Supervisory Control for Real-Time Systems Based on Conflict-Tolerant Controllers

This paper addresses the problem of detecting and resolving conflicts due to timing constraints imposed by features in real-time and hybrid systems. We consider systems composed of a base system with multiple features or controllers, each of which independently advise the system on how to react to input events so as to conform to their individual specifications. We propose a methodology for developing such systems in a modular manner based on the notion of conflict-tolerant features that are designed to continue offering advice even when their advice has been overridden in the past. We give a simple priority-based scheme forcomposing such features. This guarantees the maximal use of each feature. We provide a formal framework for specifying such features, and a compositional technique for verifying systems developed in this framework.

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

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.

Computation-Based Reliability Analysis in Real Time Applications

Reliability analysis for computing systems in aerospace applications must account for actual computations the system performs in the use environment. This paper introduces a theoretical nonhomogeneous Markov model for such applications.

A simple method for the measurement of stress in evaporated thin films by real-time holographic interferometry

The properties of thin films depend to a large extent upon their mechanical stability which in turn is dependent on the intrinsic stresses developed during evaporation. This paper describes a simple method for the measurement of stresses in thin films by the use of real-time holographic interferometry.

Real-time multipurpose reservoir operation: a case study / Exploitation en temps reacuteel d'un reservoir agrave buts multiples: eacutetude d'un cas

A real-time operational methodology has been developed for multipurpose reservoir operation for irrigation and hydropower generation with application to the Bhadra reservoir system in the state of Karnataka, India. The methodology consists of three phases of computer modelling. In the first phase, the optimal release policy for a given initial storage and inflow is determined using a stochastic dynamic programming (SDP) model. Streamflow forecasting using an adaptive AutoRegressive Integrated Moving Average (ARIMA) model constitutes the second phase. A real-time simulation model is developed in the third phase using the forecast inflows of phase 2 and the operating policy of phase 1. A comparison of the optimal monthly real-time operation with the historical operation demonstrates the relevance, applicability and the relative advantage of the proposed methodology.

Specification of Real-Time Systems

Inspite of numerous research advancements made in recent years in the area of formal techniques, specification of real-time systems is still proving to be a very challenging and difficult problem. In this context, this paper critically examines state-of-the-art specification techniques for real-time systems and analyzes the emerging trends.

Real-time Computer Simulation of Three Dimensional Elastostatics using the Finite Point Method

Real-time simulation of deformable solids is essential for some applications such as biological organ simulations for surgical simulators. In this work, deformable solids are approximated to be linear elastic, and an easy and straight forward numerical technique, the Finite Point Method (FPM), is used to model three dimensional linear elastostatics. Graphics Processing Unit (GPU) is used to accelerate computations. Results show that the Finite Point Method, together with GPU, can compute three dimensional linear elastostatic responses of solids at rates suitable for real-time graphics, for solids represented by reasonable number of points.

Conflict-Tolerant Real-Time Specifications in Metric Temporal Logic

A framework based on the notion of "conflict-tolerance" was proposed in as a compositional methodology for developing and reasoning about systems that comprise multiple independent controllers. A central notion in this framework is that of a "conflict-tolerant" specification for a controller. In this work we propose a way of defining conflict-tolerant real-time specifications in Metric Interval Temporal Logic (MITL). We call our logic CT-MITL for Conflict-Tolerant MITL. We then give a clock optimal "delay-then-extend" construction for building a timed transition system for monitoring past-MITL formulas. We show how this monitoring transition system can be used to solve the associated verification and synthesis problems for CT-MITL.

Real-time kinetic analysis of hCG-monoclonal antibody interaction using radiolabeled hCG probe: presence of two forms of Ag-mAb complex as revealed by solid phase dissociation studies

Real-time kinetics of ligand-ligate interaction has predominantly been studied by either fluorescence or surface plasmon resonance based methods. Almost all such studies are based on association between the ligand and the ligate. This paper reports our analysis of dissociation data of monoclonal antibody-antigen (hCG) system using radio-iodinated hCG as a probe and nitrocellulose as a solid support to immobilize mAb. The data was analyzed quantitatively for a one-step and a two-step model. The data fits well into the two-step model. We also found that a fraction of what is bound is non-dissociable (tight-binding portion (TBP)). The TBP was neither an artifact of immobilization nor does it interfere with analysis. It was present when the reaction was carried out in homogeneous solution in liquid phase. The rate constants obtained from the two methods were comparable. The work reported here shows that real-time kinetics of other ligand-ligate interaction can be studied using nitrocellulose as a solid support. (C) 2002 Elsevier Science B.V. All rights reserved.

A Real-time clustering system for spatio-temporal signals from network of neurons

Over past few years, the studies of cultured neuronal networks have opened up avenues for understanding the ion channels, receptor molecules, and synaptic plasticity that may form the basis of learning and memory. The hippocampal neurons from rats are dissociated and cultured on a surface containing a grid of 64 electrodes. The signals from these 64 electrodes are acquired using a fast data acquisition system MED64 (Alpha MED Sciences, Japan) at a sampling rate of 20 K samples with a precision of 16-bits per sample. A few minutes of acquired data runs in to a few hundreds of Mega Bytes. The data processing for the neural analysis is highly compute-intensive because the volume of data is huge. The major processing requirements are noise removal, pattern recovery, pattern matching, clustering and so on. In order to interface a neuronal colony to a physical world, these computations need to be performed in real-time. A single processor such as a desk top computer may not be adequate to meet this computational requirements. Parallel computing is a method used to satisfy the real-time computational requirements of a neuronal system that interacts with an external world while increasing the flexibility and scalability of the application. In this work, we developed a parallel neuronal system using a multi-node Digital Signal processing system. With 8 processors, the system is able to compute and map incoming signals segmented over a period of 200 ms in to an action in a trained cluster system in real time.