Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa

Automated Machine Learning implementation framework in the banking sector

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsAutomated Machine Learning is a subject in the Machine Learning field, designed to give the possibility of Machine Learning use to non-expert users, it aroused from the lack of subject matter experts, trying to remove humans from these topic implementations. The advantages behind automated machine learning are leaning towards the removal of human implementation, fastening the machine learning deployment speed. The organizations will benefit from effective solutions benchmarking and validations. The use of an automated machine learning implementation framework can deeply transform an organization adding value to the business by freeing the subject matter experts of the low-level machine learning projects, letting them focus on high level projects. This will also help the organization reach new competence, customization, and decision-making levels in a higher analytical maturity level. This work pretends, firstly to investigate the impact and benefits automated machine learning implementation in the banking sector, and afterwards develop an implementation framework that could be used by banking institutions as a guideline for the automated machine learning implementation through their departments. The autoML advantages and benefits are evaluated regarding business value and competitive advantage and it is presented the implementation in a fictitious institution, considering all the need steps and the possible setbacks that could arise. Banking institutions, in their business have different business processes, and since most of them are old institutions, the main concerns are related with the automating their business process, improving their analytical maturity and sensibilizing their workforce to the benefits of the implementation of new forms of work. To proceed to a successful implementation plan should be known the institution particularities, adapt to them and ensured the sensibilization of the workforce and management to the investments that need to be made and the changes in all levels of their organizational work that will come from that, that will lead to a lot of facilities in everyone’s daily work

Design and Optimization of Power Delivery and Distribution Systems Using Evolutionary Computation Techniques

Nowadays computing platforms consist of a very large number of components that require to be supplied with diferent voltage levels and power requirements. Even a very small platform, like a handheld computer, may contain more than twenty diferent loads and voltage regulators. The power delivery designers of these systems are required to provide, in a very short time, the right power architecture that optimizes the performance, meets electrical specifications plus cost and size targets. The appropriate selection of the architecture and converters directly defines the performance of a given solution. Therefore, the designer needs to be able to evaluate a significant number of options in order to know with good certainty whether the selected solutions meet the size, energy eficiency and cost targets. The design dificulties of selecting the right solution arise due to the wide range of power conversion products provided by diferent manufacturers. These products range from discrete components (to build converters) to complete power conversion modules that employ diferent manufacturing technologies. Consequently, in most cases it is not possible to analyze all the alternatives (combinations of power architectures and converters) that can be built. The designer has to select a limited number of converters in order to simplify the analysis. In this thesis, in order to overcome the mentioned dificulties, a new design methodology for power supply systems is proposed. This methodology integrates evolutionary computation techniques in order to make possible analyzing a large number of possibilities. This exhaustive analysis helps the designer to quickly define a set of feasible solutions and select the best trade-off in performance according to each application. The proposed approach consists of two key steps, one for the automatic generation of architectures and other for the optimized selection of components. In this thesis are detailed the implementation of these two steps. The usefulness of the methodology is corroborated by contrasting the results using real problems and experiments designed to test the limits of the algorithms

Design of power system stabilizers using evolutionary algorithms

Includes synopsis.Includes bibliographical references (leaves 151-159).Includes bibliographical references (leaves 125-134).Over the past decades, the issue of low frequency oscillations has been of major concern to power system engineers. These oscillations range from 0.1 to 3Hz and tend to be poorly damped especially in systems equipped with high gain fast acting AVRs and highly interconnected networks. If these oscillations are not adequately damped, they may sustain and grow, which may lead to system separation and loss of power transfer

Citations: Indicators of Quality? The Impact Fallacy

We argue that citation is a composed indicator: short-term citations can be considered as currency at the research front, whereas long-term citations can contribute to the codification of knowledge claims into concept symbols. Knowledge claims at the research front are more likely to be transitory and are therefore problematic as indicators of quality. Citation impact studies focus on short-term citation, and therefore tend to measure not epistemic quality, but involvement in current discourses in which contributions are positioned by referencing. We explore this argument using three case studies: (1) citations of the journal Soziale Welt as an example of a venue that tends not to publish papers at a research front, unlike, for example, JACS; (2) Robert Merton as a concept symbol across theories of citation; and (3) the Multi-RPYS ("Multi-Referenced Publication Year Spectroscopy") of the journals Scientometrics, Gene, and Soziale Welt. We show empirically that the measurement of "quality" in terms of citations can further be qualified: short-term citation currency at the research front can be distinguished from longer-term processes of incorporation and codification of knowledge claims into bodies of knowledge. The recently introduced Multi-RPYS can be used to distinguish between short-term and long-term impacts.Comment: accepted for publication in Frontiers in Research Metrics and Analysis; doi: 10.3389/frma.2016.0000

Engineering humans : cultural history of the science and technology of human enhancement

This thesis investigates the technological imaginary of human enhancement: how it has been conceived historically and the scientific understanding that has shaped it. Human enhancement technologies have been prominent in popular culture narratives for a long time, but in the past twenty years they have moved out of science fiction to being an issue for serious discussion, in academic disciplines, political debate and the mass media.. Even so, the bioethical debate on enhancement, whether it is pharmacological means of improving cognition and morality or genetic engineering to create smarter people or other possibilities, is consistently centred on technologies that do not yet exist. The investigation is divided into three main areas: a chapter on eugenics, two chapters on cybernetics and the cyborg, and two chapters on transhumanism. All three areas of enhancement thinking have a corresponding understanding of and reference to evolutionary theory and the human as a category. Insofar as ‘enhancement’ is a vague and relative turn, the chapters show how each approach wrestles with how to formulate what is good and desirable. When this has inevitably proven difficult, the technologies themselves dictate what and how ‘enhancement’ comes about. Eugenics treats the human in terms of populations – as a species, but also in abstract categories such as nation and race. I follow the establishment of eugenics from the development of a statistical understanding of measuring human aptitude, with emphasis on the work of Francis Galton and the formulation of the regression to the mean. The following two chapters on cybernetics and the cyborg analyses how the metaphor of the body as machine has changed relative to what is meant by ‘machine’: associated with Cartesian dualism, cybernetics marked a shift in how we understand the term. Through a reading of the original formulation of the cyborg, I connect it to evolutionary adaptationism and a cybernetic ‘black box’ approach. The last two chapters look at a more recent approach to enhancement as a moral imperative, transhumanism. Since some transhumanists seek to ground themselves philosophically as the inheritors to Enlightenment humanism, the concept of ‘morphological freedom’ is central, representing an extension of humanistic principles of liberty brought into an age which privileges information over matter. The final chapter looks at how the privileging of information leads to a universal computational ontology, and I specifically look at the work of Ray Kurzweil, a prominent transhumanist, and how the computationalist narrative creates a teleological understanding of both human worth and evolution

Towards a Self-Manufacturing Rapid Prototyping Machine

Fused Filament Fabrication (FFF) is a layer manufacturing process which can manufacture highly complex components from CAD files using a polymer extruder. RepRap is an open-source project to produce a rapid prototyping machine which can manufacture its own parts using the FFF process. This thesis focuses on the mechanical design of the ‘RepRap printer’ and documents how it was conceived, developed, tested, and finally used to make a set of its own parts. Self-manufacture was demonstrated by assembling this set of parts into a working copy of the original machine. The child machine went on to demonstrate replication without degeneracy by successfully manufacturing one of its own parts. A part count analysis of the child machine, not including the fasteners it needed in its early development phase, identified a self-manufacturing ratio of 48%. This proportion is relatively low because the design adopts modularity and redundancy principles to encourage development. Should the machine’s design be adapted to fully demonstrate self-manufacture, this ratio could rise to 67% in the near future. To increase the ratio further, the machine needs three new tool heads to print resin, conductive alloy, and flexible polymer. These developments are achievable in the mid-future and could increase the self manufactured parts ratio to 94%. As this machine is the first version of the RepRap printer, these results are encouraging. Parts which the RepRap printer is unlikely to make until the far-future include some of the electronic components, motors, conductive cable, solenoids and a heating element. However, a 94% self-manufacturing ratio will qualify it as an assisted self-replicating machine. As with natural self-reproducing organisms, the printer will benefit from geometric growth and evolution. The author discusses how, by trading power, computing, feedstock and assembly for manufacturing capability with human beings, the RepRap printer may become a household item, offering a radical alternative to the way our society manufactures and consumes.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Molecular phylogenetic analysis: design and implementation of scalable and reliable algorithms and verification of phylogenetic properties

El término bioinformática tiene muchas acepciones, una gran parte referentes a la bioinformática molecular: el conjunto de métodos matemáticos, estadísticos y computacionales que tienen como objetivo dar solución a problemas biológicos, haciendo uso exclusivamente de las secuencias de ADN, ARN y proteínas y su información asociada. La filogenética es el área de la bioinformática encargada del estudio de la relación evolutiva entre organismos de la misma o distintas especies. Al igual que sucedía con la definición anterior, los trabajos realizados a lo largo de esta tesis se centran en la filogenética molecular: la rama de la filogenética que analiza las mutaciones hereditarias en secuencias biológicas (principalmente ADN) para establecer dicha relación evolutiva. El resultado de este análisis se plasma en un árbol evolutivo o filogenia. Una filogenia suele representarse como un árbol con raíz, normalmente binario, en el que las hojas simbolizan los organismos existentes actualmente y, la raíz, su ancestro común. Cada nodo interno representa una mutación que ha dado lugar a una división en la clasificación de los descendientes. Las filogenias se construyen mediante procesos de inferencia en base a la información disponible, que pertenece mayoritariamente a organismos existentes hoy en día. La complejidad de este problema se ha visto reflejada en la clasificación de la mayoría de métodos propuestos para su solución como NP-duros [1-3].El caso real de aplicación de esta tesis ha sido el ADN mitocondrial. Este tipo de secuencias biológicas es relevante debido a que tiene un alto índice de mutación, por lo que incluso filogenias de organismos muy cercanos evolutivamente proporcionan datos significativos para la comunidad biológica. Además, varias mutaciones del ADN mitocondrial humano se han relacionado directamente con enfermedad y patogenias, la mayoría mortales en individuos no natos o de corta edad. En la actualidad hay más de 30000 secuencias disponibles de ADN mitocondrial humano, lo que, además de su utilidad científica, ha permitido el análisis de rendimiento de nuestras contribuciones para datos masivos (Big Data). La reciente incorporación de la bioinformática en la categoría Big Data viene respaldada por la mejora de las técnicas de digitalización de secuencias biológicas que sucedió a principios del siglo 21 [4]. Este cambio aumentó drásticamente el número de secuencias disponibles. Por ejemplo, el número de secuencias de ADN mitocondrial humano pasó de duplicarse cada cuatro años, a hacerlo en menos de dos. Por ello, un gran número de métodos y herramientas usados hasta entonces han quedado obsoletos al no ser capaces de procesar eficientemente estos nuevos volúmenes de datos.Este es motivo por el que todas las aportaciones de esta tesis han sido desarrolladas para poder tratar grandes volúmenes de datos. La contribución principal de esta tesis es un framework que permite diseñar y ejecutar automáticamente flujos de trabajo para la inferencia filogenética: PhyloFlow [5-7]. Su creación fue promovida por el hecho de que la mayoría de sistemas de inferencia filogenética existentes tienen un flujo de trabajo fijo y no se pueden modificar ni las herramientas software que los componen ni sus parámetros. Esta decisión puede afectar negativamente a la precisión del resultado si el flujo del sistema o alguno de sus componentes no está adaptado a la información biológica que se va a utilizar como entrada. Por ello, PhyloFlow incorpora un proceso de configuración que permite seleccionar tanto cada uno de los procesos que formarán parte del sistema final, como las herramientas y métodos específicos y sus parámetros. Se han incluido consejos y opciones por defecto durante el proceso de configuración para facilitar su uso, sobre todo a usuarios nóveles. Además, nuestro framework permite la ejecución desatendida de los sistemas filogenéticos generados, tanto en ordenadores de sobremesa como en plataformas hardware (clusters, computación en la nube, etc.). Finalmente, se han evaluado las capacidades de PhyloFlow tanto en la reproducción de sistemas de inferencia filogenética publicados anteriormente como en la creación de sistemas orientados a problemas intensivos como el de inferencia del ADN mitocondrial humano. Los resultados muestran que nuestro framework no solo es capaz de realizar los retos planteados, sino que, en el caso de la replicación de sistemas, la posibilidad de configurar cada elemento que los componen mejora ampliamente su aplicabilidad.Durante la implementación de PhyloFlow descubrimos varias carencias importantes en algunas bibliotecas software actuales que dificultaron la integración y gestión de las herramientas filogenéticas. Por este motivo se decidió crear la primera biblioteca software en Python para estudios de filogenética molecular: MEvoLib [8]. Esta biblioteca ha sido diseñada para proveer una sola interfaz para los conjuntos de herramientas software orientados al mismo proceso, como el multialineamiento o la inferencia de filogenias. MEvoLib incluye además configuraciones por defecto y métodos que hacen uso de conocimiento biológico específico para mejorar su precisión, adaptándose a las necesidades de cada tipo de usuario. Como última característica relevante, se ha incorporado un proceso de conversión de formatos para los ficheros de entrada y salida de cada interfaz, de forma que, si la herramienta seleccionada no soporta dicho formato, este es adaptado automáticamente. Esta propiedad facilita el uso e integración de MEvoLib en scripts y herramientas software.El estudio del caso de aplicación de PhyloFlow al ADN mitocondrial humano ha expuesto los elevados costes tanto computacionales como económicos asociados a la inferencia de grandes filogenias. Por ello, sistemas como PhyloTree [9], que infiere un tipo especial de filogenias de ADN mitocondrial humano, recalculan sus resultados con una frecuencia máxima anual. Sin embargo, como ya hemos comentado anteriormente, las técnicas de secuenciación actuales permiten la incorporación de cientos o incluso miles de secuencias biológicas nuevas cada mes. Este desfase entre productor y consumidor hace que dichas filogenias queden desactualizadas en unos pocos meses. Para solucionar este problema hemos diseñado un nuevo algoritmo que permite la actualización de una filogenia mediante la incorporación iterativa de nuevas secuencias: PHYSER [10]. Además, la propia información evolutiva se utiliza para detectar posibles mutaciones introducidas artificialmente por el proceso de secuenciación, inexistentes en la secuencia original. Las pruebas realizadas con ADN mitocondrial han probado su eficacia y eficiencia, con un coste temporal por secuencia inferior a los 20 segundos.El desarrollo de nuevas herramientas para el análisis de filogenias también ha sido una parte importante de esta tesis. En concreto, se han realizado dos aportaciones principales en este aspecto: PhyloViewer [11] y una herramienta para el análisis de la conservación [12]. PhyloViewer es un visualizador de filogenias extensivas, es decir, filogenias que poseen al menos un millar de hojas. Esta herramienta aporta una novedosa interfaz en la que se muestra el nodo seleccionado y sus nodos hijo, así como toda la información asociada a cada uno de ellos: identificador, secuencia biológica, ... Esta decisión de diseño ha sido orientada a evitar el habitual “borrón” que se produce en la mayoría de herramientas de visualización al mostrar este tipo de filogenias enteras por pantalla. Además, se ha desarrollado en una arquitectura clienteservidor, con lo que el procesamiento de la filogenia se realiza una única vez por parte el servidor. Así, se ha conseguido reducir significativamente los tiempos de carga y acceso por parte del cliente. Por otro lado, la aportación principal de nuestra herramienta para el análisis de la conservación se basa en la paralelización de los métodos clásicos aplicados en este campo, alcanzando speed-ups cercanos al teórico sin pérdida de precisión. Esto ha sido posible gracias a la implementación de dichos métodos desde cero, incorporando la paralelización a nivel de instrucción, en vez de paralelizar implementaciones existentes. Como resultado, nuestra herramienta genera un informe que contiene las conclusiones del análisis de conservación realizado. El usuario puede introducir un umbral de conservación para que el informe destaque solo aquellas posiciones que no lo cumplan. Además, existen dos tipos de informe con distinto nivel de detalle. Ambos se han diseñado para que sean comprensibles y útiles para los usuarios.Finalmente, se ha diseñado e implementado un predictor de mutaciones patógenas en ADN mitocondrial desarollado en máquinas de vectores de soporte (SVM): Mitoclass.1 [13]. Se trata del primer predictor para este tipo de secuencias biológicas. Tanto es así, que ha sido necesario crear el primer repositorio de mutaciones patógenas conocidas, mdmv.1, para poder entrenar y evaluar nuestro predictor. Se ha demostrado que Mitoclass.1 mejora la clasificación de las mutaciones frente a los predictores más conocidos y utilizados, todos ellos orientados al estudio de patogenicidad en ADN nuclear. Este éxito radica en la novedosa combinación de propiedades a evaluar por cada mutación en el proceso de clasificación. Además, otro factor a destacar es el uso de SVM frente a otras alternativas, que han sido probadas y descartadas debido a su menor capacidad de predicción para nuestro caso de aplicación.REFERENCIAS[1] L. Wang and T. Jiang, “On the complexity of multiple sequence alignment,” Journal of computational biology, vol. 1, no. 4, pp. 337–348, 1994.[2] W. H. E. Day, D. S. Johnson, and D. Sankoff, “The Computational Complexity of Inferring Rooted Phylogenies by Parsimony,” Mathematical Biosciences, vol. 81, no. 1, pp. 33–42, 1986.[3] S. Roch, “A short proof that phylogenetic tree reconstruction by maximum likelihood is hard,” IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), vol. 3, no. 1, p. 92, 2006.[4] E. R. Mardis, “The impact of next-generation sequencing technology on genetics,” Trends in genetics, vol. 24, no. 3, pp. 133–141, 2008.[5] J. Álvarez-Jarreta, G. de Miguel Casado, and E. Mayordomo, “PhyloFlow: A Fully Customizable and Automatic Workflow for Phylogeny Estimation,” in ECCB 2014, 2014.[6] J. Álvarez-Jarreta, G. de Miguel Casado, and E. Mayordomo, “PhyloFlow: A Fully Customizable and Automatic Workflow for Phylogenetic Reconstruction,” in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1–7, IEEE, 2014.[7] J. Álvarez, R. Blanco, and E. Mayordomo, “Workflows with Model Selection: A Multilocus Approach to Phylogenetic Analysis,” in 5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011), vol. 93 of Advances in Intelligent and Soft Computing, pp. 39–47, Springer Berlin Heidelberg, 2011.[8] J. Álvarez-Jarreta and E. Ruiz-Pesini, “MEvoLib v1.0: the First Molecular Evolution Library for Python,” BMC Bioinformatics, vol. 17, no. 436, pp. 1–8, 2016.[9] M. van Oven and M. Kayser, “Updated comprehensive phylogenetic tree of global human mitochondrial DNA variation,” Human Mutation, vol. 30, no. 2, pp. E386–E394, 2009.[10] J. Álvarez-Jarreta, E. Mayordomo, and E. Ruiz-Pesini, “PHYSER: An Algorithm to Detect Sequencing Errors from Phylogenetic Information,” in 6th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2012), pp. 105–112, 2012.[11] J. Álvarez-Jarreta and G. de Miguel Casado, “PhyloViewer: A Phylogenetic Tree Viewer for Extense Phylogenies,” in ECCB 2014, 2014.[12] F. Merino-Casallo, J. Álvarez-Jarreta, and E. Mayordomo, “Conservation in mitochondrial DNA: Parallelized estimation and alignment influence,” in 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2015), pp. 1434–1440, IEEE, 2015.[13] A. Martín-Navarro, A. Gaudioso-Simón, J. Álvarez-Jarreta, J. Montoya, E. Mayordomo, and E. Ruiz-Pesini, “Machine learning classifier for identification of damaging missense mutations exclusive to human mitochondrial DNA-encoded polypeptides,” BMC Bioinformatics, vol. 18, no. 158, pp. 1–11, 2017.<br /