Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

O desenvolvimento do pensamento abstrato através de game-based learning e do Scratch

Relatório de estágio de mestrado em Ensino de Informática

New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking

During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.

Estrategias estadístico-computacionales avanzadas para análisis de expresión de proteínas/genes en cáncer. Advanced statistical and computational strategies for protein/gene expression analysis in cancer.

El objetivo de este proyecto, enmarcado en el área de metodología de análisis en bioingeniería-biotecnología aplicadas al estudio del cancer, es el análisis y caracterización a través modelos estadísticos con efectos mixtos y técnicas de aprendizaje automático, de perfiles de expresión de proteínas y genes de las vías metabolicas asociadas a progresión tumoral. Dicho estudio se llevará a cabo mediante la utilización de tecnologías de alto rendimiento. Las mismas permiten evaluar miles de genes/proteínas en forma simultánea, generando así una gran cantidad de datos de expresión. Se hipotetiza que para un análisis e interpretación de la información subyacente, caracterizada por su abundancia y complejidad, podría realizarse mediante técnicas estadístico-computacionales eficientes en el contexto de modelos mixtos y técnias de aprendizaje automático. Para que el análisis sea efectivo es necesario contemplar los efectos ocasionados por los diferentes factores experimentales ajenos al fenómeno biológico bajo estudio. Estos efectos pueden enmascarar la información subycente y así perder informacion relavante en el contexto de progresión tumoral. La identificación de estos efectos permitirá obtener, eficientemente, los perfiles de expresión molecular que podrían permitir el desarrollo de métodos de diagnóstico basados en ellos. Con este trabajo se espera poner a disposición de investigadores de nuestro medio, herramientas y procedimientos de análisis que maximicen la eficiencia en el uso de los recursos asignados a la masiva captura de datos genómicos/proteómicos que permitan extraer información biológica relevante pertinente al análisis, clasificación o predicción de cáncer, el diseño de tratamientos y terapias específicos y el mejoramiento de los métodos de detección como así tambien aportar al entendimieto de la progresión tumoral mediante análisis computacional intensivo.

Flame simulation in rotary kilns using computational fluid dynamics

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2011

Variations and application conditions of the data type "Image" : the foundation of computational visualistics

Visualistics, computer science, picture syntax, picture semantics, picture pragmatics, interactive pictures

Analysis of complex microwave structures using suitable computational electromagnetic techniques

Complex Microwave Structures Wake Field Computatation PETRA III Generalized Multipole Technique Antenna Antennen Wakefelder Berechnung

Forearm surface EMG signals recognition and muscoloskeletal system dynamics identification using intelligent computational methods

Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods

Optimization of radial jets mixing in cross-flow of combustion chambers using computational fluid dynamics

Cross-Flow, Radial Jets Mixing, Temperature Homogenization, Optimization, Combustion Chamber, CFD

Computational methods for model reduction of large-scale sparse structured descriptor systems

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015

A Grid Supercomputing Enviroment for High Demand Computational Applications

Despite the huge increase in processor and interprocessor network performace, many computational problems remain unsolved due to lack of some critical resources such as floating point sustained performance, memory bandwidth, etc... Examples of these problems are found in areas of climate research, biology, astrophysics, high energy physics (montecarlo simulations) and artificial intelligence, among others. For some of these problems, computing resources of a single supercomputing facility can be 1 or 2 orders of magnitude apart from the resources needed to solve some them. Supercomputer centers have to face an increasing demand on processing performance, with the direct consequence of an increasing number of processors and systems, resulting in a more difficult administration of HPC resources and the need for more physical space, higher electrical power consumption and improved air conditioning, among other problems. Some of the previous problems can´t be easily solved, so grid computing, intended as a technology enabling the addition and consolidation of computing power, can help in solving large scale supercomputing problems. In this document, we describe how 2 supercomputing facilities in Spain joined their resources to solve a problem of this kind. The objectives of this experience were, among others, to demonstrate that such a cooperation can enable the solution of bigger dimension problems and to measure the efficiency that could be achieved. In this document we show some preliminary results of this experience and to what extend these objectives were achieved.

Computational explorations in Thompson's group F

Here we describe the results of some computational explorations in Thompson's group F. We describe experiments to estimate the cogrowth of F with respect to its standard finite generating set, designed to address the subtle and difficult question whether or not Thompson's group is amenable. We also describe experiments to estimate the exponential growth rate of F and the rate of escape of symmetric random walks with respect to the standard generating set.

Transforming scientific information with everyday thinking: A social representations perspective

Cette thèse examine la circulation et l'intégration des informations scientifiques dans la pensée quotidienne d'après la théorie des représentations sociales (TRS). En tant qu'alternative aux approches traditionnelles de la communication de la science, les transformations survenant entre le discours scientifique et le discours de sens commun sont considérées comme adaptatives. Deux études sur la circulation des informations dans les media (études 1 et 2) montrent des variations dans les thèmes de discours exposés aux profanes, et parmi les discours de ceux-ci, en fonction de différentes sources. Ensuite, le processus d'ancrage dans le positionnement préalable envers la science est étudié, pour l'explication qu'il fournit de la réception et de la transmission d'informations scientifiques dans le sens commun. Les effets d'ancrage dans les attitudes et croyances préexistants sont reportés dans différents contextes de circulation des informations scientifiques (études 3 à 7), incluant des études de type corrélationnel, experimental et de terrain. Globalement, cette thèse procure des arguments en faveur de la pertinence de la TRS pour la recherche sur la communication de la science, et suggère des développements théoriques et méthodologiques pour ces deux domaines de recherche. Drawing on the social representations theory (SRT), this thesis examines the circulation and integration of scientific information into everyday thinking. As an alternative to the traditional approaches of science communication, it considers transformations between scientific and common-sense discourses as adaptive. Two studies, focused on the spreading of information into the media (Studies 1 and 2), show variations in the themes of discourses introduced to laypersons and in the themes among laypersons' discourses, according to different sources. Anchoring in prior positioning toward science is then studied for the explanation it provides on the reception and transmission of scientific information into common sense. Anchoring effects in prior attitudes and beliefs are reported in different contexts of circulation of scientific information (Studies 3 to 7) by using results from correlational, field, and experimental studies. Overall, this thesis provides arguments for the relevance of SRT in science communication research and suggests theoretical and methodological developments for both domains of research.

Raising the Level of Moral Thinking among Managers Will Not Help. Kohlberg's Conventionality and Systemic Ethical Flaws in Business

Business ethicists often assume that unethical behavior arises when individuals deviate from the norms and responsibilities that are institutionalized to frame economic activities. People's greed motivates them to violate the rules of the game. In Kohlberg's terms, it is assumed that such actors make decisions in a preconventional way and act opportunistically. In this article, we propose an alternative interpretation of deviant behavior, arguing that such behavior does not result from a lack of conventional moral guidance but rather from the fact that characteristics attributed to preconventional morality by Kohlberg - the purely incentive and punishment driven opportunistic morality - have become the conventionalized morality. The prevailing norms that economic actors have internalized as their yardstick are those of the preconventional Homo economicus. Not the deviation from, but the compliance with the rules of the game explains many forms of harmful and illegal decisions made in corporations.

Optimized venous return with a self-expanding cannula: from computational fluid dynamics to clinical application.

The Smart canula concept allows for collapsed cannula insertion, and self-expansion within a vein of the body. (A) Computational fluid dynamics, and (B) bovine experiments (76+/-3.8 kg) were performed for comparative analyses, prior to (C) the first clinical application. For an 18F access, a given flow of 4 l/min (A) resulted in a pressure drop of 49 mmHg for smart cannula versus 140 mmHg for control. The corresponding Reynolds numbers are 680 versus 1170, respectively. (B) For an access of 28F, the maximal flow for smart cannula was 5.8+/-0.5 l/min versus 4.0+/-0.1 l/min for standard (P<0.0001), for 24F 5.5+/-0.6 l/min versus 3.2+/-0.4 l/min (P<0.0001), and for 20F 4.1+/-0.3 l/min versus 1.6+/-0.3 l/min (P<0.0001). The flow obtained with the smart cannula was 270+/-45% (20F), 172+/-26% (24F), and 134+/-13% (28F) of standard (one-way ANOVA, P=0.014). (C) First clinical application (1.42 m2) with a smart cannula showed 3.55 l/min (100% predicted) without additional fluids. All three assessment steps confirm the superior performance of the smart cannula design.