T here is always uncertainty about the soundness of an economic model’s structure and parameters. Therefore, central banks normally face with uncertainty about the key economic explanatory relationships. So, policymaker should take into account the uncertainty in formulating monetary policies. The present study is aimed to examine robust optimal monetary policy under uncertainty, by ...

We present an approach to multi-objective exploration whose goal is to autonomously explore an unknown indoor environment. Our objective is to build a semantic map containing highlevel information, namely rooms and the objects laid in these rooms. This approach was developed for the Panoramic and Active Camera for Object Mapping (PACOM)1 project in order to participate in a French exploration a...

The success of cleaning up a contaminated site depends on the degree of knowledge of the site's characteristics. When there is much uncertainty associated with the knowledge, the uncertainty regarding whether the remediation will work increases consequently. It is therefore essential to know how much reduction of uncertainty is needed for the purpose of designing a successful and reliable remed...

We propose a novel combined global/local model for active semi-supervised spectral clustering based on the principle of uncertainty reduction. We iteratively compute the derivative of the eigenvectors produced by spectral decomposition with respect to each item/image, and combine this with local label entropy provided by the current clustering results in order to estimate the uncertainty reduct...

Mismatch problem has been one of important issues of matched field processing for underwater source detection. Experimental use of MFP has shown that robust range and depth localization is difficult to achieve. In many cases this is due to uncertainty in the environmental inputs required by acoustic propagation models. The paper presents that EMD (Empirical mode decomposition) processing underw...

Word spotting is an effective paradigm for indexing document images with minimal human effort. Here, the use of the Bag-ofFeatures principle has been shown to achieve competitive results on different benchmarks. Recently, a spatial pyramid approach was used as a word image representation to improve the retrieval results even further. The high dimensionality of the spatial pyramids was attempted...

Various aspects of the role of uncertainty in greenhouse gas emission reduction policy are analyzed with the integrated assessment model FUND. FUND couples simple models of economy, climate, climate impacts, and emission abatement. Probability distribution functions are assumed for all major parameters in the model. Monte Carlo analyses are used to study the e!ects of parametric uncertainties. ...

This paper develops a simple model in which uncertainty about a future tax change leads to a temporary reduction in investment. When the uncertainty is resolved, investment recovers, generating a temporary boom.

In the real world, risk and uncertainty are two natural properties in the implementation of Mega projects. Most projects fail to achieve the pre-determined objectives due to uncertainty. A linear integer programming optimization model was used in this work to solve a problem in order to choose the most appropriate risk responses for the project risks. A mathematical model, in which work structu...

111 Abstract—The purpose of the present work is to quantify parametric uncertainty in Rothermel’s wildland fire spread model (implemented in software such as BehavePlus3 and FARSITE), which is undoubtedly among the most widely used fire spread models in the United States. This model consists of a nonlinear system of equations that relates environmental variables (input parameter groups) such as...