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We describe a trainable recognizer for multi-stroke symbols. The learned definitions are described in terms of the constituent geometric primitives (lines and arcs), the properties of individual primitives, and the geometric relationships between them. A definition is learned by examining a few examples of a symbol and identifying which properties and(More)
For an ideal design process, designers envision a configuration of components prior to determining dimensions or sizes of these components. Given the breadth of the component space, the design of any future artifact must be carefully planned to take advantage of the diverse set of possibilities. We conjecture that computational design tools could be(More)
Diagnostic inference involves the detection of anomalous system behavior and the identification of its cause, possibly down to a failed unit or to a parameter of a failed unit. Traditional approaches to solving this problem include expert/rule-based, model-based, and data-driven methods. Each approach (and various techniques within each approach) use(More)
Ensuring the reliability of complex software intensive systems is becoming a critical requirement for all military and commercial aerospace applications, and becomes especially more challenging when implemented for autonomous and evolving deployments required of such applications. To ensure reliability, this research asserts that knowledge, data, and models(More)
1 Introduction Few computational tools exist to assist designers during the conceptual phase of design, and design success is often heavily weighted on personal experience and innate ability. Many well-known methods (e.g. brainstorming, intrinsic and extrinsic searches, and morphological analysis) are designed to stimulate a designer's creativity, but(More)
In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we present a novel analytical and experimental approach to developing large-scale Bayesian networks by composition. This compositional approach reeects how (often redundant) subsystems are architected to form systems such as electrical(More)
A framework to compare and evaluate diagnosis algorithms (DAs) has been created jointly by NASA Ames Research Center and PARC. In this paper, we present the first concrete implementation of this framework as a competition called DXC'09. The goal of this competition was to evaluate and compare DAs in a common platform and to determine a winner based on(More)
In an ideal design process, designers envision a configuration of components prior to determining dimensions or sizes of these components. Given the breadth of suppliers and production methods that exist today, most engineered artifacts are a mix of both custom-made parts and OEM (original equipment manufacturer) parts. The design of any future artifact(More)
Early stage design provides the greatest opportunities to explore design alternatives and perform trade studies before costly design decisions are made. The goal of this research is to develop a simulation-based framework that enables architectural analysis of complex systems during the conceptual design phase. Using this framework, design teams can(More)