Real-Time Simulation of Electrical Machines on FPGA Platform

This paper presents real-time simulation models of electrical machines on FPGA platform. Implementation of the real-time numerical integration methods with digital logic elements is discussed. Several numerical integrations are presented. A real-time simulation of DC machine is carried out on this FPGA platform and important transient results are presented. These results are compared to simulation results obtained through a commercial off-line simulation software

Flexible Budgeting under Uncertainty: A Real Options Perspective

This paper examines the relationships between uncertainty and the perceived usefulness of traditional annual budgets versus flexible budgets in 95 Swedish companies. We form hypotheses that the perceived usefulness of the annual budgets as well as the attitudes to more flexible budget alternatives are influenced by the uncertainty that the companies face. Our study distinguishes between two separate kinds of uncertainty: exogenous stochastic uncertainty (deriving from the firm’s environment) and endogenous deterministic uncertainty (caused by the strategic choices made by the firm itself). Based on a structural equations modelling analysis of data from a mail survey we found that the more accentuated exogenous uncertainty a company faces, the more accentuated is the expected trend towards flexibility in the budget system, and vice versa; the more endogenous uncertainty they face, the more negative are their attitudes towards budget flexibility. We also found that these relationships were not present with regard to the attitudes towards the usefulness of the annual budget. Noteworthy is, however, that there was a significant negative relationship between the perceived usefulness of the annual budget and budget flexibility. Thus, our results seem to indicate that the degree of flexibility in the budget system is influenced by both general attitudes towards the usefulness of traditional budgets and by the actual degree of exogenous uncertainty a company faces and by the strategy that it executes.

Optimal Risk Adoption: A Real Options Approach

This study develops a real options approach for analyzing the optimal risk adoption policy in an environment where the adoption means a switch from one stochastic flow representation into another. We establish that increased volatility needs not decelerate investment, as predicted by the standard literature on real options, once the underlying volatility of the state is made endogenous. We prove that for a decision maker with a convex (concave) objective function, increased post-adoption volatility increases (decreases) the expected cumulative present value of the post-adoption profit flow, which consequently decreases (increases) the option value of waiting and, therefore, accelerates (decelerates) current investment.

Real Estate Investment and Uncertainty: Econometric Modelling using Finnish Data

The purpose of this paper is to test for the effect of uncertainty in a model of real estate investment in Finland during the hihhly cyclical period of 1975 to 1998. We use two alternative measures of uncertainty. The first measure is the volatility of stock market returns and the second measure is the heterogeneity in the answers of the quarterly business survey of the Confederation of Finnish Industry and Employers. The econometric analysis is based on the autoregressive distributed lag (ADL) model and the paper applies a 'general-to-specific' modelling approach. We find that the measure of heterogeneity is significant in the model, but the volatility of stock market returns is not. The empirical results give some evidence of an uncertainty-induced threshold slowing down real estate investment in Finland.

Dynamic programming based optimum non-uniform samples for speech reconstruction and coding

Non-uniform sampling of a signal is formulated as an optimization problem which minimizes the reconstruction signal error. Dynamic programming (DP) has been used to solve this problem efficiently for a finite duration signal. Further, the optimum samples are quantized to realize a speech coder. The quantizer and the DP based optimum search for non-uniform samples (DP-NUS) can be combined in a closed-loop manner, which provides distinct advantage over the open-loop formulation. The DP-NUS formulation provides a useful control over the trade-off between bitrate and performance (reconstruction error). It is shown that 5-10 dB SNR improvement is possible using DP-NUS compared to extrema sampling approach. In addition, the close-loop DP-NUS gives a 4-5 dB improvement in reconstruction error.

Minimum enclosing spheres formulations for support vector ordinal regression

We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples. Both approaches guarantee that the radii of the spheres are properly ordered at the optimal solution. The size of the optimization problem is linear in the number of training samples. The popular SMO algorithm is adapted to solve the resulting optimization problem. Numerical experiments on some real-world data sets verify the usefulness of our approaches for data mining.

Real-time image denoising algorithm in teleradiology systems - art.no.606304

Denoising of medical images in wavelet domain has potential application in transmission technologies such as teleradiology. This technique becomes all the more attractive when we consider the progressive transmission in a teleradiology system. The transmitted images are corrupted mainly due to noisy channels. In this paper, we present a new real time image denoising scheme based on limited restoration of bit-planes of wavelet coefficients. The proposed scheme exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each sub-band. The desired bit-rate control is achieved by applying the restoration on a limited number of bit-planes subject to the optimal smoothing. The proposed method adapts itself to the preference of the medical expert; a single parameter can be used to balance the preservation of (expert-dependent) relevant details against the degree of noise reduction. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with unrestored case, in context of error reduction. It also has capability to adapt to situations where noise level in the image varies and with the changing requirements of medical-experts. The applicability of the proposed approach has implications in restoration of medical images in teleradiology systems. The proposed scheme is computationally efficient.

Double time window targeting technique: Real-time DMRG dynamics in the Pariser-Parr-Pople model

We present a generalized adaptive time-dependent density matrix renormalization-group (DMRG) scheme, called the double time window targeting (DTWT) technique, which gives accurate results with nominal computational resources, within reasonable computational time. This procedure originates from the amalgamation of the features of pace keeping DMRG algorithm, first proposed by Luo et al. [Phys. Rev. Lett. 91, 049701 (2003)] and the time-step targeting algorithm by Feiguin and White [Phys. Rev. B 72, 020404 (2005)]. Using the DTWT technique, we study the phenomena of spin-charge separation in conjugated polymers (materials for molecular electronics an spintronics), which have long-range electron-electron interactions and belong to the class of strongly correlated low-dimensional many-body systems. The issue of real-time dynamics within the Pariser-Parr-Pople (PPP) model which includes long-range electron correlations has not been addressed in the literature so far. The present study on PPP chains has revealed that, (i) long-range electron correlations enable both the charge and spin degree of freedom of the electron, to propagate faster in the PPP model compared to Hubbard model, (ii) for standard parameters of the PPP model as applied to conjugated polymers, the charge velocity is almost twice that of the spin velocity, and (iii) the simplistic interpretation of long-range correlations by merely renormalizing the U value of the Hubbard model fails to explain the dynamics of doped holes/electrons in the PPP model.

Elusive superconductivity in polycrystalline samples of layered lanthanum nickelates

La2-xNiO4, La2-xSrxNiO4 and related layered nickelates have been investigated for possible presence of superconductivity. While there is clear onset of diamagnetism around 20 K in many of these nickelates, we do not, however, find any anomaly in the electrical resistivity, magnetoresistance or thermopower around 20 K. High energy spectroscopic studies show Ni to be in the 2+ oxidation state accompanied by a substantial proportion of oxygen holes.

Myotonic dystrophy type 2 (DM2) : Diagnostic methods and molecular pathology

Myotonic dystrophies type 1 (DM1) and type 2 (DM2) are the most common forms of muscular dystrophy affecting adults. They are autosomal dominant diseases caused by microsatellite tri- or tetranucleotide repeat expansion mutations in transcribed but not translated gene regions. The mutant RNA accumulates in nuclei disturbing the expression of several genes. The more recently identified DM2 disease is less well known, yet more than 300 patients have been confirmed in Finland thus far, and the true number is believed to be much higher. DM1 and DM2 share some features in general clinical presentation and molecular pathology, yet they show distinctive differences, including disease severity and differential muscle and fiber type involvement. However, the molecular differences underlying DM1 and DM2 muscle pathology are not well understood. Although the primary tissue affected is muscle, both DMs show a multisystemic phenotype due to wide expression of the mutation-carrying genes. DM2 is particularly intriguing, as it shows an incredibly wide spectrum of clinical manifestations. For this reason, it constitutes a real diagnostic challenge. The core symptoms in DM2 include proximal muscle weakness, muscle pain, myotonia, cataracts, cardiac conduction defects and endocrinological disturbations; however, none of these is mandatory for the disease. Myalgic pains may be the most disabling symptom for decades, sometimes leading to incapacity for work. In addition, DM2 may cause major socio-economical consequences for the patient, if not diagnosed, due to misunderstanding and false stigmatization. In this thesis work, we have (I) improved DM2 differential diagnostics based on muscle biopsy, and (II) described abnormalities in mRNA and protein expression in DM1 and DM2 patient skeletal muscles, showing partial differences between the two diseases, which may contribute to muscle pathology in these diseases. This is the first description of histopathological differences between DM1 and DM2, which can be used in differential diagnostics. Two novel high-resolution applications of in situ -hybridization have been described, which can be used for direct visualization of the DM2 mutation in muscle biopsy sections, or mutation size determination on extended DNA-fibers. By measuring protein and mRNA expression in the samples, differential changes in expression patterns affecting contractile proteins, other structural proteins and calcium handling proteins in DM2 compared to DM1 were found. The dysregulation at mRNA level was caused by altered transciption and abnormal splicing. The findings reported here indicate that the extent of aberrant splicing is higher in DM2 compared to DM1. In addition, the described abnormalities to some extent correlate to the differences in fiber type involvement in the two disorders.

A simple low-cost electrical switching analyzer for I-V characterization of switching samples and devices

The phenomena of nonlinear I-V behavior and electrical switching find extensive applications in power control, information storage, oscillators, etc. The study of I-V characteristics and switching parameters is necessary for the proper application of switching materials and devices. In the present work, a simple low-cost electrical switching analyzer has been developed for the measurement of the electrical characteristics of switching materials and devices. The system developed consists of a microcontroller-based excitation source and a high-speed data acquisition system. The design details of the excitation source, its interface with the high-speed data acquisition system and personal computer, and the details of the application software developed for automated measurements are described. Typical I-V characteristics and switching curves obtained with the system developed are also presented to illustrate the capability of the instrument developed.