Explorations in a meaning making system: Kerry as an entrepreneurial platform and the equine sector as a cluster

This Portfolio is about the changes that can be supported and achieved through transformational education that impacts on personal, professional and organisational levels. Having lived through an era of tremendous change over the second half of the twentieth century and into the twenty-first the author has a great drawing board to contemplate in the context of professional career experience as an engineer. The ability to engage in ‘subject-object’ separation is the means by which Kegan (1994, 2009) explains that transformation takes place and the Essays in this Portfolio aim to support and bring about such change. Exploration of aspects of ‘Kerry’ is the material selected to both challenge support change in the way of knowing from being subject to certain information and knowledge that to being able to consider it more objectively. The task of being able to distance judgement about the economy and economic development of Kerry was facilitated by various readings around of a number of key thinkers including Kegan, Drucker, Porter and Penrose. The central themes of Kerry or the potential for economic development are built into each Essay. Essay One focuses on reflections of Kerry life - on Kerry people within and without Kerry - and events as they affected understandings of how people related to and worked with one another. These reflections formed the basis for transformational goals identified which required a shift from an engineering mindset to encompass an economics-based view. In Essay Two knowledge of economic concepts is developed by exploring the writings of Drucker, Penrose, and Porter with pertinence to considering economic development generally, and for Kerry in particular in the form of an ‘entrepreneurial platform’. The concepts and theories were the basis of explorations presented in Essays Three and Four. Essay Three focuses on Kerry’s potential for economic development give its current economic profile and includes results from interviews with selected businesses. Essay Four is an exercise in the application of Porter’s ‘Cluster’ concept to the equine sector.

Combining and choosing case base maintenance algorithms

Case-Based Reasoning (CBR) uses past experiences to solve new problems. The quality of the past experiences, which are stored as cases in a case base, is a big factor in the performance of a CBR system. The system's competence may be improved by adding problems to the case base after they have been solved and their solutions verified to be correct. However, from time to time, the case base may have to be refined to reduce redundancy and to get rid of any noisy cases that may have been introduced. Many case base maintenance algorithms have been developed to delete noisy and redundant cases. However, different algorithms work well in different situations and it may be difficult for a knowledge engineer to know which one is the best to use for a particular case base. In this thesis, we investigate ways to combine algorithms to produce better deletion decisions than the decisions made by individual algorithms, and ways to choose which algorithm is best for a given case base at a given time. We analyse five of the most commonly-used maintenance algorithms in detail and show how the different algorithms perform better on different datasets. This motivates us to develop a new approach: maintenance by a committee of experts (MACE). MACE allows us to combine maintenance algorithms to produce a composite algorithm which exploits the merits of each of the algorithms that it contains. By combining different algorithms in different ways we can also define algorithms that have different trade-offs between accuracy and deletion. While MACE allows us to define an infinite number of new composite algorithms, we still face the problem of choosing which algorithm to use. To make this choice, we need to be able to identify properties of a case base that are predictive of which maintenance algorithm is best. We examine a number of measures of dataset complexity for this purpose. These provide a numerical way to describe a case base at a given time. We use the numerical description to develop a meta-case-based classification system. This system uses previous experience about which maintenance algorithm was best to use for other case bases to predict which algorithm to use for a new case base. Finally, we give the knowledge engineer more control over the deletion process by creating incremental versions of the maintenance algorithms. These incremental algorithms suggest one case at a time for deletion rather than a group of cases, which allows the knowledge engineer to decide whether or not each case in turn should be deleted or kept. We also develop incremental versions of the complexity measures, allowing us to create an incremental version of our meta-case-based classification system. Since the case base changes after each deletion, the best algorithm to use may also change. The incremental system allows us to choose which algorithm is the best to use at each point in the deletion process.

Engineering of metal oxide interfaces for renewable energy applications

Diminishing non-renewable energy resources and planet-wide de-pollution on our planet are among the major problems which mankind faces into the future. To solve these problems, renewable energy sources such as readily available and inexhaustible sunlight will have to be used. There are however no readily available photocatalysts that are photocatalytically active under visible light; it is well established that the band gap of the prototypical photocatalyst, titanium dioxide, is the UV region with the consequence that only 4% of sun light is utilized. For this reason, this PhD project focused on developing new materials, based on titanium dioxide, which can be used in visible light activated photocatalytic hydrogen production and destruction of pollutant molecules. The main goal of this project is to use simulations based on first principles to engineer and understand rationally, materials based on modifying TiO2 that will have the following properties: (1) a suitable band gap in order to increase the efficiency of visible light absorption, with a gap around 2 – 2.5 eV considered optimum. (2). The second key aspect in the photocatalytic process is electron and hole separation after photoexcitation, which enable oxidation/reduction reactions necessary to i.e. decompose pollutants. (3) Enhanced activity over unmodified TiO2. In this thesis I present results on new materials based on modifying TiO2 with supported metal oxide nanoclusters, from two classes, namely: transition metal oxides (Ti, Ni, Cu) and p-block metal oxides (Sn, Pb, Bi). We find that the deposited metal oxide nanoclusters are stable at rutile and anatase TiO2 surfaces and present an analysis of changes to the band gap of TiO2, identifying those modifiers that can change the band gap to the desirable range and the origin of this. A successful collaboration with experimental researchers in Japan confirms many of the simulation results where the origin of improved visible light photocatalytic activity of oxide nanocluster-modified TiO2 is now well understood. The work presented in this thesis, creates a road map for the design of materials with desired photocatalytic properties and contributes to better understanding these properties which are of great application in renewable energy utilization.