On the reduction of repetitive processes into singular and non-singular Roesser models

Multidimensional Systems and Signal Processing - In this paper we present new methods for the reduction of a polynomial system matrix describing a discrete linear repetitive process, to equivalent...     

Latent risk and trend models for the evolution of annual fatality numbers in 30 European countries

In this paper a unified methodology is presented for the modelling of the evolution of road safety in 30 European countries. For each country, annual data of the best available exposure indicator and of the number of fatalities were simultaneously analysed with the bivariate latent risk time series model. This model is based on the assumption that the amount of exposure and the number of fatalities are intrinsically related. It captures the dynamic evolution in the fatalities as the product of the dynamic evolution in two latent trends: the trend in the fatality risk and the trend in the exposure to that risk. Before applying the latent risk model to the different countries it was first investigated and tested whether the exposure indicator at hand and the fatalities in each country were in fact related at all. If they were, the latent risk model was applied to that country; if not, a univariate local linear trend model was applied to the fatalities series only, unless the latent risk time series model was found to yield better forecasts than the univariate local linear trend model. In either case, the temporal structure of the unobserved components of the optimal model was established, and structural breaks in the trends related to external events were identified and captured by adding intervention variables to the appropriate components of the model. As a final step, for each country the optimally modelled developments were projected into the future, thus yielding forecasts for the number of fatalities up to and including 2020.     

E-commerce: protecting purchaser privacy to enforce trust

It has been well documented that lack of trust between commercial entities and purchasers can restrict the potential of e-commerce. This may be because the purchaser is required to provide personal information to the commercial entity, which may then be abused, or because the purchaser may be suspicious that after payment has been processed, the goods purchased will not arrive. The challenge for the researcher is to determine the e-commerce model which maximizes the trust a purchaser has when shopping online.     

Minimal state space realisation of product factorable 2-D systems

A simple technique is presented for the minimal state space realisation of product factorable two dimensional systems. The application of this method yields the matrices A, b, c/sup T/ and the scalar d of the two dimensional Givone-Roesser state space model, having minimal dimension.<>     

Forward, backward, and symmetric solutions of discrete ARMA representations

The main objective of this paper is to determine a closed formula for the forward, backward, and symmetric solution of a general discrete-time Autoregressive Moving Average representation. The importance of this formula is that it is easily implemented in a computer algorithm and gives rise to the solution of analysis, synthesis, and design problems.     

Waveform classification and information extraction from LIDAR databy neural networks

Two different neural network schemes for the classification of light detection and ranging (LIDAR) waveforms for the LARSEN 500 airborne system and for extraction of ocean information are proposed. The first method employs a single layer of linear neurons for classification of waveforms into various clusters. Both unsupervised and supervised learning algorithms have been employed to demonstrate the spatial distribution of milt in near-shore waters. In the second method, a new multistage multilayer feedforward architecture is used for the classification of the waveforms and for the extraction of various types of ocean information. The stage I networks work in a parallel fashion and map the input waveforms to a set of characteristics. The networks in stage II use these characteristics to assign a signature number to the waveform or extract other information. Both the schemes are used with real-world data collected by the LARSEN 500 system. The paper concludes with experimental results and comparisons     

Aspergillus spp., distribution, population composition and ochratoxin A production in wine producing vineyards in Greece

Vineyard surveys of 11 wine producing grape cultivars, were carried out in sixteen vineyards, in five winemaking regions in Greece, during 2002 and 2003. The occurrence of various Aspergillus spp. in bunches of berries at setting, veraison and ripening at harvest time was investigated. Aspergillus niger aggregate and A. carbonarius were predominantly isolated from sampled berries. Although the prevailing Aspergillus spp. isolates belonged to A. niger aggregate, isolates of A. carbonarius were the most efficient ochratoxin A (OTA) producers. Of 50 tested isolates of A. carbonarius 42% produced amounts of OTA, exceeding 25 ppb, while none of the 85 isolates of A. niger aggregate tested produced above 16 ppb.