scholarly journals Dark Control: Towards a Unified Account of Default Mode Function by Markov Decision Processes

2017 ◽  
Author(s):  
Elvis Dohmatob ◽  
Guillaume Dumas ◽  
Danilo Bzdok
Keyword(s):  
Process Model ◽  
Predictive Coding ◽  
Building Blocks ◽  
Default Mode ◽  
Special Cases ◽  
Markov Decision ◽  
Semantic Associations ◽  
Neural Optimization ◽  
Experimental Findings ◽  
Adaptive Role

AbstractThe default mode network (DMN) is believed to subserve the baseline mental activity in humans. Its highest energy consumption compared to other brain networks and its intimate coupling with conscious awareness are both pointing to an overarching function. Many research streams speak in favor of an evolutionarily adaptive role in envisioning experience to anticipate the future. In the present work, we propose a process model that tries to explain how the DMN may implement continuous evaluation and prediction of the environment to guide behavior. Specifically, we answer the question whether the neurobiological properties of the DMN collectively provide the computational building blocks necessary for a Markov Decision Process. We argue that our formal account of DMN function naturally accommodates as special cases previous interpretations based on (1) predictive coding, (2) semantic associations, and (3) a sentinel role. Moreover, this process model for the neural optimization of complex behavior in the DMN offers parsimonious explanations for recent experimental findings in animals and humans.

Control of arrivals to a stochastic input–output system

1980 ◽  
Vol 12 (4) ◽  
pp. 972-999 ◽  
Author(s):  
Søren Glud Johansen ◽  
Shaler Stidham
Keyword(s):  
Markov Decision Process ◽  
Decision Process ◽  
Input Output ◽  
Distinctive Features ◽  
Control Models ◽  
Special Cases ◽  
Non Linear ◽  
Markov Decision ◽  
Output System ◽  
Stochastic Input

The problem of controlling input to a stochastic input-output system by accepting or rejecting arriving customers is analyzed as a semi-Markov decision process. Included as special cases are a GI/G/1 model and models with compound input and/or output processes, as well as several previously studied queueing-control models. We establish monotonicity of socially and individually optimal acceptance policies and the more restrictive nature of the former, with random rewards for acceptance and both customer-oriented and system-oriented non-linear waiting costs. Distinctive features of our analysis are (i) that it allows dependent interarrival times and (ii) that the monotonicity proofs do not rely on the standard concavity-preservation arguments.

Axisymmetric Boussinesq problem of a transversely isotropic half space with surface effects

2018 ◽  
Vol 24 (5) ◽  
pp. 1425-1437 ◽  
Author(s):  
Jing Jin Shen
Keyword(s):  
Half Space ◽  
Mixed Boundary ◽  
Contact Stiffness ◽  
Surface Elasticity ◽  
Transversely Isotropic ◽  
Surface Effects ◽  
Building Blocks ◽  
Material Anisotropy ◽  
Residual Surface Stress ◽  
Special Cases

A transversely isotropic half space with surface effects subjected to axisymmetric loadings is investigated in terms of the Lekhnitskii formulism. Surface effects including residual surface stress and surface elasticity are introduced by using the Gurtin–Murdoch continuum model. With the aid of the Hankel transforms, solutions corresponding to several different axisymmetic loadings are derived and used to determine the influence of surface effects on contact stiffness in nanoindentations. Numerical results are provided to show the influence of surface effects and material anisotropy on the material behaviours. Meanwhile, the obtained analytical Green’s functions for two special cases can be used as building blocks for further mixed boundary value problems.

scholarly journals PrimaVera: Synergising Predictive Maintenance

2020 ◽  
Vol 10 (23) ◽  
pp. 8348
Author(s):  
Bram Ton ◽  
Rob Basten ◽  
John Bolte ◽  
Jan Braaksma ◽  
Alessandro Di Bucchianico ◽  
...  
Keyword(s):  
Asset Management ◽  
Process Model ◽  
Building Blocks ◽  
Predictive Maintenance ◽  
Full Potential ◽  
Support Tools ◽  
Maintenance Cycle ◽  
Optimal Maintenance ◽  
Organisational Factors ◽  
Maintenance Process

The full potential of predictive maintenance has not yet been utilised. Current solutions focus on individual steps of the predictive maintenance cycle and only work for very specific settings. The overarching challenge of predictive maintenance is to leverage these individual building blocks to obtain a framework that supports optimal maintenance and asset management. The PrimaVera project has identified four obstacles to tackle in order to utilise predictive maintenance at its full potential: lack of orchestration and automation of the predictive maintenance workflow, inaccurate or incomplete data and the role of human and organisational factors in data-driven decision support tools. Furthermore, an intuitive generic applicable predictive maintenance process model is presented in this paper to provide a structured way of deploying predictive maintenance solutions.

scholarly journals Systematic design of microscope objectives. Part III: miscellaneous design principles and system synthesis

2019 ◽  
Vol 8 (5) ◽  
pp. 385-402
Author(s):  
Yueqian Zhang ◽  
Herbert Gross
Keyword(s):  
Building Blocks ◽  
Design Principles ◽  
Correction Function ◽  
High Magnification ◽  
Systematic Design ◽  
Diffractive Optical Elements ◽  
Optical Elements ◽  
Special Cases ◽  
Very High ◽  
New System

Abstract In this paper, the lens modules used in the Zones 1–4 microscope objectives, which have been summarised in Part II, are utilised to create new structures. Both the modification of available systems and the synthesis of new system structures from basic building blocks are introduced. Moreover, design principles used under four special cases are introduced in this paper, including very-low-magnification Zone 5 objectives, very-high-magnification Zone 6 objectives, objectives with correction function (CORR) and objectives with diffractive optical elements, which were not systematically discussed in Part II. All the definitions and terms are based on the preceding papers.

scholarly journals Need for Caution in Interpreting Extreme Weather Statistics

2015 ◽  
Vol 28 (23) ◽  
pp. 9166-9187 ◽  
Author(s):  
Prashant D. Sardeshmukh ◽  
Gilbert P. Compo ◽  
Cécile Penland
Keyword(s):  
Process Model ◽  
Large Scale ◽  
Probability Distributions ◽  
Extreme Weather ◽  
Recent Change ◽  
Atmospheric Variability ◽  
Tail Probabilities ◽  
The North ◽  
Special Cases ◽  
Non Gaussian

Abstract Given the reality of anthropogenic global warming, it is tempting to seek an anthropogenic component in any recent change in the statistics of extreme weather. This paper cautions that such efforts may, however, lead to wrong conclusions if the distinctively skewed and heavy-tailed aspects of the probability distributions of daily weather anomalies are ignored or misrepresented. Departures of several standard deviations from the mean, although rare, are far more common in such a distinctively non-Gaussian world than they are in a Gaussian world. This further complicates the problem of detecting changes in tail probabilities from historical records of limited length and accuracy. A possible solution is to exploit the fact that the salient non-Gaussian features of the observed distributions are captured by so-called stochastically generated skewed (SGS) distributions that include Gaussian distributions as special cases. SGS distributions are associated with damped linear Markov processes perturbed by asymmetric stochastic noise and as such represent the simplest physically based prototypes of the observed distributions. The tails of SGS distributions can also be directly linked to generalized extreme value (GEV) and generalized Pareto (GP) distributions. The Markov process model can be used to provide rigorous confidence intervals and to investigate temporal persistence statistics. The procedure is illustrated for assessing changes in the observed distributions of daily wintertime indices of large-scale atmospheric variability in the North Atlantic and North Pacific sectors over the period 1872–2011. No significant changes in these indices are found from the first to the second half of the period.

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