We introduce novel information-entropic variables—a Point Divergence Gain (Ω α ), a Point Divergence Gain Entropy (Iα), and a Point Divergence Gain Entropy Density (Pα)—which are derived from the Rényi entropy and describe spatio-temporal changes between two consecutive discrete multidimensional distributions. The behavior of Ω α is simulated for typical distributions and, together with Iα and ...

SAS® can be used as a powerful tool for systematically exploring, animating, and sharing animated multidimensional data structures using goptions dev=gifanim statement in SAS/GRAPH®. Three different examples of data animation and visual analysis are provided in this paper (viewable at http://idt.net/~haftan by selecting research). The first, and perhaps easiest example, demonstrates the visual ...

The representation of multidimensional data is an important issue in applications in diverse fields that include database management systems, computer graphics, computer vision, computational geometry, image processing, geographic information systems (GIS), pattern recognition, VLSI design, and others. The most common definition of multidimensional data is a collection of points in a higher dim...

Thanks to the explosive growth of sensing devices and capabilities, multidimensional (MD) signals — such as images, videos, multispectral images, light fields, and biomedical data volumes — have become ubiquitous. Multidimensional filter banks and the associated constructions provide a unified framework and an efficient computational tool in the formation, representation, and processing of thes...

Globally, most weather-related damages are caused by thunderstorms. Besides floods, strong wind, and hail, one of the major thunderstorm ground effects is lightning. Therefore, lightning investigations, including detection, cluster identification, tracking, and nowcasting are essential. To enable reliable decisions, current and predicted lightning clusterand track features as well as analysis r...

Integration of spatial data into multidimensional models leads to the concept of Spatial OLAP (SOLAP). Usually, SOLAP models exploit discrete spatial data. Few works integrate continuous field data into dimensions and measures. In this paper, we provide a multidimensional model that supports measures and dimension as continuous field data, independently of their implementation.

Multidimensional scaling (MDS) is a technique for visualizing the relationships among data that are similar to each other on very many dimensions. For example, meanings of words such as indefinite pronouns are similar to each other by virtue of being expressed by the same indefinite pronoun in one language or another (Haspelmath 1997). If one compares indefinite pronouns of a large number of la...

In recent work we have presented a formal framework for linguistic annotation based on labeled acyclic digraphs. These ‘annotation graphs’ offer a simple yet powerful method for representing complex annotation structures incorporating hierarchy and overlap. Here, we motivate and illustrate our approach using discourse-level annotations of text and speech data drawn from the CALLHOME, COCONUT, M...

In this paper, a natural extension of the Lempel-Ziv complexity for several finitetime sequences, defined on finite size alphabets is proposed. Some results on the defined joint Lempel-Ziv complexity are given, as well as properties in connection with the Lempel-Ziv complexity of the individual sequences. Also, some links with Shannon entropies are exhibited and, by analogy, some derived quanti...

Our aim is to elaborate a multidimensional database reduction process which will specify aggregated schema applicable over a period of time as well as retains useful data for decision support. Firstly, we describe a multidimensional database schema composed of a set of states. Each state is defined as a star schema composed of one fact and its related dimensions. Each reduced state is defined t...