In the context of Knowledge Discovery in Databases, data reduction is a pre-processing step delivering succinct yet meaningful data to sequent stages. If the target of mining are data streams, then it is crucial to suitably reduce them, since often analyses on such data require multiple scans. In this chapter, we propose a histogram-based approach to reducing sliding windows supporting approxim...

Environmental systems are complicated. They include very intricate spatio-temporal processes, interacting on a wide variety of scales. There is increasingly vast amounts of data for such processes from geographical information systems, remote sensing platforms, monitoring networks, and computer models. In addition, often there is a great variety of scientific knowledge available for such system...

The purpose of this study is to explore the users’ process mental models of classification task. Hierarchical grouping and image tests are conducted to analyze the way they classify the real product samples of mobile phones. From the database of similarity and image tests, cluster analyses were used to analyze the distribution of total images and form features (the form treatments) in the tree ...

The paper describes combinatorial framework for planning of geological exploration for oil-gas fields. The suggested scheme of the geological exploration involves the following stages: (1) building of special 4-layer tree-like model (layer of geological exploration): productive layer, group of productive layers, oil-gas field, oil-gas region (or group of the fields); (2) generations of local de...

In this work, we have presented a hierarchical scheme for classifying music data. Instead of dealing with large variety of features, proposed scheme relies on MFCC and its variants which are introduced at the different stages to satisfy the need. At the top level music is classified as song (music with voice) and instrumental (music without voice) based on MFCC. Subsequently, instrumental signa...

Boosting-based methods have recently led to the state-of-the-art face detection systems. In these systems, weak classifiers to be boosted are based on simple, local, Haar-like features. However, it can be empirically observed that in later stages of the boosting process, the non-face examples collected by bootstrapping become very similar to the face examples, and the classification error of Ha...

Organizations have difficulty learning from rare and unusual events because of their inability to interpret these events. Because organizations develop habitual ways of interpreting events—often top down—they can easily miss the novelty of rare and unusual events, which prevents them from experiencing events “richly.” We propose a multilevel, multistaged model of organizational interpretation t...

The long-term objective of this research project is to characterize multi-pollutant (arsenic, lead, cadmium, and chromium) human exposures by linking sources to biomarkers using a multi-scale (individual level, county level) hierarchical Bayesian model (HBM) that describes how multi-media pathways contribute to direct routes of exposure. Our approach is to use a statistical model that has expli...

Integrated e-supply chains are distributed manufacturing systems composed of various resources belonging to different companies and integrated with streamlined material, information and financial flow. The configuration of the supply chain network is essential for business to pursue a competitive advantage and to meet the market demand. This paper proposes a three-level hierarchical methodology...

Plasma thyrotropin (TSH) levels have been previously shown to be associated with the internal sleep structure determined by conventional scoring of sleep stages. This temporal relationship was re-evaluated using spectral analysis of the sleep electroencephalogram (EEG). Eight healthy male subjects underwent two randomized night studies after having received either placebo or 5 mg ritanserin, a ...