19,001 research outputs found

    STRATIFIED INVESTIGATION OF LOW-PERFORMING NETWORK ARCHITECTURE (SINA) USING GRAPH NEURAL NETWORKS AND PEER BENCHMARKING

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    Monitoring and troubleshooting networks to improve their performance and reliability is a complicated task, not only because it requires the checking of every single network device but also because it involves understanding the connections between those devices. To address that complexity, techniques are presented herein that support a Stratified Investigation of Low-Performing Network Architecture (SINA) system. Such a system is a framework that identifies any low-performing network architecture areas and makes improvements on a subnetwork level. Such a system may automatically identify low-performing areas of a customer’s network based on information about similar networks and expert knowledge with solutions. Such a system may employ a graph neural network (GNN) to identify areas of a customer’s network that need improvement based on a calculated performance score while considering the interaction between devices and the topology of networks. Further, such a system may leverage network performance metrics from many customers to create a performance benchmark and then evaluate where a customer’s network’s performance lies within that benchmark. Still further, such a system may employ a transformer-based natural language processing (NLP) model (that understands key semantic knowledge from documents, device configurations, and logs) to help generate solutions to network issues. Finally, based on high-performing customers relative to the benchmark and documents with best practices for configuring networks, a SINA system may provide solutions to a customer’s network that will help optimize network performance

    Creating an Information System with a Social Purpose - The Case of Re-Food

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    Project Work presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementNowadays, with the evolution of technology, the strategies of information management are constantly improving to create faster and more efficient methods of analyzing and displaying data. At the same time, the users, considering the amount of information they access every day, search for simpler, faster and cleaner ways to interact with information. These strategies with simpler designs are important, now more than ever, to help social organizations, such as Re-Food, improve their work and show to communities that they impact directly and indirectly the importance of eco-sustainability and solidarity projects. This project proposes to build an information system capable of structuring data from Re-Food resources, create faster and more efficient solutions to improve the centers’ management and show to the rest of the community the impact this organization, and the ones alike have on society

    Towards a generic compilation approach for quantum circuits through resynthesis

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    In this paper, we propose a generic quantum circuit resynthesis approach for compilation. We use an intermediate representation consisting of Paulistrings over {Z, I} and {X, I} called a ``mixed ZX-phase polynomial``. From this universal representation, we generate a completely new circuit such that all multi-qubit gates (CNOTs) are satisfying a given quantum architecture. Moreover, we attempt to minimize the amount of generated gates. The proposed algorithms generate fewer CNOTs than similar previous methods on different connectivity graphs ranging from 5-20 qubits. In most cases, the CNOT counts are also lower than Qiskit's. For large circuits, containing >= 100 Paulistrings, our proposed algorithms even generate fewer CNOTs than the TKET compiler. Additionally, we give insight into the trade-off between compilation time and final CNOT count.Comment: 10 pages including references. 2 tables, 1 figur

    Metaphors of London fog, smoke and mist in Victorian and Edwardian Art and Literature

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    Julian Wolfreys has argued that after 1850 writers employed stock images of the city without allowing them to transform their texts. This thesis argues, on the contrary, that metaphorical uses of London fog were complex and subtle during the Victorian and Edwardian periods, at least until 1914. Fog represented, in particular, formlessness and the dissolution of boundaries. Examining the idea of fog in literature, verse, newspaper accounts and journal articles, as well as in the visual arts, as part of a common discourse about London and the state of its inhabitants, this thesis charts how the metaphorical appropriation of this idea changed over time. Four of Dickens's novels are used to track his use of fog as part of a discourse of the natural and unnatural in individual and society, identifying it with London in progressively more negative terms. Visual representations of fog by Constable, Turner, Whistler, Monet, Markino, O'Connor, Roberts and Wyllie and Coburn showed an increasing readiness to engage with this discourse. Social tensions in the city in the 1880s were articulated in art as well as in fiction. Authors like Hay and Barr showed the destruction of London by its fog because of its inhabitants' supposed degeneracy. As the social threat receded, apocalyptic scenarios gave way to a more optimistic view in the work of Owen and others. Henry James used fog as a metaphorical representation of the boundaries of gendered behaviour in public, and the problems faced by women who crossed them. The dissertation also examines fog and individual transgression, in novels and short stories by Lowndes, Stevenson, Conan Doyle and Joseph Conrad. After 1914, fog was no more than a crude signifier of Victorian London in literature, film and, later, television, deployed as a cliche instead of the subtle metaphorical idea discussed in this thesis

    Desarrollo de una herramienta integral de gestión de gases de efecto invernadero para la toma de decisión contra el cambio climático a nivel regional y local en la Comunitat Valenciana

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    Tesis por compendio[ES] Actualmente, los responsables de tomar decisiones contra el cambio climático carecen de herramientas para desarrollar inventarios de emisiones de gases de efecto invernadero (GEI) con suficiente rigor científico-técnico y precisión para priorizar e invertir los recursos disponibles de manera eficiente en las medidas necesarias para luchar contra el cambio climático. Por ello, en esta tesis se expone el desarrollo de un sistema de información territorial y sectorial (SITE) para monitorear las emisiones de GEI que sirva como herramienta de gobernanza climática local y regional. SITE combina las ventajas de los enfoques metodológicos descendente o top-down (de arriba hacia abajo) y ascendente o bottom-up (de abajo hacia arriba), para lograr un enfoque híbrido innovador para contabilizar y gestionar de manera eficiente las emisiones de GEI. Por tanto, en esta tesis se definen los diferentes desarrollos metodológicos, tanto generales como específicos de sectores clave del Panel Intergubernamental de Cambio Climático (IPPC) (edificación, transporte, sector forestal, etc.), un desarrollo informático para la parte de SITE que se ejecuta del lado del servidor, que de ahora en adelante denominaremos back-end del sistema, y siete implementaciones como casos de estudio representativos, a diferentes escalas y aplicados sobre diferentes sectores. Estas implementaciones a diferentes escalas y sectores demuestran el potencial del sistema como herramienta de apoyo en la toma de decisión contra el cambio climático a nivel regional y local. Las diferentes implementaciones en casos piloto representativos, tanto a nivel regional en la Comunitat Valenciana como a nivel local en municipios grandes (València) y medianos (Quart de Poblet y Llíria) muestran el potencial de adaptación territorial y sectorial que tiene la herramienta. Las metodologías desarrolladas para los sectores específicos de tráfico rodado, edificación o sector forestal, ofrecen cuantificaciones con una resolución espacial con gran capacidad de optimizar las políticas locales y regionales. Por tanto, la herramienta cuenta con un gran potencial de escalabilidad y gran capacidad de mejora continua mediante la inclusión de nuevos enfoques metodológicos, adaptación de las metodologías a la disponibilidad de datos, metodologías concretas para sectores clave y actualización a las mejores metodologías disponibles derivadas de actividades de investigación de la comunidad científica.[CA] Actualment, els responsables de prendre decisions contra el canvi climàtic no tenen eines per aconseguir inventaris d'emissions de gasos d'efecte hivernacle (GEH) amb prou cientificotècnic rigor, precisió i integritat per invertir els recursos disponibles de manera eficient en les mesures necessàries contra el canvi climàtic. Per això, en aquesta tesis se exposa el desenvolupa un sistema d'informació territorial i sectorial (SITE) per monitoritzar les emissions de GEH com a eina de governança climàtica local i regional. Aquest sistema combina els avantatges dels enfocaments metodològics descendent o top-down (de dalt a baix) i ascendent o bottom-up (de baix a dalt), per aconseguir un enfocament híbrid innovador per comptabilitzar i gestionar de manera eficient les emissions de GEH. Per tant, en aquesta tesi doctoral es descriuen els diferents desenvolupaments metodològics, tant generals com específics de sectors clau del Panel Intergovernamental contra el Canvi Climàtic (edificació, transport, forestal, etc.), un desenvolupament informàtic per al back-end del sistema i set implementacions com a casos d'estudi representatius, a diferents escales, amb els diferents enfocaments metodològics i aplicats sobre diferents sectors. Això queda descrit en sis capítols. Aquestes implementacions a diferents escales i sectors demostren el potencial del sistema com a eina de suport en la presa de decisió contra el canvi climàtic a nivell regional i local. Les diferents implementacions en casos pilot representatius, tant a nivell regional a la Comunitat Valenciana com a nivell local en municipis grans (València) i mitjans (Quart de Poblet i Llíria,) mostren el potencial d'adaptació territorial i sectorial que té l'eina. Les metodologies desenvolupades per als sectors específics de trànsit rodat, edificació i forestal, ofereixen quantificacions amb una resolució espacial amb gran capacitat d'optimitzar les polítiques locals i regionals. Per tant, l'eina compta amb un gran potencial d'escalabilitat i gran capacitat de millora contínua mitjançant la inclusió de nous enfocaments metodològics, adaptació de les metodologies a la disponibilitat de dades, metodologies concretes per a sectors clau, i actualització a les millors metodologies disponibles derivades de activitats de investigació de la comunitat científica.[EN] Currently, regional and local decision-makers lack of tools to achieve greenhouse gases (GHG) emissions inventories with enough rigor, accuracy and completeness in order to prioritize available resources efficiently against climate change. Thus, in this thesis the development of a territorial and sectoral information system (SITE) to monitor GHG emissions as a local and regional climate governance tool is exposed. This system combines the advantages of both, top-down and bottom-up approaches, to achieve an innovative hybrid approach to account and manage efficiently GHG emissions. Furthermore, this thesis defines the methodologies developed, a computer proposal for the back-end of the system and seven implementations as representative case studies at different scales (local and regional level), with the different methodological approaches and applied to different sectors. Thus, these implementations demonstrate the potential of the system as decision-making tool against climate change at the regional and local level as climate governance tool. The different implementations in representative pilot cases, both at the regional level in the Valencian Community and at the local level in large (Valencia) and medium-sized municipalities (Quart de Poblet and Llíria) demonstrate the potential for territorial and sectoral adaptation of the system developed. The methodologies developed for the specific sectors of road transport, building and forestry, offer quantifications with a spatial resolution with a great capacity to optimize local and regional policies. Therefore, the tool has a great potential for scalability and a great capacity for continuous improvement through the inclusion of new methodological approaches, adapting the methodologies to the availability of data, specific methodologies for key sectors, and updating to the best methodologies available in the scientific community.Lorenzo Sáez, E. (2022). Desarrollo de una herramienta integral de gestión de gases de efecto invernadero para la toma de decisión contra el cambio climático a nivel regional y local en la Comunitat Valenciana [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181662TESISCompendi

    Networks: A study in Analysis and Design

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    In this dissertation, we will look at two fundamental aspects of Networks: Network Analysis and Network Design. In part A, we look at Network Analysis area of the dissertation which involves finding the densest subgraph in each graph. The densest subgraph extraction problem is fundamentally a non-linear optimization problem. Nevertheless, it can be solved in polynomial time by an exact algorithm based on the iterative solution of a series of max-flow sub-problems. To approach graphs with millions of vertices and edges, one must resort to heuristic algorithms. We provide an efficient implementation of a greedy heuristic from the literature that is extremely fast and has some nice theoretical properties. An extensive computational analysis shows that the proposed heuristic algorithm proved very effective on many test instances, often providing either the optimal solution or near-optimal solution within short computing times. In part-B, we discuss Network design, which is a cornerstone of mathematical optimization, is about defining the main characteristics of a network satisfying requirements on connectivity, capacity, and level-of-service. In multi-commodity network design, one is required to design a network minimizing the installation cost of its arcs and the operational cost to serve a set of point-to-point connections. This prototypical problem was recently enriched by additional constraints imposing that each origin-destination of a connection is served by a single path satisfying one or more level-of-service requirements, thus defining the Network Design with Service Requirements. These constraints are crucial, e.g., in telecommunications and computer networks, in order to ensure reliable and low-latency communication. We provide a new formulation for the problem, where variables are associated with paths satisfying the end-to-end service requirements. A fast algorithm for enumerating all the exponentially-many feasible paths and, when this is not viable, a column generation scheme that is embedded into a branch-and-cut-and-price algorithm is provided

    Innovative Hybrid Approaches for Vehicle Routing Problems

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    This thesis deals with the efficient resolution of Vehicle Routing Problems (VRPs). The first chapter faces the archetype of all VRPs: the Capacitated Vehicle Routing Problem (CVRP). Despite having being introduced more than 60 years ago, it still remains an extremely challenging problem. In this chapter I design a Fast Iterated-Local-Search Localized Optimization algorithm for the CVRP, shortened to FILO. The simplicity of the CVRP definition allowed me to experiment with advanced local search acceleration and pruning techniques that have eventually became the core optimization engine of FILO. FILO experimentally shown to be extremely scalable and able to solve very large scale instances of the CVRP in a fraction of the computing time compared to existing state-of-the-art methods, still obtaining competitive solutions in terms of their quality. The second chapter deals with an extension of the CVRP called the Extended Single Truck and Trailer Vehicle Routing Problem, or simply XSTTRP. The XSTTRP models a broad class of VRPs in which a single vehicle, composed of a truck and a detachable trailer, has to serve a set of customers with accessibility constraints making some of them not reachable by using the entire vehicle. This problem moves towards VRPs including more realistic constraints and it models scenarios such as parcel deliveries in crowded city centers or rural areas, where maneuvering a large vehicle is forbidden or dangerous. The XSTTRP generalizes several well known VRPs such as the Multiple Depot VRP and the Location Routing Problem. For its solution I developed an hybrid metaheuristic which combines a fast heuristic optimization with a polishing phase based on the resolution of a limited set partitioning problem. Finally, the thesis includes a final chapter aimed at guiding the computational evaluation of new approaches to VRPs proposed by the machine learning community

    The Adirondack Chronology

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    The Adirondack Chronology is intended to be a useful resource for researchers and others interested in the Adirondacks and Adirondack history.https://digitalworks.union.edu/arlpublications/1000/thumbnail.jp

    The Relative Isolation Probability of a Vertex in a Multiple-Source Edge-Weighted Graph

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    Various measures that characterize graphs exist in literature. Insights into the properties of a graph as a whole and its components are revealed largely through graph measures, also called graph metrics. In seeking to interpret a consequential edge metric from a vertex-centric perspective, the paper advances an original measure – the relative isolation probability of a vertex. Concisely, the probability of relative isolation pertains to the likelihood of a vertex to be disconnected from all designated source vertices in a graph with probability-weighted edges. A two-step algorithm for efficient calculation is presented and evaluated. Contained within the procedure is a Monte Carlo simulation and the use of a compact data structure called the zero-suppressed binary decision diagram, efficiently constructed through the frontier-based search. The novel measure is then computed for a diverse set of graphs, serving as benchmark for the proposed method. In closing, case studies on real-world networks are performed to ensure the consistency of the experimental with the actual

    Robustness against adversarial attacks on deep neural networks

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    While deep neural networks have been successfully applied in several different domains, they exhibit vulnerabilities to artificially-crafted perturbations in data. Moreover, these perturbations have been shown to be transferable across different networks where the same perturbations can be transferred between different models. In response to this problem, many robust learning approaches have emerged. Adversarial training is regarded as a mainstream approach to enhance the robustness of deep neural networks with respect to norm-constrained perturbations. However, adversarial training requires a large number of perturbed examples (e.g., over 100,000 examples are required for MNIST dataset) trained on the deep neural networks before robustness can be considerably enhanced. This is problematic due to the large computational cost of obtaining attacks. Developing computationally effective approaches while retaining robustness against norm-constrained perturbations remains a challenge in the literature. In this research we present two novel robust training algorithms based on Monte-Carlo Tree Search (MCTS) [1] to enhance robustness under norm-constrained perturbations [2, 3]. The first algorithm searches potential candidates with Scale Invariant Feature Transform method and makes decisions with Monte-Carlo Tree Search method [2]. The second algorithm adopts Decision Tree Search method (DTS) to accelerate the search process while maintaining efficiency [3]. Our overarching objective is to provide computationally effective approaches that can be deployed to train deep neural networks robust against perturbations in data. We illustrate the robustness with these algorithms by studying the resistances to adversarial examples obtained in the context of the MNIST and CIFAR10 datasets. For MNIST, the results showed an average training efforts saving of 21.1\% when compared to Projected Gradient Descent (PGD) and 28.3\% when compared to Fast Gradient Sign Methods (FGSM). For CIFAR10, we obtained an average improvement of efficiency of 9.8\% compared to PGD and 13.8\% compared to FGSM. The results suggest that these two methods here introduced are not only robust to norm-constrained perturbations but also efficient during training. In regards to transferability of defences, our experiments [4] reveal that across different network architectures, across a variety of attack methods from white-box to black-box and across various datasets including MNIST and CIFAR10, our algorithms outperform other state-of-the-art methods, e.g., PGD and FGSM. Furthermore, the derived attacks and robust models obtained on our framework are reusable in the sense that the same norm-constrained perturbations can facilitate robust training across different networks. Lastly, we investigate the robustness of intra-technique and cross-technique transferability and the relations with different impact factors from adversarial strength to network capacity. The results suggest that known attacks on the resulting models are less transferable than those models trained by other state-of-the-art attack algorithms. Our results suggest that exploiting these tree search frameworks can result in significant improvements in the robustness of deep neural networks while saving computational cost on robust training. This paves the way for several future directions, both algorithmic and theoretical, as well as numerous applications to establish the robustness of deep neural networks with increasing trust and safety.Open Acces
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