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Faculty of Accounting and Informatics

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Subject: search.filters.subject.Computer-aided design

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    Meta-heuristic search methods for big data analytics and visualization of frequently changed patterns
    (2019-03-20) Agbehadji, Israel Edem; Millham, Richard Charles; Yang, Hongji
    Throughout the world, data plays a prominent role in making decisions relevant to the socio-economic growth of organizations. As organizations grow, they tend to use diverse technologies or platforms to collect data and make data readily available for quick decision-making. These technologies have resulted in exponential growth of data whereby the problem of managing this data in a limited time interval increases in complexity, starting from the preprocessing stage to the visualization stage. Apart from the issue of managing the huge growth of data, finding a suitable method to manage certain aspects of this frequently changed data has been overlooked. These frequent changes in data form the topic of interest of this thesis. Consequently, there is a need to develop a framework both to manage big data at different stages of processing, from preprocessing to visualization, and to handle frequently changed data. The need to develop such a framework arises because traditional methods/algorithms are limited to finding frequent patterns of frequently occurring items while overlooking frequently changed data, which has a numeric and time dimension that can provide interesting business insights. Additionally, traditional visualization methods are challenged with performance scalability and response time. This thesis looked at resolving this limitation by using a meta-heuristic/bio-inspired algorithm that is modelled based on observation of the behavior and characteristics of two different animals, namely the kestrel and the dung beetle. The motivation behind the use of these animals is their ability to explore, exploit and adapt to different situations in their natural environment. The development of the computational model and testing with actual data were formulated as a six-step procedure. Based on the six steps, the proposed computational model was evaluated against selected comparative algorithms, namely BAT, WSA-MP, PSO, Firefly and ACO. The main findings on optimal value/results suggest that, in handling frequently changed data during the data preprocessing, pattern discovery and visualization stages, the proposed computational models performed optimally against the comparative meta-heuristic algorithms on test datasets. Further statistical tests, using the Wilcoxon signed rank test, were conducted on optimal results from the comparative meta-heuristic algorithms. The basis for using the statistical procedure was to select the best choice of algorithm without making any underlying assumption on accuracy of results from the comparative meta-heuristic algorithms. Theoretically, the study contributes to enhancing frequency of item frameworks by including time and numeric dimensions of item occurrence. Practically, the contribution of the study lies in its finding frequently changed patterns in big data analytics. Additionally, the concept of half-life of substances/trails was applied as part of the computational model, and this also forms part of the unique contribution of this thesis. The half-life constitutes the lifetime of interestingness of recent patterns that were discovered. In summary, this thesis is about the mathematical formulation of animal behavior and characteristics into an implementable big data management algorithm and its application to frequently changed patterns.
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    Developing a model to design and implement computer user interfaces in rural communities, an exploratory study
    (2014-10-03) Heukelman, Delene; Olugbara, Oludayo O.
    This thesis reports on original exploratory study that is aimed at contributing towards understanding of factors that influence Africa users support for alternative object metaphors for user interface icons. One of the great impediments for efficient utilization of information systems is the existing gap between system designs that typically follow western cues for crafting user interfaces and actual users who use those systems within their diverse cultural frames. The problem remains important because of the wider penetration of information systems, which serve as modern technology tools to improve service provisioning worldwide. In order to overcome the problem of optimum utilization of information systems, previous studies have proposed culturally adaptive user interfaces. The basic principle behind culture adaptive interfaces is to develop intelligent user interfaces that can automatically adapt to user contexts. However, the challenges with the new proposals for adaptive user interfaces are how to best model information about users, how to access the cultural background of individual users and empirically examine the effects of culture on user interface preferences. In order to properly contribute to solving these problems, an exploratory study was conducted to empirically establish African rural users support for alternative village object metaphors, examine effects of culture on user support and investigate response characteristic among culturally diverse user groups. The synthesis of bodystorming and cultural probes methodology was applied to engage the participation of African rural users in the study. Technology support model was developed to measure user knowledge, comprehension, skills, performance and support for alternative African village metaphors as interface icons. The partial least square analytic modelling technique and finite mixture path segmentation model were used to test a set of research hypotheses and detect heterogeneity in 71 respondent data generated. Experimental results of this study show that human cognitive factors of technology knowledge, comprehension and performance influence African users support for alternative village object metaphors as interface icons. However, skill factor is not found to influence user support for alternative African village object metaphors. The factor of culture is found to moderate the effects of comprehension on user support and effects of user performance on user support. This study also identifies three segments of African users that result in heterogeneity within the inner path model.