The accuracy of parameter estimation from noisy data, with application to resonance peak estimation in distributed Brillouin sensing

Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

An investigation into inductive parameter learning in complex hierarchical knowledge structures representing clinical expertise

This dissertation investigates the very important and current problem of modelling human expertise. This is an apparent issue in any computer system emulating human decision making. It is prominent in Clinical Decision Support Systems (CDSS) due to the complexity of the induction process and the vast number of parameters in most cases. Other issues such as human error and missing or incomplete data present further challenges. In this thesis, the Galatean Risk Screening Tool (GRiST) is used as an example of modelling clinical expertise and parameter elicitation. The tool is a mental health clinical record management system with a top layer of decision support capabilities. It is currently being deployed by several NHS mental health trusts across the UK. The aim of the research is to investigate the problem of parameter elicitation by inducing them from real clinical data rather than from the human experts who provided the decision model. The induced parameters provide an insight into both the data relationships and how experts make decisions themselves. The outcomes help further understand human decision making and, in particular, help GRiST provide more accurate emulations of risk judgements. Although the algorithms and methods presented in this dissertation are applied to GRiST, they can be adopted for other human knowledge engineering domains.

The accuracy of parameter estimation from noisy data, with application to resonance peak estimation in distributed Brillouin sensing

Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

Investigating the process of translation:humour translation norms, strategies and approaches in children's literature

Research in the present thesis is focused on the norms, strategies,and approaches which translators employ when translating humour in Children's Literature from English into Greek. It is based on process-oriented descriptive translation studies, since the focus is on investigating the process of translation. Viewing translation as a cognitive process and a problem soling activity, this thesis Think-aloud protocols (TAPs) in order to investigate translator's minds. As it is not possible to directly observe the human mind at work, an attempt is made to ask the translators themselves to reveal their mental processes in real time by verbalising their thoughts while carrying out a translation task involving humour. In this study, thirty participants at three different levels of expertise in translation competence, i.e. tn beginner, ten competent, and ten experts translators, were requested to translate two humourous extracts from the fictional diary novel The Secret Diary of Adrian Mole, Aged 13 ¾ by Sue Townsend (1982) from English into Greek. As they translated, they were asked to verbalise their thoughts and reason them, whenever possible, so that their strategies and approaches could be detected, and that subsequently, the norms that govern these strategies and approaches could be revealed. The thesis consists of four parts: the introduction, the literature review, the study, and the conclusion, and is developed in eleven chapters. the introduction contextualises the study within translation studies (TS) and presents its rationale, research questions, aims, and significance. Chapters 1 to 7 present an extensive and inclusive literature review identifying the principles axioms that guide and inform the study. In these seven chapters the following areas are critically introduced: Children's literature (Chapter 1), Children's Literature Translation (Chapter 2), Norms in Children's Literature (Chapter 3), Strategies in Children's Literature (Chapter 4), Humour in Children's Literature Translation (Chapter 5), Development of Translation Competence (Chapter 6), and Translation Process Research (Chapter 7). In Chapters 8 - 11 the fieldwork is described in detail. the piolot and the man study are described with a reference to he environments and setting, the participants, the research -observer, the data and its analysis, and limitations of the study. The findings of the study are presented and analysed in Chapter 9. Three models are then suggested for systematising translators' norms, strategies, and approaches, thus, filling the existing gap in the field. Pedagogical norms (e.g. appropriateness/correctness, famililarity, simplicity, comprehensibility, and toning down), literary norms (e.g. sound of language and fluency). and source-text norms (e.g. equivalence) were revealed to b the most prominent general and specific norms governing the translators'  strategies and approaches in the process of translating humour in ChL. The data also revealed that monitoring and communication strategies (e.g. additions, omissions, and exoticism) were the prevalent strategies employed by translators. In Chapter 10 the main findings and outcomes of a potential secondary benefit (beneficial outcomes) are discussed on the basis of the research questions and aims of the study, and implications of the study are tackled in Chapter 11. In the conclusion, suggestions for future directions are given and final remarks noted.

A strategy formulation process for the delivery of technology enabled service delivery systems

The Product Service Systems, servitization, and Service Science literature continues to grow as organisations seek to protect and improve their competitive position. The potential of technology applications to deliver service delivery systems facilitated by the ability to make real time decisions based upon ‘in the field’ performance is also significant. Research identifies four key questions to be addressed. Namely: how far along the servitization continuum should the organisation go in a single strategic step? Does the organisation have the structure and infrastructure to support this transition? What level of condition monitoring should it employ? Is the product positioned correctly in the value chain to adopt condition monitoring technology? Strategy consists of three dimensions, namely content, context, and process. The literature relating to PSS, servitization, and strategy all discuss the concepts relative to content and context but none offer a process to deliver an aligned strategy to deliver a service delivery system enabled by condition based management. This paper presents a tested iterative strategy formulation methodology which is the result of a structured development programme.

Analytic hierarchy process analyses risk of operating cross-country petroleum pipelines in India

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction methodology, and logical insurance plans. The risk-based model uses the analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to identify the factors that influence failure on specific segments and to analyze their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

High stress monitoring of prestressing tendons in nuclear concrete vessels using fibre-optic sensors

Maintaining the structural health of prestressed concrete nuclear containments is a key element in ensuring nuclear reactors are capable of meeting their safety requirements. This paper discusses the attachment, fabrication and characterisation of optical fibre strain sensors suitable for the prestress monitoring of irradiated steel prestressing tendons. The all-metal fabrication and welding process allowed the instrumented strand to simultaneously monitor and apply stresses up to 1300 MPa (80% of steel's ultimate tensile strength). There were no adverse effects to the strand's mechanical properties or integrity. After sensor relaxation through cyclic stress treatment, strain transfer between the optical fibre sensors and the strand remained at 69%. The fibre strain sensors could also withstand the non-axial forces induced as the strand was deflected around a 4.5 m bend radius. Further development of this technology has the potential to augment current prestress monitoring practices, allowing distributed measurements of short- and long-term prestress losses in nuclear prestressed-concrete vessels. © 2014 Elsevier B.V.

Heterogeneous catalysts for clean technology:spectroscopy, design, and monitoring

Reactive, but not a reactant. Heterogeneous catalysts play an unseen role in many of today's processes and products. With the increasing emphasis on sustainability in both products and processes, this handbook is the first to combine the hot topics of heterogeneous catalysis and clean technology. It focuses on the development of heterogeneous catalysts for use in clean chemical synthesis, dealing with how modern spectroscopic techniques can aid the design of catalysts for use in liquid phase reactions, their application in industrially important chemistries - including selective oxidation, hydrogenation, solid acid- and base-catalyzed processes - as well as the role of process intensification and use of renewable resources in improving the sustainability of chemical processes. With its emphasis on applications, this book is of high interest to those working in the industry.

Parametric Identification and Diagnosis of Integrated Navigation Systems in Bench Test Process

Growth of complexity and functional importance of integrated navigation systems (INS) leads to high losses at the equipment refusals. The paper is devoted to the INS diagnosis system development, allowing identifying the cause of malfunction. The proposed solutions permit taking into account any changes in sensors dynamic and accuracy characteristics by means of the appropriate error models coefficients. Under actual conditions of INS operation, the determination of current values of the sensor models and estimation filter parameters rely on identification procedures. The results of full-scale experiments are given, which corroborate the expediency of INS error models parametric identification in bench test process.

Study of Queuing Systems with a Generalized Departure Process

This work was supported by the Bulgarian National Science Fund under grant BY-TH-105/2005.

Telehealth Approach for Glaucoma Progression Monitoring

This paper presents a Web-Centric [3] extension to a previously developed glaucoma expert system that will provide access for doctors and patients from any part of the world. Once implemented, this telehealth solution will publish the services of the Glaucoma Expert System on the World Wide Web, allowing patients and doctors to interact with it from their own homes. This web-extension will also allow the expert system itself to be proactive and to send diagnosis alerts to the registered user or doctor and the patient, informing each one of any emergencies, therefore allowing them to take immediate actions. The existing Glaucoma Expert System uses fuzzy logic learning algorithms applied on historical patient data to update and improve its diagnosis rules set. This process, collectively called the learning process, would benefit greatly from a web-based framework that could provide services like patient data transfer and web- based distribution of updated rules [1].

Intelligent Computations for Flood Monitoring

Floods represent the most devastating natural hazards in the world, affecting more people and causing more property damage than any other natural phenomena. One of the important problems associated with flood monitoring is flood extent extraction from satellite imagery, since it is impractical to acquire the flood area through field observations. This paper presents a method to flood extent extraction from synthetic-aperture radar (SAR) images that is based on intelligent computations. In particular, we apply artificial neural networks, self-organizing Kohonen’s maps (SOMs), for SAR image segmentation and classification. We tested our approach to process data from three different satellite sensors: ERS-2/SAR (during flooding on Tisza river, Ukraine and Hungary, 2001), ENVISAT/ASAR WSM (Wide Swath Mode) and RADARSAT-1 (during flooding on Huaihe river, China, 2007). Obtained results showed the efficiency of our approach.

Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms

Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.

Strong Consistency of the Conditional Least Squares Estimator for a Nonstationary Process. Example of the Garch Model

2000 Mathematics Subject Classification: Primary: 62M10, 62J02, 62F12, 62M05, 62P05, 62P10; secondary: 60G46, 60F15.

Crump-Mode-Jagers Branching Process: Modelling and Application for Human Population

2010 Mathematics Subject Classification: 60J85, 92D25.