Values of enzyme kinetic parameters are a key requisite for the kinetic modelling of biochemical systems. For most kinetic parameters, however, not even an order of magnitude is known, so the estimation of model parameters from experimental data remains a major task in systems biology. We propose a statistical approach to infer values for kinetic parameters across species and enzymes making use...

Search engines are based on models to index documents, match queries and documents and rank documents. Research in Information Retrieval (IR) aims at defining these models and their parameters in order to optimize the results. Using benchmark collections, it has been shown that there is not a best system configuration that works for any query, but rather that performance varies from one query t...

In digital communications systems, interleavers are used to stir bits of channel coded data to robust against burst error in noisy channel. However, in non-cooperative context such as signal intelligence system(SIGINT) and spectrum surveillance systems, interleaver may act as encryptor to 3 party listener who has no information about the interleaver parameters used in transmitter. Therefore, bl...

Interest in hybrid methods that combine artificial neural networks and evolutionary algorithms has grown in the last few years, due to their robustness and ability to design networks by setting initial weight values, by searching the architecture and the learning rule and parameters. This paper presents an exhaustive analysis of the G-Prop method, and the different parameters the method require...

We consider the class of image recovery problems where the desired image appears as the spatially-varying coefficients of a partial differential equation (PDE), the data consists of measured values on the boundary, and the forward map can only be adequately simulated by solving the PDE subject to boundary conditions. This is the natural mathematical setting for non-invasive imaging using strong...

Models of biochemical regulation in prokaryotes and eukaryotes, typically consisting of a set of first-order nonlinear ordinary differential equations, have become increasingly popular of late. These systems have large numbers of poorly known parameters, simplified dynamics, and uncertain connectivity: three key features of a class of problems we call sloppy models, which are shared by many oth...

Biological models typically depend on many parameters. Assigning suitable values to such parameters enables model individualisation. In our clinical setting, this means finding a model for a given patient. Parameter values cannot be assigned arbitrarily, since inter-dependency constraints among them are not modelled and ignoring such constraints leads to biologically meaningless model behaviour...

It has become widely recognized that many types of statistical data only partially identify the parameters of interest as simple as population means, meaning that the parameters cannot be estimated with arbitrary precision simply by increasing the sample size. Statisticians designing surveys and experiments which generate such data could use limited resources either to reduce the extent of part...

Recently we need to manage statistical process controls to maintain product quality based on the sensor technology such as small thermometers and displacement sensors, which can give as vast information on production parameters. In bag-making process, the strength of bags is very difficult to estimate without any distraction of products, and it sometimes needs a large sample size. In place of t...

In order to obtain concrete results, we focus on estimation of the treatment specific mean, controlling for all measured baseline covariates, based on observing independent and identically distributed copies of a random variable consisting of baseline covariates, a subsequently assigned binary treatment, and a final outcome. The statistical model only assumes possible restrictions on the condit...