Cognitive modeling aims more and more to explain, predict and integrate behavioral data with brain activations found in fMRI studies. In this article we analyze transitive inferences (e.g. A is left of B and B is left of C then A is left of C) during the spatial reasoning processes. Behavioral findings suggest that reasoners tend to construct a mental model from the premises, which they in turn...

This paper reports on an experiment to determine the optimal parameters for a speech recogniser that is part of a computer aided instruction system for assisting learners of English as a Second Language. The recogniser uses Hidden Markov Model (HMM) technology. To find the best choice of parameters for the recogniser, an exhaustive experiment with 2370 combinations of parameters was performed o...

Duration of an event tends to be underestimated as it becomes temporally distant (Spetch & Wilkie, 1983). The current study investigated this so-called choose-short effect in time and length in order to reevaluate the claim that the choose-short effect is special to temporal memory (Wearden, Parry, & Stamp, 2002). Participants made discrimination judgments in time or length on a pair of line st...

The application of the generalized gravity model in analyzing the Bangladesh’s trade reveals that Bangladesh’s trade is positively determined by the size of the economies, per capita GNP differential of the countries involved and openness of the trading countries. Bangladesh’s exports are positively determined by the exchange rate, partner countries’ total import demand and openness of the Bang...

RevBayes has as a central idea that phylogenetic models, like any statistical model, are composed of smaller parts that can be decomposed and put back together in a modular fashion. This comes from considering phylogenetic models as probabilistic graphical models, which lends flexibility and enhances the capabilities of the program. RevBayes implements an R-like language (complete with control ...

Latent class analysis (LCA) and latent profile analysis (LPA) are techniques that aim to recover hidden groups from observed data. They are similar to clustering techniques but more flexible because they are based on an explicit model of the data, and allow you to account for the fact that the recovered groups are uncertain. LCA and LPA are useful when you want to reduce a large number of conti...

We have determined the rescaling of the scalar condensate Z ≡ Z ϕ near the critical line of a 4D Ising model. Our lattice data, supporting previous numerical indications, confirm the behaviour Z ϕ ∼ ln(cutoff). This result is predicted in an alternative description of symmetry breaking where there are no upper bounds on the Higgs boson mass from 'triviality'. There are many computational and an...

An exposition on the use of O’Sullivan penalized splines in contemporary semiparametric regression, including mixed model and Bayesian formulations, is presented. O’Sullivan penalized splines are similar to P-splines, but have the advantage of being a direct generalization of smoothing splines. Exact expressions for the O’Sullivan penalty matrix are obtained. Comparisons between the two types o...

In this study, we investigated the information processing stages underlying associative recognition. We recorded EEG data while participants performed a task that involved deciding whether a probe word triple matched any previously studied triple. We varied the similarity between probes and studied triples. According to a model of associative recognition developed in the Adaptive Control of Tho...

In this paper we present a new computer based training environment for the domain of air traffic control. It is the application of an already existing implementation of a cognitive model for air traffic control (Niessen et al., 1998) that is based on the psychologically founded cognitive architecture ACT-R (Anderson & Lebiere, 1998). The novelty of our new training system lies in its approach t...