Modelling of non-stationary processes using radial basis function networks

This paper reports preliminary progress on a principled approach to modelling nonstationary phenomena using neural networks. We are concerned with both parameter and model order complexity estimation. The basic methodology assumes a Bayesian foundation. However to allow the construction of pragmatic models, successive approximations have to be made to permit computational tractibility. The lowest order corresponds to the (Extended) Kalman filter approach to parameter estimation which has already been applied to neural networks. We illustrate some of the deficiencies of the existing approaches and discuss our preliminary generalisations, by considering the application to nonstationary time series.

Bistable attractors in a model of convection-driven spherical dynamos

The range of existence and the properties of two essentially different chaotic attractors found in a model of nonlinear convection-driven dynamos in rotating spherical shells are investigated. A hysteretic transition between these attractors is established as a function of the rotation parameter t. The width of the basins of attraction is also estimated. © 2012 The Royal Swedish Academy of Sciences.

Methodology for the model-driven development of self-managing systems

Based on recent advances in autonomic computing, we propose a methodology for the cost-effective development of self-managing systems starting from a model of the resources to be managed and using a general-purpose autonomic architecture.

Designing a model for a corpus-driven dictionary of academic English

University students encounter difficulties with academic English because of its vocabulary, phraseology, and variability, and also because academic English differs in many respects from general English, the language which they have experienced before starting their university studies. Although students have been provided with many dictionaries that contain some helpful information on words used in academic English, these dictionaries remain focused on the uses of words in general English. There is therefore a gap in the dictionary market for a dictionary for university students, and this thesis provides a proposal for such a dictionary (called the Dictionary of Academic English; DOAE) in the form of a model which depicts how the dictionary should be designed, compiled, and offered to students. The model draws on state-of-the-art techniques in lexicography, dictionary-use research, and corpus linguistics. The model demanded the creation of a completely new corpus of academic language (Corpus of Academic Journal Articles; CAJA). The main advantages of the corpus are its large size (83.5 million words) and balance. Having access to a large corpus of academic language was essential for a corpus-driven approach to data analysis. A good corpus balance in terms of domains enabled a detailed domain-labelling of senses, patterns, collocates, etc. in the dictionary database, which was then used to tailor the output according to the needs of different types of student. The model proposes an online dictionary that is designed as an online dictionary from the outset. The proposed dictionary is revolutionary in the way it addresses the needs of different types of student. It presents students with a dynamic dictionary whose contents can be customised according to the user's native language, subject of study, variant spelling preferences, and/or visual preferences (e.g. black and white).

Gold nanoparticles decorated with oligo(ethylene glycol) thiols:kinetics of colloid aggregation driven by depletion forces

We have studied the kinetics of the phase-separation process of mixtures of colloid and protein in solutions by real-time UV-vis spectroscopy. Complementary small-angle X-ray scattering (SAXS) was employed to determine the structures involved. The colloids used are gold nanoparticles functionalized with protein resistant oligo(ethylene glycol) (OEG) thiol, HS(CH(2))(11)(OCH(2)CH(2))(6)OMe (EG6OMe). After mixing with protein solution above a critical concentration, c*, SAXS measurements show that a scattering maximum appears after a short induction time at q = 0.0322 angstrom(-1) stop, which increases its intensity with time but the peak position does not change with time, protein concentration and salt addition. The peak corresponds to the distance of the nearest neighbor in the aggregates. The upturn of scattering intensities in the low q-range developed with time indicating the formation of aggregates. No Bragg peaks corresponding to the formation of colloidal crystallites could be observed before the clusters dropped out from the solution. The growth kinetics of aggregates is followed in detail by real-time UV-vis spectroscopy, using the flocculation parameter defined as the integral of the absorption in the range of 600-800 nm wavelengths. At low salt addition (<0.5 M), a kinetic crossover from reaction-limited cluster aggregation (RLCA) to diffusion-limited cluster aggregation (DLCA) growth model is observed, and interpreted as being due to the effective repulsive interaction barrier between colloids within the depletion potential. Above 0.5 M NaCl, the surface charge of proteins is screened significantly, and the repulsive potential barrier disappeared, thus the growth kinetics can be described by a DLCA model only.

From practice to field:a multi-level model of practice-driven institutional change

This article develops a model of practice-driven institutional change - or change that originates in the everyday work of individuals but results in a shift in field-level logic. In demonstrating how improvisations at work can generate institutional change, we attend to the earliest moments of change, which extant research has neglected; and we contrast existing accounts that focus on active entrepreneurship and the contested nature of change. We outline the specific mechanisms by which change emerges from everyday work, becomes justified, and diffuses within an organization and field, as well as precipitating and enabling dynamics that trigger and condition these mechanisms. © Academy of Management Journal.

An aspect-oriented and model-driven approach for managing dynamic variability

Constructing and executing distributed systems that can adapt to their operating context in order to sustain provided services and the service qualities are complex tasks. Managing adaptation of multiple, interacting services is particularly difficult since these services tend to be distributed across the system, interdependent and sometimes tangled with other services. Furthermore, the exponential growth of the number of potential system configurations derived from the variabilities of each service need to be handled. Current practices of writing low-level reconfiguration scripts as part of the system code to handle run time adaptation are both error prone and time consuming and make adaptive systems difficult to validate and evolve. In this paper, we propose to combine model driven and aspect oriented techniques to better cope with the complexities of adaptive systems construction and execution, and to handle the problem of exponential growth of the number of possible configurations. Combining these techniques allows us to use high level domain abstractions, simplify the representation of variants and limit the problem pertaining to the combinatorial explosion of possible configurations. In our approach we also use models at runtime to generate the adaptation logic by comparing the current configuration of the system to a composed model representing the configuration we want to reach. © 2008 Springer-Verlag Berlin Heidelberg.

Model-driven software adaptation:report on the workshop M-ADAPT at ECOOP 2007

This first edition of the workshop Model-driven Software Adaptation (M-ADAPT'07) took place in the Technische Universität Berlin with the International Conference ECOOP'07 in the beautiful and buzzing city of Berlin, on the 30th of July, 2007. The workshop was organized by Gordon Blair, Nelly Bencomo, and Robert France. Participants explored how to develop appropriate model-driven approaches to model, analyze, and validate the volatile properties of the behaviour of adaptive systems and its environments. This report gives an overview of the presentations as well as an account of the fruitful discussions that took place at M-ADAPT'07. © 2008 Springer-Verlag Berlin Heidelberg.

Run-time model evaluation for requirements model-driven self-adaptation

A self-adaptive system adjusts its configuration to tolerate changes in its operating environment. To date, requirements modeling methodologies for self-adaptive systems have necessitated analysis of all potential system configurations, and the circumstances under which each is to be adopted. We argue that, by explicitly capturing and modelling uncertainty in the operating environment, and by verifying and analysing this model at runtime, it is possible for a system to adapt to tolerate some conditions that were not fully considered at design time. We showcase in this paper our tools and research results. © 2012 IEEE.

Genie:supporting the model driven development of reflective, component-based adaptive systems

Engineering adaptive software is an increasingly complex task. Here, we demonstrate Genie, a tool that supports the modelling, generation, and operation of highly reconfigurable, component-based systems. We showcase how Genie is used in two case-studies: i) the development and operation of an adaptive flood warning system, and ii) a service discovery application. In this context, adaptation is enabled by the Gridkit reflective middleware platform.

Form follows function:model-driven engineering for clinical trials

We argue that, for certain constrained domains, elaborate model transformation technologies-implemented from scratch in general-purpose programming languages-are unnecessary for model-driven engineering; instead, lightweight configuration of commercial off-the-shelf productivity tools suffices. In particular, in the CancerGrid project, we have been developing model-driven techniques for the generation of software tools to support clinical trials. A domain metamodel captures the community's best practice in trial design. A scientist authors a trial protocol, modelling their trial by instantiating the metamodel; customized software artifacts to support trial execution are generated automatically from the scientist's model. The metamodel is expressed as an XML Schema, in such a way that it can be instantiated by completing a form to generate a conformant XML document. The same process works at a second level for trial execution: among the artifacts generated from the protocol are models of the data to be collected, and the clinician conducting the trial instantiates such models in reporting observations-again by completing a form to create a conformant XML document, representing the data gathered during that observation. Simple standard form management tools are all that is needed. Our approach is applicable to a wide variety of information-modelling domains: not just clinical trials, but also electronic public sector computing, customer relationship management, document workflow, and so on. © 2012 Springer-Verlag.

A lumped parameter model for the analysis of the motion of the muscles of the lower limbs under whole-body vibration

Through a lumped parameter modelling approach, a dynamical model, which can reproduce the motion of the muscles of a human body standing in different postures during Whole Body Vibrations (WBVs) treatment, has been developed. The key parameters, associated to the dynamics of the motion of the muscles of the lower limbs, have been identified starting from accelerometer measurements. The developed model can be usefully applied to the optimization of WBVs treatments which can effectively enhance muscle activation. © 2013 IEEE.

Fluctuation-driven traffic congestion in a scale-free model of the Internet

In studies of complex heterogeneous networks, particularly of the Internet, significant attention was paid to analysing network failures caused by hardware faults or overload. There network reaction was modelled as rerouting of traffic away from failed or congested elements. Here we model network reaction to congestion on much shorter time scales when the input traffic rate through congested routes is reduced. As an example we consider the Internet where local mismatch between demand and capacity results in traffic losses. We describe the onset of congestion as a phase transition characterised by strong, albeit relatively short-lived, fluctuations of losses caused by noise in input traffic and exacerbated by the heterogeneous nature of the network manifested in a power-law load distribution. The fluctuations may result in the network strongly overreacting to the first signs of congestion by significantly reducing input traffic along the communication paths where congestion is utterly negligible. © 2013 IEEE.