We present an implementation of a part-of-speech tagger based on a hidden Markov model. The methodology enables robust and accurate tagging with few resource requirements. Only a lexicon and some unlabeled training text are required. Accuracy exceeds 96%. We describe implementation strategies and optimizations which result in high-speed operation. Three applications for tagging are described: phrase recognition; word sense disambiguation; and grammatical function assignment.

In our earlier work, we proposed an architecture for a Web-based Video Database Management System (VDBMS) providing an integrated support for spatio-temporal and semantic queries. In this paper, we focus on the task of spatio-temporal query processing, and also propose an SQL-like video query language that has the capability to handle a broad range of spatio-temporal queries. The language is rule-based in that it allows users to express spatial conditions in terms of Prolog-type predicates.

DATA MODELING AND QUERYING FOR VIDEO DATABASES Ph.D. in Computer Engineering Supervisors: Assoc. Prof. Dr.

Computer simulation is an important tool for investigating the propagation behaviour of electrical excitation in cardiac tissue. When ionic models of cell membrane excitation are combined with the bidomain model of macroscopic tissue properties, numerical solution of the resulting partial differential equations requires a substantial amount of computation. Thus more efficient numerical methods are needed. One aspect of the computational complexity of this problem is the need for detailed spatial and temporal resolution while the depolarizing front of excitation propagates through the domain. During the subsequent, and more protracted, repolarization phase, the solution changes more slowly and a much coarser discretization would be adequate. Previous approaches have incorporated explicit integration methods whose stability limitations have prevented exploitation of this change in time scales. This study applies a stable implicit integration method which allows the time-step to be contro...

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Abstract—We present a framework to automatically evaluate the performance of Mobile Ad-hoc Networks (MANETs) in terms of different kinds of metrics, such as throughput and energy consumption. We use a probabilistic process calculus to model MANETs; we translate process terms into Markov Decision Processes (MDPs) and use the probabilistic model checker PRISM to automatically evaluate the network performance. We present a case study consisting of a network which uses flooding for communicating, and we analyse how time and energy costs vary when pursuing different power control strategies. Index Terms—process algebra; MANETS; model checking; network throughput; energy consumption I.