Search results for "Poster"
showing 10 items of 679 documents
EP 34. Functional hierarchy within the neural network for optokinetic ‘look’ nystagmus
2016
Item does not contain fulltext Key nodes of neural networks for ocular motor control and visual motion processing have been localized using saccades, smooth pursuit, and optokinetic nystagmus (OKN). Within the context of an independent fMRI study using OKN, 9 bilateral network nodes were localized comprising cortical eye fields in frontal (FEF), supplementary motor (SEF), cingulate (CEF) and parietal cortex (PEF), visual motion centers MT+ and V6, the superior colliculus (SC), the lateral geniculate nucleus (LGN) and the globus pallidus (GP). Here, we examined the network's functional hierarchy as present in the structural co-variation (SCoV) and resting-state (RS) fMRI, and the effect of R…
Outcomes of in-bag transvaginal extraction in a series of 692 laparoscopic myomectomies: results from a large retrospective analysis
2022
Transvaginal extraction is a feasible method to remove surgical specimen. In this study, we aim to report our experience with in-bag transvaginal specimen retrieval after laparoscopic myomectomy over the past 15 years.Single-center retrospective analysis.Academic hospital.Women who underwent laparoscopic myomectomy from January 2005 to April 2021.Posterior colpotomy and in-bag transvaginal extraction of the surgical specimen.We collected and analyzed data about patients' characteristics, main indication for surgery, and intra- and postoperative (within 30 days) complications.A total of 692 women underwent transvaginal specimen retrieval after laparoscopic myomectomy (mean largest myoma diam…
A Posteriori Error Bounds for Approximations of the Oseen Problem and Applications to the Uzawa Iteration Algorithm
2014
Abstract. We derive computable bounds of deviations from the exact solution of the stationary Oseen problem. They are applied to approximations generated by the Uzawa iteration method. Also, we derive an advanced form of the estimate, which takes into account approximation errors arising due to discretization of the boundary value problem, generated by the main step of the Uzawa method. Numerical tests confirm our theoretical results and show practical applicability of the estimates.
Perceptual adaptive insensitivity for support vector machine image coding.
2005
Support vector machine (SVM) learning has been recently proposed for image compression in the frequency domain using a constant epsilon-insensitivity zone by Robinson and Kecman. However, according to the statistical properties of natural images and the properties of human perception, a constant insensitivity makes sense in the spatial domain but it is certainly not a good option in a frequency domain. In fact, in their approach, they made a fixed low-pass assumption as the number of discrete cosine transform (DCT) coefficients to be used in the training was limited. This paper extends the work of Robinson and Kecman by proposing the use of adaptive insensitivity SVMs [2] for image coding u…
Bayesian inference in Markovian queues
1994
This paper is concerned with the Bayesian analysis of general queues with Poisson input and exponential service times. Joint posterior distribution of the arrival rate and the individual service rate is obtained from a sample consisting inn observations of the interarrival process andm complete service times. Posterior distribution of traffic intensity inM/M/c is also obtained and the statistical analysis of the ergodic condition from a decision point of view is discussed.
Adaptive Importance Sampling: The past, the present, and the future
2017
A fundamental problem in signal processing is the estimation of unknown parameters or functions from noisy observations. Important examples include localization of objects in wireless sensor networks [1] and the Internet of Things [2]; multiple source reconstruction from electroencephalograms [3]; estimation of power spectral density for speech enhancement [4]; or inference in genomic signal processing [5]. Within the Bayesian signal processing framework, these problems are addressed by constructing posterior probability distributions of the unknowns. The posteriors combine optimally all of the information about the unknowns in the observations with the information that is present in their …
A Bayesian unified framework for risk estimation and cluster identification in small area health data analysis.
2020
Many statistical models have been proposed to analyse small area disease data with the aim of describing spatial variation in disease risk. In this paper, we propose a Bayesian hierarchical model that simultaneously allows for risk estimation and cluster identification. Our model formulation assumes that there is an unknown number of risk classes and small areas are assigned to a risk class by means of independent allocation variables. Therefore, areas within each cluster are assumed to share a common risk but they may be geographically separated. The posterior distribution of the parameter representing the number of risk classes is estimated using a novel procedure that combines its prior …
Mesh-adaptive methods for viscous flow problem with rotation
2007
In this paper, new functional type a posteriori error estimates for the viscous flow problem with rotating term are presented. The estimates give guaranteed upper bounds of the energy norm of the error and provide reliable error indication. We describe the implementation of the adaptive finite element methods (AFEM) in the framework of the functional type estimates proposed. Computational properties of the estimates are investigated on series of numerical examples.
Spatial-temporal interactions in the human brain
2009
The review summarises current evidence on the cognitive mechanisms for the integration of spatial and temporal representations and of common brain structures to process the where and when of stimuli. Psychophysical experiments document the presence of spatially localised distortions of sub-second time intervals and suggest that visual events are timed by neural mechanisms that are spatially selective. On the other hand, experiments with supra-second intervals suggest that time could be represented on a mental time-line ordered from left-to-right, similar to what is reported for other ordered quantities, such as numbers. Neuroimaging and neuropsychological findings point towards the posterio…