Closing the loop of design and analysis : Parametric modelling tools for early decision support

There is a growing need for parametric design software that communicates building performance feedback in early architectural exploration to support decision-making. This paper examines how the circuit of design and analysis process can be closed to provide active and concurrent feedback between architecture and services engineering domains. It presents the structure for an openly customisable design system that couples parametric modelling and energy analysis software to allow designers to assess the performance of early design iterations quickly. Finally, it discusses how user interactions with the system foster information exchanges that facilitate the sharing of design intelligence across disciplines.

A design approach to teaching new product development

The educational unit new product development, taught within the industrial design program at the Queensland University of Technology (QUT) introduces the relationship between product design and commercialisation to third year industrial design undergraduate students. In which, they are exposed for the first time to product strategy development aimed at meeting consumer expectations, whilst at the same time achieving corporate objectives. Delivered content such as intellectual property, market opportunities, competitor analysis and investor requirements are taught within the thirteen week semester timeframe. New product development theory is not a new field. However, the design approach to teaching this theory and more importantly how designers can use it in the design process is novel. This paper provides an overview of the curriculum design of this unit as well as its incremental development over the past four year duration period. Student project outcomes and more importantly the process and tools from this unit are also discussed and presented.

Engineering-based modelling experiences in the elementary classroom

Introducing engineering-based model-eliciting experiences in the elementary curriculum is a new and increasingly important domain of research by mathematics, science, technology, and engineering educators. Recent research has raised questions about the context of engineering problems that are meaningful, engaging, and inspiring for young students. In the present study an environmental engineering activity was implemented in two classes of 11-year-old students in Cyprus. The problem required students to develop a procedure for selecting among alternative countries from which to buy water. Students created a range of models that adequately solved the problem although not all models took into account all of the data provided. The models varied in the number of problem factors taken into consideration and also in the different approaches adopted in dealing with the problem factors. At least two groups of students integrated into their models the environmental aspect of the problem (energy consumption, water pollution) and further refined their models. Results indicate that engineering model-eliciting activities can be introduced effectively into the elementary curriculum, providing rich opportunities for students to deal with engineering contexts and to apply their learning in mathematics and science to solving real-world engineering problems.

Complex modelling in the primary/middle school years

The world’s increasing complexity, competitiveness, interconnectivity, and dependence on technology generate new challenges for nations and individuals that cannot be met by continuing education as usual (Katehi, Pearson, & Feder, 2009). With the proliferation of complex systems have come new technologies for communication, collaboration, and conceptualisation. These technologies have led to significant changes in the forms of mathematical and scientific thinking that are required beyond the classroom. Modelling, in its various forms, can develop and broaden children’s mathematical and scientific thinking beyond the standard curriculum. This paper first considers future competencies in the mathematical sciences within an increasingly complex world. Next, consideration is given to interdisciplinary problem solving and models and modelling. Examples of complex, interdisciplinary modelling activities across grades are presented, with data modelling in 1st grade, model-eliciting in 4th grade, and engineering-based modelling in 7th-9th grades.

An additional step towards modelling the mechanical behaviour of sugar cane bagasse

A better understanding of the behaviour of prepared cane and bagasse, especially the ability to model the mechanical behaviour of bagasse as it is squeezed in a milling unit to extract juice, would help identify how to improve the current milling process; for example to reduce final bagasse moisture. Previous investigations have proven with certainty that juice flow through bagasse obeys Darcy’s permeability law, that the grip of the rough surface of the grooves on the bagasse can be represented by the Mohr- Coulomb failure criterion for soils, and that the internal mechanical behaviour of the bagasse can be represented by critical state behaviour similar to that of sand and clay. Current Finite Element Models (FEM) available in commercial software have adequate permeability models. However, commercial software does not contain an adequate mechanical model for bagasse. Progress has been made in the last ten years towards implementing a mechanical model for bagasse in finite element software code. This paper builds on that progress and carries out a further step towards obtaining an adequate material model. In particular, the prediction of volume change during shearing of normally consolidated final bagasse is addressed.

Load modelling : induction motors

Modelling the power systems load is a challenge since the load level and composition varies with time. An accurate load model is important because there is a substantial component of load dynamics in the frequency range relevant to system stability. The composition of loads need to be charaterised because the time constants of composite loads affect the damping contributions of the loads to power system oscillations, and their effects vary with the time of the day, depending on the mix of motors loads. This chapter has two main objectives: 1) describe the load modelling in small signal using on-line measurements; and 2) present a new approach to develop models that reflect the load response to large disturbances. Small signal load characterisation based on on-line measurements allows predicting the composition of load with improved accuracy compared with post-mortem or classical load models. Rather than a generic dynamic model for small signal modelling of the load, an explicit induction motor is used so the performance for larger disturbances can be more reliably inferred. The relation between power and frequency/voltage can be explicitly formulated and the contribution of induction motors extracted. One of the main features of this work is the induction motor component can be associated to nominal powers or equivalent motors

A descriptive approach for power system stability and security assessment

Power system dynamic analysis and security assessment are becoming more significant today due to increases in size and complexity from restructuring, emerging new uncertainties, integration of renewable energy sources, distributed generation, and micro grids. Precise modelling of all contributed elements/devices, understanding interactions in detail, and observing hidden dynamics using existing analysis tools/theorems are difficult, and even impossible. In this chapter, the power system is considered as a continuum and the propagated electomechanical waves initiated by faults and other random events are studied to provide a new scheme for stability investigation of a large dimensional system. For this purpose, the measured electrical indices (such as rotor angle and bus voltage) following a fault in different points among the network are used, and the behaviour of the propagated waves through the lines, nodes, and buses is analyzed. The impact of weak transmission links on a progressive electromechanical wave using energy function concept is addressed. It is also emphasized that determining severity of a disturbance/contingency accurately, without considering the related electromechanical waves, hidden dynamics, and their properties is not secure enough. Considering these phenomena takes heavy and time consuming calculation, which is not suitable for online stability assessment problems. However, using a continuum model for a power system reduces the burden of complex calculations

User behaviour modelling in a multi-dimensional environment for personalization and recommendation

Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

Bayesian mixtures for modelling complex medical data : a case study in Parkinson’s disease

Mixture models are a flexible tool for unsupervised clustering that have found popularity in a vast array of research areas. In studies of medicine, the use of mixtures holds the potential to greatly enhance our understanding of patient responses through the identification of clinically meaningful clusters that, given the complexity of many data sources, may otherwise by intangible. Furthermore, when developed in the Bayesian framework, mixture models provide a natural means for capturing and propagating uncertainty in different aspects of a clustering solution, arguably resulting in richer analyses of the population under study. This thesis aims to investigate the use of Bayesian mixture models in analysing varied and detailed sources of patient information collected in the study of complex disease. The first aim of this thesis is to showcase the flexibility of mixture models in modelling markedly different types of data. In particular, we examine three common variants on the mixture model, namely, finite mixtures, Dirichlet Process mixtures and hidden Markov models. Beyond the development and application of these models to different sources of data, this thesis also focuses on modelling different aspects relating to uncertainty in clustering. Examples of clustering uncertainty considered are uncertainty in a patient’s true cluster membership and accounting for uncertainty in the true number of clusters present. Finally, this thesis aims to address and propose solutions to the task of comparing clustering solutions, whether this be comparing patients or observations assigned to different subgroups or comparing clustering solutions over multiple datasets. To address these aims, we consider a case study in Parkinson’s disease (PD), a complex and commonly diagnosed neurodegenerative disorder. In particular, two commonly collected sources of patient information are considered. The first source of data are on symptoms associated with PD, recorded using the Unified Parkinson’s Disease Rating Scale (UPDRS) and constitutes the first half of this thesis. The second half of this thesis is dedicated to the analysis of microelectrode recordings collected during Deep Brain Stimulation (DBS), a popular palliative treatment for advanced PD. Analysis of this second source of data centers on the problems of unsupervised detection and sorting of action potentials or "spikes" in recordings of multiple cell activity, providing valuable information on real time neural activity in the brain.

The rise of co-creative consumers : user experience sharing behaviour in online communities

This thesis examines consumer initiated value co-creation behaviour in the context of convergent mobile online services using a Service-Dominant logic (SD logic) theoretical framework. It focuses on non-reciprocal marketing phenomena such as open innovation and user generated content whereby new viable business models are derived and consumer roles and community become essential to the success of business. Attention to customers. roles and personalised experiences in value co-creation has been recognised in the literature (e.g., Prahalad & Ramaswamy, 2000; Prahalad, 2004; Prahalad & Ramaswamy, 2004). Similarly, in a subsequent iteration of their 2004 version of the foundations of SD logic, Vargo and Lusch (2006) replaced the concept of value co-production with value co-creation and suggested that a value co-creation mindset is essential to underpin the firm-customer value creation relationship. Much of this focus, however, has been limited to firm initiated value co-creation (e.g., B2B or B2C), while consumer initiated value creation, particularly consumer-to-consumer (C2C) has received little attention in the SD logic literature. While it is recognised that not every consumer wishes to make the effort to engage extensively in co-creation processes (MacDonald & Uncles, 2009), some consumers may not be satisfied with a standard product, instead they engage in the effort required for personalisation that potentially leads to greater value for themselves, and which may benefit not only the firm, but other consumers as well. Literature suggests that there are consumers who do, and as a result initiate such behaviour and expend effort to engage in co-creation activity (e.g., Gruen, Osmonbekov and Czaplewski, 2006; 2007 MacDonald & Uncles, 2009). In terms of consumers. engagement in value proposition (co-production) and value actualisation (co-creation), SD logic (Vargo & Lusch, 2004, 2008) provides a new lens that enables marketing scholars to transcend existing marketing theory and facilitates marketing practitioners to initiate service centric and value co-creation oriented marketing practices. Although the active role of the consumer is acknowledged in the SD logic oriented literature, we know little about how and why consumers participate in a value co-creation process (Payne, Storbacka, & Frow, 2008). Literature suggests that researchers should focus on areas such as C2C interaction (Gummesson 2007; Nicholls 2010) and consumer experience sharing and co-creation (Belk 2009; Prahalad & Ramaswamy 2004). In particular, this thesis seeks to better understand consumer initiated value co-creation, which is aligned with the notion that consumers can be resource integrators (Baron & Harris, 2008) and more. The reason for this focus is that consumers today are more empowered in both online and offline contexts (Füller, Mühlbacher, Matzler, & Jawecki, 2009; Sweeney, 2007). Active consumers take initiatives to engage and co-create solutions with other active actors in the market for their betterment of life (Ballantyne & Varey, 2006; Grönroos & Ravald, 2009). In terms of the organisation of the thesis, this thesis first takes a „zoom-out. (Vargo & Lusch, 2011) approach and develops the Experience Co-Creation (ECo) framework that is aligned with balanced centricity (Gummesson, 2008) and Actor-to-Actor worldview (Vargo & Lusch, 2011). This ECo framework is based on an extended „SD logic friendly lexicon. (Lusch & Vargo, 2006): value initiation and value initiator, value-in-experience, betterment centricity and betterment outcomes, and experience co-creation contexts derived from five gaps identified from the SD logic literature review. The framework is also designed to accommodate broader marketing phenomena (i.e., both reciprocal and non-reciprocal marketing phenomena). After zooming out and establishing the ECo framework, the thesis takes a zoom-in approach and places attention back on the value co-creation process. Owing to the scope of the current research, this thesis focuses specifically on non-reciprocal value co-creation phenomena initiated by consumers in online communities. Two emergent concepts: User Experience Sharing (UES) and Co-Creative Consumers are proposed grounded in the ECo framework. Together, these two theorised concepts shed light on the following two propositions: (1) User Experience Sharing derives value-in-experience as consumers make initiative efforts to participate in value co-creation, and (2) Co-Creative Consumers are value initiators who perform UES. Three research questions were identified underpinning the scope of this research: RQ1: What factors influence consumers to exhibit User Experience Sharing behaviour? RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part of value co-creation behaviour? RQ3: What are the characteristics of Co-Creative Consumers? To answer these research questions, two theoretical models were developed: the User Experience Sharing Behaviour Model (UESBM) grounded in the Theory of Planned Behaviour framework, and the Co-Creative Consumer Motivation Model (CCMM) grounded in the Motivation, Opportunity, Ability framework. The models use SD logic consistent constructs and draw upon multiple streams of literature including consumer education, consumer psychology and consumer behaviour, and organisational psychology and organisational behaviour. These constructs include User Experience Sharing with Other Consumers (UESC), User Experience Sharing with Firms (UESF), Enjoyment in Helping Others (EIHO), Consumer Empowerment (EMP), Consumer Competence (COMP), and Intention to Engage in User Experience Sharing (INT), Attitudes toward User Experience Sharing (ATT) and Subjective Norm (SN) in the UESBM, and User Experience Sharing (UES), Consumer Citizenship (CIT), Relating Needs of Self (RELS) and Relating Needs of Others (RELO), Newness (NEW), Mavenism (MAV), Use Innovativeness (UI), Personal Initiative (PIN) and Communality (COMU) in the CCMM. Many of these constructs are relatively new to marketing and require further empirical evidence for support. Two studies were conducted to underpin the corresponding research questions. Study One was conducted to calibrate and re-specify the proposed models. Study Two was a replica study to confirm the proposed models. In Study One, data were collected from a PC DIY online community. In Study Two, a majority of data were collected from Apple product online communities. The data were examined using structural equation modelling and cluster analysis. Considering the nature of the forums, the Study One data is considered to reflect some characteristics of Prosumers and the Study Two data is considered to reflect some characteristics of Innovators. The results drawn from two independent samples (N = 326 and N = 294) provide empirical support for the overall structure theorised in the research models. The results in both models show that Enjoyment in Helping Others and Consumer Competence in the UESBM, and Consumer Citizenship and Relating Needs in CCMM have significant impacts on UES. The consistent results appeared in both Study One and Study Two. The results also support the conceptualisation of Co-Creative Consumers and indicate Co-Creative Consumers are individuals who are able to relate the needs of themselves and others and feel a responsibility to share their valuable personal experiences. In general, the results shed light on "How and why consumers voluntarily participate in the value co-creation process?. The findings provide evidence to conceptualise User Experience Sharing behaviour as well as the Co-Creative Consumer using the lens of SD logic. This research is a pioneering study that incorporates and empirically tests SD logic consistent constructs to examine a particular area of the logic – that is consumer initiated value co-creation behaviour. This thesis also informs practitioners about how to facilitate and understand factors that engage with either firm or consumer initiated online communities.

Integrating collaborative filtering and search-based techniques for personalized online product recommendation

The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

Data modelling with first-grade students

This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling. Results are reported from the first year of a 3-year longitudinal study in which three classes of first-grade children (6-year-olds) and their teachers engaged in data modelling activities. The theme of Looking after our Environment, part of the children’s science curriculum, provided the task context. The goals for the two activities addressed here included engaging children in core components of data modelling, namely, selecting attributes, structuring and representing data, identifying variation in data, and making predictions from given data. Results include the various ways in which children represented and re represented collected data, including attribute selection, and the metarepresentational competence they displayed in doing so. The “data lenses” through which the children dealt with informal inference (variation and prediction) are also reported.

Multi-body modelling of wagon trains for crashworthiness analysis

Three-dimensional wagon train models have been developed for the crashworthiness analysis using multi-body dynamics approach. The contributions of the train size (number of wagon) to the frontal crash forces can be identified through the simulations. The effects of crash energy management (CEM) design and crash speed on train crashworthiness are examined. The CEM design can significantly improve the train crashworthiness and the consequential vehicle stability performance - reducing derailment risks.

Mathematical modelling of tumour-induced angiogenesis

The growth of solid tumours beyond a critical size is dependent upon angiogenesis, the formation of new blood vessels from an existing vasculature. Tumours may remain dormant at microscopic sizes for some years before switching to a mode in which growth of a supportive vasculature is initiated. The new blood vessels supply nutrients, oxygen, and access to routes by which tumour cells may travel to other sites within the host (metastasize). In recent decades an abundance of biological research has focused on tumour-induced angiogenesis in the hope that treatments targeted at the vasculature may result in a stabilisation or regression of the disease: a tantalizing prospect. The complex and fascinating process of angiogenesis has also attracted the interest of researchers in the field of mathematical biology, a discipline that is, for mathematics, relatively new. The challenge in mathematical biology is to produce a model that captures the essential elements and critical dependencies of a biological system. Such a model may ultimately be used as a predictive tool. In this thesis we examine a number of aspects of tumour-induced angiogenesis, focusing on growth of the neovasculature external to the tumour. Firstly we present a one-dimensional continuum model of tumour-induced angiogenesis in which elements of the immune system or other tumour-cytotoxins are delivered via the newly formed vessels. This model, based on observations from experiments by Judah Folkman et al., is able to show regression of the tumour for some parameter regimes. The modelling highlights a number of interesting aspects of the process that may be characterised further in the laboratory. The next model we present examines the initiation positions of blood vessel sprouts on an existing vessel, in a two-dimensional domain. This model hypothesises that a simple feedback inhibition mechanism may be used to describe the spacing of these sprouts with the inhibitor being produced by breakdown of the existing vessel's basement membrane. Finally, we have developed a stochastic model of blood vessel growth and anastomosis in three dimensions. The model has been implemented in C++, includes an openGL interface, and uses a novel algorithm for calculating proximity of the line segments representing a growing vessel. This choice of programming language and graphics interface allows for near-simultaneous calculation and visualisation of blood vessel networks using a contemporary personal computer. In addition the visualised results may be transformed interactively, and drop-down menus facilitate changes in the parameter values. Visualisation of results is of vital importance in the communication of mathematical information to a wide audience, and we aim to incorporate this philosophy in the thesis. As biological research further uncovers the intriguing processes involved in tumourinduced angiogenesis, we conclude with a comment from mathematical biologist Jim Murray, Mathematical biology is : : : the most exciting modern application of mathematics.