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Streams, structures, spaces, scenarios, societies (5s): A formal model for digital libraries
The fundamental abstractions of Streams, Structures, Spaces, Scenarios, and Societies (5S), which allow us to define digital libraries rigorously and usefully, are proposed.
Algorithm 652: HOMPACK: a suite of codes for globally convergent homotopy algorithms
HOMPACK provides three qualitatively different algorithms for tracking the homotopy zero curve: ordinary differential equation-based, normal flow, and augmented Jacobian matrix.
Digraph Models of Bard-Type Algorithms for the Linear Complementarity Problem
These digraphs show that such algorithms based on complementary pivoting for solving the linear complementarity problem can cycle even for symmetric, positive deFinite M, and provide some insight into the algorithms' behavior.
Photosynthetic Acclimation Is Reflected in Specific Patterns of Gene Expression in Drought-Stressed Loblolly Pine1[w]
Genes encoding heat shock proteins, late embryogenic-abundant proteins, enzymes from the aromatic acid and flavonoid biosynthetic pathways, and from carbon metabolism showed distinctive responses associated with acclimation.
Genetic algorithm optimization and blending of composite laminates by locally reducing laminate thickness
Genetic algorithms with local improvement for composite laminate design
This paper describes the application of a genetic algorithm to the stacking sequence optimization of a laminated composite plate for buckling load maximization. Two approaches for reducing the number…
Modeling the Transient Effects during the Hot-Pressing of Wood-Based Composites
The Topographic Primal Sketch
A complete mathematical treatment is given for describing the topographic primal sketch of the underlying gray tone intensity surface of a digital image. Each picture element is independently…
COMPOSITE LAMINATE DESIGN OPTIMIZATION BY GENETIC ALGORITHM WITH GENERALIZED ELITIST SELECTION
Efficient global optimization algorithm assisted by multiple surrogate techniques
The multiple surrogate efficient global optimization (MSEGO) algorithm is proposed, which adds several points per optimization cycle with the help of multiple surrogates, and is found that MSEGO works well even with imported uncertainty estimates, delivering better results in a fraction of the optimization cycles needed by EGO.