scholarly journals A Hierarchical Bayesian Implementation of the Experience-Weighted Attraction Model

2020 ◽  
Vol 4 ◽  
pp. 40-60
Author(s):  
Zhihao Zhang ◽  
Saksham Chandra ◽  
Andrew Kayser ◽  
Ming Hsu ◽  
Joshua L. Warren
Keyword(s):  
Disease Progression ◽  
Computational Models ◽  
Behavioral Science ◽  
Estimation Methods ◽  
Hierarchical Bayesian ◽  
Strategic Learning ◽  
Unified Framework ◽  
Flexible Tool ◽  
Wide Range ◽  
Bayesian Implementation

Social and decision-making deficits are often the first symptoms of neuropsychiatric disorders. In recent years, economic games, together with computational models of strategic learning, have been increasingly applied to the characterization of individual differences in social behavior, as well as their changes across time due to disease progression, treatment, or other factors. At the same time, the high dimensionality of these data poses an important challenge to statistical estimation of these models, potentially limiting the adoption of such approaches in patients and special populations. We introduce a hierarchical Bayesian implementation of a class of strategic learning models, experience-weighted attraction (EWA), that is widely used in behavioral game theory. Importantly, this approach provides a unified framework for capturing between- and within-participant variation, including changes associated with disease progression, comorbidity, and treatment status. We show using simulated data that our hierarchical Bayesian approach outperforms representative agent and individual-level estimation methods that are commonly used in extant literature, with respect to parameter estimation and uncertainty quantification. Furthermore, using an empirical dataset, we demonstrate the value of our approach over competing methods with respect to balancing model fit and complexity. Consistent with the success of hierarchical Bayesian approaches in other areas of behavioral science, our hierarchical Bayesian EWA model represents a powerful and flexible tool to apply to a wide range of behavioral paradigms for studying the interplay between complex human behavior and biological factors.

An efficient approach to converting three-dimensional image data into highly accurate computational models

2008 ◽  
Vol 366 (1878) ◽  
pp. 3155-3173 ◽  
Author(s):  
P.G Young ◽  
T.B.H Beresford-West ◽  
S.R.L Coward ◽  
B Notarberardino ◽  
B Walker ◽  
...  
Keyword(s):  
Mesh Generation ◽  
Computational Models ◽  
Three Dimensional ◽  
Image Data ◽  
Model Material ◽  
Imaging Data ◽  
Material Inhomogeneity ◽  
Dimensional Image ◽  
Wide Range ◽  
Impact Modelling

Image-based meshing is opening up exciting new possibilities for the application of computational continuum mechanics methods (finite-element and computational fluid dynamics) to a wide range of biomechanical and biomedical problems that were previously intractable owing to the difficulty in obtaining suitably realistic models. Innovative surface and volume mesh generation techniques have recently been developed, which convert three-dimensional imaging data, as obtained from magnetic resonance imaging, computed tomography, micro-CT and ultrasound, for example, directly into meshes suitable for use in physics-based simulations. These techniques have several key advantages, including the ability to robustly generate meshes for topologies of arbitrary complexity (such as bioscaffolds or composite micro-architectures) and with any number of constituent materials (multi-part modelling), providing meshes in which the geometric accuracy of mesh domains is only dependent on the image accuracy (image-based accuracy) and the ability for certain problems to model material inhomogeneity by assigning the properties based on image signal strength. Commonly used mesh generation techniques will be compared with the proposed enhanced volumetric marching cubes (EVoMaCs) approach and some issues specific to simulations based on three-dimensional image data will be discussed. A number of case studies will be presented to illustrate how these techniques can be used effectively across a wide range of problems from characterization of micro-scaffolds through to head impact modelling.

scholarly journals Cycle and flow trusses in directed networks

2016 ◽  
Vol 3 (11) ◽  
pp. 160270 ◽  
Author(s):  
Taro Takaguchi ◽  
Yuichi Yoshida
Keyword(s):  
Truss Structures ◽  
Directed Network ◽  
Unified Framework ◽  
Directed Networks ◽  
Research Fields ◽  
Wide Range ◽  
Definition Of ◽  
Information Finding ◽  
Empirical Networks ◽  
Module Structures

When we represent real-world systems as networks, the directions of links often convey valuable information. Finding module structures that respect link directions is one of the most important tasks for analysing directed networks. Although many notions of a directed module have been proposed, no consensus has been reached. This lack of consensus results partly because there might exist distinct types of modules in a single directed network, whereas most previous studies focused on an independent criterion for modules. To address this issue, we propose a generic notion of the so-called truss structures in directed networks. Our definition of truss is able to extract two distinct types of trusses, named the cycle truss and the flow truss, from a unified framework. By applying the method for finding trusses to empirical networks obtained from a wide range of research fields, we find that most real networks contain both cycle and flow trusses. In addition, the abundance of (and the overlap between) the two types of trusses may be useful to characterize module structures in a wide variety of empirical networks. Our findings shed light on the importance of simultaneously considering different types of modules in directed networks.

Constrained Minimum Discrimination Information: A Unifying Tool for Modeling Spatial and Individual Choice Behavior

1982 ◽  
Vol 14 (10) ◽  
pp. 1341-1354 ◽  
Author(s):  
K E Haynes ◽  
F Y Phillips
Keyword(s):  
Choice Behavior ◽  
Applied Research ◽  
Probabilistic Models ◽  
Estimation Methods ◽  
Regression Estimation ◽  
Individual Choice ◽  
Wide Range ◽  
Alternative Hypotheses ◽  
Discrimination Information ◽  
Minimum Discrimination Information

Mathematical programming and statistical inference are combined in a constrained minimum discrimination information (MDI) method to provide a basis for a wide range of spatial and individual choice behavior problems. This approach offers an alternative to linear and loglinear regression estimation methods as well as probabilistic models of the logit and probit variety. Some logical and computational difficulties inherent in these approaches are resolved. Further, the approach leads endogenously to alternative hypotheses if the null hypothesis is rejected, and hence has implications for the interaction between research that is oriented toward theory construction and applied research that is empirically oriented.

The attachment length in orificed hollow cathodes

2021 ◽  
Author(s):  
Christopher Wordingham ◽  
Pierre-Yves Taunay ◽  
Edgar Choueiri
Keyword(s):  
Electron Temperature ◽  
Plasma Density ◽  
Hollow Cathode ◽  
Computational Models ◽  
Closed Form Solution ◽  
Form Solution ◽  
Decay Length ◽  
Plasma Density Profile ◽  
Wide Range ◽  
Approximate Boundary Condition

Abstract A first-principles approach to obtain the attachment length within a hollow cathode with a constrictive orifice, and its scaling with internal cathode pressure, is developed. This parameter, defined herein as the plasma density decay length scale upstream of (away from) the cathode orifice, is critical because it controls the utilization of the hollow cathode insert and influences cathode life. A two-dimensional framework is developed from the ambipolar diffusion equation for the insert-region plasma. A closed-form solution for the plasma density is obtained using standard partial differential equation techniques by applying an approximate boundary condition at the cathode orifice plane. This approach also yields the attachment length and electron temperature without reliance on measured plasma property data or complex computational models. The predicted plasma density profile is validated against measurements from the NSTAR discharge cathode, and calculated electron temperatures and attachment lengths agree with published values. Nondimensionalization of the governing equations reveals that the solution depends almost exclusively on the neutral pressure-diameter product in the insert plasma region. Evaluation of analytical results over a wide range of input parameters yields scaling relations for the variation of the attachment length and electron temperature with the pressure-diameter product. For the range of orifice-to-insert diameter ratio studied, the influence of orifice size is shown to be small except through its effect on insert pressure, and the attachment length is shown to be proportional to the insert inner radius, suggesting high-pressure cathodes should be constructed with larger-diameter inserts.

scholarly journals A Hierarchical Bayesian Approach to Ecological Count Data: A Flexible Tool for Ecologists

PLoS ONE ◽  
2011 ◽  
Vol 6 (11) ◽  
pp. e26785 ◽  
Author(s):  
James A. Fordyce ◽  
Zachariah Gompert ◽  
Matthew L. Forister ◽  
Chris C. Nice
Keyword(s):  
Bayesian Approach ◽  
Count Data ◽  
Hierarchical Bayesian ◽  
Flexible Tool

Hierarchical Bayesian Parameter Estimation for Modeling and Analysis of User Affective Influence

2013 ◽  
Author(s):  
Feng Zhou ◽  
Jianxin (Roger) Jiao
Keyword(s):  
Decision Making ◽  
Interior Design ◽  
Computational Models ◽  
Human Perception ◽  
Model Parameters ◽  
Hierarchical Bayesian ◽  
Affective States ◽  
Modeling And Analysis ◽  
Human Decision

Traditional user experience (UX) models are mostly qualitative in terms of its measurement and structure. This paper proposes a quantitative UX model based on cumulative prospect theory. It takes a decision making perspective between two alternative design profiles. However, affective elements are well-known to have influence on human decision making, the prevailing computational models for analyzing and simulating human perception on UX are mainly cognition-based models. In order to incorporate both affective and cognitive factors in the decision making process, we manipulate the parameters involved in the cumulative prospect model to show the affective influence. Specifically, three different affective states are induced to shape the model parameters. A hierarchical Bayesian model with a technique called Markov chain Monte Carlo is used to estimate the parameters. A case study of aircraft cabin interior design is illustrated to show the proposed methodology.

scholarly journals Translating surveillance data into incidence estimates

2018 ◽  
Author(s):  
Yoann Bourhis ◽  
Timothy R. Gottwald ◽  
Frank van den Bosch
Keyword(s):  
Disease Incidence ◽  
Surveillance Data ◽  
Estimation Methods ◽  
Full Model ◽  
Estimation Model ◽  
Sampling Series ◽  
Wide Range ◽  
Incidence Estimation

AbstractMonitoring a population for a disease requires the hosts to be sampled and tested for the pathogen. This results in sampling series from which to estimate the disease incidence,i.e. the proportion of hosts infected. Existing estimation methods assume that disease incidence is not changing between monitoring rounds, resulting in underestimation of the disease incidence. In this paper we develop an incidence estimation model accounting for epidemic growth with monitoring rounds sampling varying incidence. We also show how to accommodate the asymptomatic period characteristic to most diseases. For practical use, we produce an approximation of the model, which is subsequently shown accurate for relevant epidemic and sampling parameters. Both the approximation and the full model are applied to stochastic spatial simulations of epidemics. The results prove their consistency for a very wide range of situations.

scholarly journals A hierarchical Bayesian framework for force field selection in molecular dynamics simulations

2016 ◽  
Vol 374 (2060) ◽  
pp. 20150032 ◽  
Author(s):  
S. Wu ◽  
P. Angelikopoulos ◽  
C. Papadimitriou ◽  
R. Moser ◽  
P. Koumoutsakos
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Force Field ◽  
Computational Cost ◽  
Md Simulations ◽  
Bayesian Framework ◽  
Underlying Structure ◽  
Hierarchical Bayesian ◽  
Wide Range ◽  
Selection Of

We present a hierarchical Bayesian framework for the selection of force fields in molecular dynamics (MD) simulations. The framework associates the variability of the optimal parameters of the MD potentials under different environmental conditions with the corresponding variability in experimental data. The high computational cost associated with the hierarchical Bayesian framework is reduced by orders of magnitude through a parallelized Transitional Markov Chain Monte Carlo method combined with the Laplace Asymptotic Approximation. The suitability of the hierarchical approach is demonstrated by performing MD simulations with prescribed parameters to obtain data for transport coefficients under different conditions, which are then used to infer and evaluate the parameters of the MD model. We demonstrate the selection of MD models based on experimental data and verify that the hierarchical model can accurately quantify the uncertainty across experiments; improve the posterior probability density function estimation of the parameters, thus, improve predictions on future experiments; identify the most plausible force field to describe the underlying structure of a given dataset. The framework and associated software are applicable to a wide range of nanoscale simulations associated with experimental data with a hierarchical structure.

SAMPLE CLOCK OFFSET COMPENSATION IN THE FIFTH-GENERATION NEW RADIO UPLINK

2021 ◽  
Author(s):  
О.Г. ПОНОМАРЕВ ◽  
М. АСАФ
Keyword(s):  
Signal To Noise Ratio ◽  
Radio Channel ◽  
Estimation Method ◽  
Estimation Methods ◽  
Fifth Generation ◽  
New Radio ◽  
Shared Channel ◽  
Wide Range ◽  
Offset Compensation ◽  
Clock Offset

Рассмотрена проблема коррекции искажений OFDM-сигнала, вызванных смещением частоты дискретизации сигнала в приемном и передающем устройствах системы сотовой связи пятого поколения. Предлагаемый метод компенсации смещения частоты дискретизации основывается на прямой коррекции искажений, вносимых в передаваемый сигнал наличием смещения, и не предполагает какой-либо оценки величины смещения. Метод предназначен для коррекции сигналов в восходящем канале системы сотовой связи пятого поколения и основывается на использовании референсных сигналов, рекомендованных стандартами 3GPP. Результаты численного моделирования показали, что использование предлагаемого метода позволяет повысить эффективность передачи данных по многолучевому радиоканалу более чем на 15% в широком диапазоне значений отношения сигнал/шум. 5G-NR, CP-OFDM, synchronization, sample clock offset, PUSCH. О The paper investigates the issue of sampling clock offset ( SCO) in the fifth generation new radio systems. Due to the imperfect SCO estimation methods, the correction methods relying on the SCO estimation are not perfect, so the proposed method directly corrects the effect of SCO without using any kind of estimation method. Our method is designed to correct the signals in the physical uplink shared channel (PUSCH). The method uses reference signals as recommended by the 3rd generation partnership project (3GPP) standards. The results of the numerical simulation show that the use of the proposed method increases the efficiency of data transmission over the multipath radio channel by more than 15% in a wide range of signal-to-noise ratio values.

Unconscious mental states

2018 ◽  
Author(s):  
Georges Rey
Keyword(s):  
Computational Models ◽  
A Priori ◽  
Mental States ◽  
A Priori Knowledge ◽  
Pupillary Dilation ◽  
Mental Life ◽  
Mental Processes ◽  
The Unconscious ◽  
Wide Range ◽  
The Moment

Unconscious phenomena are those mental phenomena which their possessor cannot introspect, not only at the moment at which the phenomenon occurs, but even when prompted (‘Do you think/want/…?’). There are abundant allusions to many kinds of unconscious phenomena from classical times to Freud. Most notably, Plato in his Meno defended a doctrine of anamnesis according to which a priori knowledge of, for example, geometry is ‘recollected’ from a previous life. But the notion of a rich, unconscious mental life really takes hold in nineteenth-century writers, such as Herder, Hegel, Helmholtz and Schopenhauer. It is partly out of this latter tradition that Freud’s famous postulations of unconscious, ‘repressed’ desires and memories emerged. Partly in reaction to the excesses of introspection and partly because of the rise of computational models of mental processes, twentieth-century psychology has often been tempted by Lashley’s view that ‘no activity of mind is ever conscious’ (1956). A wide range of recent experiments do suggest that people can be unaware of a multitude of sensory cognitive factors (for example, pupillary dilation, cognitive dissonance, subliminal cues to problem-solving) that demonstrably affect their behaviour. And Weiskrantz has documented cases of ‘blindsight’ in which patients with damage to their visual cortex can be shown to be sensitive to visual material they sincerely claim they cannot see. The most controversial cases of unconscious phenomena are those which the agent could not possibly introspect, even in principle. Chomsky ascribes unconscious knowledge of quite abstract principles of grammar to adults and even newborn children that only a linguist could infer. Many philosophers have found these claims about the unconscious unconvincing, even incoherent. However, they need to show how the evidence cited above could be otherwise explained, and why appeals to the unconscious have seemed so perfectly intelligible throughout history.

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