Induction of classification rules is one of the most important technologies in data mining. Most of the work in this field has concentrated on the Top Down Induction of Decision Trees (TDIDT) approach. However, alternative approaches have been developed such as the Prism algorithm for inducing modular rules. Prism often produces qualitatively better rules than TDIDT but suffers from higher comp...

The optical dispersive prism is a well-studied element, which allows separating white light into its constituent spectral colors, and stands in nature as water droplets. In analogy to this definition, the acoustic dispersive prism should be an acoustic device with capability of splitting a broadband acoustic wave into its constituent Fourier components. However, due to the acoustical nature of ...

Definitions of ‘knowledge’ and its relationships with ‘data’ and ‘information’ are varied, inconsistent and often contradictory. In particular the traditional hierarchy of data-information-knowledge and its various revisions do not stand up to close scrutiny. We suggest that the problem lies in a flawed analysis that sees data, information and knowledge as separable concepts that are transforme...

A progressive lens produces a smooth increase in positive foca_or addition_ power from distance to near without any lines of demarcation. In order to provide this gradual change in power, the curvature of a convex progressive lens surface must become increasingly steeper toward the bottom of the lens (Figure 1). The addition power of a convex progressive lens surface is simply the result of the...

A warm welcome from the Editorial desk of the ONTC’s newsletter “Prism”. It is our pleasure to bring to you this third edition of PRISM – ONTC’s quarterly newsletter. The industry is moving towards two interesting trends, of consolidation and new business models. Providers and vendors are both adopting new business models as well as new technologies that will have a significant impact The curre...

We propose a methodology for constructing a stochastic performance model of a public transportation network using real-world data. Our main data source consists of Automatic Vehicle Location (AVL) measurements of buses in the Edinburgh region. Although the data has a relatively low frequency, we can use it to parameterise a model in which a bus moves between predefined patches in the city. We f...