Submitted by Caio Vítor Beojone null (beojone@hotmail.com) on 2017-10-25T17:47:50Z No. of bitstreams: 1 Caio Vitor Beojone - Dissertação.pdf: 10092472 bytes, checksum: 470115087a1c1f987a7a8e2cffec7cd4 (MD5) / Approved for entry into archive by Monique Sasaki (sayumi_sasaki@hotmail.com) on 2017-10-31T16:52:11Z (GMT) No. of bitstreams: 1 beojone_cv_me_bauru.pdf: 10092472 bytes, checksum: 470115087a1c1f987a7a8e2cffec7cd4 (MD5) / Made available in DSpace on 2017-10-31T16:52:11Z (GMT). No. of bitstreams: 1 beojone_cv_me_bauru.pdf: 10092472 bytes, checksum: 470115087a1c1f987a7a8e2cffec7cd4 (MD5) Previous issue date: 2017-10-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Vários Sistemas de Atendimento Emergenciais (SAE’s) sofrem com as variações diárias da demanda e da disponibilidade das ambulâncias. Nesses sistemas pode haver flutuação do desempenho ao longo do dia devido, por exemplo, a mudança no número de servidores e nas taxas de chegada, levando à necessidade de considerar explicitamente tais variações em uma extensão ao modelo hipercubo ainda não explorada na literatura. Como ocorre em alguns SAE’s, as ambulâncias melhor equipadas são reservadas para o atendimento exclusivo de chamados com risco de vida. Dessa maneira, a política de despacho pode ser diferenciada com a finalidade de reservar totalmente o atendimento de alguns servidores para certas gravidades de ocorrências. Além disso, somam-se à natureza aleatória desses sistemas, como por exemplo, as incertezas da disponibilidade das ambulâncias, a chegada de um novo chamado e sua localização. Nesse contexto, os objetivos do presente estudo são: (i) estender o modelo hipercubo de filas para reserva total de capacidade, dependendo do tipo do chamado; (ii) estender o modelo hipercubo de filas para torná-lo mais eficiente computacionalmente, sem haver perda de precisão durante a modelagem e resolução; e (iii) propor uma abordagem baseada no modelo hipercubo não-estacionário para organização do trabalho das ambulâncias em qualquer momento do dia. Para verificar a viabilidade e a aplicabilidade dessas abordagens, é realizado um estudo de caso no SAMU da cidade de Bauru (SAMU-Bauru) que, além de reservar suas ambulâncias avançadas para ocorrências mais graves, é afetado pelas variações diárias na demanda e disponibilidade das ambulâncias. Além da configuração original do SAMU-Bauru, estudada em duas etapas, foram analisados um total de quatro cenários alternativos que consideram questões importantes: o impacto do aumento na demanda do período mais congestionado; a mitigação desse impacto incluindo uma nova ambulância; a alteração do horário das pausas diárias; e o impacto de aumentos na demanda em horários específicos do dia. Foram calculadas importantes medidas de desempenho para cada cenário como a carga de trabalho, tempos médios de espera e tempos médios de resposta. Os resultados mostram que as extensões realizadas no modelo hipercubo são capazes de analisar satisfatoriamente sistemas como o SAMU-Bauru, além de possibilitar a criação e mensuração de propostas de melhorias nos níveis táticos e operacionais. / Many Emergency Service Systems face daily variations on demand and ambulance availability. These systems may suffer, for example, performance fluctuations throughout the day, changes on the number of servers and on arrival rates, leading to the need to explicitly consider such variations in a hypercube model extension not yet explored in the literature. As occurs in some SAMU’s, which reserve their best equipped ambulances to exclusively serve life-threating requests. Therefore, the dispatch policy can be differentiated in order to completely reserve the service of some ambulances to more severe requests. These problems add up to the random nature of these systems with uncertainties upon ambulance availability or the arrival of a new request and its location. Thus, this study aims to: (i) extend the hypercube queueing model to be able to capture the complete capacity reservation of advanced ambulances, depending on the request classification; (ii) extend the hypercube model in order to make it more computationally efficient, without losing any information during modeling and resolution. (iii) propose an approach based on nonstationary hypercube queueing model to organize the operation of ambulances at any time of the day. To verify the feasibility of these approaches, a case study is carried out on the SAMU from Bauru city (SAMU-Bauru), which, in addition to the advanced ambulance reservation for life-threating requests, is affected by daily variations in demand and ambulance availability. In addition to the original configuration of SAMU-Bauru, studied on a two-step approach, we studied a total of four alternative scenarios that exploited important matters as: the impact of average demand increase on the congestion peak; mitigation of this impact by including a new ambulance; changing the schedule of daily breaks; and the impact of increases in the demand at specific hours of the day. We calculated important performance measures for each scenario, such as workload, mean waiting times and mean response times. Results show that the proposed extensions to the hypercube model are capable of satisfactorily analyze systems such as SAMU-Bauru, besides making it possible to create and to measure improvements proposals in tactical and operational levels.

Im Berliner Zentrum für Craniofaciale Fehlbildungen in der Klinik für Mund-, Kiefer- und Gesichtschirurgie- Klinische Navigation und Robotik der Charité Campus Virchow-Klinikum in Berlin wird der mobile CT Philips Tomoscan M in die Implantation von extraoralen kraniofazialen Knochenankern zur Epithesenfixierung eingebunden. Es stellt sich dabei die Frage nach der Ortstreue und Dimensionstreue von knöchernen Strukturen und extraoralen kraniofazialen Implantaten im CT. Ein Knochenphantom dient der Vermessung von Lochpaaren verschiedener Abstände, einer Knochenschraube, eines Abutments und eines Magneten unter variierten Scanparametern durch Werkzeuge der Scannerkonsole. Die Ortstreue von Löchern und Implantaten liegt in >99% im Intervall ±0,2mm. Fenstereinstellungen haben einen geringen Einfluss auf Lochabstände. Lochdurchmesser zeigen unter Anhebung des Window Level (WL) Korrelation (r2=0,776) und eine lineare Größenzunahme bei maßstabgerechter Skalierung, variieren aber wenig unter Variation der Window Width (WW). Alle Implantate werden zu groß abgebildet, außer in extremen Fenstereinstellungen. Implantatdimensionen nehmen bei maßstabgerechter Skalierung mit höheren WL linear ab. Die Variabilität der Darstellung nimmt mit dichterem Implantatmaterial ab. Kontaktflächen von Implantaten mit Gewebe sind im CT nicht beurteilbar. / In the Berlin Centre for Craniofacial Malformations at the Clinic for Oromaxillofacial Surgery of the Charité, Campus Virchow- Clinic in Berlin, a mobile CT Scanner Philips Tomoscan M is integrated into the process of extraoral bone anchor implantation for prosthesis fixture. With implementation of the scanner, accuracy of localisation and dimensional accuracy of bony structures and implants have been questioned. A bone phantom is used for measuring distances between holes, hole diameters and dimensions of an implant fixture, an abutment and a magnet with measuring tools of the scanner under variation of scan parameters. Localisation accuracy of holes and implants is found in >99% within ±0.2mm. Window settings have little influence on hole distances. Diameters show linear growth at standardized scaling and correlation with window level augmentation (r2=.776). Little Variation of diameters is found with variation of window width. All Implants are magnified. Implant dimensions diminish with window level augmentation at standardized scaling. Variability of dimension decreases with more radio opaque implant material. Implant contact with tissues cannot be assessed in CT scans.

Dans cette thèse, nous proposons une méthodologie basée sur les modèles pour gérer la complexité de la conception des systèmes autonomiques cognitifs intégrant des objets connectés. Cette méthodologie englobe un ensemble de patrons de conception dont nous avons défini pour modéliser la coordination dynamique des processus autonomiques pour gérer l’évolution des besoins du système, et pour enrichir les systèmes avec des propriétés cognitives qui permettent de comprendre les données et de générer des nouvelles connaissances. De plus, pour gérer les problèmes reliés à la gestion des big data et à la scalabilité du système lors du déploiement des processus, nous proposons une plate-forme sémantique supportant le traitement des grandes quantités de données afin d’intégrer des sources de données distribuées et hétérogènes déployées sur le cloud pour générer des connaissances qui seront exposées en tant que service (KaaS). Comme application de nos contributions, nous proposons un système cognitif prescriptif pour la gestion du plan de traitement du patient. Ainsi, nous élaborons des modèles ontologiques décrivant les capteurs et le contexte du patient, ainsi que la connaissance médicale pour la prise de décision. Le système proposé est évalué de point de vue clinique en collaborant avec des experts médicaux, et de point de vue performance en proposant des différentes configurations dans le KaaS. / In this thesis, we propose a collaborative model driven methodology for designing Autonomic Cognitive IoT systems to deal with IoT design complexity. We defined within this methodology a set of autonomic cognitive design patterns that aim at (1) delineating the dynamic coordination of the autonomic processes to deal with the system's context changeability and requirements evolution at run-time, and (2) adding cognitive abilities to IoT systems to understand big data and generate new insights. To address challenges related to big data and scalability, we propose a generic semantic big data platform that aims at integrating heterogeneous distributed data sources deployed on the cloud and generating knowledge that will be exposed as a service (Knowledge as a Service--KaaS). As an application of the proposed contributions, we instantiated and combined a set of patterns for the development of prescriptive cognitive system for the patient treatment management. Thus, we elaborated two ontological models describing the wearable devices and the patient context as well as the medical knowledge for decision-making. The proposed system is evaluated from the clinical prescriptive through collaborating with medical experts, and from the performance perspective through deploying the system within the KaaS following different configurations