We present a model for context-aware applications that relies on the concept of aggregability, a function that tells how aggregated a message can be before being propagated.
In short, this paper makes the following contributions: We present a model for context-aware applications that relies on the concept of aggregability, a function that tells how aggregated a message can be before being propagated.
Guided by Dobrow et al.'s (2004) conceptual model for context-based evidence-based decision-making, this study will use a multiple case study design with embedded units of analysis to examine contextual factors influencing the prenatal record revision process in different Canadian provinces and territories.
The training process has to be applied only for the new context to get the context model for the context classification and to get the sound event models for the event detection.
Results were compared to a sample of commercial models for context.
As such, we provide a well-grounded, holistic overview of design issues that are the most critical in developing viable business models for context-aware services, based on interviews with eighteen esteemed practitioners and academics in the mobile services domain, at CEO and Professor level.
The baseline uncompressed system consisted of continuous density hidden Markov models for context-dependent crossword triphones.
Models for context-aware and self-adaptive systems have been widely studied in the last years, and several surveys have been proposed (see the work in [14, 19], just to name the most well known).
Besides feature models for DSLPs, this approach uses additional models for representing system context, architecture and reasoning (i.e., configuration selection), while we instead appeal to a unified model for representing context, architecture and reasoning.
