The case-crossover design is useful for studying the effects of transient exposures on short-term risk of diseases or injuries when only data on cases are available. The crossover nature of this design allows each subject to serve as his/her own control. While the original design was proposed for univariate event data, in many applications recurrent events are encountered (e.g. elderly falls, g...

Motion segmentation is a formidable computer vision task, aiming to segment moving targets from dynamic scene. In this paper, we choose introduce an additional modality bolster the robustness. The event camera bio-inspired sensor that accurately detects and captures intensity changes with exceptional temporal resolution range, which optimal choice for motion segmentation. Therefore, present nov...

Multivariate failure time data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated failure time when an individual is followed for the occurrence of two or more types of events for which the individual is simultaneously at risk, or when distinct individuals have dependent event times; o...

This study investigates whether people represent the beginnings and ends of events as fuzzy temporal frames and subsequently construct event temporal relations. The study adopted Allen’s (1984; 1991) seven logical categories of temporal relations. Constructing the seven relations often requires the accurate encoding and (or) retrieval of the beginnings and ends of events. We used a recurrent ne...

Segmenting observations from an input stream is an important capability of human cognition. Evidence suggests that humans refine this ability through experiences with the world. However, few models address the unsupervised development of event segmentation in artificial agents. This paper presents work towards developing a computational model of how an intelligent agent can independently learn ...