Environmental risk management system design for hazardous waste materials

Hazardous materials can be generally deemed as any material which, because of its quantity, concentration, or physical, chemical, or infectious characteristics, may cause, or pose a substantial or potential hazard to human health or the environment. In the context of "sustainable development", most 'materials' could be deemed to be 'hazardous' at some stage of their lifecycle, i.e. from extraction to final disposal.This PhD study develops a decision support system for engineers and policy makers to help limit environmental burden, by reducing the environmental risk and the associated carbon footprint, from the perspective of 'hazardous' materials in product design, through the application of 'game theory' and 'grey theory' etc, as well as various computational approaches, by helping the designer identify novel solutions or mitigation strategies.The thesis starts by introducing the problem situation of the study and identify the research objectives, as well as previous studies have been reviewed in order to set this study in context.Since it is evident that consumers drive the open market, and their preference may be influenced by the carbon footprint label of products, the decision support system proposes an improved carbon labelling scheme to demonstrate the significance of a product‘s carbon footprint in a more visual way. The prototype of the scheme is derived from the concept of 'tolerability of risk', providing a framework by which judgments can be made as to whether society will accept the risk from hazardous materials.Application of game theory for decision support is a novel approach in this study, which aids decision-making by selecting appropriate strategies for both organisations and policy makers to reduce environmental impact. In this context, a game between manufacturers and government in the field of clean production is generated with various game scenarios to reflect the variation trend of strategic actions, and then developed to discuss the reduction of the inherent risk posed by 'hazardous' materials and carbon emissions on the supply chain network.The 'hierarchy of waste' suggests that the most preferable state for sustainability is prevention or the elimination of waste. Although this is not wholly practicable in real terms, the framework gives the importance to waste minimisation and prevention, especially promotes the cleaner production. In addition to strategy selection for mitigating environmental impact, the decision support system also develops an evaluation methodology for application by engineers to aid decision-making on materials selection, thus to improve the materials performances, promote cleaner production and provide better and sustainable products for public consumption

Evolutionary Kuramoto Dynamics

Biological systems have a variety of time-keeping mechanisms ranging from molecular clocks within cells to a complex interconnected unit across an entire organism. The suprachiasmatic nucleus, comprising interconnected oscillatory neurons, serves as a master-clock in mammals. The ubiquity of such systems indicates an evolutionary benefit that outweighs the cost of establishing and maintaining them, but little is known about the process of evolutionary development. To begin to address this shortfall, we introduce and analyse a new evolutionary game theoretic framework modelling the behaviour and evolution of systems of coupled oscillators. Each oscillator is characterized by a pair of dynamic behavioural dimensions, a phase and a communication strategy, along which evolution occurs. We measure success of mutations by comparing the benefit of synchronization balanced against the cost of connections between the oscillators. Despite the simple set-up, this model exhibits non-trivial behaviours mimicking several different classical games—the Prisoner’s Dilemma, snowdrift games, coordination games—as the landscape of the oscillators changes over time. Across many situations, we find a surprisingly simple characterization of synchronization through connectivity and communication: if the benefit of synchronization is greater than twice the cost, the system will evolve towards complete communication and phase synchronization

The detection of globular clusters in galaxies as a data mining problem

We present an application of self-adaptive supervised learning classifiers derived from the Machine Learning paradigm, to the identification of candidate Globular Clusters in deep, wide-field, single band HST images. Several methods provided by the DAME (Data Mining & Exploration) web application, were tested and compared on the NGC1399 HST data described in Paolillo 2011. The best results were obtained using a Multi Layer Perceptron with Quasi Newton learning rule which achieved a classification accuracy of 98.3%, with a completeness of 97.8% and 1.6% of contamination. An extensive set of experiments revealed that the use of accurate structural parameters (effective radius, central surface brightness) does improve the final result, but only by 5%. It is also shown that the method is capable to retrieve also extreme sources (for instance, very extended objects) which are missed by more traditional approaches.Comment: Accepted 2011 December 12; Received 2011 November 28; in original form 2011 October 1

Numerical simulations in 3-dimensions of reaction–diffusion models for brain tumour growth

We work with a well-known model of reaction–diffusion type for brain tumour growth and accomplish full 3-dimensional (3d) simulations of the tumour in time on two types of imaging data, the 3d Shepp–Logan head phantom image and an MRI T1-weighted brain scan from the Internet Brain Segmentation Repository. The source term is such that we have logistic growth. These simulations are obtained using standard finite difference approximations with novel calculations to increase speed and accuracy. Moreover, biological background to the model, its well-posedness together with a variational formulation are given. The variational formulation enable the feasibility of different derivations and modifications of the model