6,943 research outputs found
Data management of on-line partial discharge monitoring using wireless sensor nodes integrated with a multi-agent system
On-line partial discharge monitoring has been the subject of significant research in previous years but little work has been carried out with regard to the management of on-site data. To date, on-line partial discharge monitoring within a substation has only been concerned with single plant items, so the data management problem has been minimal. As the age of plant equipment increases, so does the need for condition monitoring to ensure maximum lifespan. This paper presents an approach to the management of partial discharge data through the use of embedded monitoring techniques running on wireless sensor nodes. This method is illustrated by a case study on partial discharge monitoring data from an ageing HVDC reactor
Case studies to enhance online student evaluation: Bond University – Surveying students online to improve learning and teaching
One of the most sensible ways of improving learning and teaching is to ask the students for feedback. At the end of each teaching period (i.e. semester or term) all universities and many schools survey their students. Usually these surveys are managed online. Questions ask for student perceptions about teaching, assessment and workload. The survey administrators report four common problems
Scattering and absorption of ultracold atoms by nanotubes
We investigate theoretically how cold atoms, including Bose-Einstein
condensates, are scattered from, or absorbed by nanotubes with a view to
analysing recent experiments. In particular we consider the role of potential
strength, quantum reflection, atomic interactions and tube vibrations on atom
loss rates. Lifshitz theory calculations deliver a significantly stronger
scattering potential than that found in experiment and we discuss possible
reasons for this. We find that the scattering potential for dielectric tubes
can be calculated to a good approximation using a modified pairwise summation
approach, which is efficient and easily extendable to arbitrary geometries.
Quantum reflection of atoms from a nanotube may become a significant factor at
low temperatures, especially for non-metallic tubes. Interatomic interactions
are shown to increase the rate at which atoms are lost to the nanotube and lead
to non-trivial dynamics. Thermal nanotube vibrations do not significantly
increase loss rates or reduce condensate fractions, but lower frequency
oscillations can dramatically heat the cloud.Comment: 7 pages, 4 figure
More on coupling coefficients for the most degenerate representations of SO(n)
We present explicit closed-form expressions for the general group-theoretical
factor appearing in the alpha-topology of a high-temperature expansion of
SO(n)-symmetric lattice models. This object, which is closely related to
6j-symbols for the most degenerate representation of SO(n), is discussed in
detail.Comment: 9 pages including 1 table, uses IOP macros Update of Introduction and
Discussion, References adde
Ad- and desorption of Rb atoms on a gold nanofilm measured by surface plasmon polaritons
Hybrid quantum systems made of cold atoms near nanostructured surfaces are
expected to open up new opportunities for the construction of quantum sensors
and for quantum information. For the design of such tailored quantum systems
the interaction of alkali atoms with dielectric and metallic surfaces is
crucial and required to be understood in detail. Here, we present real-time
measurements of the adsorption and desorption of Rubidium atoms on gold
nanofilms. Surface plasmon polaritons (SPP) are excited at the gold surface and
detected in a phase sensitive way. From the temporal change of the SPP phase
the Rubidium coverage of the gold film is deduced with a sensitivity of better
than 0.3 % of a monolayer. By comparing the experimental data with a Langmuir
type adsorption model we obtain the thermal desorption rate and the sticking
probability. In addition, also laser-induced desorption is observed and
quantified.Comment: 9 pages, 6 figure
Difference score correlations in relationship research: A conceptual primer
The practice of computing correlations between “difference” or “discrepancy” scores and an outcome variable is common in many areas of social science. Relationship researchers most commonly use difference scores to index the (dis)similarity of members of two-person relationships. Using an intuitive, graphical approach—and avoiding formulas and pointing fingers—we illustrate problems with using difference score correlations in relationship research, suggest ways to ensure that difference score correlations are maximally informative, and briefly review alternatives to difference score correlations in studying similarity, accuracy, and related constructs.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73008/1/j.1475-6811.1999.tb00206.x.pd
Detecting periodicity in experimental data using linear modeling techniques
Fourier spectral estimates and, to a lesser extent, the autocorrelation
function are the primary tools to detect periodicities in experimental data in
the physical and biological sciences. We propose a new method which is more
reliable than traditional techniques, and is able to make clear identification
of periodic behavior when traditional techniques do not. This technique is
based on an information theoretic reduction of linear (autoregressive) models
so that only the essential features of an autoregressive model are retained.
These models we call reduced autoregressive models (RARM). The essential
features of reduced autoregressive models include any periodicity present in
the data. We provide theoretical and numerical evidence from both experimental
and artificial data, to demonstrate that this technique will reliably detect
periodicities if and only if they are present in the data. There are strong
information theoretic arguments to support the statement that RARM detects
periodicities if they are present. Surrogate data techniques are used to ensure
the converse. Furthermore, our calculations demonstrate that RARM is more
robust, more accurate, and more sensitive, than traditional spectral
techniques.Comment: 10 pages (revtex) and 6 figures. To appear in Phys Rev E. Modified
styl
Group Formation Among Peer-to-Peer Agents: Learning Group Characteristics
This paper examines the decentralized formation of groups within a peer-to-peer multi-agent system. More specifically, it frames group formation as a clustering problem, and examines how to determine cluster characteristics such as area and density in the absence of information about the entire data set, such as the number of points, the number of clusters, or the maximum distance between points, that are available to centralized clustering algorithms. We develop a method in which agents individually search for other agents with similar characteristics in a peer-to-peer manner. These agents group into small centrally controlled clusters which learn cluster parameters by examining and improving their internal composition over time. We show through simulation that this method allows us to find clusters of a wide variety of sizes without adjusting agent parameters
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