Unified Algorithm (unified + algorithm)

Distribution by Scientific Domains


Selected Abstracts


Unified algorithm for undirected discovery of exception rules

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 7 2005
Einoshin Suzuki
This article presents an algorithm that seeks every possible exception rule that violates a commonsense rule and satisfies several assumptions of simplicity. Exception rules, which represent systematic deviation from commonsense rules, are often found interesting. Discovery of pairs that consist of a commonsense rule and an exception rule, resulting from undirected search for unexpected exception rules, was successful in various domains. In the past, however, an exception rule represented a change of conclusion caused by adding an extra condition to the premise of a commonsense rule. That approach formalized only one type of exception and failed to represent other types. To provide a systematic treatment of exceptions, we categorize exception rules into 11 categories, and we propose a unified algorithm for discovering all of them. Preliminary results on 15 real-world datasets provide an empirical proof of effectiveness of our algorithm in discovering interesting knowledge. The empirical results also match our theoretical analysis of exceptions, showing that the 11 types can be partitioned in three classes according to the frequency with which they occur in data. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 673,691, 2005. [source]


Incremental Updates for Rapid Glossy Global Illumination

COMPUTER GRAPHICS FORUM, Issue 3 2001
Xavier Granier
We present an integrated global illumination algorithm including non-diffuse light transport which can handle complex scenes and enables rapid incremental updates. We build on a unified algorithm which uses hierarchical radiosity with clustering and particle tracing for diffuse and non-diffuse transport respectively. We present a new algorithm which chooses between reconstructing specular effects such as caustics on the diffuse radiosity mesh, or special purpose caustic textures, when high frequencies are present. Algorithms are presented to choose the resolution of these textures and to reconstruct the high-frequency non-diffuse lighting effects. We use a dynamic spatial data structure to restrict the number of particles re-emitted during the local modifications of the scene. By combining this incremental particle trace with a line-space hierarchy for incremental update of diffuse illumination, we can locally modify complex scenes rapidly. We also develop an algorithm which, by permitting slight quality degradation during motion, achieves quasi-interactive updates. We present an implementation of our new method and its application to indoors and outdoors scenes. [source]


Direct Manipulation and Interactive Sculpting of PDE Surfaces

COMPUTER GRAPHICS FORUM, Issue 3 2000
Haixia Du
This paper presents an integrated approach and a unified algorithm that combine the benefits of PDE surfaces and powerful physics-based modeling techniques within one single modeling framework, in order to realize the full potential of PDE surfaces. We have developed a novel system that allows direct manipulation and interactive sculpting of PDE surfaces at arbitrary location, hence supporting various interactive techniques beyond the conventional boundary control. Our prototype software affords users to interactively modify point, normal, curvature, and arbitrary region of PDE surfaces in a predictable way. We employ several simple, yet effective numerical techniques including the finite-difference discretization of the PDE surface, the multigrid-like subdivision on the PDE surface, the mass-spring approximation of the elastic PDE surface, etc. to achieve real-time performance. In addition, our dynamic PDE surfaces can also be approximated using standard bivariate B-spline finite elements, which can subsequently be sculpted and deformed directly in real-time subject to intrinsic PDE constraints. Our experiments demonstrate many attractive advantages of our dynamic PDE formulation such as intuitive control, real-time feedback, and usability to the general public. [source]


A combined iterative scheme for identification and control redesigns

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2004
Paresh Date
Abstract This work proposes a unified algorithm for identification and control. Frequency domain data of the plant is weighted to satisfy the given performance specifications. A model is then identified from this weighted frequency domain data and a controller is synthesised using the ,, loopshaping design procedure. The cost function used in the identification stage essentially minimizes a tight upper bound on the difference between the achieved and the designed performance in the sense of the ,, loopshaping design paradigm. Given a model, a method is also suggested to re-adjust model and weighting transfer functions to reduce further the worst case chordal distance between the weighted true plant and the model. Copyright © 2004 John Wiley & Sons, Ltd. [source]


Unified algorithm for undirected discovery of exception rules

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 7 2005
Einoshin Suzuki
This article presents an algorithm that seeks every possible exception rule that violates a commonsense rule and satisfies several assumptions of simplicity. Exception rules, which represent systematic deviation from commonsense rules, are often found interesting. Discovery of pairs that consist of a commonsense rule and an exception rule, resulting from undirected search for unexpected exception rules, was successful in various domains. In the past, however, an exception rule represented a change of conclusion caused by adding an extra condition to the premise of a commonsense rule. That approach formalized only one type of exception and failed to represent other types. To provide a systematic treatment of exceptions, we categorize exception rules into 11 categories, and we propose a unified algorithm for discovering all of them. Preliminary results on 15 real-world datasets provide an empirical proof of effectiveness of our algorithm in discovering interesting knowledge. The empirical results also match our theoretical analysis of exceptions, showing that the 11 types can be partitioned in three classes according to the frequency with which they occur in data. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 673,691, 2005. [source]