The Bayesian Approach to Signal Modelling

In this paper, an introduction to Bayesian methods in signal processing will be given. The paper starts by considering the important issues of model selection and parameter estimation and derives analytic expressions for the model probabilities of two simple models. The idea of marginal estimation of certain model parameter is then introduced and expressions are derived for the marginal probabilitiy densities for frequencies in white Gaussian noise and a Bayesian approach to general changepoint analysis is given. Numerical integration methods are introduced based on Markov chain Monte Carlo techniques and the Gibbs sampler in particular.

A comparison of methods for the coupled analysis of floating structures

The dynamic analysis of a deepwater floating platform and the associated mooring/riser system should ideally be fully coupled to ensure a reliable response prediction. It is generally held that a time domain analysis is the only means of capturing the various coupling and nonlinear effects accurately. However, in recent work it has been found that for an ultra-deepwater floating system (2000m water depth), the highly efficient frequency domain approach can provide highly accurate response predictions. One reason for this is the accuracy of the drag linearization procedure over both first and second order motions, another reason is the minimal geometric nonlinearity displayed by the mooring lines in deepwater. In this paper, the aim is to develop an efficient analysis method for intermediate water depths, where both mooring/vessel coupling and geometric nonlinearity are of importance. It is found that the standard frequency domain approach is not so accurate for this case and two alternative methods are investigated. In the first, an enhanced frequency domain approach is adopted, in which line nonlinearities are linearized in a systematic way. In the second, a hybrid approach is adopted in which the low frequency motion is solved in the time domain while the high frequency motion is solved in the frequency domain; the two analyses are coupled by the fact that (i) the low frequency motion affects the mooring line geometry for the high frequency motion, and (ii) the high frequency motion affects the drag forces which damp the low frequency motion. The accuracy and efficiency of each of the methods are systematically compared. Copyright © 2007 by ASME.

Value roadmapping: A structured approach for early stage technology investment decisions

Deciding to invest in early stage technologies is one of the most important tasks of technology management and arguably also the most uncertain. It assumes a particular significance in the rise of technology companies in emerging economies, which have to make appropriate investment decisions. Technology managers already have a wide range of methods and tools at their disposal, but these are mostly focussed on quantitative measures such as discounted cash flow and real options techniques. However, in the early stages of technology development there seems to be a lot of dissatisfaction with these techniques as there appears to be a lack of accuracy with respect to the underlying assumptions that these models require. In order to complement these models this paper will discuss an alternative approach that we call value road-mapping. By adapting roadmapping techniques the potential value streams of early stages technologies can be plotted and hence a clearer consensus based picture of the future potential of new technologies emerges. Roadmapping is a workshop-based process bringing together multifunctional perspectives, and supporting communication in particular between technical and commercial groups. The study is work in progress and is based on a growing number of cases. (c) 2006 PICMET.

Design-phase-specific selection of user research methods

For increasing the usability of a medical device the usability engineering standards IEC 60601-1-6 and IEC 62366 suggest incorporating user information in the design and development process. However, practice shows that integrating user information and the related investigation of users, called user research, is difficult in the field of medical devices. In particular, identifying the most appropriate user research methods is a difficult process. This difficulty results from the complexity of the medical device industry, especially with respect to regulations and standards, the characteristics of this market and the broad range of potential user research methods available from various research disciplines. Against this background, this study aimed at guiding designers and engineers in selecting effective user research methods according to their stage in the design process. Two approaches are described which reduce the complexity of method selection by summarizing the high number of methods into homogenous method classes. These approaches are closely connected to the medical device industry characteristic design phases and therefore provide the possibility of selecting design-phase- specific user research methods. In the first approach potential user research methods are classified after their characteristics in the design process. The second approach suggests a method summarization according to their similarity in the data collection techniques and provides an additional linkage to design phase characteristics. Both approaches have been tested in practice and the results show that both approaches facilitate user research method selection. © 2009 Springer-Verlag.

A method for identifying scope and assumptions in developing and selecting methods and tools

This technical report describes a practical method consisting of a checklist and a supporting techniques for those planning or just starting to develop or select design tools and methods. The method helps to summarize and illustrate the envisaged tool or method by identifying its scope and the underlying assumptions. The resulting tool or method description clarifies the problem that is addressed, the approach and the possible implications, and can thus be used by a variety of people involved in assessing a tool or method in an early stage. For the developers themselves the method reveals how realistic the envisaged method or tool is, and whether the scope has to be narrowed.

Improving data quality in DSM modelling: A structural comparison approach

The Dependency Structure Matrix (DSM) has proved to be a useful tool for system structure elicitation and analysis. However, as with any modelling approach, the insights gained from analysis are limited by the quality and correctness of input information. This paper explores how the quality of data in a DSM can be enhanced by elicitation methods which include comparison of information acquired from different perspectives and levels of abstraction. The approach is based on comparison of dependencies according to their structural importance. It is illustrated through two case studies: creation of a DSM showing the spatial connections between elements in a product, and a DSM capturing information flows in an organisation. We conclude that considering structural criteria can lead to improved data quality in DSM models, although further research is required to fully explore the benefits and limitations of our proposed approach.

Combustion rumble prediction with integrated computational-fluid-dynamics/ low-order-model methods

The pressure oscillation within combustion chambers of aeroengines and industrial gas turbines is a major technical challenge to the development of high-performance and low-emission propulsion systems. In this paper, an approach integrating computational fluid dynamics and one-dimensional linear stability analysis is developed to predict the modes of oscillation in a combustor and their frequencies and growth rates. Linear acoustic theory was used to describe the acoustic waves propagating upstream and downstream of the combustion zone, which enables the computational fluid dynamics calculation to be efficiently concentrated on the combustion zone. A combustion oscillation was found to occur with its predicted frequency in agreement with experimental measurements. Furthermore, results from the computational fluid dynamics calculation provide the flame transfer function to describe unsteady heat release rate. Departures from ideal one-dimensional flows are described by shape factors. Combined with this information, low-order models can work out the possible oscillation modes and their initial growth rates. The approach developed here can be used in more general situations for the analysis of combustion oscillations. Copyright © 2012 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Linear quadratic game and non-cooperative predictive methods for potential application to modelling driver-AFS interactive steering control

This paper is concerned with the modelling of strategic interactions between the human driver and the vehicle active front steering (AFS) controller in a path-following task where the two controllers hold different target paths. The work is aimed at extending the use of mathematical models in representing driver steering behaviour in complicated driving situations. Two game theoretic approaches, namely linear quadratic game and non-cooperative model predictive control (non-cooperative MPC), are used for developing the driver-AFS interactive steering control model. For each approach, the open-loop Nash steering control solution is derived; the influences of the path-following weights, preview and control horizons, driver time delay and arm neuromuscular system (NMS) dynamics are investigated, and the CPU time consumed is recorded. It is found that the two approaches give identical time histories as well as control gains, while the non-cooperative MPC method uses much less CPU time. Specifically, it is observed that the introduction of weight on the integral of vehicle lateral displacement error helps to eliminate the steady-state path-following error; the increase in preview horizon and NMS natural frequency and the decline in time delay and NMS damping ratio improve the path-following accuracy. © 2013 Copyright Taylor and Francis Group, LLC.

Methodological implications of critical realism for mixed-methods research

Building on recent developments in mixed methods, we discuss the methodological implications of critical realism and explore how these can guide dynamic mixed-methods research design in information systems. Specifically, we examine the core ontological assumptions of CR in order to gain some perspective on key epistemological issues such as causation and validity, and illustrate how these shape our logic of inference in the research process through what is known as retroduction. We demonstrate the value of a CR-led mixed-methods research approach by drawing on a study that examines the impact of ICT adoption in the financial services sector. In doing so, we provide insight into the interplay between qualitative and quantitative methods and the particular value of applying mixed methods guided by CR methodological principles. Our positioning of demi-regularities within the process of retroduction contributes a distinctive development in this regard. We argue that such a research design enables us to better address issues of validity and the development of more robust meta-inferences.

A new approach to the analytical and numerical form-finding of tensegrity structures

We develop a new formulation for the form-finding of tensegrity structures in which the primary variables are the Cartesian components of element lengths. Both an analytical and a numerical implementation of the formulation are described; each require a description of the connectivity of the tensegrity, with the iterative numerical method also requiring a random starting vector of member force densities. The analytical and numerical form-finding of tensegrity structures is demonstrated through six examples, and the results obtained are compared and contrasted with those available in the literature to verify the accuracy and viability of the suggested methods. © 2013 Elsevier Ltd. All rights reserved.

Enhanced integrated modelling approach to reconfiguring manufacturing enterprises

Dynamism and uncertainty are real challenges for present day manufacturing enterprises (MEs). Reasons include: an increasing demand for customisation, reduced time to market, shortened product life cycles and globalisation. MEs can reduce competitive pressure by becoming reconfigurable and change-capable. However, modern manufacturing philosophies, including agile and lean, must complement the application of reconfigurable manufacturing paradigms. Choosing and applying the best philosophies and techniques is very difficult as most MEs deploy complex and unique configurations of processes and resource systems, and seek economies of scope and scale in respect of changing and distinctive product flows. It follows that systematic methods of achieving model driven reconfiguration and interoperation of component based manufacturing systems are required to design, engineer and change future MEs. This thesis, titled Enhanced Integrated Modelling Approach to Reconfiguring Manufacturing Enterprises , introduces the development and prototyping a model-driven environment for the design, engineering, optimisation and control of the reconfiguration of MEs with an embedded capability to handle various types of change. The thesis describes a novel systematic approach, namely enhanced integrated modelling approach (EIMA), in which coherent sets of integrated models are created that facilitates the engineering of MEs especially their production planning and control (PPC) systems. The developed environment supports the engineering of common types of strategic, tactical and operational processes found in many MEs. The EIMA is centred on the ISO standardised CIMOSA process modelling approach. Early study led to the development of simulation models during which various CIMOSA shortcomings were observed, especially in its support for aspects of ME dynamism. A need was raised to structure and create semantically enriched models hence forming an enhanced integrated modelling environment. The thesis also presents three industrial case examples: (1) Ford Motor Company; (2) Bradgate Furniture Manufacturing Company; and (3) ACM Bearings Company. In order to understand the system prior to realisation of any PPC strategy, multiple process segments of any target organisation need to be modelled. Coherent multi-perspective case study models are presented that have facilitated process reengineering and associated resource system configuration. Such models have a capability to enable PPC decision making processes in support of the reconfiguration of MEs. During these case studies, capabilities of a number of software tools were exploited such as Arena®, Simul8®, Plant Simulation®, MS Visio®, and MS Excel®. Case study results demonstrated effectiveness of the concepts related to the EIMA. The research has resulted in new contributions to knowledge in terms of new understandings, concepts and methods in following ways: (1) a structured model driven integrated approach to the design, optimisation and control of future reconfiguration of MEs. The EIMA is an enriched and generic process modelling approach with capability to represent both static and dynamic aspects of an ME; and (2) example application cases showing benefits in terms of reduction in lead time, cost and resource load and in terms of improved responsiveness of processes and resource systems with a special focus on PPC; (3) identification and industrial application of a new key performance indicator (KPI) known as P3C the measuring and monitoring of which can aid in enhancing reconfigurability and responsiveness of MEs; and (4) an enriched modelling concept framework (E-MUNE) to capture requirements of static and dynamic aspects of MEs where the conceptual framework has the capability to be extended and modified according to the requirements. The thesis outlines key areas outlining a need for future research into integrated modelling approaches, interoperation and updating mechanisms of partial models in support of the reconfiguration of MEs.

2.1 GHz MOS mixer linearisation approach for IIP2 enhancement using multiple factor compensation

An integrated downconversion CMOS mixer incorporating a comprehensive compensation scheme is presented which aims to minimise second-order intermodulation distortion (IMD2). Unlike previously reported IMD2 calibration schemes which tune only one nonlinear factor at a time, the presented solution allows simultaneous adjustment of several different factors thus achieving a better compensation. The mixer has been implemented in UMC 0.18 μm CMOS to verify the proposed scheme and for comparison with alternative compensation methods. Measurements show that the solution described can improve the input intercept point (IIP2) by over 20 dB while maintaining good amplification and noise performance. IMD2 calibration results are presented and show useful advantages over other approaches. To the best of the authors' knowledge, this scheme for IMD2 calibration has not been previously reported. © The Institution of Engineering and Technology 2013.

Structuring technological information for technology roadmapping: Data mining approach

Most research on technology roadmapping has focused on its practical applications and the development of methods to enhance its operational process. Thus, despite a demand for well-supported, systematic information, little attention has been paid to how/which information can be utilised in technology roadmapping. Therefore, this paper aims at proposing a methodology to structure technological information in order to facilitate the process. To this end, eight methods are suggested to provide useful information for technology roadmapping: summary, information extraction, clustering, mapping, navigation, linking, indicators and comparison. This research identifies the characteristics of significant data that can potentially be used in roadmapping, and presents an approach to extracting important information from such raw data through various data mining techniques including text mining, multi-dimensional scaling and K-means clustering. In addition, this paper explains how this approach can be applied in each step of roadmapping. The proposed approach is applied to develop a roadmap of radio-frequency identification (RFID) technology to illustrate the process practically. © 2013 © 2013 Taylor & Francis.

Optimization on manifolds: Methods and applications

This paper provides an introduction to the topic of optimization on manifolds. The approach taken uses the language of differential geometry, however,we choose to emphasise the intuition of the concepts and the structures that are important in generating practical numerical algorithms rather than the technical details of the formulation. There are a number of algorithms that can be applied to solve such problems and we discuss the steepest descent and Newton's method in some detail as well as referencing the more important of the other approaches.There are a wide range of potential applications that we are aware of, and we briefly discuss these applications, as well as explaining one or two in more detail. © 2010 Springer -Verlag Berlin Heidelberg.