Design of experiments for bivariate binary responses modelled by Copula functions

Optimal design for generalized linear models has primarily focused on univariate data. Often experiments are performed that have multiple dependent responses described by regression type models, and it is of interest and of value to design the experiment for all these responses. This requires a multivariate distribution underlying a pre-chosen model for the data. Here, we consider the design of experiments for bivariate binary data which are dependent. We explore Copula functions which provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. We present methods for deriving optimal experimental designs for dependent bivariate binary data using Copulas, and demonstrate that, by including the dependence between responses in the design process, more efficient parameter estimates are obtained than by the usual practice of simply designing for a single variable only. Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.

An approach to statistical lip modelling for speaker identification via chromatic feature extraction

This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS¹ database, show encouraging results

Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data

In this paper we present a sequential Monte Carlo algorithm for Bayesian sequential experimental design applied to generalised non-linear models for discrete data. The approach is computationally convenient in that the information of newly observed data can be incorporated through a simple re-weighting step. We also consider a flexible parametric model for the stimulus-response relationship together with a newly developed hybrid design utility that can produce more robust estimates of the target stimulus in the presence of substantial model and parameter uncertainty. The algorithm is applied to hypothetical clinical trial or bioassay scenarios. In the discussion, potential generalisations of the algorithm are suggested to possibly extend its applicability to a wide variety of scenarios

Optical and microscopic study of a polymer-nanotube mixture for organic photovoltaic applications

Organic solar cells based on bulk heterojunction between a conductive polymer and a carbon nanostructure offer potential advantages compared to conventional inorganic cells. Low cost, light weight, flexibility and high peak power per unit weight are all features that can be considered a reality for organic photovoltaics. Although polymer/carbon nanotubes solar cells have been proposed, only low power conversion efficiencies have been reached without addressing the mechanisms responsible for this poor performance. The purpose of this work is therefore to investigate the basic interaction between carbon nanotubes and poly(3-hexylthiophene) in order to demonstrate how this interaction affects the performance of photovoltaic devices. The outcomes of this study are the contributions made to the knowledge of the phenomena explaining the behaviour of electronic devices based on carbon nanotubes and poly(3-hexylthiophene). In this PhD, polymer thin films with the inclusion of uniformly distributed carbon nanotubes were deposited from solution and characterised. The bulk properties of the composites were studied with microscopy and spectroscopy techniques to provide evidence of higher degrees of polymer order when interacting with carbon nanotubes. Although bulk investigation techniques provided useful information about the interaction between the polymer and the nanotubes, clear evidence of the phenomena affecting the heterojunction formed between the two species was investigated at nanoscale. Identifying chirality-driven polymer assisted assembly on the carbon nanotube surface was one of the major achievements of this study. Moreover, the analysis of the electrical behaviour of the heterojunction between the polymer and the nanotube highlighted the charge transfer responsible for the low performance of photovoltaic devices. Polymer and carbon nanotube composite-based devices were fabricated and characterised in order to study their electronic properties. The carbon nanotube introduction in the polymer matrix evidenced a strong electrical conductivity enhancement but also a lower photoconductivity response. Moreover, the extension of pristine polymer device characterisation models to composites based devices evidenced the conduction mechanisms related to nanotubes. Finally, the introduction of carbon nanotubes in the polymer matrix was demonstrated to improve the pristine polymer solar cell performance and the spectral response even though the power conversion efficiency is still too low.

Use of a zeolite synthesised from alkali treated kaolin as a K fertiliser : glasshouse experiments on leaching and uptake of K by wheat plants in sandy soil

Zeolite N, a zeolite referred to in earlier publications as MesoLite, is made by caustic reaction of kaolin at temperatures between 80 °C and 95 °C. This material has a very high cation exchange capacity (CEC ≈ 500 meq/100 g). Soil column leaching experiments have shown that K-zeolite N additions greatly reduce leaching of NH4+ fertilisers but the agronomic effectiveness of the retained K+ and NH4+ is unknown. To measure the bioavailability of K in this zeolite, wheat was grown in a glasshouse with K-zeolite N as the K fertiliser in highly-leached and non-leached pots for four weeks and compared with a soluble K fertiliser (KCl). The plants grown in non-leached pots and fertilised with K-zeolite N were slightly larger than those grown with KCl. The elemental compositions in the plants were similar except for Si being significantly more concentrated in the plants supplied with K-zeolite N. Thus K-zeolite N may be an effective K-fertiliser. Plants grown in highly-leached pots were significantly smaller than those grown in non-leached pots. Plants grown in highly-leached pots were severely K deficient as half of the K from both KCl and K-zeolite N was leached from the pots within three days.

Factors of process model comprehension : findings from a series of experiments

In order to make good decisions about the design of information systems, an essential skill is to understand process models of the business domain the system is intended to support. Yet, little knowledge to date has been established about the factors that affect how model users comprehend the content of process models. In this study, we use theories of semiotics and cognitive load to theorize how model and personal factors influence how model viewers comprehend the syntactical information of process models. We then report on a four-part series of experiments, in which we examined these factors. Our results show that additional semantical information impedes syntax comprehension, and that theoretical knowledge eases syntax comprehension. Modeling experience further contributes positively to comprehension efficiency, measured as the ratio of correct answers to the time taken to provide answers. We discuss implications for practice and research.

ACE research vignette 018 : experiments in the MBA classroom : the case of time frames in project teams

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepeneurship researchers. In this vignette, Dr Rene Bakker considers project team dynamics and how executive education can be enriched by studying them in the classroom.

Scenes, quarters and clusters : new experiments in the formation and governance of creative places in China

This thesis examines the formation and governance patterns of the social and spatial concentration of creative people and creative business in cities. It develops a typology for creative places, adding the terms 'scene' and 'quarter' to 'clusters', to fill in the literature gap of partial emphasis on the 'creative clusters' model as an organising mechanism for regional and urban policy. In this framework, a cluster is the gathering of firms with a core focus on economic benefits; a quarter is the urban milieu usually driven by a growth coalition consisting of local government, real estate agents and residential communities; and a scene is the spontaneous assembly of artists, performers and fans with distinct cultural forms. The framework is applied to China, specifically to Hangzhou – a second-tier city in central eastern China that is ambitious to become a 'national cultural and creative industries centre'. The thesis selects three cases – Ideal & Silian 166 Creative Industries Park, White-horse Lake Eco-creative City and LOFT49 Creative Industries Park – to represent scene, quarter and cluster respectively. Drawing on in-depth interviews with initiators, managers and creative professionals of these places, together with extensive documentary analysis, the thesis investigates the composition of actors, characteristics of the locality and the diversity of activities. The findings illustrate that, in China, planning and government intervention is the key to the governance of creative space; spontaneous development processes exist, but these need a more tolerant environment, a greater diversity of cultural forms and more time to develop. Moreover, the main business development model is still real estate based: this model needs to incorporate more mature business models and an enhanced IP protection system. The thesis makes a contribution to literature on economic and cultural geography, urban planning and creative industries theory. It advocates greater attention to self-management, collaborative governance mechanisms and business strategies for scenes, quarters and clusters. As intersections exist in the terms discussed, a mixed toolkit of the three models is required to advance the creative city discourse in China.

Removal of toxic metals in a multi metal system using sorbents for potential application to urban stormwater treatment

In the context of increasing demand for potable water and the depletion of water resources, stormwater is a logical alternative. However, stormwater contains pollutants, among which metals are of particular interest due to their toxicity and persistence in the environment. Hence, it is imperative to remove toxic metals in stormwater to the levels prescribed by drinking water guidelines for potable use. Consequently, various techniques have been proposed, among which sorption using low cost sorbents is economically viable and environmentally benign in comparison to other techniques. However, sorbents show affinity towards certain toxic metals, which results in poor removal of other toxic metals. It was hypothesised in this study that a mixture of sorbents that have different metal affinity patterns can be used for the efficient removal of a range of toxic metals commonly found in stormwater. The performance of six sorbents in the sorption of Al, Cr, Cu, Pb, Ni, Zn and Cd, which are the toxic metals commonly found in urban stormwater, was investigated to select suitable sorbents for creating the mixtures. For this purpose, a multi criteria analytical protocol was developed using the decision making methods: PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) and GAIA (Graphical Analysis for Interactive Assistance). Zeolite and seaweed were selected for the creation of trial mixtures based on their metal affinity pattern and the performance on predetermined selection criteria. The metal sorption mechanisms employed by seaweed and zeolite were defined using kinetics, isotherm and thermodynamics parameters, which were determined using the batch sorption experiments. Additionally, the kinetics rate-limiting steps were identified using an innovative approach using GAIA and Spearman correlation techniques developed as part of the study, to overcome the limitation in conventional graphical methods in predicting the degree of contribution of each kinetics step in limiting the overall metal removal rate. The sorption kinetics of zeolite was found to be primarily limited by intraparticle diffusion followed by the sorption reaction steps, which were governed mainly by the hydrated ionic diameter of metals. The isotherm study indicated that the metal sorption mechanism of zeolite was primarily of a physical nature. The thermodynamics study confirmed that the energetically favourable nature of sorption increased in the order of Zn < Cu < Cd < Ni < Pb < Cr < Al, which is in agreement with metal sorption affinity of zeolite. Hence, sorption thermodynamics has an influence on the metal sorption affinity of zeolite. On the other hand, the primary kinetics rate-limiting step of seaweed was the sorption reaction process followed by intraparticle diffusion. The boundary layer diffusion was also found to limit the metal sorption kinetics at low concentration. According to the sorption isotherm study, Cd, Pb, Cr and Al were sorbed by seaweed via ion exchange, whilst sorption of Ni occurred via physisorption. Furthermore, ionic bonding is responsible for the sorption of Zn. The thermodynamics study confirmed that sorption by seaweed was energetically favourable in the order of Zn < Cu < Cd < Cr . Al < Pb < Ni. However, this did not agree with the affinity series derived for seaweed suggesting a limited influence of sorption thermodynamics on metal affinity for seaweed. The investigation of zeolite-seaweed mixtures indicated that mixing sorbents have an effect on the kinetics rates and the sorption affinity. Additionally, the theoretical relationships were derived to predict the boundary layer diffusion rate, intraparticle diffusion rate, the sorption reaction rate and the enthalpy of mixtures based on that of individual sorbents. In general, low coefficient of determination (R2) for the relationships between theoretical and experimental data indicated that the relationships were not statistically significant. This was attributed to the heterogeneity of the properties of sorbents. Nevertheless, in relative terms, the intraparticle diffusion rate, sorption reaction rate and enthalpy of sorption had higher R2 values than the boundary layer diffusion rate suggesting that there was some relationship between the former set of parameters of mixtures and that of sorbents. The mixture, which contained 80% of zeolite and 20% of seaweed, showed similar affinity for the sorption of Cu, Ni, Cd, Cr and Al, which was attributed to approximately similar sorption enthalpy of the metal ions. Therefore, it was concluded that the seaweed-zeolite mixture can be used to obtain the same affinity for various metals present in a multi metal system provided the metal ions have similar enthalpy during sorption by the mixture.

Dirichlet process mixture models for unsupervised clustering of symptoms in Parkinson's disease

In this paper, the goal of identifying disease subgroups based on differences in observed symptom profile is considered. Commonly referred to as phenotype identification, solutions to this task often involve the application of unsupervised clustering techniques. In this paper, we investigate the application of a Dirichlet Process mixture (DPM) model for this task. This model is defined by the placement of the Dirichlet Process (DP) on the unknown components of a mixture model, allowing for the expression of uncertainty about the partitioning of observed data into homogeneous subgroups. To exemplify this approach, an application to phenotype identification in Parkinson’s disease (PD) is considered, with symptom profiles collected using the Unified Parkinson’s Disease Rating Scale (UPDRS). Clustering, Dirichlet Process mixture, Parkinson’s disease, UPDRS.

Restructuring of carbonaceous particles upon exposure to organic vapours

Recent research has described the restructuring of particles upon exposure to organic vapours; however, as yet hypotheses able to explain this phenomenon are limited. In this study, a range of experiments were performed to explore different hypotheses related to carbonaceous particle restructuring upon exposure to organic and water vapours, such as: the effect of surface tension, the role of organics in flocculating primary particles, as well as the ability of vapours to “wet” the particle surface. The change in mobility diameter (dm) was investigated for a range carbonaceous particle types (diesel exhaust, petrol exhaust, cigarette smoke, candle smoke, particles generated in a heptane/toluene flame, and wood smoke particles) exposed to different organic (heptane, ethanol, and dimethyl sulfoxide/water (1:1 vol%) mixture) and water vapours. Particles were first size-selected and then bubbled through an impinger (bubbler) containing either an organic solvent or water, where particles trapped inside rising bubbles were exposed to saturated vapours of the solvent in the impinger. The size distribution of particles was simultaneously measured upstream and downstream from the impinger. A size-dependent reduction in dm was observed when bubbling diesel exhaust, particles generated in a heptane/toluene flame, and candle smoke particles through heptane, ethanol and a dimethyl sulfoxide/water (1:1 vol %) mixture. In addition, the size distributions of particles bubbled through an impinger were broader. Moreover, an increase of the geometric standard deviation (σ) of the size distributions of particles bubbled through an impinger was also found to be size-dependent. Size-dependent reduction in dm and an increase of σ indicate that particles undergo restructuring to a more compact form, which was confirmed by TEM analysis. However, bubbling of these particles through water did not result in a size-dependent reduction in dm, nor in an increase of σ. Cigarette smoke, petrol exhaust, and wood smoke particles did not result in any substantial change in dm, or σ, when bubbled through organic solvents or water. Therefore, size-dependent reduction in the dm upon bubbling through organic solvents was observed only for particles that had a fractal-like structure, whilst particles that were liquid or were assumed to be spherical did not exhibit any reduction in dm. Compaction of fractal-like particles was attributed to the ability of condensing vapours to efficiently wet the particles. Our results also show that the presence of an organic layer on the surface of fractal-like particles, or the surface tension of the condensed liquid do not influence the extent of compaction.