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Thesis (M.A.)--University of Texas at El Paso, 2008. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

There are two main defined classes of uncertainty namely: fuzziness and ambiguity, where ambiguity is ‘one-to-many’ relationship between syntax and semantic of a proposition. This definition seems that it ignores ‘many-to-many’ relationship ambiguity type of uncertainty. In this thesis, we shall use complex-uncertainty to term many-to-many relationship ambiguity type of uncertainty. This research proposes a new approach for handling the complex ambiguity type of uncertainty that may exist in data, for software engineering of predictive Data Mining (DM) classification models. The proposed approach is based on Relative-Fuzzy Logic (RFL), a novel type of fuzzy logic. RFL defines a new formulation of the problem of ambiguity type of uncertainty in terms of States Of Proposition (SOP). RFL describes its membership (semantic) value by using the new definition of Domain of Proposition (DOP), which is based on the relativity principle as defined by possible-worlds logic. To achieve the goal of proposing RFL, a question is needed to be answered, which is: how these two approaches; i.e. fuzzy logic and possible-world, can be mixed to produce a new membership value set (and later logic) that able to handle fuzziness and multiple viewpoints at the same time? Achieving such goal comes via providing possible world logic the ability to quantifying multiple viewpoints and also model fuzziness in each of these multiple viewpoints and expressing that in a new set of membership value. Furthermore, a new architecture of Hierarchical Neural Network (HNN) called ML/RFL-Based Net has been developed in this research, along with a new learning algorithm and new recalling algorithm. The architecture, learning algorithm and recalling algorithm of ML/RFL-Based Net follow the principles of RFL. This new type of HNN is considered to be a RFL computation machine. The ability of the Relative Fuzzy-based DM prediction model to tackle the problem of complex ambiguity type of uncertainty has been tested. Special-purpose Integrated Development Environment (IDE) software, which generates a DM prediction model for speech recognition, has been developed in this research too, which is called RFL4ASR. This special purpose IDE is an extension of the definition of the traditional IDE. Using multiple sets of TIMIT speech data, the prediction model of type ML/RFL-Based Net has classification accuracy of 69.2308%. This accuracy is higher than the best achievements of WEKA data mining machines given the same speech data.

Mega construction projects are complex undertakings. The complexity is increased during a construction boom in a city such as Dubai where more than 80% of material and labour resources are imported. The complexities inherent in mega construction projects include uncertainty and interdependencies, which affect project management performance at the operational level where most of the problems occur. Understanding these processes, how they interrelate and how to overcome the complexities is crucial for increasing the chances of project management success. This research contributed to construction project management theory and practice by using a highly inductive exploratory qualitative approach for capturing formal and informal processes in mega construction projects in Dubai. A dynamic model depicting the complementary formal and informal processes is developed showing formal and informal processes and how they interrelate to reduce complexity. Guidelines on how and when to use specific processes are provided as a framework for the model. This framework may be used to help develop communication processes in future complex projects to increase chances of project management success. The research was conducted by exploring two case study projects fitting the characteristics of mega construction projects. Both case study projects were of values above 1.5 Billion US Dollars and were similar in scope with elements including amusement parks, retail areas, hotels, extensive infrastructure and large landscape areas. Both case study projects were of an experimental character, considered an engineering achievement, complex, and thereby, difficult to control. The research data were collected through semi-structured interviews with 83 project staff from both case study projects. Rich picture diagrams of the organization and processes were made from data collected during the interviews and case study project documents. The analysis was performed in three phases where the results from each phase were built upon cumulatively. The first phase examined what the most crucial critical success factors (CSFs) were in the case study projects. These were revealed to be communication, top management support and effective change management. In the second phase each CSF was analyzed where it was found it that the majority of important communication modes were informal and were was most effective in reducing complexity. Furthermore, it was found that the characteristics of the client were crucial in both case study projects. The third phase involved development of the dynamic hybrid model from the rich picture diagrams created showing the interplay between formal and informal processes. It was found that informal processes are ad-hoc and chaotic in nature and controlled by individuals in the project. Development of guidelines for the positive use of informal processes was required. From the analysis it was found that the characteristics of client staff and individuals in the case study projects provided the main guidelines for effective use of the hybrid model. The research provides insights into the formal and informal processes and the reduction and management of complexity inherent in mega construction projects. Current research in managing complexity is from the perspective of the formal process where the informal processes are neglected, despite research and practice indicating their importance in construction projects. The research presents a systemic dynamic model of the processes for mega construction projects revealing that formal and informal processes are required and are complementary. Guidelines for the successful use of the model provide a framework for its application in practice. This shows how it can be used to inform understanding of processes in the context of the research. The model and guidelines were validated via discussions with practitioners experienced in construction of mega projects. Future work should expand the findings to applications of the model in practice for management of complex projects. The model may be used by practitioners to act as a guide in how to manage construction processes to consciously overcome the inherent complexities to achieve project management objectives. This tool may also be used to inform clients of the inherent complexities and the level of informality required to overcome them. IT/IS practitioners may use the model and framework to understand the complexities in construction, and thereby, develop systems that are practically applied in construction projects. Researchers in the field may build upon the model and findings to increase knowledge regarding construction processes, particularly informal processes.

This PhD thesis was developed in the context of contemporary challenges within water policy and governance; specifically the issue of managing diffuse pollution risk in fresh water catchments. As highlighted in the European Water Framework Directive (WFD) diffuse pollution poses a major risk in many European catchments where the sustainability of the ecosystems and water uses is compromised by intensive agriculture. The challenge for catchment management is the tricky nature of diffuse pollution. It is what you would term a ‘wicked problem’ or ‘Post Normal Science’ wherein the facts are uncertain, values are in dispute, stakes are high and decision-making is urgent (Funtowicz and Ravetz, 1993; Patterson et al., 2013). In response to the WFD the UK Government have proposed the Catchment Based Approach (CaBA) which represents a paradigmatic shift in approaches to water management; from a ‘command and control’ approach (i.e. the historic practice of direct regulation) to a participatory governance approach (i.e. devolution of power and involvement local stakeholders) (Dryzek, 2005; Müller-Grabherr et al., 2014). The project had two aims. The practical aim was to identify the drivers and barriers to delivering the CaBA. The academic aim was to employ the relational concept of ambiguity to explore why and how catchment stakeholders understand, frame and respond to diffuse pollution risk differently. In order to address these aims Timothy embedded himself in Loe Pool Forum (www.loepool.org) for four years. Loe Pool Forum (LPF) are a voluntary catchment partnership, based in West Cornwall, working to address the risk of diffuse pollution through taking a CaBA at the WFD waterbody scale. The methodology was directed by Participatory Action Research (PAR) and underpinned by ethnography. PAR enabled Timothy to work collaboratively to engender positive change within LPF while ethnography generated data upon how partnership and participatory working happens in practice. New insights into the geographies of risk stemmed from the application of ambiguity as the conceptual lever. Ambiguity is a dimension of uncertainty which accounts for the relational properties of risk. Ambiguity is defined as the simultaneous presence of multiple frames of reference about a certain phenomenon (Brugnach et al., 2007). Timothy examined ambiguity from three different directions. Firstly, where the ambiguities are in catchment management and how local partnerships negotiate them. Secondly, how risk frames are produced by both water scientists and the agricultural community. Thirdly, what the drivers and barriers are to delivering the CaBA. By thinking through risk relationally this thesis provides new insights into the practice of catchment management and the socio-cultural geographies around the water-environment.