Data visualisation and exploration with prior knowledge

Visualising data for exploratory analysis is a major challenge in many applications. Visualisation allows scientists to gain insight into the structure and distribution of the data, for example finding common patterns and relationships between samples as well as variables. Typically, visualisation methods like principal component analysis and multi-dimensional scaling are employed. These methods are favoured because of their simplicity, but they cannot cope with missing data and it is difficult to incorporate prior knowledge about properties of the variable space into the analysis; this is particularly important in the high-dimensional, sparse datasets typical in geochemistry. In this paper we show how to utilise a block-structured correlation matrix using a modification of a well known non-linear probabilistic visualisation model, the Generative Topographic Mapping (GTM), which can cope with missing data. The block structure supports direct modelling of strongly correlated variables. We show that including prior structural information it is possible to improve both the data visualisation and the model fit. These benefits are demonstrated on artificial data as well as a real geochemical dataset used for oil exploration, where the proposed modifications improved the missing data imputation results by 3 to 13%.

Effective knowledge transfer: a terminological perspective - Dismantling the jargon barrier to knowledge about computer security

The research is concerned with the terminological problems that computer users experience when they try to formulate their knowledge needs and attempt to access information contained in computer manuals or online help systems while building up their knowledge. This is the recognised but unresolved problem of communication between the specialist and the layman. The initial hypothesis was that computer users, through their knowledge of language, have some prior knowledge of the subdomain of computing they are trying to come to terms with, and that language can be a facilitating mechanism, or an obstacle, in the development of that knowledge. Related to this is the supposition that users have a conceptual apparatus based on both theoretical knowledge and experience of the world, and of several domains of special reference related to the environment in which they operate. The theoretical argument was developed by exploring the relationship between knowledge and language, and considering the efficacy of terms as agents of special subject knowledge representation. Having charted in a systematic way the territory of knowledge sources and types, we were able to establish that there are many aspects of knowledge which cannot be represented by terms. This submission is important, as it leads to the realisation that significant elements of knowledge are being disregarded in retrieval systems because they are normally expressed by language elements which do not enjoy the status of terms. Furthermore, we introduced the notion of `linguistic ease of retrieval' as a challenge to more conventional thinking which focuses on retrieval results.

An investigation into the use of knowledge representation in computer-integrated manufacturing

In a certain automobile factory, batch-painting of the body types in colours is controlled by an allocation system. This tries to balance production with orders, whilst making optimally-sized batches of colours. Sequences of cars entering painting cannot be optimised for easy selection of colour and batch size. `Over-production' is not allowed, in order to reduce buffer stocks of unsold vehicles. Paint quality is degraded by random effects. This thesis describes a toolkit which supports IKBS in an object-centred formalism. The intended domain of use for the toolkit is flexible manufacturing. A sizeable application program was developed, using the toolkit, to test the validity of the IKBS approach in solving the real manufacturing problem above, for which an existing conventional program was already being used. A detailed statistical analysis of the operating circumstances of the program was made to evaluate the likely need for the more flexible type of program for which the toolkit was intended. The IKBS program captures the many disparate and conflicting constraints in the scheduling knowledge and emulates the behaviour of the program installed in the factory. In the factory system, many possible, newly-discovered, heuristics would be awkward to represent and it would be impossible to make many new extensions. The representation scheme is capable of admitting changes to the knowledge, relying on the inherent encapsulating properties of object-centres programming to protect and isolate data. The object-centred scheme is supported by an enhancement of the `C' programming language and runs under BSD 4.2 UNIX. The structuring technique, using objects, provides a mechanism for separating control of expression of rule-based knowledge from the knowledge itself and allowing explicit `contexts', within which appropriate expression of knowledge can be done. Facilities are provided for acquisition of knowledge in a consistent manner.

A semantic modelling approach to knowledge based statistical software

The topic of this thesis is the development of knowledge based statistical software. The shortcomings of conventional statistical packages are discussed to illustrate the need to develop software which is able to exhibit a greater degree of statistical expertise, thereby reducing the misuse of statistical methods by those not well versed in the art of statistical analysis. Some of the issues involved in the development of knowledge based software are presented and a review is given of some of the systems that have been developed so far. The majority of these have moved away from conventional architectures by adopting what can be termed an expert systems approach. The thesis then proposes an approach which is based upon the concept of semantic modelling. By representing some of the semantic meaning of data, it is conceived that a system could examine a request to apply a statistical technique and check if the use of the chosen technique was semantically sound, i.e. will the results obtained be meaningful. Current systems, in contrast, can only perform what can be considered as syntactic checks. The prototype system that has been implemented to explore the feasibility of such an approach is presented, the system has been designed as an enhanced variant of a conventional style statistical package. This involved developing a semantic data model to represent some of the statistically relevant knowledge about data and identifying sets of requirements that should be met for the application of the statistical techniques to be valid. Those areas of statistics covered in the prototype are measures of association and tests of location.

Knowledge acquisition in international strategic alliances among Malaysian manufacturing firms

This thesis examines the process of knowledge acquisition by Malaysian manufacturing firms through their involvement in international strategic alliances. The strategic alliances can be with or without equity involvement. Firms involved with a foreign partner with equity involvement are joint venture firms while non-equity involvement are firms that engaged in contractual agreements. Using empirical evidence from 65 international alliances gathered through a survey conducted in high-technology manufacturing sectors, several factors that influence the process of knowledge acquisition are examined. The factors are: learning capacity, experience, goals, active involvement and accessibility to the foreign knowledge. Censored regression analysis and ordered probit analysis are used to analyse the effects of these factors on knowledge acquisition and its determinant parts, and the effects of knowledge acquisition and its determinants on the performance of the alliances. A second questionnaire gathered evidence relating to the factors, which encouraged tacit knowledge transfer between the foreign and Malaysian partners in international alliances. The key findings of the study are: knowledge acquisition in international strategic alliances is influenced by five determining factors; learning capacity, experience, articulated goals, active involvement and accessibility; new technology knowledge, product development knowledge and manufacturing process knowledge are influenced differently by the determining factors; knowledge acquisition and its determinant factors have a significant impact on the firm’s performance; cultural differences tend to moderate the effect on the firm’s performance; acquiring tacit knowledge is not only influenced by the five determinant factors but also by other factors, such as dependency, accessibility, trust, manufacturing control, learning methods and organisational systems; Malaysian firms involved in joint ventures tend to acquire more knowledge than those involved in contractual agreements, but joint ventures also exhibit higher degrees of dependency than contractual agreements; and the presence of R&D activity in the Malaysian partner encourages knowledge acquisition, but the amount of R&D expenditure has no effect on knowledge acquisition.

Moving from HRM to knowledge productivity:a study of whether and how organizations become learning organizations

Practitioners and academics are in broad agreement that, above all, organizations need to be able to learn, to innovate and to question existing ways of working. This thesis develops a model to take into account, firstly, what determines whether or not organizations endorse practices designed to facilitate learning. Secondly, the model evaluates the impact of such practices upon organizational outcomes, measured in terms of products and technological innovation. Researchers have noted that organizations that are committed to producing innovation show great resilience in dealing with adverse business conditions (e.g. Pavitt, 1991; Leonard Barton, 1998). In effect, such organizations bear many of the characteristics associated with the achievement of ‘learning organization’ status (Garvin, 1993; Pedler, Burgoyne & Boydell, 1999; Senge, 1990). Seven studies are presented to support this theoretical framework. The first empirical study explores the antecedents to effective learning. The three following studies present data to suggest that people management practices are highly significant in determining whether or not organizations are able to produce sustained innovation. The thesis goes on to explore the relationship between organizational-level job satisfaction, learning and innovation, and provides evidence to suggest that there is a strong, positive relationship between these variables. The final two chapters analyze learning and innovation within two similar manufacturing organizations. One manifests relatively low levels of innovation whilst the other is generally considered to be outstandingly innovative. I present the comparative framework for exploring the different approaches to learning manifested by the two organizations. The thesis concludes by assessing the extent to which the theoretical model presented in the second chapter is borne out by the findings of the study. Whilst this is a relatively new field of inquiry, findings reveal that organizations have a much stronger chance of producing sustained innovation where they manage people proactively where people process themselves to be satisfied at work. Few studies to date have presented empirical evidence to substantiate theoretical endorsements to engage in higher order learning, so this research makes an important contribution to existing literature in this field.

Social capital and tacit knowledge sharing in organisational projects in Malaysian ICT companies

An increasing number of organisational researchers have turned to social capital theory in an attempt to better understand the impetus for knowledge sharing at the individual and organisational level. This thesis extends that research by investigating the impact of social capital on knowledge sharing at the group-level in the organisational project context. The objective of the thesis is to investigate the importance of social capital in fostering tacit knowledge sharing among the team members of a project. The analytical focus is on the Nahapiet and Ghoshal framework of social capital but also includes elements of other scholars' work. In brief, social capital is defined as an asset that is embedded in the network of relationships possessed by an individual or social unit. It is argued that the main dimensions of social capital that are of relevance to knowledge sharing are structural, cognitive, and relational because these, among other things, foster the exchange and combination of knowledge and resources among the team members. Empirically, the study is based on the grounded theory method. Data were collected from five projects in large, medium, and small ICT companies in Malaysia. Underpinned by the constant comparative method, data were derived from 55 interviews, and observations. The data were analysed using open, axial, and selective coding. The analysis also involved counting frequency occurrence from the coding generated by grounded theory to find the important items and categories under social capital dimensions and knowledge sharing, and for further explaining sub-groups within the data. The analysis shows that the most important dimension for tacit knowledge sharing is structural capital. Most importantly, the findings also suggest that structural capital is a prerequisite of cognitive capital and relational capital at the group-level in an organisational project. It also found that in a project context, relational capital is hard to realise because it requires time and frequent interactions among the team members. The findings from quantitative analysis show that frequent meetings and interactions, relationship, positions, shared visions, shared objectives, and collaboration are among the factors that foster the sharing of tacit knowledge among the team members. In conclusion, the present study adds to the existing literature on social capital in two main ways. Firstly, it distinguishes the dimensions of social capital and identifies that structural capital is the most important dimension in social capital and it is a prerequisite of cognitive and relational capital in a project context. Secondly, it identifies the causal sequence in the dimension of social capital suggesting avenues for further theoretical and empirical work in this emerging area of inquiry.

A knowledge-based system for process planning in a seamless steel tube plant

The thesis describes the work carried out to develop a prototype knowledge-based system 'KBS-SETUPP' to generate process plans for the manufacture of seamless tubes. The work is specifically related to a plant in which hollows are made from solid billets using a rotary piercing process and then reduced to required size and finished properties using the fixed plug cold drawing process. The thesis first discusses various methods of tube production in order to give a general background of tube manufacture. Then a review of the automation of the process planning function is presented in terms of its basic sub-tasks and the techniques and suitability of a knowledge-based system is established. In the light of such a review and a case study, the process planning problem is formulated in the domain of seamless tube manufacture, its basic sub-tasks are identified and capabilities and constraints of the available equipment in the specific plant are established. The task of collecting and collating the process planning knowledge in seamless tube manufacture is discussed and is mostly fulfilled from domain experts, analysing of existing manufacturing records specific to plant, textbooks and applicable Standards. For the cold drawing mill, tube-drawing schedules have been rationalised to correspond with practice. The validation of such schedules has been achieved by computing the process parameters and then comparing these with the drawbench capacity to avoid over-loading. The existing models cannot be simulated in the computer program as such, therefore a mathematical model has been proposed which estimates the process parameters which are in close agreement with experimental values established by other researchers. To implement the concepts, a Knowledge-Based System 'KBS- SETUPP' has been developed on Personal Computer using Turbo- Prolog. The system is capable of generating process plans, production schedules and some additional capabilities to supplement process planning. The system generated process plans have been compared with the actual plans of the company and it has been shown that the results are satisfactory and encouraging and that the system has the capabilities which are useful.

A process view of knowledge management:it ain't want you do, it's the way that you do it

Knowledge management needs to consider the three related elements of people, processes and technology. Much existing work has concentrated on either people or technology, often to the exclusion of the other two elements. Yet without thinking about process ? the way people, organisations and even technology actually do things ? any implementation of a knowledge management initiative is at best risky, and at worst doomed to failure. This paper looks at various ways in which a process view has appeared, expl icitly or implicitly, in knowledge management research and practice so far, and reflects on how more 'thinking about process' might improve knowledge management in the future. Consistent with this overall viewpoint, the issues generally centre less on wha t a process view would suggest should be done, but rather on the way that it would be implemented in practice.

The application of methods of uncertain reasoning to the biological classification of river water quality

This thesis presents an investigation into the application of methods of uncertain reasoning to the biological classification of river water quality. Existing biological methods for reporting river water quality are critically evaluated, and the adoption of a discrete biological classification scheme advocated. Reasoning methods for managing uncertainty are explained, in which the Bayesian and Dempster-Shafer calculi are cited as primary numerical schemes. Elicitation of qualitative knowledge on benthic invertebrates is described. The specificity of benthic response to changes in water quality leads to the adoption of a sensor model of data interpretation, in which a reference set of taxa provide probabilistic support for the biological classes. The significance of sensor states, including that of absence, is shown. Novel techniques of directly eliciting the required uncertainty measures are presented. Bayesian and Dempster-Shafer calculi were used to combine the evidence provided by the sensors. The performance of these automatic classifiers was compared with the expert's own discrete classification of sampled sites. Variations of sensor data weighting, combination order and belief representation were examined for their effect on classification performance. The behaviour of the calculi under evidential conflict and alternative combination rules was investigated. Small variations in evidential weight and the inclusion of evidence from sensors absent from a sample improved classification performance of Bayesian belief and support for singleton hypotheses. For simple support, inclusion of absent evidence decreased classification rate. The performance of Dempster-Shafer classification using consonant belief functions was comparable to Bayesian and singleton belief. Recommendations are made for further work in biological classification using uncertain reasoning methods, including the combination of multiple-expert opinion, the use of Bayesian networks, and the integration of classification software within a decision support system for water quality assessment.

The application of expert systems techniques in the design of durable concrete

This thesis describes work done exploring the application of expert system techniques to the domain of designing durable concrete. The nature of concrete durability design is described and some problems from the domain are discussed. Some related work on expert systems in concrete durability are described. Various implementation languages are considered - PROLOG and OPS5, and rejected in favour of a shell - CRYSTAL3 (later CRYSTAL4). Criteria for useful expert system shells in the domain are discussed. CRYSTAL4 is evaluated in the light of these criteria. Modules in various sub-domains (mix-design, sulphate attack, steel-corrosion and alkali aggregate reaction) are developed and organised under a BLACKBOARD system (called DEX). Extensions to the CRYSTAL4 modules are considered for different knowledge representations. These include LOTUS123 spreadsheets implementing models incorporating some of the mathematical knowledge in the domain. Design databases are used to represent tabular design knowledge. Hypertext representations of the original building standards texts are proposed as a tool for providing a well structured and extensive justification/help facility. A standardised approach to module development is proposed using hypertext development as a structured basis for expert systems development. Some areas of deficient domain knowledge are highlighted particularly in the use of data from mathematical models and in gaps and inconsistencies in the original knowledge source Digests.

The knowledge-based perspective of risk management in healthcare organisations

The aim of this research is to investigate how risk management in a healthcare organisation can be supported by knowledge management. The subject of research is the development and management of existing logs called "risk registers", through specific risk management processes employed in a N.H.S. (Foundation) Trust in England, in the U.K. Existing literature on organisational risk management stresses the importance of knowledge for the effective implementation of risk management programmes, claiming that knowledge used to perceive risk is biased by the beliefs of individuals and groups involved in risk management and therefore is considered incomplete. Further, literature on organisational knowledge management presents several definitions and categorisations of knowledge and approaches for knowledge manipulation in the organisational context as a whole. However, there is no specific approach regarding "how to deal" with knowledge in the course of organisational risk management. The research is based on a single case study, on a N.H.S. (Foundation) Trust, is influenced by principles of interpretivism and the frame of mind of Soft Systems Methodology (S.S.M.) to investigate the management of risk registers, from the viewpoint of people involved in the situation. Data revealed that knowledge about risks and about the existing risk management policy and procedures is situated in several locations in the Trust and is neither consolidated nor present where and when required. This study proposes a framework that identifies required knowledge for each of the risk management processes and outlines methods for conversion of this knowledge, based on the SECI knowledge conversion model, and activities to facilitate knowledge conversion so that knowledge is effectively used for the development of risk registers and the monitoring of risks throughout the whole Trust under study. This study has theoretical impact in the management science literature as it addresses the issue of incomplete knowledge raised in the risk management literature using concepts of the knowledge management literature, such as the knowledge conversion model. In essence, the combination of required risk and risk management related knowledge with the required type of communication for risk management creates the proposed methods for the support of each risk management process for the risk registers. Further, the indication of the importance of knowledge in risk management and the presentation of a framework that consolidates knowledge required for the risk management processes and proposes way(s) for the communication of this knowledge within a healthcare organisation have practical impact in the management of healthcare organisations.

Knowledge acquisition from L2 specialist texts

This research aims to investigate knowledge acquisition and concept formation in the domain of economics and business studies through a foreign language, English, from the very initial to the very final stage of development in the context of Higher Education in Turkey. It traces both the processes as well as the product of acquisition in order to provide a detailed picture of how knowledge acquisition occurs. It aims to explore ways in which the acquisition process can be facilitated and promoted while prospective students of the Department of Economics and Business Administration receive a language training programme, following the completion of which they will join their academic community which offers part of its courses through the English language. The study draws upon (some) theories of mental representation of knowledge, such as schema, frame and script. The concept of discourse community with its characteristics is investigated, enculturation of prospective students to acquire knowledge of their domain through L2 is explored, and the crucial role of the constructivist theory in relation to knowledge acquisition is highlighted. The present study was conducted through a process of enculturation taking place partly at the language centre of Çukurova University and partly at the target discourse community. The data utilised for initiating knowledge acquisition was obtained by establishing a corpus of economics and business texts, which the learners are expected to read during their academic courses utilising computerised technology. The method of think aloud protocols was used to analyse processes taking place in knowledge acquisition, while the product of what was acquired was investigated by means of written recall protocols. It has been discovered that knowledge acquisition operates on the basis of analogical and to a certain extent metaphorical reasoning. The evidence obtained from the think aloud protocols showed that neophytes were able to acquire fundamental concepts of their future domain by reaching the level of shared understanding with the members of their target community of the faculty. Diaries and questionnaire analyses demonstrated that enculturation facilitated learners' transition from the language centre into the target community. Analyses of the written recall protocols and examinations from the post-enculturation stage of the research showed that neophytes' academic performances in their target community were much higher than those of their non-enculturated counterparts. Processes learners go through and strategies they spontaneously make use of, especially while acquiring knowledge of a specific domain through L2 have so far remained unexplored research areas. The present research makes a potential contribution to the language and knowledge acquisition theories by examining closely and systematically the language and the strategies they employ in acquiring such knowledge. The research findings offer useful implications to English language teaching at language schools. Language teachers are provided with useful guidelines as to how they can provide prospective students of a particular academic community with an experience of acquiring fundamental concepts of their discipline before they become members of their target community.