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

Data flow and validation in workflow modelling

A complete workflow specification requires careful integration of many different process characteristics. Decisions must be made as to the definitions of individual activities, their scope, the order of execution that maintains the overall business process logic, the rules governing the discipline of work list scheduling to performers, identification of time constraints and more. The goal of this paper is to address an important issue in workflows modelling and specification, which is data flow, its modelling, specification and validation. Researchers have neglected this dimension of process analysis for some time, mainly focussing on structural considerations with limited verification checks. In this paper, we identify and justify the importance of data modelling in overall workflows specification and verification. We illustrate and define several potential data flow problems that, if not detected prior to workflow deployment may prevent the process from correct execution, execute process on inconsistent data or even lead to process suspension. A discussion on essential requirements of the workflow data model in order to support data validation is also given..

Using secondary knowledge to support decision tree classification of retrospective clinical data

Retrospective clinical data presents many challenges for data mining and machine learning. The transcription of patient records from paper charts and subsequent manipulation of data often results in high volumes of noise as well as a loss of other important information. In addition, such datasets often fail to represent expert medical knowledge and reasoning in any explicit manner. In this research we describe applying data mining methods to retrospective clinical data to build a prediction model for asthma exacerbation severity for pediatric patients in the emergency department. Difficulties in building such a model forced us to investigate alternative strategies for analyzing and processing retrospective data. This paper describes this process together with an approach to mining retrospective clinical data by incorporating formalized external expert knowledge (secondary knowledge sources) into the classification task. This knowledge is used to partition the data into a number of coherent sets, where each set is explicitly described in terms of the secondary knowledge source. Instances from each set are then classified in a manner appropriate for the characteristics of the particular set. We present our methodology and outline a set of experiential results that demonstrate some advantages and some limitations of our approach. © 2008 Springer-Verlag Berlin Heidelberg.

Target consolidation under high temporal processing demands as revealed by MEG

We investigated the nature of resource limitations during visual target processing by imposing high temporal processing demands on the cognitive system. This was achieved by embedding target stimuli into rapid-serial-visual-presentation-streams (RSVP). In RSVP streams, it is difficult to report the second of two targets (T2) if the second follows the first (T1) within 500 ms. This effect is known as the attentional blink (AB). For the AB to occur, it is essential that T1 is followed by a mask, as without such a stimulus, the AB is significantly attenuated. Usually, it is thought that T1 processing is delayed by the mask, which in turn delays T2 processing, increasing the likelihood for T2 failures (AB). Predictions regarding amplitudes and latencies of cortical responses (M300, the magnetic counterpart to the P300) to targets were tested by investigating the neurophysiological effects of the post-T1 item (mask) by means of magnetoencephalography (MEG). Cortical M300 responses to targets drawn from prefrontal sources – areas associated with working memory – revealed accelerated T1 yet delayed T2 processing with an intervening mask. The explanation we are proposing assumes that “protection” of ongoing T1 processing necessitated by the occurrence of the mask suppresses other activation patterns, which boosts T1 yet also hinders further processing. Our data shed light on the mechanisms employed by the human brain for ensuring visual target processing under high temporal processing demands, which is hypothesized to occur at the expense of subsequently presented information.

A generalized adaptive mathematical morphological filter for LIDAR data

Airborne Light Detection and Ranging (LIDAR) technology has become the primary method to derive high-resolution Digital Terrain Models (DTMs), which are essential for studying Earth's surface processes, such as flooding and landslides. The critical step in generating a DTM is to separate ground and non-ground measurements in a voluminous point LIDAR dataset, using a filter, because the DTM is created by interpolating ground points. As one of widely used filtering methods, the progressive morphological (PM) filter has the advantages of classifying the LIDAR data at the point level, a linear computational complexity, and preserving the geometric shapes of terrain features. The filter works well in an urban setting with a gentle slope and a mixture of vegetation and buildings. However, the PM filter often removes ground measurements incorrectly at the topographic high area, along with large sizes of non-ground objects, because it uses a constant threshold slope, resulting in "cut-off" errors. A novel cluster analysis method was developed in this study and incorporated into the PM filter to prevent the removal of the ground measurements at topographic highs. Furthermore, to obtain the optimal filtering results for an area with undulating terrain, a trend analysis method was developed to adaptively estimate the slope-related thresholds of the PM filter based on changes of topographic slopes and the characteristics of non-terrain objects. The comparison of the PM and generalized adaptive PM (GAPM) filters for selected study areas indicates that the GAPM filter preserves the most "cut-off" points removed incorrectly by the PM filter. The application of the GAPM filter to seven ISPRS benchmark datasets shows that the GAPM filter reduces the filtering error by 20% on average, compared with the method used by the popular commercial software TerraScan. The combination of the cluster method, adaptive trend analysis, and the PM filter allows users without much experience in processing LIDAR data to effectively and efficiently identify ground measurements for the complex terrains in a large LIDAR data set. The GAPM filter is highly automatic and requires little human input. Therefore, it can significantly reduce the effort of manually processing voluminous LIDAR measurements.

Data-analytiikan hyödyntäminen yrityksen talouden ohjauksessa

Kandidaatintyö on toteutettu kirjallisuuskatsauksena, jonka tavoitteena on selvittää data-analytiikan käyttökohteita ja datan hyödyntämisen vaikutusta liiketoimintaan. Työ käsittelee data-analytiikan käyttöä ja datan tehokkaan hyödyntämisen haasteita. Työ on rajattu tarkastelemaan yrityksen talouden ohjausta, jossa analytiikkaa käytetään johdon ja rahoituksen laskentatoimessa. Datan määrän eksponentiaalinen kasvunopeus luo data-analytiikan käytölle uusia haasteita ja mahdollisuuksia. Datalla itsessään ei kuitenkaan ole suurta arvoa yritykselle, vaan arvo syntyy prosessoinnin kautta. Vaikka data-analytiikkaa tutkitaan ja käytetään jo runsaasti, se tarjoaa paljon nykyisiä sovelluksia suurempia mahdollisuuksia. Yksi työn keskeisimmistä tuloksista on, että data-analytiikalla voidaan tehostaa johdon laskentatoimea ja helpottaa rahoituksen laskentatoimen tehtäviä. Tarjolla olevan datan määrä kasvaa kuitenkin niin nopeasti, että käytettävissä oleva teknologia ja osaamisen taso eivät pysy kehityksessä mukana. Varsinkin big datan laajempi käyttöönotto ja sen tehokas hyödyntäminen vaikuttavat jatkossa talouden ohjauksen käytäntöihin ja sovelluksiin yhä enemmän.

Ethical Perspectives on Big Data in Agri-food: Ownership and Governance for Safety

Big data are reshaping the way we interact with technology, thus fostering new applications to increase the safety-assessment of foods. An extraordinary amount of information is analysed using machine learning approaches aimed at detecting the existence or predicting the likelihood of future risks. Food business operators have to share the results of these analyses when applying to place on the market regulated products, whereas agri-food safety agencies (including the European Food Safety Authority) are exploring new avenues to increase the accuracy of their evaluations by processing Big data. Such an informational endowment brings with it opportunities and risks correlated to the extraction of meaningful inferences from data. However, conflicting interests and tensions among the involved entities - the industry, food safety agencies, and consumers - hinder the finding of shared methods to steer the processing of Big data in a sound, transparent and trustworthy way. A recent reform in the EU sectoral legislation, the lack of trust and the presence of a considerable number of stakeholders highlight the need of ethical contributions aimed at steering the development and the deployment of Big data applications. Moreover, Artificial Intelligence guidelines and charters published by European Union institutions and Member States have to be discussed in light of applied contexts, including the one at stake. This thesis aims to contribute to these goals by discussing what principles should be put forward when processing Big data in the context of agri-food safety-risk assessment. The research focuses on two interviewed topics - data ownership and data governance - by evaluating how the regulatory framework addresses the challenges raised by Big data analysis in these domains. The outcome of the project is a tentative Roadmap aimed to identify the principles to be observed when processing Big data in this domain and their possible implementations.

POPREP: a generic report for population management

Genetic variation provides a basis upon which populations can be genetically improved. Management of animal genetic resources in order to minimize loss of genetic diversity both within and across breeds has recently received attention at different levels, e. g., breed, national and international levels. A major need for sustainable improvement and conservation programs is accurate estimates of population parameters, such as rate of inbreeding and effective population size. A software system (POPREP) is presented that automatically generates a typeset report. Key parameters for population management, such as age structure, generation interval, variance in family size, rate of inbreeding, and effective population size form the core part of this report. The report includes a default text that describes definition, computation and meaning of the various parameters. The report is summarized in two pdf files, named Population Structure and Pedigree Analysis Reports. In addition, results (e. g., individual inbreeding coefficients, rate of inbreeding and effective population size) are stored in comma-separate-values files that are available for further processing. Pedigree data from eight livestock breeds from different species and countries were used to describe the potential of POPREP and to highlight areas for further research.

Sensorless synchronization method for thin-film direct optical broadband monitoring system

Optical monitoring systems are necessary to manufacture multilayer thin-film optical filters with low tolerance on spectrum specification. Furthermore, to have better accuracy on the measurement of film thickness, direct monitoring is a must. Direct monitoring implies acquiring spectrum data from the optical component undergoing the film deposition itself, in real time. In making film depositions on surfaces of optical components, the high vacuum evaporator chamber is the most popular equipment. Inside the evaporator, at the top of the chamber, there is a metallic support with several holes where the optical components are assembled. This metallic support has rotary motion to promote film homogenization. To acquire a measurement of the spectrum of the film in deposition, it is necessary to pass a light beam through a glass witness undergoing the film deposition process, and collect a sample of the light beam using a spectrometer. As both the light beam and the light collector are stationary, a synchronization system is required to identify the moment at which the optical component passes through the light beam.

Leanness na manutenção aeronáutica: o caso FAP

Os sistemas de armas da Força Aérea Portuguesa (FAP) têm por missão a defesa militar de Portugal, através de operações aéreas e da defesa do espaço aéreo nacional, sendo o F-16 o principal avião de ataque em uso nesta organização. Neste sentido, e tendo em conta o actual contexto económico mundial, as organizações devem rentabilizar todos os recursos disponíveis, custos associados e optimizar processos de trabalho. Tendo por base os pressupostos anteriores, o presente estudo pretende analisar a implementação de lean na FAP, uma vez que esta filosofia assenta na eliminação de desperdícios com vista a uma melhoria da qualidade e diminuição de tempos e custos. Posto isto, a análise deste trabalho vai recair sobre a área de manutenção do F-16, em concreto na Inspeção de Fase (IF), um tipo de manutenção que esta aeronave realiza a cada trezentas horas de voo. O estudo de caso vai incidir em dois momentos da IF: o primeiro ponto relaciona-se com o processamento da recolha de dados para a reunião preliminar onde são definidas, para as áreas de trabalho executantes, as ações de manutenção a realizar com a paragem da aeronave. Deste modo, pretende-se averiguar as causas inerentes aos atrasos verificados para a realização desta reunião. O segundo ponto em observação compreende a informação obtida através da aplicação informática SIAGFA, em uso na FAP, para o processamento de dados de manutenção das quatro aeronaves que inauguraram a IF com a filosofia lean. Esta análise permitiu perceber o número de horas de trabalho dispendidas (em média pelas quatro aeronaves) por cada uma das cartas de trabalho, verificando-se que as cartas adicionais comportam mais horas; foi possível compreender quais as áreas de trabalho consideradas críticas; foram identificados os dias de trabalho realizado e tempos de paragem sem qualquer tipo de intervenção. Foi ainda avaliado, por aeronave, o número de horas de trabalho realizadas na IF e quais os constrangimentos que se verificaram nas aeronaves, que não realizaram a IF no tempo definido para tal.

A aprendizagem cooperativa como ferramenta para a inclusão

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção do grau de Mestre em Ciências da Educação - Especialização em Educação Especial, Domínio Cognição e Multideficiência

Bem-estar psicológico e qualidade de vida em pessoas idosas

Dissertação de Mestrado em Psicologia da Educação, especialidade em Contextos Comunitários.

A problemática do controlo interno na área das vendas

Contabilidade em Auditoria

Uso eficiente da água nos Açores : análise de viabilidade e boas práticas em habitações unifamiliares

Dissertação de Mestrado, Engenharia e Gestão de Sistemas de Água, 4 de Março de 2016, Universidade dos Açores.

Sistemas de informação para executivos (EIS). Uma experiência de aplicação

Tese submetida à Universidade Portucalense para obtenção do grau de Mestre em Informática, elaborada sob a orientação de Prof. Doutor Reis Lima e Eng. Jorge S. Coelho.