Information extraction in the medical domain involves handling of a number of vital tasks such as identification of medical terms, identification of attributes such as negation, uncertainty, severity, identification of relationships between entities and mapping terms in the document to concepts in domain specific ontologies. The entire process depends on a number of fundamental NLP processes su...

The competitive equilibrium correspondence, which associates equilibrium prices of commodities and assets with allocations of endowments, identifies the preferences and beliefs of individuals under uncertainty; this is the case even if the asset market is incomplete.

In Operational Modal Analysis, the modal parameters (natural frequencies, damping ratios and mode shapes) obtained from Stochastic Subspace Identification (SSI) of a structure, are afflicted with statistical uncertainty. For evaluating the quality of the obtained results it is essential to know the appropriate confidence intervals of these figures. In this paper we present algorithms that autom...

A procedure for identifying a linear MIMO model with LFT-type uncertainty is presented. The uncertainty is minimized subject to the requirement that known input-output data do not invalidate the model. The optimization problem is solved stepwise. First, the uncertainty is minimized frequency-byfrequency with respect to the sampled frequency response of a nominal model subject to data-matching c...

Subspace identification algorithms are user friendly, numerical fast and stable and they provide a good consistent estimate of the deterministic part of a system. The weak point is the stochastic part. The uncertainty on this part is discussed below and methods to reduce it is derived.

Abstract: This paper addresses the problem of robust identification/fault detection when a model with parametric modelling is considered. Two identification methods are introduced following, respectively, the worst-case and set-membership approaches. In particular those algorithms will use zonotopes to bound the parametric uncertainty. These two identification approaches lead to two robust faul...

The application of Artificial Intelligence (AI) techniques to the problem of botanical identification is not particularly widespread even less so on Internet. There are several interactive identification systems but they usually deal with raw knowledge so it appears that “research and development of web-based expert systems are still in their early stage” (Li et al., 2002). In this paper we pre...

Modern robust control techniques require a description of the uncertainty in the plant to be controlled. For lightly damped structures, the most appropriate description of the uncertainty is in terms of interval ranges for parameters such as natural frequencies and damping ratios. What is desired is an algorithm which can determine such interval ranges from noisy transfer function measurements ...

Autonomous vehicles (AVs) require accurate metric and topological location estimates for safe, effective navigation and decision-making. Although many high-definition (HD) roadmaps exist, they are not always accurate since public roads are dynamic, shaped unpredictably by both human activity and nature. Thus, AVs must be able to handle situations in which the topology specified by the map does ...

Subspace identification algorithms are user friendly, numerical fast and stable and they provide a good consistent estimate of the deterministic part of a system. The weak point is the stochastic part. The uncertainty on this part is discussed below and methods to reduce it is derived.