Segmentation of brain MR images plays an important role in longitudinal investigation of developmental, aging, disease progression changes in the cerebral cortex. However, most existing brain segmentation methods consider multiple time-point images individually and thus cannot achieve longitudinal consistency. For example, cortical thickness measured from the segmented image will contain unnece...

Datasets are created in the linked data ecosystem with varying data and metadata quality. Shallow (or poor-quality) metadata prevent dataset provision services (CKAN catalogs, etc.) from supporting their users in efficient search and exploration of datasets they need. In this paper we approach the problem by formalizing the dataset exploration scenario, introducing the notion of ontology-based ...

The amount of data available to study spatial temporal patterns in complex phenomena like disease diffusion has vastly increased over the years. Extraction of useful information is often hindered by the complexity of the patterns. In this paper we propose a method of training a SOM on a complete dataset and mapping back subsets of this dataset to allow comparison between a complete dataset and ...

This paper reports the results of temporal analysis of platelet (PLT) data in chronic hepatitis dataset. First we briefly introduce a cluster analysis system for temporal data that we have developed. Second, we show the results of cluster analysis of PLT sequences. Third, we show the results of PLT value-based temporal analysis aiming at finding years for reaching F4, years elapsed between stag...

Quantitative spatio-temporal (ST) sequences represent chains of ST event types in a ST framework. For example, it has been widely observed that deforestation in peat-land regions in Southeast Asia are often followed by forest fires, in close proximity of space and time [9]. Such patterns between deforestation and forest fires are attributed to the physical phenomena of degradation of soil due t...

While a variety of statistical models now exist for the spatio-temporal analysis of two-dimensional (surface) data collected over time, there are few published examples of analogous models for the spatial analysis of data taken over four dimensions: latitude, longitude, height or depth, and time. When taking account of the autocorrelation of data within and between dimensions, the notion of clo...

Quantitative spatio-temporal (ST) sequences represent chains of ST event types in a ST framework. For example, it has been widely observed that deforestation in peat-land forests are often followed by forest fires, in close proximity of space and time. Such patterns between deforestation and forest fires are attributed to the physical phenomena of degradation of soil due to logging, which reduc...

In this paper we argue that complex qualitative phenomena such as creativity can and should be investigated from a quantitative viewpoint and, in particular, within the framework of a time-constrained model of memory.

As documents tend to contain temporal information, extracting such information is attracting much research interests recently. In this paper, we propose a hybrid method that combines machine-learning models and hand-crafted rules for the task of extracting temporal information from unstructured Korean texts. We address Korean-specific research issues and propose a new probabilistic model to gen...