Developing parallel discrete event simulation programs is a difficult and time consuming process often ending with disappointment as the achieved performance is often lower than expected. Developers need performance prediction tools that are capable of providing information on the future performance of the parallel program prior to implementation. This paper describes a performance analyser too...

A flow injection method (FI) for the sequential determination of ethanol and acetic acid in vinegar is reported. The determination of ethanol is based on the oxidation of the pervaporated ethanol by K2Cr2O7. The acetic acid is determined by an acid-base reaction with Thymol Blue as the indicator. Both reactions are monitored photometrically at 600 nm using a single detector. Optimisation studie...

This paper presents a methodology for automatic generation of massive parallel simulation systems to estimate the power consumption of sequential CMOS circuits. Based on a high level description of Finite State Machines C++ simulator code is being generated to estimate the power consumption of a CMOS based implementation. From a symbolic FSM description, a Monte Carlo simulation is used to esti...

Parallel and sequential implementations of the Multi-sensor Joint Probabilistic Data Association (MSJPDA) tracking algorithm are analyzed and compared. The sequential implementation is shown to be exponentially less computationally complex as the number of sensors increases. Simulation results suggest that the sequential method also yields better tracking performance on the average. This is pri...

Companies are nowadays controlled by a mass of business figures. These business figures build a system and are typically dependent upon restrictions that arise from balance equations. The introduction of uncertainty within these figures dismisses standard mathematical formulations. Uncertainty is imposed by forecasting or estimation, but also by evaluation of stochastic process. This article gi...

We present sequential parameter estimation in the framework of the Hidden Markov Models. The sequential algorithm is a sequential Kullback proximal algorithm, which chooses the KullbackLiebler divergence as a penalty function for the maximum likelihood estimation. The scheme is implemented as £lters. In contrast to algorithms based on the sequential EM algorithm, the algorithm has faster conver...

ÐTwo fast algorithms for static test sequence compaction are proposed for sequential circuits. The algorithms are based on the observation that test sequences traverse through a small set of states and some states are frequently revisited throughout the application of a test set. Subsequences that start and end on the same states may be removed if necessary and if sufficient conditions are met ...