The text and the tale: differences between scientific reports and scientists’ reportings on the eruption of Mount Chance, Montserrat

This article looks at the difference between scientists’ written reports and their oral accounts, explanations and stories. The subject of these discourses is the eruption of Mount Chance on Montserrat, a British Overseas Territory in the Eastern Caribbean, and its continued monitoring and reporting. Scientific notions of risk and uncertainty which feature in these texts and tales will subsequently be examined and critiqued. Further to this, this article will end by pointing out that, ironically, the latter - the tale – can in some cases be a more effective and approximate mode of communication with the public than the former – the text.

Robust Extraction of Text from Camera Images using Colour and Spatial Information Simultaneously

The importance and use of text extraction from camera based coloured scene images is rapidly increasing with time. Text within a camera grabbed image can contain a huge amount of meta data about that scene. Such meta data can be useful for identification, indexing and retrieval purposes. While the segmentation and recognition of text from document images is quite successful, detection of coloured scene text is a new challenge for all camera based images. Common problems for text extraction from camera based images are the lack of prior knowledge of any kind of text features such as colour, font, size and orientation as well as the location of the probable text regions. In this paper, we document the development of a fully automatic and extremely robust text segmentation technique that can be used for any type of camera grabbed frame be it single image or video. A new algorithm is proposed which can overcome the current problems of text segmentation. The algorithm exploits text appearance in terms of colour and spatial distribution. When the new text extraction technique was tested on a variety of camera based images it was found to out perform existing techniques (or something similar). The proposed technique also overcomes any problems that can arise due to an unconstraint complex background. The novelty in the works arises from the fact that this is the first time that colour and spatial information are used simultaneously for the purpose of text extraction.

Introduction to Domain-Driven Data Mining Special Section

In the last decade, data mining has emerged as one of the most dynamic and lively areas in information technology. Although many algorithms and techniques for data mining have been proposed, they either focus on domain independent techniques or on very specific domain problems. A general requirement in bridging the gap between academia and business is to cater to general domain-related issues surrounding real-life applications, such as constraints, organizational factors, domain expert knowledge, domain adaption, and operational knowledge. Unfortunately, these either have not been addressed, or have not been sufficiently addressed, in current data mining research and development.Domain-Driven Data Mining (D3M) aims to develop general principles, methodologies, and techniques for modeling and merging comprehensive domain-related factors and synthesized ubiquitous intelligence surrounding problem domains with the data mining process, and discovering knowledge to support business decision-making. This paper aims to report original, cutting-edge, and state-of-the-art progress in D3M. It covers theoretical and applied contributions aiming to: 1) propose next-generation data mining frameworks and processes for actionable knowledge discovery, 2) investigate effective (automated, human and machine-centered and/or human-machined-co-operated) principles and approaches for acquiring, representing, modelling, and engaging ubiquitous intelligence in real-world data mining, and 3) develop workable and operational systems balancing technical significance and applications concerns, and converting and delivering actionable knowledge into operational applications rules to seamlessly engage application processes and systems.

Discourse and Text

This article discusses tense and aspect in the context of attested forms of discourse and text. The emphasis is on the semantic, pragmatic, textual, and stylistic functions of tense in context, taking into account linguistic features in the surrounding discourse, as well as the importance of factors such as medium (spoken or written), register (degree of formality), text type (literary vs. journalistic vs. conversational etc.), and discourse mode (narrative vs. report vs. description, etc.). Thus, tense and aspect are analyzed not purely as part of a linguistic “system” as such, but in the context of particular texts or forms of discourse. The article also explores the concept of “markedness” through two case studies: the narrative present and the narrative imperfect. Finally, it assesses the roles played by tenses in conveying particular points of view in texts, including shifts and/or ambiguities in point of view; Segmented Discourse Representation Theory; internal focalization and the French imperfective past tense; and textual polyphony.