Exploiting Information-centric Networking to Federate Spatial Databases

This paper explores the methodologies, challenges, and expected advantages related to the use of the information-centric network (ICN) technology for federating spatial databases. ICN services allow simplifying the design of federation procedures, improving their performance, and providing so-called data-centric security. In this work, we present an architecture that is able to federate spatial databases and evaluate its performance using a real data set coming from OpenStreetMap within a heterogeneous federation formed by MongoDB and CouchBase spatial database systems

Detecting Weak Signals of the Future: A System Implementation Based on Text Mining and Natural Language Processing

[EN] Organizations, companies and start-ups need to cope with constant changes on the market which are difficult to predict. Therefore, the development of new systems to detect significant future changes is vital to make correct decisions in an organization and to discover new opportunities. A system based on business intelligence techniques is proposed to detect weak signals, that are related to future transcendental changes. While most known solutions are based on the use of structured data, the proposed system quantitatively detects these signals using heterogeneous and unstructured information from scientific, journalistic and social sources, applying text mining to analyze the documents and natural language processing to extract accurate results. The main contributions are that the system has been designed for any field, using different input datasets of documents, and with an automatic classification of categories for the detected keywords. In this research paper, results from the future of remote sensors are presented. Remote sensing services are providing new applications in observation and analysis of information remotely. This market is projected to witness a significant growth due to the increasing demand for services in commercial and defense industries. The system has obtained promising results, evaluated with two different methodologies, to help experts in the decision-making process and to discover new trends and opportunities.This research is partially supported by EIT Climate-KIC of the European Institute of Technology (project EIT Climate-KIC Accelerator-TC_3.1.5_190607_P066-1A) and InnoCENS from Erasmus + (573965-EPP-1-2016-1-SE-EPPKA2-CBHE-JP).Griol-Barres, I.; Milla, S.; Cebrián Ferriols, AJ.; Fan, H.; Millet Roig, J. (2020). Detecting Weak Signals of the Future: A System Implementation Based on Text Mining and Natural Language Processing. 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Development of a methodological approach for hybrid SQL/NOSQL database design and usage

Ова дисертација је настала из потребе теоретског, развојног и практичног решавања проблема пројектовања и коришћења хибридне SQL/NoSQL базе података. Различити типови база података, како је описано у наставку, садрже специфичности које је потребно узети у обзир приликом развоја методолошког приступа за реализацију процеса пројектовања и коришћења. Дисертација је написана као резултат спровођења процеса научног истраживања, прегледа области истраживања, анализе постојећих решења и приступа, развоја нових приступа пројектовања и коришћења (са свим њиховим саставним деловима), примене новоразвијених приступа на примере из праксе, тестирања изабраних аспеката перформанси (по одређеним критеријумима) и компаративне анализе постигнутих резултата хибридне базе података пројектоване применом новог приступа и „традиционално“ пројектоване базе података. Циљ ове докторске дисертације је био развој новог приступа за пројектовање хибридне SQL/NoSQL базе података и интеграцију и униформно коришћење њених компоненти (SQL и NoSQL база података). У докторској дисертацији су анализирани погодни критеријуми за доношење одлуке о оправданости преласка са постојеће SQL базе података на хибридну базу података. Укључивање аспеката пројектовања нових и редизајна постојећих база података у новоразвијени приступ, проширио је опсег његове могуће примене. За потребе приступа развијена је и нова архитектура, која је омогућила да се над целокупном хибридном базом података (и свим базама података које чине њене саставне компоненте) управља мета подацима, правилима интегритета, правилима мапирања и извршавањем наредби као над јединственом логичком базом податка.This dissertation has originated out of the need for theoretical, developmental and practical solving of the issue of the design and integral and uniform usage of hybrid SQL/NoSQL databases. As described in the course of this dissertation, various types of databases contain specificities that have to be taken into account when developing a methodological approach for the realization of aforementioned processes of database design and usage. The dissertation is written based on many activities. It was driven by conducting scientific research, review of research areas, analysis of existing solutions and approaches. Besides that, dissertation included development of new approach for design and usage (with all their integral parts), application of newly developed approach to examples from practice, testing of chosen aspects of performances (based on certain criteria) and comparative analysis of achieved results of hybrid database developed by applying a new approach and ‘traditionally’ designed database. The aim of this doctoral dissertation was the development of a new approach for the design of hybrid SQL/NoSQL database and integration and uniform usage of its components (SQL and NoSQL databases). A criterion for making a decision on the justification of transition from existing SQL database to hybrid database has been defined in this dissertation. Including aspect of new database design, as well as including aspect of existing database redesign expanded the scope of newly developed approach. For the approach needs, a new architecture has also been developed, which enabled managing metadata, integrity rules, mapping rules and statement execution over the entire hybrid database (including all its component databases) as over a unique logical database

Modelling of a System for the Detection of Weak Signals Through Text Mining and NLP. Proposal of Improvement by a Quantum Variational Circuit

Tesis por compendio[ES] En esta tesis doctoral se propone y evalúa un sistema para detectar señales débiles (weak signals) relacionadas con cambios futuros trascendentales. Si bien la mayoría de las soluciones conocidas se basan en el uso de datos estructurados, el sistema propuesto detecta cuantitativamente estas señales utilizando información heterogénea y no estructurada de fuentes científicas, periodísticas y de redes sociales. La predicción de nuevas tendencias en un medio tiene muchas aplicaciones. Por ejemplo, empresas y startups se enfrentan a cambios constantes en sus mercados que son muy difíciles de predecir. Por esta razón, el desarrollo de sistemas para detectar automáticamente cambios futuros significativos en una etapa temprana es relevante para que cualquier organización tome decisiones acertadas a tiempo. Este trabajo ha sido diseñado para obtener señales débiles del futuro en cualquier campo dependiendo únicamente del conjunto de datos de entrada de documentos. Se aplican técnicas de minería de textos y procesamiento del lenguaje natural para procesar todos estos documentos. Como resultado, se obtiene un mapa con un ranking de términos, una lista de palabras clave clasificadas automáticamente y una lista de expresiones formadas por múltiples palabras. El sistema completo se ha probado en cuatro sectores diferentes: paneles solares, inteligencia artificial, sensores remotos e imágenes médicas. Este trabajo ha obtenido resultados prometedores, evaluados con dos metodologías diferentes. Como resultado, el sistema ha sido capaz de detectar de forma satisfactoria nuevas tendencias en etapas muy tempranas que se han vuelto cada vez más importantes en la actualidad. La computación cuántica es un nuevo paradigma para una multitud de aplicaciones informáticas. En esta tesis doctoral también se presenta un estudio de las tecnologías disponibles en la actualidad para la implementación física de qubits y puertas cuánticas, estableciendo sus principales ventajas y desventajas, y los marcos disponibles para la programación e implementación de circuitos cuánticos. Con el fin de mejorar la efectividad del sistema, se describe un diseño de un circuito cuántico basado en máquinas de vectores de soporte (SVM) para la resolución de problemas de clasificación. Este circuito está especialmente diseñado para los ruidosos procesadores cuánticos de escala intermedia (NISQ) que están disponibles actualmente. Como experimento, el circuito ha sido probado en un computador cuántico real basado en qubits superconductores por IBM como una mejora para el subsistema de minería de texto en la detección de señales débiles. Los resultados obtenidos con el experimento cuántico muestran también conclusiones interesantes y una mejora en el rendimiento de cerca del 20% sobre los sistemas convencionales, pero a su vez confirman que aún se requiere un desarrollo tecnológico continuo para aprovechar al máximo la computación cuántica.[CA] En aquesta tesi doctoral es proposa i avalua un sistema per detectar senyals febles (weak signals) relacionats amb canvis futurs transcendentals. Si bé la majoria de solucions conegudes es basen en l'ús de dades estructurades, el sistema proposat detecta quantitativament aquests senyals utilitzant informació heterogènia i no estructurada de fonts científiques, periodístiques i de xarxes socials. La predicció de noves tendències en un medi té moltes aplicacions. Per exemple, empreses i startups s'enfronten a canvis constants als seus mercats que són molt difícils de predir. Per això, el desenvolupament de sistemes per detectar automàticament canvis futurs significatius en una etapa primerenca és rellevant perquè les organitzacions prenguen decisions encertades a temps. Aquest treball ha estat dissenyat per obtenir senyals febles del futur a qualsevol camp depenent únicament del conjunt de dades d'entrada de documents. S'hi apliquen tècniques de mineria de textos i processament del llenguatge natural per processar tots aquests documents. Com a resultat, s'obté un mapa amb un rànquing de termes, un llistat de paraules clau classificades automàticament i un llistat d'expressions formades per múltiples paraules. El sistema complet s'ha provat en quatre sectors diferents: panells solars, intel·ligència artificial, sensors remots i imatges mèdiques. Aquest treball ha obtingut resultats prometedors, avaluats amb dues metodologies diferents. Com a resultat, el sistema ha estat capaç de detectar de manera satisfactòria noves tendències en etapes molt primerenques que s'han tornat cada cop més importants actualment. La computació quàntica és un paradigma nou per a una multitud d'aplicacions informàtiques. En aquesta tesi doctoral també es presenta un estudi de les tecnologies disponibles actualment per a la implementació física de qubits i portes quàntiques, establint-ne els principals avantatges i desavantatges, i els marcs disponibles per a la programació i implementació de circuits quàntics. Per tal de millorar l'efectivitat del sistema, es descriu un disseny d'un circuit quàntic basat en màquines de vectors de suport (SVM) per resoldre problemes de classificació. Aquest circuit està dissenyat especialment per als sorollosos processadors quàntics d'escala intermèdia (NISQ) que estan disponibles actualment. Com a experiment, el circuit ha estat provat en un ordinador quàntic real basat en qubits superconductors per IBM com una millora per al subsistema de mineria de text. Els resultats obtinguts amb l'experiment quàntic també mostren conclusions interessants i una millora en el rendiment de prop del 20% sobre els sistemes convencionals, però a la vegada confirmen que encara es requereix un desenvolupament tecnològic continu per aprofitar al màxim la computació quàntica.[EN] In this doctoral thesis, a system to detect weak signals related to future transcendental changes is proposed and tested. While most known solutions are based on the use of structured data, the proposed system quantitatively detects these signals using heterogeneous and unstructured information from scientific, journalistic, and social sources. Predicting new trends in an environment has many applications. For instance, companies and startups face constant changes in their markets that are very difficult to predict. For this reason, developing systems to automatically detect significant future changes at an early stage is relevant for any organization to make right decisions on time. This work has been designed to obtain weak signals of the future in any field depending only on the input dataset of documents. Text mining and natural language processing techniques are applied to process all these documents. As a result, a map of ranked terms, a list of automatically classified keywords and a list of multi-word expressions are obtained. The overall system has been tested in four different sectors: solar panels, artificial intelligence, remote sensing, and medical imaging. This work has obtained promising results that have been evaluated with two different methodologies. As a result, the system was able to successfully detect new trends at a very early stage that have become more and more important today. Quantum computing is a new paradigm for a multitude of computing applications. This doctoral thesis also presents a study of the technologies that are currently available for the physical implementation of qubits and quantum gates, establishing their main advantages and disadvantages and the available frameworks for programming and implementing quantum circuits. In order to improve the effectiveness of the system, a design of a quantum circuit based on support vector machines (SVMs) is described for the resolution of classification problems. This circuit is specially designed for the noisy intermediate-scale quantum (NISQ) computers that are currently available. As an experiment, the circuit has been tested on a real quantum computer based on superconducting qubits by IBM as an improvement for the text mining subsystem in the detection of weak signals. The results obtained with the quantum experiment show interesting outcomes with an improvement of close to 20% better performance than conventional systems, but also confirm that ongoing technological development is still required to take full advantage of quantum computing.Griol Barres, I. (2022). Modelling of a System for the Detection of Weak Signals Through Text Mining and NLP. Proposal of Improvement by a Quantum Variational Circuit [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/183029TESISCompendi