In this paper we present results related to achieving finegrained activity recognition for
context-aware computing applications. We examine the advantages and challenges of …

Containing a summary of several recent results on Markov-based input modeling in a
coherent notation, this book introduces and compares algorithms for parameter fitting and …

Asynchronous stochastic systems are abundant in the real world. Examples include queuing
systems, telephone exchanges, and computer networks. Yet, little attention has been given …

A number of approximate analysis techniques are based on matching moments of
continuous time phase type (PH) distributions. This paper presents an explicit method to …

Approximating general distributions by phase-type (PH) distributions is a popular technique
in stochastic analysis, since the Markovian property of PH distributions often allows …

A challenge in building pervasive and smart spaces is to learn and recognize human
activities of daily living (ADLs). In this paper, we address this problem and argue that in …

In this paper, a system is considered that fails when the cumulative damage due to shocks
exceeds the handling capacity of the system. It is also supposed that if the time between two …

We present the first near-exact analysis of an M/PH/k queue with m> 2 preemptive-resume
priority classes. Our analysis introduces a new technique, which we refer to as Recursive …

We introduce the generalized semi-Markov decision process (GSMDP) as an extension of
continuous-time MDPs and semi-Markov decision processes (SMDPs) for modeling …

In the airline industry, deciding the ticket price for each flight directly affects the number of
people that in the future will try to buy a ticket. Depending on the willingness-to-pay of the …