On Solution Sets of Information Inequalities

We investigate solution sets of a special kind of linear inequality systems. In particular, we derive characterizations of these sets in terms of minimal solution sets. The studied inequalities emerge as information inequalities in the context of Bayesian networks. This allows to deduce important properties of Bayesian networks, which is important within causal inference.

Semi-algebraic methods for symbolic analysis of complex reaction networks

The identification of chemical mechanism that can exhibit oscillatory phenomena in reaction networks are currently of intense interest. In particular, the parametric question of the existence of Hopf bifurcations has gained increasing popularity due to its relation to the oscillatory behavior around the fixed points. However, the detection of oscillations in high-dimensional systems and systems with constraints by the available symbolic methods has proven to be difficult. The development of new efficient methods are therefore required to tackle the complexity caused by the high-dimensionality and non-linearity of these systems. In this thesis, we mainly present efficient algorithmic methods to detect Hopf bifurcation fixed points in (bio)-chemical reaction networks with symbolic rate constants, thereby yielding information about their oscillatory behavior of the networks. The methods use the representations of the systems on convex coordinates that arise from stoichiometric network analysis. One of the methods called HoCoQ reduces the problem of determining the existence of Hopf bifurcation fixed points to a first-order formula over the ordered field of the reals that can then be solved using computational-logic packages. The second method called HoCaT uses ideas from tropical geometry to formulate a more efficient method that is incomplete in theory but worked very well for the attempted high-dimensional models involving more than 20 chemical species. The instability of reaction networks may lead to the oscillatory behaviour. Therefore, we investigate some criterions for their stability using convex coordinates and quantifier elimination techniques. We also study Muldowney's extension of the classical Bendixson-Dulac criterion for excluding periodic orbits to higher dimensions for polynomial vector fields and we discuss the use of simple conservation constraints and the use of parametric constraints for describing simple convex polytopes on which periodic orbits can be excluded by Muldowney's criteria. All developed algorithms have been integrated into a common software framework called PoCaB (platform to explore bio- chemical reaction networks by algebraic methods) allowing for automated computation workflows from the problem descriptions. PoCaB also contains a database for the algebraic entities computed from the models of chemical reaction networks.

Relatedness in Evidence Networks

Einhergehend mit der Entwicklung und zunehmenden Verfügbarkeit des Internets hat sich die Art der Informationsbereitstellung und der Informationsbeschaffung deutlich geändert. Die einstmalige Trennung zwischen Publizist und Konsument wird durch kollaborative Anwendungen des sogenannten Web 2.0 aufgehoben, wo jeder Teilnehmer gleichsam Informationen bereitstellen und konsumieren kann. Zudem können Einträge anderer Teilnehmer erweitert, kommentiert oder diskutiert werden. Mit dem Social Web treten schließlich die sozialen Beziehungen und Interaktionen der Teilnehmer in den Vordergrund. Dank mobiler Endgeräte können zu jeder Zeit und an nahezu jedem Ort Nachrichten verschickt und gelesen werden, neue Bekannschaften gemacht oder der aktuelle Status dem virtuellen Freundeskreis mitgeteilt werden. Mit jeder Aktivität innerhalb einer solchen Applikation setzt sich ein Teilnehmer in Beziehung zu Datenobjekten und/oder anderen Teilnehmern. Dies kann explizit geschehen, indem z.B. ein Artikel geschrieben wird und per E-Mail an Freunde verschickt wird. Beziehungen zwischen Datenobjekten und Nutzern fallen aber auch implizit an, wenn z.B. die Profilseite eines anderen Teilnehmers aufgerufen wird oder wenn verschiedene Teilnehmer einen Artikel ähnlich bewerten. Im Rahmen dieser Arbeit wird ein formaler Ansatz zur Analyse und Nutzbarmachung von Beziehungsstrukturen entwickelt, welcher auf solchen expliziten und impliziten Datenspuren aufbaut. In einem ersten Teil widmet sich diese Arbeit der Analyse von Beziehungen zwischen Nutzern in Applikationen des Social Web unter Anwendung von Methoden der sozialen Netzwerkanalyse. Innerhalb einer typischen sozialen Webanwendung haben Nutzer verschiedene Möglichkeiten zu interagieren. Aus jedem Interaktionsmuster werden Beziehungsstrukturen zwischen Nutzern abgeleitet. Der Vorteil der impliziten Nutzer-Interaktionen besteht darin, dass diese häufig vorkommen und quasi nebenbei im Betrieb des Systems abfallen. Jedoch ist anzunehmen, dass eine explizit angegebene Freundschaftsbeziehung eine stärkere Aussagekraft hat, als entsprechende implizite Interaktionen. Ein erster Schwerpunkt dieser Arbeit ist entsprechend der Vergleich verschiedener Beziehungsstrukturen innerhalb einer sozialen Webanwendung. Der zweite Teil dieser Arbeit widmet sich der Analyse eines der weit verbreitetsten Profil-Attributen von Nutzern in sozialen Webanwendungen, dem Vornamen. Hierbei finden die im ersten Teil vorgestellten Verfahren und Analysen Anwendung, d.h. es werden Beziehungsnetzwerke für Namen aus Daten von sozialen Webanwendungen gewonnen und mit Methoden der sozialen Netzwerkanalyse untersucht. Mithilfe externer Beschreibungen von Vornamen werden semantische Ähnlichkeiten zwischen Namen bestimmt und mit jeweiligen strukturellen Ähnlichkeiten in den verschiedenen Beziehungsnetzwerken verglichen. Die Bestimmung von ähnlichen Namen entspricht in einer praktischen Anwendung der Suche von werdenden Eltern nach einem passenden Vornamen. Die Ergebnisse zu der Analyse von Namensbeziehungen sind die Grundlage für die Implementierung der Namenssuchmaschine Nameling, welche im Rahmen dieser Arbeit entwickelt wurde. Mehr als 35.000 Nutzer griffen innerhalb der ersten sechs Monate nach Inbetriebnahme auf Nameling zu. Die hierbei anfallenden Nutzungsdaten wiederum geben Aufschluss über individuelle Vornamenspräferenzen der Anwender. Im Rahmen dieser Arbeit werden diese Nutzungsdaten vorgestellt und zur Bestimmung sowie Bewertung von personalisierten Vornamensempfehlungen verwendet. Abschließend werden Ansätze zur Diversifizierung von personalisierten Vornamensempfehlungen vorgestellt, welche statische Beziehungsnetzwerke für Namen mit den individuellen Nutzungsdaten verknüpft.

Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks

Sigmoid type belief networks, a class of probabilistic neural networks, provide a natural framework for compactly representing probabilistic information in a variety of unsupervised and supervised learning problems. Often the parameters used in these networks need to be learned from examples. Unfortunately, estimating the parameters via exact probabilistic calculations (i.e, the EM-algorithm) is intractable even for networks with fairly small numbers of hidden units. We propose to avoid the infeasibility of the E step by bounding likelihoods instead of computing them exactly. We introduce extended and complementary representations for these networks and show that the estimation of the network parameters can be made fast (reduced to quadratic optimization) by performing the estimation in either of the alternative domains. The complementary networks can be used for continuous density estimation as well.

Belief Propagation and Revision in Networks with Loops

Local belief propagation rules of the sort proposed by Pearl(1988) are guaranteed to converge to the optimal beliefs for singly connected networks. Recently, a number of researchers have empirically demonstrated good performance of these same algorithms on networks with loops, but a theoretical understanding of this performance has yet to be achieved. Here we lay the foundation for an understanding of belief propagation in networks with loops. For networks with a single loop, we derive ananalytical relationship between the steady state beliefs in the loopy network and the true posterior probability. Using this relationship we show a category of networks for which the MAP estimate obtained by belief update and by belief revision can be proven to be optimal (although the beliefs will be incorrect). We show how nodes can use local information in the messages they receive in order to correct the steady state beliefs. Furthermore we prove that for all networks with a single loop, the MAP estimate obtained by belief revisionat convergence is guaranteed to give the globally optimal sequence of states. The result is independent of the length of the cycle and the size of the statespace. For networks with multiple loops, we introduce the concept of a "balanced network" and show simulati.

Multilevel multitrait-multimethod model: application to the measurement of egocentered social networks

Our goal in this paper is to assess reliability and validity of egocentered network data using multilevel analysis (Muthen, 1989, Hox, 1993) under the multitrait-multimethod approach. The confirmatory factor analysis model for multitrait-multimethod data (Werts & Linn, 1970; Andrews, 1984) is used for our analyses. In this study we reanalyse a part of data of another study (Kogovšek et al., 2002) done on a representative sample of the inhabitants of Ljubljana. The traits used in our article are the name interpreters. We consider egocentered network data as hierarchical; therefore a multilevel analysis is required. We use Muthen's partial maximum likelihood approach, called pseudobalanced solution (Muthen, 1989, 1990, 1994) which produces estimations close to maximum likelihood for large ego sample sizes (Hox & Mass, 2001). Several analyses will be done in order to compare this multilevel analysis to classic methods of analysis such as the ones made in Kogovšek et al. (2002), who analysed the data only at group (ego) level considering averages of all alters within the ego. We show that some of the results obtained by classic methods are biased and that multilevel analysis provides more detailed information that much enriches the interpretation of reliability and validity of hierarchical data. Within and between-ego reliabilities and validities and other related quality measures are defined, computed and interpreted

Adding new components to the knowledge plane GMPLS over WDM networks

A recent study defines a new network plane: the knowledge plane. The incorporation of the knowledge plane over the network allows having more accurate information of the current and future network states. In this paper, the introduction and management of the network reliability information in the knowledge plane is proposed in order to improve the quality of service with protection routing algorithms in GMPLS over WDM networks. Different experiments prove the efficiency and scalability of the proposed scheme in terms of the percentage of resources used to protect the network

W3233 -- Networks and Complexity in Social Systems (Collective Dynamics Group ISERP -- Columbia University) Course Syllabus

The Networks and Complexity in Social Systems course commences with an overview of the nascent field of complex networks, dividing it into three related but distinct strands: Statistical description of large scale networks, viewed as static objects; the dynamic evolution of networks, where now the structure of the network is understood in terms of a growth process; and dynamical processes that take place on fixed networks; that is, "networked dynamical systems". (A fourth area of potential research ties all the previous three strands together under the rubric of co-evolution of networks and dynamics, but very little research has been done in this vein and so it is omitted.) The remainder of the course treats each of the three strands in greater detail, introducing technical knowledge as required, summarizing the research papers that have introduced the principal ideas, and pointing out directions for future development. With regard to networked dynamical systems, the course treats in detail the more specific topic of information propagation in networks, in part because this topic is of great relevance to social science, and in part because it has received the most attention in the literature to date.

Provision of information and documentation on education in the Austrian Federal Ministry of Education. 'Provisión de información y documentación en educación en el Ministerio Federal de Educación de Austria'.

En un país pequeño como Austria es necesario recibir estímulo del exterior a nivel europeo respectivamente internacional para que los responsables vean lo útil que son las iniciativas nacionales en el campo de documentación educativa. Trabajar de manera comparativa en un contexto europeo ayuda a comprender mejor su propia posición y sirve de base para tomar decisiones y para desarrollar nuevos proyectos en el futuro. Ha crecido el interés en utilizar la información y documentación educativa durante las últimas décadas. Actualmente los ministros de educación ya no pueden seguir su trabajo sin recurrir a todos aquellos datos que han sido recopilados en los respectivos países y presentados a través de las redes europeas como EURYDICE, la red europea de información en educación (htttp://www.eurydice.org).

Social Networks and Small World phenomena

Social Networking tools like Facebook yield recognisable small world phenomena, that is particular kinds of social graphs that facilitate particular kinds of interaction and information exchange.

Data-Driven Text Generation using Neural Networks & Provenance is Complicated and Boring — Is there a solution?

Title: Data-Driven Text Generation using Neural Networks Speaker: Pavlos Vougiouklis, University of Southampton Abstract: Recent work on neural networks shows their great potential at tackling a wide variety of Natural Language Processing (NLP) tasks. This talk will focus on the Natural Language Generation (NLG) problem and, more specifically, on the extend to which neural network language models could be employed for context-sensitive and data-driven text generation. In addition, a neural network architecture for response generation in social media along with the training methods that enable it to capture contextual information and effectively participate in public conversations will be discussed. Speaker Bio: Pavlos Vougiouklis obtained his 5-year Diploma in Electrical and Computer Engineering from the Aristotle University of Thessaloniki in 2013. He was awarded an MSc degree in Software Engineering from the University of Southampton in 2014. In 2015, he joined the Web and Internet Science (WAIS) research group of the University of Southampton and he is currently working towards the acquisition of his PhD degree in the field of Neural Network Approaches for Natural Language Processing. Title: Provenance is Complicated and Boring — Is there a solution? Speaker: Darren Richardson, University of Southampton Abstract: Paper trails, auditing, and accountability — arguably not the sexiest terms in computer science. But then you discover that you've possibly been eating horse-meat, and the importance of provenance becomes almost palpable. Having accepted that we should be creating provenance-enabled systems, the challenge of then communicating that provenance to casual users is not trivial: users should not have to have a detailed working knowledge of your system, and they certainly shouldn't be expected to understand the data model. So how, then, do you give users an insight into the provenance, without having to build a bespoke system for each and every different provenance installation? Speaker Bio: Darren is a final year Computer Science PhD student. He completed his undergraduate degree in Electronic Engineering at Southampton in 2012.

Information externalities and export trade duration at the firm level

Recent empirical work emphasizes the importance of the extensive margin of trade (new exporters, new export activities) for long run export growth. In this context, understanding the determinants of duration of new exporters is key for underpinning the dynamics of exports growth. As new exporters tend to show low survival rates, identifying the determinants of export duration is highly relevant for academic and policy purposes. In this paper, we explore whether information externalities arising from different levels of spatial interaction allow new exporters to increase the duration of their trade activities. For this, we use transaction level data on Colombian exports between 2004 and 2011. Results show that export networks, understood as the agglomeration of exporting firms at different spatial levels, reduce the risk of dropping out from exporting and that this effect is stronger the more similar are export activities carried out by firms

Automatic diagnosis of voltage disturbances in power distribution networks

This thesis proposes a framework for identifying the root-cause of a voltage disturbance, as well as, its source location (upstream/downstream) from the monitoring place. The framework works with three-phase voltage and current waveforms collected in radial distribution networks without distributed generation. Real-world and synthetic waveforms are used to test it. The framework involves features that are conceived based on electrical principles, and assuming some hypothesis on the analyzed phenomena. Features considered are based on waveforms and timestamp information. Multivariate analysis of variance and rule induction algorithms are applied to assess the amount of meaningful information explained by each feature, according to the root-cause of the disturbance and its source location. The obtained classification rates show that the proposed framework could be used for automatic diagnosis of voltage disturbances collected in radial distribution networks. Furthermore, the diagnostic results can be subsequently used for supporting power network operation, maintenance and planning.

Enhanced fault recovery methods for protected traffic services in GMPLS networks

Les noves tecnologies a la xarxa ens permeten transportar, cada cop més, grans volums d' informació i trànsit de xarxa amb diferents nivells de prioritat. En aquest escenari, on s'ofereix una millor qualitat de servei, les conseqüències d'una fallada en un enllaç o en un node esdevenen més importants. Multiprotocol Lavel Switching (MPLS), juntament amb l'extensió a MPLS generalitzat (GMPLS), proporcionen mecanismes ràpids de recuperació de fallada establint camins, Label Switch Path (LSPs), redundants per ser utilitzats com a camins alternatius. En cas de fallada podrem utilitzar aquests camins per redireccionar el trànsit. El principal objectiu d'aquesta tesi ha estat millorar alguns dels actuals mecanismes de recuperació de fallades MPLS/GMPLS, amb l'objectiu de suportar els requeriments de protecció dels serveis proporcionats per la nova Internet. Per tal de fer aquesta avaluació s'han tingut en compte alguns paràmetres de qualitat de protecció com els temps de recuperació de fallada, les pèrdues de paquets o el consum de recursos. En aquesta tesi presentem una completa revisió i comparació dels principals mètodes de recuperació de fallada basats en MPLS. Aquest anàlisi inclou els mètodes de protecció del camí (backups globals, backups inversos i protecció 1+1), els mètodes de protecció locals i els mètodes de protecció de segments. També s'ha tingut en compte l'extensió d'aquests mecanismes a les xarxes òptiques mitjançant el pla de control proporcionat per GMPLS. En una primera fase d'aquest treball, cada mètode de recuperació de fallades és analitzat sense tenir en compte restriccions de recursos o de topologia. Aquest anàlisi ens dóna una primera classificació dels millors mecanismes de protecció en termes de pèrdues de paquets i temps de recuperació. Aquest primer anàlisi no és aplicable a xarxes reals. Per tal de tenir en compte aquest nou escenari, en una segona fase, s'analitzen els algorismes d'encaminament on sí tindrem en compte aquestes limitacions i restriccions de la xarxa. Es presenten alguns dels principals algorismes d'encaminament amb qualitat de servei i alguna de les principals propostes d'encaminament per xarxes MPLS. La majoria dels actual algorismes d'encaminament no tenen en compte l'establiment de rutes alternatives o utilitzen els mateixos objectius per seleccionar els camins de treball i els de protecció. Per millorar el nivell de protecció introduïm i formalitzem dos nous conceptes: la Probabilitat de fallada de la xarxa i l'Impacte de fallada. Un anàlisi de la xarxa a nivell físic proporciona un primer element per avaluar el nivell de protecció en termes de fiabilitat i disponibilitat de la xarxa. Formalitzem l'impacte d'una fallada, quant a la degradació de la qualitat de servei (en termes de retard i pèrdues de paquets). Expliquem la nostra proposta per reduir la probabilitat de fallada i l'impacte de fallada. Per últim fem una nova definició i classificació dels serveis de xarxa segons els valors requerits de probabilitat de fallada i impacte. Un dels aspectes que destaquem dels resultats d'aquesta tesi és que els mecanismes de protecció global del camí maximitzen la fiabilitat de la xarxa, mentre que les tècniques de protecció local o de segments de xarxa minimitzen l'impacte de fallada. Per tant podem assolir mínim impacte i màxima fiabilitat aplicant protecció local a tota la xarxa, però no és una proposta escalable en termes de consum de recursos. Nosaltres proposem un mecanisme intermig, aplicant protecció de segments combinat amb el nostre model d'avaluació de la probabilitat de fallada. Resumint, aquesta tesi presenta diversos mecanismes per l'anàlisi del nivell de protecció de la xarxa. Els resultats dels models i mecanismes proposats milloren la fiabilitat i minimitzen l'impacte d'una fallada en la xarxa.

Collaborative business networks evaluation of technological tools for decision support making

Nowadays, companies are living great difficulties on managing their business due to constant and unpredictable economic market fluctuations. Recent changes in market trends (such as the constant demand for new products and services, mass customization and the drastic reduction of delivery time) lead companies to adopt strategies of creating partnerships with other companies as a way to respond effectively to such difficult economical times. Collaborative Networks’ concept born by the consequence of companies could no longer consider their internal business processes’ management as sufficient and tend to seek for a collaborative approach with other partners for their critical processes. Information technologies (ICT) assumed a major role acting as “enablers” of these kinds of networks, enhancing information sharing and business process integration. Several new trends concerning ICT architectures have been created to support collaborative networks requirements, but still doesn’t exist a common platform to reduce the needed integration effort on virtual organizations. This study aims to investigate the current technological solutions available in the market which enhances the management of companies’ business processes (specially, Collaborative Planning). Finally, the research work ends with the presentation of a conceptual model to answer to the constraints evaluated.