margins measured by pathologist after histologic processing. The highest percentage of retraction occurs at the time of resection. Margin shrinkage based on tumor site and tumor stage should be considered by any oncologic surgeon to ensure adequate margins of resection cleared of tumor.
Taylor, Simon R J; Gonzalez-Begne, Mireya; Dewhurst, Stephen; Chimini, Giovanna; Higgins, Christopher F; Melvin, James E; Elliott, James I
2008-01-01
Patterns of change in cell volume and plasma membrane phospholipid distribution during cell death are regarded as diagnostic means of distinguishing apoptosis from necrosis, the former being associated with cell shrinkage and early phosphatidylserine (PS) exposure, whereas necrosis is associated with cell swelling and consequent lysis. We demonstrate that cell volume regulation during lymphocyte death stimulated via the purinergic receptor P2X7 is distinct from both. Within seconds of stimulation, murine lymphocytes undergo rapid shrinkage concomitant with, but also required for, PS exposure. However, within 2 min shrinkage is reversed and swelling ensues ending in cell rupture. P2X7-induced shrinkage and PS translocation depend upon K+ efflux via KCa3.1, but use a pathway of Cl- efflux distinct from that previously implicated in apoptosis. Thus, P2X7 stimulation activates a novel pathway of cell death that does not conform to those conventionally associated with apoptosis and necrosis. The mixed apoptotic/necrotic phenotype of P2X7-stimulated cells is consistent with a potential role for this death pathway in lupus disease.
A modelling study of drying shrinkage damage in concrete repair systems
Lukovic, M.; Savija, B.; Schlangen, E.; Ye, G.; van Breugel, K.
2014-01-01
Differential shrinkage between repair material and concrete substrate is considered to be the main cause of premature failure of repair systems (Martinola, Sadouki et al. 2001, Beushausen and Alexander 2007). Magnitude of induced stresses depends on many factors, for example the amount of restraint,
Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space.
Directory of Open Access Journals (Sweden)
Ivar Østby
2009-01-01
Full Text Available Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance and astrocyte function, the phenomenon remains unexplained. Here we present a dynamic model that accounts for current experimental data related to the shrinkage phenomenon in wild-type as well as in gene knockout individuals. We find that neuronal release of potassium and uptake of sodium during stimulation, astrocyte uptake of potassium, sodium, and chloride in passive channels, action of the Na/K/ATPase pump, and osmotically driven transport of water through the astrocyte membrane together seem sufficient for generating ECS shrinkage as such. However, when taking into account ECS and astrocyte ion concentrations observed in connection with neuronal stimulation, the actions of the Na(+/K(+/Cl(- (NKCC1 and the Na(+/HCO(3 (- (NBC cotransporters appear to be critical determinants for achieving observed quantitative levels of ECS shrinkage. Considering the current state of knowledge, the model framework appears sufficiently detailed and constrained to guide future key experiments and pave the way for more comprehensive astroglia-neuron interaction models for normal as well as pathophysiological situations.
Brain shrinkage in alcoholics is not caused by changes in hydration: a pathological study.
Harper, C. G.; Kril, J J; Daly, J.M.
1988-01-01
Measurement of the water content of the cerebral white matter in 26 control and 24 alcoholic cases supports in vivo MRI studies and previous necropsy studies which appeared to show an increase in the water content in the alcoholic group. This negates the hypothesis that reversible brain shrinkage in alcoholics is caused by changes in the state of hydration.
Differential brain shrinkage over 6 months shows limited association with cognitive practice.
Raz, Naftali; Schmiedek, Florian; Rodrigue, Karen M; Kennedy, Kristen M; Lindenberger, Ulman; Lövdén, Martin
2013-07-01
The brain shrinks with age, but the timing of this process and the extent of its malleability are unclear. We measured changes in regional brain volumes in younger (age 20-31) and older (age 65-80) adults twice over a 6 month period, and examined the association between changes in volume, history of hypertension, and cognitive training. Between two MRI scans, 49 participants underwent intensive practice in three cognitive domains for 100 consecutive days, whereas 23 control group members performed no laboratory cognitive tasks. Regional volumes of seven brain structures were measured manually and adjusted for intracranial volume. We observed significant mean shrinkage in the lateral prefrontal cortex, the hippocampus, the caudate nucleus, and the cerebellum, but no reliable mean change of the prefrontal white matter, orbital-frontal cortex, and the primary visual cortex. Individual differences in change were reliable in all regions. History of hypertension was associated with greater cerebellar shrinkage. The cerebellum was the only region in which significantly reduced shrinkage was apparent in the experimental group after completion of cognitive training. Thus, in healthy adults, differential brain shrinkage can be observed in a narrow time window, vascular risk may aggravate it, and intensive cognitive activity may have a limited effect on it.
Significant reversibility of alcoholic brain shrinkage within 3 weeks of abstinence.
Trabert, W; Betz, T; Niewald, M; Huber, G
1995-08-01
Chronic alcoholism is often associated with brain shrinkage or atrophy. During recent years, it has been demonstrated that this shrinkage is, at least in part, reversible when abstinence is maintained. There are different hypotheses concerning the mechanisms for this reversibility, but many questions are still open. Especially the time conditions for these reversible changes are subject of discussion. Twenty-eight male patients with severe alcohol dependence were investigated in a computed tomographic study at the beginning of abstinence and 3 weeks later. Planimetric evaluation of 5 selected slices revealed a significant decrease in liquor areas and an increase of brain volume. The densitometric analysis showed an increase in brain tissue density. In a multiple regression approach it was shown that the reversibility was mostly influenced by the age of the patients. Our results support neither the hypothesis of an increase in brain water as the most important principle for reversibility in alcoholic brain shrinkage nor the hypothesis of augmented dendritic growth. Other mechanisms like reduced (during chronic intoxication) and normalized (during abstinence) cerebral hemoperfusion have to be considered as possible mechanisms for the reversibility of alcoholic brain shrinkage.
Shrinkages in heavy-sized cast components of nodular cast iron – NDT and fatigue
Directory of Open Access Journals (Sweden)
Bleicher Christoph
2014-06-01
Full Text Available Material defects like shrinkages, dross, pores and chunky graphite are likely to occur in thick-walled castings and are a challenge for the foundries and their customers. These defects are mostly detected with handheld ultrasonic testing (UT or X-ray analysis. Within a research project done at the Fraunhofer Institute for Structural Durability and System Reliability LBF, the fatigue of Dross, shrinkages and chunky graphite in thick-walled cast material GGG-40 was estimated based on X-ray and fatigue tests on bending specimens. High fatigue reductions were received for the different material imperfections. Based on these impressions a further research project was executed at the Fraunhofer LBF to get an estimation of the informational value of UT in relation to fatigue of shrinkages in thick-walled castings of the material EN-GJS-400-18U-LT, EN-GJS-450-18 and EN-GJS-700-2. With the help of X-ray analysis and the UT technique Sampling Phased Array (SPA information about geometry and density were derived for a numerical analysis of shrinkages in thick-walled castings concerning fatigue. The following text summarizes the fatigue results achieved in the two research projects with the help of the X-ray and UT analysis.
Tijani, Yakub; Heinrietz, André; Stets, Wolfram; Voigt, Patrick
2013-12-01
In the current study, test bars of cast aluminum alloys EN AC-AlSi8Cu3 and EN AC-AlSi7Mg0.3 were produced with a defined amounts of shrinkage pores and oxides. For this purpose, a permanent mold with heating and cooling devices for the generation of pores was constructed. The oxides were produced by contaminating the melt. The specimens and their corresponding defect distributions were examined and quantified by X-ray computer tomography (CT) and quantitative metallography, respectively. A special test algorithm for the simultaneous image analyses of pores and oxides was developed. Fatigue tests were conducted on the defective samples. It was found that the presence of shrinkage pores lowers the fatigue strength, and only few oxide inclusions were found to initiate fatigue cracks when shrinkage pores are present. The results show that the pore volume is not sufficient to characterize the influence of shrinkage pores on fatigue life. A parametric model for the calculation of fatigue life based on the pore parameters obtained from CT scans was implemented. The model accounts for the combined impact of pore location, size, and shape on fatigue life reduction.
Institute of Scientific and Technical Information of China (English)
MA Baoguo; WANG Xin'gang; LI Xiangguo; YANG Lei
2007-01-01
The effects of polynaphthalene series superplasticizers(PNS) with a low content of sodium sulfate (H-UNF),with a high content of sodium sulfate(C-UNF) and polycarboxylate type superplasticizer (PC) on strength and shrinkage cracking of cement mortar under drying conditions were investigated by means of multi-channel ellipse ring shrinkage cracking test, free shrinkage and strength test. The general effect of PNS and PC is to increase the initial cracking time of mortars, and decrease the cracking sensitivity of mortars. As for decreasing the cracking sensitivity of mortars, PC＞H-UNF＞C-UNF. To incorporate superplasticizers is apparently to increase the free shrinkage of mortars when keeping the constant w/b ratio and the content of cement pastes. As for the effect of controlling the volume stability of mortars, PC＞C-UNF＞H-UNF. Maximum crack width of mortars containing PC is lower, but the development rate of maximum crack width of mortars containing H-UNF is faster in comparison with control mortars. The flexural and compressive strengths of mortars at 28-day increase with increasing superplasticizer dosages under drying conditions. PC was superior to PNS in the aspect of increasing strength.
Numerical Analysis of Influence of the Mold Material on the Distribution of Shrinkage Cavities
Directory of Open Access Journals (Sweden)
R. Dyja
2013-01-01
Full Text Available Production of castings, like any other field of technology is aimed at providing high-quality product, free from defects. One of the maincauses of defects in castings is the phenomenon of shrinkage of the casting. This phenomenon causes the formation of shrinkage cavitiesand porosity in the casting. The major preventive measure is supplementing a shortage of liquid metal. For supplement to be effective, it is necessary to use risers in proper shapes. Usually, the risers are selected on the basis of determination the place of formation of hot-spots in the castings. Although in these places the shrinkage defects are most likely to occur, shape and size of these defects are also affected by other factors. The article describes the original program setting out the shape and location of possible cavities in the casting. In the program is also taken into account the effect of temperature on the change in volume of liquid metal and the resultant differences in the shape and size of formed shrinkage cavities. The aim of the article is to describe the influence that have material properties of the mold on the simulation results.
Autogenous shrinkage of Ducorit S5R ASTM C 1698-09 test method
DEFF Research Database (Denmark)
Damkilde, Lars
The report deals with experimental measurement of autogenous shrinkage of Ducorit S5R according to the test method ASTM C 1698-09. This test method measures the bulk strain of a sealed cementitious specimen, at constant temperature and not subjected to external forces, from the time of final...
Porous stainless steel hollow fibers with shrinkage-controlled small radial dimensions
Luiten-Olieman, Mieke W.J.; Raaijmakers, Michiel J.T.; Winnubst, Louis; Wessling, Matthias; Nijmeijer, Arian; Benes, Nieck E.
2011-01-01
A method is presented for the preparation of thin (∼250 μm) porous stainless steel hollow fiber membranes based on dry–wet spinning of a particle-loaded polymer solution followed by heat treatment. Extraordinarily small radial dimensions were achieved by controlled shrinkage during thermal treatment
Gregor, L.; Bortolotto, T.; Feilzer, A.J.; Krejci, I.
2013-01-01
Purpose: To evaluate the relation between the linear displacement (LD), shrinkage force (SF) and marginal adaptation of a methacrylate- and a silorane-based composite. Materials and Methods: The LD and SF of 8 samples made of Filtek Supreme XT (methacrylate-based composite) and Filtek Silorane (silo
Shrinkage of bubbles and drops in the lattice Boltzmann equation method for nonideal gases
Zheng, Lin; Lee, Taehun; Guo, Zhaoli; Rumschitzki, David
2014-03-01
One characteristic of multiphase lattice Boltzmann equation (LBE) methods is that the interfacial region has a finite (i.e., noninfinitesimal) thickness known as a diffuse interface. In simulations of, e.g., bubble or drop dynamics, for problems involving nonideal gases, one frequently observes that the diffuse interface method produces a spontaneous, nonphysical shrinkage of the bubble or drop radius. In this paper, we analyze in detail a single-fluid two-phase model and use a LBE model for nonideal gases in order to explain this fundamental problem. For simplicity, we only investigate the static bubble or droplet problem. We find that the method indeed produces a density shift, bubble or droplet shrinkage, as well as a critical radius below which the bubble or droplet eventually vanishes. Assuming that the ratio between the interface thickness D and the initial bubble or droplet radius r0 is small, we analytically show the existence of this density shift, bubble or droplet radius shrinkage, and critical bubble or droplet survival radius. Numerical results confirm our analysis. We also consider droplets on a solid surface with different curvatures, contact angles, and initial droplet volumes. Numerical results show that the curvature, contact angle, and the initial droplet volume have an effect on this spontaneous shrinkage process, consistent with the survival criterion.
Properties of a New Dental Photocurable Matrix Resin with Low Shrinkage
Institute of Scientific and Technical Information of China (English)
FU Jing; JIA Fang; XU Haiping; JI Baohui; LIU Xiaoqing
2011-01-01
In order to reduce the amount of volumetric shrinkage that occurs in dental composites as a result of curing, a new kind of dental matrix resin combining bisphenol-S-bis(3-meth acry late-2-hydroxy propyl)ether(BisS-GMA) with the expanding monomer unsaturated spiro orthoesters 2-methylene-1, 4, 6-trispiro[4, 4] nonane (SOE) was prepared, with triethylene glycol dimethacrylate (TEGDMA) as diluent. CQ (camphorquinone) of 1wt% and DMAEMA (2-(dimethylamino) ethyl meth acrylate) of 2wt% were used as photoinitiation system to initiate the copolymerization of the matrix resins. The performance including volumetric shrinkage, degree of conversion and condition of the ring-opening reaction of SOE, as well as curing time and the tensile bond strength were investigated respectively by the dilatometer, Fourier transfer infrared, the universal testing machine, and so on.The ring-opening polymerization of SOE occurred. Meanwhile, the obtain copolymers were crosslinked. The matrix resin containing BisS-GMA and SOE showed a reduced amount of volumetric shrinkage at 1.52%, which is a promising strategy for obtaining a polymer with a low amount of volumetric shrinkage. Furthermore, the other properties were not compromised.
Urban shrinkage, local housing markets and the role of voluntary community organisations
DEFF Research Database (Denmark)
Larsen, Jacob Norvig
Since the beginning of the crisis in 2007-08 urban shrinkage has hit a large number of Danish municipalities, towns and villages outside the two major metropolitan areas in the country .Abandoned homes, plunging property prices and out-migration are among the major symptoms. As a consequence of t...
Wehrl, Hans F; Bezrukov, Ilja; Wiehr, Stefan; Lehnhoff, Mareike; Fuchs, Kerstin; Mannheim, Julia G; Quintanilla-Martinez, Leticia; Kohlhofer, Ursula; Kneilling, Manfred; Pichler, Bernd J; Sauter, Alexander W
2015-05-01
Especially for neuroscience and the development of new biomarkers, a direct correlation between in vivo imaging and histology is essential. However, this comparison is hampered by deformation and shrinkage of tissue samples caused by fixation, dehydration and paraffin embedding. We used magnetic resonance (MR) imaging and computed tomography (CT) imaging to analyze the degree of shrinkage on murine brains for various fixatives. After in vivo imaging using 7 T MRI, animals were sacrificed and the brains were dissected and immediately placed in different fixatives, respectively: zinc-based fixative, neutral buffered formalin (NBF), paraformaldehyde (PFA), Bouin-Holland fixative and paraformaldehyde-lysine-periodate (PLP). The degree of shrinkage based on mouse brain volumes, radiodensity in Hounsfield units (HU), as well as non-linear deformations were obtained. The highest degree of shrinkage was observed for PLP (68.1%, P brain shrinkage and only small deformations and is therefore recommended for in vivo ex vivo comparison studies.
Zainudin, A.; Sia, C. K.; Ong, P.; Narong, O. L. C.; Nor, N. H. M.
2017-01-01
In the preparation of triaxial porcelain from Palm Oil Fuel Ash (POFA), a new parameter variable must be determined. The parameters involved are the particle size of POFA, percentage of POFA in triaxial porcelain composition, moulding pressure, sintering temperature and soaking time. Meanwhile, the shrinkage is the dependent variable. The optimization process was investigated using a hybrid Taguchi design and flower pollination algorithm (FPA). The interaction model of shrinkage was derived from regression analysis and found that the shrinkage is highly dependent on the sintering temperature followed by POFA composition, moulding pressure, POFA particle size and soaking time. The interaction between sintering temperature and soaking time highly affects the shrinkage. From the FPA process, targeted shrinkage approaching zero values were predicted for 142 μm particle sizes of POFA, 22.5 wt% of POFA, 3.4 tonne moulding pressure, 948.5 °C sintering temperature and 264 minutes soaking time.
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
The effects of metallurgical and processing parameters on the formation of shrinkage cavities and porosities in spheroidal graphite cast iron have been studied, considering the parameters of carbon equivalent, inoculation, casting modulus, mold type (green or dry) and pouring temperature within specific ranges of these variables. Based on the orthogonal experiments, the metallurgical and processing parameters of the minimum casting shrinkage and the maximum casting shrinkage were obtained, and the effects of metallurgical and processing parameters on the formation of shrinkage cavities and porosities in spheroidal graphite cast iron castings were discussed. Finally,two regression equations relating these variables to the formation of shrinkage porosity were derived based upon the orthogonal experiments conducted.
Bayesian Smoothing with Gaussian Processes Using Fourier Basis Functions in the spectralGP Package
Directory of Open Access Journals (Sweden)
Christopher J. Paciorek
2007-04-01
Full Text Available The spectral representation of stationary Gaussian processes via the Fourier basis provides a computationally efficient specification of spatial surfaces and nonparametric regression functions for use in various statistical models. I describe the representation in detail and introduce the spectralGP package in R for computations. Because of the large number of basis coefficients, some form of shrinkage is necessary; I focus on a natural Bayesian approach via a particular parameterized prior structure that approximates stationary Gaussian processes on a regular grid. I review several models from the literature for data that do not lie on a grid, suggest a simple model modification, and provide example code demonstrating MCMC sampling using the spectralGP package. I describe reasons that mixing can be slow in certain situations and provide some suggestions for MCMC techniques to improve mixing, also with example code, and some general recommendations grounded in experience.
Bayesian priors for transiting planets
Kipping, David M
2016-01-01
As astronomers push towards discovering ever-smaller transiting planets, it is increasingly common to deal with low signal-to-noise ratio (SNR) events, where the choice of priors plays an influential role in Bayesian inference. In the analysis of exoplanet data, the selection of priors is often treated as a nuisance, with observers typically defaulting to uninformative distributions. Such treatments miss a key strength of the Bayesian framework, especially in the low SNR regime, where even weak a priori information is valuable. When estimating the parameters of a low-SNR transit, two key pieces of information are known: (i) the planet has the correct geometric alignment to transit and (ii) the transit event exhibits sufficient signal-to-noise to have been detected. These represent two forms of observational bias. Accordingly, when fitting transits, the model parameter priors should not follow the intrinsic distributions of said terms, but rather those of both the intrinsic distributions and the observational ...
Bayesian approach to rough set
Marwala, Tshilidzi
2007-01-01
This paper proposes an approach to training rough set models using Bayesian framework trained using Markov Chain Monte Carlo (MCMC) method. The prior probabilities are constructed from the prior knowledge that good rough set models have fewer rules. Markov Chain Monte Carlo sampling is conducted through sampling in the rough set granule space and Metropolis algorithm is used as an acceptance criteria. The proposed method is tested to estimate the risk of HIV given demographic data. The results obtained shows that the proposed approach is able to achieve an average accuracy of 58% with the accuracy varying up to 66%. In addition the Bayesian rough set give the probabilities of the estimated HIV status as well as the linguistic rules describing how the demographic parameters drive the risk of HIV.
Deep Learning and Bayesian Methods
Directory of Open Access Journals (Sweden)
Prosper Harrison B.
2017-01-01
Full Text Available A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.
Deep Learning and Bayesian Methods
Prosper, Harrison B.
2017-03-01
A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.
Bayesian Source Separation and Localization
Knuth, K H
1998-01-01
The problem of mixed signals occurs in many different contexts; one of the most familiar being acoustics. The forward problem in acoustics consists of finding the sound pressure levels at various detectors resulting from sound signals emanating from the active acoustic sources. The inverse problem consists of using the sound recorded by the detectors to separate the signals and recover the original source waveforms. In general, the inverse problem is unsolvable without additional information. This general problem is called source separation, and several techniques have been developed that utilize maximum entropy, minimum mutual information, and maximum likelihood. In previous work, it has been demonstrated that these techniques can be recast in a Bayesian framework. This paper demonstrates the power of the Bayesian approach, which provides a natural means for incorporating prior information into a source model. An algorithm is developed that utilizes information regarding both the statistics of the amplitudes...
Bayesian Inference for Radio Observations
Lochner, Michelle; Zwart, Jonathan T L; Smirnov, Oleg; Bassett, Bruce A; Oozeer, Nadeem; Kunz, Martin
2015-01-01
(Abridged) New telescopes like the Square Kilometre Array (SKA) will push into a new sensitivity regime and expose systematics, such as direction-dependent effects, that could previously be ignored. Current methods for handling such systematics rely on alternating best estimates of instrumental calibration and models of the underlying sky, which can lead to inaccurate uncertainty estimates and biased results because such methods ignore any correlations between parameters. These deconvolution algorithms produce a single image that is assumed to be a true representation of the sky, when in fact it is just one realisation of an infinite ensemble of images compatible with the noise in the data. In contrast, here we report a Bayesian formalism that simultaneously infers both systematics and science. Our technique, Bayesian Inference for Radio Observations (BIRO), determines all parameters directly from the raw data, bypassing image-making entirely, by sampling from the joint posterior probability distribution. Thi...
Bayesian inference on proportional elections.
Directory of Open Access Journals (Sweden)
Gabriel Hideki Vatanabe Brunello
Full Text Available Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software.
Bayesian analysis for kaon photoproduction
Energy Technology Data Exchange (ETDEWEB)
Marsainy, T., E-mail: tmart@fisika.ui.ac.id; Mart, T., E-mail: tmart@fisika.ui.ac.id [Department Fisika, FMIPA, Universitas Indonesia, Depok 16424 (Indonesia)
2014-09-25
We have investigated contribution of the nucleon resonances in the kaon photoproduction process by using an established statistical decision making method, i.e. the Bayesian method. This method does not only evaluate the model over its entire parameter space, but also takes the prior information and experimental data into account. The result indicates that certain resonances have larger probabilities to contribute to the process.
Bayesian priors and nuisance parameters
Gupta, Sourendu
2016-01-01
Bayesian techniques are widely used to obtain spectral functions from correlators. We suggest a technique to rid the results of nuisance parameters, ie, parameters which are needed for the regularization but cannot be determined from data. We give examples where the method works, including a pion mass extraction with two flavours of staggered quarks at a lattice spacing of about 0.07 fm. We also give an example where the method does not work.
Space Shuttle RTOS Bayesian Network
Morris, A. Terry; Beling, Peter A.
2001-01-01
With shrinking budgets and the requirements to increase reliability and operational life of the existing orbiter fleet, NASA has proposed various upgrades for the Space Shuttle that are consistent with national space policy. The cockpit avionics upgrade (CAU), a high priority item, has been selected as the next major upgrade. The primary functions of cockpit avionics include flight control, guidance and navigation, communication, and orbiter landing support. Secondary functions include the provision of operational services for non-avionics systems such as data handling for the payloads and caution and warning alerts to the crew. Recently, a process to selection the optimal commercial-off-the-shelf (COTS) real-time operating system (RTOS) for the CAU was conducted by United Space Alliance (USA) Corporation, which is a joint venture between Boeing and Lockheed Martin, the prime contractor for space shuttle operations. In order to independently assess the RTOS selection, NASA has used the Bayesian network-based scoring methodology described in this paper. Our two-stage methodology addresses the issue of RTOS acceptability by incorporating functional, performance and non-functional software measures related to reliability, interoperability, certifiability, efficiency, correctness, business, legal, product history, cost and life cycle. The first stage of the methodology involves obtaining scores for the various measures using a Bayesian network. The Bayesian network incorporates the causal relationships between the various and often competing measures of interest while also assisting the inherently complex decision analysis process with its ability to reason under uncertainty. The structure and selection of prior probabilities for the network is extracted from experts in the field of real-time operating systems. Scores for the various measures are computed using Bayesian probability. In the second stage, multi-criteria trade-off analyses are performed between the scores
Elements of Bayesian experimental design
Energy Technology Data Exchange (ETDEWEB)
Sivia, D.S. [Rutherford Appleton Lab., Oxon (United Kingdom)
1997-09-01
We consider some elements of the Bayesian approach that are important for optimal experimental design. While the underlying principles used are very general, and are explained in detail in a recent tutorial text, they are applied here to the specific case of characterising the inferential value of different resolution peakshapes. This particular issue was considered earlier by Silver, Sivia and Pynn (1989, 1990a, 1990b), and the following presentation confirms and extends the conclusions of their analysis.
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
. This allows for a Bayesian formulation of the indicators whereby the experience and expertise of the inspection personnel may be fully utilized and consistently updated as frequentistic information is collected. The approach is illustrated on an example considering a concrete structure subject to corrosion....... It is shown how half-cell potential measurements may be utilized to update the probability of excessive repair after 50 years....
Maia, Rodrigo R; Reis, Rodrigo S; Moro, André F V; Perez, Cesar R; Pessôa, Bárbara M; Dias, Katia R H C
2015-01-01
Purpose. This study tested the null hypothesis that different classes of direct restorative dental materials: silorane-based resin, low-shrinkage and conventional (non-flowable and flowable) resin-based composite (RBC) do not differ from each other with regard to polymerization shrinkage, depth of cure or microhardness. Methods. 140 RBC samples were fabricated and tested by one calibrated operator. Polymerization shrinkage was measured using a gas pycnometer both before and immediately after curing with 36 J/cm(2) light energy density. Depth of cure was determined, using a penetrometer and the Knoop microhardness was tested from the top surface to a depth of 5 mm. Results. Considering polymerization shrinkage, the authors found significant differences (p flowable RBCs showed lower values compared to flowable RBCs, with the silorane-based resin presenting the smallest shrinkage. The low shrinkage flowable composite performed similarly to non-flowable with significant statistical differences compared to the two other flowable RBCs. Regarding to depth of cure, low-shrinkage flowable RBC, were most effective compared to other groups. Microhardness was generally higher for the non-flowable vs. flowable RBCs (p flowable did not differ significantly from those of non-flowable, but were significantly higher than those of the other flowable RBCs. Clinical Significance. RBCs have undergone many modifications as they have evolved and represent the most relevant restorative materials in today's dental practice. This study of low-shrinkage RBCs, conventional RBCs (non-flowable and flowable) and silorane-based composite-by in vitro evaluation of volumetric shrinkage, depth of cure and microhardness-reveals that although filler content is an important determinant of polymerization shrinkage, it is not the only variable that affects properties of materials that were tested in this study.
Shrinkage of dental composite in simulated cavity measured with digital image correlation.
Li, Jianying; Thakur, Preetanjali; Fok, Alex S L
2014-07-21
Polymerization shrinkage of dental resin composites can lead to restoration debonding or cracked tooth tissues in composite-restored teeth. In order to understand where and how shrinkage strain and stress develop in such restored teeth, Digital Image Correlation (DIC) was used to provide a comprehensive view of the displacement and strain distributions within model restorations that had undergone polymerization shrinkage. Specimens with model cavities were made of cylindrical glass rods with both diameter and length being 10 mm. The dimensions of the mesial-occlusal-distal (MOD) cavity prepared in each specimen measured 3 mm and 2 mm in width and depth, respectively. After filling the cavity with resin composite, the surface under observation was sprayed with first a thin layer of white paint and then fine black charcoal powder to create high-contrast speckles. Pictures of that surface were then taken before curing and 5 min after. Finally, the two pictures were correlated using DIC software to calculate the displacement and strain distributions. The resin composite shrunk vertically towards the bottom of the cavity, with the top center portion of the restoration having the largest downward displacement. At the same time, it shrunk horizontally towards its vertical midline. Shrinkage of the composite stretched the material in the vicinity of the "tooth-restoration" interface, resulting in cuspal deflections and high tensile strains around the restoration. Material close to the cavity walls or floor had direct strains mostly in the directions perpendicular to the interfaces. Summation of the two direct strain components showed a relatively uniform distribution around the restoration and its magnitude equaled approximately to the volumetric shrinkage strain of the material.
Salma, Imre; Németh, Zoltán; Weidinger, Tamás; Kovács, Boldizsár; Kristóf, Gergely
2016-06-01
Budapest platform for Aerosol Research and Training (BpART) was created for advancing long-term on-line atmospheric measurements and intensive aerosol sample collection campaigns in Budapest. A joint study including atmospheric chemistry or physics, meteorology, and fluid dynamics on several-year-long data sets obtained at the platform confirmed that the location represents a well-mixed, average atmospheric environment for the city centre. The air streamlines indicated that the host and neighbouring buildings together with the natural orography play an important role in the near-field dispersion processes. Details and features of the airflow structure were derived, and they can be readily utilised for further interpretations. An experimental method to determine particle diffusion losses in the differential mobility particle sizer (DMPS) system of the BpART facility was proposed. It is based on CPC-CPC (condensation particle counter) and DMPS-CPC comparisons. Growth types of nucleated particles observed in 4 years of measurements were presented and discussed specifically for cities. Arch-shaped size distribution surface plots consisting of a growth phase followed by a shrinkage phase were characterised separately since they supply information on nucleated particles. They were observed in 4.5 % of quantifiable nucleation events. The shrinkage phase took 1 h 34 min in general, and the mean shrinkage rate with standard deviation was -3.8 ± 1.0 nm h-1. The shrinkage of particles was mostly linked to changes in local atmospheric conditions, especially in global radiation and the gas-phase H2SO4 concentration through its proxy, or to atmospheric mixing in few cases. Some indirect results indicate that variations in the formation and growth rates of nucleated particles during their atmospheric transport could be a driving force of shrinkage for particles of very small sizes and on specific occasions.
12th Brazilian Meeting on Bayesian Statistics
Louzada, Francisco; Rifo, Laura; Stern, Julio; Lauretto, Marcelo
2015-01-01
Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comparison to objectivistic or frequentist Statistics counterparts; and the appropriate application of Bayesian foundations. This research in Bayesian Statistics is applicable to data analysis in biostatistics, clinical trials, law, engineering, and the social sciences. EBEB, the Brazilian Meeting on Bayesian Statistics, is held every two years by the ISBrA, the International Society for Bayesian Analysis, one of the most active chapters of the ISBA. The 12th meeting took place March 10-14, 2014 in Atibaia. Interest in foundations of inductive Statistics has grown recently in accordance with the increasing availability of Bayesian methodological alternatives. Scientists need to deal with the ever more difficult choice of the optimal method to apply to their problem. This volume shows how Bayes can be the answer. The examination and discussion on the foundations work towards the goal of proper application of Bayesia...
Halo detection via large-scale Bayesian inference
Merson, Alexander I.; Jasche, Jens; Abdalla, Filipe B.; Lahav, Ofer; Wandelt, Benjamin; Jones, D. Heath; Colless, Matthew
2016-08-01
We present a proof-of-concept of a novel and fully Bayesian methodology designed to detect haloes of different masses in cosmological observations subject to noise and systematic uncertainties. Our methodology combines the previously published Bayesian large-scale structure inference algorithm, HAmiltonian Density Estimation and Sampling algorithm (HADES), and a Bayesian chain rule (the Blackwell-Rao estimator), which we use to connect the inferred density field to the properties of dark matter haloes. To demonstrate the capability of our approach, we construct a realistic galaxy mock catalogue emulating the wide-area 6-degree Field Galaxy Survey, which has a median redshift of approximately 0.05. Application of HADES to the catalogue provides us with accurately inferred three-dimensional density fields and corresponding quantification of uncertainties inherent to any cosmological observation. We then use a cosmological simulation to relate the amplitude of the density field to the probability of detecting a halo with mass above a specified threshold. With this information, we can sum over the HADES density field realisations to construct maps of detection probabilities and demonstrate the validity of this approach within our mock scenario. We find that the probability of successful detection of haloes in the mock catalogue increases as a function of the signal to noise of the local galaxy observations. Our proposed methodology can easily be extended to account for more complex scientific questions and is a promising novel tool to analyse the cosmic large-scale structure in observations.
Bayesian Inversion of Seabed Scattering Data
2014-09-30
Bayesian Inversion of Seabed Scattering Data (Special Research Award in Ocean Acoustics) Gavin A.M.W. Steininger School of Earth & Ocean...project are to carry out joint Bayesian inversion of scattering and reflection data to estimate the in-situ seabed scattering and geoacoustic parameters...valid OMB control number. 1. REPORT DATE 30 SEP 2014 2. REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE Bayesian
Anomaly Detection and Attribution Using Bayesian Networks
2014-06-01
UNCLASSIFIED Anomaly Detection and Attribution Using Bayesian Networks Andrew Kirk, Jonathan Legg and Edwin El-Mahassni National Security and...detection in Bayesian networks , en- abling both the detection and explanation of anomalous cases in a dataset. By exploiting the structure of a... Bayesian network , our algorithm is able to efficiently search for local maxima of data conflict between closely related vari- ables. Benchmark tests using
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Chavira, Mark; Darwiche, Adnan
2004-01-01
We describe a system for exact inference with relational Bayesian networks as defined in the publicly available \\primula\\ tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference by evaluating...... and differentiating these circuits in time linear in their size. We report on experimental results showing the successful compilation, and efficient inference, on relational Bayesian networks whose {\\primula}--generated propositional instances have thousands of variables, and whose jointrees have clusters...
SYNTHESIZED EXPECTED BAYESIAN METHOD OF PARAMETRIC ESTIMATE
Institute of Scientific and Technical Information of China (English)
Ming HAN; Yuanyao DING
2004-01-01
This paper develops a new method of parametric estimate, which is named as "synthesized expected Bayesian method". When samples of products are tested and no failure events occur, thedefinition of expected Bayesian estimate is introduced and the estimates of failure probability and failure rate are provided. After some failure information is introduced by making an extra-test, a synthesized expected Bayesian method is defined and used to estimate failure probability, failure rateand some other parameters in exponential distribution and Weibull distribution of populations. Finally,calculations are performed according to practical problems, which show that the synthesized expected Bayesian method is feasible and easy to operate.
Learning dynamic Bayesian networks with mixed variables
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned....... An automated procedure for specifying prior distributions for the parameters in a dynamic Bayesian network is presented. It is a simple extension of the procedure for the ordinary Bayesian networks. Finally the W¨olfer?s sunspot numbers are analyzed....
Variational bayesian method of estimating variance components.
Arakawa, Aisaku; Taniguchi, Masaaki; Hayashi, Takeshi; Mikawa, Satoshi
2016-07-01
We developed a Bayesian analysis approach by using a variational inference method, a so-called variational Bayesian method, to determine the posterior distributions of variance components. This variational Bayesian method and an alternative Bayesian method using Gibbs sampling were compared in estimating genetic and residual variance components from both simulated data and publically available real pig data. In the simulated data set, we observed strong bias toward overestimation of genetic variance for the variational Bayesian method in the case of low heritability and low population size, and less bias was detected with larger population sizes in both methods examined. The differences in the estimates of variance components between the variational Bayesian and the Gibbs sampling were not found in the real pig data. However, the posterior distributions of the variance components obtained with the variational Bayesian method had shorter tails than those obtained with the Gibbs sampling. Consequently, the posterior standard deviations of the genetic and residual variances of the variational Bayesian method were lower than those of the method using Gibbs sampling. The computing time required was much shorter with the variational Bayesian method than with the method using Gibbs sampling.
Shah, Furqan A; Johansson, Bengt R; Thomsen, Peter; Palmquist, Anders
2015-04-01
The integrity of the interface between the osteocyte (Ot) process and the canalicular wall was investigated in terms of change in the lateral dimensions of the Ot process in relation to the canalicular width, i.e., widening of the pericellular space. This has been interpreted as shrinkage of the Ot process relative to the canalicular wall during sample preparation stages of fixation, dehydration, and resin embedding. Sprague-Dawley rat tibial cross-sections were prepared for transmission electron microscopy (TEM). Four different fixative preparations: paraformaldehyde (PF), modified Karnovsky's (MK), glutaraldehyde (GRR) with ruthenium red (GRR), and zinc formalin (ZF); and two different embedding resins: LR Gold (LRG) and Epon812 (Epon) were evaluated. It was found that for LRG embedding, formalin-only fixatives (PF and ZF) induced lower shrinkage than GRR-containing fixatives (MK and GRR). In contrast, for Epon embedding, MK showed the highest shrinkage, while no differences were found between the remaining fixatives (PF, ZF, and GRR). All formalin-containing fixatives (MK, PF, and ZF) induced similar shrinkage in both embedding media. The most dramatic difference was for GRR fixation, which in combination with LRG embedding showed ∼ 62% more shrinkage than with Epon embedding, suggesting that the combination of GRR fixation and LRG embedding synergistically amplifies Ot shrinkage. These differences likely suggest a role of the resin in secondarily influencing the tissue structure following fixation. Further, the work confirms LRG as a poor embedding medium for bone specimens, as it causes large variations in shrinkage depending on fixation.
Bayesian Analysis of the Cosmic Microwave Background
Jewell, Jeffrey
2007-01-01
There is a wealth of cosmological information encoded in the spatial power spectrum of temperature anisotropies of the cosmic microwave background! Experiments designed to map the microwave sky are returning a flood of data (time streams of instrument response as a beam is swept over the sky) at several different frequencies (from 30 to 900 GHz), all with different resolutions and noise properties. The resulting analysis challenge is to estimate, and quantify our uncertainty in, the spatial power spectrum of the cosmic microwave background given the complexities of "missing data", foreground emission, and complicated instrumental noise. Bayesian formulation of this problem allows consistent treatment of many complexities including complicated instrumental noise and foregrounds, and can be numerically implemented with Gibbs sampling. Gibbs sampling has now been validated as an efficient, statistically exact, and practically useful method for low-resolution (as demonstrated on WMAP 1 and 3 year temperature and polarization data). Continuing development for Planck - the goal is to exploit the unique capabilities of Gibbs sampling to directly propagate uncertainties in both foreground and instrument models to total uncertainty in cosmological parameters.
Bayesian data assimilation in shape registration
Cotter, C J
2013-03-28
In this paper we apply a Bayesian framework to the problem of geodesic curve matching. Given a template curve, the geodesic equations provide a mapping from initial conditions for the conjugate momentum onto topologically equivalent shapes. Here, we aim to recover the well-defined posterior distribution on the initial momentum which gives rise to observed points on the target curve; this is achieved by explicitly including a reparameterization in the formulation. Appropriate priors are chosen for the functions which together determine this field and the positions of the observation points, the initial momentum p0 and the reparameterization vector field ν, informed by regularity results about the forward model. Having done this, we illustrate how maximum likelihood estimators can be used to find regions of high posterior density, but also how we can apply recently developed Markov chain Monte Carlo methods on function spaces to characterize the whole of the posterior density. These illustrative examples also include scenarios where the posterior distribution is multimodal and irregular, leading us to the conclusion that knowledge of a state of global maximal posterior density does not always give us the whole picture, and full posterior sampling can give better quantification of likely states and the overall uncertainty inherent in the problem. © 2013 IOP Publishing Ltd.
Bayesian Methods and Universal Darwinism
Campbell, John
2009-12-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent Champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a `copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the Operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that Systems will evolve to states of highest entropy subject to the constraints of scientific law. This principle may be inverted to provide illumination as to the nature of scientific law. Our best cosmological theories suggest the universe contained much less complexity during the period shortly after the Big Bang than it does at present. The scientific subject matter of atomic physics, chemistry, biology and the social sciences has been created since that time. An explanation is proposed for the existence of this subject matter as due to the evolution of constraints in the form of adaptations imposed on Maximum Entropy. It is argued these adaptations were discovered and instantiated through the Operations of a succession of Darwinian processes.
Bayesian Query-Focused Summarization
Daumé, Hal
2009-01-01
We present BayeSum (for ``Bayesian summarization''), a model for sentence extraction in query-focused summarization. BayeSum leverages the common case in which multiple documents are relevant to a single query. Using these documents as reinforcement for query terms, BayeSum is not afflicted by the paucity of information in short queries. We show that approximate inference in BayeSum is possible on large data sets and results in a state-of-the-art summarization system. Furthermore, we show how BayeSum can be understood as a justified query expansion technique in the language modeling for IR framework.
Numeracy, frequency, and Bayesian reasoning
Directory of Open Access Journals (Sweden)
Gretchen B. Chapman
2009-02-01
Full Text Available Previous research has demonstrated that Bayesian reasoning performance is improved if uncertainty information is presented as natural frequencies rather than single-event probabilities. A questionnaire study of 342 college students replicated this effect but also found that the performance-boosting benefits of the natural frequency presentation occurred primarily for participants who scored high in numeracy. This finding suggests that even comprehension and manipulation of natural frequencies requires a certain threshold of numeracy abilities, and that the beneficial effects of natural frequency presentation may not be as general as previously believed.
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
2013-01-01
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Bayesian homeopathy: talking normal again.
Rutten, A L B
2007-04-01
Homeopathy has a communication problem: important homeopathic concepts are not understood by conventional colleagues. Homeopathic terminology seems to be comprehensible only after practical experience of homeopathy. The main problem lies in different handling of diagnosis. In conventional medicine diagnosis is the starting point for randomised controlled trials to determine the effect of treatment. In homeopathy diagnosis is combined with other symptoms and personal traits of the patient to guide treatment and predict response. Broadening our scope to include diagnostic as well as treatment research opens the possibility of multi factorial reasoning. Adopting Bayesian methodology opens the possibility of investigating homeopathy in everyday practice and of describing some aspects of homeopathy in conventional terms.
Effectiveness of shrinkage-reducing admixtures on Portland pozzolan cement concrete
Directory of Open Access Journals (Sweden)
Videla, C.
2005-06-01
Full Text Available Drying shrinkage causes tensile stress in restrained concrete members. Since all structural elements are subject to some degree of restraint, drying shrinkage is regarded to be one of the main causes of concrete cracking. The purpose of the present study was to evaluate the effectiveness of SRA in reducing drying shrinkage strain in Portland pozzolan cement concrete. The major variables examined included slump, admixture type and dose, and specimen size. The measured results indicate that any of the admixtures used in the study significantly reduced shrinkage. Concrete manufactured with shrinkage reducing admixtures shrank an average of 43% less than concrete without admixtures. As a rule, the higher the dose of admixture, the higher was its shrinkage reduction performance. The experimental results were compared to the shrinkage strain estimated with the ACI 209, CEB MC 90, B3, GL 2000, Sakata 1993 and Sakata 2001 models. Although none of these models was observed to accurately describe the behaviour of Portland pozzolan cement concrete with shrinkage reducing admixtures, the Sakata 2001 model, with a weighted coefficient of variation of under 30%, may be regarded to be roughly adequate.
La retracción por secado es un fenómeno intrínseco del hormigón que produce tensiones de tracción en elementos restringidos de hormigón. Puesto que todos los elementos presentan algún grado de retracción, se considera a la retracción por secado como una de las principales causas de agrietamiento en proyectos de construcción en hormigón. Por lo tanto, el objetivo de esta investigación fue evaluar la efectividad de los aditivos reductores de retracción (SRA en hormigones fabricados con cemento Portland puzolánico. Las variables principales estudiadas incluyen el asentamiento de cono de Abrams, marca y dosis de aditivo reductor de retracción, y tamaño de espécimen de hormigón. Los resultados obtenidos permiten concluir que el uso de
A moment projection method for population balance dynamics with a shrinkage term
Wu, Shaohua; Yapp, Edward K. Y.; Akroyd, Jethro; Mosbach, Sebastian; Xu, Rong; Yang, Wenming; Kraft, Markus
2017-02-01
A new method of moments for solving the population balance equation is developed and presented. The moment projection method (MPM) is numerically simple and easy to implement and attempts to address the challenge of particle shrinkage due to processes such as oxidation, evaporation or dissolution. It directly solves the moment transport equation for the moments and tracks the number of the smallest particles using the algorithm by Blumstein and Wheeler (1973) [41]. The performance of the new method is measured against the method of moments (MOM) and the hybrid method of moments (HMOM). The results suggest that MPM performs much better than MOM and HMOM where shrinkage is dominant. The new method predicts mean quantities which are almost as accurate as a high-precision stochastic method calculated using the established direct simulation algorithm (DSA).
Shpotyuk, Olha; Adamiak, Stanislaw; Bezvushko, Elvira; Cebulski, Jozef; Iskiv, Maryana; Shpotyuk, Oleh; Balitska, Valentina
2017-01-01
Light-curing volumetric shrinkage in dimethacrylate-based dental resin composites Dipol® is examined through comprehensive kinetics research employing nanoindentation measurements and nanoscale atomic-deficient study with lifetime spectroscopy of annihilating positrons. Photopolymerization kinetics determined through nanoindentation testing is shown to be described via single-exponential relaxation function with character time constants reaching respectively 15.0 and 18.7 s for nanohardness and elastic modulus. Atomic-deficient characteristics of composites are extracted from positron lifetime spectra parameterized employing unconstrained x3-term fitting. The tested photopolymerization kinetics can be adequately reflected in time-dependent changes observed in average positron lifetime (with 17.9 s time constant) and fractional free volume of positronium traps (with 18.6 s time constant). This correlation proves that fragmentation of free-volume positronium-trapping sites accompanied by partial positronium-to-positron traps conversion determines the light-curing volumetric shrinkage in the studied composites.
Stein-Rule Estimation and Generalized Shrinkage Methods for Forecasting Using Many Predictors
DEFF Research Database (Denmark)
Hillebrand, Eric Tobias; Lee, Tae-Hwy
We examine the Stein-rule shrinkage estimator for possible improvements in estimation and forecasting when there are many predictors in a linear time series model. We consider the Stein-rule estimator of Hill and Judge (1987) that shrinks the unrestricted unbiased OLS estimator towards a restricted...... biased principal component (PC) estimator. Since the Stein-rule estimator combines the OLS and PC estimators, it is a model-averaging estimator and produces a combined forecast. The conditions under which the improvement can be achieved depend on several unknown parameters that determine the degree......-to-noise ratio is low, the PC estimator is superior. If the signal-to-noise ratio is high, the OLS estimator is superior. In out-of-sample forecasting with AR(1) predictors, the Stein-rule shrinkage estimator can dominate both OLS and PC estimators when the predictors exhibit low persistence....
Directory of Open Access Journals (Sweden)
K. Grzeskowiak
2015-04-01
Full Text Available This paper presents the results of thermal properties and linear shrinkage of jewelry waxes utilized in investment casting. Three types of jewelry waxes were cyclically processed (by heating, holding in a molten state and coolingin the temperature range between 25 and 90 °C for about 7 hours. The samples were tested after 5th, 10th and 15thcycle. The remelting was designed to simulate the process of waxes reusability for production of patterns. Changes in thermal properties of waxes were determined using differential scanning calorimetry (DSC and linear shrinkage values were specified. The conducted examinations allowed to establish the way of multiple utilization of waxes in producing precise models.
Non-linear shrinkage estimation of large-scale structure covariance
Joachimi, Benjamin
2017-03-01
In many astrophysical settings, covariance matrices of large data sets have to be determined empirically from a finite number of mock realizations. The resulting noise degrades inference and precludes it completely if there are fewer realizations than data points. This work applies a recently proposed non-linear shrinkage estimator of covariance to a realistic example from large-scale structure cosmology. After optimizing its performance for the usage in likelihood expressions, the shrinkage estimator yields subdominant bias and variance comparable to that of the standard estimator with a factor of ∼50 less realizations. This is achieved without any prior information on the properties of the data or the structure of the covariance matrix, at a negligible computational cost.
Characterization of a gel in the cell wall to elucidate the paradoxical shrinkage of tension wood.
Clair, Bruno; Gril, Joseph; Di Renzo, Francesco; Yamamoto, Hiroyuki; Quignard, Françoise
2008-02-01
Wood behavior is characterized by high sensibility to humidity and strongly anisotropic properties. The drying shrinkage along the fibers, usually small due to the reinforcing action of cellulosic microfibrils, is surprisingly high in the so-called tension wood, produced by trees to respond to strong reorientation requirements. In this study, nitrogen adsorption-desorption isotherms of supercritically dried tension wood and normal wood show that the tension wood cell wall has a gel-like structure characterized by a pore surface more than 30 times higher than that in normal wood. Syneresis of the tension wood gel explains its paradoxical drying shrinkage. This result could help to reduce technological problems during drying. Potential applications in biomechanics and biomimetics are worth investigating, considering that, in living trees, tension wood produces tensile growth stresses 10 times higher than that of normal wood.
Early age shrinkage pattern of concrete on replacement of fine aggregate with industrial by-product
Directory of Open Access Journals (Sweden)
R.K. Mishra
2016-10-01
Full Text Available This is an experimental work carried out to investigate early age shrinkage pattern of concrete, prepared, on 50% replacement of industrial by-product (like pond ash and granulated blast furnace slag as fine aggregate using OPC, PPC and PSC as a binder. This is to observe the effect of pond ash and slag as they are having some cementitious properties and effect of cement type is also discussed. All the mixes were prepared keeping in view of pumpable concrete without any super plasticizers. Higher shrinkage value indicates the presence of more bleed water or internal moisture. It is concluded that slag is the best option for fine aggregate replacement for concrete making and durable structure.
The effect of using hybrid nanomaterials on drying shrinkage and strength of cement pastes
Directory of Open Access Journals (Sweden)
Saaid I. Zaki
2016-04-01
Full Text Available The aim of this work is to study the effect of nanomaterials on the properties of cement paste, the experimental program included three parts: a- two types of nanosilica, locally produced NS1 and imported NS2, b- nanoclay (NC and c- Hybrid nanoparticles (NS1 & NC. In each part, cement paste was used with different percentages of nanoparticles. Compressive strength and drying shrinkage tests were applied in each part on the cured and uncured samples. The results showed that the compressive strength improved in the cement paste mixtures in the cured condition, the optimum percentages was 1% for NS1, 1% for NS2, 5% for NC, and 5% (0.5%NS1 & 4.5%NC for hybrid nanoparticles. The drying shrinkage increases with adding nanosilica and hybrid nanoparticles, while it decreases when adding NC.
Minimal volume regulation after shrinkage of red blood cells from five species of reptiles
DEFF Research Database (Denmark)
Kristensen, Karina; Berenbrink, Michael; Koldkjær, Pia
2008-01-01
Red blood cells (RBCs) from most vertebrates restore volume upon hypertonic shrinkage and the mechanisms underlying this regulatory volume increase (RVI) have been studied extensively in these cells. Despite the phylogenetically interesting position of reptiles, very little is known about their red...... cell function. The present study demonstrates that oxygenated RBCs in all major groups of reptiles exhibit no or a very reduced RVI upon ~ 25% calculated hyperosmotic shrinkage. Thus, RBCs from the snakes Crotalus durissus and Python regius, the turtle Trachemys scripta and the alligator Alligator...... was not characterized. It seems, therefore, that the RVI response based on NHE activation was lost among the early sauropsids that gave rise to modern reptiles and birds, while it was retained in mammals. An RVI response has then reappeared in birds, but based on activation of the NKCC. Alternatively, the absence...
Edge detection algorithm based on ICA-domain shrinkage in noisy images
Institute of Scientific and Technical Information of China (English)
HAN XianHua; DAI ShuiYan; LI Jian; XIA GuoRong
2008-01-01
We propose a robust edge detection method based on ICA-domain shrinkage (independent component analysis). It is known that most basis functions extracted from natural images by ICA are sparse and similar to localized and oriented receptive fields, and in the proposed edge detection method, a target image is first transformed by ICA basis functions and then the edges are detected or reconstructed with sparse components. Furthermore, by applying a shrinkage algorithm to filter out the components of noise in ICA-domain, we can readily obtain the sparse components of the original image, resulting in a kind of robust edge detection even for a noisy image with a very low SN ratio. The efficiency of the proposed method is demonstrated by experiments with some natural images.
Effect of selected physical properties of waxes on investments and casting shrinkage.
Ito, M; Yamagishi, T; Oshida, Y; Munoz, C A
1996-02-01
This study evaluated the relationship between flow characteristics, bending strength, and softening temperature of paraffin and dental inlay waxes to casting shrinkage when patterns were invested with a phosphate-bonded investment. This study found that the casting shrinkage decreased as the flow of the wax pattern increased. If a low flow wax is used or if there is a need for a thick pattern, the size of the casting ring should be increased. When wax patterns are formed for cast restorations, it is important to select the type of wax with the most desirable properties for the margin and the occlusal portions. Moreover, to accurately fabricate castings, it is necessary to understand the physical properties of the chosen waxes.
Autogenous shrinkage prediction on high-performance concrete of fly ash based on BP neural network
Wang, Baomin; Zhang, Wenping; Wang, Lijiu
2006-11-01
The article adopts test data of neural network for autogenous shrinkage to train and predict on the data which doesn't join training. The article's prediction is on the basis of common medium sand, 5-31.5mm limestone rubble, second class fly-ash, P.O42.5 silicate cement, considering factors include five ones such as ratio of water and cement, sand rate, content of cement, content of fly ash, etc.By adjusting various parameters of neural network structure, it obtains three optimized results of neural network simulation. The error between concrete autogtenous shrinkage value of neural network prediction and trial value is within 3%, which can meet requirement of the concrete engineering.
Zhao, Tuo; Liu, Han
2016-01-01
We propose an accelerated path-following iterative shrinkage thresholding algorithm (APISTA) for solving high dimensional sparse nonconvex learning problems. The main difference between APISTA and the path-following iterative shrinkage thresholding algorithm (PISTA) is that APISTA exploits an additional coordinate descent subroutine to boost the computational performance. Such a modification, though simple, has profound impact: APISTA not only enjoys the same theoretical guarantee as that of PISTA, i.e., APISTA attains a linear rate of convergence to a unique sparse local optimum with good statistical properties, but also significantly outperforms PISTA in empirical benchmarks. As an application, we apply APISTA to solve a family of nonconvex optimization problems motivated by estimating sparse semiparametric graphical models. APISTA allows us to obtain new statistical recovery results which do not exist in the existing literature. Thorough numerical results are provided to back up our theory. PMID:28133430
Fissure formation in coke. 2: Effect of heating rate, shrinkage and coke strength
Energy Technology Data Exchange (ETDEWEB)
D.R. Jenkins; M.R. Mahoney [CSIRO, North Ryde, NSW (Australia). Mathematical and Information Sciences
2010-07-15
We investigate the effects of the heating rate, coke shrinkage and coke breakage strength upon the fissure pattern developed in a coke oven charge during carbonisation. This is done principally using a mechanistic model of the formation of fissures, which considers them to be an array of equally spaced fissures, whose depth follows a 'period doubling' pattern based upon the time history of the fissures. The model results are compared with pilot scale coke oven experiments. The results show that the effect of heating rate on the fissure pattern is different to the effect of coke shrinkage, while the effect of coke breakage strength on the pattern is less pronounced. The results can be seen in both the shape and size of resulting coke lumps after stabilisation. The approach gives the opportunity to consider means of controlling the carbonisation process in order to tune the size of the coke lumps produced. 7 refs., 18 figs., 4 tabs.
Shrinkage-based diagonal discriminant analysis and its applications in high-dimensional data.
Pang, Herbert; Tong, Tiejun; Zhao, Hongyu
2009-12-01
High-dimensional data such as microarrays have brought us new statistical challenges. For example, using a large number of genes to classify samples based on a small number of microarrays remains a difficult problem. Diagonal discriminant analysis, support vector machines, and k-nearest neighbor have been suggested as among the best methods for small sample size situations, but none was found to be superior to others. In this article, we propose an improved diagonal discriminant approach through shrinkage and regularization of the variances. The performance of our new approach along with the existing methods is studied through simulations and applications to real data. These studies show that the proposed shrinkage-based and regularization diagonal discriminant methods have lower misclassification rates than existing methods in many cases.
Counting people with low-level features and Bayesian regression.
Chan, Antoni B; Vasconcelos, Nuno
2012-04-01
An approach to the problem of estimating the size of inhomogeneous crowds, which are composed of pedestrians that travel in different directions, without using explicit object segmentation or tracking is proposed. Instead, the crowd is segmented into components of homogeneous motion, using the mixture of dynamic-texture motion model. A set of holistic low-level features is extracted from each segmented region, and a function that maps features into estimates of the number of people per segment is learned with Bayesian regression. Two Bayesian regression models are examined. The first is a combination of Gaussian process regression with a compound kernel, which accounts for both the global and local trends of the count mapping but is limited by the real-valued outputs that do not match the discrete counts. We address this limitation with a second model, which is based on a Bayesian treatment of Poisson regression that introduces a prior distribution on the linear weights of the model. Since exact inference is analytically intractable, a closed-form approximation is derived that is computationally efficient and kernelizable, enabling the representation of nonlinear functions. An approximate marginal likelihood is also derived for kernel hyperparameter learning. The two regression-based crowd counting methods are evaluated on a large pedestrian data set, containing very distinct camera views, pedestrian traffic, and outliers, such as bikes or skateboarders. Experimental results show that regression-based counts are accurate regardless of the crowd size, outperforming the count estimates produced by state-of-the-art pedestrian detectors. Results on 2 h of video demonstrate the efficiency and robustness of the regression-based crowd size estimation over long periods of time.
Modelling of JET diagnostics using Bayesian Graphical Models
Energy Technology Data Exchange (ETDEWEB)
Svensson, J. [IPP Greifswald, Greifswald (Germany); Ford, O. [Imperial College, London (United Kingdom); McDonald, D.; Hole, M.; Nessi, G. von; Meakins, A.; Brix, M.; Thomsen, H.; Werner, A.; Sirinelli, A.
2011-07-01
The mapping between physics parameters (such as densities, currents, flows, temperatures etc) defining the plasma 'state' under a given model and the raw observations of each plasma diagnostic will 1) depend on the particular physics model used, 2) is inherently probabilistic, from uncertainties on both observations and instrumental aspects of the mapping, such as calibrations, instrument functions etc. A flexible and principled way of modelling such interconnected probabilistic systems is through so called Bayesian graphical models. Being an amalgam between graph theory and probability theory, Bayesian graphical models can simulate the complex interconnections between physics models and diagnostic observations from multiple heterogeneous diagnostic systems, making it relatively easy to optimally combine the observations from multiple diagnostics for joint inference on parameters of the underlying physics model, which in itself can be represented as part of the graph. At JET about 10 diagnostic systems have to date been modelled in this way, and has lead to a number of new results, including: the reconstruction of the flux surface topology and q-profiles without any specific equilibrium assumption, using information from a number of different diagnostic systems; profile inversions taking into account the uncertainties in the flux surface positions and a substantial increase in accuracy of JET electron density and temperature profiles, including improved pedestal resolution, through the joint analysis of three diagnostic systems. It is believed that the Bayesian graph approach could potentially be utilised for very large sets of diagnostics, providing a generic data analysis framework for nuclear fusion experiments, that would be able to optimally utilize the information from multiple diagnostics simultaneously, and where the explicit graph representation of the connections to underlying physics models could be used for sophisticated model testing. This
Bayesian credible interval construction for Poisson statistics
Institute of Scientific and Technical Information of China (English)
ZHU Yong-Sheng
2008-01-01
The construction of the Bayesian credible (confidence) interval for a Poisson observable including both the signal and background with and without systematic uncertainties is presented.Introducing the conditional probability satisfying the requirement of the background not larger than the observed events to construct the Bayesian credible interval is also discussed.A Fortran routine,BPOCI,has been developed to implement the calculation.
Advances in Bayesian Modeling in Educational Research
Levy, Roy
2016-01-01
In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...... for complex networks can be derived and point out relevant literature....
Modeling Diagnostic Assessments with Bayesian Networks
Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego
2007-01-01
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Using Bayesian Networks to Improve Knowledge Assessment
Millan, Eva; Descalco, Luis; Castillo, Gladys; Oliveira, Paula; Diogo, Sandra
2013-01-01
In this paper, we describe the integration and evaluation of an existing generic Bayesian student model (GBSM) into an existing computerized testing system within the Mathematics Education Project (PmatE--Projecto Matematica Ensino) of the University of Aveiro. This generic Bayesian student model had been previously evaluated with simulated…
The Bayesian Revolution Approaches Psychological Development
Shultz, Thomas R.
2007-01-01
This commentary reviews five articles that apply Bayesian ideas to psychological development, some with psychology experiments, some with computational modeling, and some with both experiments and modeling. The reviewed work extends the current Bayesian revolution into tasks often studied in children, such as causal learning and word learning, and…
Bayesian analysis of exoplanet and binary orbits
Schulze-Hartung, Tim; Launhardt, Ralf; Henning, Thomas
2012-01-01
We introduce BASE (Bayesian astrometric and spectroscopic exoplanet detection and characterisation tool), a novel program for the combined or separate Bayesian analysis of astrometric and radial-velocity measurements of potential exoplanet hosts and binary stars. The capabilities of BASE are demonstrated using all publicly available data of the binary Mizar A.
Bayesian Network for multiple hypthesis tracking
W.P. Zajdel; B.J.A. Kröse
2002-01-01
For a flexible camera-to-camera tracking of multiple objects we model the objects behavior with a Bayesian network and combine it with the multiple hypohesis framework that associates observations with objects. Bayesian networks offer a possibility to factor complex, joint distributions into a produ
Bayesian coestimation of phylogeny and sequence alignment
Directory of Open Access Journals (Sweden)
Jensen Jens
2005-04-01
Full Text Available Abstract Background Two central problems in computational biology are the determination of the alignment and phylogeny of a set of biological sequences. The traditional approach to this problem is to first build a multiple alignment of these sequences, followed by a phylogenetic reconstruction step based on this multiple alignment. However, alignment and phylogenetic inference are fundamentally interdependent, and ignoring this fact leads to biased and overconfident estimations. Whether the main interest be in sequence alignment or phylogeny, a major goal of computational biology is the co-estimation of both. Results We developed a fully Bayesian Markov chain Monte Carlo method for coestimating phylogeny and sequence alignment, under the Thorne-Kishino-Felsenstein model of substitution and single nucleotide insertion-deletion (indel events. In our earlier work, we introduced a novel and efficient algorithm, termed the "indel peeling algorithm", which includes indels as phylogenetically informative evolutionary events, and resembles Felsenstein's peeling algorithm for substitutions on a phylogenetic tree. For a fixed alignment, our extension analytically integrates out both substitution and indel events within a proper statistical model, without the need for data augmentation at internal tree nodes, allowing for efficient sampling of tree topologies and edge lengths. To additionally sample multiple alignments, we here introduce an efficient partial Metropolized independence sampler for alignments, and combine these two algorithms into a fully Bayesian co-estimation procedure for the alignment and phylogeny problem. Our approach results in estimates for the posterior distribution of evolutionary rate parameters, for the maximum a-posteriori (MAP phylogenetic tree, and for the posterior decoding alignment. Estimates for the evolutionary tree and multiple alignment are augmented with confidence estimates for each node height and alignment column
[Studies on the pour type resin for denture. (II) Curing shrinkage (author's transl)].
Nagata, K
1976-09-01
This study was to investigate the influence of concentration of crossliniking agents in the monomer and pressure applied on the curing shrinkage in pour type resins. A pressure could improve the dimentional accuracy in both case of the syrup and the power-liquid type resins, on the other hand crosslinking agents gave adversed effect on the dimentional accuracy of the pour type resins, especially on that of the group.
Mamy, Laurent; Letouzey, Vincent; Lavigne, Jean-Philippe; Garric, Xavier; Gondry, Jean; Mares, Pierre; De Tayrac, Renaud
2010-01-01
International audience; INTRODUCTION AND HYPOTHESIS: The aim of this study was to evaluate a link between mesh infection and shrinkage. METHODS: Twenty-eight Wistar rats were implanted with synthetic meshes that were either non-absorbable (polypropylene (PP), n = 14) or absorbable (poly (D: ,L: -lactic acid) (PLA94), n = 14). A validated animal incisionnal abdominal hernia model of mesh infection was used. Fourteen meshes (n = 7 PLA94 and n = 7 PP meshes) were infected intraoperatively with 1...
Kurovics, E.; Buzimov, A. Y.; Gömze, L. A.
2016-04-01
In this work some new raw material compositions from alumina, conventional brick-clays and sawdust were mixed, compacted and heat treated by the authors. Depending on raw material compositions and firing temperatures the specimens were examined on shrinkage, water absorption, heat conductivity and microstructures. The real raised experiments have shown the important role of firing temperature and raw material composition on color, heat conductivity and microstructure of the final product.
Evolutionary trajectory of white spot syndrome virus (WSSV genome shrinkage during spread in Asia.
Directory of Open Access Journals (Sweden)
Mark P Zwart
Full Text Available BACKGROUND: White spot syndrome virus (WSSV is the sole member of the novel Nimaviridae family, and the source of major economic problems in shrimp aquaculture. WSSV appears to have rapidly spread worldwide after the first reported outbreak in the early 1990s. Genomic deletions of various sizes occur at two loci in the WSSV genome, the ORF14/15 and ORF23/24 variable regions, and these have been used as molecular markers to study patterns of viral spread over space and time. We describe the dynamics underlying the process of WSSV genome shrinkage using empirical data and a simple mathematical model. METHODOLOGY/PRINCIPAL FINDINGS: We genotyped new WSSV isolates from five Asian countries, and analyzed this information together with published data. Genome size appears to stabilize over time, and deletion size in the ORF23/24 variable region was significantly related to the time of the first WSSV outbreak in a particular country. Parameter estimates derived from fitting a simple mathematical model of genome shrinkage to the data support a geometric progression (k<1 of the genomic deletions, with k = 0.371 ± 0.150. CONCLUSIONS/SIGNIFICANCE: The data suggest that the rate of genome shrinkage decreases over time before attenuating. Bioassay data provided support for a link between genome size and WSSV fitness in an aquaculture setting. Differences in genomic deletions between geographic WSSV isolates suggest that WSSV spread did not follow a smooth pattern of geographic radiation, suggesting spread of WSSV over long distances by commercial activities. We discuss two hypotheses for genome shrinkage, an adaptive and a neutral one. We argue in favor of the adaptive hypothesis, given that there is support for a link between WSSV genome size and fitness.
Minimum Reinforcement in Concrete Structures under Restrained Shrinkage and Thermal Actions
DEFF Research Database (Denmark)
Christiansen, Morten Bo; Nielsen, Mogens Peter
1999-01-01
The present paper deals with minimum reinforcement to ensure limitation of crack widths in concrete structures subjected to small imposed strains, such as those from restrained shrinkage or thermal actions. A theory is presented, which models the behaviour of a tensile member from zero load...... to first yielding of reinforcement. The theory takes into account the formation of each crack. However, concluding the paper, a simple design formula is given, which provides the amount of reinforcement, necessary to ensure a given crack width....
Jeong, Tae-Sung; Kang, Ho-Seung; Kim, Sung-Ki; Kim, Shin; Kim, Hyung-Il; Kwon, Yong Hoon
2009-07-01
The present study sought to evaluate the effect of resin shades on the degree of the polymerization. To this end, response variables affected by the degree of polymerization were examined in this study - namely, microhardness, polymerization shrinkage, and color change. Two commercial composite resins of four different shades were employed in this study: shades A3, A3.5, B3, and C3 of Z250 (Z2) and shades A3, A3.5, B3, and B4 of Solitaire 2 (S2). After light curing, the reflectance/absorbance, microhardness, polymerization shrinkage, and color change of the specimens were measured. On reflectance and absorbance, Z2 and S2 showed similar distribution curves regardless of the resin shade, with shade A3.5 of Z2 and shade A3 of S2 exhibiting the lowest/highest distributions. Similarly for attenuation coefficient and microhardness, the lowest/highest values were exhibited by shade A3.5 of Z2 and shade A3 of S2. On polymerization shrinkage, no statistically significant differences were observed among the different shades of Z2. Similarly for color change, Z2 specimens exhibited only a slight (DeltaE*=0.5-0.9) color change after immersion in distilled water for 10 days, except for shades A3 and A3.5. Taken together, results of the present study suggested that the degree of polymerization of the tested composite resins was minimally affected by resin shade.
Statistical mechanics provides novel insights into microtubule stability and mechanism of shrinkage.
Jain, Ishutesh; Inamdar, Mandar M; Padinhateeri, Ranjith
2015-02-01
Microtubules are nano-machines that grow and shrink stochastically, making use of the coupling between chemical kinetics and mechanics of its constituent protofilaments (PFs). We investigate the stability and shrinkage of microtubules taking into account inter-protofilament interactions and bending interactions of intrinsically curved PFs. Computing the free energy as a function of PF tip position, we show that the competition between curvature energy, inter-PF interaction energy and entropy leads to a rich landscape with a series of minima that repeat over a length-scale determined by the intrinsic curvature. Computing Langevin dynamics of the tip through the landscape and accounting for depolymerization, we calculate the average unzippering and shrinkage velocities of GDP protofilaments and compare them with the experimentally known results. Our analysis predicts that the strength of the inter-PF interaction (E(s)(m)) has to be comparable to the strength of the curvature energy (E(b)(m)) such that E(s)(m) - E(b)(m) ≈ 1kBT, and questions the prevalent notion that unzippering results from the domination of bending energy of curved GDP PFs. Our work demonstrates how the shape of the free energy landscape is crucial in explaining the mechanism of MT shrinkage where the unzippered PFs will fluctuate in a set of partially peeled off states and subunit dissociation will reduce the length.
The influence of polymerization shrinkage of resin cements on bonding to metal.
Verzijden, C W; Feilzer, A J; Creugers, N H; Davidson, C L
1992-02-01
During the setting of a resin composite cement (RCC) used as an adhesive between a resin-bonded bridge and tooth structure, the adhesion may be disrupted by the development of shrinkage stress. The aim of this study was to investigate the influence of the shrinkage stress of three different RCCs on their adhesive and cohesive qualities when bonded to metal surfaces in a rigid set-up. Two opposing parallel NiCr discs (Wiron 77) were mounted in a tensilometer at a mutual distance of 200 microns and cemented with Panavia Ex, Clearfil F2, or Microfill Pontic C. The alloy surfaces were treated by either electrolytic etching, sand-blasting, silane-coating, or tin-plating. During setting, the discs were kept at their original mutual distance to simulate the extreme clinical situation of "complete" rigidity, where the casting and the tooth cannot move toward each other. The developing shrinkage stress was recorded continuously. During setting, the adhesive strength of the RCCs to silane-coated surfaces was always higher than their early cohesive strength. Electrolytically-etched surfaces as well as sand-blasted surfaces showed, in almost all cases, adhesive failure. The tin-plated samples showed mainly adhesive failure at the metal/resin interface. The highest bond strength values were found for silane-coated surfaces in combination with Clearfil F2.
Non-uniform shrinkage of multiple-walled carbon nanotubes under in situ electron beam irradiation
Energy Technology Data Exchange (ETDEWEB)
Li, Lunxiong [South China Normal University, Brain Science Institute, Guangzhou (China); Xiamen University, China-Australia Joint Laboratory for Functional Nanomaterials and Physics Department, Xiamen (China); Su, Jiangbin [Xiamen University, China-Australia Joint Laboratory for Functional Nanomaterials and Physics Department, Xiamen (China); Chang Zhou University, School of Mathematics and Physics, Changzhou (China); Zhu, Xianfang [Xiamen University, China-Australia Joint Laboratory for Functional Nanomaterials and Physics Department, Xiamen (China)
2016-10-15
Instability of multiple-walled carbon nanotubes (MWCNTs) was investigated by in situ transmission electron microscopy at room temperature. Specially, the non-uniform shrinkage of tubes was found: The pristine MWCNT shrank preferentially in its axial direction from the most curved free cap end of the tube, but the shrinkage of the tube diameter was offset by the axial shrinkage: For the complex MWCNT, the two inner MWCNTs also preferentially axially shrank from their most curved cap ends and separated from each other. However, for the effect of the radial pressure from the out walls which enveloped the two inner tubes and the tube amorphization, the two inner tubes were extruded to come close to each other and finally touched again. The new ''evaporation'' and ''diffusion'' mechanisms of carbon atoms as driven by the nano-curvature of CNT and the electron beam-induced athermal activation were suggested to explain the above phenomena. (orig.)
DH and ESPI laser interferometry applied to the restoration shrinkage assessment
Campos, L. M. P.; Parra, D. F.; Vasconcelos, M. R.; Vaz, M.; Monteiro, J.
2014-01-01
In dental restoration postoperative marginal leakage is commonly associated to polymerization shrinkage effects. In consequence the longevity and quality of restorative treatment depends on the shrinkage mechanisms of the composite filling during the polymerization. In this work the development of new techniques for evaluation of those effects under light-induced polymerization of dental nano composite fillings is reported. The composite resins activated by visible light, initiate the polymerization process by absorbing light in wavelengths at about 470 nm. The techniques employed in the contraction assessment were digital holography (DH) and Electronic Speckle Pattern Interferometry (ESPI) based on laser interferometry. A satisfactory resolution was achieved in the non-contact displacement field measurements on small objects concerning the experimental dental samples. According to a specific clinical protocol, natural teeth were used (human mandibular premolars). A class I cavity was drilled and restored with nano composite material, according to Black principles. The polymerization was monitored by DH and ESPI in real time during the cure reaction of the restoration. The total displacement reported for the material in relation of the tooth wall was 3.7 μm (natural tooth). The technique showed the entire tooth surface (wall) deforming during polymerization shrinkage.
A cure shrinkage model for analyzing the stresses and strains in encapsulated assemblies
Energy Technology Data Exchange (ETDEWEB)
Chambers, R.S.; Lagasse, R.R.; Guess, T.R. (Sandia National Labs., Albuquerque, NM (United States)); Plazek, D.J.; Bero, C. (Pittsburgh Univ., PA (United States). Dept. of Materials Science and Engineering)
1992-01-01
Electrical component assemblies are encapsulated to provide delicate parts with voltage isolation and protection against damage caused by shock, vibration, and harsh atmospheric environments. During cure, thermosetting resins shrink and harden simultaneously. If the natural deformation of the resin is constrained by adhesion to the mold or to relatively stiff embedded components, cure shrinkage stresses are generated in the encapsulant. Subsequent cooling or thermal cycling produces additional stresses that are caused by the mismatches in thermal strains among the materials in the encapsulated assembly. Although cure shrinkage stresses frequently are neglected because they are considerably smaller than thermal stresses, cure shrinkage stresses can cause delamination or fractures in the encapsulant, since the partially cured resin is not as tough as the fully cured material. Cracks generated during cure can compromise performance (e. g., permit dielectric breakdown), degrade a component's protection, and grow under subsequent thermal cycling producing residual stresses that differ from those found in uncracked assemblies. 3 refs., 11 figs.
Statistical mechanics provides novel insights into microtubule stability and mechanism of shrinkage.
Directory of Open Access Journals (Sweden)
Ishutesh Jain
2015-02-01
Full Text Available Microtubules are nano-machines that grow and shrink stochastically, making use of the coupling between chemical kinetics and mechanics of its constituent protofilaments (PFs. We investigate the stability and shrinkage of microtubules taking into account inter-protofilament interactions and bending interactions of intrinsically curved PFs. Computing the free energy as a function of PF tip position, we show that the competition between curvature energy, inter-PF interaction energy and entropy leads to a rich landscape with a series of minima that repeat over a length-scale determined by the intrinsic curvature. Computing Langevin dynamics of the tip through the landscape and accounting for depolymerization, we calculate the average unzippering and shrinkage velocities of GDP protofilaments and compare them with the experimentally known results. Our analysis predicts that the strength of the inter-PF interaction (E(s(m has to be comparable to the strength of the curvature energy (E(b(m such that E(s(m - E(b(m ≈ 1kBT, and questions the prevalent notion that unzippering results from the domination of bending energy of curved GDP PFs. Our work demonstrates how the shape of the free energy landscape is crucial in explaining the mechanism of MT shrinkage where the unzippered PFs will fluctuate in a set of partially peeled off states and subunit dissociation will reduce the length.
Directory of Open Access Journals (Sweden)
Al-Swaidani A.
2014-09-01
Full Text Available In the study, three types of cement have been prepared; one CEM I type (the control sample and two blended cements: CEM II/A-P and CEM II/B-P (EN 197-1, each of them with three replacement levels of volcanic scoria: (10 %, 15 %, 20 % wt. and (25 %, 30 %, 35 % wt., respectively. Strength development of mortars has been investigated at 2, 7, 28 and 90 days curing. Evaluation of chemical resistance of mortars containing scoria-based cements has been investigated through exposure to 5 % sulphate and 5 % sulphuric acid solutions in accordance with ASTM C1012 & ASTM 267, respectively. Drying shrinkage has been evaluated in accordance with ASTM C596. Test results showed that at early ages, the mortars containing CEM II/B-P binders had strengths much lower than that of the control mortar. However, at 90 days curing, the strengths were comparable to the control mortar. In addition, the increase of scoria significantly improved the sulphate resistance of mortars. Further, an increase in scoria addition improved the sulphuric acid resistance of mortar, especially at the early days of exposure. The results of drying shrinkage revealed that the CEM II/B-P mortar bars exhibited a greater contraction when compared to the control mortar, especially at early ages. However, drying shrinkage of mortars was not influenced much at longer times.
Low shrinkage composite resins: influence on sealing ability in unfavorable C-factor cavities
Directory of Open Access Journals (Sweden)
Eliza Burlamaqui Klautau
2011-02-01
Full Text Available The present investigation observed the sealing ability of low shrinkage composite resins in large and deep cavities, placed and photocured in one increment. Large, deep cavities (5.0 mm diameter and 2.5 mm deep surrounded by enamel were prepared in bovine teeth, which were then divided into five groups. Groups 1, 2, 3 and 4: acid conditioning + Adper Single Bond (3M/ESPE, St Paul, MN, USA and restoration with Aelite LS Posterior (BISCO Inc. Schaumburg, IL, USA (G1; Filtek Z-350 (3M/ESPE,St Paul, MN, USA (G2; Filtek Z-350 Flow (3M/ESPE, St Paul, MN, USA (G3; Premisa (KERR Corporation, Orange, CA, USA (G4. Group 5: Silorane Adhesive system (3M/ESPE, St Paul, MN, USA + restoration with Filtek Low Shrinkage Posterior P90 (3M/ESPE, St Paul, MN, USA. After polymerization, the teeth were immersed in 0.5% basic fuchsine solution and immediately washed. Using the Imagetool Software, the extent of dye along the margins was calculated as a percentage of total perimeter. The restorations were then transversally sectioned and the depth of dye penetration was calculated in mm, using the same software. Kruskal-Wallis analysis for all groups showed no statistical differences for extent (p = 0.54 or depth (p = 0.8364 of dye penetration. According to this methodology, the so-called low shrinkage composite resins had the same sealing ability compared to regular and flowable nanocomposite materials.
A Study of Shrinkage Stress Reduction and Mechanical Properties of Nanogel-Modified Resin Systems.
Liu, Jiancheng; Howard, Gregory D; Lewis, Steven H; Barros, Matthew D; Stansbury, Jeffrey W
2012-11-01
A series of nanogel compositions were prepared from urethane dimethacrylate (UDMA) and isobornyl methacrylate (IBMA) in the presence of a thiol chain transfer agent. The linear oligomer of IBMA was synthesized by a similar solution polymerization technique. The nanogels were prepared with different crosslinker concentrations to achieve varied branching densities and molecular weights. The prepolymers were dispersed in triethylene glycol dimethacrylate at loading levels ranging from 10 wt% to 50 wt%. Photopolymerization reaction kinetics of all prepolymer modified systems were enhanced relative to the nanogel-free control during early stage polymerization while limiting conversion was similar for most samples. Volumetric polymerization shrinkage was reduced proportionally with the prepolymer content while the corresponding decrease in polymerization stress was potentially greater than an additive linear behavior. Flexural strength for inert linear polymer-modified systems decreased significantly with the increase in the prepolymer content; however, with an increase in the crosslinker concentration within the nanogel additives, and an increase in the concentration of residual pendant reactive sites, flexural strength was maintained or improved regardless of the nanogel loading level. This demonstrates that covalent attachment rather than just physical entanglement with the polymer matrix is important for effective polymer mechanical reinforcement by nanogel additives. Reactive nanogel additives can be considered as a practical, generic means to achieve substantial reductions in polymerization shrinkage and shrinkage stress in common polymers.
Large-proportional shrunken bio-replication of shark skin based on UV-curing shrinkage
Chen, Huawei; Che, Da; Zhang, Xin; Yue, Yue; Zhang, Deyuan
2015-01-01
The shark skin effect has attracted worldwide attention because of its superior drag reduction. As the product of natural selection, the maximum drag reduction of shark skin is found in its normal living environment. Large-proportional shrinkage of shark skin morphology is greatly anticipated for its adaptation to faster fluid flow. One novel approach, large-proportional shrunken bio-replication, is proposed as a method to adjust the optimal drag reduction region of shark skin based on the shrinkage of UV-cured material. The shark skin is taken as a replica template to allow large-proportional shrinking in the drag reduction morphology by taking advantage of the shrinkage of UV-curable material. The accuracy of the large-proportional shrunken bio-replication approach is verified by a comparison between original and shrunken bio-replicated shark skin, which shows that the shrinking ratio can reach 23% and the bio-replication accuracy is higher than 95%. In addition, the translation of the optimum drag reduction peak of natural surface function to various applications and environments is proved by drag reduction experiments.
Directory of Open Access Journals (Sweden)
Amira Touil
2014-01-01
Full Text Available Drying behaviour of prickly pear cladodes and fruits was studied with an Infrared dryer. The volume shrinkage for Opuntia ficus-indica products is calculated and a linear relation was established to describe the experimental variation of shrinkage of the product versus its moisture content. Effective diffusion coefficient of moisture transfer was determined using the Fick law at three drying temperatures (40, 50, and 60°C. Shrinkage was also included into the diffusion model for the determination of the effective diffusion coefficient. The obtained results of the effective moisture diffusivity, for the cladode and the fruit, were evaluated in the range of 1.77 × 10−10–5.07 × 10−10 m2/s and 2.53 × 10−10–7.6 × 10−10 m2/s, respectively. The values of the activation energies for cladode and fruit were estimated to be 45.39 and 47.79 kJ/mol, respectively. However, these values of moisture diffusivity were estimated independently of the evolution of moisture content during drying process. Therefore, a correlation (full quadratic equation for moisture diffusivity as a function of moisture content and temperature was developed. The parameters are obtained by a multilinear regression method. This equation was found satisfactory to describe the diffusivity evolution function of moisture content and temperature with correlation coefficients of 91.5 and 95%.
Shrinkage-based diagonal Hotelling’s tests for high-dimensional small sample size data
Dong, Kai
2015-09-16
DNA sequencing techniques bring novel tools and also statistical challenges to genetic research. In addition to detecting differentially expressed genes, testing the significance of gene sets or pathway analysis has been recognized as an equally important problem. Owing to the “large pp small nn” paradigm, the traditional Hotelling’s T2T2 test suffers from the singularity problem and therefore is not valid in this setting. In this paper, we propose a shrinkage-based diagonal Hotelling’s test for both one-sample and two-sample cases. We also suggest several different ways to derive the approximate null distribution under different scenarios of pp and nn for our proposed shrinkage-based test. Simulation studies show that the proposed method performs comparably to existing competitors when nn is moderate or large, but it is better when nn is small. In addition, we analyze four gene expression data sets and they demonstrate the advantage of our proposed shrinkage-based diagonal Hotelling’s test.
Scheibehenne, Benjamin; Pachur, Thorsten
2015-04-01
To be useful, cognitive models with fitted parameters should show generalizability across time and allow accurate predictions of future observations. It has been proposed that hierarchical procedures yield better estimates of model parameters than do nonhierarchical, independent approaches, because the formers' estimates for individuals within a group can mutually inform each other. Here, we examine Bayesian hierarchical approaches to evaluating model generalizability in the context of two prominent models of risky choice-cumulative prospect theory (Tversky & Kahneman, 1992) and the transfer-of-attention-exchange model (Birnbaum & Chavez, 1997). Using empirical data of risky choices collected for each individual at two time points, we compared the use of hierarchical versus independent, nonhierarchical Bayesian estimation techniques to assess two aspects of model generalizability: parameter stability (across time) and predictive accuracy. The relative performance of hierarchical versus independent estimation varied across the different measures of generalizability. The hierarchical approach improved parameter stability (in terms of a lower absolute discrepancy of parameter values across time) and predictive accuracy (in terms of deviance; i.e., likelihood). With respect to test-retest correlations and posterior predictive accuracy, however, the hierarchical approach did not outperform the independent approach. Further analyses suggested that this was due to strong correlations between some parameters within both models. Such intercorrelations make it difficult to identify and interpret single parameters and can induce high degrees of shrinkage in hierarchical models. Similar findings may also occur in the context of other cognitive models of choice.
Hepatitis disease detection using Bayesian theory
Maseleno, Andino; Hidayati, Rohmah Zahroh
2017-02-01
This paper presents hepatitis disease diagnosis using a Bayesian theory for better understanding of the theory. In this research, we used a Bayesian theory for detecting hepatitis disease and displaying the result of diagnosis process. Bayesian algorithm theory is rediscovered and perfected by Laplace, the basic idea is using of the known prior probability and conditional probability density parameter, based on Bayes theorem to calculate the corresponding posterior probability, and then obtained the posterior probability to infer and make decisions. Bayesian methods combine existing knowledge, prior probabilities, with additional knowledge derived from new data, the likelihood function. The initial symptoms of hepatitis which include malaise, fever and headache. The probability of hepatitis given the presence of malaise, fever, and headache. The result revealed that a Bayesian theory has successfully identified the existence of hepatitis disease.
2nd Bayesian Young Statisticians Meeting
Bitto, Angela; Kastner, Gregor; Posekany, Alexandra
2015-01-01
The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Université Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session ...
BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.
Khakabimamaghani, Sahand; Ester, Martin
2016-01-01
The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data.
Energy Technology Data Exchange (ETDEWEB)
Gomes, Many R.S.; Melo, Paulo F.F.F. e, E-mail: mgomes@con.ufrj.br, E-mail: frutuoso@nuclear.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Programa de Pos-Graduacao em Engenharia Nuclear
2015-07-01
This work models by Bayesian networks the residual heat removal system (SRCR) of Angra I nuclear power plant, using fault tree mapping for systematically identifying all possible modes of occurrence caused by a large loss of coolant accident (large LOCA). The focus is on dependent events, such as the bridge system structure of the residual heat removal system and the occurrence of common-cause failures. We used the Netica™ tool kit, Norsys Software Corporation and Python 2.7.5 for modeling Bayesian networks and Microsoft Excel for modeling fault trees. Working with dependent events using Bayesian networks is similar to the solutions proposed by other models, beyond simple understanding and ease of application and modification throughout the analysis. The results obtained for the unavailability of the system were satisfactory, showing that in most cases the system will be available to mitigate the effects of an accident as described above. (author)
Wavelet-Bayesian inference of cosmic strings embedded in the cosmic microwave background
McEwen, J D; Peiris, H V; Wiaux, Y; Ringeval, C; Bouchet, F R
2016-01-01
Cosmic strings are a well-motivated extension to the standard cosmological model and could induce a subdominant component in the anisotropies of the cosmic microwave background (CMB), in addition to the standard inflationary component. The detection of strings, while observationally challenging, would provide a direct probe of physics at very high energy scales. We develop a new framework for cosmic string inference, constructing a Bayesian analysis in wavelet space where the string-induced CMB component has distinct statistical properties to the standard inflationary component. Our wavelet-Bayesian framework provides a principled approach to compute the posterior distribution of the string tension $G\\mu$ and the Bayesian evidence ratio comparing the string model to the standard inflationary model. Furthermore, we present a technique to recover an estimate of any string-induced CMB map embedded in observational data. Using Planck-like simulations we demonstrate the application of our framework and evaluate it...
Energy Technology Data Exchange (ETDEWEB)
Warabi, T.; Miyasaka, K.; Inoue, K.; Nakamura, N.
1987-09-01
A computed tomographic method for analyzing the shrinkage of the basis pedunculi (BP) due to the secondary degeneration of the descending fibers was applied in correlation to the site of cerebral lesions in 89 chronic hemiplegic patients. Cerebral lesions in the anterior corona radiata or the anterior limb of the capsula interna caused shrinkage of the medial BP. Lesions in the central corona radiata or the genu and posterior limb of the capsula interna caused shrinkage of the central BP, while lesions of the posterior corona radiata or the posterior limb of the capsula interna caused shrinkage of the lateral BP. These results suggested that CT images are able to reveal the principle sites of atrophy of the descending fiber tracts in chronic hemiplegia.
Directory of Open Access Journals (Sweden)
Hamid Kermanshah
2016-01-01
Conclusion: Silorane did not provide better marginal seal than the low shrinkage methacrylate-based composites (except Aelite. In addition, cyclic loading did not affect the marginal microleakage of evaluated composite restorations .
Sparse Bayesian Information Filters for Localization and Mapping
2008-02-01
nonlinear dataset to better understand their performance in practice . 3.4.1 Linear Gaussian Simulation In an effort to better understand the theoretical...T T ! { = ] = [• u i FAu ’=0-- axi+byi+cx + dy + e=O. Recalling our earlier discussion on multiple view geometry techniques in Sec- tion B.1, an
Bayesian multi-QTL mapping for growth curve parameters
DEFF Research Database (Denmark)
Heuven, Henri C M; Janss, Luc L G
2010-01-01
. The locations of the QTLs for separate parameters were very close in some cases and probably caused the genetic correlation observed between ASYM and XMID and SCAL respectively. None of the QTL appeared on chromosome five. Conclusions Repeated observations on individuals were affected by at least nine QTLs...
Water transfer properties and shrinkage in lime-based rendering mortars
Arizzi, A.; Cultrone, G.
2012-04-01
aspect to be considered in the evaluation of the decay caused by water is the high shrinkage suffered by renders when they are applied on an extended surface (i.e. a wall), especially when they are aerial lime-based mortars. The shrinkage causes the formation of fissures that become an easy way for water to entry and diffuse through the mortar pore system. This factor is rarely taken into consideration during the hydric assays performed in the laboratory, since mortar samples of 4x4x16 or 4x4x4 cm in size do not undergo to such degree of shrinkage. For this reason, we have also studied the shrinkage of these mortars and considered it in the final assessment of mortars hydric properties. The shrinkage was evaluated according to a non-standardized method, by means of a shrinkage-measuring device that measures the mortar dimensional variations over time. This measurement has shown that the highest the lime content the biggest the mortar shrinkage and, consequently, the strongest the decay due to water.
Ge, Honghao; Ren, Fengli; Li, Jun; Han, Xiujun; Xia, Mingxu; Li, Jianguo
2017-03-01
A four-phase dendritic model was developed to predict the macrosegregation, shrinkage cavity, and porosity during solidification. In this four-phase dendritic model, some important factors, including dendritic structure for equiaxed crystals, melt convection, crystals sedimentation, nucleation, growth, and shrinkage of solidified phases, were taken into consideration. Furthermore, in this four-phase dendritic model, a modified shrinkage criterion was established to predict shrinkage porosity (microporosity) of a 55-ton industrial Fe-3.3 wt pct C ingot. The predicted macrosegregation pattern and shrinkage cavity shape are in a good agreement with experimental results. The shrinkage cavity has a significant effect on the formation of positive segregation in hot top region, which generally forms during the last stage of ingot casting. The dendritic equiaxed grains also play an important role on the formation of A-segregation. A three-dimensional laminar structure of A-segregation in industrial ingot was, for the first time, predicted by using a 3D case simulation.
Evaluation of logistic Bayesian LASSO for identifying association with rare haplotypes.
Biswas, Swati; Papachristou, Charalampos
2014-01-01
It has been hypothesized that rare variants may hold the key to unraveling the genetic transmission mechanism of many common complex traits. Currently, there is a dearth of statistical methods that are powerful enough to detect association with rare haplotypes. One of the recently proposed methods is logistic Bayesian LASSO for case-control data. By penalizing the regression coefficients through appropriate priors, logistic Bayesian LASSO weeds out the unassociated haplotypes, making it possible for the associated rare haplotypes to be detected with higher powers. We used the Genetic Analysis Workshop 18 simulated data to evaluate the behavior of logistic Bayesian LASSO in terms of its power and type I error under a complex disease model. We obtained knowledge of the simulation model, including the locations of the functional variants, and we chose to focus on two genomic regions in the MAP4 gene on chromosome 3. The sample size was 142 individuals and there were 200 replicates. Despite the small sample size, logistic Bayesian LASSO showed high power to detect two haplotypes containing functional variants in these regions while maintaining low type I errors. At the same time, a commonly used approach for haplotype association implemented in the software hapassoc failed to converge because of the presence of rare haplotypes. Thus, we conclude that logistic Bayesian LASSO can play an important role in the search for rare haplotypes.
Quantum Bayesianism at the Perimeter
Fuchs, Christopher A
2010-01-01
The author summarizes the Quantum Bayesian viewpoint of quantum mechanics, developed originally by C. M. Caves, R. Schack, and himself. It is a view crucially dependent upon the tools of quantum information theory. Work at the Perimeter Institute for Theoretical Physics continues the development and is focused on the hard technical problem of a finding a good representation of quantum mechanics purely in terms of probabilities, without amplitudes or Hilbert-space operators. The best candidate representation involves a mysterious entity called a symmetric informationally complete quantum measurement. Contemplation of it gives a way of thinking of the Born Rule as an addition to the rules of probability theory, applicable when one gambles on the consequences of interactions with physical systems. The article ends by outlining some directions for future work.
On Bayesian System Reliability Analysis
Energy Technology Data Exchange (ETDEWEB)
Soerensen Ringi, M.
1995-05-01
The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person`s state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs.
Hedging Strategies for Bayesian Optimization
Brochu, Eric; de Freitas, Nando
2010-01-01
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It is able to do this by sampling the objective using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several different parameterized acquisition functions in the literature, and it is often unclear which one to use. Instead of using a single acquisition function, we adopt a portfolio of acquisition functions governed by an online multi-armed bandit strategy. We describe the method, which we call GP-Hedge, and show that this method almost always outperforms the best individual acquisition function.
Nonparametric Bayesian inference in biostatistics
Müller, Peter
2015-01-01
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...
Multiview Bayesian Correlated Component Analysis
DEFF Research Database (Denmark)
Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai
2015-01-01
Correlated component analysis as proposed by Dmochowski, Sajda, Dias, and Parra (2012) is a tool for investigating brain process similarity in the responses to multiple views of a given stimulus. Correlated components are identified under the assumption that the involved spatial networks are iden......Correlated component analysis as proposed by Dmochowski, Sajda, Dias, and Parra (2012) is a tool for investigating brain process similarity in the responses to multiple views of a given stimulus. Correlated components are identified under the assumption that the involved spatial networks...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....
Bayesian networks in educational assessment
Almond, Russell G; Steinberg, Linda S; Yan, Duanli; Williamson, David M
2015-01-01
Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as ...
Elvira, Clément; Dobigeon, Nicolas
2015-01-01
Sparse representations have proven their efficiency in solving a wide class of inverse problems encountered in signal and image processing. Conversely, enforcing the information to be spread uniformly over representation coefficients exhibits relevant properties in various applications such as digital communications. Anti-sparse regularization can be naturally expressed through an $\\ell_{\\infty}$-norm penalty. This paper derives a probabilistic formulation of such representations. A new probability distribution, referred to as the democratic prior, is first introduced. Its main properties as well as three random variate generators for this distribution are derived. Then this probability distribution is used as a prior to promote anti-sparsity in a Gaussian linear inverse problem, yielding a fully Bayesian formulation of anti-sparse coding. Two Markov chain Monte Carlo (MCMC) algorithms are proposed to generate samples according to the posterior distribution. The first one is a standard Gibbs sampler. The seco...
Bayesian Inference in Queueing Networks
Sutton, Charles
2010-01-01
Modern Web services, such as those at Google, Yahoo!, and Amazon, handle billions of requests per day on clusters of thousands of computers. Because these services operate under strict performance requirements, a statistical understanding of their performance is of great practical interest. Such services are modeled by networks of queues, where one queue models each of the individual computers in the system. A key challenge is that the data is incomplete, because recording detailed information about every request to a heavily used system can require unacceptable overhead. In this paper we develop a Bayesian perspective on queueing models in which the arrival and departure times that are not observed are treated as latent variables. Underlying this viewpoint is the observation that a queueing model defines a deterministic transformation between the data and a set of independent variables called the service times. With this viewpoint in hand, we sample from the posterior distribution over missing data and model...
A Bayesian Reflection on Surfaces
Directory of Open Access Journals (Sweden)
David R. Wolf
1999-10-01
Full Text Available Abstract: The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informative inference of continuous-basis fields, that is where the basis for the field is itself a continuous object and not representable in a finite manner; the tradeoff between accuracy of representation in terms of information learned, and memory or storage capacity in bits; the approximation of probability distributions so that a maximal amount of information about the object being inferred is preserved; an information theoretic justification for multigrid methodology. The maximally informative field inference framework is described in full generality and denoted the Generalized Kalman Filter. The Generalized Kalman Filter allows the update of field knowledge from previous knowledge at any scale, and new data, to new knowledge at any other scale. An application example instance, the inference of continuous surfaces from measurements (for example, camera image data, is presented.
Radiation dose reduction in computed tomography perfusion using spatial-temporal Bayesian methods
Fang, Ruogu; Raj, Ashish; Chen, Tsuhan; Sanelli, Pina C.
2012-03-01
In current computed tomography (CT) examinations, the associated X-ray radiation dose is of significant concern to patients and operators, especially CT perfusion (CTP) imaging that has higher radiation dose due to its cine scanning technique. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) parameter as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and degrade CT perfusion maps greatly if no adequate noise control is applied during image reconstruction. To capture the essential dynamics of CT perfusion, a simple spatial-temporal Bayesian method that uses a piecewise parametric model of the residual function is used, and then the model parameters are estimated from a Bayesian formulation of prior smoothness constraints on perfusion parameters. From the fitted residual function, reliable CTP parameter maps are obtained from low dose CT data. The merit of this scheme exists in the combination of analytical piecewise residual function with Bayesian framework using a simpler prior spatial constrain for CT perfusion application. On a dataset of 22 patients, this dynamic spatial-temporal Bayesian model yielded an increase in signal-tonoise-ratio (SNR) of 78% and a decrease in mean-square-error (MSE) of 40% at low dose radiation of 43mA.
Bayesian models a statistical primer for ecologists
Hobbs, N Thompson
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark
2006-01-01
We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available PRIMULA tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference...... by evaluating and differentiating these circuits in time linear in their size. We report on experimental results showing successful compilation and efficient inference on relational Bayesian networks, whose PRIMULA--generated propositional instances have thousands of variables, and whose jointrees have clusters...
The Diagnosis of Reciprocating Machinery by Bayesian Networks
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
A Bayesian Network is a reasoning tool based on probability theory and has many advantages that other reasoning tools do not have. This paper discusses the basic theory of Bayesian networks and studies the problems in constructing Bayesian networks. The paper also constructs a Bayesian diagnosis network of a reciprocating compressor. The example helps us to draw a conclusion that Bayesian diagnosis networks can diagnose reciprocating machinery effectively.
Guo, Wei; Jia, Kebin; Tian, Jie; Han, Dong; Liu, Xueyan; Wu, Ping; Feng, Jinchao; Yang, Xin
2012-03-01
Among many molecular imaging modalities, Bioluminescence tomography (BLT) is an important optical molecular imaging modality. Due to its unique advantages in specificity, sensitivity, cost-effectiveness and low background noise, BLT is widely studied for live small animal imaging. Since only the photon distribution over the surface is measurable and the photo propagation with biological tissue is highly diffusive, BLT is often an ill-posed problem and may bear multiple solutions and aberrant reconstruction in the presence of measurement noise and optical parameter mismatches. For many BLT practical applications, such as early detection of tumors, the volumes of the light sources are very small compared with the whole body. Therefore, the L1-norm sparsity regularization has been used to take advantage of the sparsity prior knowledge and alleviate the ill-posedness of the problem. Iterative shrinkage (IST) algorithm is an important research achievement in a field of compressed sensing and widely applied in sparse signal reconstruction. However, the convergence rate of IST algorithm depends heavily on the linear operator. When the problem is ill-posed, it becomes very slow. In this paper, we present a sparsity regularization reconstruction method for BLT based on the two-step iterated shrinkage approach. By employing Two-step strategy of iterative reweighted shrinkage (IRS) to improve IST, the proposed method shows faster convergence rate and better adaptability for BLT. The simulation experiments with mouse atlas were conducted to evaluate the performance of proposed method. By contrast, the proposed method can obtain the stable and comparable reconstruction solution with less number of iterations.
GPstuff: Bayesian Modeling with Gaussian Processes
Vanhatalo, J.; Riihimaki, J.; Hartikainen, J.; Jylänki, P.P.; Tolvanen, V.; Vehtari, A.
2013-01-01
The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for Bayesian inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods.
Bayesian Uncertainty Analyses Via Deterministic Model
Krzysztofowicz, R.
2001-05-01
Rational decision-making requires that the total uncertainty about a variate of interest (a predictand) be quantified in terms of a probability distribution, conditional on all available information and knowledge. Suppose the state-of-knowledge is embodied in a deterministic model, which is imperfect and outputs only an estimate of the predictand. Fundamentals are presented of three Bayesian approaches to producing a probability distribution of the predictand via any deterministic model. The Bayesian Processor of Output (BPO) quantifies the total uncertainty in terms of a posterior distribution, conditional on model output. The Bayesian Processor of Ensemble (BPE) quantifies the total uncertainty in terms of a posterior distribution, conditional on an ensemble of model output. The Bayesian Forecasting System (BFS) decomposes the total uncertainty into input uncertainty and model uncertainty, which are characterized independently and then integrated into a predictive distribution.
Picturing classical and quantum Bayesian inference
Coecke, Bob
2011-01-01
We introduce a graphical framework for Bayesian inference that is sufficiently general to accommodate not just the standard case but also recent proposals for a theory of quantum Bayesian inference wherein one considers density operators rather than probability distributions as representative of degrees of belief. The diagrammatic framework is stated in the graphical language of symmetric monoidal categories and of compact structures and Frobenius structures therein, in which Bayesian inversion boils down to transposition with respect to an appropriate compact structure. We characterize classical Bayesian inference in terms of a graphical property and demonstrate that our approach eliminates some purely conventional elements that appear in common representations thereof, such as whether degrees of belief are represented by probabilities or entropic quantities. We also introduce a quantum-like calculus wherein the Frobenius structure is noncommutative and show that it can accommodate Leifer's calculus of `cond...
Learning Bayesian networks for discrete data
Liang, Faming
2009-02-01
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.
An Intuitive Dashboard for Bayesian Network Inference
Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.
2014-03-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.
Predicting coastal cliff erosion using a Bayesian probabilistic model
Hapke, C.; Plant, N.
2010-01-01
Regional coastal cliff retreat is difficult to model due to the episodic nature of failures and the along-shore variability of retreat events. There is a growing demand, however, for predictive models that can be used to forecast areas vulnerable to coastal erosion hazards. Increasingly, probabilistic models are being employed that require data sets of high temporal density to define the joint probability density function that relates forcing variables (e.g. wave conditions) and initial conditions (e.g. cliff geometry) to erosion events. In this study we use a multi-parameter Bayesian network to investigate correlations between key variables that control and influence variations in cliff retreat processes. The network uses Bayesian statistical methods to estimate event probabilities using existing observations. Within this framework, we forecast the spatial distribution of cliff retreat along two stretches of cliffed coast in Southern California. The input parameters are the height and slope of the cliff, a descriptor of material strength based on the dominant cliff-forming lithology, and the long-term cliff erosion rate that represents prior behavior. The model is forced using predicted wave impact hours. Results demonstrate that the Bayesian approach is well-suited to the forward modeling of coastal cliff retreat, with the correct outcomes forecast in 70-90% of the modeled transects. The model also performs well in identifying specific locations of high cliff erosion, thus providing a foundation for hazard mapping. This approach can be employed to predict cliff erosion at time-scales ranging from storm events to the impacts of sea-level rise at the century-scale. ?? 2010.
Shrinkage in canned mushrooms treated with xanthan gum as a pre-blanch soak treatment
Gormley, T. R. (Thomas Ronan)
1986-01-01
Vacuum treating freshly harvested mushrooms with a 1 % xanthan gum solution (XVT)containing 0.25% sodium metabisulphite{SMBS) prior to blanching and canning gave a lower shrinkage value than for corresponding samples vacuum treated with water, or those canned by conventional means or the 3S process. A combination of chill storage (2-4°C) for 1-3 days coupled with 1 % XVT was found best and gave even lower total canning losses (chill storage loss+blanch loss+retort loss); these were6% lower th...
Optimal Process Design of Shrinkage and Sink Marks in Injection Molding
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The optimal process conditions of an injection molded polypropylenes dustpan were investigated to improve the part quality. A fractional factorial experiment was employed to screen the significant factors and main combinations among the numerous process parameters. And, with the consideration of interaction effects, an L27 orthogonal array based on the Taguchi method was conducted to determine the optimal process conditions. The results indicate that the melt temperature has the most remarkable influence on both the volume shrinkage and sink marks criterion weights. But the optimal process conditions and the order of influence are different for the two criterion weights.
Shrinkage of large isolated pores during hot isostatic pressing of presintered alumina ceramics
Energy Technology Data Exchange (ETDEWEB)
Oh, K.S.; Kim, D.Y. [Seoul National Univ. (Korea, Republic of). Dept. of Inorganic Materials Engineering; Cho, S.J. [Korea Research Inst. of Standards and Science, Taejon (Korea, Republic of)
1995-09-01
The shrinkage process of large pores during hot isostatic pressing (HIP) of presintered Al{sub 2}O{sub 3} and Al{sub 2}O{sub 3}-ZrO{sub 2} ceramics has been investigated. Large pores were observed to collapse by grain-boundary sliding, and then small pores resulting from the misfit of flowed grains disappeared, mainly by diffusion. Due to the high resistance to grain-boundary sliding, the pores in the Al{sub 2}O{sub 3}-ZrO{sub 2} ceramics were hard to eliminate.
ProFit: Bayesian galaxy fitting tool
Robotham, A. S. G.; Taranu, D.; Tobar, R.
2016-12-01
ProFit is a Bayesian galaxy fitting tool that uses the fast C++ image generation library libprofit (ascl:1612.003) and a flexible R interface to a large number of likelihood samplers. It offers a fully featured Bayesian interface to galaxy model fitting (also called profiling), using mostly the same standard inputs as other popular codes (e.g. GALFIT ascl:1104.010), but it is also able to use complex priors and a number of likelihoods.
Bayesian target tracking based on particle filter
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.
Variational Bayesian Approximation methods for inverse problems
Mohammad-Djafari, Ali
2012-09-01
Variational Bayesian Approximation (VBA) methods are recent tools for effective Bayesian computations. In this paper, these tools are used for inverse problems where the prior models include hidden variables and where where the estimation of the hyper parameters has also to be addressed. In particular two specific prior models (Student-t and mixture of Gaussian models) are considered and details of the algorithms are given.
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel
2010-01-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel; Bessière, Pierre
2011-03-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.