Elemental estimators for the Generalized Extreme Value tail

In a companion paper (McRobie(2013) arxiv:1304.3918), a simple set of `elemental' estimators was presented for the Generalized Pareto tail parameter. Each elemental estimator: involves only three log-spacings; is absolutely unbiased for all values of the tail parameter; is location- and scale-invariant; and is valid for all sample sizes $N$, even as small as $N= 3$. It was suggested that linear combinations of such elementals could then be used to construct efficient unbiased estimators. In this paper, the analogous mathematical approach is taken to the Generalised Extreme Value (GEV) distribution. The resulting elemental estimators, although not absolutely unbiased, are found to have very small bias, and may thus provide a useful basis for the construction of efficient estimators.

The user-value of rural electrification: An analysis and adoption of existing models and theories

User-value is a determining factor for product acceptance in product design. Research on rural electrification to date, however, does not draw sufficient attention to the importance of user-value with regard to the overall success of a project. This is evident from the analysis of project reports and applicable indicators from agencies active in the sector. Learning from the design, psychology and sociology literatures, it is important that rural electrification projects incorporate the value perception of the end-user and extend their success beyond the commonly used criteria of financial value, the appropriateness of the technology, capacity building and technology uptake. Creating value for the end-user is particularly important for project acceptance and the sustainability of a scheme once it has been handed over to the local community. In this research paper, existing theories and models of value-theory are transposed and applied to community operated rural electrification schemes and a user-value framework is developed. Furthermore, the importance of value to the end-user is clarified. Current literature on product design reveals that user-value has different properties, many of which are applicable to rural electrification. Five value pillars and their sub-categories important for the users of rural electrification projects are identified, namely: functional; social significance; epistemic; emotional; and cultural values. These pillars provide the main structure for the conceptual framework developed in this research paper. It is proposed that by targeting the values of the end-user, the key factors of user-value applicable to rural electrification projects will be identified and the sustainability of the project will be better ensured. © 2014 The Authors.

A comparison of methods for assessing the lifetime reliability of a moored FPSO

Current design codes for floating offshore structures are based on measures of short-term reliability. That is, a design storm is selected via an extreme value analysis of the environmental conditions and the reliability of the vessel in that design storm is computed. Although this approach yields valuable information on the vessel motions, it does not produce a statistically rigorous assessment of the lifetime probability of failure. An alternative approach is to perform a long-term reliability analysis in which consideration is taken of all sea states potentially encountered by the vessel during the design life. Although permitted as a design approach in current design codes, the associated computational expense generally prevents its use in practice. A new efficient approach to long-term reliability analysis is presented here, the results of which are compared with a traditional short-term analysis for the surge motion of a representative moored FPSO in head seas. This serves to illustrate the failure probabilities actually embedded within current design code methods, and the way in which design methods might be adapted to achieve a specified target safety level.

Proceedings of an international workshop on the value of computer-based engineering tools, held in Cambridge in April 1997

There is increasing adoption of computer-based tools to support the product development process. Tolls include computer-aided design, computer-aided manufacture, systems engineering and product data management systems. The fact that companies choose to invest in tools might be regarded as evidence that tools, in aggregate, are perceived to possess business value through their application to engineering activities. Yet the ways in which value accrues from tool technology are poorly understood.

This report records the proceedings of an international workshop during which some novel approaches to improving our understanding of this problem of tool valuation were presented and debated. The value of methods and processes were also discussed. The workshop brought together British, Dutch, German and Italian researchers. The presenters included speakers from industry and academia (the University of Cambridge, the University of Magdeburg and the Politechnico de Torino)

The work presented showed great variety. Research methods include case studies, questionnaires, statistical analysis, semi-structured interviews, deduction, inductive reasoning, the recording of anecdotes and analogies. The presentations drew on financial investment theory, the industrial experience of workshop participants, discussions with students developing tools, modern economic theories and speculation on the effects of company capabilities.

The Bayesian view of extreme events

The Bayesian perspective of designing for the consequences of hazard is discussed. Structural engineers should be educated in Bayesian theory and its underlying philosophy, and about the centrality to the prediction problem of the predictive distribution. The primary contribution that Bayesianism can make to the debate about extreme possibilities is its clarification of the language of and thinking about risk. Frequentist methodologies are the wrong approach to the decisions that engineers need to make, decisions that involve assessments of abstract future possibilities based on incomplete and abstract information.

Managing global network operations along the engineering value chain

Purpose: This paper aims to improve understanding of how to manage global network operations from an engineering perspective. Design/methodology/approach: This research adopted a theory building approach based on case studies. Grounded in the existing literature, the theoretical framework was refined and enriched through nine in-depth case studies in the industry sectors of aerospace, automotives, defence and electrics and electronics. Findings: This paper demonstrates the main value creation mechanisms of global network operations along the engineering value chain. Typical organisational features to support the value creation mechanisms are captured, and the key issues in engineering network design and operations are presented with an overall framework. Practical implications: Evidenced by a series of pilot applications, outputs of this research can help companies to improve the performance of their current engineering networks and design new engineering networks to better support their global businesses and customers in a systematic way. Originality/value: Issues about the design and operations of global engineering networks (GEN) are poorly understood in the existing literature in contrast to their apparent importance in value creation and realisation. To address this knowledge gap, this paper introduces the concept of engineering value chain to highlight the potential of a value chain approach to the exploration of engineering activities in a complex business context. At the same time, it develops an overall framework for managing GEN along the engineering value chain. This improves our understanding of engineering in industrial value chains and extends the theoretical understanding of GEN through integrating the engineering network theories and the value chain concepts. © Emerald Group Publishing Limited.

Re-conceptualising value in the engineering design process: The value cycle map

Introducing a "Cheaper, Faster, Better" product in today's highly competitive market is a challenging target. Therefore, for organizations to improve their performance in this area, they need to adopt methods such as process modelling, risk mitigation and lean principles. Recently, several industries and researchers focused efforts on transferring the value orientation concept to other phases of the Product Life Cycle (PLC) such as Product Development (PD), after its evident success in manufacturing. In PD, value maximization, which is the main objective of lean theory, has been of particular interest as an improvement concept that can enhance process flow logistics and support decision-making. This paper presents an ongoing study of the current understanding of value thinking in PD (VPD) with a focus on value dimensions and implementation benefits. The purpose of this study is to consider the current state of knowledge regarding value thinking in PD, and to propose a definition of value and a framework for analyzing value delivery. The framework-named the Value Cycle Map (VCM)- intends to facilitate understanding of value and its delivery mechanism in the context of the PLC. We suggest the VCM could be used as a foundation for future research in value modelling and measurement in PD.

A Stochastic Model for Electron Multiplication Charge-Coupled Devices - From Theory to Practice

Electron multiplication charge-coupled devices (EMCCD) are widely used for photon counting experiments and measurements of low intensity light sources, and are extensively employed in biological fluorescence imaging applications. These devices have a complex statistical behaviour that is often not fully considered in the analysis of EMCCD data. Robust and optimal analysis of EMCCD images requires an understanding of their noise properties, in particular to exploit fully the advantages of Bayesian and maximum-likelihood analysis techniques, whose value is increasingly recognised in biological imaging for obtaining robust quantitative measurements from challenging data. To improve our own EMCCD analysis and as an effort to aid that of the wider bioimaging community, we present, explain and discuss a detailed physical model for EMCCD noise properties, giving a likelihood function for image counts in each pixel for a given incident intensity, and we explain how to measure the parameters for this model from various calibration images. © 2013 Hirsch et al.

Independence is elusive: set size effects on encoding precision in visual search.

Looking for a target in a visual scene becomes more difficult as the number of stimuli increases. In a signal detection theory view, this is due to the cumulative effect of noise in the encoding of the distractors, and potentially on top of that, to an increase of the noise (i.e., a decrease of precision) per stimulus with set size, reflecting divided attention. It has long been argued that human visual search behavior can be accounted for by the first factor alone. While such an account seems to be adequate for search tasks in which all distractors have the same, known feature value (i.e., are maximally predictable), we recently found a clear effect of set size on encoding precision when distractors are drawn from a uniform distribution (i.e., when they are maximally unpredictable). Here we interpolate between these two extreme cases to examine which of both conclusions holds more generally as distractor statistics are varied. In one experiment, we vary the level of distractor heterogeneity; in another we dissociate distractor homogeneity from predictability. In all conditions in both experiments, we found a strong decrease of precision with increasing set size, suggesting that precision being independent of set size is the exception rather than the rule.

The price of pain and the value of suffering.

Estimating the financial value of pain informs issues as diverse as the market price of analgesics, the cost-effectiveness of clinical treatments, compensation for injury, and the response to public hazards. Such valuations are assumed to reflect a stable trade-off between relief of discomfort and money. Here, using an auction-based health-market experiment, we show that the price people pay for relief of pain is strongly determined by the local context of the market, that is, by recent intensities of pain or immediately disposable income (but not overall wealth). The absence of a stable valuation metric suggests that the dynamic behavior of health markets is not predictable from the static behavior of individuals. We conclude that the results follow the dynamics of habit-formation models of economic theory, and thus, this study provides the first scientific basis for this type of preference modeling.

Probability-Matching Predictors for Extreme Extremes

A location- and scale-invariant predictor is constructed which exhibits good probability matching for extreme predictions outside the span of data drawn from a variety of (stationary) general distributions. It is constructed via the three-parameter {\mu, \sigma, \xi} Generalized Pareto Distribution (GPD). The predictor is designed to provide matching probability exactly for the GPD in both the extreme heavy-tailed limit and the extreme bounded-tail limit, whilst giving a good approximation to probability matching at all intermediate values of the tail parameter \xi. The predictor is valid even for small sample sizes N, even as small as N = 3. The main purpose of this paper is to present the somewhat lengthy derivations which draw heavily on the theory of hypergeometric functions, particularly the Lauricella functions. Whilst the construction is inspired by the Bayesian approach to the prediction problem, it considers the case of vague prior information about both parameters and model, and all derivations are undertaken using sampling theory.

Theory of high-power mode-locked lasers with a slow absorber

We develop an analytical theory of high-power passively mode-locked lasers with a slow absorber; the theory is valid at pulse energies well exceeding the saturation energy. We analyze the Haus modelocking master equation in the pulse-energy-domain representation, approximating the intensity profile function by a series in the vicinity of its peak value. We consider the high-power operation regime of subpicosecond blue-violet GaN mode-locked diode lasers, using the approach developed. © 2010 Springer Science+Business Media, Inc.

Finite Element studies on indentation size effect using a higher order strain gradient theory

In this work, a Finite Element implementation of a higher order strain gradient theory (due to Fleck and Hutchinson, 2001) has been used within the framework of large deformation elasto-viscoplasticity to study the indentation of metals with indenters of various geometries. Of particular interest is the indentation size effect (ISE) commonly observed in experiments where the hardness of a range of materials is found to be significantly higher at small depths of indentation but reduce to a lower, constant value at larger depths. That the ISE can be explained by strain gradient plasticity is well known but this work aims to qualitatively compare a gamut of experimental observations on this effect with predictions from a higher order strain gradient theory. Results indicate that many of the experimental observations are qualitatively borne out by our simulations. However, areas exist where conflicting experimental results make assessment of numerical predictions difficult. © 2012 Elsevier Ltd. All rights reserved.