Transfer function modeling is a standard technique in classical Linear Time Invariant and Statistical Process Control. The work of Box and Jenkins was seminal in developing methods for identifying parameters associated with classical (r, s, k) transfer functions. Computing systems are often fundamentally discrete and feedback control in these situations may require discrete event systems for mo...

This paper presents a new parallel algorithm for backward symbolic execution. We use a program modeling allowing an easy distributed symbolic execution and a scalable program testing. A program is divided into several parts assigned to different nodes. A particular node: the Coordinator allocates tasks to workers and collects final results.

In this paper we present a generic modeling strategy for the derivation of approximated symbolic expressions for small-signal characteristics of analog circuits. This approach is characterized by a tight interaction between symbolic and numeric computations to ensure continuous error control and verification of the results. The workflow may also be extended to the derivation of nonlinear circui...

8] S. Hanks and D. McDermott. Modeling a dynamic and uncertain world I: symbolic and prob-abilistic reasoning about change.

Performance prediction is an important engineering tool that provides valuable feedback on design choices in program synthesis and machine architecture development. We present an analytic performance modeling approach aimed to minimize prediction cost, while providing a prediction accuracy that is sufficient to enable major code and data mapping decisions. Our approach is based on a performance...

Generative design based on symbolic grammars is oriented on individual artists. Team work is not supported since single scripts produced by various artists have to be linked and maintained manually with a lot of effort. The main motivation for a collaborative modeling framework was to reduce the script management required for large projects. We achieved even more by extending the design paradig...

Modeling and analysis of high consequence, high assurance systems requires special modeling considerations. System safety and reliability information must be captured in the models. Previously, high consequence systems were modeled using separate, disjoint models for safety, reliability, and security. The MultiGraph Architecture facilitates the implementation of a model-integrated system for mo...

Metastable attractors and heteroclinic orbits are present in the dynamics of various complex systems. Although their occurrence is well-known, their identification and modeling is a challenging task. The present work reviews briefly the literature and proposes a novel combination of their identification in experimental data and their modeling by dynamical systems. This combination applies recur...

This work proposes a semantic data model for video documents based on the story-line structure powerful enough to express various human interpretations of video documents, and introduces a formal query language for video retrieval that facilitates retrieval of users' heterogeneous queries based on the proposed model. The paper identifies the elementary semantic units, composite semantic units, ...

Understanding the functioning of genetic regulatory networks supposes a modeling of biological processes in order to simulate behaviors and to reason on the model. Unfortunately, the modeling task is confronted to incomplete knowledge about the system. To deal with this problem we propose a methodology that uses the qualitative approach developed by R. Thomas. A symbolic transition system can r...