Full Stack Application Generation for Insurance Sales based on Product Models

The insurance market is segregated in various lines-of-business such as Life, Health, Property & Casualty, among others. This segregation allows product engineers to focus on the rules and details of a speci c insurance area. However, having di erent conceptual models leads to an additional complexity when a generic presentation layer application has to be continuously adapted to work with these distinct models. With the objective to streamline these continuous adaptations in an existent presentation layer, this work investigates and proposes the usage of code generators to allow a complete application generation, able to communicate with the given insurance product model. Therefore, this work compares and combines di erent code generation tools to accomplish the desired application generation. During this project, it is chosen an existing framework to create several software layers and respective components such as necessary classes to represent the Domain Model ; database mappings; Service layer; REST Application Program Interface (API); and a rich javascript-based presentation layer. As a conclusion, this project demonstrates that the proposed tool can generate the application already adapted and able to communicate with the provided conceptual model. Proving that this autonomous process is faster than the current manual development processes to adapt a presentation layer to an Insurance product model.O mercado segurador encontra-se dividido em várias linhas-de-negócio (e.g. Vida, Saúde, Propriedade) que têm naturalmente, diferentes modelos conceptuais para a representação dos seus produtos. Esta panóplia de modelos leva a uma dificuldade acrescida quando o software de camada de apresentação tem que ser constantemente adaptado aos novos modelos bem como ás alterações efetuadas aos modelos existentes. Com o intuito de suprimir esta constante adaptação a novos modelos, este trabalho visa a exploração e implementação de geradores de código de forma a permitir gerar toda uma aplicação que servirá de camada de apresentação ao utilizador para um dado modelo. Assim, este trabalho expõe e compara várias ferramentas de geração de código actualmente disponíveis, de forma a que seja escolhida a mais eficaz para responder aos objectivos estabelecidos. É então selecionada a ferramenta mais promissora e capaz de gerar vários componentes de software, gerando o seu modelo de domínio, mapeamento com as respectivas tabelas de base de dados, uma camada de lógica de negócio, serviços REST bem como uma camada de apresentação. Como conclusão, este trabalho apresenta uma solução que é capaz de se basear num modelo proveniente do sistema de modelação de produto e assim gerar completamente a aplicação de camada de apresentação desejada para esse mesmo modelo. Permitindo assim, um processo mais rápido e eficaz quando comparado com os processos manuais de desenvolvimento e de adaptação de código-fonte existentes

Le nuage de point intelligent

Discrete spatial datasets known as point clouds often lay the groundwork for decision-making applications. E.g., we can use such data as a reference for autonomous cars and robot’s navigation, as a layer for floor-plan’s creation and building’s construction, as a digital asset for environment modelling and incident prediction... Applications are numerous, and potentially increasing if we consider point clouds as digital reality assets. Yet, this expansion faces technical limitations mainly from the lack of semantic information within point ensembles. Connecting knowledge sources is still a very manual and time-consuming process suffering from error-prone human interpretation. This highlights a strong need for domain-related data analysis to create a coherent and structured information. The thesis clearly tries to solve automation problematics in point cloud processing to create intelligent environments, i.e. virtual copies that can be used/integrated in fully autonomous reasoning services. We tackle point cloud questions associated with knowledge extraction – particularly segmentation and classification – structuration, visualisation and interaction with cognitive decision systems. We propose to connect both point cloud properties and formalized knowledge to rapidly extract pertinent information using domain-centered graphs. The dissertation delivers the concept of a Smart Point Cloud (SPC) Infrastructure which serves as an interoperable and modular architecture for a unified processing. It permits an easy integration to existing workflows and a multi-domain specialization through device knowledge, analytic knowledge or domain knowledge. Concepts, algorithms, code and materials are given to replicate findings and extend current applications.Les ensembles discrets de données spatiales, appelés nuages de points, forment souvent le support principal pour des scénarios d’aide à la décision. Par exemple, nous pouvons utiliser ces données comme référence pour les voitures autonomes et la navigation des robots, comme couche pour la création de plans et la construction de bâtiments, comme actif numérique pour la modélisation de l'environnement et la prédiction d’incidents... Les applications sont nombreuses et potentiellement croissantes si l'on considère les nuages de points comme des actifs de réalité numérique. Cependant, cette expansion se heurte à des limites techniques dues principalement au manque d'information sémantique au sein des ensembles de points. La création de liens avec des sources de connaissances est encore un processus très manuel, chronophage et lié à une interprétation humaine sujette à l'erreur. Cela met en évidence la nécessité d'une analyse automatisée des données relatives au domaine étudié afin de créer une information cohérente et structurée. La thèse tente clairement de résoudre les problèmes d'automatisation dans le traitement des nuages de points pour créer des environnements intelligents, c'est-àdire des copies virtuelles qui peuvent être utilisées/intégrées dans des services de raisonnement totalement autonomes. Nous abordons plusieurs problématiques liées aux nuages de points et associées à l'extraction des connaissances - en particulier la segmentation et la classification - la structuration, la visualisation et l'interaction avec les systèmes cognitifs de décision. Nous proposons de relier à la fois les propriétés des nuages de points et les connaissances formalisées pour extraire rapidement les informations pertinentes à l'aide de graphes centrés sur le domaine. La dissertation propose le concept d'une infrastructure SPC (Smart Point Cloud) qui sert d'architecture interopérable et modulaire pour un traitement unifié. Elle permet une intégration facile aux flux de travail existants et une spécialisation multidomaine grâce aux connaissances liée aux capteurs, aux connaissances analytiques ou aux connaissances de domaine. Plusieurs concepts, algorithmes, codes et supports sont fournis pour reproduire les résultats et étendre les applications actuelles.Diskrete räumliche Datensätze, so genannte Punktwolken, bilden oft die Grundlage für Entscheidungsanwendungen. Beispielsweise können wir solche Daten als Referenz für autonome Autos und Roboternavigation, als Ebene für die Erstellung von Grundrissen und Gebäudekonstruktionen, als digitales Gut für die Umgebungsmodellierung und Ereignisprognose verwenden... Die Anwendungen sind zahlreich und nehmen potenziell zu, wenn wir Punktwolken als Digital Reality Assets betrachten. Allerdings stößt diese Erweiterung vor allem durch den Mangel an semantischen Informationen innerhalb von Punkt-Ensembles auf technische Grenzen. Die Verbindung von Wissensquellen ist immer noch ein sehr manueller und zeitaufwendiger Prozess, der unter fehleranfälliger menschlicher Interpretation leidet. Dies verdeutlicht den starken Bedarf an domänenbezogenen Datenanalysen, um eine kohärente und strukturierte Information zu schaffen. Die Arbeit versucht eindeutig, Automatisierungsprobleme in der Punktwolkenverarbeitung zu lösen, um intelligente Umgebungen zu schaffen, d.h. virtuelle Kopien, die in vollständig autonome Argumentationsdienste verwendet/integriert werden können. Wir befassen uns mit Punktwolkenfragen im Zusammenhang mit der Wissensextraktion - insbesondere Segmentierung und Klassifizierung - Strukturierung, Visualisierung und Interaktion mit kognitiven Entscheidungssystemen. Wir schlagen vor, sowohl Punktwolkeneigenschaften als auch formalisiertes Wissen zu verbinden, um schnell relevante Informationen mithilfe von domänenzentrierten Grafiken zu extrahieren. Die Dissertation liefert das Konzept einer Smart Point Cloud (SPC) Infrastruktur, die als interoperable und modulare Architektur für eine einheitliche Verarbeitung dient. Es ermöglicht eine einfache Integration in bestehende Workflows und eine multidimensionale Spezialisierung durch Gerätewissen, analytisches Wissen oder Domänenwissen. Konzepte, Algorithmen, Code und Materialien werden zur Verfügung gestellt, um Erkenntnisse zu replizieren und aktuelle Anwendungen zu erweitern

International Conference of Territorial Intelligence, Alba Iulia 2006. Vol.1, Papers on region, identity and sustainable development (deliverable 12 of caENTI, project funded under FP6 research program of the European Union), Aeternitas, Alba Iulia, 2007

GIRARDOT J.-J., PASCARU M., ILEANA I., 2007A.deliverable 12 of caENTIThese acts gather the communications of the International Conference of Territorial Intelligence that took place in ALBA IULIA in Romania, from September, the 20th to September, the 22nd 2006. This conference was the fourth conference of territorial intelligence, but the conference of ALBA IULIA is the first one that took place in the CAENTI, Coordination Action of the European Network of Territorial Intelligence, framework. Consequently, it has a particular organization. A part is devoted to the presentation of the CAENTI research activities and of their prospects. The CAENTI specific communications are published in another volume

Multikonferenz Wirtschaftsinformatik (MKWI) 2016: Technische Universität Ilmenau, 09. - 11. März 2016; Band III

Übersicht der Teilkonferenzen Band III • Service Systems Engineering • Sicherheit, Compliance und Verfügbarkeit von Geschäftsprozessen • Smart Services: Kundeninduzierte Kombination komplexer Dienstleistungen • Strategisches IT-Management • Student Track • Telekommunikations- und Internetwirtschaft • Unternehmenssoftware – quo vadis? • Von der Digitalen Fabrik zu Industrie 4.0 – Methoden und Werkzeuge für die Planung und Steuerung von intelligenten Produktions- und Logistiksystemen • Wissensmanagemen

Advances in Manufacturing Technology XXVII: Proceedings of the 11th International Conference on Manufacturing Research (ICMR2013)

ICMR2013 was organised by Cranfield University on the 19-20 September 2013. The conference focuses on any aspects of product development, manufacturing technology, manufacturing systems, information systems and digital technologies. It provides an excellent avenue for researchers to present state-of-the-art multidisciplinary manufacturing research and exchange ideas. In addition to the four keynote speeches from Airbus and Rolls-Royce and three invited presentations, there are 108 papers in these proceedings. These papers are split into 24 technical sessions. The International Conference on Manufacturing Research is a major event for academics and industrialists engaged in manufacturing research. Held annually in the UK since the late 1970s, the conference is renowned as a friendly and inclusive environment that brings together a broad community of researchers who share a common goal; developing and managing the technologies and operations that are key to sustaining the success of manufacturing businesses. For over two decades, ICMR has been the main manufacturing research conference organised in the UK, successfully bringing researchers, academics and industrialists together to share their knowledge and experiences. Initiated a National Conference by the Consortium of UK University Manufacturing Engineering Heads (COMEH), it became an International Conference in 2003. COMEH is an independent body established in 1978. Its main aim is to promote manufacturing engineering education, training and research. To achieve this, the Consortium maintains a close liaison with government bodies concerned with the training and continuing development of professional engineers, while responding to the appropriate consultative and discussion documents and other initiatives. COMEH is represented on the Engineering Professor’s council (EPC) and it organises and supports national manufacturing engineering education research conferences and symposia