Population computation of vectorial transformations

Many neurons of the central nervous system are broadly tuned to some sensory or motor variables. This property allows one to assign to each neuron a preferred attribute (PA). The width of tuning curves and the distribution of PAs in a population of neurons tuned to a given variable define the collective behavior of the population. In this article, we study the relationship of the nature of the tuning curves, the distribution of PAs, and computational properties of linear neuronal populations. We show that noise-resistant distributed linear algebraic processing and learning can be implemented by a population of cosine tuned neurons assuming a nonuniform but regular distribution of PAs. We extend these results analytically to the noncosine tuning and uniform distribution case and show with a numerical simulation that the results remain valid for a nonuniform regular distribution of PAs for broad noncosine tuning curves. These observations provide a theoretical basis for modeling general nonlinear sensorimotor transformations as sets of local linearized representations.     

A Unifying and Rigorous Shape from Shading Method Adapted to Realistic Data and Applications

We propose a new method for the Lambertian Shape From Shading (SFS) problem based on the notion of Crandall-Lions viscosity solution. This method has the advantage of requiring the knowledge of the solution (the surface to be reconstructed) only on some part of the boundary and/or of the singular set (the set of the points at maximal intensity). Moreover it unifies in an unique mathematical formulation the works of Rouy et al. [34, 50], Falcone et al. [21], Prados et al. [46, 48, 49], based on the notion of viscosity solutions and the work of Dupuis and Oliensis [17] dealing with classical solutions and value functions. Also, it allows to generalize their results to the “perspective SFS” problem recently simultaneously introduced in [13,46,55]. While the theoretical part has been developed in [44], in this paper we give some stability results and we describe numerical schemes for the SFS based on this method. We construct provably convergent and robust algorithms. Finally, we apply our SFS method to real images and we suggest some real-life applications.     

Large-Eddy Simulation of the Lid-Driven Cubic Cavity Flow by the Spectral Element Method

This paper presents the large-eddy simulation of the lid-driven cubic cavity flow by the spectral element method (SEM) using the dynamic model. Two spectral filtering techniques suitable for these simulations have been implemented. Numerical results for Reynolds number Re=12,000 are showing very good agreement with other experimental and DNS results found in the literature.     

Uniform controllability of semidiscrete approximations of parabolic control systems

Controlling an approximation model of a controllable infinite dimensional linear control system does not necessarily yield a good approximation of the control needed for the continuous model. In the present paper, under the main assumptions that the discretized semigroup is uniformly analytic, and that the control operator is mildly unbounded, we prove that the semidiscrete approximation models are uniformly controllable. Moreover, we provide a computationally efficient way to compute the approximation controls. An example of application is implemented for the one- and two-dimensional heat equation with Neumann boundary control.     

The Addiction-Stroop test: Theoretical considerations and procedural recommendations.

Decisions about using addictive substances are influenced by distractions by addiction-related stimuli, of which the user might be unaware. The addiction-Stroop task is a paradigm used to assess this distraction. The empirical evidence for the addiction-Stroop effect is critically reviewed, and meta-analyses of alcohol-related and smoking-related studies are presented. Studies finding the strongest effects were those in which participants had strong current concerns about an addictive substance or such concerns were highlighted through experimental manipulations, especially those depriving participants of the substance. Theories to account for addiction-related attentional bias are discussed, of which the motivational theory of current concerns appears to provide the most complete account of the phenomenon. Recommendations are made for maximizing the precision of the addiction-Stroop test in future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Elastic wave velocities in various alloy strips

The zeroth order plate mode shear wave velocity has been measured in thin strip specimens of Oriented Electrical Steel, Elinvar-Extra, and RMI 464 titanium alloy as a function of the angle between the propagation direction and the rolling direction. Also, the plane wave shear and longitudinal velocities have been measured along the normal to the rolling plane. The results in the Oriented Electrical Steel agree with the known (110)[001] texture. In the Elinvar-Extra there is a texture indistinguishable elastically from (100)[Oil], or partial (100)[011] superimposed on a random background. Different annealing temperatures following cold-rolling yield different degrees of anisotropy and different dependences (1/G)(dG/dT) of the shear modulus upon ambient temperature. At an annealing temperature of about 850‡C, (1/G)(dG/dT) evaluated near room temperature changes from positive to negative, and anisotropy becomes minimum. In the RMI 464 titanium alloy, the shear velocity anisotropy was only 1 pct in the rolling plane. Formerly with Bell Telephone Laboratories, Allen town, Pa.     

Deriving tabular event-based specifications from goal-oriented requirements models

Goal-oriented methods are increasingly popular for elaborating software requirements. They offer systematic support for incrementally building intentional, structural and operational models of the software and its environment. They also provide various techniques for early analysis, notably, to manage conflicting goals or to anticipate abnormal environment behaviours that prevent goals from being achieved. On the other hand, tabular event-based methods are well-established for specifying operational requirements for control software. They provide sophisticated techniques and tools for late analysis of software behaviour models through simulation, model checking or table exhaustiveness checks. The paper proposes to take the best out of these two worlds to engineer requirements for control software. It presents a technique for deriving event-based specifications, written in the SCR tabular language, from operational specifications built according to the KAOS goal-oriented method. The technique consists of a series of transformation steps each of which resolves semantic, structural or syntactic differences between the KAOS source language and the SCR target language. Some of these steps need human intervention and illustrate the kind of semantic subtleties that need to be taken into account when integrating multiple formalisms. As a result of our technique SCR specifiers may use upstream goal-based processes à la KAOS for the incremental elaboration, early analysis, organization and documentation of their tables, while KAOS modelers may use downstream tables à la SCR for later analysis of the behaviour models derived from goal specifications.     

A NON-PARAMETRIC APPROACH TO SIMPLICITY CLUSTERING

The simplicity principle—an updating of Ockham's razor to take into account modern information theory—states that the preferred theory for a set of data is the one that allows for the most efficient encoding of the data. We consider this in the context of classification, or clustering, as a data reduction technique that helps describe a set of objects by dividing the objects into groups. The simplicity model we present favors clusters such that the similarity of the items in the clusters is maximal, while the similarity of items between clusters is minimal. Several novel features of our clustering criterion make it especially appropriate for clustering of data derived from, psychological procedures (e.g., similarity ratings): It is non-parametric, and may be applied in situations where the metric axioms are violated without requiring (information-forgetting) transformation procedures. We illustrate the use of the criterion with a selection of data sets. A distinctive aspect of this research is that it motivates a clustering algorithm from psychological principles.