Drought policy: a graphical analysis

The standard approach to modelling production under uncertainty has relied on the concept of the stochastic production function. In the present paper, it is argued that a state-contingent production model is more flexible and realistic. The model is applied to the problem of drought policy.

Complexity, conflict and uncertainty: Issues in collaboration between child protection and mental health services

This paper provides an analysis of data from a state-wide survey of statutory child protection workers, adult mental health workers, and child mental health workers. Respondents provided details of their experience of collaboration on cases where a parent had mental health problems and there were serious child protection concerns. The survey was conducted as part of a large mixed-method research project on developing best practice at the intersection of child protection and mental health services. Descriptions of 300 cases were provided by 122 respondents. Analyses revealed that a great deal of collaboration occur-red across a wide range of government and community-based agencies; that collaborative processes were often positive and rewarding for workers; and that collaboration was most difficult when the nature of the parental mental illness or the need for child protection intervention was contested. The difficulties experienced included communication, role clarity, competing primary focus, contested parental mental health needs, contested child protection needs, and resources. (C) 2004 Elsevier Ltd. All rights reserved.

A cost-effectiveness analysis of two rehabilitation support services for women with breast cancer

The purpose of this research was to estimate the cost-effectiveness of two rehabilitation interventions for breast cancer survivors, each compared to a population-based, non-intervention group (n = 208). The two services included an early home-based physiotherapy intervention (DAART, n = 36) and a group-based exercise and psychosocial intervention (STRETCH, n = 31). A societal perspective was taken and costs were included as those incurred by the health care system, the survivors and community. Health outcomes included: (a) 'rehabilitated cases' based on changes in health-related quality of life between 6 and 12 months post-diagnosis, using the Functional Assessment of Cancer Therapy - Breast Cancer plus Arm Morbidity (FACT-B+4) questionnaire, and (b) quality-adjusted life years (QALYs) using utility scores from the Subjective Health Estimation (SHE) scale. Data were collected using self-reported questionnaires, medical records and program budgets. A Monte-Carlo modelling approach was used to test for uncertainty in cost and outcome estimates. The proportion of rehabilitated cases was similar across the three groups. From a societal perspective compared with the non-intervention group, the DAART intervention appeared to be the most efficient option with an incremental cost of $1344 per QALY gained, whereas the incremental cost per QALY gained from the STRETCH program was $14,478. Both DAART and STRETCH are low-cost, low-technological health promoting programs representing excellent public health investments.

Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data

Background Our aim was to calculate the global burden of disease and risk factors for 2001, to examine regional trends from 1990 to 2001, and to provide a starting point for the analysis of the Disease Control Priorities Project (DCPP). Methods We calculated mortality, incidence, prevalence, and disability adjusted life years (DALYs) for 136 diseases and injuries, for seven income/geographic country groups. To assess trends, we re-estimated all-cause mortality for 1990 with the same methods as for 2001. We estimated mortality and disease burden attributable to 19 risk factors. Findings About 56 million people died in 2001. Of these, 10.6 million were children, 99% of whom lived in low-and-middle-income countries. More than half of child deaths in 2001 were attributable to acute respiratory infections, measles, diarrhoea, malaria, and HIV/AIDS. The ten leading diseases for global disease burden were perinatal conditions, lower respiratory infections, ischaemic heart disease, cerebrovascular disease, HIV/AIDS, diarrhoeal diseases, unipolar major depression, malaria, chronic obstructive pulmonary disease, and tuberculosis. There was a 20% reduction in global disease burden per head due to communicable, maternal, perinatal, and nutritional conditions between 1990 and 2001. Almost half the disease burden in low-and-middle-income countries is now from non-communicable diseases (disease burden per head in Sub-Saharan Africa and the low-and-middle-income countries of Europe and Central Asia increased between 1990 and 2001). Undernutrition remains the leading risk factor for health loss. An estimated 45% of global mortality and 36% of global disease burden are attributable to the joint hazardous effects of the 19 risk factors studied. Uncertainty in all-cause mortality estimates ranged from around 1% in high-income countries to 15-20% in Sub-Saharan Africa. Uncertainty was larger for mortality from specific diseases, and for incidence and prevalence of non-fatal outcomes. Interpretation Despite uncertainties about mortality and burden of disease estimates, our findings suggest that substantial gains in health have been achieved in most populations, countered by the HIV/AIDS epidemic in Sub-Saharan Africa and setbacks in adult mortality in countries of the former Soviet Union. our results on major disease, injury, and risk factor causes of loss of health, together with information on the cost-effectiveness of interventions, can assist in accelerating progress towards better health and reducing the persistent differentials in health between poor and rich countries.

'Seeing the market': Technical analysis in trading styles

Whilst financial markets are not strangers to academic and professional scrutiny, they still remain epistemologically contested. For individuals trying to profit by trading shares, this uncertainty is manifested in the varying trading styles which they are able to utilize. This paper examines one trading style commonly used by non-professional share traders-technical analysis. Using research data obtained from individuals who identify themselves as technical analysts, this paper seeks to explain the ways in which individuals understand and use the technique in an attempt to make trading profits. In particular, four distinct subcategories or ideal types of technical analysis can be identified, each providing an alternative perceptual form for participating in financial markets. Each of these types relies upon a particular method for seeing the market, these visualization techniques highlighting the existence of forms of professional vision (as originally identified by Goodwin (1994)) in the way the trading styles are comprehended and acted upon.

Anisotropy-based robust performance analysis of finite horizon linear discrete time varying systems

We consider a problem of robust performance analysis of linear discrete time varying systems on a bounded time interval. The system is represented in the state-space form. It is driven by a random input disturbance with imprecisely known probability distribution; this distributional uncertainty is described in terms of entropy. The worst-case performance of the system is quantified by its a-anisotropic norm. Computing the anisotropic norm is reduced to solving a set of difference Riccati and Lyapunov equations and a special form equation.

Introducing uncertainty into pattern discovery in temporal event sequences

Pattern discovery in temporal event sequences is of great importance in many application domains, such as telecommunication network fault analysis. In reality, not every type of event has an accurate timestamp. Some of them, defined as inaccurate events may only have an interval as possible time of occurrence. The existence of inaccurate events may cause uncertainty in event ordering. The traditional support model cannot deal with this uncertainty, which would cause some interesting patterns to be missing. A new concept, precise support, is introduced to evaluate the probability of a pattern contained in a sequence. Based on this new metric, we define the uncertainty model and present an algorithm to discover interesting patterns in the sequence database that has one type of inaccurate event. In our model, the number of types of inaccurate events can be extended to k readily, however, at a cost of increasing computational complexity.

A robustness framework for monitoring real options under uncertainty

This paper presents a problem structuring methodology to assess real option decisions in the face of unpredictability. Based on principles of robustness analysis and scenario planning, we demonstrate how decision-aiding can facilitate participation in projects setting and achieve effective decision making through the use of real options reasoning. We argue that robustness heuristics developed in earlier studies can be practical proxies for real options performance, hence indicators of efficient flexible planning. The developed framework also highlights how to integrate real options solutions in firms’ strategic plans and operating actions. The use of the methodology in a location decision application is provided for illustration.

Exchanging uncertainty: interoperable geostatistics?

Traditionally, geostatistical algorithms are contained within specialist GIS and spatial statistics software. Such packages are often expensive, with relatively complex user interfaces and steep learning curves, and cannot be easily integrated into more complex process chains. In contrast, Service Oriented Architectures (SOAs) promote interoperability and loose coupling within distributed systems, typically using XML (eXtensible Markup Language) and Web services. Web services provide a mechanism for a user to discover and consume a particular process, often as part of a larger process chain, with minimal knowledge of how it works. Wrapping current geostatistical algorithms with a Web service layer would thus increase their accessibility, but raises several complex issues. This paper discusses a solution to providing interoperable, automatic geostatistical processing through the use of Web services, developed in the INTAMAP project (INTeroperability and Automated MAPping). The project builds upon Open Geospatial Consortium standards for describing observations, typically used within sensor webs, and employs Geography Markup Language (GML) to describe the spatial aspect of the problem domain. Thus the interpolation service is extremely flexible, being able to support a range of observation types, and can cope with issues such as change of support and differing error characteristics of sensors (by utilising descriptions of the observation process provided by SensorML). XML is accepted as the de facto standard for describing Web services, due to its expressive capabilities which allow automatic discovery and consumption by ‘naive’ users. Any XML schema employed must therefore be capable of describing every aspect of a service and its processes. However, no schema currently exists that can define the complex uncertainties and modelling choices that are often present within geostatistical analysis. We show a solution to this problem, developing a family of XML schemata to enable the description of a full range of uncertainty types. These types will range from simple statistics, such as the kriging mean and variances, through to a range of probability distributions and non-parametric models, such as realisations from a conditional simulation. By employing these schemata within a Web Processing Service (WPS) we show a prototype moving towards a truly interoperable geostatistical software architecture.

Is it all tough talking at the top? A post-structuralist analysis of the construction of gendered speaker identities of British business leaders within interview narratives

This paper uses a feminist post-structuralist approach to examine the gendered identities of a sample of British business leaders in Britain. While recent national surveys offer many material reasons why women are acutely under-represented as business leaders, the role of language is rarely addressed. This paper explores the ways in which ten senior women and men construct their sense of leadership identities through the medium of interview narratives. Drawing upon two poststructuralist models of analysis (Derrida’s 1987 theory of deconstruction and Bakhtin’s 1927/1981 concept of double-voiced discourse), the paper shows how both females and males are able to shift pragmatically between interwoven corporate discourses, which demand competing cultural allegiances from one moment to the next, allegiances constantly tested by the rapid change and uncertainty that characterise global business. While male leaders experience a relative freedom of movement between different cultural discourses, female leaders are circumscribed by negative and reductive representations of female speech and behaviour. In sum, senior women are required constantly to observe, review, police and repair their use of leadership language, which potentially undermines their confidence and authority as leaders.

Calculating the balance between water resources and water demands:an approach using risk analysis

Predicting future need for water resources has traditionally been, at best, a crude mixture of art and science. This has prevented the evaluation of water need from being carried out in either a consistent or comprehensive manner. This inconsistent and somewhat arbitrary approach to water resources planning led to well publicised premature developments in the 1970's and 1980's but privatisation of the Water Industry, including creation of the Office of Water Services and the National Rivers Authority in 1989, turned the tide of resource planning to the point where funding of schemes and their justification by the Regulators could no longer be assumed. Furthermore, considerable areas of uncertainty were beginning to enter the debate and complicate the assessment It was also no longer appropriate to consider that contingencies would continue to lie solely on the demand side of the equation. An inability to calculate the balance between supply and demand may mean an inability to meet standards of service or, arguably worse, an excessive provision of water resources and excessive costs to customers. United Kingdom Water Industry Research limited (UKWlR) Headroom project in 1998 provided a simple methodology for the calculation of planning margins. This methodology, although well received, was not, however, accepted by the Regulators as a tool sufficient to promote resource development. This thesis begins by considering the history of water resource planning in the UK, moving on to discuss events following privatisation of the water industry post·1985. The mid section of the research forms the bulk of original work and provides a scoping exercise which reveals a catalogue of uncertainties prevalent within the supply-demand balance. Each of these uncertainties is considered in terms of materiality, scope, and whether it can be quantified within a risk analysis package. Many of the areas of uncertainty identified would merit further research. A workable, yet robust, methodology for evaluating the balance between water resources and water demands by using a spreadsheet based risk analysis package is presented. The technique involves statistical sampling and simulation such that samples are taken from input distributions on both the supply and demand side of the equation and the imbalance between supply and demand is calculated in the form of an output distribution. The percentiles of the output distribution represent different standards of service to the customer. The model allows dependencies between distributions to be considered, for improved uncertainties to be assessed and for the impact of uncertain solutions to any imbalance to be calculated directly. The method is considered a Significant leap forward in the field of water resource planning.

Exploratory data analysis with non-linear and missing data in geochemistry

Exploratory analysis of data seeks to find common patterns to gain insights into the structure and distribution of the data. In geochemistry it is a valuable means to gain insights into the complicated processes making up a petroleum system. Typically linear visualisation methods like principal components analysis, linked plots, or brushing are used. These methods can not directly be employed when dealing with missing data and they struggle to capture global non-linear structures in the data, however they can do so locally. This thesis discusses a complementary approach based on a non-linear probabilistic model. The generative topographic mapping (GTM) enables the visualisation of the effects of very many variables on a single plot, which is able to incorporate more structure than a two dimensional principal components plot. The model can deal with uncertainty, missing data and allows for the exploration of the non-linear structure in the data. In this thesis a novel approach to initialise the GTM with arbitrary projections is developed. This makes it possible to combine GTM with algorithms like Isomap and fit complex non-linear structure like the Swiss-roll. Another novel extension is the incorporation of prior knowledge about the structure of the covariance matrix. This extension greatly enhances the modelling capabilities of the algorithm resulting in better fit to the data and better imputation capabilities for missing data. Additionally an extensive benchmark study of the missing data imputation capabilities of GTM is performed. Further a novel approach, based on missing data, will be introduced to benchmark the fit of probabilistic visualisation algorithms on unlabelled data. Finally the work is complemented by evaluating the algorithms on real-life datasets from geochemical projects.

Managing uncertainty in integrated environmental modelling:the UncertWeb framework

Web-based distributed modelling architectures are gaining increasing recognition as potentially useful tools to build holistic environmental models, combining individual components in complex workflows. However, existing web-based modelling frameworks currently offer no support for managing uncertainty. On the other hand, the rich array of modelling frameworks and simulation tools which support uncertainty propagation in complex and chained models typically lack the benefits of web based solutions such as ready publication, discoverability and easy access. In this article we describe the developments within the UncertWeb project which are designed to provide uncertainty support in the context of the proposed ‘Model Web’. We give an overview of uncertainty in modelling, review uncertainty management in existing modelling frameworks and consider the semantic and interoperability issues raised by integrated modelling. We describe the scope and architecture required to support uncertainty management as developed in UncertWeb. This includes tools which support elicitation, aggregation/disaggregation, visualisation and uncertainty/sensitivity analysis. We conclude by highlighting areas that require further research and development in UncertWeb, such as model calibration and inference within complex environmental models.

Effects of pharmaceutical marketing:a re-analysis of the study of Windmeijer et al

Despite a growing body of scientific research, there is still much uncertainty about the effects of marketing expenditures on the demand for pharmaceuticals. Recently it was found that higher marketing expenditures for a brand may reduce the price elasticity of demand, and hence allow firms to charge higher prices (Windmeijer et al [1]). In this study we reconsider the study by Windmeijer et al. We find that their econometric models are based on an incorrect assumption of homogeneous parameters across brands. As a consequence, our conclusions concerning the effects of pharmaceutical marketing are different from theirs.

RELAX:a language to address uncertainty in self-adaptive systems requirement

Self-adaptive systems have the capability to autonomously modify their behavior at run-time in response to changes in their environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, and environmental monitoring systems. While a few techniques have been developed to support the monitoring and analysis of requirements for adaptive systems, limited attention has been paid to the actual creation and specification of requirements of self-adaptive systems. As a result, self-adaptivity is often constructed in an ad-hoc manner. In order to support the rigorous specification of adaptive systems requirements, this paper introduces RELAX, a new requirements language for self-adaptive systems that explicitly addresses uncertainty inherent in adaptive systems. We present the formal semantics for RELAX in terms of fuzzy logic, thus enabling a rigorous treatment of requirements that include uncertainty. RELAX enables developers to identify uncertainty in the requirements, thereby facilitating the design of systems that are, by definition, more flexible and amenable to adaptation in a systematic fashion. We illustrate the use of RELAX on smart home applications, including an adaptive assisted living system.