A comparison between bond graphs switching modelling techniques implemented on a boost dc-dc converter

A Bond Graph is a graphical modelling technique that allows the representation of energy flow between the components of a system. When used to model power electronic systems, it is necessary to incorporate bond graph elements to represent a switch. In this paper, three different methods of modelling switching devices are compared and contrasted: the Modulated Transformer with a binary modulation ratio (MTF), the ideal switch element, and the Switched Power Junction (SPJ) method. These three methods are used to model a dc-dc Boost converter and then run simulations in MATLAB/SIMULINK. To provide a reference to compare results, the converter is also simulated using PSPICE. Both quantitative and qualitative comparisons are made to determine the suitability of each of the three Bond Graph switch models in specific power electronics applications

Improvement of link failure restoration utilising multi-protocol label switching (MPLS) as a means to maintain quality of service (QOS)

This paper proposes a practical approach to the enhancement of Quality of Service (QoS) routing by means of providing alternative or repair paths in the event of a breakage of a working path. The proposed scheme guarantees that every Protected Node (PN) is connected to a multi-repair path such that no further failure or breakage of single or double repair paths can cause any simultaneous loss of connectivity between an ingress node and an egress node. Links to be protected in an MPLS network are predefined and a Label Switched path (LSP) request involves the establishment of a working path. The use of multi-protection paths permits the formation of numerous protection paths allowing greater flexibility. Our analysis examined several methods including single, double and multi-repair routes and the prioritization of signals along the protected paths to improve the Quality of Service (QoS), throughput, reduce the cost of the protection path placement, delay, congestion and collision. Results obtained indicated that creating multi-repair paths and prioritizing packets reduces delay and increases throughput in which case the delays at the ingress/egress LSPs were low compared to when the signals had not been classified. Therefore the proposed scheme provided a means to improve the QoS in path restoration in MPLS using available network resources. Prioritizing the packets in the data plane has revealed that the amount of traffic transmitted using a medium and low priority Label Switch Paths (LSPs) does not have any impact on the explicit rate of the high priority LSP in which case the problem of a knock-on effect is eliminated.

A single director switching mode for monodomain liquid crystal elastomer

We report rotation of a single director in a nematic monodomain, acrylate based side-chain elastomer which was subjected to mechanical fields applied at angles in the range to the director, , present at the time of network formation. Time and spatially resolving wide angle X-ray scattering, together with polarised light microscopy measurements revealed a pronounced, almost discontinuous switching mode at a critical extension as the strain was applied at angles approaching to , whereas a more continuous rotation was seen when the strain was applied at more acute angles. This director reorientation was more or less uniform across the complete sample and was accompanied by a modest decrease in orientation parameter . At strains sufficient to induce switching there was some continuous distribution of director orientations with fluctuations of 10 although there was no evidence for any localised director inhomogenities such as domain formation. The observed deformation behaviour of these acrylate-based nematic monodomains was in accord with the predictions of a theory developed by Bladon et al., in that the complete set of data could be accounted for through a single parameter describing the chain anisotropy. The experimentally deduced chain anisotropy parameter was in broad agreement with that obtained from small-angle neutron scattering procedures, but was somewhat greater than that obtained by spontaneous shape changes at the nematic-isotropic transition.

Persistence of UK Real Estate returns: a Markov chain analysis

The persistence of investment performance is a topic of perennial interest to investors. Efficient Markets theory tells us that past performance can not be used to predict future performance yet investors appear to be influenced by the historical performance in making their investment allocation decisions. The problem has been of particular interest to investors in real estate; not least because reported returns from investment in real estate are serially correlated thus implying some persistence in investment performance. This paper applies the established approach of Markov Chain analysis to investigate the relationship between past and present performance of UK real estate over the period 1981 to 1996. The data are analysed by sector, region and size. Furthermore some variations in investment performance classification are reported and the results are shown to be robust.

Property company performance and real interest rates: a regime-switching approach

Linear models of property market performance may be misspecified if there exist distinct states where the market drivers behave in different ways. This paper examines the applicability of non-linear regime-based models. A Self Exciting Threshold Autoregressive (SETAR) model is applied to property company share data, using the real rate of interest to define regimes. Distinct regimes appear exhibiting markedly different market behaviour. The model both casts doubt on the specification of conventional linear models and offers the possibility of developing effective trading rules for real estate equities.

Markov models of aging: theory and practice

We review and structure some of the mathematical and statistical models that have been developed over the past half century to grapple with theoretical and experimental questions about the stochastic development of aging over the life course. We suggest that the mathematical models are in large part addressing the problem of partitioning the randomness in aging: How does aging vary between individuals, and within an individual over the lifecourse? How much of the variation is inherently related to some qualities of the individual, and how much is entirely random? How much of the randomness is cumulative, and how much is merely short-term flutter? We propose that recent lines of statistical inquiry in survival analysis could usefully grapple with these questions, all the more so if they were more explicitly linked to the relevant mathematical and biological models of aging. To this end, we describe points of contact among the various lines of mathematical and statistical research. We suggest some directions for future work, including the exploration of information-theoretic measures for evaluating components of stochastic models as the basis for analyzing experiments and anchoring theoretical discussions of aging.

Bayesian parameter estimation for latent Markov random fields and social networks

Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an intractable normalising constant. This problem has received much attention, but very little of this has focussed on the important practical case where the data consists of noisy or incomplete observations of the underlying hidden structure. This paper specifically addresses this problem, comparing two alternative methodologies. In the first of these approaches particle Markov chain Monte Carlo (Andrieu et al., 2010) is used to efficiently explore the parameter space, combined with the exchange algorithm (Murray et al., 2006) for avoiding the calculation of the intractable normalising constant (a proof showing that this combination targets the correct distribution in found in a supplementary appendix online). This approach is compared with approximate Bayesian computation (Pritchard et al., 1999). Applications to estimating the parameters of Ising models and exponential random graphs from noisy data are presented. Each algorithm used in the paper targets an approximation to the true posterior due to the use of MCMC to simulate from the latent graphical model, in lieu of being able to do this exactly in general. The supplementary appendix also describes the nature of the resulting approximation.

Towards a uniform approach to code-switching and borrowing

This is one of the first papers in which arguments are given to treat code-switching and borrowing as similar phenomena. It is argued that it is theoretically undesirable to distinguish both phenomena, and empirically very problematic. A probabilistic account of code-switching and a hierarchy of switched constituents (similar to hierarchies of borrowability) are proposed which account for the fact that some constituents are more likely to be borrowed/switched than others. It is argued that the same kinds of constraints apply to both code-switching and borrowing.

Analytical calculation of resonant inductance for zero voltage switching in phase-shifted full-bridge converters

The phase shift full bridge (PSFB) converter allows high efficiency power conversion at high frequencies through zero voltage switching (ZVS); the parasitic drain-to-source capacitance of the MOSFET is discharged by a resonant inductance before the switch is gated resulting in near zero turn-on switching losses. Typically, an extra inductance is added to the leakage inductance of a transformer to form the resonant inductance necessary to charge and discharge the parasitic capacitances of the PSFB converter. However, many PSFB models do not consider the effects of the magnetizing inductance or dead-time in selecting the resonant inductance required to achieve ZVS. The choice of resonant inductance is crucial to the ZVS operation of the PSFB converter. Incorrectly sized resonant inductance will not achieve ZVS or will limit the load regulation ability of the converter. This paper presents a unique and accurate equation for calculating the resonant inductance required to achieve ZVS over a wide load range incorporating the effects of the magnetizing inductance and dead-time. The derived equations are validated against PSPICE simulations of a PSFB converter and extensive hardware experimentations.

Digital code-switching between Cypriot and Standard Greek: performance and identity play online

Studies of code-switching in writing are very limited in comparison with the numerous investigations of this phenomenon in oral communication. Recent research has revealed that in text-based computer-mediated communication internet users bring into play the various languages available in their linguistic repertoire and, consequently, switch between them. In this case study, I investigate digital code-switching between Cypriot and Standard Greek, the two varieties of Greek spoken on the island of Cyprus. Following Auer’s conversation analytic approach and Gafaranga’s view that conversational structure coexists with social structure, I investigate code-switching in online interactions. The data to be analysed here, unlike those considered in most studies of code-switching, are written data, obtained from channel #Cyprus of Internet Relay Chat. The results suggest that code-switching in writing is influenced not only by macro-sociolinguistic factors, but they are also shaped by the medium- and social-specific characteristics of Internet Relay Chat. This, in turn, allows internet users to gain access to different roles and perform various identities within this online context.

Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels

Monte Carlo algorithms often aim to draw from a distribution π by simulating a Markov chain with transition kernel P such that π is invariant under P. However, there are many situations for which it is impractical or impossible to draw from the transition kernel P. For instance, this is the case with massive datasets, where is it prohibitively expensive to calculate the likelihood and is also the case for intractable likelihood models arising from, for example, Gibbs random fields, such as those found in spatial statistics and network analysis. A natural approach in these cases is to replace P by an approximation Pˆ. Using theory from the stability of Markov chains we explore a variety of situations where it is possible to quantify how ’close’ the chain given by the transition kernel Pˆ is to the chain given by P . We apply these results to several examples from spatial statistics and network analysis.