Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

Finding scientific articles in a large digital archive: BioStor and the Biodiversity Heritage Library

The Biodiversity Heritage Library (BHL) is a large digital archive of legacy biological literature, comprising over 31 million pages scanned from books, monographs, and journals. During the digitisation process basic metadata about the scanned items is recorded, but not article-level metadata. Given that the article is the standard unit of citation, this makes it difficult to locate cited literature in BHL. Adding the ability to easily find articles in BHL would greatly enhance the value of the archive. A service was developed to locate articles in BHL based on matching article metadata to BHL metadata using approximate string matching, regular expressions, and string alignment. This article finding service is exposed as a standard OpenURL resolver on the BioStor web site "http://biostor.org/openurl/":http://biostor.org/openurl/. This resolver can be used on the web, or called by bibliographic tools that support OpenURL. BioStor provides tools for extracting, annotating, and visualising articles from the Biodiversity Heritage Library. BioStor is available from "http://biostor.org/":http://biostor.org/

The development of computer science research in the People's Republic of China 2000-2009: A bibliometric study

This paper reports a bibliometric study of the development of computer science research in the People's Republic of China in the 21st century, using data from the Web of Science, Journal Citation Reports and CORE databases. Focusing on the areas of data mining, operating systems and web design, it is shown that whilst the productivity of Chinese research has risen dramatically over the period under review, its impact is still low when compared with established scientific nations such as the USA, the UK and Japan. The publication and citation data for China are compared with corresponding data for the other three BRIC nations (Brazil, Russian and India). It is shown that China dominates the BRIC nations in terms of both publications and citations, but that Indian publications often have a greater individual impact. © The Author(s) 2012

A Historical Perspective on Runtime Assertion Checking in Software Development

This report presents initial results in the area of software testing and analysis produced as part of the Software Engineering Impact Project. The report describes the historical development of runtime assertion checking, including a description of the origins of and significant features associated with assertion checking mechanisms, and initial findings about current industrial use. A future report will provide a more comprehensive assessment of development practice, for which we invite readers of this report to contribute information

Recent advances in directional statistics

Mainstream statistical methodology is generally applicable to data observed in Euclidean space. There are, however, numerous contexts of considerable scientific interest in which the natural supports for the data under consideration are Riemannian manifolds like the unit circle, torus, sphere and their extensions. Typically, such data can be represented using one or more directions, and directional statistics is the branch of statistics that deals with their analysis. In this paper we provide a review of the many recent developments in the field since the publication of Mardia and Jupp (1999), still the most comprehensive text on directional statistics. Many of those developments have been stimulated by interesting applications in fields as diverse as astronomy, medicine, genetics, neurology, aeronautics, acoustics, image analysis, text mining, environmetrics, and machine learning. We begin by considering developments for the exploratory analysis of directional data before progressing to distributional models, general approaches to inference, hypothesis testing, regression, nonparametric curve estimation, methods for dimension reduction, classification and clustering, and the modelling of time series, spatial and spatio-temporal data. An overview of currently available software for analysing directional data is also provided, and potential future developments discussed.Comment: 61 page

A Survey on Continuous Time Computations

We provide an overview of theories of continuous time computation. These theories allow us to understand both the hardness of questions related to continuous time dynamical systems and the computational power of continuous time analog models. We survey the existing models, summarizing results, and point to relevant references in the literature