Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04

Selecting optimal instantiations of data models - Theory and validation of an ex ante approach

The schema of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. Obtaining quickly the appropriate data increases the likelihood that an organization will make good decisions and respond adeptly to challenges. This research presents and validates a methodology for evaluating, ex ante, the relative desirability of alternative instantiations of a model of data. In contrast to prior research, each instantiation is based on a different formal theory. This research theorizes that the instantiation that yields the lowest weighted average query complexity for a representative sample of information requests is the most desirable instantiation for end-user queries. The theory was validated by an experiment that compared end-user performance using an instantiation of a data structure based on the relational model of data with performance using the corresponding instantiation of the data structure based on the object-relational model of data. Complexity was measured using three different Halstead metrics: program length, difficulty, and effort. For a representative sample of queries, the average complexity using each instantiation was calculated. As theorized, end users querying the instantiation with the lower average complexity made fewer semantic errors, i.e., were more effective at composing queries. (c) 2005 Elsevier B.V. All rights reserved.

Using computational fluid dynamics in combating erosion-corrosion

Computational fluid dynamics was used to search for the links between the observed pattern of attack seen in a bauxite refinery's heat exchanger headers and the hydrodynamics inside the header. Validation of the computational fluid dynamics results was done by comparing then with flow parameters measured in a 1:5 scale model of the first pass header in the laboratory. Computational fluid dynamics simulations were used to establish hydrodynamic similarity between the 1:5 scale and full scale models of the first pass header. It was found that the erosion-corrosion damage seen at the tubesheet of the first pass header was a consequence of increased levels of turbulence at the tubesheet caused by a rapidly turning flow. A prismatic flow corrections device introduced in the past helped in rectifying the problem at the tubesheet but exaggerated the erosion-corrosion problem at the first pass header shell. A number of alternative flow correction devices were tested using computational fluid dynamics. Axial ribbing in the first pass header and an inlet flow diffuser have shown the best performance and were recommended for implementation. Computational fluid dynamics simulations have revealed a smooth orderly low turbulence flow pattern in the second, third and fourth pass as well as the exit headers where no erosion-corrosion was seen in practice. This study has confirmed that near-wall turbulence intensity, which can be successfully predicted by using computational fluid dynamics, is a good hydrodynamic predictor of erosion-corrosion damage in complex geometries. (c) 2006 Published by Elsevier Ltd.

Assessing the quality of risk factor survey data: lessons from the WHO MONICA Project

Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.

Data quality initiatives - striving for continuous improvements

Although managers consider accurate, timely, and relevant information as critical to the quality of their decisions, evidence of large variations in data quality abounds. Over a period of twelve months, the action research project reported herein attempted to investigate and track data quality initiatives undertaken by the participating organisation. The investigation focused on two types of errors: transaction input errors and processing errors. Whenever the action research initiative identified non-trivial errors, the participating organisation introduced actions to correct the errors and prevent similar errors in the future. Data quality metrics were taken quarterly to measure improvements resulting from the activities undertaken during the action research project. The action research project results indicated that for a mission-critical database to ensure and maintain data quality, commitment to continuous data quality improvement is necessary. Also, communication among all stakeholders is required to ensure common understanding of data quality improvement goals. The action research project found that to further substantially improve data quality, structural changes within the organisation and to the information systems are sometimes necessary. The major goal of the action research study is to increase the level of data quality awareness within all organisations and to motivate them to examine the importance of achieving and maintaining high-quality data.

Dissecting query performance in logical data models: Parsimony vs. greater ontological clarity

Even when data repositories exhibit near perfect data quality, users may formulate queries that do not correspond to the information requested. Users’ poor information retrieval performance may arise from either problems understanding of the data models that represent the real world systems, or their query skills. This research focuses on users’ understanding of the data structures, i.e., their ability to map the information request and the data model. The Bunge-Wand-Weber ontology was used to formulate three sets of hypotheses. Two laboratory experiments (one using a small data model and one using a larger data model) tested the effect of ontological clarity on users’ performance when undertaking component, record, and aggregate level tasks. The results indicate for the hypotheses associated with different representations but equivalent semantics that parsimonious data model participants performed better for component level tasks but that ontologically clearer data model participants performed better for record and aggregate level tasks.

Neural networks for time-varying data

This paper reviews some basic issues and methods involved in using neural networks to respond in a desired fashion to a temporally-varying environment. Some popular network models and training methods are introduced. A speech recognition example is then used to illustrate the central difficulty of temporal data processing: learning to notice and remember relevant contextual information. Feedforward network methods are applicable to cases where this problem is not severe. The application of these methods are explained and applications are discussed in the areas of pure mathematics, chemical and physical systems, and economic systems. A more powerful but less practical algorithm for temporal problems, the moving targets algorithm, is sketched and discussed. For completeness, a few remarks are made on reinforcement learning.

Nonlinear loop mirror-based all-optical signal processing in fiber-optic communications

All-optical data processing is expected to play a major role in future optical communications. The fiber nonlinear optical loop mirror (NOLM) is a valuable tool in optical signal processing applications. This paper presents an overview of our recent advances in developing NOLM-based all-optical processing techniques for application in fiber-optic communications. The use of in-line NOLMs as a general technique for all-optical passive 2R (reamplification, reshaping) regeneration of return-to-zero (RZ) on-off keyed signals in both high-speed, ultralong-distance transmission systems and terrestrial photonic networks is reviewed. In this context, a theoretical model enabling the description of the stable propagation of carrier pulses with periodic all-optical self-regeneration in fiber systems with in-line deployment of nonlinear optical devices is presented. A novel, simple pulse processing scheme using nonlinear broadening in normal dispersion fiber and loop mirror intensity filtering is described, and its employment is demonstrated as an optical decision element at a RZ receiver as well as an in-line device to realize a transmission technique of periodic all-optical RZ-nonreturn-to-zero-like format conversion. The important issue of phase-preserving regeneration of phase-encoded signals is also addressed by presenting a new design of NOLM based on distributed Raman amplification in the loop fiber. © 2008 Elsevier Inc. All rights reserved.

Exploratory database visualisation: the application and assessment of data and dimensionality reduction

This thesis describes the development of a complete data visualisation system for large tabular databases, such as those commonly found in a business environment. A state-of-the-art 'cyberspace cell' data visualisation technique was investigated and a powerful visualisation system using it was implemented. Although allowing databases to be explored and conclusions drawn, it had several drawbacks, the majority of which were due to the three-dimensional nature of the visualisation. A novel two-dimensional generic visualisation system, known as MADEN, was then developed and implemented, based upon a 2-D matrix of 'density plots'. MADEN allows an entire high-dimensional database to be visualised in one window, while permitting close analysis in 'enlargement' windows. Selections of records can be made and examined, and dependencies between fields can be investigated in detail. MADEN was used as a tool for investigating and assessing many data processing algorithms, firstly data-reducing (clustering) methods, then dimensionality-reducing techniques. These included a new 'directed' form of principal components analysis, several novel applications of artificial neural networks, and discriminant analysis techniques which illustrated how groups within a database can be separated. To illustrate the power of the system, MADEN was used to explore customer databases from two financial institutions, resulting in a number of discoveries which would be of interest to a marketing manager. Finally, the database of results from the 1992 UK Research Assessment Exercise was analysed. Using MADEN allowed both universities and disciplines to be graphically compared, and supplied some startling revelations, including empirical evidence of the 'Oxbridge factor'.

Novel approaches in nonlinear optical fibre-based signal processing

All-optical data processing is expected to play a major role in future optical communications. Nonlinear effects in optical fibres have many attractive features and a great, not yet fully explored potential in optical signal processing. Here, we overview our recent advances in developing novel techniques and approaches to all-optical processing based on optical fibre nonlinearities.

Processing and rendering of Fourier domain optical coherence tomography images at a line rate over 524 kHz using a graphics processing unit

In Fourier domain optical coherence tomography (FD-OCT), a large amount of interference data needs to be resampled from the wavelength domain to the wavenumber domain prior to Fourier transformation. We present an approach to optimize this data processing, using a graphics processing unit (GPU) and parallel processing algorithms. We demonstrate an increased processing and rendering rate over that previously reported by using GPU paged memory to render data in the GPU rather than copying back to the CPU. This avoids unnecessary and slow data transfer, enabling a processing and display rate of well over 524,000 A-scan/s for a single frame. To the best of our knowledge this is the fastest processing demonstrated to date and the first time that FD-OCT processing and rendering has been demonstrated entirely on a GPU.

Nonlinear pulse shaping in fibres for pulse generation and optical processing

The development of new all-optical technologies for data processing and signal manipulation is a field of growing importance with a strong potential for numerous applications in diverse areas of modern science. Nonlinear phenomena occurring in optical fibres have many attractive features and great, but not yet fully explored, potential in signal processing. Here, we review recent progress on the use of fibre nonlinearities for the generation and shaping of optical pulses and on the applications of advanced pulse shapes in all-optical signal processing. Amongst other topics, we will discuss ultrahigh repetition rate pulse sources, the generation of parabolic shaped pulses in active and passive fibres, the generation of pulses with triangular temporal profiles, and coherent supercontinuum sources. The signal processing applications will span optical regeneration, linear distortion compensation, optical decision at the receiver in optical communication systems, spectral and temporal signal doubling, and frequency conversion. © Copyright 2012 Sonia Boscolo and Christophe Finot.

All-optical nonlinear fibre signal processing

All-optical technologies for data processing and signal manipulation are expected to play a major role in future optical communications. Nonlinear phenomena occurring in optical fibre have many attractive features and great, but not yet fully exploited potential in optical signal processing. Here, we overview our recent results and advances in developing novel photonic techniques and approaches to all-optical processing based on fibre nonlinearities. Amongst other topics, we will discuss phase-preserving optical 2R regeneration, the possibility of using parabolic/flat-top pulses for optical signal processing and regeneration, and nonlinear optical pulse shaping. A method for passive nonlinear pulse shaping based on pulse pre-chirping and propagation in a normally dispersive fibre will be presented. The approach provides a simple way of generating various temporal waveforms of fundamental and practical interest. Particular emphasis will be given to the formation and characterization of pulses with a triangular intensity profile. A new technique of doubling/copying optical pulses in both the frequency and time domains using triangular-shaped pulses will be also introduced.