Electromagnetic interference from variable speed motor drives

A methodology is presented which can be used to produce the level of electromagnetic interference, in the form of conducted and radiated emissions, from variable speed drives, the drive that was modelled being a Eurotherm 583 drive. The conducted emissions are predicted using an accurate circuit model of the drive and its associated equipment. The circuit model was constructed from a number of different areas, these being: the power electronics of the drive, the line impedance stabilising network used during the experimental work to measure the conducted emissions, a model of an induction motor assuming near zero load, an accurate model of the shielded cable which connected the drive to the motor, and finally the parasitic capacitances that were present in the drive modelled. The conducted emissions were predicted with an error of +/-6dB over the frequency range 150kHz to 16MHz, which compares well with the limits set in the standards which specify a frequency range of 150kHz to 30MHz. The conducted emissions model was also used to predict the current and voltage sources which were used to predict the radiated emissions from the drive. Two methods for the prediction of the radiated emissions from the drive were investigated, the first being two-dimensional finite element analysis and the second three-dimensional transmission line matrix modelling. The finite element model took account of the features of the drive that were considered to produce the majority of the radiation, these features being the switching of the IGBT's in the inverter, the shielded cable which connected the drive to the motor as well as some of the cables that were present in the drive.The model also took account of the structure of the test rig used to measure the radiated emissions. It was found that the majority of the radiation produced came from the shielded cable and the common mode currents that were flowing in the shield, and that it was feasible to model the radiation from the drive by only modelling the shielded cable. The radiated emissions were correctly predicted in the frequency range 30MHz to 200MHz with an error of +10dB/-6dB. The transmission line matrix method modelled the shielded cable which connected the drive to the motor and also took account of the architecture of the test rig. Only limited simulations were performed using the transmission line matrix model as it was found to be a very slow method and not an ideal solution to the problem. However the limited results obtained were comparable, to within 5%, to the results obtained using the finite element model.

On a distinction between casual and formative variable models:theoretical issues and practical implications for organizational researchers

Formative measurement has seen increasing acceptance in organizational research since the turn of the 21st Century. However, in more recent times, a number of criticisms of the formative approach have appeared. Such work argues that formatively-measured constructs are empirically ambiguous and thus flawed in a theory-testing context. The aim of the present paper is to examine the underpinnings of formative measurement theory in light of theories of causality and ontology in measurement in general. In doing so, a thesis is advanced which draws a distinction between reflective, formative, and causal theories of latent variables. This distinction is shown to be advantageous in that it clarifies the ontological status of each type of latent variable, and thus provides advice on appropriate conceptualization and application. The distinction also reconciles in part both recent supportive and critical perspectives on formative measurement. In light of this, advice is given on how most appropriately to model formative composites in theory-testing applications, placing the onus on the researcher to make clear their conceptualization and operationalisation.

Improving envelopment in Data Envelopment Analysis under variable returns to scale

In a Data Envelopment Analysis model, some of the weights used to compute the efficiency of a unit can have zero or negligible value despite of the importance of the corresponding input or output. This paper offers an approach to preventing inputs and outputs from being ignored in the DEA assessment under the multiple input and output VRS environment, building on an approach introduced in Allen and Thanassoulis (2004) for single input multiple output CRS cases. The proposed method is based on the idea of introducing unobserved DMUs created by adjusting input and output levels of certain observed relatively efficient DMUs, in a manner which reflects a combination of technical information and the decision maker's value judgements. In contrast to many alternative techniques used to constrain weights and/or improve envelopment in DEA, this approach allows one to impose local information on production trade-offs, which are in line with the general VRS technology. The suggested procedure is illustrated using real data. © 2011 Elsevier B.V. All rights reserved.

Solvability and asymptotics of the heat equation with mixed variable lateral conditions and applications in the opening of the exocytotic fusion pore in cells

We investigate a mixed problem with variable lateral conditions for the heat equation that arises in modelling exocytosis, i.e. the opening of a cell boundary in specific biological species for the release of certain molecules to the exterior of the cell. The Dirichlet condition is imposed on a surface patch of the boundary and this patch is occupying a larger part of the boundary as time increases modelling where the cell is opening (the fusion pore), and on the remaining part, a zero Neumann condition is imposed (no molecules can cross this boundary). Uniform concentration is assumed at the initial time. We introduce a weak formulation of this problem and show that there is a unique weak solution. Moreover, we give an asymptotic expansion for the behaviour of the solution near the opening point and for small values in time. We also give an integral equation for the numerical construction of the leading term in this expansion.

Multi-level visualisation using Gaussian process latent variable models

Projection of a high-dimensional dataset onto a two-dimensional space is a useful tool to visualise structures and relationships in the dataset. However, a single two-dimensional visualisation may not display all the intrinsic structure. Therefore, hierarchical/multi-level visualisation methods have been used to extract more detailed understanding of the data. Here we propose a multi-level Gaussian process latent variable model (MLGPLVM). MLGPLVM works by segmenting data (with e.g. K-means, Gaussian mixture model or interactive clustering) in the visualisation space and then fitting a visualisation model to each subset. To measure the quality of multi-level visualisation (with respect to parent and child models), metrics such as trustworthiness, continuity, mean relative rank errors, visualisation distance distortion and the negative log-likelihood per point are used. We evaluate the MLGPLVM approach on the ‘Oil Flow’ dataset and a dataset of protein electrostatic potentials for the ‘Major Histocompatibility Complex (MHC) class I’ of humans. In both cases, visual observation and the quantitative quality measures have shown better visualisation at lower levels.

Discontinuous control of multi-variable processes

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The upstream Variable Number Tandem Repeat polymorphism of the monoamine oxidase type A gene influences trigeminal pain-related evoked responses

Monoamines have an important role in neural plasticity, a key factor in cortical pain processing that promotes changes in neuronal network connectivity. Monoamine oxidase type A (MAOA) is an enzyme that, due to its modulating role in monoaminergic activity, could play a role in cortical pain processing. The X-linked MAOA gene is characterized by an allelic variant of length, the MAOA upstream Variable Number Tandem Repeat (MAOA-uVNTR) region polymorphism. Two allelic variants of this gene are known, the high-activity MAOA (HAM) and low-activity MAOA (LAM). We investigated the role of MAOA-uVNTR in cortical pain processing in a group of healthy individuals measured by the trigeminal electric pain-related evoked potential (tPREP) elicited by repeated painful stimulation. A group of healthy volunteers was genotyped to detect MAOA-uVNTR polymorphism. Electrical tPREPs were recorded by stimulating the right supraorbital nerve with a concentric electrode. The N2 and P2 component amplitude and latency as well as the N2-P2 inter-peak amplitude were measured. The recording was divided into three blocks, each containing 10 consecutive stimuli and the N2-P2 amplitude was compared between blocks. Of the 67 volunteers, 37 were HAM and 30 were LAM. HAM subjects differed from LAM subjects in terms of amplitude of the grand-averaged and first-block N2-P2 responses (HAM>LAM). The N2-P2 amplitude decreased between the first and third block in HAM subjects but not LAM subjects. The MAOA-uVNTR polymorphism seemed to influence the brain response in a repeated tPREP paradigm and suggested a role of the MAOA as a modulator of neural plasticity related to cortical pain processing. Monoamines have an important role in neural plasticity, a key factor in cortical pain processing that promotes changes in neuronal network connectivity. Monoamine oxidase type A (MAOA) is an enzyme that, due to its modulating role in monoaminergic activity, could play a role in cortical pain processing. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

The influence of socio-cultural environments on the performance of nascent entrepreneurs:an instrumental variable approach

The importance of informal institutions and in particular culture for entrepreneurship is a subject of ongoing interest. Past research has mostly concentrated on cross-national comparisons, cultural values, and the direct effects of culture on entrepreneurial behavior, but in the main found inconsistent results. The present research adds a fresh perspective to this research stream by turning attention to community-level culture and cultural norms. We hypothesize indirect effects of cultural norms on venture emergence. Specifically that community-level cultural norms (performance-based culture and socially-supportive institutional norms) impact important supply-side variables (entrepreneurial self-efficacy and entrepreneurial motivation) which in turn influence nascent entrepreneurs’ success in creating operational ventures (venture emergence). We test our predictions on a unique longitudinal data set (PSED II) tracking nascent entrepreneurs venture creation efforts over a 5 year time span and find evidence supporting them. Our research contributes to a more fine-grained understanding of how culture, in particular perceptions of community cultural norms, influences venture emergence. This research highlights the embeddedness of entrepreneurial behavior and its immediate antecedent beliefs in the local, community context.

Null Condition for Semilinear Wave Equation with Variable Coefficients

∗The author was partially supported by M.U.R.S.T. Progr. Nazionale “Problemi Non Lineari...”

Fluid, heat and mass transfer in a Venlo type greenhouse with variable boundary conditions

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Multidimensional Heterogeneous Variable Prediction Based on Experts’ Statements

* The work was supported by the RFBR under Grant N07-01-00331a.

An Approach to Variable Aggregation in Efficiency Analysis

In the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.

On Coordination of Experts’ Estimations of Quantitative Variable

* The work was supported by the RFBR under Grants N07-01-00331a, 08-07-00136a