Neural networks,rational functions,and realization theory

The problem of parametrizing single hidden layer scalar neural networks with continuous activation functions is investigated. A connection is drawn between realization theory for linear dynamical systems, rational functions, and neural networks that appears to be new. A result of this connection is a general parametrization of such neural networks in terms of strictly proper rational functions. Some existence and uniqueness results are derived. Jordan decompositions are developed, which show how the general form can be expressed in terms of a sum of canonical second order sections. The parametrization may be useful for studying learning algorithms.This work was supported by the Australian Research Council, the Australian Telecommunications and Electronics Research Board, and the Boeing Commencai Aircraft Company (thanks to John Moore).     

Towards the automatic generation of software diagrams

The authors formulate the criteria for drawing dataflow diagrams and describe the placement and routing algorithms used in a system called MONDRIAN. A generalized approach to the question of software diagrams is proposed based on the authors' experience with MONDRIAN and a metasystem approach to the creation of CASE (computer-aided software engineering) environments. A formal approach to the definition of software objects and their graphical representation is given. The use of location constraints as a basis for generalized layout algorithms is discussed     

A peptide sequence from platelet factor 4 (CT-112) is effective in the treatment of type II collagen induced arthritis in mice

OBJECTIVE: Platelet factor 4 (PF-4) is a critical alpha chemokine in inflammation and injury responses, with multiple effects upon cellular activities. Discrete peptide sequences of the PF-4 molecule have been shown to retain biological activity. Our aim was to examine the influence of the PF-4 derived octapeptide (CT-112; TTSQVRPR) on type II collagen induced arthritis in mice, to determine if this peptide exhibited antiinflammatory properties. METHODS: DBA/1 mice were treated with CT-112 from either the time of immunization with type II collagen or from the initial onset of arthritis. RESULTS: CT-112 both prevented the development of arthritis in mice treated prophylactically and reduced progression of disease in animals treated therapeutically, and was active when delivered by either subcutaneous injection or oral gavage. No marked immunosuppressive effects were observed during CT-112 treatment, with only moderate decrease in antibody levels and mitogen responses. A significant reduction of the circulating levels of IL-1 was a consistent finding in mice treated therapeutically with CT-112. CONCLUSION: These data suggest PF-4 derived octapeptide exerts antiinflammatory effects of experimental arthritis in mice.     

Decision support in early development phases—A case study from machine engineering

In the case study presented in this paper we consider early development phases of a mechanical product. We want to evaluate different concepts and decide which one(s) to pursue. A problem in early phases is that usually no test runs are available. In our case study, based on a standard, there are ways to compute the lifetime distributions of the components of the different concepts. Some parameters needed for these computations are not known precisely. Unfortunately, the lifetime distributions of the components are highly sensitive to these parameters. Our approach is to equip these parameters with distributions. These distributions would be called prior distributions in Bayesian terminology, but no update is possible since no test runs are available. Our approach implies that the distribution of the system lifetime for each concept is random, i.e. we get random elements in the space of lifetime distributions. Using Monte-Carlo simulations, we demonstrate several ways to compare the random lifetime distributions of the concepts. Some of these comparisons use stochastic orderings. We also introduce a new stochastic ordering which is particularly suitable for reliability purposes. Our case study, consisting of three scenarios, allows us to demonstrate some conclusions that can be reached.     

Quantitative measurement of gas hold-up distribution in a stirred chemical reactor using X-ray cone-beam computed tomography

Cone-beam type X-ray computed tomography (CBCT) is a potential method to measure three-dimensional phase distributions in vessels. An example for that is the measurement of gas profiles in stirred chemical reactors. Such data are highly valuable for the assessment and evaluation of chemical processes, for optimisation of the reactor and stirrer design, and for evaluation of computational fluid dynamics codes used to model the fluid flow and heat transfer in reactive systems. However, there are considerable difficulties for accurate quantitative measurements due to beam hardening and radiation scattering effects. In a theoretical and experimental work we have investigated the non-linear effects of both physical phenomena and developed a suitable measurement setup as well as calibration and software correction methods to achieve a highly accurate measurement of void fraction profiles with CBCT.