Area-class maps are conventionally delineated by human hands based on limited observed (or high-quality) data and expert knowledge. It is recognized that areaclass maps contain spatial uncertainty because the classification of unobserved locations is not completely certain. Spatial uncertainty associated with an area-class map may be quantified by spatial statistical approaches through estimati...

Characteristics of uncertainty and imprecision, even imperfection is presented from knowledge acquisition in map reconstruction of autonomous mobile robots. Especially in the course of building grid map using sonar, this characteristic of uncertainty is especially servere. Jean Dezert and Florentin Smarandache have recently proposed a new information fusion theory (DSmT), whose greatest merit i...

This paper presents two linked empirical studies focused on uncertainty visualization. The experiments are framed from two conceptual perspectives. First, a typology of uncertainty is used to delineate kinds of uncertainty matched with space, time, and attribute components of data. Second, concepts from visual semiotics are applied to characterize the kind of visual signification that is approp...

The first genetic linkage map for silver birch, Betula pendula Roth, was constructed by using a pseudo-testcross mapping strategy and integration of linkage data from 3 unrelated 2-generation pedigrees. The map is based on the genetic inheritance and segregation of 82 amplified fragment length polyhmorphisms and 19 microsatellite markers, and was constructed by simultaneously comparing the perf...

We search for an unusual alignment of the preferred axes of the quadrupole and octopole, the so-called axis of evil, in the CMB temperature and polarization data from WMAP. We split the temperature and polarization maps into a part correlated with the respective other map, and a part uncorrelated with that. We then determine the preferred axes for the quadrupole and octopole in all four of thos...

Spatial data uncertainty models (SDUM) are necessary tools that quantify the reliability of results from geographic information system (GIS) applications. One technique used by SDUM is Monte Carlo simulation, a technique that quantifies spatial data and application uncertainty by determining the possible range of application results. A complete Monte Carlo SDUM for generalized continuous surfac...

Recent prior studies with argumentation systems have shown that, unfortunately, with larger learner groups using argumentation software over longer periods of time, argument maps inevitably increase greatly in size and complexity, often leading to learner confusion. To help users understand and navigate within large and complex argument maps, we implemented an initial version of mini maps withi...

Abstract. We study the time evolution of the quantum-classical correspondence (QCC) for the well known model of quantised perturbed cat maps on the torus in the very specific regime of semi-classically small perturbations. The quality of the QCC is measured by the overlap of classical phase-space density and corresponding Wigner function of the quantum system called quantum-classical fidelity (...

IS projects success is a complex concept, and its evaluation is complicated, unstructured and not readily quantifiable. Numerous scientific publications address the issue of success in the IS field as well as in other fields. But, little efforts have been done for processing indeterminacy and uncertainty in success research. This paper shows a formal method for mapping success using Neutrosophi...

This paper deals with the problem of managing the uncertainty of an environment where a mobile robot is navigating in. This uncertainty is local to each feature detected in the environment. These features are modelled as fuzzy segments, in which their uncertainty is represented as a trapezoidal fuzzy set. An application of this schema, the localisation problem, is also described. In this case a...