Developing a conceptual model of marine farming in New Zealand

Survey and Geographic Information System (GIS) data analysis describes the relative influence of biophysical and human variables on site choices made by marine farmers in New Zealand. Community conflicts have grown in importance in determining farm location and different government planning strategies leave distinct signature patterns. Recent legislation empowers local governments to choose among three strategies for future regional aquaculture development. This paper suggests each strategy could result in different spatial outcomes. Simulation modelling of the type described here can provide a better understanding of farmer responses to management approaches and the range of futures that could result from planning choices made today

Evaluating Interactive Visualization of Multidimensional Data Projection with Feature Transformation

There has been extensive research on dimensionality reduction techniques. While these make it possible to present visually the high-dimensional data in 2D or 3D, it remains a challenge for users to make sense of such projected data. Recently, interactive techniques, such as Feature Transformation, have been introduced to address this. This paper describes a user study that was designed to understand how the feature transformation techniques affect user’s understanding of multi-dimensional data visualisation. It was compared with the traditional dimension reduction techniques, both unsupervised (PCA) and supervised (MCML). Thirty-one participants were recruited to detect visual clusters and outliers using visualisations produced by these techniques. Six different datasets with a range of dimensionality and data size were used in the experiment. Five of these are benchmark datasets, which makes it possible to compare with other studies using the same datasets. Both task accuracy and completion time were recorded for comparison. The results show that there is a strong case for the feature transformation technique. Participants performed best with the visualisations produced with high-level feature transformation, in terms of both accuracy and completion time. The improvements over other techniques are substantial, particularly in the case of the accuracy of the clustering task. However, visualising data with very high dimensionality (i.e., greater than 100 dimensions) remains a challenge

Visualising Time

This study investigates the visualisation of temporal relationships between objects. A popular method employed for such information visualisations is the time line consisting of a single horizontal axis along which temporal events or objects are depicted at specific points or intervals. The orientation of the temporal progression along the axis line will generally coincide with the orientation of the literary writing progression of the culture and language. For example a time line visualised in a Western culture with English as its literary base will exhibit a temporal progression orientation of early/left, later/right whereas Arabian culture with an Arabic literary base will exhibit the reverse temporal progression orientation. In both cultures and languages temporal metaphor use spatial concepts to describe temporal relationships with no discourse to transversal orientation. This is reflected by never hearing the phrase “the months to the right” but rather “the months ahead”. In science, Einstein showed via his special and general theories of relativity that time and space are interlinked. The scientific rationalisation of time and space along with the use of spatial concepts as temporal metaphor implies that the underlying perception of time is spatial. Information visualisations are the externalisations of our perceptions. Therefore temporal information visualisations should employ spatial visualisation techniques. This study evaluated spatial visualisation techniques for temporal information visualisations via a web survey. The spatial temporal information visualisations used in the survey employed no temporal cues such as time or date stamps but conferred all temporal progression via spatial cues. The findings from the analysis of the participant responses to the survey showed that spatial cues do impart temporal cues for temporal relationships

Runtime visualisation of object-oriented software

Software is a complex and invisible entity, yet one which is core to modem life. The development and maintenance of such software includes one staple task, the need to understand the software at the implementation level. This process of program comprehension is difficult and time consuming. Yet, despite its importance, there remains very limited tool support for program comprehension activities. The results of this research show the role that runtime visualisation can play in aiding the comprehension of object-oriented software by highlighting both its static and dynamic structure. Previous work in this area is discussed, both in terms of the representations used and the methods of extracting runtime information. Building on this previous work, this thesis develops new representations of object-oriented software at runtime, which are then implemented in a proof of concept tool. This tool allowed the representations to be investigated on real software systems. The representations are evaluated against two feature-based evaluation frameworks. The evaluation focuses on generic software visualisation criteria, due to the lack of any specific frameworks for visualising dynamic information. The evaluation also includes lessons learnt in the implementation of a prototype visualisation tool. The object-oriented paradigm continues to grow in popularity and provides advantages to program comprehension activities. However, it also brings a number of new challenges to program comprehension due to the discrepancies between its static definition and its runtime structure. Therefore, techniques that highlight both the static definition and the runtime behaviour of object-oriented systems offer benefits to their comprehension. Software visualisation offers an approach to aid program comprehension activities through providing a means to deal with the size and complexity of the software and its invisible nature. This thesis highlights the generic issues that software visualisation faces, before focusing on how the visualisation of runtime information affects these issues. Many of the issues are compounded by the dynamic nature of the information to be visualised and the explosive growth in the volume of information that this dynamism can bring. Wider results of this research have allowed the proposal of the necessary concepts that should be considered in the design and evaluation of runtime visualisations. Software visualisation at runtime is still a relatively unexplored area and there remains many research challenges within it. This thesis aims to act as a first step to addressing these challenges and aims to promote interest and future development within this area

Uncertainty in Neural Networks; Bayesian Ensembles, Priors & Prediction Intervals

The breakout success of deep neural networks (NNs) in the 2010's marked a new era in the quest to build artificial intelligence (AI). With NNs as the building block of these systems, excellent performance has been achieved on narrow, well-defined tasks where large amounts of data are available. However, these systems lack certain capabilities that are important for broad use in real-world applications. One such capability is the communication of uncertainty in a NN's predictions and decisions. In applications such as healthcare recommendation or heavy machinery prognostics, it is vital that AI systems be aware of and express their uncertainty – this creates safer, more cautious, and ultimately more useful systems. This thesis explores how to engineer NNs to communicate robust uncertainty estimates on their predictions, whilst minimising the impact on usability. One way to encourage uncertainty estimates to be robust is to adopt the Bayesian framework, which offers a principled approach to handling uncertainty. Two of the major contributions in this thesis relate to Bayesian NNs (BNNs). Specifying appropriate priors is an important step in any Bayesian model, yet it is not clear how to do this in BNNs. The first contribution shows that the connection between BNNs and Gaussian Processes (GPs) provides an effective lens to study BNN priors. NN architectures are derived which mirror the combining of GP kernels to create priors tailored to a task. The second major contribution is a novel way to perform approximate Bayesian inference in BNNs using a modified version of ensembling. Novel analysis improves an understanding of a technique known as randomised MAP sampling. It's shown this is particularly effective when strong correlations exist between parameters, making it well suited to NNs. The third major contribution of the thesis is a non-Bayesian technique that trains a NN to directly output prediction intervals for regression tasks through a tailored objective function. This advances over related works that were incompatible with gradient descent, and ignored one source of uncertainty.EPSRC, Alan Turing Institut

Multi-agent Communication Protocols with Emergent Behaviour

The emergent behaviour of a multiagent system depends on the component agents and how they interact. A critical part of interaction between agents is communication. This thesis presents a multi-agent system communication model for physical moving agents. The work presented in this thesis provides all the tools to create a physical multi-agent communication system. The model integrates different agent technologies at both the micro and macro level. The micro structure involves the architecture of the individual components in the system whilst the macro structure involves the interaction relationships between these individual components in the system. Regarding the micro structure of the system, the model provides the description of a novel hybrid BDI-Blackboard architectured agent that builds-in a hybrid of reactive and deliberative agent. The macro structure of the system, provided by this model, provides the operational specifications of the communication protocols. The thesis presents a theory of communication that integrates an animal intelligence technique together with a cognitive intelligence one. This results in a local co-ordination of movements, and global task coordination. Accordingly, agents are designed to communicate with other agents in order to coordinate their movements via a set of behavioural rules. These behavioural rules allow a simple directed flocking behaviour to emerge. A flocking algorithm is used because it satisfies a major objective, i.e. it has a real time response to local environmental changes and minimises the cost of path planning. A higher level communication mechanism is implemented for task distribution that is carried out via a blackboard conversation and ii negotiation process with a ground based controller. All the tasks are distributed as team tasks. A novel utilization of speech acts as communication utterances through a blackboard negotiation process is proposed. In order to implement the proposed communication model, a virtual environment is built that satisfies the realism of representing the agents, environment, and the sensors as well as representing the actions. The virtual environment used in the work is built as a semi-immersive full-scale environment and provides the visualisation tools required to test, modify, compare and evaluate different behaviours under different conditions. The visualization tools allow the user to visualize agents negotiations and interacting with them. The 3D visualisation and simulation tools allow the communication protocol to be tested and the emergent behaviour to be seen in an easy and understandable manner. The developed virtual environment can be used as a toolkit to test different communication protocols and different agent’s architecture in real time

CFD analyses and performance comparison of micro-hydropowder plants

The project concerns the hydropower renewable energy technology at its micro scale: thanks to an internship performed with the Belgian startup TurbulentHydro, the purpose of this Master Thesis is to evaluate the energy performance of 2 di erent models currently under investigation: the so-called Flatblades and Streamlines con gurations. These layouts are similar in shape but di erent both in dimension and for the turbine used. After a little introduction on renewable energies and hydropower technology, the selected CFD simulation procedure and all its options have been explained as well as the choice of the turbulence model to apply, computing the meaningful parameters to add in the model. This dissertation highlights the uid dynamics behaviour by means of suitable softwares for this purpose: Autodesk Inventor, the 3D CAD mechanical design software in order to build, and edit when necessary, the geometries of the models considered, MeshMixer, a state-of-art software for locally adjusting the mesh of the starting model and OpenFOAM, a free and open source CFD program in order to run and evaluate any details of the analysis, simulating the operation conditions by means of its components and tools. Eventually, the most important CFD results are presented. Di erent con gurations bring di erent results. Regarding Flatblades model, the scope was re ned the CFD initial setup in order to achieve results as close to the real case validation as possible whereas, for Streamlines model, an additional new component has been added for improving the current design in terms of energy output at the turbine level. At the end, conclusions stated possible re nements and improvements for these simulations as well as uncertainties arose from the results that might be avoided for the next stages

Isosurface modelling of soft objects in computer graphics.

There are many different modelling techniques used in computer graphics to describe a wide range of objects and phenomena. In this thesis, details of research into the isosurface modelling technique are presented. The isosurface technique is used in conjunction with more traditional modelling techniques to describe the objects needed in the different scenes of an animation. The isosurface modelling technique allows the description and animation of objects that would be extremely difficult, or impossible to describe using other methods. The objects suitable for description using isosurface modelling are soft objects. Soft objects merge elegantly with each other, pull apart, bubble, ripple and exhibit a variety of other effects. The representation was studied in three phases of a computer animation project: modelling of the objects; animation of the objects; and the production of the images. The research clarifies and presents many algorithms needed to implement the isosurface representation in an animation system. The creation of a hierarchical computer graphics animation system implementing the isosurface representation is described. The scalar fields defining the isosurfaces are represented using a scalar field description language, created as part of this research, which is automatically generated from the hierarchical description of the scene. This language has many techniques for combining and building the scalar field from a variety of components. Surface attributes of the objects are specified within the graphics system. Techniques are described which allow the handling of these attributes along with the scalar field calculation. Many animation techniques specific to the isosurface representation are presented. By the conclusion of the research, a graphics system was created which elegantly handles the isosurface representation in a wide variety of animation situations. This thesis establishes that isosurface modelling of soft objects is a powerful and useful technique which has wide application in the computer graphics community