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