Inés Fernando Vega López

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Spatiotemporal databases are becoming increasingly more common. Typically, applications modeling spatiotemporal objects need to process vast amounts of data. In such cases, generating aggregate information from the data set is more useful than individually analyzing every entry. In this paper, we study the most relevant techniques for the evaluation of(More)
The ability to model time-varying natures is essential to many database applications such as data warehousing and mining. However, the temporal aspects provide many unique characteristics and challenges for query processing and optimization. Among the challenges is computing temporal aggregates, which is complicated by having to compute temporal grouping.(More)
Dense vesicles can be observed in live bovine chromaffin cells using fluorescent reflection confocal microscopy. These vesicles display a similar distribution, cytoplasmic density and average size as the chromaffin granules visualized by electron microscopy. In addition, the acidic vesicles labeled with Lysotracker Red comprised a subpopulation of the(More)
We have developed a new indexing strategy that helps overcome the curse of dimensionality for time series data. Our proposed approach, called skyline index, adopts new skyline bounding regions (SBR) to approximate and represent a group of time series data according to their collective shape. Skyline bounding regions allow us to define a distance function(More)
Using a rapid Fourier SSFP imaging technique, which is sensitive to slow flow (approximately 1 mm/sec) in the plane of the image, we obtained 135 brain MRI examinations. The CSF flow/motion patterns were mapped by two images with orthogonal in plane flow sensitivity directions. Analysis showed significant deviations from the "normal" pattern in ventricular(More)
The ability to model time-varying natures is essential to many database applications such as data warehousing and mining. However, the temporal aspects provide many unique characteristics and challenges for query processing and optimization. Among the challenges is computing temporal aggregates, which is complicated by having to compute temporal grouping.(More)
In recent years, we have observed a growing interest in similarity search on large collections of time series data. The research community has provided ingenious approaches for solving this problem. Most of the proposals advocate transforming a time series data to a smaller object that can be indexed by a spatial access method. Unfortunately, these(More)
Although near-field acoustic holography (NAH) is recognized as a powerful and extremely fast acoustic imaging method based on the inverse solution of the wave-equation, its practical implementation has suffered from problems with the use of the discrete Fourier transformation (DFT) in combination with small aperture sizes and windowing. In this paper, a(More)
Indexing time series data is an interesting problem that has attracted much interest in the research community for the last decade. Traditional indexing methods organize the data space using different metrics. However, searching high-dimensional spaces using a hierarchical index is not always efficient because a large portion of the index might need to be(More)
Indexing Time Series Data is an interesting problem that has attracted much interest in the research community for the last decade. Traditional indexing methods organize the data space using different metrics. For time series, however, there are some cases when a metric is not suited for properly assessing the similarity between sequences. For instance, to(More)