19 research outputs found
Hazard mapping
Während wir die verheerenden Kräfte von Naturgefahren verstehen und wir davon
ausgehen müssen, dass diese unvermeidbar sind, müssen wir auch bedenken, dass dies
ein Problem ist, wo wir etwas tun können.
Studien über Gefahren ebnen den Weg, um seinen Einfluss auf die Gesellschaft zu
reduzieren. Da Katastrophen nur dann aus Naturgefahren entstehen, wenn diese mit
menschlichen Systemen konfrontiert werden, sollte die Bereitschaft in den relevanten
Gebieten steigen, um die Verluste in zukünftigen Ereignissen zu minimieren und somit
eine nachhaltige Katastrophenvorsorge zu erlangen.
Geographische Informationssysteme bieten dabei neue Möglichkeiten im
interdisziplinären Ansatz in der Katastrophenvorsorge. Damit ist es möglich ein besseres
Verständnis von den räumlichen Beziehungen und Prozesse zu erhalten. Außerdem
können Geographische Informationssysteme verwendet werden, um neue Informationen
zu gewinnen, die von unschätzbarem Wert für die Katastrophenvorbeugung sein können.
Das Hauptziel der vorliegenden Arbeit ist es, die Rolle von Gefahrenzonenkarten als
wirksames Instrument und deren kartographischen Aspekte in der Risikokommunikation
zu beleuchten. Ein konzeptioneller Rahmen, um das Gefahrenrisiko von Tsunamis in
betroffenen Küstengebieten zu beurteilen und darzustellen, wird am Ende der Arbeit
präsentiert.While we realize the devastating capacities of natural hazards and we presume that they
are unavoidable, we also have to think that it is a problem that we could do something.
Studies about hazards pave the way to minimize its impacts on our societies. As the
hazards create disasters only when it is confronted with human use systems, the
preparedness and capacity building measures for relevant communities would lead to
reduce the losses in future events and sustainable disaster mitigation.
Geographic information systems provide new possibilities in cross disciplinary approach
in disaster mitigation. It enables better understanding of spatial relationships and
processes. As well, geographic information systems could also be utilized to present new
information in maps that are invaluable in disaster mitigation.
The main objective of this work is to study the role of hazard maps as effective tools and
their cartographic aspects in spatial risk communication. A conceptual framework to
assess and present the tsunami hazard risk in an affected coastal area is discussed at the
end of the study
A novel tool for survival analysis in lymphoma patients
Annually, cancer is responsible for 40% of earlier deaths due to non-communicable
diseases, and this number increases at an annual rate of around 1.6%. These alarming
values make it essential to study this disease at a global level, to help better the lives of
all the affected patients and disseminate prevention when possible.
With the advance in technology and thanks to the influx of patients with digitalised
records that suffer from this disease, there is a greater capability to elaborate a study
about the possible causes and consequences drawn from the patient’s data. Furthermore,
the ability to better the patient’s quality of life by analysing their data and sensitising
them is fundamental in the fight against cancer.
The dissertation focuses on developing a computational tool that enables tha ability
to obtain simple statistics, thanks to classical techniques of survival analysis as well
as the analysis of lymphoma cancer, both Hodgkin and non-Hodgkin lymphomas that
constitute nearly 48% of blood cancers. To determine the factors that influence the study
of the received patients’ database, a preprocessing is done where the descriptive statistics
are obtained using the patients’ database information. After that, Kaplan-Meier estimator
curves are elaborated to determine the relationship between the studied phenomenon
and the different variables present in the database. After taking brief conclusions from
the obtained variables and subsequent descriptive analysis, an analysis using the Kaplan-
Meier estimator is done. The integration of the achieved results is implemented in a tool
that constitutes CLARIFY 1’s project dashboard.
This dissertation was created in conjunction with the CLARIFY European project, led
by the oncology medical team of University Hospital Puerta Hierro de Majadahonda.Anualmente, o cancro é responsável por 40% das mortes precoces devido a doenças
não transmissíveis, e este valor aumenta anualmente cerca de 1.6%. Estes valores alarman-
tes fazem o estudo desta doença um foco fundamental a nível global de modo a melhorar
a vida de todos os pacientes e disseminar prevenção a quando possibilidade do mesmo.
Com o avançar da tecnologia e graças a um influxo de registos digitalizados sobre
pacientes que sofrem este tipo de doença, existe uma maior capacidade de elaborar um
estudo sobre as possíveis causas e consequências retiradas a partir dos dados de pacientes
que passaram por isso. Para além disso, a capacidade de melhorar a qualidade de vida dos
pacientes através da análise dos seus dados e da sensibilização dos mesmos é fundamental
para uma constante luta contra o cancro.
Esta dissertação foca-se no desenvolvimento de uma ferramenta computacional que
permite aceder de forma simples, a estimativas obtidas a partir de técnicas clássicas de
análise de sobrevivência como exemplo de aplicação, foca-se ainda na análise do cancro
linfoma tanto Hodgkin como não-Hodgkin, que abrange cerca de 48% dos cancros de
sangue. Com o objetivo de averiguar os fatores de risco que influenciam a sobrevivência
dos pacientes da base de dados em estudo, é efetuado um pré-processamento dos dados,
onde são obtidas estatísticas descritivas da base de dados de pacientes e produzidas
estatísticas das curvas de sobrevivência com recurso ao estimador de Kaplan-Meier de
modo a determinar a relevância das variáveis analisadas da base de dados em relação
ao acontecimento analisado. A integração dos resultados obtidos através do estimador
Kaplan-Meier será integrada numa ferramenta que por sua vez fará parte do Dashboard
do projeto do CLARIFY 2.
Esta dissertação foi criada em conjunto com o projeto europeu, Clarify, liderado pela
equipa médica de oncologia do Hospital Universitário Puerta Hierro de Majadahond
Semantic discovery and reuse of business process patterns
Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse
Theoretical and methodological advances in semi-supervised learning and the class-imbalance problem.
201 p.Este trabajo se centra en la generalización teórica y práctica de dos situaciones desafiantes y conocidas del campo del aprendizaje automático a problemas de clasificación en los cuales la suposición de tener una única clase binaria no se cumple.Aprendizaje semi-supervisado es una técnica que usa grandes cantidades de datos no etiquetados para, así, mejorar el rendimiento del aprendizaje supervisado cuando el conjunto de datos etiquetados es muy acotado. Concretamente, este trabajo contribuye con metodologías potentes y computacionalmente eficientes para aprender, de forma semi-supervisada, clasificadores para múltiples variables clase. También, se investigan, de forma teórica, los límites fundamentales del aprendizaje semi-supervisado en problemas multiclase.El problema de desbalanceo de clases aparece cuando las variables objetivo presentan una distribución de probabilidad lo suficientemente desbalanceada como para desvirtuar las soluciones propuestas por los algoritmos de aprendizaje supervisado tradicionales. En este proyecto, se propone un marco teórico para separar la desvirtuación producida por el desbalanceo de clases de otros factores que afectan a la precisión de los clasificadores. Este marco es usado principalmente para realizar una recomendación de métricas de evaluación de clasificadores en esta situación. Por último, también se propone una medida del grado de desbalanceo de clases en un conjunto de datos correlacionada con la pérdida de precisión ocasionada.Intelligent Systems Grou
Theoretical and Methodological Advances in Semi-supervised Learning and the Class-Imbalance Problem
his paper focuses on the theoretical and practical generalization of two known and challenging situations from the field of machine learning to classification problems in which the assumption of having a single binary class is not fulfilled.semi-supervised learning is a technique that uses large amounts of unlabeled data to improve the performance of supervised learning when the labeled data set is very limited. Specifically, this work contributes with powerful and computationally efficient methodologies to learn, in a semi-supervised way, classifiers for multiple class variables. Also, the fundamental limits of semi-supervised learning in multi-class problems are investigated in a theoretical way. The problem of class unbalance appears when the target variables present a probability distribution unbalanced enough to distort the solutions proposed by the traditional supervised learning algorithms. In this project, a theoretical framework is proposed to separate the deviation produced by class unbalance from other factors that affect the accuracy of classifiers. This framework is mainly used to make a recommendation of classifier assessment metrics in this situation. Finally, a measure of the degree of class unbalance in a data set correlated with the loss of accuracy caused is also proposed
Research in the Archival Multiverse
Over the past 15 years, the field of archival studies around the world has experienced unprecedented growth within the academy and within the profession, and archival studies graduate education programs today have among the highest enrolments in any information field. During the same period, there has also been unparalleled expansion and innovation in the diversity of methods and theories being applied in archival scholarship. Global in scope, Research in the Archival Multiverse compiles critical and reflective essays across a wide range of emerging research areas and interests in archival studies; it aims to provide current and future archival academics with a text addressing possible methods and theoretical frameworks that have been and might be used in archival scholarship and research