Analysis of document-mining techniques and tools for technology intelligence: Discovering knowledge from technical documents

This research proposes a method for extracting technology intelligence (TI) systematically from a large set of document data. To do this, the internal and external sources in the form of documents, which might be valuable for TI, are first identified. Then the existing techniques and software systems applicable to document analysis are examined. Finally, based on the reviews, a document-mining framework designed for TI is suggested and guidelines for software selection are proposed. The research output is expected to support intelligence operatives in finding suitable techniques and software systems for getting value from document-mining and thus facilitate effective knowledge management. Copyright © 2012 Inderscience Enterprises Ltd.

Change propagation analysis in complex technical systems

Understanding how and why changes propagate during engineering design is critical because most products and systems emerge from predecessors and not through clean sheet design. This paper applies change propagation analysis methods and extends prior reasoning through examination of a large data set from industry including 41,500 change requests, spanning 8 years during the design of a complex sensor system. Different methods are used to analyze the data and the results are compared to each other and evaluated in the context of previous findings. In particular the networks of connected parent, child and sibling changes are resolved over time and mapped to 46 subsystem areas. A normalized change propagation index (CPI) is then developed, showing the relative strength of each area on the absorber-multiplier spectrum between -1 and +1. Multipliers send out more changes than they receive and are good candidates for more focused change management. Another interesting finding is the quantitative confirmation of the "ripple" change pattern. Unlike the earlier prediction, however, it was found that the peak of cyclical change activity occurred late in the program driven by systems integration and functional testing. Patterns emerged from the data and offer clear implications for technical change management approaches in system design. Copyright © 2007 by ASME.

Current research in embankment dam engineering at imperial college London

This paper gives a short introduction to two research streams in embankment dam engineering underway at Imperial College London. The first is the modelling of embankment dam behaviour during earthquakes and the second is an investigation into the susceptibility of granular filters to internal erosion. The research motivation, methods and expected outcomes of each stream are discussed.

Report on the British Society of Rheology mid-winter meeting on The Rheology of Foams and Emulsions, Royal School of Mines, Imperial College, London 10th - 11th December 2007

S.J. Cox, S. Neethling and H. Wilson (2008) British Society of Rheology mid-winter meeting on The Rheology of Foams and Emulsions. Applied Rheology 18:93-95

Femina (Trinity College, Cambridge MS B.14.40) : edited with an Introduction and Notes

Rothwell, W., Femina (Trinity College, Cambridge MS B.14.40); edited with an Introduction and Notes (The Anglo-Norman On-Line Hub, 2005) RAE2008

O perfil de personalidade dos estudantes de engenharia informática

Dissertação apresentada à Universidade Fernando Pessoa, como parte dos requisitos necessários para a obtenção do grau Mestre em Psicologia, ramo de Psicologia do Trabalho e das Organizações

A proposal for the better supplying of churches in our foreign plantations, and for converting the savage Americans to Christianity, by a college to be erected in the Summer Islands, otherwise called the Isles of Bermuda.

http://www.archive.org/details/proposalforbette00berkrich

A Two-step Statistical Approach for Inferring Network Traffic Demands (Revises Technical Report BUCS-2003-003)

Accurate knowledge of traffic demands in a communication network enables or enhances a variety of traffic engineering and network management tasks of paramount importance for operational networks. Directly measuring a complete set of these demands is prohibitively expensive because of the huge amounts of data that must be collected and the performance impact that such measurements would impose on the regular behavior of the network. As a consequence, we must rely on statistical techniques to produce estimates of actual traffic demands from partial information. The performance of such techniques is however limited due to their reliance on limited information and the high amount of computations they incur, which limits their convergence behavior. In this paper we study a two-step approach for inferring network traffic demands. First we elaborate and evaluate a modeling approach for generating good starting points to be fed to iterative statistical inference techniques. We call these starting points informed priors since they are obtained using actual network information such as packet traces and SNMP link counts. Second we provide a very fast variant of the EM algorithm which extends its computation range, increasing its accuracy and decreasing its dependence on the quality of the starting point. Finally, we evaluate and compare alternative mechanisms for generating starting points and the convergence characteristics of our EM algorithm against a recently proposed Weighted Least Squares approach.