Molecular Dynamics and Relaxation Phenomena in Glasses
Proceedings of a Workshop Held at the Zentrum für interdisziplinäre Forschung Universität Bielefeld, Bielefeld, FRG November 11–13, 1985
Chapter and Conference Paper
It is well known (1,2) that most dipolar amorphous polymers exhibit multiple dielectric relaxation processes. At low temperatures the α and β processes are observed which, on raising the temperature at a given...
Chapter and Conference Paper
The motion of molecules in the solid and liquid states may be studied using such techniques as dielectric relaxation1–4, NMR relaxation5–7, infra-red and Raman spectroscopy8–10 inelastic neutron scattering11–13 i...
Article
The most important discovery in the field of gold plating was undoubtedly the use of gold compounds in potassium cyanide solution as the electrolyte. In this article the author examines the state of diffusion ...
Chapter and Conference Paper
The article outlines our current understanding of the multiple relaxations observed in crystalline and amorphous solid polymers, as studied using dielectric techniques. An attempt is made to interpret the rela...
Chapter and Conference Paper
The essential features of the dielectric relaxation behaviour selected amorphous and crystalline polymers are considered. For amorphous polymers it is shown that three dipole relaxation processes are generally...
Chapter
The reorientational motions of molecules in the supercooled liquid state and in liquid-crystal-forming materials just above the clearing point may occur on a time-scale which is far longer than that encountere...
Book and Conference Proceedings
Proceedings of a Workshop Held at the Zentrum für interdisziplinäre Forschung Universität Bielefeld, Bielefeld, FRG November 11–13, 1985
Article
Nature 326, 544-545 (1987). IN this News and Views piece this figure was poorly printed and details of shading lost. It is a schematic representation of the rich molecular architecture of liquid-crystalline po...
Article
Article
We describe the alignment behaviour of different liquidcrystalline (LC) side-chain polymers when they are subjected to electrical/thermal treatments. It is shown that the alignment behaviour is determined by s...
Chapter
Chapter and Conference Paper
Data Mining draws on many technologies to deliver novel and actionable discoveries from very large collections of data. The Australian Government’s Cooperative Research Centre for Advanced Computational System...
Chapter and Conference Paper
Australia has extensive administrative health data collected by Commonwealth and state agencies. Using a unique cleaned and linked administrative health dataset we address the problem of empirically defining e...
Chapter and Conference Paper
We consider the problem of finding outliers in large multivariate databases. Outlier detection can be applied during the data cleansing process of data mining to identify problems with the data itself, and to ...
Chapter and Conference Paper
There are many methods for finding association rules in very large data. However it is well known that most general association rule discovery methods find too many rules, many of which are uninteresting rules...
Chapter and Conference Paper
Health databases are characterised by large number of records, large number of attributes and mild density. This encourages data miners to use methodologies that are more sensitive to health undustry specifics...
Chapter and Conference Paper
Historically the identification of adverse drug reactions relies on manual processes whereby doctors and hospitals report incidences to a central agency. In this paper we suggest a data mining approach using a...
Chapter and Conference Paper
In many real world applications, systematic analysis of rare events, such as credit card frauds and adverse drug reactions, is very important. Their low occurrence rate in large databases often makes it diffic...
Article
Outlier detection is a fundamental issue in data mining, specifically in fraud detection, network intrusion detection, network monitoring, etc. SmartSifter is an outlier detection engine addressing this proble...
Chapter and Conference Paper
An association classification algorithm has been developed to explore adverse drug reactions in a large medical transaction dataset with unbalanced classes. Rules discovered can be used to alert medical practi...