Dynamical Analysis and Visualization of Tornadoes Time Series

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.

Sentiment analysis on twitter for the portuguese language

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

O âmbito de aplicação material da legislação de proteção de dados pessoais e o tratamento de imagem por pessoa singular

Images have gained a never before seen importance. Technological changes have given the Information Society extraordinary means to capture, treat and transmit images, wheter your own or those of others, with or without a commercial purpose, with no boundaries of time or country, without “any kind of eraser”. From the several different ways natural persons may engage in image processing with no commercial purpose, the cases of sharing pictures through social networks and video surveillance assume particular relevance. Consequently there are growing legitimate concerns with the protection of one's image, since its processing may sometimes generate situations of privacy invasion or put at risk other fundamental rights. With this in mind, the present thesis arises from the question: what are the existent legal instruments in Portuguese Law that enable citizens to protect themselves from the abusive usage of their own pictures, whether because that image have been captured by a smartphone or some video surveillance camera, whether because it was massively shared through a blog or some social network? There is no question the one's right to not having his or her image used in an abusive way is protected by the Portuguese constitution, through the article 26th CRP, as well as personally right, under the article 79th of the Civil Code, and finally through criminal law, articles 192nd and 193rd of the Criminal Code. The question arises in the personal data protection context, considering that one's picture, given certain conditions, is personal data. Both the Directive 95/46/CE dated from 1995 as well as the LPD from 1998 are applicable to the processing of personal data, but both exclude situations of natural persons doing so in the pursuit of activities strictly personal or family-related. These laws demand complex procedures to natural persons, such as the preemptive formal authorisation request to the Data Protection National Commission. Failing to do so a natural person may result in the application of fines as high as €2.500,00 or even criminal charges. Consequently, the present thesis aims to study if the image processing with no commercial purposes by a natural person in the context of social networks or through video surveillance belongs to the domain of the existent personal data protection law. To that effect, it was made general considerations regarding the concept of video surveillance, what is its regimen, in a way that it may be distinguishable from Steve Mann's definition of sousveillance, and what are the associated obligations in order to better understand the concept's essence. The application of the existent laws on personal data protection to images processing by natural persons has been analysed taking into account the Directive 95/46/CE, the LPD and the General Regulation. From this analysis it is concluded that the regimen from 1995 to 1998 is out of touch with reality creating an absence of legal shielding in the personal data protection law, a flaw that doesn't exist because compensated by the right to image as a right to personality, that anyway reveals the inability of the Portuguese legislator to face the new technological challenges. It is urgent to legislate. A contrary interpretation will evidence the unconstitutionality of several rules on the LPD due to the obligations natural persons are bound to that violate the right to the freedom of speech and information, which would be inadequate and disproportionate. Considering the recently approved General Regulation and in the case it becomes the final version, the use for natural person of video surveillance of private spaces, Google Glass (in public and private places) and other similar gadgets used to recreational purposes, as well as social networks are subject to its regulation only if the images are shared without limits or existing commercial purposes. Video surveillance of public spaces in all situations is subject to General Regulation provisions.

A vinculação das sociedades por quotas nas situações de gerência plural e as limitações constantes do pacto social: análise dos institutos jurídicos e o sentido das decisões judiciais

Relatório de atividade profissional de mestrado em Direito dos Contratos e da Empresa

Coordinación socio-política. Redes de influencia y estructuras de poder en CórdobaSocio-political coordination. Influence Networks and power structures in Córdoba.

Los mecanismos de producción y reproducción de la influencia política es una importante área de estudio de la ciencia política en las últimas décadas. En la misma se han disputado diferentes teorías, desde las que plantean la influencia predominante de grupos de poder y sectores corporativos tanto en las decisiones del estado como en las no decisiones, hasta los que plantean que existe la puja de diferentes intereses dentro del Estado pero que no existe ningún grupo predominante. El análisis de redes (network analysis) permite estudiar este objeto mediante la observación de la estructura de relaciones de los actores influyentes dentro de la política provincial. En esta area de estudio, este proyecto propone estudiar de qué manera se produce y reproduce la influencia política en la Provincia de Córdoba.Las hipótesis que plantea el proyecto son las siguientes: H1- La estructura del poder socio-político provincial adquiere una configuración reticular en la que existe un núcleo de actores que representan intereses tradicionales organizados y permite un escaso acceso de nuevas organizaciones que defienden intereses sociales difusos. H2- En el proceso de influencia sociopolítica provincial operan mecanismos de influencia interpersonales directos e indirectos (Brokerage) que permiten a los actores acceder e influir en los decisores públicos. H3- En el proceso de influencia socio-política interviene una diversidad de recursos de poder que los actores utilizan para influir las políticas públicas. Para esto se propone como objetivos del proyecto los siguientes: 1- Identificar y analizar la estructura de poder e influencia que subyace a la política provincial. 2- Analizar los intereses, actores y sectores incluidos y excluidos de la estructura de influencia política. 3- Analizar los mecanismos y recursos de producción y reproducción del poder y la influencia. 4- Analizar las áreas de política del estado provincial que resultan lugar de influencia de los actores y sectores que configuran la estructura de poder socio-política. 5- Analizar el sistema de decisión colectiva (policy domain) en dos áreas de política provincial. 6- Analizar los recursos que posibilitan a los actores ejercer poder e influencia en las áreas de políticas estudiadas. Para la verificación empírica de las hipótesis se realiza un diseño de investigación que incluye el mapeo y análisis de dos tipos de redes políticas diferentes, la "red de influencia en la política provincial" y la red de influencia en un "área de políticas públicas". La reconstrucción de las redes políticas se realizará mediante entrevistas semi-estructuradas a actores sociales y políticos en un muestreo no probabilístico de tipo "bola de nieve". La investigación pretende realizar un aporte a la comprensión de la coordinación política y, en tal sentido, espera alcanzar una adecuada descripción y comprensión de los procesos de influencia y de estructuración del poder en la Provincia de Córdoba.

How central and connected am I in my family? Bridging and bonding social capital in family configurations of young adults with psychiatric disorders

AIMS: This article explores the structures of relational resources that individuals with psychiatric disorders get from their family configurations using the concept of social capital. METHODS: The research is based on a sample of 54 individuals with psychiatric disorders and behavioural problems, and a comparison sample of 54 individuals without a clinical record matched to the clinical respondents for age and sex. Standard measures of social capital from social network methods are applied on family configurations of individuals from both samples. Differences are tested by variance analysis. RESULTS: Structures of family resources available to individuals with psychiatric disorders are distinct. Individuals with psychiatric disorders perceive themselves as less central in their family configurations and less connected to their family members. Their significant family members are perceived as less connected with each other. As a whole, their family configurations are smaller and do not include spouses or partners. Therefore bridging and bonding social capitals are not readily available for them. CONCLUSION: As family configurations of individuals with psychiatric disorders provide fewer relational resources than other families, they are not able to deal with social integration of individuals with psychiatric disorders on their own.

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

The Swiss Business Elite (1980-2000): How the Changing Composition of the Elite Explains the Decline of the Swiss Company Network

In this paper we analyse the decline of the Swiss corporate network between 1980 and 2000. We address the theoretical and methodological challenge of this transformation by the use of a combination of network analysis and multiple correspondence analysis (MCA). Based on a sample of top managers of the 110 largest Swiss companies in 1980 and 2000 we show that, beyond an adjustment to structural pressure, an explanation of the decline of the network has to include the strategies of the fractions of the business elites. We reveal that three factors contribute crucially to the decline of the Swiss corporate network: the managerialization of industrial leaders, the marginalization of law degree holders and the influx of hardly connected foreign managers.

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Finite-size scaling analysis of the avalanches in the three-dimensional Gaussian random-field Ising model with metastable dynamics

A numerical study is presented of the third-dimensional Gaussian random-field Ising model at T=0 driven by an external field. Standard synchronous relaxation dynamics is employed to obtain the magnetization versus field hysteresis loops. The focus is on the analysis of the number and size distribution of the magnetization avalanches. They are classified as being nonspanning, one-dimensional-spanning, two-dimensional-spanning, or three-dimensional-spanning depending on whether or not they span the whole lattice in different space directions. Moreover, finite-size scaling analysis enables identification of two different types of nonspanning avalanches (critical and noncritical) and two different types of three-dimensional-spanning avalanches (critical and subcritical), whose numbers increase with L as a power law with different exponents. We conclude by giving a scenario for avalanche behavior in the thermodynamic limit.

Kinetics of martensitic transitions in Cu-Al-Mn under thermal cycling: Analysis at multiple length scales

In this paper we study the evolution of the kinetic features of the martensitic transition in a Cu-Al-Mn single crystal under thermal cycling. The use of several experimental techniques including optical microscopy, calorimetry, and acoustic emission, has enabled us to perform an analysis at multiple scales. In particular, we have focused on the analysis of avalanche events (associated with the nucleation and growth of martensitic domains), which occur during the transition. There are significant differences between the kinetics at large and small length scales. On the one hand, at small length scales, small avalanche events tend to sum to give new larger events in subsequent loops. On the other hand, at large length scales the large domains tend to split into smaller ones on thermal cycling. We suggest that such different behavior is the necessary ingredient that leads the system to the final critical state corresponding to a power-law distribution of avalanches.

Firm's network capability and innovation performance: evidences from China hi-tech industry

ABSTRACT : A firm's competitive advantage can arise from internal resources as well as from an interfirm network. -This dissertation investigates the competitive advantage of a firm involved in an innovation network by integrating strategic management theory and social network theory. It develops theory and provides empirical evidence that illustrates how a networked firm enables the network value and appropriates this value in an optimal way according to its strategic purpose. The four inter-related essays in this dissertation provide a framework that sheds light on the extraction of value from an innovation network by managing and designing the network in a proactive manner. The first essay reviews research in social network theory and knowledge transfer management, and identifies the crucial factors of innovation network configuration for a firm's learning performance or innovation output. The findings suggest that network structure, network relationship, and network position all impact on a firm's performance. Although the previous literature indicates that there are disagreements about the impact of dense or spare structure, as well as strong or weak ties, case evidence from Chinese software companies reveals that dense and strong connections with partners are positively associated with firms' performance. The second essay is a theoretical essay that illustrates the limitations of social network theory for explaining the source of network value and offers a new theoretical model that applies resource-based view to network environments. It suggests that network configurations, such as network structure, network relationship and network position, can be considered important network resources. In addition, this essay introduces the concept of network capability, and suggests that four types of network capabilities play an important role in unlocking the potential value of network resources and determining the distribution of network rents between partners. This essay also highlights the contingent effects of network capability on a firm's innovation output, and explains how the different impacts of network capability depend on a firm's strategic choices. This new theoretical model has been pre-tested with a case study of China software industry, which enhances the internal validity of this theory. The third essay addresses the questions of what impact network capability has on firm innovation performance and what are the antecedent factors of network capability. This essay employs a structural equation modelling methodology that uses a sample of 211 Chinese Hi-tech firms. It develops a measurement of network capability and reveals that networked firms deal with cooperation between, and coordination with partners on different levels according to their levels of network capability. The empirical results also suggests that IT maturity, the openness of culture, management system involved, and experience with network activities are antecedents of network capabilities. Furthermore, the two-group analysis of the role of international partner(s) shows that when there is a culture and norm gap between foreign partners, a firm must mobilize more resources and effort to improve its performance with respect to its innovation network. The fourth essay addresses the way in which network capabilities influence firm innovation performance. By using hierarchical multiple regression with data from Chinese Hi-tech firms, the findings suggest that there is a significant partial mediating effect of knowledge transfer on the relationships between network capabilities and innovation performance. The findings also reveal that the impacts of network capabilities divert with the environment and strategic decision the firm has made: exploration or exploitation. Network constructing capability provides a greater positive impact on and yields more contributions to innovation performance than does network operating capability in an exploration network. Network operating capability is more important than network constructing capability for innovative firms in an exploitation network. Therefore, these findings highlight that the firm can shape the innovation network proactively for better benefits, but when it does so, it should adjust its focus and change its efforts in accordance with its innovation purposes or strategic orientation.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.