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Table 3: Summary of a collection of physically-based deformable models.

in unknown title
by unknown authors
"... In PAGE 12: ... Tables 2 and 3 list some of the previous developments in this area (including those for AORs and HORs), and their main technical char- acteristics. After a summary of empirical deformable models (Table 2), we brie y examine several major physically-based models ( Table3 ). We then consider techniques for rendering deformation directly.... In PAGE 12: ... Finally we give an overview of defor- mation techniques in the context of a particular application, namely surgical simulation, where SOR deformation could potentially play a major role. As shown in Table3 , physically-based models are usually de ned on mesh-based data representations. In some appli- cations, such as surgical simulation, it has been common to add analytical information (e.... In PAGE 13: ... For this reason, there have been many physically-based models proposed for deformation. As shown in Table3 , almost all physically-based mod- els are associated with a mesh data representation, typi- cally with triangular or rectangular elements for surfaces and tetrahedral or hexahedral elements for solids or volumes. In most applications involving SORs, such data representations can be extracted or reconstructed from SORs using the tech- niques discussed in Section 4.... ..."

Table 1. Primitive BinX data types.

in Binx - a tool for retrieving, searching and transforming structured binary files
by Rob Baxter, Robert Carroll, Denise J. Ecklund, Bob Gibbins, Davy Virdee, Ted Wen 2003
"... In PAGE 3: ...1 Data Types BinX supports a broad range of primitive data types, particularly those that are important for e- Science applications. Table1 summarises currently supported BinX data types. The underlying physical representation of each primitive data type must be described.... ..."
Cited by 3

Table 4.1: The physical joint representation.

in Building a Hand Posture Recognition System from Multiple Video Images: A Bottom-Up Approach
by Declan Murphy 2002
Cited by 2

TABLE 1. Constraint Mathematical representation Physical meaning

in Solving the converter placement problem in wdm ring networks using genetic algorithms
by Tak-ming Chan, Sam Kwong, K. F. Man
Cited by 1

Table 1: Example data capture modalities, and their typical characteristics and representation schemes.

in unknown title
by unknown authors
"... In PAGE 5: ... Digitization is the primary technology for acquiring SORs of real-life objects and phenomena. This technology, which is based on measuring various physical properties, is avail- able in a wide range of modalities as listed in Table1 . In most of these modalities, a sampling process may involve the processing of multi-channel or multi-dimensional sig- nals, including convolution and deconvolution, quantization, and signal space conversion.... ..."

Table 2. Representation of the means and ends of the collaboratory work domain

in Collaboration, communication and categorical complexity: A case study in collaboratory evaluation
by Bryan Richard Cleal, Hans H. K. Andersen, Hanne Albrechtsen 2004
"... In PAGE 3: ... The data was segmented into initial broad categories, following the framework for evaluation. The initial broad categories were mapped into an initial overall means-ends representation of the common work domain of collaborative film research ( Table2 ). ... In PAGE 4: ... The abstraction hierarchy has five levels of domain attributes, from goals and constraints of a work domain to physical resources in the domain. The means-ends representation of the common work domain of the film research collaboratory ( Table2 ) addresses the properties of the three most abstract means-ends levels: Goals/constraints, priorities and functions. The properties of processes and physical resources are not mapped into this representation.... ..."
Cited by 1

Table 9.1: Construction of ORI Identifiers for Physical Representations

in unknown title
by unknown authors

Table C.2: Equivalent Physical Time Constants [s] D Gain Scheduling Schemes In principle, there are two approaches to control design for systems which exhibit signi- cant changes in dynamics across their operating envelope. One possibility is to consider local representations of such a system and to design controllers for individual operating points. The functionality of the controllers is then to be integrated to cover the entire operating envelope by interpolation. In doing so, it is important to ensure that the data to be interpolated are su ciently smooth and that the states of the di erent controllers are always consistent with the state of the system.

in Robust Air-Fuel Ratio Control for Combustion Engines
by Markus Brandstetter, Markus Brandstetter

Table 1: Model Physical Data

in Minimal Energy Control of a Biped Robot with Numerical Methods and a Recursive Symbolic Dynamic Model
by Michael Hardt, Kenneth Kreutz-delgado, J. William Helton 1998
Cited by 5

Table 1. CMG Physical Data

in An Experimental Comparison of CMG Steering Control Laws
by Dongwon Jung, Panagiotis Tsiotras
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