Most civil engineering tasks require accessing, surveying and modifying geospatial data in the field and referencing this virtual, geospatial information to the real world situation. Augmented Reality (AR) can be a useful tool to create, edit and update geospatial data representing real world artifacts by interacting with the 3D graphical representation of the geospatial data augmented in the u...

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In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a variable number of non-overlapping clustering rules, where each rule includes d intervals, one for each feature. The encoding scheme is non-binary as the values for the boundaries of the intervals are drawn from discr...

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A bs tr act. We attempt to find the suitable modeling for complex gesture patterns so that we can utilize it for their recognition and reproduction. As a result, we propose a hybrid framework where the observable characteristics of gestures are modeled explicitly, while pattern details are processed by blind learning methods. Our hybrid approach thus consists of multiple layers with inter-commu...

A majority of contribution in the domain of rule mining overemphasize on maximizing the predictive accuracy of the discovered patterns. The user-oriented criteria such as comprehensibility and interestingness are have been given secondary importance. Recently, it has been widely acknowledged that even highly accurate discovered knowledge might be worthless if it scores low on the qualitative pa...

Supervised classification is a particular data-mining task that forms part of the knowledge discovery process. Its objectives are to extract accurate, comprehensible and interesting knowledge form data. However, many existing supervised classification approaches only focus on one of these objectives. This paper introduces a Multi-Objective Evolutionary Rule Base Induction System called MERBIS t...

In many application domains, there is a need for learning algorithms that generate accurate as well as comprehensible classifiers. In this paper, we present TRIPPER a rule induction algorithm that extends RIPPER, a widely used rule-learning algorithm. TRIPPER exploits knowledge in the form of taxonomies over the values of features used to describe data. We compare the performance of TRIPPER wit...

Conceptual Schemas with Abstractions – Making flat conceptual schemas more comprehensi-ble, L. Abstract Flat graphical, conceptual modeling techniques are widely accepted as visually effective ways in which to specify and communicate the conceptual data requirements of an information system. Conceptual schema diagrams provide modelers with a picture of the salient structures underlying the mode...

The patterns of variation within a molecular sequence data set result from the interplay between population genetic, molecular evolutionary and macroevolutionary processes-the standard purview of evolutionary biologists. Elucidating these patterns, particularly for large data sets, requires an understanding of the structure, assumptions and limitations of the algorithms used by bioinformatics s...