A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Multi-sensor context-awareness in mobile devices and smart artifacts
Mobile Networks and Applications
Part 1: introduction to ontological engineering
New Generation Computing - Quantum computing
An aggregate weld product model for the early design stages
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
The Knowledge Engineering Review
The Smart Phone: A Ubiquitous Input Device
IEEE Pervasive Computing
Deployment of an ontological framework of functional design knowledge
Advanced Engineering Informatics
Dealing with device collaboration rules for the PCSCW model
CRIWG'10 Proceedings of the 16th international conference on Collaboration and technology
Disparate attributes algorithm for semantic assembly design rule management
Advanced Engineering Informatics
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Comparing with general mobile devices, Ubiquitous Smart Device (USD) is characterized by its capability to generate or use context data for autonomous services, and it provides users with personalized and situation-aware interfaces. While the USD development requires more knowledge-intensive and collaborative environment, the capture, retrieval, accessibility, and reusability of that design knowledge are increasingly critical. In the design collaboration, the cumulative, evolutionary design information and design rules behind the USD design are infrequently captured and often difficult to hurdle due to its complexity. Rough set theory synthesizes approximation of concepts, analyzes data by discovering patterns, and classifies into certain decision classes. Such patterns can be extracted from data by means of methods based on Boolean reasoning and discernibility. In this paper, a rough set theory generates demanded rules and selects the appropriate minimal rules among the demanded rules associated to USD physical component design. The presented method shows the feasibility of rough-set based rule selection considering complex design data objects of USD physical components.