This paper presents the development of an ontology for component service degradation. In this paper, degradation mechanisms in gas turbine metallic components are used for a case study to explain how a taxonomy within an ontology can be validated. The validation method used in this paper uses an iterative process and sanity checks. Data extracted from on-demand textual information are filtered and grouped into classes of degradation mechanisms. Various concepts are systematically and hierarchically arranged for use in the service maintenance ontology. The allocation of the mechanisms to the AS-IS ontology presents a robust data collection hub. Data integrity is guaranteed when the TO-BE ontology is introduced to analyse processes relative to various failure events. The initial evaluation reveals improvement in the performance of the TO-BE domain ontology based on iterations and updates with recognised mechanisms. The information extracted and collected is required to improve service k nowledge and performance feedback which are important for service engineers. Existing research areas such as natural language processing, knowledge management, and information extraction were also examined.

One way to evaluate the life-time performance of dental restorative materials is to use in vitro dental wear simulators, which generate accelerated artificial dental wear on dental restorative components outside of the human oral environment. However, the work of several researchers has questioned the reliability of these in vitro results as a consequence of significant result variations produced by different types of dental wear simulators testing identical dental specimens. Natural six degree of freedom (DOF) mandibular movements and other characteristics of the human masticatory system are not replicated by any of these available simulators. A simulator replicating and controlling 6 DOF mandibular movements and occlusal bite forces improves this situation. This paper presents a method by which accurate jaw motion data can be obtained using a conventional 6 DOF motion capturing system and a method of measuring occlusal bite forces. The data obtained have subsequently been used as input signals for a new 6 DOF dental wear simulator capable of generating single and multi-contact wear formations in dental wear studies.

MOTIVATION: HIV-1 antiretroviral drug resistance testing produces large amounts of HIV-1 protease and reverse transcriptase sequences. These provide an excellent resource to study the incidence, spread and clinical significance of HIV-1 subtypes. We have produced a program, Subtype Analyser (STAR) that rapidly and accurately subtypes HIV-1. Here we have determined a robust and statistically validated model for subtype assignment. RESULTS: We have significantly extended our HIV-1 subtyping tool (STAR), such that each query sequence when evaluated against subtype profile alignments, returns a discriminating score based on the ratio of subtype positive to negative amino acid positions. These scores were transformed into a Z-score distribution and evaluated. Of the 141 sequences used to define the subtype alignments, 98% were correctly reclassified. Inclusion of additional recombination detection within STAR increased the detection of known recombinant sequences to 95%. AVAILABILITY: STAR is available as compiled (Linux Fedora 3) or source code from http://pgv19.virol.ucl.ac.uk/download/star_linux.tar CONTACT: [email protected] SUPPLEMENTARY INFORMATION: http://pgv19.virol.ucl.ac.uk/download/star_supplement