The evolution of learning systems:to Bayes or not to be

Bayesian algorithms pose a limit to the performance learning algorithms can achieve. Natural selection should guide the evolution of information processing systems towards those limits. What can we learn from this evolution and what properties do the intermediate stages have? While this question is too general to permit any answer, progress can be made by restricting the class of information processing systems under study. We present analytical and numerical results for the evolution of on-line algorithms for learning from examples for neural network classifiers, which might include or not a hidden layer. The analytical results are obtained by solving a variational problem to determine the learning algorithm that leads to maximum generalization ability. Simulations using evolutionary programming, for programs that implement learning algorithms, confirm and expand the results. The principal result is not just that the evolution is towards a Bayesian limit. Indeed it is essentially reached. In addition we find that evolution is driven by the discovery of useful structures or combinations of variables and operators. In different runs the temporal order of the discovery of such combinations is unique. The main result is that combinations that signal the surprise brought by an example arise always before combinations that serve to gauge the performance of the learning algorithm. This latter structures can be used to implement annealing schedules. The temporal ordering can be understood analytically as well by doing the functional optimization in restricted functional spaces. We also show that there is data suggesting that the appearance of these traits also follows the same temporal ordering in biological systems. © 2006 American Institute of Physics.

The design of contact lens based ocular drug delivery systems for single-day use:part (I) structural factors, surrogate ophthalmic dyes and passive diffusion studies

The poor retention and efficacy of instilled drops as a means of delivering drugs to the ophthalmic environment is well-recognised. The potential value of contact lenses as a means of ophthalmic drug delivery, and consequent improvement of pre-corneal retention is one obvious route to the development of a more effective ocular delivery system. Furthermore, the increasing availability and clinical use of daily disposable contact lenses provides the platform for the development of viable single-day use drug delivery devices based on existing materials and lenses. In order to provide a basis for the effective design of such devices, a systematic understanding of the factors affecting the interaction of individual drugs with the lens matrix is required. Because a large number of potential structural variables are involved, it is necessary to achieve some rationalisation of the parameters and physicochemical properties (such as molecular weight, charge, partition coefficients) that influence drug interactions. Ophthalmic dyes and structurally related compounds based on the same core structure were used to investigate these various factors and the way in which they can be used in concert to design effective release systems for structurally different drugs. Initial studies of passive diffusional release form a necessary precursor to the investigation of the features of the ocular environment that over-ride this simple behaviour. Commercially available contact lenses of differing structural classifications were used to study factors affecting the uptake of the surrogate actives and their release under 'passive' conditions. The interaction between active and lens material shows considerable and complex structure dependence, which is not simply related to equilibrium water content. The structure of the polymer matrix itself was found to have the dominant controlling influence on active uptake; hydrophobic interaction with the ophthalmic dye playing a major role. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Visualising and controlling the flow in biomolecular systems at and between multiple scales:from atoms to hydrodynamics at different locations in time and space

A novel framework for modelling biomolecular systems at multiple scales in space and time simultaneously is described. The atomistic molecular dynamics representation is smoothly connected with a statistical continuum hydrodynamics description. The system behaves correctly at the limits of pure molecular dynamics (hydrodynamics) and at the intermediate regimes when the atoms move partly as atomistic particles, and at the same time follow the hydrodynamic flows. The corresponding contributions are controlled by a parameter, which is defined as an arbitrary function of space and time, thus, allowing an effective separation of the atomistic 'core' and continuum 'environment'. To fill the scale gap between the atomistic and the continuum representations our special purpose computer for molecular dynamics, MDGRAPE-4, as well as GPU-based computing were used for developing the framework. These hardware developments also include interactive molecular dynamics simulations that allow intervention of the modelling through force-feedback devices.

Representing human expertise by the OWL web ontology language to support knowledge engineering in decision support systems

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

Modelling sustainability performance to achieve absolute reductions in socio-ecological systems

As the world’s natural resources dwindle and critical levels of environmental pollution are approached, sustainability becomes a key issue for governments, organisations and individuals. With the consequences of such an issue in mind, this paper introduces a unifying approach to measure the sustainability performance of socio-economic systems based on the interplay between two key variables: essentiality of consumption and environmental impact. This measure attributes to every system a ‘fitness’ value i.e. a quantity that reflects its ability to remain resilient/healthy by avoiding ecological, social and economic collapse as it consumes the available resources. This new measure is tested on a system where there is a limited supply of resources and four basic consumption types. The analysis has theoretical implications as well as practical importance as it can help countries, organisations or even individuals, in finding better ways to measure sustainability performance.

Manufacturing and assembly automation by integrated metrology systems for aircraft wing fabrication

Discrepancies of materials, tools, and factory environments, as well as human intervention, make variation an integral part of the manufacturing process of any component. In particular, the assembly of large volume, aerospace parts is an area where significant levels of form and dimensional variation are encountered. Corrective actions can usually be taken to reduce the defects, when the sources and levels of variation are known. For the unknown dimensional and form variations, a tolerancing strategy is typically put in place in order to minimize the effects of production inconsistencies related to geometric dimensions. This generates a challenging problem for the automation of the corresponding manufacturing and assembly processes. Metrology is becoming a major contributor to being able to predict, in real time, the automated assembly problems related to the dimensional variation of parts and assemblies. This is done by continuously measuring dimensions and coordinate points, focusing on the product's key characteristics. In this paper, a number of metrology focused activities for large-volume aerospace products, including their implementation and application in the automation of manufacturing and assembly processes, are reviewed. This is done by using a case study approach within the assembly of large-volume aircraft wing structures.

Recommender systems

The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has great scientific depth and combines diverse research fields which makes it interesting for physicists as well as interdisciplinary researchers. © 2012 Elsevier B.V.

Revisiting goal-oriented models for self-aware systems-of-systems

Systems-of-systems (SoS) are systems resulted from the interaction among other independent constituent systems that collaborate to offer new functionalities towards accomplishing global missions. Each of these constituent systems accomplishes its individual missions and is able to contribute to the achievement of the global missions of the SoS, both being viewed as a set of associated goals. In the perspective of self-aware systems, SoS need to exhibit goal-awareness, i.e., They need to be aware of their own goals and of how their constituent systems contribute to their accomplishment. In this paper, we revisit goal-oriented concepts aiming at identifying and modeling goals at both SoS level and the constituent systems level. Moreover, we take advantage of such goal-oriented models to express the relationship among goals at these levels as well as to define how each constituent system can contribute to the accomplishment of global goals of an SoS. In addition, we shed light on important issues related to goal modeling in self-aware SoS to be addressed in future research.

Institutional complexity in Thai state-owned enterprises:the implementation of performance measurement systems

This study explores institutional complexity in Thai State-Owned Enterprises (SOEs). In doing so, a qualitative approach has been employed in this study in order to identify institutional logics in the field of Thai SOEs and to understand organisational and individual perceptions of institutional complexity in the implementation of performance measurement systems (PMS) and how they respond to the complexity. To achieve this goal, two Thai SOEs were studied, both of which faced challenges in the implementation of Economic Value Management (EVM) and Balance Scorecard (BSC) as well as difficulties in linking their individual BSC and incentive systems. The qualitative data were collected from semi-structured interviews and document reviews. The empirical aspects of this study reveal that the institutional logics in the field of Thai SOEs are the logic of bureaucracy, commercial operations, social activities, seniority and unity. Regarding the multiple institutional logics embedded, SOEs experienced the institutional complexity in the implementation of PMS. The results suggest that the organisations have decoupled the EVM and loosely coupled the BSC from organisational practices to cope with institutional complexity and conflict institutional demands. Also, the evidence shows that the institutional logics influence SOEs’ actions towards resisting changes incentive systems and the relationship between individual BSC and incentives.