Transputer network implementation of a parallel projection algorithm for conceptual graphs

Author(s):  
Alfred Chan ◽  
Pavel Kocura
Author(s):  
Kohji Kamejima

A parallel distributed scheme is presented for extracting a computable feature associated with self similar patterns. Observed patterns are assumed to be specified in terms of a set of contraction mappings that evokes an "avalanche of exploration" in image field. This intrinsically non-deterministic imaging process yields a conditional probability that is represented on a diffusion system. For identifying mapping set, a parallel projection algorithm is designed on a computable set of local minimums of the conditional distribution. The scheme is applied to dynamic detection of fractal patterns.


Author(s):  
Amy M. McGough ◽  
Robert Josephs

The remarkable deformability of the erythrocyte derives in large part from the elastic properties of spectrin, the major component of the membrane skeleton. It is generally accepted that spectrin's elasticity arises from marked conformational changes which include variations in its overall length (1). In this work the structure of spectrin in partially expanded membrane skeletons was studied by electron microscopy to determine the molecular basis for spectrin's elastic properties. Spectrin molecules were analysed with respect to three features: length, conformation, and quaternary structure. The results of these studies lead to a model of how spectrin mediates the elastic deformation of the erythrocyte.Membrane skeletons were isolated from erythrocyte membrane ghosts, negatively stained, and examined by transmission electron microscopy (2). Particle lengths and end-to-end distances were measured from enlarged prints using the computer program MACMEASURE. Spectrin conformation (straightness) was assessed by calculating the particles’ correlation length by iterative approximation (3). Digitised spectrin images were correlation averaged or Fourier filtered to improve their signal-to-noise ratios. Three-dimensional reconstructions were performed using a suite of programs which were based on the filtered back-projection algorithm and executed on a cluster of Microvax 3200 workstations (4).


Author(s):  
TRU H. CAO

Conceptual graphs and fuzzy logic are two logical formalisms that emphasize the target of natural language, where conceptual graphs provide a structure of formulas close to that of natural language sentences while fuzzy logic provides a methodology for computing with words. This paper proposes fuzzy conceptual graphs as a knowledge representation language that combines the advantages of both the two formalisms for artificial intelligence approaching human expression and reasoning. Firstly, the conceptual graph language is extended with functional relation types for representing functional dependency, and conjunctive types for joining concepts and relations. Then fuzzy conceptual graphs are formulated as a generalization of conceptual graphs where fuzzy types and fuzzy attribute-values are used in place of crisp types and crisp attribute-values. Projection and join as basic operations for reasoning on fuzzy conceptual graphs are defined, taking into account the semantics of fuzzy set-based values.


Sign in / Sign up

Export Citation Format

Share Document