Uncertainty analysis in the Model Web

This thesis provides a set of tools for managing uncertainty in Web-based models and workflows.To support the use of these tools, this thesis firstly provides a framework for exposing models through Web services. An introduction to uncertainty management, Web service interfaces,and workflow standards and technologies is given, with a particular focus on the geospatial domain.An existing specification for exposing geospatial models and processes, theWeb Processing Service (WPS), is critically reviewed. A processing service framework is presented as a solutionto usability issues with the WPS standard. The framework implements support for Simple ObjectAccess Protocol (SOAP), Web Service Description Language (WSDL) and JavaScript Object Notation (JSON), allowing models to be consumed by a variety of tools and software. Strategies for communicating with models from Web service interfaces are discussed, demonstrating the difficultly of exposing existing models on the Web. This thesis then reviews existing mechanisms for uncertainty management, with an emphasis on emulator methods for building efficient statistical surrogate models. A tool is developed to solve accessibility issues with such methods, by providing a Web-based user interface and backend to ease the process of building and integrating emulators. These tools, plus the processing service framework, are applied to a real case study as part of the UncertWeb project. The usability of the framework is proved with the implementation of aWeb-based workflow for predicting future crop yields in the UK, also demonstrating the abilities of the tools for emulator building and integration. Future directions for the development of the tools are discussed.

Living with uncertainty in the age of runtime models

Uncertainty can be defined as the difference between information that is represented in an executing system and the information that is both measurable and available about the system at a certain point in its life-time. A software system can be exposed to multiple sources of uncertainty produced by, for example, ambiguous requirements and unpredictable execution environments. A runtime model is a dynamic knowledge base that abstracts useful information about the system, its operational context and the extent to which the system meets its stakeholders' needs. A software system can successfully operate in multiple dynamic contexts by using runtime models that augment information available at design-time with information monitored at runtime. This chapter explores the role of runtime models as a means to cope with uncertainty. To this end, we introduce a well-suited terminology about models, runtime models and uncertainty and present a state-of-the-art summary on model-based techniques for addressing uncertainty both at development- and runtime. Using a case study about robot systems we discuss how current techniques and the MAPE-K loop can be used together to tackle uncertainty. Furthermore, we propose possible extensions of the MAPE-K loop architecture with runtime models to further handle uncertainty at runtime. The chapter concludes by identifying key challenges, and enabling technologies for using runtime models to address uncertainty, and also identifies closely related research communities that can foster ideas for resolving the challenges raised. © 2014 Springer International Publishing.

1-Tb/s DWDM amplification in a fiber optical parametric amplifier

We report less than 1-dB cross-talk penalty for 26 DWDM channels modulated at 43.7 Gb/s RZ-DPSK when amplified by a fiber optical parametric amplifier showing compatibility with high-capacity (> 1 Tb/s) communication systems. © 2010 Optical Society of America.

Longitudinal parametric oscillation in photorefractive sillenites: comparison between theory and experiment

By using an alternative setup for photorefractive parametric oscillation in which wave mixing between the recording beams is avoided it has become possible to make more detailed comparisons with the space-charge wave theory. In the present paper we compare the experimental features of longitudinal parametric oscillation observed in a crystal of Bi12SiO20 with the theoretical predictions.

1-Tb/s DWDM long-haul transmission employing a fiber optical parametric amplifier

In this letter, we report the performance of a fiber optical parametric amplifier (OPA) when used as a source or intermediate node amplifier in a dense wavelength-division-multiplexed (DWDM) long-haul transmission testbed with 26 DWDM channels modulated at 43.7-Gb/s return-to-zero differential phase-shift keying. In both scenarios, we demonstrate similar performance to an erbium-doped fiber amplifier. This shows the OPAs compatibility with high-capacity (>1 Tb/s) long-haul communication systems.

Fiber optical parametric amplifier in high-speed WDM networks

We report high-capacity (> 1 Tb/s) amplification by a fiber optical parametric amplifier in different roles displaying compatibility and versatility in future WDM networks with phase-shift keying modulation format.

Influence of beam-coupling on photorefractive parametric oscillation in a dc-field-biased Bi12SiO20 crystal

The influence of beam coupling on photorefractive parametric oscillation generated in a Bi12SiO20 crystal is investigated experimentally by comparing two configurations with and without the presence of beam coupling. It is shown that beam coupling has a great influence; for example, the transversal split of the K/2 subharmonic grating is seen only in the beam-coupling geometry. A case that resembles K/4 subharmonic generation can, however, still be found in the absence of beam coupling.

Risk and uncertainty in supply markets and sustainability-related innovation

tentially valuable innovations. In energy policy, much attention is given to analysing and incentivising customer demand, but new technologies also need new supply markets, to provide products and services to build, operate and maintain the innovative technology. This paper addresses the impact of supply constraints on the long-term viability of sustainability related innovations, using the case of energy from waste (EfW). Uncertainties in the pricing and availability of feedstock (i.e. waste) deter potential investors in EfW projects. We draw on prior supply management research to conceptualise the problem, and identify what steps might be taken to address it. Based on this analysis, we propose a research agenda aimed at purchasing and supply scholars and centred on the need to understand better how markets evolve and how stakeholders can (legitimately) influence the evolution of supply markets to support the adoption of sustainability related innovation. Within this broad case, specific themes are recommended for further investigation.

A non-parametric data envelopment analysis approach for improving energy efficiency of grape production

Grape is one of the world's largest fruit crops with approximately 67.5 million tonnes produced each year and energy is an important element in modern grape productions as it heavily depends on fossil and other energy resources. Efficient use of these energies is a necessary step toward reducing environmental hazards, preventing destruction of natural resources and ensuring agricultural sustainability. Hence, identifying excessive use of energy as well as reducing energy resources is the main focus of this paper to optimize energy consumption in grape production.In this study we use a two-stage methodology to find the association of energy efficiency and performance explained by farmers' specific characteristics. In the first stage a non-parametric Data Envelopment Analysis is used to model efficiencies as an explicit function of human labor, machinery, chemicals, FYM (farmyard manure), diesel fuel, electricity and water for irrigation energies. In the second step, farm specific variables such as farmers' age, gender, level of education and agricultural experience are used in a Tobit regression framework to explain how these factors influence efficiency of grape farming.The result of the first stage shows substantial inefficiency between the grape producers in the studied area while the second stage shows that the main difference between efficient and inefficient farmers was in the use of chemicals, diesel fuel and water for irrigation. The use of chemicals such as insecticides, herbicides and fungicides were considerably less than inefficient ones. The results revealed that the more educated farmers are more energy efficient in comparison with their less educated counterparts. © 2013.

Universality in the merging dynamics of parametric active contours:a study in MRI based lung segmentation

Measurement of lung ventilation is one of the most reliable techniques in diagnosing pulmonary diseases. The time-consuming and bias-prone traditional methods using hyperpolarized H 3He and 1H magnetic resonance imageries have recently been improved by an automated technique based on 'multiple active contour evolution'. This method involves a simultaneous evolution of multiple initial conditions, called 'snakes', eventually leading to their 'merging' and is entirely independent of the shapes and sizes of snakes or other parametric details. The objective of this paper is to show, through a theoretical analysis, that the functional dynamics of merging as depicted in the active contour method has a direct analogue in statistical physics and this explains its 'universality'. We show that the multiple active contour method has an universal scaling behaviour akin to that of classical nucleation in two spatial dimensions. We prove our point by comparing the numerically evaluated exponents with an equivalent thermodynamic model. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.

Fuzzy knowledge-based approach to treating uncertainty in inventory control

Inventory control in complex manufacturing environments encounters various sources of uncertainity and imprecision. This paper presents one fuzzy knowledge-based approach to solving the problem of order quantity determination, in the presence of uncertain demand, lead time and actual inventory level. Uncertain data are represented by fuzzy numbers, and vaguely defined relations between them are modeled by fuzzy if-then rules. The proposed representation and inference mechanism are verified using a large numbers of examples. The results of three representative cases are summarized. Finally a comparison between the developed fuzzy knowledge-based and traditional, probabilistic approaches is discussed.

Parametric study of femtosecond inscription of microstructures for OCT artefact fabrication

As optical coherence tomography (OCT) becomes widespread, validation and characterization of systems becomes important. Reference standards are required to qualitatively and quantitatively measure the performance between difference systems. This would allow the performance degradation of the system over time to be monitored. In this report, the properties of the femtosecond inscribed structures from three different systems for making suitable OCT characterization artefacts (phantoms) are analyzed. The parameter test samples are directly inscribed inside transparent materials. The structures are characterized using an optical microscope and a swept-source OCT. The high reproducibility of the inscribed structures shows high potential for producing multi-modality OCT calibration and characterization phantoms. Such that a single artefact can be used to characterize multiple performance parameters such the resolution, linearity, distortion, and imaging depths. © 2012 SPIE.