674,424 research outputs found
Validation of a model of regulation in the tryptophan operon against multiple experiment data using global optimisation
This paper is concerned with validating a mathematical model of regulation in the tryptophan operon using global optimization. Although a number of models for this biochemical network are proposed, in many cases only qualitative agreement between the model output and experimental data was demonstrated, since very little information is currently available to guide the selection of parameter values for the models. This paper presents a model validating method using both multiple experimental data and global optimization
On Validating an Astrophysical Simulation Code
We present a case study of validating an astrophysical simulation code. Our
study focuses on validating FLASH, a parallel, adaptive-mesh hydrodynamics code
for studying the compressible, reactive flows found in many astrophysical
environments. We describe the astrophysics problems of interest and the
challenges associated with simulating these problems. We describe methodology
and discuss solutions to difficulties encountered in verification and
validation. We describe verification tests regularly administered to the code,
present the results of new verification tests, and outline a method for testing
general equations of state. We present the results of two validation tests in
which we compared simulations to experimental data. The first is of a
laser-driven shock propagating through a multi-layer target, a configuration
subject to both Rayleigh-Taylor and Richtmyer-Meshkov instabilities. The second
test is a classic Rayleigh-Taylor instability, where a heavy fluid is supported
against the force of gravity by a light fluid. Our simulations of the
multi-layer target experiments showed good agreement with the experimental
results, but our simulations of the Rayleigh-Taylor instability did not agree
well with the experimental results. We discuss our findings and present results
of additional simulations undertaken to further investigate the Rayleigh-Taylor
instability.Comment: 76 pages, 26 figures (3 color), Accepted for publication in the ApJ
An information architecture for validating courseware
Courseware validation should locate Learning Objects inconsistent with the courseware instructional design being used. In order for validation to take place it is necessary to identify the implicit and explicit information needed for validation. In this paper, we identify this information and formally define an information architecture to model courseware validation information explicitly. This promotes tool-support for courseware validation and its interoperability with the courseware specifications
Validating simulated interaction for retrieval evaluation
A searcher’s interaction with a retrieval system consists of actions such as query formulation, search result list interaction and document interaction. The simulation of searcher interaction has recently gained momentum in the analysis and evaluation of interactive information retrieval (IIR). However, a key issue that has not yet been adequately addressed is the validity of such IIR simulations and whether they reliably predict the performance obtained by a searcher across the session. The aim of this paper is to determine the validity of the common interaction model (CIM) typically used for simulating multi-query sessions. We focus on search result interactions, i.e., inspecting snippets, examining documents and deciding when to stop examining the results of a single query, or when to stop the whole session. To this end, we run a series of simulations grounded by real world behavioral data to show how accurate and responsive the model is to various experimental conditions under which the data were produced. We then validate on a second real world data set derived under similar experimental conditions. We seek to predict cumulated gain across the session. We find that the interaction model with a query-level stopping strategy based on consecutive non-relevant snippets leads to the highest prediction accuracy, and lowest deviation from ground truth, around 9 to 15% depending on the experimental conditions. To our knowledge, the present study is the first validation effort of the CIM that shows that the model’s acceptance and use is justified within IIR evaluations. We also identify and discuss ways to further improve the CIM and its behavioral parameters for more accurate simulations
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