Search results for "CONTRAST"

How to reach optimal estimates of confidence intervals in microscopic counting of phytoplankton?

2021

Abstract Present practices in the microscopic counting of phytoplankton to estimate the reliability of results rely on the assumption of a random distribution of taxa in sample preparations. In contrast to that and in agreement with the literature, we show that aggregated distribution is common and can lead to over-optimistic confidence intervals, if estimated according to the shortcut procedure of Lund et al. based on the number of counted cells. We found a good linear correlation between the distribution independent confidence intervals for medians and those for parametric statistics so that 95% confidence intervals can be approximated by using a correction factor of 1.4. Instead, the rec…

Colour and luminance contrasts predict the human detection of natural stimuli in complex visual environments.

2017

Much of what we know about human colour perception has come from psychophysical studies conducted in tightly-controlled laboratory settings. An enduring challenge, however, lies in extrapolating this knowledge to the noisy conditions that characterize our actual visual experience. Here we combine statistical models of visual perception with empirical data to explore how chromatic (hue/saturation) and achromatic (luminant) information underpins the detection and classification of stimuli in a complex forest environment. The data best support a simple linear model of stimulus detection as an additive function of both luminance and saturation contrast. The strength of each predictor is modest …

Optimizing MRI contrast with B1 pulses using optimal control theory

2016

The variety of achievable contrasts by MRI makes it a highly flexible and valuable diagnostic tool. Contrast results from relaxation time differences, which are intrinsic properties of each tissue. Using optimal control theory, one can control the obtained contrast by applying excitation pulses that bring the magnetization in a user-defined target state. Simulation results are presented to illustrate the feasibility and the flexibility of using optimal contrast pulses. The robustness to experimental variable parameters such as field inhomogeneities is also studied. Finally, an in-vitro contrast experiment is performed on a small-animal MRI showing a reasonable match with the simulation resu…

Assembly Assistance System with Decision Trees and Ensemble Learning

2021

This paper presents different prediction methods based on decision tree and ensemble learning to suggest possible next assembly steps. The predictor is designed to be a component of a sensor-based assembly assistance system whose goal is to provide support via adaptive instructions, considering the assembly progress and, in the future, the estimation of user emotions during training. The assembly assistance station supports inexperienced manufacturing workers, but it can be useful in assisting experienced workers, too. The proposed predictors are evaluated on the data collected in experiments involving both trainees and manufacturing workers, as well as on a mixed dataset, and are compared …

George-Veeramani Fuzzy Metrics Revised

2018

In this note, we present an alternative approach to the concept of a fuzzy metric, calling it a revised fuzzy metric. In contrast to the traditional approach to the theory of fuzzy metric spaces which is based on the use of a t-norm, we proceed from a t-conorm in the definition of a revised fuzzy metric. Here, we restrict our study to the case of fuzzy metrics as they are defined by George-Veeramani, however, similar revision can be done also for some other approaches to the concept of a fuzzy metric.

Assembly Process Modeling Through Long Short-Term Memory

2021

This paper studies Long Short-Term Memory as a component of an adaptive assembly assistance system suggesting the next manufacturing step. The final goal is an assistive system able to help the inexperienced workers in their training stage or even experienced workers who prefer such support in their manufacturing activity. In contrast with the earlier analyzed context-based techniques, Long Short-Term Memory can be applied in unknown scenarios. The evaluation was performed on the data collected previously in an experiment with 68 participants assembling as target product a customizable modular tablet. We are interested in identifying the most accurate method of next assembly step prediction…

First muography of Stromboli volcano

2019

AbstractMuography consists in observing the differential absorption of muons – elementary particles produced through cosmic-ray interactions in the Earth atmosphere – going through the volcano and can attain a spatial resolution of tens of meters. We present here the first experiment of nuclear emulsion muography at the Stromboli volcano. Muons have been recorded during a period of five months by a detector of 0.96 m2 area. The emulsion films were prepared at the Gran Sasso underground laboratory and were analyzed at Napoli, Salerno and Tokyo scanning laboratories. Our results highlight a significant low-density zone at the summit of the volcano with density contrast of 30–40% with respect …

Harnessing the potential of noninvasive in vivo preclinical imaging of the immune system: challenges and prospects.

2016

Preclinical imaging has become a powerful method for investigation of in vivo processes such as pharmacokinetics of therapeutic substances and visualization of physiologic and pathophysiological mechanisms. These are important aspects to understand diseases and develop strategies to modify their progression with pharmacologic interventions. One promising intervention is the application of specifically tailored nanoscale particles that modulate the immune system to generate a tumor targeting immune response. In this complex interaction between immunomodulatory therapies, the immune system and malignant disease, imaging methods are expected to play a key role on the way to generate new thera…

2020

Background Small sample sizes combined with multiple correlated endpoints pose a major challenge in the statistical analysis of preclinical neurotrauma studies. The standard approach of applying univariate tests on individual response variables has the advantage of simplicity of interpretation, but it fails to account for the covariance/correlation in the data. In contrast, multivariate statistical techniques might more adequately capture the multi-dimensional pathophysiological pattern of neurotrauma and therefore provide increased sensitivity to detect treatment effects. Results We systematically evaluated the performance of univariate ANOVA, Welch’s ANOVA and linear mixed effects models …

Ultra-Fast Detection of Higher-Order Epistatic Interactions on GPUs

2017

Detecting higher-order epistatic interactions in Genome-Wide Association Studies (GWAS) remains a challenging task in the fields of genetic epidemiology and computer science. A number of algorithms have recently been proposed for epistasis discovery. However, they suffer from a high computational cost since statistical measures have to be evaluated for each possible combination of markers. Hence, many algorithms use additional filtering stages discarding potentially non-interacting markers in order to reduce the overall number of combinations to be examined. Among others, Mutual Information Clustering (MIC) is a common pre-processing filter for grouping markers into partitions using K-Means…