7 research outputs found
A list of websites and reading materials on strategy & complexity
The list has been developed based on a broad interpretation of the subject of ‘strategy & complexity’. Resources will therefore more, or less directly relate to ‘being strategic in the face of complexity’. Many of the articles and reports referred to in the attached bibliography can be accessed and downloaded from the internet. Most books can be found at amazon.com where you will often find a number of book reviews and summaries as well. Sometimes, reading the reviews will suffice and will give you the essence of the contents of the book after which you do not need to buy it. If the book looks interesting enough, buying options are easy
Visualização de informação
O relatório está dividido em duas partes. Na primeira parte, é abordado o problema da
visualização exactamente no que diz respeito à subtil correlação existente entre as técnicas (e
respectivas metáforas), o utilizador e os dados. Na segunda parte, são analisadas algumas
aplicações, projectos, ferramentas e sistemas de Visualização de Informação. Para categorizalos,
serão considerados sete tipos de dados básicos subjacentes a eles: unidimensional,
bidimensional, tridimensional, multi-dimensional, temporal, hierárquico, rede e workspace.O tema deste relatório é a visualização da informação. Esta é uma área actualmente
muito activa e vital no ensino, na pesquisa e no desenvolvimento tecnológico. A ideia básica é
utilizar imagens geradas pelo computador como meio para se obter uma maior compreensão e
apreensão da informação que está presente nos dados (geometria) e suas relações (topologia).
É um conceito simples, porém poderoso que tem criado imenso impacto em diversas áreas da
engenharia e ciência.The theme of this report is information visualization. Nowadays, this is a very active
and vital area of research, teaching and development. The basic idea of using computer
generated pictures to gain information and understanding from data and relationships is the
key concept behind it. This is an extremely simple, but very important concept which is
having a powerful impact on methodology of engineering and science.
This report is consisted of two parts. The first one, is an overview of the subtle
correlation between the visual techniques, the user perception and the data. In the second part,
several computer applications, tools, projects and information visualization systems are
analyzed. In order to categorize them, seven basic types of data are considered: onedimensional,
two- dimensional, three-dimensional, multidimensional, temporal, hierarchic,
network and workspace
Cognitive Activity Support Tools: Design of the Visual Interface
This dissertation is broadly concerned with interactive computational tools that support the performance of complex cognitive activities, examples of which are analytical reasoning, decision making, problem solving, sense making, forecasting, and learning. Examples of tools that support such activities are visualization-based tools in the areas of: education, information visualization, personal information management, statistics, and health informatics. Such tools enable access to information and data and, through interaction, enable a human-information discourse. In a more specific sense, this dissertation is concerned with the design of the visual interface of these tools. This dissertation presents a large and comprehensive theoretical framework to support research and design. Issues treated herein include interaction design and patterns of interaction for cognitive and epistemic support; analysis of the essential properties of interactive visual representations and their influences on cognitive and perceptual processes; an analysis of the structural components of interaction and how different operational forms of interaction components affect the performance of cognitive activities; an examination of how the information-processing load should be distributed between humans and tools during the performance of complex cognitive activities; and a categorization of common visualizations according to their structure and function, and a discussion of the cognitive utility of each category. This dissertation also includes a chapter that describes the design of a cognitive activity support tool, as guided by the theoretical contributions that comprise the rest of the dissertation. Those that may find this dissertation useful include researchers and practitioners in the areas of data and information visualization, visual analytics, medical and health informatics, data science, journalism, educational technology, and digital games
Population-based algorithms for improved history matching and uncertainty quantification of Petroleum reservoirs
In modern field management practices, there are two important steps that shed light on a multimillion dollar investment. The first step is history matching where the simulation model is calibrated to reproduce the historical observations from the field. In this inverse problem, different geological and petrophysical properties may provide equally good history matches. Such diverse models are likely to show different production behaviors in future. This ties the history matching with the second step, uncertainty quantification of predictions. Multiple history matched models are essential for a realistic uncertainty estimate of the future field behavior. These two steps facilitate decision making and have a direct impact on technical and financial performance of oil and gas companies.
Population-based optimization algorithms have been recently enjoyed growing popularity for solving engineering problems. Population-based systems work with a group of individuals that cooperate and communicate to accomplish a task that is normally beyond the capabilities of each individual. These individuals are deployed with the aim to solve the problem with maximum efficiency.
This thesis introduces the application of two novel population-based algorithms for history matching and uncertainty quantification of petroleum reservoir models. Ant colony optimization and differential evolution algorithms are used to search the space of parameters to find multiple history matched models and, using a Bayesian framework, the posterior probability of the models are evaluated for prediction of reservoir performance.
It is demonstrated that by bringing latest developments in computer science such as ant colony, differential evolution and multiobjective optimization, we can improve the history matching and uncertainty quantification frameworks. This thesis provides insights into performance of these algorithms in history matching and prediction and develops an understanding of their tuning parameters. The research also brings a comparative study of these methods with a benchmark technique called Neighbourhood Algorithms. This comparison reveals the superiority of the proposed methodologies in various areas such as computational efficiency and match quality
CHUB: um modelo cartográfico para a visualização e análise do corpo humano
Tese de Doutoramento em Tecnologias e Sistemas de Informação - Área do Conhecimento Engenharia de Programação e dos Sistemas InformáticosA visualização é a representação visual realística ou abstracta de um conjunto de dados que
são gerados por modelos computacionais ou resultantes de medições físicas realizadas no
mundo real. É fundamental para auxiliar as pessoas a compreenderem dados e processos
complexos e pode ser classificada consoante os seus objectivos (nomeadamente a visualização
científica e de informação). A correcta modelação e caracterização dos dados são partes
fundamentais para a escolha de técnicas visuais eficazes e a produção de uma visualização
válida. O grande desafio é exactamente o de identificar como a análise dos resultados pode e
deve ser mostrada ao potencial utilizador de uma forma simultaneamente sucinta, coerente e
útil.
O conceito de modelação cartográfica ou álgebra de mapas foi desenvolvido por Dana
Tomlin em 1983 com o Map Analysis Package1 [Sendra2000]. Um modelo cartográfico pode
ser visualizado como uma colecção de mapas registados numa base cartográfica comum, em
que cada mapa é uma variável sujeita a operações matemáticas tradicionais. A modelação é
um processo que decorre de operações primitivas de pontos, vizinhança e regiões sobre
diferentes mapas, numa lógica sequencial para interpretar e resolver problemas espaciais.
Neste contexto, a sequência de operações é similar à solução algébrica de um conjunto de
equações.
A criação de ferramentas informáticas para a análise e visualização de dados
relacionados com o corpo humano é uma área em forte expansão e de especial interesse.
Apesar destas ferramentas serem muito úteis, sofrem bastante da limitação imposta pela
arquitectura dos modelos utilizados para o seu desenvolvimento e consequente
implementação. Isto ocorre porque estes modelos adoptam os mesmos princípios e
ponderações que são aplicados a dados de natureza não humana ou biológica e tratando-os de
forma independente e atómica. Por outro lado, a utilização de técnicas visuais pouco intuitivas
no sentido de denotar a interdependência espacial inerente a este tipo de informação é outra
limitação a salientar neste tipo de ferramentas.
Os dados relacionados com o corpo humano apresentam uma forte componente
espacial. Para que seja possível uma análise e investigação correctas é necessário ter isso
sempre em consideração. Um bom exemplo desta situação é o diagnóstico médico. A
combinação de informação oriunda de diferentes partes do corpo humano é normalmente
necessária para que um médico possa diagnosticar a doença de um paciente. O acto de
diagnosticar pode ser traduzido por um conjunto de operações de álgebra de mapas
executadas sobre os dados relacionados com o corpo humano do paciente.
Qualquer modelo que pretenda servir de base para o desenvolvimento e
implementação de ferramentas informáticas orientadas para a medicina, e em especial, para a
análise e visualização de dados relacionado com o corpo humano, deve incorporar os
princípios fundamentais da modelação cartográfica. Desta maneira, é possível que os dados
possam ser devidamente modelados e consequentemente extrapolada mais informação útil.
Por outro lado, a utilização da visualização como instrumento de comunicação de resultados,
com a inclusão de metáforas visuais cartográficas é outra mais-valia a ter em conta.
O modelo CHUB (Cartographic Human Body), que é apresentado neste trabalho,
pretende colmatar essa falha identificada no tratamento e visualização de dados relacionados
com o corpo humano. Utiliza a modelação cartográfica como alicerce fundamental para a
análise dos dados e a visualização científica e de informação como meio para a comunicação
de resultados. Para ser possível a sua avaliação e validação foram considerados dois estudos
de caso: diagnóstico da artrose no joelho e a análise de sessões de hidrocinesioterapia. Para
estes dois estudos de caso foi implementado um protótipo que instancia o modelo CHUB
nestes casos particulares, permitindo a sua utilização, avaliação e validação em dois domínios
específicos. Os resultados obtidos após a utilização e avaliação do protótipo permitiram
validar com sucesso o modelo CHUB proposto nesta tese de doutoramento.Visualization is the realistic or abstract visual representation of a dataset that is generated by
computer models or resulting from physical measurements of the real world. Visualization is
fundamental to help people understand data and complexes processes and can be categorized
according its goals (scientific or information). The correct data model and characterization are
essential to the right choice of the visualization techniques and the production of useful
visualizations. The great challenge lies in how to determine that the results are showed to the
final users at the same time in a coherent, useful and simple way.
The cartographic model concept was developed by Dana Tomlin in 1983 with the Map
Analysis Package2 [Sendra2000]. A cartographic model can be seen as a collection of maps
that are registered in a cartographic database, where each map is a “variable” that can be
mathematically operated. These operations may involve primitives such as points or areas of
different maps, for example, in a sequential order to interpret and solve spatial problems. In
this context, the sequence of operations is similar to the algebraic solution of a group of
equations.
The creation of automatic tools for human’s body data analysis and visualization is a
field in expansion and of great interest. However these tools are very valuable, they suffer
from a common limitation that is imposed by their basis architectural model. In general, they
rarely represent in a suitable way biological, morphological and/or biomedical data spatial
interdependency. These models treat data in an almost total focused and independent way.
The human body systems and organs work as a complex machine, where each part depends
strongly on the others. This dependency might be stronger or weaker to the system or organ
importance on the overall patient condition. The doctor diagnoses an illness by comparing and
analyzing information not only directly related to the mostly affected organ, but also to the
body as a whole. In fact the doctor performs a subtle spatial analysis, and therefore, executes a
typical algebraic map operation in his/her mind, when diagnosing a patient. An illness might arouse different symptoms and physiological changes in systems/organs that are not directly
related to the spatial location of it.
CHUB is a model that was developed taking into consideration the main principles of
cartographic modelling. It structures data according to different layers of information. Each
layer is associated to a specific organ and/or system, and might contain geometric data or
attributes that are “human-referenced”. CHUB has not been developed as a dynamic model. It
is considered that dynamic issues related to human’s body data, such as body movement,
blood flow or heartbeat (besides others) will be accomplished by other models that should be
used as a specialized extension to CHUB.
In order to validate CHUB two cases of study were considered – osteoarthritis knee
diagnosis and hydrokinetic therapy sessions analysis, proposed two strategies for its
validation and a prototype implemented. This prototype allowed its utilization, evaluation and
validation in two different domains. The results achieved after its utilization and test lead to a
complete CHUB validation
A Knowledge Integration Framework for Information Visualization
Abstract. Users can better understand complex data sets by combining insights from multiple coordinated visual displays that include relevant domain knowledge. When dealing with multidimensional data and clustering results, the most familiar displays and comprehensible are 1- and 2-dimensional projections (histograms, and scatterplots). Other easily understood displays of domain knowledge are tabular and hierarchical information for the same or related data sets. The novel parallel coordinates view [6] powered by a direct-manipulation search, offers strong advantages, but requires some training for most users. We provide a review of related work in the area of information visualization, and introduce new tools and interaction examples on how to incorporate users ’ domain knowledge for understanding clustering results. Our examples present hierarchical clustering of gene expression data, coordinated with a parallel coordinates view and with the gene annotation and gene ontology.