Capture and storage of respiratory test data

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY WITH PRIOR ARRANGEMENT

Generation of Testing Source Code for Object-Oriented Programs

Красимир Манев, Антон Желязков, Станимир Бойчев - В статията е представена имплементацията на последната фаза на автоматичен генератор на тестови данни за структурно тестване на софтуер, написан на обектно-ориентиран език за програмиране – генерирането на изходен код на тестващия модул. Някои детайли от имплементацията на останалите фази, които са важни за имплементацията на последната фаза, са представени първо. След това е описан и алгоритъмът за генериране на кода на тестващия модул.

Evolutionary computing in search-based software engineering

This master’s thesis aims to study and represent from literature how evolutionary algorithms are used to solve different search and optimisation problems in the area of software engineering. Evolutionary algorithms are methods, which imitate the natural evolution process. An artificial evolution process evaluates fitness of each individual, which are solution candidates. The next population of candidate solutions is formed by using the good properties of the current population by applying different mutation and crossover operations. Different kinds of evolutionary algorithm applications related to software engineering were searched in the literature. Applications were classified and represented. Also the necessary basics about evolutionary algorithms were presented. It was concluded, that majority of evolutionary algorithm applications related to software engineering were about software design or testing. For example, there were applications about classifying software production data, project scheduling, static task scheduling related to parallel computing, allocating modules to subsystems, N-version programming, test data generation and generating an integration test order. Many applications were experimental testing rather than ready for real production use. There were also some Computer Aided Software Engineering tools based on evolutionary algorithms.

Extracting Business Rules through Static Analysis of the Source Code

Красимир Манев, Нели Манева, Хараламби Хараламбиев - Подходът с използване на бизнес правила (БП) беше въведен в края на миналия век, за да се улесни специфицирането на фирмен софтуер и да може той да задоволи по-добре нуждите на съответния бизнес. Днес повечето от целите на подхода са постигнати. Но усилията, в научно-изследователски и практически аспект, за постигане на „’формална основа за обратно извличане на БП от съществуващи системи “продължават. В статията е представен подход за извличане на БП от програмен код, базиран на методи за статичен анализ на кода. Посочени са някои предимства и недостатъци на такъв подход.

Aplicando programación lineal entera a la búsqueda de conjuntos de productos de prueba priorizados para líneas de productos software

Las líneas de productos software son familias de productos que están íntimamente relacionados entre sí, normalmente formados por combinaciones de un conjunto de características software. Generalmente no es factible testar todos los productos de la familia, ya que el número de productos es muy elevado debido a la explosión combinatoria de características. Por este motivo, se han propuesto criterios de cobertura que pretenden probar al menos todas las interacciones entre características sin necesidad de probar todos los productos, por ejemplo todos los pares de características (emph{pairwise coverage}). Además, es deseable testar primero los productos compuestos por un conjunto de características prioritarias. Este problema es conocido como emph{Prioritized Pairwise Test Data Generation}. En este trabajo proponemos una técnica basada en programación lineal entera para generar este conjunto de pruebas priorizado. Nuestro estudio revela que la propuesta basada en programación lineal entera consigue mejores resultados estadísticamente tanto en calidad como en tiempo de computación con respecto a las técnicas existentes para este problema.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Analyzing the researcher's work in generating data: The case of complaints

This article investigates the researcher's work in the coproduction (or not) of complaint sequences in research interviews. Using a conversation analytic approach, we show how the interviewer's management of complaint sequences in a research setting is consequential for subsequent talk and thus directly affects the data generated. In the examples shown here, researchers sharing cocategorial incumbency with respondents may well provide spaces for research participants to formulate complaints. This article examines sequences of talk surrounding complaints to show how researchers generate complaints (or not) and handle unsafe complaints. Researchers are able to provoke specific types of accounts from respondents, whereas their respondents may actively resist the researchers' direction. For researchers using the interview as a method of data generation, examination of complaint sequences and how these appear in interview data provides insight into how interview talk is coproduced and managed within a socially situated setting.

Discovery and retrieval of Geographic data using Google

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Pooling of dentin microtensile bond strength data improves clinical correlation.

Purpose: To evaluate whether the correlation between in vitro bond strength data and estimated clinical retention rates of cervical restorations after two years depends on pooled data obtained from multicenter studies or single-test data. Materials and Methods: Pooled mean data for six dentin adhesive systems (Adper Prompt L-Pop, Clearfil SE, OptiBond FL, Prime & Bond NT, Single Bond, and Scotchbond Multipurpose) and four laboratory methods (macroshear, microshear, macrotensile and microtensile bond strength test) (Scherrer et al, 2010) were correlated to estimated pooled two-year retention rates of Class V restorations using the same adhesive systems. For bond strength data from a single test institute, the literature search in SCOPUS revealed one study that tested all six adhesive systems (microtensile) and two that tested five of the six systems (microtensile, macroshear). The correlation was determined with a database designed to perform a meta-analysis on the clinical performance of cervical restorations (Heintze et al, 2010). The clinical data were pooled and adjusted in a linear mixed model, taking the study effect, dentin preparation, type of isolation and bevelling of enamel into account. A regression analysis was carried out to evaluate the correlation between clinical and laboratory findings. Results: The results of the regression analysis for the pooled data revealed that only the macrotensile (adjusted R2 = 0.86) and microtensile tests (adjusted R2 = 0.64), but not the shear and the microshear tests, correlated well with the clinical findings. As regards the data from a single-test institute, the correlation was not statistically significant. Conclusion: Macrotensile and microtensile bond strength tests showed an adequate correlation with the retention rate of cervical restorations after two years. Bond strength tests should be carried out by different operators and/or research institutes to determine the reliability and technique sensitivity of the material under investigation.

Integration of high-resolution geophysical data for the characterization of alluvial aquifers : new approaches and implications for hydrological predictions

Abstract Accurate characterization of the spatial distribution of hydrological properties in heterogeneous aquifers at a range of scales is a key prerequisite for reliable modeling of subsurface contaminant transport, and is essential for designing effective and cost-efficient groundwater management and remediation strategies. To this end, high-resolution geophysical methods have shown significant potential to bridge a critical gap in subsurface resolution and coverage between traditional hydrological measurement techniques such as borehole log/core analyses and tracer or pumping tests. An important and still largely unresolved issue, however, is how to best quantitatively integrate geophysical data into a characterization study in order to estimate the spatial distribution of one or more pertinent hydrological parameters, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first develop a strategy for the assimilation of several types of hydrogeophysical data having varying degrees of resolution, subsurface coverage, and sensitivity to the hydrologic parameter of interest. In this regard a novel simulated annealing (SA)-based conditional simulation approach was developed and then tested in its ability to generate realizations of porosity given crosshole ground-penetrating radar (GPR) and neutron porosity log data. This was done successfully for both synthetic and field data sets. A subsequent issue that needed to be addressed involved assessing the potential benefits and implications of the resulting porosity realizations in terms of groundwater flow and contaminant transport. This was investigated synthetically assuming first that the relationship between porosity and hydraulic conductivity was well-defined. Then, the relationship was itself investigated in the context of a calibration procedure using hypothetical tracer test data. Essentially, the relationship best predicting the observed tracer test measurements was determined given the geophysically derived porosity structure. Both of these investigations showed that the SA-based approach, in general, allows much more reliable hydrological predictions than other more elementary techniques considered. Further, the developed calibration procedure was seen to be very effective, even at the scale of tomographic resolution, for predictions of transport. This also held true at locations within the aquifer where only geophysical data were available. This is significant because the acquisition of hydrological tracer test measurements is clearly more complicated and expensive than the acquisition of geophysical measurements. Although the above methodologies were tested using porosity logs and GPR data, the findings are expected to remain valid for a large number of pertinent combinations of geophysical and borehole log data of comparable resolution and sensitivity to the hydrological target parameter. Moreover, the obtained results allow us to have confidence for future developments in integration methodologies for geophysical and hydrological data to improve the 3-D estimation of hydrological properties.

Pedotransfer functions to estimate proctor test parameters under different tillage systems

The Proctor test is time-consuming and requires sampling of several kilograms of soil. Proctor test parameters were predicted in Mollisols, Entisols and Vertisols of the Pampean region of Argentina under different management systems. They were estimated from a minimum number of readily available soil properties (soil texture, total organic C) and management (training data set; n = 73). The results were used to generate a soil compaction susceptibility model, which was subsequently validated using a second group of independent data (test data set; n = 24). Soil maximum bulk density was estimated as follows: Maximum bulk density (Mg m-3) = 1.4756 - 0.00599 total organic C (g kg-1) + 0.0000275 sand (g kg-1) + 0.0539 management. Management was equal to 0 for uncropped and untilled soils and 1 for conventionally tilled soils. The established models predicted the Proctor test parameters reasonably well, based on readily available soil properties. Tillage systems induced changes in the maximum bulk density regardless of total organic matter content or soil texture. The lower maximum apparent bulk density values under no-tillage require a revision of the relative compaction thresholds for different no-tillage crops.

Development of data sheets for statistical evaluation of fatigue data

To enable a mathematically and physically sound execution of the fatigue test and a correct interpretation of its results, statistical evaluation methods are used to assist in the analysis of fatigue testing data. The main objective of this work is to develop step-by-stepinstructions for statistical analysis of the laboratory fatigue data. The scopeof this project is to provide practical cases about answering the several questions raised in the treatment of test data with application of the methods and formulae in the document IIW-XIII-2138-06 (Best Practice Guide on the Statistical Analysis of Fatigue Data). Generally, the questions in the data sheets involve some aspects: estimation of necessary sample size, verification of the statistical equivalence of the collated sets of data, and determination of characteristic curves in different cases. The series of comprehensive examples which are given in this thesis serve as a demonstration of the various statistical methods to develop a sound procedure to create reliable calculation rules for the fatigue analysis.

Mapping Bias Overestimates Reference Allele Frequencies at the HLA Genes in the 1000 Genomes Project Phase I Data.

Next-generation sequencing (NGS) technologies have become the standard for data generation in studies of population genomics, as the 1000 Genomes Project (1000G). However, these techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the human leukocyte antigen (HLA) genes. Because accurate genotype calls and allele frequency estimations are crucial to population genomics analyses, it is important to assess the reliability of NGS data. Here, we evaluate the reliability of genotype calls and allele frequency estimates of the single-nucleotide polymorphisms (SNPs) reported by 1000G (phase I) at five HLA genes (HLA-A, -B, -C, -DRB1, and -DQB1). We take advantage of the availability of HLA Sanger sequencing of 930 of the 1092 1000G samples and use this as a gold standard to benchmark the 1000G data. We document that 18.6% of SNP genotype calls in HLA genes are incorrect and that allele frequencies are estimated with an error greater than ±0.1 at approximately 25% of the SNPs in HLA genes. We found a bias toward overestimation of reference allele frequency for the 1000G data, indicating mapping bias is an important cause of error in frequency estimation in this dataset. We provide a list of sites that have poor allele frequency estimates and discuss the outcomes of including those sites in different kinds of analyses. Because the HLA region is the most polymorphic in the human genome, our results provide insights into the challenges of using of NGS data at other genomic regions of high diversity.

Developing sustainable research data management services: an institutional collaboration

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Case study of the use of remotely sensed data for modeling flood inundation on the river Severn, UK.

A methodology for using remotely sensed data to both generate and evaluate a hydraulic model of floodplain inundation is presented for a rural case study in the United Kingdom: Upton-upon-Severn. Remotely sensed data have been processed and assembled to provide an excellent test data set for both model construction and validation. In order to assess the usefulness of the data and the issues encountered in their use, two models for floodplain inundation were constructed: one based on an industry standard one-dimensional approach and the other based on a simple two-dimensional approach. The results and their implications for the future use of remotely sensed data for predicting flood inundation are discussed. Key conclusions for the use of remotely sensed data are that care must be taken to integrate different data sources for both model construction and validation and that improvements in ground height data shift the focus in terms of model uncertainties to other sources such as boundary conditions. The differences between the two models are found to be of minor significance.