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<title>General</title>
<link>http://hdl.handle.net/10453/205</link>
<description/>
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<rdf:li rdf:resource="http://hdl.handle.net/10453/12792"/>
<rdf:li rdf:resource="http://hdl.handle.net/10453/12382"/>
<rdf:li rdf:resource="http://hdl.handle.net/10453/11807"/>
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<dc:date>2013-05-24T12:25:30Z</dc:date>
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<title>A case for contrast as a catalyst for change</title>
<link>http://hdl.handle.net/10453/12792</link>
<description>A case for contrast as a catalyst for change
Young Louise; Freeman Lynne

This is a qualitative, largely reflective, interpretive case study of our evolution from teachers of market research to educational collaborators who work with students to co-develop qualitative researchers. This case both explores the ways to extend and improve qualitative research and researchers and presents a more general, interpretivist approach to problem-solving. The case is mixed method. It reports the combination and interpretation of reflective elements including articulating our individual memories and inter-relating these in a series of discussions where we also considered the nature and meaning of our educational approaches and the effectiveness of what we are doing.
</description>
<dc:date>2008-01-01T00:00:00Z</dc:date>
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<item rdf:about="http://hdl.handle.net/10453/12382">
<title>Mining Dynamic Databases by Weighting</title>
<link>http://hdl.handle.net/10453/12382</link>
<description>Mining Dynamic Databases by Weighting
Zhang Shichao; Liu Li

A dynamic database is a set of transactions, in which the content and the size can change over time. There is an essential difference between dynamic database mining and traditional database mining. This is because recently added transactions can be more 'interesting' than those inserted long ago in a dynamic database. This paper presents a method for mining dynamic databases. This approach uses weighting techniques to increase efficiency, enabling us to reuse frequent itemsets mined previously. This model also considers the novelty of itemsets when assigning weights. In particular, this method can find a kind of new patterns from dynamic databases, referred to trend patterns. To evaluate the effectiveness and efficiency of the proposed method, we implemented our approach and compare it with existing methods.
</description>
<dc:date>2003-01-01T00:00:00Z</dc:date>
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<title>Matrix analysis techniques in cage induction machines</title>
<link>http://hdl.handle.net/10453/11807</link>
<description>Matrix analysis techniques in cage induction machines
Dorrell David

Modern analysis techniques for electrical machines are either analytical or use finite element analysis. Both methods are implemented using computational techniques to solve the magnetic circuit and produce performance predictions. This paper puts forward a steady-state impedance matrix method for analysing a split-phase induction machine that is at the leading edge of analytical modelling of induction motors. The method is implemented and verified against an example to illustrate the asynchronous torques in a non-sinusoidal winding. In the second half of the paper it is shown how the technique can be applied to a three-phase machine and the classical per-phase model is obtained from the derivation. The steady-state model derives a mathematical rigorous equivalent circuit that includes the skew reactance term in the rotor circuit.
</description>
<dc:date>2009-01-01T00:00:00Z</dc:date>
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<title>First-class patterns</title>
<link>http://hdl.handle.net/10453/11805</link>
<description>First-class patterns
Jay Barry; Kesner D

Pure pattern calculus supports pattern-matching functions in which patterns are first-class citizens that can be passed as parameters, evaluated and returned as results. This new expressive power supports two new forms of polymorphism. Path polymorphism allows recursive functions to traverse arbitrary data structures. Pattern polymorphism allows patterns to be treated as parameters which may be collected from various sources or generated from training data. A general framework for pattern calculi is developed. It supports a proof of confluence that is parameterised by the nature of the matching algorithm, Suitable for the pure pattern calculus and all other known pattern calculi.
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<dc:date>2009-01-01T00:00:00Z</dc:date>
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