Robust automatic mapping algorithms in a network monitoring scenario

Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.

The macular mapping test:a reliability study

Background: Age-related macular degeneration (ARMD) is the leading cause of visual disability in people over 60 years of age in the developed world. The success of treatment deteriorates with increased latency of diagnosis. The purpose of this study was to determine the reliability of the macular mapping test (MMT), and to investigate its potential as a screening tool. Methods: The study population comprised of 31 healthy eyes of 31 participants. To assess reliability, four macular mapping test (MMT) measurements were taken in two sessions separated by one hour by two practitioners, with reversal of order in the second session. MMT readings were also taken from 17 age-related maculopathy (ARM), and 12 AMD affected eyes. Results: For the normal cohort, average MMT scores ranged from 85.5 to 100.0 MMT points. Scores ranged from 79.0 to 99.0 for the ARM group and from 9.0 to 92.0 for the AMD group. MMT scores were reliable to within ± 7.0 points. The difference between AMD affected eyes and controls (z = 3.761, p = < 0.001) was significant. The difference between ARM affected eyes and controls was not significant (z = -0.216, p = 0.829). Conclusion: The reliability data shows that a change of 14 points or more is required to indicate a clinically significant change. This value is required for use of the MMT as an outcome measure in clinical trials. Although there was no difference between MMT scores from ARM affected eyes and controls, the MMT has the advantage over the Amsler grid in that it uses a letter target, has a peripheral fixation aid, and it provides a numerical score. This score could be beneficial in office and home monitoring of AMD progression, as well as an outcome measure in clinical research. © 2005 Bartlett et al; licensee BioMed Central Ltd.

Mapping the mind for the modern market researcher

Purpose - To describe the utility of three of the main cognitive neuroscientific techniques currently in use within the neuroscience community, and how they can be applied to the emerging field of neuromarket research. Design/methodology/approach - A brief development of functional magnetic resonance imaging, magnetoencephalography and transcranial magnetic stimulation are described, as the core principles are behind their respective use. Examples of actual data from each of the brain imaging techniques are provided to assist the neuromarketer with subsequent data for interpretation. Finally, to ensure the neuromarketer has an understanding of the experience of neuroimaging, qualitative data from a questionnaire exploring attitudes about neuroimaging techniques are included which summarize participants' experiences of having a brain scan. Findings - Cognitive neuroscientific techniques have great utility in market research and can provide more "honest" indicators of consumer preference where traditional methods such as focus groups can be unreliable. These techniques come with complementary strengths which allow the market researcher to converge onto a specific research question. In general, participants considered brain imaging techniques to be relatively safe. However, care is urged to ensure that participants are positioned correctly in the scanner as incorrect positioning is a stressful factor during an imaging procedure that can impact data quality. Originality/value - This paper is an important and comprehensive resource to the market researcher who wishes to use cognitive neuroscientific techniques.

The Aston Medication Adherence Study:mapping the adherence patterns of an inner-city population

Background: The Aston Medication Adherence Study was designed to examine non-adherence to prescribed medicines within an inner-city population using general practice (GP) prescribing data. Objective: To examine non-adherence patterns to prescribed oralmedications within three chronic disease states and to compare differences in adherence levels between various patient groups to assist the routine identification of low adherence amongst patients within the Heart of Birmingham teaching Primary Care Trust (HoBtPCT). Setting: Patients within the area covered by HoBtPCT (England) prescribed medication for dyslipidaemia, type-2 diabetes and hypothyroidism, between 2000 and 2010 inclusively. HoBtPCT's population was disproportionately young,with seventy per cent of residents fromBlack and Minority Ethnic groups. Method: Systematic computational analysis of all medication issue data from 76 GP surgeries dichotomised patients into two groups (adherent and non-adherent) for each pharmacotherapeutic agent within the treatment groups. Dichotomised groupings were further analysed by recorded patient demographics to identify predictors of lower adherence levels. Results were compared to an analysis of a self-reportmeasure of adherence [using the Modified Morisky Scale© (MMAS-8)] and clinical value data (cholesterol values) from GP surgery records. Main outcome: Adherence levels for different patient demographics, for patients within specific longterm treatment groups. Results: Analysis within all three groups showed that for patients with the following characteristics, adherence levels were statistically lower than for others; patients: younger than 60 years of age; whose religion is coded as "Islam"; whose ethnicity is coded as one of the Asian groupings or as "Caribbean", "Other Black" and "African"; whose primary language is coded as "Urdu" or "Bengali"; and whose postcodes indicate that they live within the most socioeconomically deprived areas of HoBtPCT. Statistically significant correlations between adherence status and results from the selfreport measure of adherence and of clinical value data analysis were found. Conclusion: Using data fromGP prescribing systems, a computerised tool to calculate individual adherence levels for oral pharmacotherapy for the treatment of diabetes, dyslipidaemia and hypothyroidism has been developed.The tool has been used to establish nonadherence levels within the three treatment groups and the demographic characteristics indicative of lower adherence levels, which in turn will enable the targeting of interventional support within HoBtPCT. © Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie 2013.

Sharing of value in business relationships:a theoretical model

This paper explores the sharing of value in business transactions. Although there is an increased usage of the terminology of value in marketing (such concepts as value based selling and pricing), as well as in purchasing (value-based purchasing), the definition of the term is still vague. In order to better understand the definition of value, the author’s argue that it is important to understand the sharing of value, in general and the element of power for the sharing of value in particular. The aim of this paper is to add to this debate and this requires us to critique the current models. The key process that the analysis of power will help to explain is the division of the available revenue stream flowing up the chain from the buyer's customers. If the buyer and supplier do not cooperate, then power will be key in the sharing of that money flow. If buyers and suppliers fully cooperate, they may be able to reduce their costs and/or increase the quality of the sales offering the buyer makes to their customer.

Numerical solution of the Dirichlet initial boundary value problem for the heat equation in exterior 3-dimensional domains using integral equations

A numerical method for the Dirichlet initial boundary value problem for the heat equation in the exterior and unbounded region of a smooth closed simply connected 3-dimensional domain is proposed and investigated. This method is based on a combination of a Laguerre transformation with respect to the time variable and an integral equation approach in the spatial variables. Using the Laguerre transformation in time reduces the parabolic problem to a sequence of stationary elliptic problems which are solved by a boundary layer approach giving a sequence of boundary integral equations of the first kind to solve. Under the assumption that the boundary surface of the solution domain has a one-to-one mapping onto the unit sphere, these integral equations are transformed and rewritten over this sphere. The numerical discretisation and solution are obtained by a discrete projection method involving spherical harmonic functions. Numerical results are included.

Measurability characteristics mapping for large volume metrology instruments selection

Measurement and verification of products and processes during the early design is attracting increasing interest from high value manufacturing industries. Measurement planning is deemed as an effective means to facilitate the integration of the metrology activity into a wider range of production processes. However, the literature reveals that there are very few research efforts in this field, especially regarding large volume metrology. This paper presents a novel approach to accomplish instruments selection, the first stage of measurement planning process, by mapping measurability characteristics between specific measurement assignments and instruments.