Optimization of chemical plant simulation using double collocation

A method has been constructed for the solution of a wide range of chemical plant simulation models including differential equations and optimization. Double orthogonal collocation on finite elements is applied to convert the model into an NLP problem that is solved either by the VF 13AD package based on successive quadratic programming, or by the GRG2 package, based on the generalized reduced gradient method. This approach is termed simultaneous optimization and solution strategy. The objective functional can contain integral terms. The state and control variables can have time delays. Equalities and inequalities containing state and control variables can be included into the model as well as algebraic equations and inequalities. The maximum number of independent variables is 2. Problems containing 3 independent variables can be transformed into problems having 2 independent variables using finite differencing. The maximum number of NLP variables and constraints is 1500. The method is also suitable for solving ordinary and partial differential equations. The state functions are approximated by a linear combination of Lagrange interpolation polynomials. The control function can either be approximated by a linear combination of Lagrange interpolation polynomials or by a piecewise constant function over finite elements. The number of internal collocation points can vary by finite elements. The residual error is evaluated at arbitrarily chosen equidistant grid-points, thus enabling the user to check the accuracy of the solution between collocation points, where the solution is exact. The solution functions can be tabulated. There is an option to use control vector parameterization to solve optimization problems containing initial value ordinary differential equations. When there are many differential equations or the upper integration limit should be selected optimally then this approach should be used. The portability of the package has been addressed converting the package from V AX FORTRAN 77 into IBM PC FORTRAN 77 and into SUN SPARC 2000 FORTRAN 77. Computer runs have shown that the method can reproduce optimization problems published in the literature. The GRG2 and the VF I 3AD packages, integrated into the optimization package, proved to be robust and reliable. The package contains an executive module, a module performing control vector parameterization and 2 nonlinear problem solver modules, GRG2 and VF I 3AD. There is a stand-alone module that converts the differential-algebraic optimization problem into a nonlinear programming problem.

Projected sequential Gaussian processes: flexible interpolation for large data sets

Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential framework for inference in such projected processes is presented, where the observations are considered one at a time. We introduce a C++ library for carrying out such projected, sequential estimation which adds several novel features. In particular we have incorporated the ability to use a generic observation operator, or sensor model, to permit data fusion. We can also cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the variogram parameters is based on maximum likelihood estimation. We illustrate the projected sequential method in application to synthetic and real data sets. We discuss the software implementation and suggest possible future extensions.

A web processing service for validating interpolation

An interoperable web processing service (WPS) for the automatic interpolation of environmental data has been developed in the frame of the INTAMAP project. In order to assess the performance of the interpolation method implemented, a validation WPS has also been developed. This validation WPS can be used to perform leave one out and K-fold cross validation: a full dataset is submitted and a range of validation statistics and diagnostic plots (e.g. histograms, variogram of residuals, mean errors) is received in return. This paper presents the architecture of the validation WPS and a case study is used to briefly illustrate its use in practice. We conclude with a discussion on the current limitations of the system and make proposals for further developments.

INTAMAP: an interoperable automated interpolation web service

INTAMAP is a web processing service for the automatic interpolation of measured point data. Requirements were (i) using open standards for spatial data such as developed in the context of the open geospatial consortium (OGC), (ii) using a suitable environment for statistical modelling and computation, and (iii) producing an open source solution. The system couples the 52-North web processing service, accepting data in the form of an observations and measurements (O&M) document with a computing back-end realized in the R statistical environment. The probability distribution of interpolation errors is encoded with UncertML, a new markup language to encode uncertain data. Automatic interpolation needs to be useful for a wide range of applications and the algorithms have been designed to cope with anisotropies and extreme values. In the light of the INTAMAP experience, we discuss the lessons learnt.

Lessons learned from INTAMAP, an interoperable web service for the real-time interpolation of environmental variables

Interpolated data are an important part of the environmental information exchange as many variables can only be measured at situate discrete sampling locations. Spatial interpolation is a complex operation that has traditionally required expert treatment, making automation a serious challenge. This paper presents a few lessons learnt from INTAMAP, a project that is developing an interoperable web processing service (WPS) for the automatic interpolation of environmental data using advanced geostatistics, adopting a Service Oriented Architecture (SOA). The “rainbow box” approach we followed provides access to the functionality at a whole range of different levels. We show here how the integration of open standards, open source and powerful statistical processing capabilities allows us to automate a complex process while offering users a level of access and control that best suits their requirements. This facilitates benchmarking exercises as well as the regular reporting of environmental information without requiring remote users to have specialized skills in geostatistics.

Satellite borne radar altimetry : empirical orbit refinement and ocean signal recovery techniques

Measurements of the sea surface obtained by satellite borne radar altimetry are irregularly spaced and contaminated with various modelling and correction errors. The largest source of uncertainty for low Earth orbiting satellites such as ERS-1 and Geosat may be attributed to orbital modelling errors. The empirical correction of such errors is investigated by examination of single and dual satellite crossovers, with a view to identifying the extent of any signal aliasing: either by removal of long wavelength ocean signals or introduction of additional error signals. From these studies, it was concluded that sinusoidal approximation of the dominant one cycle per revolution orbit error over arc lengths of 11,500 km did not remove a significant mesoscale ocean signal. The use of TOPEX/Poseidon dual crossovers with ERS-1 was shown to substantially improve the radial accuracy of ERS-1, except for some absorption of small TOPEX/Poseidon errors. The extraction of marine geoid information is of great interest to the oceanographic community and was the subject of the second half of this thesis. Firstly through determination of regional mean sea surfaces using Geosat data, it was demonstrated that a dataset with 70cm orbit error contamination could produce a marine geoid map which compares to better than 12cm with an accurate regional high resolution gravimetric geoid. This study was then developed into Optimal Fourier Transform Interpolation, a technique capable of analysing complete altimeter datasets for the determination of consistent global high resolution geoid maps. This method exploits the regular nature of ascending and descending data subsets thus making possible the application of fast Fourier transform algorithms. Quantitative assessment of this method was limited by the lack of global ground truth gravity data, but qualitative results indicate good signal recovery from a single 35-day cycle.

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.

Accuracy of Goldmann, ocular response analyser, Pascal and TonoPen XL tonometry in keratoconic and normal eyes

Aim: The aim of this study was to evaluate the practicality and accuracy of tonometers used in routine clinical practice for established keratoconus (KC). Methods: This was a prospective study of 118 normal and 76 keratoconic eyes where intraocular pressure (IOP) was measured in random order using the Goldman applanation tonometer (GAT), Pascal dynamic contour tonometer (DCT), Reichert ocular response analyser (ORA) and TonoPen XL tonometer. Corneal hysteresis (CH) and corneal resistance factor (CRF), as calculated by the ORA, were recorded. Central corneal thickness (CCT) was measured using an ultrasound pachymeter. Results: The difference in IOP values between instruments was highly significant in both study groups (p<0.001). All other IOP measures were significantly higher than those for GAT, except for the Goldmann-correlated IOP (average of the two applanation pressure points) (IOPg) as measured by ORA in the control group and the CH-corrected IOP (corneal-compensated IOP value) (IOPcc) measures in the KC group. CCT, CH and CRF were significantly less in the KC group (p<0.001). Apart from the DCT, all techniques tended to measure IOP higher in eyes with thicker corneas. Conclusion: The DCT and the ORA are currently the most appropriate tonometers to use in KC for the measurement of IOPcc. Corneal factors such as CH and CRT may be of more importance than CCT in causing inaccuracies in applanation tonometry techniques.

INTAMAP: the design and implementation of an interoperable automated interpolation web service

INTAMAP is a Web Processing Service for the automatic spatial interpolation of measured point data. Requirements were (i) using open standards for spatial data such as developed in the context of the Open Geospatial Consortium (OGC), (ii) using a suitable environment for statistical modelling and computation, and (iii) producing an integrated, open source solution. The system couples an open-source Web Processing Service (developed by 52°North), accepting data in the form of standardised XML documents (conforming to the OGC Observations and Measurements standard) with a computing back-end realised in the R statistical environment. The probability distribution of interpolation errors is encoded with UncertML, a markup language designed to encode uncertain data. Automatic interpolation needs to be useful for a wide range of applications and the algorithms have been designed to cope with anisotropy, extreme values, and data with known error distributions. Besides a fully automatic mode, the system can be used with different levels of user control over the interpolation process.

Projection and interpolation based techniques for structured and impulsive noise filtering

In this chapter we present the relevant mathematical background to address two well defined signal and image processing problems. Namely, the problem of structured noise filtering and the problem of interpolation of missing data. The former is addressed by recourse to oblique projection based techniques whilst the latter, which can be considered equivalent to impulsive noise filtering, is tackled by appropriate interpolation methods.

Novel speech signal processing algorithms for high-accuracy classification of Parkinson's disease

There has been considerable recent research into the connection between Parkinson's disease (PD) and speech impairment. Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to predict PD symptom severity using speech signals have been introduced. In this paper, we test how accurately these novel algorithms can be used to discriminate PD subjects from healthy controls. In total, we compute 132 dysphonia measures from sustained vowels. Then, we select four parsimonious subsets of these dysphonia measures using four feature selection algorithms, and map these feature subsets to a binary classification response using two statistical classifiers: random forests and support vector machines. We use an existing database consisting of 263 samples from 43 subjects, and demonstrate that these new dysphonia measures can outperform state-of-the-art results, reaching almost 99% overall classification accuracy using only ten dysphonia features. We find that some of the recently proposed dysphonia measures complement existing algorithms in maximizing the ability of the classifiers to discriminate healthy controls from PD subjects. We see these results as an important step toward noninvasive diagnostic decision support in PD.

Rapid testing for group B streptococcus during labour: a test accuracy study with evaluation of acceptability and cost-effectiveness

OBJECTIVE: To determine the accuracy, acceptability and cost-effectiveness of polymerase chain reaction (PCR) and optical immunoassay (OIA) rapid tests for maternal group B streptococcal (GBS) colonisation at labour. DESIGN: A test accuracy study was used to determine the accuracy of rapid tests for GBS colonisation of women in labour. Acceptability of testing to participants was evaluated through a questionnaire administered after delivery, and acceptability to staff through focus groups. A decision-analytic model was constructed to assess the cost-effectiveness of various screening strategies. SETTING: Two large obstetric units in the UK. PARTICIPANTS: Women booked for delivery at the participating units other than those electing for a Caesarean delivery. INTERVENTIONS: Vaginal and rectal swabs were obtained at the onset of labour and the results of vaginal and rectal PCR and OIA (index) tests were compared with the reference standard of enriched culture of combined vaginal and rectal swabs. MAIN OUTCOME MEASURES: The accuracy of the index tests, the relative accuracies of tests on vaginal and rectal swabs and whether test accuracy varied according to the presence or absence of maternal risk factors. RESULTS: PCR was significantly more accurate than OIA for the detection of maternal GBS colonisation. Combined vaginal or rectal swab index tests were more sensitive than either test considered individually [combined swab sensitivity for PCR 84% (95% CI 79-88%); vaginal swab 58% (52-64%); rectal swab 71% (66-76%)]. The highest sensitivity for PCR came at the cost of lower specificity [combined specificity 87% (95% CI 85-89%); vaginal swab 92% (90-94%); rectal swab 92% (90-93%)]. The sensitivity and specificity of rapid tests varied according to the presence or absence of maternal risk factors, but not consistently. PCR results were determinants of neonatal GBS colonisation, but maternal risk factors were not. Overall levels of acceptability for rapid testing amongst participants were high. Vaginal swabs were more acceptable than rectal swabs. South Asian women were least likely to have participated in the study and were less happy with the sampling procedure and with the prospect of rapid testing as part of routine care. Midwives were generally positive towards rapid testing but had concerns that it might lead to overtreatment and unnecessary interference in births. Modelling analysis revealed that the most cost-effective strategy was to provide routine intravenous antibiotic prophylaxis (IAP) to all women without screening. Removing this strategy, which is unlikely to be acceptable to most women and midwives, resulted in screening, based on a culture test at 35-37 weeks' gestation, with the provision of antibiotics to all women who screened positive being most cost-effective, assuming that all women in premature labour would receive IAP. The results were sensitive to very small increases in costs and changes in other assumptions. Screening using a rapid test was not cost-effective based on its current sensitivity, specificity and cost. CONCLUSIONS: Neither rapid test was sufficiently accurate to recommend it for routine use in clinical practice. IAP directed by screening with enriched culture at 35-37 weeks' gestation is likely to be the most acceptable cost-effective strategy, although it is premature to suggest the implementation of this strategy at present.

Pulse oximetry as a screening test for congenital heart defects in newborn infants: a test accuracy study with evaluation of acceptability and cost-effectiveness

Background: Screening for congenital heart defects (CHDs) relies on antenatal ultrasound and postnatal clinical examination; however, life-threatening defects often go undetected. Objective: To determine the accuracy, acceptability and cost-effectiveness of pulse oximetry as a screening test for CHDs in newborn infants. Design: A test accuracy study determined the accuracy of pulse oximetry. Acceptability of testing to parents was evaluated through a questionnaire, and to staff through focus groups. A decision-analytic model was constructed to assess cost-effectiveness. Setting: Six UK maternity units. Participants: These were 20,055 asymptomatic newborns at = 35 weeks’ gestation, their mothers and health-care staff. Interventions: Pulse oximetry was performed prior to discharge from hospital and the results of this index test were compared with a composite reference standard (echocardiography, clinical follow-up and follow-up through interrogation of clinical databases). Main outcome measures: Detection of major CHDs – defined as causing death or requiring invasive intervention up to 12 months of age (subdivided into critical CHDs causing death or intervention before 28 days, and serious CHDs causing death or intervention between 1 and 12 months of age); acceptability of testing to parents and staff; and the cost-effectiveness in terms of cost per timely diagnosis. Results: Fifty-three of the 20,055 babies screened had a major CHD (24 critical and 29 serious), a prevalence of 2.6 per 1000 live births. Pulse oximetry had a sensitivity of 75.0% [95% confidence interval (CI) 53.3% to 90.2%] for critical cases and 49.1% (95% CI 35.1% to 63.2%) for all major CHDs. When 23 cases were excluded, in which a CHD was already suspected following antenatal ultrasound, pulse oximetry had a sensitivity of 58.3% (95% CI 27.7% to 84.8%) for critical cases (12 babies) and 28.6% (95% CI 14.6% to 46.3%) for all major CHDs (35 babies). False-positive (FP) results occurred in 1 in 119 babies (0.84%) without major CHDs (specificity 99.2%, 95% CI 99.0% to 99.3%). However, of the 169 FPs, there were six cases of significant but not major CHDs and 40 cases of respiratory or infective illness requiring medical intervention. The prevalence of major CHDs in babies with normal pulse oximetry was 1.4 (95% CI 0.9 to 2.0) per 1000 live births, as 27 babies with major CHDs (6 critical and 21 serious) were missed. Parent and staff participants were predominantly satisfied with screening, perceiving it as an important test to detect ill babies. There was no evidence that mothers given FP results were more anxious after participating than those given true-negative results, although they were less satisfied with the test. White British/Irish mothers were more likely to participate in the study, and were less anxious and more satisfied than those of other ethnicities. The incremental cost-effectiveness ratio of pulse oximetry plus clinical examination compared with examination alone is approximately £24,900 per timely diagnosis in a population in which antenatal screening for CHDs already exists. Conclusions: Pulse oximetry is a simple, safe, feasible test that is acceptable to parents and staff and adds value to existing screening. It is likely to identify cases of critical CHDs that would otherwise go undetected. It is also likely to be cost-effective given current acceptable thresholds. The detection of other pathologies, such as significant CHDs and respiratory and infective illnesses, is an additional advantage. Other pulse oximetry techniques, such as perfusion index, may enhance detection of aortic obstructive lesions.

Mind-Reading Accuracy in Intimate Relationships:Assessing the Roles of the Relationship, the Target, and the Judge

Using a video-review procedure, multiple perceivers carried out mind-reading tasks of multiple targets at different levels of acquaintanceship (50 dating couples, friends of the dating partners, and strangers). As predicted, the authors found that mind-reading accuracy was (a) higher as a function of increased acquaintanceship, (b) relatively unaffected by target effects, (c) influenced by individual differences in perceivers' ability, and (d) higher for female than male perceivers. In addition, superior mind-reading accuracy (for dating couples and friends) was related to higher relationship satisfaction, closeness, and more prior disclosure about the problems discussed, but only under moderating conditions related to sex and relationship length. The authors conclude that the nature of the relationship between the perceiver and the target occupies a pivotal role in determining mind-reading accuracy.

Interactions between landcover pattern and geospatial processing methods:effects on landscape metrics and classification accuracy

Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric "number of patches" than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty. © 2013 Elsevier B.V.