scholarly journals Visualization of Flooding Using Adaptive Spatial Resolution

2019 ◽  
Vol 8 (5) ◽  
pp. 204 ◽  
Author(s):  
I. Alihan Hadimlioglu ◽  
Scott A. King
Keyword(s):  
Particle Interaction ◽  
Adaptive Grids ◽  
Heat Map ◽  
Dynamic Representation ◽  
Precise Evaluation ◽  
Grid Approach ◽  
Computationally Expensive ◽  
Flood Simulations ◽  
Insight Into ◽  
Adaptive Spatial Resolution

Flood simulations are vital to gain insight into possible dangers and damages for effective emergency planning. With flexible and natural ways of visualizing water flow, more precise evaluation of the study area is achieved. In this study, we describe a method for flood visualization using both regular and adaptive grids for position-based fluids method to visualize the depth of water in the study area. The mapping engine utilizes adaptive cell sizes to represent the study area and utilizes Jenks natural breaks method to classify the data. Predefined single-hue and multi-hue color sets are used to generate a heat map of the study area. It is shown that the dynamic representation benefits the mapping engine through enhanced precision when the study area has non-disperse clusters. Moreover, it is shown that, through decreasing precision, and utilizing an adaptive grid approach, the simulation runs more efficiently when particle interaction is computationally expensive.

SPIKING NEURAL NETWORKS

2009 ◽  
Vol 19 (04) ◽  
pp. 295-308 ◽  
Author(s):  
SAMANWOY GHOSH-DASTIDAR ◽  
HOJJAT ADELI
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Information Transfer ◽  
Spiking Neurons ◽  
Spiking Neural Networks ◽  
Classification Problems ◽  
Temporal Dimension ◽  
Information Encoding ◽  
Dynamic Representation ◽  
Insight Into

Most current Artificial Neural Network (ANN) models are based on highly simplified brain dynamics. They have been used as powerful computational tools to solve complex pattern recognition, function estimation, and classification problems. ANNs have been evolving towards more powerful and more biologically realistic models. In the past decade, Spiking Neural Networks (SNNs) have been developed which comprise of spiking neurons. Information transfer in these neurons mimics the information transfer in biological neurons, i.e., via the precise timing of spikes or a sequence of spikes. To facilitate learning in such networks, new learning algorithms based on varying degrees of biological plausibility have also been developed recently. Addition of the temporal dimension for information encoding in SNNs yields new insight into the dynamics of the human brain and could result in compact representations of large neural networks. As such, SNNs have great potential for solving complicated time-dependent pattern recognition problems because of their inherent dynamic representation. This article presents a state-of-the-art review of the development of spiking neurons and SNNs, and provides insight into their evolution as the third generation neural networks.

scholarly journals Bayesian confidence for drift diffusion observers in dynamic stimuli tasks

2020 ◽  
Author(s):  
Joshua Calder-Travis ◽  
Rafal Bogacz ◽  
Nick Yeung
Keyword(s):  
Diffusion Model ◽  
Drift Rate ◽  
Response Times ◽  
Time Dependent ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Dynamic Stimuli ◽  
Computationally Expensive ◽  
Insight Into ◽  
Confidence Data

AbstractMuch work has explored the possibility that the drift diffusion model, a model of response times and choices, could be extended to account for confidence reports. Many methods for making predictions from such models exist, although these methods either assume that stimuli are static over the course of a trial, or are computationally expensive, making it difficult to capitalise on trial-by-trial variability in dynamic stimuli. Using the framework of the drift diffusion model with time-dependent thresholds, and the idea of a Bayesian confidence readout, we derive expressions for the probability distribution over confidence reports. In line with current models of confidence, the derivations allow for the accumulation of “pipeline” evidence which has been received but not processed by the time of response, the effect of drift rate variability, and metacognitive noise. The expressions are valid for stimuli which change over the course of a trial with normally distributed fluctuations in the evidence they provide. A number of approximations are made to arrive at the final expressions, and we test all approximations via simulation. The derived expressions only contain a small number of standard functions, and only require evaluating once per trial, making trial-by-trial modelling of confidence data in dynamic stimuli tasks more feasible. We conclude by using the expressions to gain insight into the confidence of optimal observers, and empirically observed patterns.

scholarly journals Adsorption of dye molecules on metallic nanoparticles: Unraveling the origins of the modified spectral absorption

2021 ◽  
Author(s):  
◽  
Xiaohan Chen
Keyword(s):  
Metallic Nanoparticles ◽  
Particle Interaction ◽  
Metallic Nanoparticle ◽  
Surface Absorption ◽  
High Coverage ◽  
Silver Colloids ◽  
Chemical Effects ◽  
Surface Enhanced ◽  
Low Coverage ◽  
Insight Into

<p>The enhanced optical response of molecules in the vicinity of metallic nanoparticle is the basis for many surface enhanced spectroscopies and of interest to the field of plasmonics. However, the mechanisms behind the enhancement are still a matter of debate because of the interplay between electromagnetic and chemical effects, which complicates the interpretation of spectral changes. Our ability to measure the surface absorption of dyes from very low coverage to high coverage allows us to identify the con- tribution of each effect (dye-dye interaction and dye-particle interaction) to the spectral modifications. In the course of this investigation, we also measured the adsorption isotherms of dyes in the presence of halide ions, which provides a detailed insight into the adsorption process on silver colloids.</p>

X-Ray Scattering Studies of Expanded Fluid Metals

2021 ◽  
pp. 183-217
Author(s):  
Kazuhiro Matsuda ◽  
Masanori Inui
Keyword(s):  
Particle Interaction ◽  
State Dependence ◽  
X Ray ◽  
X Ray Scattering ◽  
Electrons And Ions ◽  
Structural And Electronic Properties ◽  
Thermodynamic Conditions ◽  
Insight Into ◽  
Conducting Fluids ◽  
Ray Scattering

Fluid metals exhibit significant properties of thermodynamic-state dependence, since the inter-particle interaction among the constituents (electrons and ions) considerably changes depending on their thermodynamic conditions. The authors have thus far carried out X-ray scattering experiments of fluid metals in the expanded state, which have enabled them to gain insight into microscopic understanding of the structural and electronic properties of fluid metals. The purpose of this chapter is to provide intriguing aspects of fluid metals originated from the existence of conduction electrons, which distinguishes fluid metals from non-conducting fluids, through the results of fluid rubidium and mercury.

A complementary modelling approach to manage uncertainty of computationally expensive models

2007 ◽  
Vol 56 (8) ◽  
pp. 1-9 ◽  
Author(s):  
Z. Vojinovic
Keyword(s):  
Support Vector ◽  
Model Parameters ◽  
Machine Model ◽  
Systematic Analysis ◽  
Physically Based Model ◽  
Physically Based ◽  
Computationally Expensive ◽  
Estimation Of Model Parameters ◽  
Insight Into ◽  
Modelling Approach

The fact that the models applied in the ‘water domain’ are far from reality can be attributed to many reasons. In this context, a systematic analysis of uncertainties reflected by the model error can provide insight into the level of confidence in the model results and how to approach estimation of optimal model parameters. This paper discusses the four commonly used approaches for estimation of model parameters and suggests that an alternative complementary modelling approach should be considered in cases where the traditional model calibration gives limited results and particularly in cases where the computationally expensive models are concerned. It treats uncertainty as modelling the total discrepancy between the model and physical process. The proposed approach combines the results from a physically-based model and Support Vector Machine model into the final solution.

X-Ray Scattering Studies of Expanded Fluid Metals

2017 ◽  
pp. 102-134
Author(s):  
Kazuhiro Matsuda ◽  
Masanori Inui
Keyword(s):  
Particle Interaction ◽  
State Dependence ◽  
X Ray ◽  
X Ray Scattering ◽  
Electrons And Ions ◽  
Structural And Electronic Properties ◽  
Thermodynamic Conditions ◽  
Insight Into ◽  
Conducting Fluids ◽  
Ray Scattering

Fluid metals exhibit significant properties of thermodynamic-state dependence, since the inter-particle interaction among the constituents (electrons and ions) considerably changes depending on their thermodynamic conditions. The authors have thus far carried out X-ray scattering experiments of fluid metals in the expanded state, which have enabled us to gain insight into microscopic understanding of the structural and electronic properties of fluid metals. The purpose of this chapter is to provide intriguing aspects of fluid metals originated from the existence of conduction electrons, which distinguishes fluid metals from non-conducting fluids, through the results of fluid rubidium and mercury.

scholarly journals Adsorption of dye molecules on metallic nanoparticles: Unraveling the origins of the modified spectral absorption

2021 ◽  
Author(s):  
◽  
Xiaohan Chen
Keyword(s):  
Metallic Nanoparticles ◽  
Particle Interaction ◽  
Metallic Nanoparticle ◽  
Surface Absorption ◽  
High Coverage ◽  
Silver Colloids ◽  
Chemical Effects ◽  
Surface Enhanced ◽  
Low Coverage ◽  
Insight Into

<p>The enhanced optical response of molecules in the vicinity of metallic nanoparticle is the basis for many surface enhanced spectroscopies and of interest to the field of plasmonics. However, the mechanisms behind the enhancement are still a matter of debate because of the interplay between electromagnetic and chemical effects, which complicates the interpretation of spectral changes. Our ability to measure the surface absorption of dyes from very low coverage to high coverage allows us to identify the con- tribution of each effect (dye-dye interaction and dye-particle interaction) to the spectral modifications. In the course of this investigation, we also measured the adsorption isotherms of dyes in the presence of halide ions, which provides a detailed insight into the adsorption process on silver colloids.</p>

Modelling retinal pulsatile blood flow from video data

2016 ◽  
Vol 27 (5) ◽  
pp. 1575-1584 ◽  
Author(s):  
Brigid Betz-Stablein ◽  
Martin L Hazelton ◽  
William H Morgan
Keyword(s):  
Blood Flow ◽  
Video Sequence ◽  
Retinal Vessel ◽  
Statistical Modelling ◽  
Video Data ◽  
Heat Map ◽  
Video Images ◽  
Harmonic Regression ◽  
Analyse Data ◽  
Insight Into

Modern day datasets continue to increase in both size and diversity. One example of such ‘big data’ is video data. Within the medical arena, more disciplines are using video as a diagnostic tool. Given the large amount of data stored within a video image, it is one of most time consuming types of data to process and analyse. Therefore, it is desirable to have automated techniques to extract, process and analyse data from video images. While many methods have been developed for extracting and processing video data, statistical modelling to analyse the outputted data has rarely been employed. We develop a method to take a video sequence of periodic nature, extract the RGB data and model the changes occurring across the contiguous images. We employ harmonic regression to model periodicity with autoregressive terms accounting for the error process associated with the time series nature of the data. A linear spline is included to account for movement between frames. We apply this model to video sequences of retinal vessel pulsation, which is the pulsatile component of blood flow. Slope and amplitude are calculated for the curves generated from the application of the harmonic model, providing clinical insight into the location of obstruction within the retinal vessels. The method can be applied to individual vessels, or to smaller segments such as 2 × 2 pixels which can then be interpreted easily as a heat map.

Calibration problems in hydrogen luminosities

1966 ◽  
Vol 24 ◽  
pp. 322-330
Author(s):  
A. Beer
Keyword(s):  
Galactic Structure ◽  
B Stars ◽  
Insight Into

The investigations which I should like to summarize in this paper concern recent photo-electric luminosity determinations of O and B stars. Their final aim has been the derivation of new stellar distances, and some insight into certain patterns of galactic structure.

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