Physical and MAC layer techniques for next generation satellite communications

In this thesis, we consider four different scenarios of interest in modern satellite communications. For each scenario, we will propose the use of advanced solutions aimed at increasing the spectral efficiency of the communication links. First, we will investigate the optimization of the current standard for digital video broadcasting. We will increase the symbol rate of the signal and determine the optimal signal bandwidth. We will apply the time packing technique and propose a specifically design constellation. We will then compare some receiver architectures with different performance and complexity. The second scenario still addresses broadcast transmissions, but in a network composed of two satellites. We will compare three alternative transceiver strategies, namely, signals completely overlapped in frequency, frequency division multiplexing, and the Alamouti space-time block code, and, for each technique, we will derive theoretical results on the achievable rates. We will also evaluate the performance of said techniques in three different channel models. The third scenario deals with the application of multiuser detection in multibeam satellite systems. We will analyze a case in which the users are near the edge of the coverage area and, hence, they experience a high level of interference from adjacent cells. Also in this case, three different approaches will be compared. A classical approach in which each beam carries information for a user, a cooperative solution based on time division multiplexing, and the Alamouti scheme. The information theoretical analysis will be followed by the study of practical coded schemes. We will show that the theoretical bounds can be approached by a properly designed code or bit mapping. Finally, we will consider an Earth observation scenario, in which data is generated on the satellite and then transmitted to the ground. We will study two channel models, taking into account one or two transmit antennas, and apply techniques such as time and frequency packing, signal predistortion, multiuser detection and the Alamouti scheme.

Semi-global techniques in image matching and change detection with applications to civil and environmental engineering.

This work of thesis wants to present a dissertation of the wide range of modern dense matching algorithms, which are spreading in different application and research fields, with a particular attention to the innovative “Semi-Global” matching techniques. The choice of develop a semi-global numerical code was justified by the need of getting insight on the variables and strategies that affect the algorithm performances with the primary objective of maximizing the method accuracy and efficiency, and the results level of completeness. The dissertation will consist in the metrological characterization of the proprietary implementation of the semi-global matching algorithm, evaluating the influence of several matching variables and functions implemented in the process and comparing the accuracy and completeness of different results (digital surface models, disparity maps and 2D displacement fields) obtained using our code and other commercial and open-source matching programs in a wide variety of application fields.

The use of proteomic techniques to explore the holistic effects of nutrients in vivo

The availability of ‘omics’ technologies is transforming scientific approaches to physiological problems from a reductionist viewpoint to that of a holistic viewpoint. This is of profound importance in nutrition, since the integration of multiple systems at the level of gene expression on the synthetic side through to metabolic enzyme activity on the degradative side combine to govern nutrient availability to tissues. Protein activity is central to the process of nutrition from the initial absorption of nutrients via uptake carriers in the gut, through to distribution and transport in the blood, metabolism by degradative enzymes in tissues and excretion through renal tubule exchange proteins. Therefore, the global profiling of the proteome, defined as the entire protein complement of the genome expressed in a particular cell or organ, or in plasma or serum at a particular time, offers the potential for identification of important biomarkers of nutritional state that respond to alterations in diet. The present review considers the published evidence of nutritional modulation of the proteome in vivo which has expanded exponentially over the last 3 years. It highlights some of the challenges faced by researchers using proteomic approaches to understand the interactions of diet with genomic and metabolic–phenotypic variables in normal populations.

The application of physiological observation methods to emotion research

Purpose - The purpose of this paper is to examine consumer emotions and the social science and observation measures that can be utilised to capture the emotional experiences of consumers. The paper is not setting out to solve the theoretical debate surrounding emotion research, rather to provide an assessment of methodological options available to researchers to aid their investigation into both the structure and content of the consumer emotional experience, acknowledging both the conscious and subconscious elements of that experience. Design/methodology/approach - A review of a wide range of prior research from the fields of marketing, consumer behaviour, psychology and neuroscience are examined to identify the different observation methods available to marketing researchers in the study of consumer emotion. This review also considers the self report measures available to researchers and identifies the main theoretical debates concerning emotion to provide a comprehensive overview of the issues surrounding the capture of emotional responses in a marketing context and to highlight the benefits that observation methods offer this area of research. Findings - This paper evaluates three observation methods and four widely used self report measures of emotion used in a marketing context. Whilst it is recognised that marketers have shown preference for the use of self report measures in prior research, mainly due to ease of implementation, it is posited that the benefits of observation methodology and the wealth of data that can be obtained using such methods can compliment prior research. In addition, the use of observation methods cannot only enhance our understanding of the consumer emotion experience but also enable us to collaborate with researchers from other fields in order to make progress in understanding emotion. Originality/value - This paper brings perspectives and methods together to provide an up to date consideration of emotion research for marketers. In order to generate valuable research in this area there is an identified need for discussion and implementation of the observation techniques available to marketing researchers working in this field. An evaluation of a variety of methods is undertaken as a point to start discussion or consideration of different observation techniques and how they can be utilised.

Probing three-way interactions in moderated multiple regression:Development and application of a slope difference test

Researchers often use 3-way interactions in moderated multiple regression analysis to test the joint effect of 3 independent variables on a dependent variable. However, further probing of significant interaction terms varies considerably and is sometimes error prone. The authors developed a significance test for slope differences in 3-way interactions and illustrate its importance for testing psychological hypotheses. Monte Carlo simulations revealed that sample size, magnitude of the slope difference, and data reliability affected test power. Application of the test to published data yielded detection of some slope differences that were undetected by alternative probing techniques and led to changes of results and conclusions. The authors conclude by discussing the test's applicability for psychological research. Copyright 2006 by the American Psychological Association.

Response-based segmentation using Finite Mixture Partial Least Squares: theoretical foundations and an application to American Customer Satisfaction Index Data

When applying multivariate analysis techniques in information systems and social science disciplines, such as management information systems (MIS) and marketing, the assumption that the empirical data originate from a single homogeneous population is often unrealistic. When applying a causal modeling approach, such as partial least squares (PLS) path modeling, segmentation is a key issue in coping with the problem of heterogeneity in estimated cause-and-effect relationships. This chapter presents a new PLS path modeling approach which classifies units on the basis of the heterogeneity of the estimates in the inner model. If unobserved heterogeneity significantly affects the estimated path model relationships on the aggregate data level, the methodology will allow homogenous groups of observations to be created that exhibit distinctive path model estimates. The approach will, thus, provide differentiated analytical outcomes that permit more precise interpretations of each segment formed. An application on a large data set in an example of the American customer satisfaction index (ACSI) substantiates the methodology’s effectiveness in evaluating PLS path modeling results.

Approximate Bayesian techniques for inference in stochastic dynamical systems

This thesis is concerned with approximate inference in dynamical systems, from a variational Bayesian perspective. When modelling real world dynamical systems, stochastic differential equations appear as a natural choice, mainly because of their ability to model the noise of the system by adding a variant of some stochastic process to the deterministic dynamics. Hence, inference in such processes has drawn much attention. Here two new extended frameworks are derived and presented that are based on basis function expansions and local polynomial approximations of a recently proposed variational Bayesian algorithm. It is shown that the new extensions converge to the original variational algorithm and can be used for state estimation (smoothing). However, the main focus is on estimating the (hyper-) parameters of these systems (i.e. drift parameters and diffusion coefficients). The new methods are numerically validated on a range of different systems which vary in dimensionality and non-linearity. These are the Ornstein-Uhlenbeck process, for which the exact likelihood can be computed analytically, the univariate and highly non-linear, stochastic double well and the multivariate chaotic stochastic Lorenz '63 (3-dimensional model). The algorithms are also applied to the 40 dimensional stochastic Lorenz '96 system. In this investigation these new approaches are compared with a variety of other well known methods such as the ensemble Kalman filter / smoother, a hybrid Monte Carlo sampler, the dual unscented Kalman filter (for jointly estimating the systems states and model parameters) and full weak-constraint 4D-Var. Empirical analysis of their asymptotic behaviour as a function of observation density or length of time window increases is provided.

Finding natural groups in data:an application to strategic group research

The best way of finding “natural groups” in management research remains subject to debate and within the literature there is no accepted consensus. The principle motivation behind this study is to explore the effect of choices of method upon strategic group research, an area that has suffered enduring criticism, as we believe that these method choices are still not fully exploited. Our study is novel in the use of a variety of more robust clustering and validation techniques, rarely used in management research, some borrowed from the natural sciences, which may provide a useful and more robust base for this type of research. Our results confirm that methods do exist to address the concerns over strategic group research and adoption of our chosen methods will improve the quality of management research.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.

Shareholder value application in UK listed companies

This paper is based upon the initial findings of a CIMA research project into the way in which corporate performance measurement systems are influenced by the use of shareholder value management techniques. It compares and contrasts the techniques in use in a sample of 10 companies that either explicitly use shareholder value techniques also known as Value-Based Management (VBM), or explicitly do not use such techniques. The analysis undertaken is based upon the finding of semi-structured interviews with company representatives which formed the first part of the data collection process of the project. The analysis traces the interactions between corporate objectives, decision making criteria, performance measurement systems and executive incentive schemes in order to develop an understanding of the effects of such shareholder value techniques upon corporate behaviour. The literature reviewed suggests that the other aspects of the planning and control system should be aligned with the corporate objectives whether a company has adopted VBM or not. Therefore this research contributes new evidence on the use of VBM techniques in the UK and also more generally on whether VBM and non-VBM companies internal planning and control systems are aligned.

Advanced optical techniques for high capacity transmission

This thesis presents several advanced optical techniques that are crucial for improving high capacity transmission systems. The basic theory of optical fibre communications are introduced before optical solitons and their usage in optically amplified fibre systems are discussed. The design, operation, limitations and importance of the recirculating loop are illustrated. The crucial role of dispersion management in the transmission systems is then considered. Two of the most popular dispersion compensation methods - dispersion compensating fibres and fibre Bragg gratings - are emphasised. A tunable dispersion compensator is fabricated using the linear chirped fibre Bragg gratings and a bending rig. Results show that it is capable of compensating not only the second order dispersion, but also higher order dispersion. Stimulated Raman Scattering (SRS) are studied and discussed. Different dispersion maps are performed for all Raman amplified standard fibre link to obtain maximum transmission distances. Raman amplification is used in most of our loop experiments since it improves the optical signal-to-noise ratio (OSNR) and significantly reduces the nonlinear intrachannel effects of the transmission systems. The main body of the experimental work is concerned with nonlinear optical switching using the nonlinear optical loop mirrors (NOLMs). A number of different types of optical loop mirrors are built, tested and implemented in the transmission systems for noise suppression and 2R regeneration. Their results show that for 2R regeneration, NOLM does improve system performance, while NILM degrades system performance due to its sensitivity to the input pulse width, and the NALM built is unstable and therefore affects system performance.

Surface wave techniques for the study of engineering structures and materials

A wire drive pulse echo method of measuring the spectrum of solid bodies described. Using an 's' plane representation, a general analysis of the transient response of such solids has been carried out. This was used for the study of the stepped amplitude transient of high order modes of disks and for the case where there are two adjacent resonant frequencies. The techniques developed have been applied to the measurenent of the elasticities of refractory materials at high temperatures. In the experimental study of the high order in-plane resonances of thin disks it was found that the energy travelled at the edge of the disk and this initiated the work on one dimensional Rayleigh waves.Their properties were established for the straight edge condition by following an analysis similar to that of the two dimensional case. Experiments were then carried out on the velocity dispersion of various circuits including the disk and a hole in a large plate - the negative curvature condition.Theoretical analysis established the phase and group velocities for these cases and experimental tests on aluminium and glass gave good agreement with theory. At high frequencies all velocities approach that of the one dimensional Rayleigh waves. When applied to crack detection it was observed that a signal burst travelling round a disk showed an anomalous amplitude effect. In certain cases the signal which travelled the greater distance had the greater amplitude.An experiment was designed to investigate the phenanenon and it was established that the energy travelled in two nodes with different velocities.It was found by analysis that as well as the Rayleigh surface wave on the edge, a seoond node travelling at about the shear velocity was excited and the calculated results gave reasonable agreement with the experiments.

Signal processing techniques for ultrasonic inspection

This thesis discusses the need for nondestructive testing and highlights some of the limitations in present day techniques. Special interest has been given to ultrasonic examination techniques and the problems encountered when they are applied to thick welded plates. Some suggestions are given using signal processing methods. Chapter 2 treats the need for nondestructive testing as seen in the light of economy and safety. A short review of present day techniques in nondestructive testing is also given. The special problems using ultrasonic techniques for welded structures is discussed in Chapter 3 with some examples of elastic wave propagation in welded steel. The limitations in applying sophisticated signal processing techniques to ultrasonic NDT~ mainly found in the transducers generating or receiving the ultrasound. Chapter 4 deals with the different transducers used. One of the difficulties with ultrasonic testing is the interpretation of the signals encountered. Similar problems might be found with SONAR/RADAR techniques and Chapter 5 draws some analogies between SONAR/RADAR and ultrasonic nondestructive testing. This chapter also includes a discussion on some on the techniques used in signal processing in general. A special signal processing technique found useful is cross-correlation detection and this technique is treated in Chapter 6. Electronic digital compute.rs have made signal processing techniques easier to implement -Chapter 7 discusses the use of digital computers in ultrasonic NDT. Experimental equipment used to test cross-correlation detection of ultrasonic signals is described in Chapter 8. Chapter 9 summarises the conclusions drawn during this investigation.

Development of real-time process control systems using formal techniques

A major application of computers has been to control physical processes in which the computer is embedded within some large physical process and is required to control concurrent physical processes. The main difficulty with these systems is their event-driven characteristics, which complicate their modelling and analysis. Although a number of researchers in the process system community have approached the problems of modelling and analysis of such systems, there is still a lack of standardised software development formalisms for the system (controller) development, particular at early stage of the system design cycle. This research forms part of a larger research programme which is concerned with the development of real-time process-control systems in which software is used to control concurrent physical processes. The general objective of the research in this thesis is to investigate the use of formal techniques in the analysis of such systems at their early stages of development, with a particular bias towards an application to high speed machinery. Specifically, the research aims to generate a standardised software development formalism for real-time process-control systems, particularly for software controller synthesis. In this research, a graphical modelling formalism called Sequential Function Chart (SFC), a variant of Grafcet, is examined. SFC, which is defined in the international standard IEC1131 as a graphical description language, has been used widely in industry and has achieved an acceptable level of maturity and acceptance. A comparative study between SFC and Petri nets is presented in this thesis. To overcome identified inaccuracies in the SFC, a formal definition of the firing rules for SFC is given. To provide a framework in which SFC models can be analysed formally, an extended time-related Petri net model for SFC is proposed and the transformation method is defined. The SFC notation lacks a systematic way of synthesising system models from the real world systems. Thus a standardised approach to the development of real-time process control systems is required such that the system (software) functional requirements can be identified, captured, analysed. A rule-based approach and a method called system behaviour driven method (SBDM) are proposed as a development formalism for real-time process-control systems.