182 research outputs found
Impact of Data Quantization on Empirical Multifractal Analysis.
Multifractal Analysis is nowadays commonly used in real-life data analyses and involved in standard signal processing tasks such as detection, identification or classification. In a number of situations, mostly in Image Processing, the data are available for the analyses only in (possibly severely) quantized versions. The present contribution aims at analyzing the robustness of standard multifractal estimation procedures against quantization. To this end, we analyze the behaviors and statistical performance of these procedures when applied to a large number of realizations of known synthetic multifractal processes subject to various quantization levels. Our study shows that immunity against quantization can be obtained by restricting the range of scales involved in multifractal parameter estimation to the largest ones. Comparing multifractal analyses based on different multiresolution quantities, increments, wavelet coefficients and leaders, we show that wavelets, thanks to their good frequency localization, bring robustness against quantization when increments do not. This study provides the practitioner with a clear guide line to perform multifractal analysis over quantized data
Large deviations estimates for the multiscale analysis of heart rate variability
International audienceIn the realm of multiscale signal analysis, multifractal analysis provides with a natural and rich framework to measure the roughness of a time series. As such, it has drawn special attention of both mathematicians and practitioners, and led them to characterize relevant physiological factors impacting the heart rate variability. Notwithstanding these considerable progresses, multifractal analysis almost exclusively developed around the concept of Legendre singularity spectrum, for which efficient and elaborate estimators exist, but which are structurally blind to subtle features like non-concavity or, to a certain extent, non scaling of the distributions. Large deviations theory allows bypassing these limitations but it is only very recently that performing estimators were proposed to reliably compute the corresponding large deviations singularity spectrum. In this article, we illustrate the relevance of this approach, on both theoretical objects and on human heart rate signals from the Physionet public database. As conjectured, we verify that large deviations principles reveal significant information that otherwise remains hidden with classical approaches, and which can be reminiscent of some physiological characteristics. In particular we quantify the presence/absence of scale invariance of RR signals
Computer-aided detection and diagnosis of breast cancer in 2D and 3D medical imaging through multifractal analysis
This Thesis describes the research work performed in the scope of a doctoral research program
and presents its conclusions and contributions. The research activities were carried on in the
industry with Siemens S.A. Healthcare Sector, in integration with a research team.
Siemens S.A. Healthcare Sector is one of the world biggest suppliers of products, services and
complete solutions in the medical sector. The company offers a wide selection of diagnostic
and therapeutic equipment and information systems. Siemens products for medical imaging and
in vivo diagnostics include: ultrasound, computer tomography, mammography, digital breast tomosynthesis,
magnetic resonance, equipment to angiography and coronary angiography, nuclear
imaging, and many others.
Siemens has a vast experience in Healthcare and at the beginning of this project it was strategically
interested in solutions to improve the detection of Breast Cancer, to increase its competitiveness
in the sector.
The company owns several patents related with self-similarity analysis, which formed the background
of this Thesis. Furthermore, Siemens intended to explore commercially the computer-
aided automatic detection and diagnosis eld for portfolio integration. Therefore, with the
high knowledge acquired by University of Beira Interior in this area together with this Thesis,
will allow Siemens to apply the most recent scienti c progress in the detection of the breast
cancer, and it is foreseeable that together we can develop a new technology with high potential.
The project resulted in the submission of two invention disclosures for evaluation in Siemens
A.G., two articles published in peer-reviewed journals indexed in ISI Science Citation Index,
two other articles submitted in peer-reviewed journals, and several international conference
papers. This work on computer-aided-diagnosis in breast led to innovative software and novel
processes of research and development, for which the project received the Siemens Innovation
Award in 2012.
It was very rewarding to carry on such technological and innovative project in a socially sensitive
area as Breast Cancer.No cancro da mama a deteção precoce e o diagnóstico correto são de extrema importância na
prescrição terapêutica e caz e e ciente, que potencie o aumento da taxa de sobrevivência Ã
doença. A teoria multifractal foi inicialmente introduzida no contexto da análise de sinal e a
sua utilidade foi demonstrada na descrição de comportamentos siológicos de bio-sinais e até
na deteção e predição de patologias. Nesta Tese, três métodos multifractais foram estendidos
para imagens bi-dimensionais (2D) e comparados na deteção de microcalci cações em mamogramas.
Um destes métodos foi também adaptado para a classi cação de massas da mama, em
cortes transversais 2D obtidos por ressonância magnética (RM) de mama, em grupos de massas
provavelmente benignas e com suspeição de malignidade. Um novo método de análise multifractal
usando a lacunaridade tri-dimensional (3D) foi proposto para classi cação de massas da
mama em imagens volumétricas 3D de RM de mama. A análise multifractal revelou diferenças
na complexidade subjacente às localizações das microcalci cações em relação aos tecidos normais,
permitindo uma boa exatidão da sua deteção em mamogramas. Adicionalmente, foram
extraÃdas por análise multifractal caracterÃsticas dos tecidos que permitiram identi car os casos
tipicamente recomendados para biópsia em imagens 2D de RM de mama. A análise multifractal
3D foi e caz na classi cação de lesões mamárias benignas e malignas em imagens 3D de RM de
mama. Este método foi mais exato para esta classi cação do que o método 2D ou o método
padrão de análise de contraste cinético tumoral. Em conclusão, a análise multifractal fornece
informação útil para deteção auxiliada por computador em mamogra a e diagnóstico auxiliado
por computador em imagens 2D e 3D de RM de mama, tendo o potencial de complementar a
interpretação dos radiologistas
Emotional persistence in online chatting communities
How do users behave in online chatrooms, where they instantaneously read and
write posts? We analyzed about 2.5 million posts covering various topics in
Internet relay channels, and found that user activity patterns follow known
power-law and stretched exponential distributions, indicating that online chat
activity is not different from other forms of communication. Analysing the
emotional expressions (positive, negative, neutral) of users, we revealed a
remarkable persistence both for individual users and channels. I.e. despite
their anonymity, users tend to follow social norms in repeated interactions in
online chats, which results in a specific emotional "tone" of the channels. We
provide an agent-based model of emotional interaction, which recovers
qualitatively both the activity patterns in chatrooms and the emotional
persistence of users and channels. While our assumptions about agent's
emotional expressions are rooted in psychology, the model allows to test
different hypothesis regarding their emotional impact in online communication.Comment: 34 pages, 4 main and 12 supplementary figure
Measuring the Complexity of Continuous Distributions
We extend previously proposed measures of complexity, emergence, and
self-organization to continuous distributions using differential entropy. This
allows us to calculate the complexity of phenomena for which distributions are
known. We find that a broad range of common parameters found in Gaussian and
scale-free distributions present high complexity values. We also explore the
relationship between our measure of complexity and information adaptation.Comment: 21 pages, 5 Tables, 4 Figure
Video traffic : characterization, modelling and transmission
EThOS - Electronic Theses Online ServiceGBUnited Kingdo
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