Search results for "Poster"

Visual aftereffects and sensory nonlinearities from a single statistical framework

2015

When adapted to a particular scenery our senses may fool us: colors are misinterpreted, certain spatial patterns seem to fade out, and static objects appear to move in reverse. A mere empirical description of the mechanisms tuned to color, texture, and motion may tell us where these visual illusions come from. However, such empirical models of gain control do not explain why these mechanisms work in this apparently dysfunctional manner. Current normative explanations of aftereffects based on scene statistics derive gain changes by (1) invoking decorrelation and linear manifold matching/equalization, or (2) using nonlinear divisive normalization obtained from parametric scene models. These p…

Quantized ATDHF: theory and realistic applications to heavy ion fusion

1982

The quantized ATDHF theory is reviewed and discussed in the context of the generator coordinate method. This allows for a derivation which does not require an a posteriori quantization process. The ATDHF equations are then solved numerically on a coordinate and momentum grid in fully three dimensional geometry. The theory is applied to various heavy ion systems, where potentials, mass parameters and quantum corrections are evaluated and compared to conventional results from constrained Hartree-Fock. Subbarrier fusion cross sections are calculated and compared with experiment.

A posteriori error estimates for a Maxwell type problem

2009

In this paper, we discuss a posteriori estimates for the Maxwell type boundary-value problem. The estimates are derived by transformations of integral identities that define the generalized solution and are valid for any conforming approximation of the exact solution. It is proved analytically and confirmed numerically that the estimates indeed provide a computable and guaranteed bound of approximation errors. Also, it is shown that the estimates imply robust error indicators that represent the distribution of local (inter-element) errors measured in terms of different norms. peerReviewed

Object Migration Automata for Non-equal Partitioning Problems with Known Partition Sizes

2021

Part 4: Automated Machine Learning; International audience; Solving partitioning problems in random environments is a classic and challenging task, and has numerous applications. The existing Object Migration Automaton (OMA) and its proposed enhancements, which include the Pursuit and Transitivity phenomena, can solve problems with equi-sized partitions. Currently, these solutions also include one where the partition sizes possess a Greatest Common Divisor (GCD). In this paper, we propose an OMA-based solution that can solve problems with both equally and non-equally-sized groups, without restrictions on their sizes. More specifically, our proposed approach, referred to as the Partition Siz…

Landmark identification on direct digital versus film-based cephalometric radiographs: A human skull study

2002

The purpose of this study was to investigate differences in landmark identification on vertically scanned, direct digital and conventional (18 x 24 cm) cephalometric radiographs. Eight observers, all orthodontists or postgraduate orthodontic students, recorded 6 landmarks twice on 3 digital and 3 conventional cephalograms obtained from 3 human skulls in a standardized fashion. Digital images were displayed on a 15.1-in TFT monitor in 3:1 mode (20 x 26 cm). Recordings were transferred into standardized coordinate systems and evaluated separately for each coordinate. After correcting for magnification, precision was assessed with Maloney-Rastogi tests, and intraobserver and interobserver repr…

P03.04 Signaling questions assessing brain tumor patients’ distress in clinical routine - a feasibility study

2019

Abstract BACKGROUND Approximately 20%-35% of patients with intracranial tumors show depressive symptoms and distress. Assessment in these patients remains challenging due to cognitive and/or neurological deficits. We developed 3 signaling questions in order to assess patients during patient-doctor consultation. The aim is to implement them in clinical routine and to compare the results with patient reported outcome measures (PROMs) along disease trajectory. MATERIAL AND METHODS Patients were prospectively examined in a structured interview applying the 3 following questions: 1),Has your mood worsened? (I)”; 2),Are you strained by physical changes? (II)”; 3),Has your faculty of thought decre…

Vemurafenib and cobimetinib combination therapy for BRAFV600E-mutated melanoma favors posterior reversible encephalopathy syndrome

2019

An Ordinal Joint Model for Breast Cancer

2017

We propose a Bayesian joint model to analyze the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model and the time-to-event process through a left-truncated Cox proportional hazards model with information of the longitudinal marker and baseline covariates. Both longitudinal and survival processes are connected by a common vector of random effects.

Análisis de la capa de fibras nerviosas usando el GDx en pacientes pseudofáquicos con opacificación capsular posterior

2008

Adaptive design optimization: a mutual information-based approach to model discrimination in cognitive science.

2010

Discriminating among competing statistical models is a pressing issue for many experimentalists in the field of cognitive science. Resolving this issue begins with designing maximally informative experiments. To this end, the problem to be solved in adaptive design optimization is identifying experimental designs under which one can infer the underlying model in the fewest possible steps. When the models under consideration are nonlinear, as is often the case in cognitive science, this problem can be impossible to solve analytically without simplifying assumptions. However, as we show in this letter, a full solution can be found numerically with the help of a Bayesian computational trick d…