SEARCHING NEUROIMAGING BIOMARKERS IN MENTAL DISORDERS WITH GRAPH AND MULTIMODAL FUSION ANALYSIS OF FUNCTIONAL CONNECTIVITY

Mental disorders such as schizophrenia (SZ), bipolar (BD), and major depression disorders (MDD) can cause severe symptoms and life disruption. They share some symptoms, which can pose a major clinical challenge to their differentiation. Objective biomarkers based on neuroimaging may help to improve diagnostic accuracy and facilitate optimal treatment for patients. Over the last decades, non-invasive in-vivo neuroimaging techniques such as magnetic resonance imaging (MRI) have been increasingly applied to measure structure and function in human brains. With functional MRI (fMRI) or structural MRI (sMRI), studies have identified neurophysiological deficits in patients’ brain from different perspective. Functional connectivity (FC) analysis is an approach that measures functional integration in brains. By assessing the temporal coherence of the hemodynamic activity among brain regions, FC is considered capable of characterizing the large-scale integrity of neural activity. In this work, we present two data analysis frameworks for biomarker detection on brain imaging with FC, 1) graph analysis of FC and 2) multimodal fusion analysis, to better understand the human brain. Graph analysis reveals the interaction among brain regions based on graph theory, while the multimodal fusion framework enables us to utilize the strength of different imaging modalities through joint analysis. Four applications related to FC using these frameworks were developed. First, FC was estimated using a model-based approach, and revealed altered the small-world network structure in SZ. Secondly, we applied graph analysis on functional network connectivity (FNC) to differentiate BD and MDD during resting-state. Thirdly, two functional measures, FNC and fractional amplitude of low frequency fluctuations (fALFF), were spatially overlaid to compare the FC and spatial alterations in SZ. And finally, we utilized a multimodal fusion analysis framework, multi-set canonical correlation analysis + joint independent component analysis (mCCA+jICA) to link functional and structural abnormalities in BD and MDD. We also evaluated the accuracy of predictive diagnosis through classifiers generated on the selected features. In summary, via the two frameworks, our work has made several contributions to advance FC analysis, which improves our understanding of underlying brain function and structure, and our findings may be ultimately useful for the development of biomarkers of mental disease

Distributed Late-binding Micro-scheduling and Data Caching for Data-Intensive Workflows

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, leída el 06-07-2015El mundo de hoy en día se encuentra inundado por ingentes cantidades de información digital procedente de muy diversas fuentes. Todo apunta, además, a que esta tendencia se agudizará en el futuro. Ni la industria, ni la sociedad en general, ni, muy particularmente, la ciencia, permanecen indiferentes ante este hecho. Al contrario, se esfuerzan por obtener el máximo provecho de esta información, lo que significa que deben capturarla, transferirla, almacenarla y procesarla puntual y eficientemente, utilizando una amplia gama de recursos computacionales. Pero esta tarea no es siempre sencilla. Un ejemplo representativo de los desafíos que suponen el manejo y procesamiento de grandes cantidades de datos es el de los experimentos de física de partículas del Large Hadron Collider (LHC), en Ginebra, que cada año deben gestionar decenas de petabytes de información. Basándonos en la experiencia de una de estas colaboraciones, hemos estudiado los principales problemas relativos a la gestión de volúmenes de datos masivos y a la ejecución de vastos flujos de trabajo que necesitan consumirlos. En este contexto, hemos desarrollado una arquitectura de propósito general para la planificación y ejecución de flujos de trabajo con importantes requisitos de datos, que hemos llamado Task Queue. Este nuevo sistema aprovecha el modelo de asignación tardía basado en agentes que ha ayudado a los experimentos del LHC a superar los problemas asociados con la heterogeneidad y la complejidad de las grandes infraestructuras grid de computación. Nuestra propuesta presenta varias mejoras con respecto a los sistemas existentes. Los agentes de ejecución de la arquitectura Task Queue comparten una tabla hash distribuida (Distributed Hash Table, DHT) y realizan la asignación de tareas de una manera cooperativa. De esta forma, se evitan los problemas de escalabilidad de los algoritmos centralizados de asignación y se mejoran los tiempos de ejecución. Esta escalabilidad nos permite realizar una microplanificación de grano fino lo cual posibilita nuevas funcionalidades, como la implementación de una cache distribuida en los nodos de ejecución y el uso de la información de ubicación de los datos en las decisiones de asignación de tareas. Esto mejora la eficiencia del procesado de datos y ayuda a aliviar los habitualmente congestionados servicios de almacenamiento del grid. Además, nuestro sistema es más robusto frente a problemas en la interacción con la cola central de tareas y ofrece mejor comportamiento en situaciones con patrones de acceso a datos exigentes o en ausencia de servicios de almacenamiento locales. Todo esto ha sido demostrado en una amplia serie de pruebas de evaluación. Dado que nuestro procedimiento de planificación de tareas distribuido requiere el uso de mensajes de broadcast, también hemos realizado un profundo estudio de las posibles aproximaciones a la implementación de esta operación sobre el DHT Kademlia, el cual es utilizado para la cache de datos compartida. Kademlia ofrece enrutamiento a nodos individuales pero no incluye ninguna primitiva de broadcast. Nuestro trabajo expone las peculiaridades de este sistema, particularmente su métrica basada en la operación XOR, y estudia analíticamente qué técnicas de broadcast pueden ser usadas con él. También se ha desarrollado un modelo que estima la cobertura de nodos en función de la probabilidad que cada mensaje individual alcance su destino correctamente. Como validación, los algoritmos se han implementado y se han evaluado exhaustivamente. Además, proponemos varias técnicas para mejorar los protocolos en situaciones adversas, por ejemplo cuando el sistema presenta una alta rotación de nodos o la tasa de error en las entregas no es despreciable. Esta técnicas incluyen redundancia, reenvío e inundación (flooding), así como combinaciones de las mismas. Presentamos un análisis de las fortalezas y debilidades de los diferentes algoritmos y las mencionadas técnicas complementarias.Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Advancing Urban Flood Resilience With Smart Water Infrastructure

Advances in wireless communications and low-power electronics are enabling a new generation of smart water systems that will employ real-time sensing and control to solve our most pressing water challenges. In a future characterized by these systems, networks of sensors will detect and communicate flood events at the neighborhood scale to improve disaster response. Meanwhile, wirelessly-controlled valves and pumps will coordinate reservoir releases to halt combined sewer overflows and restore water quality in urban streams. While these technologies promise to transform the field of water resources engineering, considerable knowledge gaps remain with regards to how smart water systems should be designed and operated. This dissertation presents foundational work towards building the smart water systems of the future, with a particular focus on applications to urban flooding. First, I introduce a first-of-its-kind embedded platform for real-time sensing and control of stormwater systems that will enable emergency managers to detect and respond to urban flood events in real-time. Next, I introduce new methods for hydrologic data assimilation that will enable real-time geolocation of floods and water quality hazards. Finally, I present theoretical contributions to the problem of controller placement in hydraulic networks that will help guide the design of future decentralized flood control systems. Taken together, these contributions pave the way for adaptive stormwater infrastructure that will mitigate the impacts of urban flooding through real-time response.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163144/1/mdbartos_1.pd

Methods for revealing and reshaping the African Internet Ecosystem as a case study for developing regions: from isolated networks to a connected continent

Mención Internacional en el título de doctorWhile connecting end-users worldwide, the Internet increasingly promotes local development by making challenges much simpler to overcome, regardless of the field in which it is used: governance, economy, education, health, etc. However, African Network Information Centre (AfriNIC), the Regional Internet Registry (RIR) of Africa, is characterized by the lowest Internet penetration: 28.6% as of March 2017 compared to an average of 49.7% worldwide according to the International Telecommunication Union (ITU) estimates [139]. Moreover, end-users experience a poor Quality of Service (QoS) provided at high costs. It is thus of interest to enlarge the Internet footprint in such under-connected regions and determine where the situation can be improved. Along these lines, this doctoral thesis thoroughly inspects, using both active and passive data analysis, the critical aspects of the African Internet ecosystem and outlines the milestones of a methodology that could be adopted for achieving similar purposes in other developing regions. The thesis first presents our efforts to help build measurements infrastructures for alleviating the shortage of a diversified range of Vantage Points (VPs) in the region, as we cannot improve what we can not measure. It then unveils our timely and longitudinal inspection of the African interdomain routing using the enhanced RIPE Atlas measurements infrastructure for filling the lack of knowledge of both IPv4 and IPv6 topologies interconnecting local Internet Service Providers (ISPs). It notably proposes reproducible data analysis techniques suitable for the treatment of any set of similar measurements to infer the behavior of ISPs in the region. The results show a large variety of transit habits, which depend on socio-economic factors such as the language, the currency area, or the geographic location of the country in which the ISP operates. They indicate the prevailing dominance of ISPs based outside Africa for the provision of intracontinental paths, but also shed light on the efforts of stakeholders for traffic localization. Next, the thesis investigates the causes and impacts of congestion in the African IXP substrate, as the prevalence of this endemic phenomenon in local Internet markets may hinder their growth. Towards this end, Ark monitors were deployed at six strategically selected local Internet eXchange Points (IXPs) and used for collecting Time-Sequence Latency Probes (TSLP) measurements during a whole year. The analysis of these datasets reveals no evidence of widespread congestion: only 2.2% of the monitored links experienced noticeable indication of congestion, thus promoting peering. The causes of these events were identified during IXP operator interviews, showing how essential collaboration with stakeholders is to understanding the causes of performance degradations. As part of the Internet Society (ISOC) strategy to allow the Internet community to profile the IXPs of a particular region and monitor their evolution, a route-collector data analyzer was then developed and afterward, it was deployed and tested in AfriNIC. This open source web platform titled the “African” Route-collectors Data Analyzer (ARDA) provides metrics, which picture in real-time the status of interconnection at different levels, using public routing information available at local route-collectors with a peering viewpoint of the Internet. The results highlight that a small proportion of Autonomous System Numbers (ASNs) assigned by AfriNIC (17 %) are peering in the region, a fraction that remained static from April to September 2017 despite the significant growth of IXPs in some countries. They show how ARDA can help detect the impact of a policy on the IXP substrate and help ISPs worldwide identify new interconnection opportunities in Africa, the targeted region. Since broadening the underlying network is not useful without appropriately provisioned services to exploit it, the thesis then delves into the availability and utilization of the web infrastructure serving the continent. Towards this end, a comprehensive measurement methodology is applied to collect data from various sources. A focus on Google reveals that its content infrastructure in Africa is, indeed, expanding; nevertheless, much of its web content is still served from the United States (US) and Europe, although being the most popular content source in many African countries. Further, the same analysis is repeated across top global and regional websites, showing that even top African websites prefer to host their content abroad. Following that, the primary bottlenecks faced by Content Providers (CPs) in the region such as the lack of peering between the networks hosting our probes and poorly configured DNS resolvers are explored to outline proposals for further ISP and CP deployments. Considering the above, an option to enrich connectivity and incentivize CPs to establish a presence in the region is to interconnect ISPs present at isolated IXPs by creating a distributed IXP layout spanning the continent. In this respect, the thesis finally provides a four-step interconnection scheme, which parameterizes socio-economic, geographical, and political factors using public datasets. It demonstrates that this constrained solution doubles the percentage of continental intra-African paths, reduces their length, and drastically decreases the median of their Round Trip Times (RTTs) as well as RTTs to ASes hosting the top 10 global and top 10 regional Alexa websites. We hope that quantitatively demonstrating the benefits of this framework will incentivize ISPs to intensify peering and CPs to increase their presence, for enabling fast, affordable, and available access at the Internet frontier.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: David Fernández Cambronero.- Secretario: Alberto García Martínez.- Vocal: Cristel Pelsse

Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out