In this article the methodology proposed by Li and Wang for mixed qualitative and quantitative modeling and simulation of temporal behavior of processing unit is reexamined and extended to more complex case. The main issue of their approach considers the multivariate statistics of principal component analysis (PCA), along with clustered fuzzy digraphs and reasoning. The PCA and fuz...

What are the cognitive processes in play when someone uses a visualization tool to interactively explore a new dataset? Here, we focus on one particular type of visualization—the scatter plot—which, despite (or perhaps because of) its simplicity, is still one of the most frequently used plot types in many dataintensive disciplines. We conducted a pilot study to investigate how expert astronomer...

We deene a quantitative Temporal Logic that is based on a simple modality within the framework of Monadic Predicate Logic. Its canonical model is the real line (and not an !-sequence of some type). We prove its decidability using general theorems from Logic (and not Automata theory). We show that it is as expressive as any alternative suggested in the literature.

Due to intra-class variation, camera jitter, background clutter, etc, human activity recognition is a challenging task in computer vision. We propose an exemplar-based key pose sequence model for human interaction recognition. In our model, an activity is modelled with a sequence of key poses, important atomic-level actions performed by the actors. We employ a strict temporal ordering of the ke...

We deene Parameterized Real-Time Computation Tree Logic (PRTCTL), which allows quantitative temporal speciications to be parameterized over the natural numbers. Parameterized quantitative speciications are quantitative speciications in which concrete timing information has been abstracted away. Such abstraction allows designers to specify quantitative restrictions on the temporal ordering of ev...

Tensor total variation (TTV) regularized deconvolution has been proposed for robust low radiation dose CT perfusion. In this paper, we extended TTV algorithm with anisotropic regularization weighting for the temporal and spatial dimension. We evaluated TTV algorithm on synthetic dataset for bolus delay, uniform region variability and contrast preservation, and on clinical dataset for reduced sa...

drought monitoring, which is a crucial component of drought management, aims to provide information that enables and supports people and organizations to take actions to reduce potential drought-related impact and damage. we usually tend to focus on drought when it is occurring and to react when crises strike. however, recent experiences and developments on drought knowledge are encouraging soc...

In this paper, we propose a novel spatio-temporal feature which is useful for feature-fusion-based action recognition with Multiple Kernel Learning (MKL). The proposed spatio-temporal feature is based on moving SURF interest points grouped by Delaunay triangulation and on their motion over time. Since this local spatio-temporal feature has different characteristics from holistic appearance feat...