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

Physicochemical Characteristics of Cobalt Selenides & Their Catalytic Activities

775-77

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