background and aim: attention is an important cognitive process that is necessary for educational purposes. blind people are deprived from the most widely used human sense, the sense of vision. there are reports that blind individuals have a significantly better performance in attentional tasks, as compared with normal subjects. the purpose of this study was to evaluate sustained auditory atten...

Often, the performance on a supervised machine learning task is evaluated with a task loss function that cannot be optimized directly. Examples of such loss functions include the classification error, the edit distance and the BLEU score. A common workaround for this problem is to instead optimize a surrogate loss function, such as for instance cross-entropy or hinge loss. In order for this rem...

We study joint modeling of survival and longitudinal data. There are two regression models of interest. The primary model is for survival outcomes, which are assumed to follow a time-varying coefficient proportional hazards model. The second model is for longitudinal data, which are assumed to follow a random effects model. Based on the trajectory of a subject's longitudinal data, some covariat...

A class of semiparametric estimators are proposed in the general setting of functional measurement error models. The estimators follow from estimating equations that are based on the semiparametric efficient score derived under a possibly incorrect distributional assumption for the unobserved ‘measured with error’ covariates. It is shown that such estimators are consistent and asymptotically no...

A spectral color reproduction method is proposed based on a vector error diffusion method. A low-dimensional linear model is used to approximate reflectance spectra, and the vector error diffusion is performed in a score vector space of the linear model. A suitable set of primary colors is also selected from oil colors. Presented method performed better than conventional colorimetric vector err...

In this paper, we propose two enhancements to a statistical machine translation based approach to grammar correction for correcting all error categories. First, we propose tuning the SMT systems to optimize a metric more suited to the grammar correction task (F-β score) rather than the traditional BLEU metric used for tuning language translation tasks. Since the F-β score favours higher precisi...