Narrow Results

In the first part of the paper I present a definition of becoming that overcomes the irrelevant as well as misleading debates between presentists and eternalists. Since my definition essentially requires an ontology of events occurring in temporal succession, I go on showing that not only the theory of relativity, but also quantum mechanics, in its various interpretations, requires such an ontology, despite the limitations in the possibility of representing quantum processes in a spatiotemporal arena.

The past few years have seen an increased interest in the potential use of wireless sensor networks (WSNs) in applications. Unreliability and a dynamic nature are frequently present in the field of WSN, making anomaly detection necessary. Although events are often functions of more than one attribute and the energy in sensors is limited, the combination of data fusion and spatiotemporal correlations can overcome these limitations effectively. In this paper, we propose a spatiotemporal correlation-based anomaly detection model to differentiate normal and abnormal events in WSNs. The update phase occurs when abnormal events are detected. We demonstrate the usability and advantages of applying the spatiotemporal relevance in anomaly detection. Experimental results indicate its high performance in handling multi-dimensional sensor data.

Seismic data can be used to ima the acoustic impedance variations in the earth. In order to convert such data an image that more. closely matches the vision of geology, image enhancement techniques including pattern recognition methods must be applied. A syntax-dependent approach employing a string-to-string matching algorithm matches peaks between traces on a seismic record. A filtering process then enforces matching coherence by correcting matches that deviate seriously from the general trend around anomalous pairs. Connected pairs form lateral coherent events which have a confidence measure. These events are targets of any seismic investigation. Clustering technique can be used to associate the events with geologic zones. The algorithm performs well in a test run and detects most of the strong reflections…