Search results for: OWL-S

Authors: Seunghwan Lee

Abstract:

The lubricating properties of commercially available mucins originating from different animal organs, namely bovine submaxillary mucin (BSM) and porcine gastric mucin (PGM), have been characterized at polymeric surfaces for biomedical applications. Atomic force microscopy (AFM) and pin-on-disk tribometry have been employed for tribological studies at nanoscale and macroscale contacts, respectively. Polystyrene (PS) was employed to represent ‘rigid’ contacts, whereas poly(dimethylsiloxane) (PDMS) was employed to represent ‘soft contacts’. To understand the lubricating properties of mucins in correlation with the coverage on surfaces, adsorption properties of mucins onto the polymeric substrates have been characterized by means of optical waveguide light-mode spectroscopy (OWLS). Both mucins showed facile adsorption onto both polymeric substrates, but the lubricity was highly dependent upon the pH change between 2 and 7.

Keywords: Bovine submaxillary mucin (BSM), Porcine Gastric Mucin (PGM), lubricity, biomedical.

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Authors: N. Neysani Samany, M.R. Delavar, N. Chrisman, M.R. Malek

Abstract:

Location-aware computing is a type of pervasive computing that utilizes user-s location as a dominant factor for providing urban services and application-related usages. One of the important urban services is navigation instruction for wayfinders in a city especially when the user is a tourist. The services which are presented to the tourists should provide adapted location aware instructions. In order to achieve this goal, the main challenge is to find spatial relevant objects and location-dependent information. The aim of this paper is the development of a reusable location-aware model to handle spatial relevancy parameters in urban location-aware systems. In this way we utilized ontology as an approach which could manage spatial relevancy by defining a generic model. Our contribution is the introduction of an ontological model based on the directed interval algebra principles. Indeed, it is assumed that the basic elements of our ontology are the spatial intervals for the user and his/her related contexts. The relationships between them would model the spatial relevancy parameters. The implementation language for the model is OWLs, a web ontology language. The achieved results show that our proposed location-aware model and the application adaptation strategies provide appropriate services for the user.

Keywords: Spatial relevancy, Context-aware, Ontology, Modeling

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