Search Results

We consider the following video activity recognition (VAR) task: given a video, infer the set of activities being performed in the video and assign each frame to an activity. Although VAR can be solved accurately using existing deep learning techniques, ...

When modelling multivariate continuous time series, a common issue is to find that the original processes that generated the data are nonlinear or that they drift away from the original distribution as the system evolves over time. In these ...

Abstract: The subsea emergency safety valve is an essential and critical subsystem of the subsea blowout preventer system. Performance degradation of the subsea emergency safety valve may lead to leakage incident, which can cause a serious well kick; ...

Virtual machine (VM) migration mechanisms and the design of data centres for the cloud have a significant impact on energy cost and SLA constraints. The recent work focuses on how to use VM migration to achieve stable physical machine utilisation with the ...

This paper reports on a formal user study on visual encodings of networks with multiple edge types in adjacency matrices. Our tasks and conditions were inspired by real problems in computational biology. We focus on encodings in adjacency matrices, ...

Provenance records the history of data acquisition and transmission. In wireless sensor networks (WSNs), provenance is critical for many different purposes, including assessing the trustworthiness of data acquired and forwarded by sensors, supporting ...

Touch-sensitive surfaces have become a predominant input medium for computing devices. In particular, multitouch capability of these devices has given rise to developing rich interaction vocabularies for “real” direct manipulation of user interfaces. ...

Recent research shows a lack of student interest and declined enrollment in physics. Our system offers four levels of difficulty with activities that enable students to exercise a range of lower and higher order cognitive skills. Moreover, we adopt ...

Managing the uncertainties that arise in disasters - such as ship fire - can be extremely challenging. Previous work has typically focused either on modeling crowd behavior or hazard dynamics, targeting fully known environments. However, when a disaster ...

While a great variety of algorithms have been developed and applied to learning static Bayesian networks, the learning of dynamic networks has been relatively neglected. The causal discovery program CaMML has been enhanced with a highly flexible set of ...

Interactive story-based learning environments offer significant potential for crafting narrative tutorial guidance to create pedagogically effective learning experiences that are tailored to individual students. This paper reports on an empirical ...

We present a novel probabilistic framework that fuses information coming from the audio and video modality to perform speaker diarization. The proposed framework is a Dynamic Bayesian Network (DBN) that is an extension of a factorial Hidden Markov Model ...

Though a plethora of techniques have been used to build gene regulatory networks (GRN) from time-series gene expression data, stabilities of such techniques have not been studied. This paper investigates the stability of GRN built using dynamic Bayesian ...

Applying a dynamic Bayesian network model can help detect neural interactions and analyze the characteristics of a monkey's motor cortex during reach-to-grasp tasks.

In this article, we focus on keyword detection in children's speech as it is needed in voice command systems. We use the FAU Aibo Emotion Corpus which contains emotionally colored spontaneous children's speech recorded in a child-robot interaction ...

The high complexity in the gene regulation mechanism and the prevalent noise in high-throughput detection experiments are considered to be the two major obstacles in discovering transcriptional regulation with high accuracy from experimental gene ...

Much knowledge of human physiology is formalised as systems of differential equations. For example, standard models of pharma-cokinetics and pharmacodynamics use systems of differential equations to describe a drug's movement through the body and its ...

Interactive narrative-centered learning environments offer significant potential for scaffolding guided discovery learning in rich virtual storyworlds while creating engaging and pedagogically effective experiences. Within these environments students ...

Automatic video segmentation and action recognition has been a long-standing problem in computer vision. Much work in the literature treats video segmentation and action recognition as two independent problems; while segmentation is often done without a ...

This paper demonstrates the use of qualitative probabilistic networks (QPNs) to aid Dynamic Bayesian Networks (DBNs) in the process of learning the structure of gene regulatory networks from microarray gene expression data. We present a study which ...