Docitive Networks. A Step Beyond Cognition

Projecte fet en col.laboració amb Centre Tecnològic de Telecomunicacions de CatalunyaCatalà: En les Xarxes Docents es por ta més enllà la idea d'elaborar decisions intel ligents. Per mitjà de compartir informació entre els nodes, amb l'objectiu primordial de reduir la complexitat i millorar el rendiment de les Xarxes Cognitives. Per a això es revisen alguns conceptes importants de les bases de l'Aprenentatge Automàtic, prestant especial atenció a l'aprenentatge per reforç. També es fa una visió de la Teoria de Jocs Evolutius i de la dinàmica de rèpliques. Finalment, simulacions ,basades en el projecte TIC-BUNGEE, es mostren per validar els conceptes introduïts.Castellano: Las Redes Docentes llevan más alla la idea de elaborar decisiones inteligentes, por medio de compartir información entre los nodos, con el objetivo primordial de reducir la complejidad y mejorar el rendimiento de las Redes Cognitiva. Para ello se revisan algunos conceptos importantes de las bases del Aprendizaje Automático, prestando especial atencion al aprendizaje por refuerzo, también damos una visón de la Teoría de Juegos Evolutivos y de la replicación de dinamicas. Por último, las simulaciones basadas en el proyecto TIC-BUNGEE se muestran para validar los conceptos introducidos.English: The Docitive Networks further use the idea of drawing intelligent decisions by means of sharing information between nodes with the prime aim of reduce complexity and enhance performance of Congnitive Networks. To this end we review some important concepts form Machine Learning, paying special atention to Reinforcement Learning, we also go insight Evolutionary Game Theory and Replicator Dynamics. Finally, simulations Based on ICT-BUNGEE project are shown to validate the introduced concepts

On Masked Pre-training and the Marginal Likelihood

Masked pre-training removes random input dimensions and learns a model that can predict the missing values. Empirical results indicate that this intuitive form of self-supervised learning yields models that generalize very well to new domains. A theoretical understanding is, however, lacking. This paper shows that masked pre-training with a suitable cumulative scoring function corresponds to maximizing the model's marginal likelihood, which is de facto the Bayesian model selection measure of generalization. Beyond shedding light on the success of masked pre-training, this insight also suggests that Bayesian models can be trained with appropriately designed self-supervision. Empirically, we confirm the developed theory and explore the main learning principles of masked pre-training in large language models

Missing Persons App: an Android app for missing people

During the last years, the smartphone industry has really advanced by leaps and bounds. In 2017, the number of smartphone users was 2.4 billion, with an increase of 10,8% respecting the year before. As we can see, there is a huge market, and more people get used to use the mobile phone to do daily things such as online shopping, visiting webpages or sending emails. The following project covers an aspect that very few people worked in, the people who disappeared. Nowadays, the data of disappeared people has not been digitized, or if it has, is outdated in the current times. The aim is to create an Android application for disappeared people. The app will collect and share information among users, whose use will be helping in the research of people who disappeared. Also, the idea is to offer a database and allow people to access data easily. In this document is explained all the process of making the app, starting from analysing similar apps in the actual market, all the technologies that were used (from backend to frontend) and in which order was the app made. Finally, we will test the app and see how it works. Also, a manual for the backend and the app will be attached.Outgoin

Docitive Networks. A Step Beyond Cognition

Projecte fet en col.laboració amb Centre Tecnològic de Telecomunicacions de CatalunyaCatalà: En les Xarxes Docents es por ta més enllà la idea d'elaborar decisions intel ligents. Per mitjà de compartir informació entre els nodes, amb l'objectiu primordial de reduir la complexitat i millorar el rendiment de les Xarxes Cognitives. Per a això es revisen alguns conceptes importants de les bases de l'Aprenentatge Automàtic, prestant especial atenció a l'aprenentatge per reforç. També es fa una visió de la Teoria de Jocs Evolutius i de la dinàmica de rèpliques. Finalment, simulacions ,basades en el projecte TIC-BUNGEE, es mostren per validar els conceptes introduïts.Castellano: Las Redes Docentes llevan más alla la idea de elaborar decisiones inteligentes, por medio de compartir información entre los nodos, con el objetivo primordial de reducir la complejidad y mejorar el rendimiento de las Redes Cognitiva. Para ello se revisan algunos conceptos importantes de las bases del Aprendizaje Automático, prestando especial atencion al aprendizaje por refuerzo, también damos una visón de la Teoría de Juegos Evolutivos y de la replicación de dinamicas. Por último, las simulaciones basadas en el proyecto TIC-BUNGEE se muestran para validar los conceptos introducidos.English: The Docitive Networks further use the idea of drawing intelligent decisions by means of sharing information between nodes with the prime aim of reduce complexity and enhance performance of Congnitive Networks. To this end we review some important concepts form Machine Learning, paying special atention to Reinforcement Learning, we also go insight Evolutionary Game Theory and Replicator Dynamics. Finally, simulations Based on ICT-BUNGEE project are shown to validate the introduced concepts

Vision as inverse graphics for detailed scene understanding

An image of a scene can be described by the shape, pose and appearance of the objects within it, as well as the illumination, and the camera that captured it. A fundamental goal in computer vision is to recover such descriptions from an image. Such representations can be useful for tasks such as autonomous robotic interaction with an environment, but obtaining them can be very challenging due the large variability of objects present in natural scenes. A long-standing approach in computer vision is to use generative models of images in order to infer the descriptions that generated the image. These methods are referred to as “vision as inverse graphics” or “inverse graphics”. We propose using this approach to scene understanding by making use of a generative model (GM) in the form of a graphics renderer. Since searching over scene factors to obtain the best match for an image is very inefficient, we make use of convolutional neural networks, which we refer to as the recognition models (RM), trained on synthetic data to initialize the search. First we address the effect that occlusions on objects have on the performance of predictive models of images. We propose an inverse graphics approach to predicting the shape, pose, appearance and illumination with a GM which includes an outlier model to account for occlusions. We study how the inferences are affected by the degree of occlusion of the foreground object, and show that a robust GM which includes an outlier model to account for occlusions works significantly better than a non-robust model. We then characterize the performance of the RM and the gains that can be made by refining the search using the robust GM, using a new synthetic dataset that includes background clutter and occlusions. We find that pose and shape are predicted very well by the RM, but appearance and especially illumination less so. However, accuracy on these latter two factors can be clearly improved with the generative model. Next we apply our inverse graphics approach to scenes with multiple objects. We propose using a method to efficiently and differentiably model self shadowing which improves the realism of the GM renders. We also propose a way to render object occlusion boundaries which results in more accurate gradients of the rendering function. We evaluate these improvements using a dataset with multiple objects and show that the refinement step of the GM clearly improves on the predictions of the RM for the latent variables of shape, pose, appearance and illumination. Finally we tackle the task of learning generative models of 3D objects from a collection of meshes. We present a latent variable architecture that learns to separately capture the underlying factors of shape and appearance from the meshes. To do so we first transform the meshes of a given class to a data representation that sidesteps the need for landmark correspondences across meshes when learning the GM. The ability and usefulness of learning a disentangled latent representation of objects is demonstrated via an experiment where the appearance of one object is transferred onto the shape of another

Les Façanes de l'Eixample de Barcelona a través dels anys : un estudi de les transformacions en els edificis construïts entre el 1850 i el 1950

Estudi de les façanes de l'Eixample d'edificis construits entre l'any 1850 i 1950 i la seva evolució fins a dia d'avui

RESTful Web services in Wireless Sensor Networks

Premi Accenture al millor projecte de fi de carrera d’Enginyeria de Telecomunicació en Serveis Telemàtics (curs 2011-2012)English: Wireless Sensor Networks (WSNs) have become very popular in recent years. A WSN consists of distributed autonomous sensors to monitor physical or environmental conditions and to cooperatively send their data through the network to a main location. A WSN facilitates the creation of low-cost networks that can be used for multiple applications when the use of wires is impractical and expensive. Examples of these applications are home and building automation, asset management and logistics or health care automation. The main objective of this work is to investigate and propose a solution to enable Web services in WSNs. To accomplish this task, a research to choose the Web architectural style that fits best with WSNs has been done. Discussions show that the REST architectural style seems to be the one which is more suitable for WSNs. The next step is to choose an appropriate application layer protocol. In this sense, the CoAP protocol has been used to enable Web services in constrained networks. In this work, a CoAP implementation for the TinyOS operating system is proposed and developed. The most popular application protocol used in the Internet is HTTP. In order to integrate the proposed solution with the Internet, some translation between CoAP and HTTP is needed. In this work, a hardware and software proxy-based solution to connect CoAP resources with the actual Internet is proposed and developed. This solution also enables extra services that are interesting in WSNs. Finally, a performance evaluation is done in order evaluate the proposed implementation. Results show that using CoAP in constrained devices in WSNs improves the overall latency in comparison with using HTTP/1.0 in constrained nodes. A comparison between using a CoAP client to access CoAP resources and using a HTTP client using the proposed proxy solution has been done. Results show that using the proxy solution adds low extra latency, thus providing a good solution when using a CoAP client is not possible.Castellano: Las redes de sensores inalámbricas se han vuelto muy populares durante los últimos años. Están formadas por sensores autónomos que están distribuidos para monitorizar las condiciones físicas y ambientales y transferir de forma colaborativa sus datos a través de una red hasta un punto central. Estas redes facilitan la creación e implantación de redes de bajo coste en lugares donde emplear cableado es difícil y costoso. Algunos ámbitos en los que se podrían aplicar estas redes serían la domótica, la logística o la salud. El principal objetivo de este trabajo es investigar y proponer una solución para conseguir integrar servicios Web en redes de sensores inalámbricas. Para realizar esta tarea, se ha investigado cuál de los dos modelos de arquitecturas Web actuales más utilizadas (REST o SOAP) es el que mejor se ajusta a las características de estas redes. Las conclusiones obtenidas apuntan a que el modelo REST es el que mejor se ajusta. El siguiente paso ha sido seleccionar un protocolo de aplicación para las diferentes redes de sensores. El protocolo utilizado en este trabajo es el protocolo CoAP. Se ha desarrollado un software para integrar este protocolo en el sistema operativo TinyOS, que se ha utilizado y probado sobre el hardware TelosB. El protocolo de aplicación más utilizado en Internet es el propocolo HTTP. Para conseguir integrar la solución propuesta para las redes inalámbricas de sensores en el modelo actual de Internet, es necesaria una traducción entre los protocolos CoAP y HTTP. Este trabajo propone una solución hardware y software basada en la utilización de un proxy que permite a los clientes HTTP acceder a recursos CoAP. Finalmente, se ha realizado una evaluación para extraer algunas conclusiones sobre las implementaciones realizadas. Los resultados muestran que el uso de este protocolo proporciona mejores resultados en términos de latencia si se compara con utilizar HTTP/1.0 sobre dispositivos con recursos limitados. También se ha realizado una comparativa entre utilizar un cliente CoAP para acceder a los recursos de la red o utilizar un cliente HTTP mediante el proxy propuesto. Los resultados muestran que en los casos en los que utilizar un cliente CoAP no sea viable, la propuesta de proxy es una buena solución que ofrece una baja latencia.Català: Les xarxes de sensors inalàmbriques s'han tornat molt populars durant els darrers anys. Estan formades per sensors autònoms que estan distribuïts per monitoritzar les condicions físiques i ambientals i transferir de forma col·laborativa les seves dades a través de la xarxa fins a un punt central. Aquestes xarxes faciliten la creació i integració de xarxes de baix cost en escenaris on utilitzar cablejat és difícil i costós. Alguns exemples d'àmbits on aquestes xarxes es podrien aplicar serien la domòtica, la logística o la salut. El principal objectiu d'aquest treball és investigar i proposar una solució per aconseguir integrar serveis Web sobre xarxes de sensors inalàmbriques. Per a realizar aquesta tasca, s'ha fet una recerca per saber quin dels models d'arquitectures actuals més utilitzats a la Web (REST o SOAP) és el que s'ajusta millor als requeriments d'aquestes xarxes. Les conclusions obtingudes apunten a que el model REST és el que millor s'ajusta. El següent pas ha estat triar un protocol d'aplicació per les diferents xarxes de sensors. El protocol utilitzat en aquest treball és el protocol CoAP. S'ha desenvolupat una programari per integrar aquest protocol al sistema operatiu TinyOS, que s'ha utilitzat i provat sobre el maquinari TelosB. El protocol d'aplicació més utilitzat a Internet és el protocol HTTP. Per aconseguir integrar la solució proposada en el model actual d'Internet, és necessària una traducció entre el protocol CoAP i el protocol HTTP. En aquest treball es proposa una solució (tant maquinari com programari) basada en un proxy que permet als clients HTTP actuals accedir a recursos CoAP. Finalment, s'ha realitzat una avaluació per extreure algunes conclusions sobre les implementacions realitzades. Els resultats mostren que l'ús d'aquest protocol dóna millors resultats en termes de latència si es compara amb utilitzar HTTP/1.0 sobre dispositius limitats en recursos. També s'ha realizat una comparativa entre utilitzar un client CoAP per accedir als recursos de la xarxa o bé fer servir un client HTTP per connectar-se mitjaçant un proxy. Els resultats mostren que en els casos on fer servir un client CoAP no sigui possible, la solució proposada és una bona alternativa que afegeix poca latència.Award-winnin

The son-killer microbe Arsenophonus nasoniae is a widespread associate of the parasitic wasp Nasonia vitripennis in Europe

Heritable microbes that exhibit reproductive parasitism are common in insects. One class of these are the malekilling bacteria, which are found in a broad range of insect hosts. Commonly, our knowledge of the incidence of these microbes is based on one or a few sampling sites, and the degree and causes of spatial variation are unclear. In this paper, we examine the incidence of the son-killer microbe Arsenophonus nasoniae across European populations of its wasp host, Nasonia vitripennis. In preliminary work, we noticed two female N. vitripennis producing highly female biased sex ratios in a field study from the Netherlands and Germany. When tested, the brood from Germany was revealed to be infected with A. nasoniae. We then completed a broad survey in 2012, in which fly pupal hosts of N. vitripennis were collected from vacated birds’ nests from four European populations, N. vitripennis wasps allowed to emerge and then tested for A. nasoniae presence through PCR assay. We then developed a new screening methodology based on direct PCR assays of fly pupae and applied this to ethanolpreserved material collected from great tit (Parus major) nests in Portugal. These data show A. nasoniae is found widely in European N. vitripennis, being present in Germany, the UK, Finland, Switzerland and Portugal. Samples varied in the frequency with which they carry A. nasoniae, from being rare to being present in 50% of the pupae parasitised by N. vitripennis. Direct screening of ethanol-preserved fly pupae was an effective method for revealing both wasp and A. nasoniae infection, and will facilitate sample transport across national boundaries. Future research should examine the causes of variation in frequency, in particular testing the hypothesis that N. vitripennis superparasitism rates drive the variation in A. nasoniae frequency through providing opportunities for infectious transmission.The NERC (NE/I01067X/1)BBSRC (BB/S017534/1)Grants lzp-2021/1-02772022/1-0348 from the Latvian Council of Science to IKGrant from Academy of Finland (338180)Grants from the Fundaçao para a Ciencia e a Tecnologia to ACN (UIDB/04292/2020; UIDP/04292/2020LA/P/0069/2020; DL57/2016/CP1370/CT89)Grants from AUIP and Spanish Ministry of Education (FPU18/03034

Implicit Shape and Appearance Priors for Few-Shot Full Head Reconstruction

Recent advancements in learning techniques that employ coordinate-based neural representations have yielded remarkable results in multi-view 3D reconstruction tasks. However, these approaches often require a substantial number of input views (typically several tens) and computationally intensive optimization procedures to achieve their effectiveness. In this paper, we address these limitations specifically for the problem of few-shot full 3D head reconstruction. We accomplish this by incorporating a probabilistic shape and appearance prior into coordinate-based representations, enabling faster convergence and improved generalization when working with only a few input images (even as low as a single image). During testing, we leverage this prior to guide the fitting process of a signed distance function using a differentiable renderer. By incorporating the statistical prior alongside parallelizable ray tracing and dynamic caching strategies, we achieve an efficient and accurate approach to few-shot full 3D head reconstruction. Moreover, we extend the H3DS dataset, which now comprises 60 high-resolution 3D full head scans and their corresponding posed images and masks, which we use for evaluation purposes. By leveraging this dataset, we demonstrate the remarkable capabilities of our approach in achieving state-of-the-art results in geometry reconstruction while being an order of magnitude faster than previous approaches