Abstract
Addresses the problem of transmitting real-time periodic traffic in a DQDB network. In a DQDB network, connection-oriented isochronous services use the pre-arbitrated (PA) access. The standard specifies that isochronous connections must have guaranteed periodic bandwidth but mechanisms to provide it, such as the slot allocation scheme, are not described. We propose a real-time service provider (RTSP) based on the use of the PA access. The RTSP consists of an off-line centralized scheduling algorithm and an on-line mode change algorithm which allows to take into account load changes. Means are also provided to guarantee a minimum fairness level for the asynchronous traffic. © 1994 IEEE.

Abstract

Abstract

Abstract

Abstract
This paper addresses the problem of buying commodities through the futures markets and deals specifically with a heuristic rule developed for the scenario described as ‘purchasing under a deadline’. The rule is based on a short-term forecasts produced by Taylor’s price-trend model. In a previous study applied to the Chicago Board of Trade (CBOT) corn futures market the price-trend parameters of the stochastic process generating the daily returns were shown to be nearly stable over time and hence could be estimated using a static procedure. However, the analysis presented in this paper concerning the CBOT soybean futures market strongly suggests that those parameters were unstable, impairing the successful application of the purchasing rule. The authors recommend the continuous CUSUM monitoring of the purchasing results and propose a procedure for dynamically calibrating the price-trend and buying parameters. Under this procedure the price-trend parameter estimates are derived from exponentially smoothed sample autocorrelation coefficients of the rescaled daily returns. The procedure was developed and tested using the 1972-87 series of CBOT daily soybean futures closing prices. The results suggest that it leads to an improvement on the purchasing results derived from the static parameter calibration procedure formerly adopted. © 1994 Operational Research Society Ltd.

Abstract
The proper analysis and successful operation of a power system implies a reliable estimate of its state. As a result the State Estimation (SE) is nowadays considered as the heart of the modern control centers. Several dynamic state estimation algorithms based on the extended Kalman filtering theory (EKF) have been proposed in the literature but as it has been reported numerical problems may arise in its implementation in practice. To circumvent the problems inherent to the Kalman filter algorithm we present in this paper an algorithm for power system state estimation based in the square root filtering technique. The estimator proposed is decoupled in nature due to modifications made in the measurement equations resulting in a new observation model.