10,390 research outputs found
Setting Parameters by Example
We introduce a class of "inverse parametric optimization" problems, in which
one is given both a parametric optimization problem and a desired optimal
solution; the task is to determine parameter values that lead to the given
solution. We describe algorithms for solving such problems for minimum spanning
trees, shortest paths, and other "optimal subgraph" problems, and discuss
applications in multicast routing, vehicle path planning, resource allocation,
and board game programming.Comment: 13 pages, 3 figures. To be presented at 40th IEEE Symp. Foundations
of Computer Science (FOCS '99
Proceedings of the USDA-ARS workshop "Real world" infiltration
Compiled and edited by L.R. Ahuja and Amy Garrison.Includes bibliographical references.Proceedings of the 1996 workshop held on July 22-25, 1996 in Pingree Park, Colorado
Magnetoresistance behavior of a ferromagnetic shape memory alloy: Ni_1.75Mn_1.25Ga
A negative-positive-negative switching behavior of magnetoresistance (MR)
with temperature is observed in a ferromagnetic shape memory alloy
Ni_1.75Mn_1.25Ga. In the austenitic phase between 300 and 120 K, MR is negative
due to s-d scattering. Curiously, below 120K MR is positive, while at still
lower temperatures in the martensitic phase, MR is negative again. The positive
MR cannot be explained by Lorentz contribution and is related to a magnetic
transition. Evidence for this is obtained from ab initio density functional
theory, a decrease in magnetization and resistivity upturn at 120 K. Theory
shows that a ferrimagnetic state with anti-ferromagnetic alignment between the
local magnetic moments of the Mn atoms is the energetically favoured ground
state. In the martensitic phase, there are two competing factors that govern
the MR behavior: a dominant negative trend up to the saturation field due to
the decrease of electron scattering at twin and domain boundaries; and a weaker
positive trend due to the ferrimagnetic nature of the magnetic state. MR
exhibits a hysteresis between heating and cooling that is related to the first
order nature of the martensitic phase transition.Comment: 17 pages, 5 figures. Accepted in Phys. Rev.
Phase transitions in diluted negative-weight percolation models
We investigate the geometric properties of loops on two-dimensional lattice
graphs, where edge weights are drawn from a distribution that allows for
positive and negative weights. We are interested in the appearance of spanning
loops of total negative weight. The resulting percolation problem is
fundamentally different from conventional percolation, as we have seen in a
previous study of this model for the undiluted case.
Here, we investigate how the percolation transition is affected by additional
dilution. We consider two types of dilution: either a certain fraction of edges
exhibit zero weight, or a fraction of edges is even absent. We study these
systems numerically using exact combinatorial optimization techniques based on
suitable transformations of the graphs and applying matching algorithms. We
perform a finite-size scaling analysis to obtain the phase diagram and
determine the critical properties of the phase boundary.
We find that the first type of dilution does not change the universality
class compared to the undiluted case whereas the second type of dilution leads
to a change of the universality class.Comment: 8 pages, 7 figure
Developing natural resource models using the object modeling system: feasibility and challenges
International audienceCurrent challenges in natural resource management have created demand for integrated, flexible, and easily parameterized hydrologic models. Most of these monolithic models are not modular, thus modifications (e.g., changes in process representation) require considerable time, effort, and expense. In this paper, the feasibility and challenges of using the Object Modeling System (OMS) for natural resource model development will be explored. The OMS is a Java-based modeling framework that facilitates simulation model development, evaluation, and deployment. In general, the OMS consists of a library of science, control, and database modules and a means to assemble the selected modules into an application-specific modeling package. The framework is supported by data dictionary, data retrieval, GIS, graphical visualization, and statistical analysis utility modules. Specific features of the OMS that will be discussed include: 1) how to reduce duplication of effort in natural resource modeling; 2) how to make natural resource models easier to build, apply, and evaluate; 3) how to facilitate long-term maintainability of existing and new natural resource models; and 4) how to improve the quality of natural resource model code and ensure credibility of model implementations. Examples of integrating a simple water balance model and a large monolithic model into the OMS will be presented
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