The main objective of this research work is to construct a Fuzzy Temporal Rule Based Classifier that uses fuzzy rough set and temporal logic in order to mine temporal patterns in medical databases. The lower approximation concepts and fuzzy decision table with the fuzzy features are used to obtain fuzzy decision classes for building the classifier. The goals are pre-processing for feature selec...

In order to present a quantitative indicator for the onset of instability, in this paper, the critical points of a stratified gravitational flow on a slope are found and analyzed. These points are obtained by means of the solution of the two-dimensional Navier-Stokes equations via the standard Arakawa-C finite-difference method. Results show that in the marginal Richardson numbers, the critical...

Parkinson’s disease (PD) is the second most common neurodegenerative disease in the elderly. Santiago and Potashkin (1) recently performed a network-based metaanalysis of four independent microarray datasets and identified hepatocyte nuclear factor 4 alpha (HNF4A) and polypyrimidine tract binding protein 1 (PTBP1) to be the longitudinally dynamic biomarkers for PD. They found that HNF4A is a ce...

Spatio-temporal salient features localize the local motion events and are used to represent video sequences for many computer vision tasks such as action recognition. The robust detection of these features under geometric variations such as affine transformation and view/scale changes is however an open problem. Existing methods use the same filter for both time and space and hence, perform an ...

Human action recognition is an important task in computer vision. Extracting discriminative spatial and temporal features to model the spatial and temporal evolutions of different actions plays a key role in accomplishing this task. In this work, we propose an end-to-end spatial and temporal attention model for human action recognition from skeleton data. We build our model on top of the Recurr...

Research on context management and activity recognition in smart environments is essential in the development of innovative well adapted services. This paper presents two main contributions. First, we present ContextAct@A4H, a new real-life dataset of daily living activities with rich context data. It is a high quality dataset collected in a smart apartment with a dense but non intrusive sensor...

Predicting traffic conditions has been recently explored as a way to relieve traffic congestion. Several pioneering approaches have been proposed based on traffic observations of the target location as well as its adjacent regions, but they obtain somewhat limited accuracy due to lack of mining road topology. To address the effect attenuation problem, we propose to take account of the traffic o...