The market of IOT devices continues to grow at a rapid speed as well as constrained wireless sensor networks. Today, the main network paradigm is host centric where a users have to specify which host they want to receive their data from. Information-centric networking is a new paradigm for the future internet, which is based on named data instead of named hosts. With ICN, a user needs to send a request for a perticular data in order to retrieve it. When sent, any participant in the network, router or server, containing the data will respond to the request. In order to achieve low latency between data creation and its consumption, as well as being able to follow data which is sequentially produced at a fixed rate, an algortihm was developed. This algortihm calculates and determines when to send the next interest message towards the sensor. It uses a ‘one time subscription’ approach to send its interest message in advance of the creation of the data, thereby enabling a low latency from data creation to consumption. The result of this algorithm shows that a consumer can retrieve the data with minimum latency from its creation by the sensor over an extended period of time, without using a publish/subscribe system such as MQTT or similar which pushes their data towards their consumers. The performance evaluation carried out which analysed the Content Centric Network application on the sensor shows that the application has little impact on the overall round trip time in the network. Based on the results, this thesis concluded that the ICN paradigm, together with a ’one-time subscription’ model, can be a suitable option for communication within the IoT domain where consumers ask for sequentially produced data.

[pt] A segmentação semântica das estruturas anatômicas em imagens de mamografia desempenha um papel significativo no apoio da análise médica. Esta tarefa pode ser abordada com o uso de um modelo de aprendizado de máquina, que deve ser capaz de identificar e delinear corretamente as estruturas de interesse tais como papila, tecido fibroglandular, músculo peitoral e tecido gorduroso. No entanto, a segmentação de estruturas pequenas como papila e peitoral é frequentemente um desafio. Sendo o maior desafio o reconhecimento ou deteção do músculo peitoral na vista craniocaudal (CC), devido ao seu tamanho variável, possíveis ausências e sobreposição de tecido fibroglandular. Para enfrentar esse desafio, este trabalho propõe uma abordagem centrada em dados para melhorar o desempenho do modelo de segmentação na papila mamária e no músculo peitoral. Especificamente, aprimorando os dados de treinamento e as anotações em duas etapas. A primeira etapa é baseada em modificações nas anotações. Foram desenvolvidos algoritmos para buscar automaticamente anotações fora do comum dependendo da sua forma. Com estas anotações encontradas, foi feita uma revisão e correção manual. A segunda etapa envolve um downsampling do conjunto de dados, reduzindo as amostras de imagens do conjunto de treinamento. Foram analisados os casos de falsos positivos e falsos negativos, identificando as imagens que fornecem informações confusas, para posteriormente removê-las do conjunto. Em seguida, foram treinados modelos usando os dados de cada etapa e foram obtidas as métricas de classificação para o músculo peitoral em vista CC e o IoU para cada estrutura nas vistas CC e MLO (Mediolateral Oblíqua). Os resultados do treinamento mostram uma melhora progressiva na identificação e segmentação do músculo peitoral em vista CC e uma melhora na papila em vista MLO, mantendo as métricas para as demais estruturas. / [en] The semantic segmentation of anatomical structures in mammography images plays a significant role in supporting medical analysis. This task can be approached using a machine learning model, which must be capable of identifying and accurately delineating the structures. However, segmentation of small structures such as nipple and pectoral is often challenging. Especially in there cognition or detection of the pectoral muscle in the craniocaudal (CC) view,due to its variable size, possible absences and overlapping of fibroglandular tissue.To tackle this challenge, this work proposes a data-centric approach to improvethe segmentation model s performance on the mammary papilla and pectoral muscle. Specifically, enhancing the training data and annotations in two stages.The first stage is based on modifications to the annotations. Algorithms were developed to automatically search for uncommon annotations dependingon their shape. Once these annotations were found, a manual review and correction were performed.The second stage involves downsampling the dataset, reducing the image samples in the training set. Cases of false positives and false negatives were analyzed, identifying images that provide confusing information, which were subsequently removed from the set. Next, models were trained using the data from each stage, and classification metrics were obtained for the pectoral muscle in the CC view and IoU for each structure in CC and MLO (mediolateral oblique) views. The training results show a progressive improvement in the identification and segmentation of the pectoral muscle in the CC view and an enhancement in the mammary papilla in the MLO view, while maintaining segmentation metricsfor the other structures.

Thesis (M.S. in Systems Engineering)--Naval Postgraduate School, June 2010. / Thesis Advisor(s): Goshorn, Rachel ; Goshorn, Deborah. "June 2010." Description based on title screen as viewed on June 24, 2010. Author(s) subject terms: Anomaly Detection, Artificial Intelligence, Automation, Behavior Analysis, Distributed Artificial Intelligence, Intelligence-Surveillance-Reconnaissance, Maritime Domain Awareness, Maritime Force Protection, Multi-agent Systems, Network-centric Operations, Network-centric Systems Engineering, Network-centric Warfare, Smart Sensor Networks, Systems Engineering, Systems Integration, System of Systems. Includes bibliographical references (p. 209-212). Also available in print.

Automated solid modeling, integrated with computational fluid dynamics (CFD) and optimization of a 3D jet turbine engine has never been accomplished. This is due mainly to the computational power required, and the lack of associative parametric modeling tools and techniques necessary to adjust and optimize the design. As an example, the fluid domain of a simple household fan with three blades may contain 500,000 elements per blade passage. Therefore, a complete turbine engine that includes many stages, with sets of thirty or more blades each, will have hundreds of millions of elements. The fluid domains associated with each blade creates a nearly incomprehensible challenge. One method of organizing and passing geometric and non-geometric data is through the utilization of knowledge based engineering (KBE). The focus of this thesis will be the development of a set of techniques utilizing KBE principles to analyze an assembly which includes multiple fluid domains. This comprehensive system will be referred to as the Parametric Optimization Design System (PODS).

Content Centric Networking (CCN) est une architecture pour l'Internet du futur. CCN inclut des fonctionnalités de cache dans tous les noeuds du réseau. Son efficacité dépend largement de la performance de ses stratégies de cache. C'est pour cela que plusieurs études proposent des nouvelles stratégies de cache pour améliorer la performance d'un réseau CCN. Cependant parmi toutes ces stratégies, ce n'est pas évident de décider laquelle fonctionne le mieux. Il manque un environnement commun pour comparer ces stratégies. De plus, il n'est pas certain que ces approches soient les meilleures alternatives pour améliorer la performance du réseau. Dans cette thèse, on vise le problème de choisir les meilleures stratégies de caches pour CCN et les contributions sont les suivantes. On construit un environnement commun d'évaluation dans lequel on compare via simulation les stratégies de caches disponibles: Leave Copy Everywhere (LCE), Leave Copy Down (LCD), ProbCache, Cache "Less For More" et MAGIC. On analyse la performance de toutes ces stratégies et on décide la meilleure stratègie de cache pour chaque scénario. Ensuite, on propose deux stratégies de cache basées sur la popularité pour CCN. On commence avec un étude de la popularité de contenu et on présent la stratégie Most Popular Caching (MPC). MPC privilèges la distribution de contenu populaire dans les caches afin d'ameliorer les autres stratégies de cache. Dans une deuxième étape, on présent une stratègie de cache basé dans l'information des réseaux sociaux: Socially-Aware Caching Strategy (SACS). SACS privilèges la distribution de contenu publié par les utilisateurs les plus importantes / Content Centric Networking (CCN) is a new architecture for a future Internet. CCN includes in-network caching capabilities at every node. Its effciency depends drastically on performances of caching strategies. A lot of studies proposing new caching strategies to improve the performances of CCN. However, among all these strategies, it is still unclear which one performs better as there is a lack of common environment to compare these strategies. In this thesis, we address the challenge of selecting the best caching strategies for CCN. The contribution of this thesis are the following. We build a common evaluation scenario and we compare via simulation the state of the art caching strategies: Leave Copy Everywhere (LCE), Leave Copy Down (LCD), ProbCache, Cache "Less" For More and MAGIC. We analyze the performance of all the strategies in terms of Cache Hit, Stretch, Diversity and Complexity, and determine the cache strategy that fits the best with every scenario. Later on, we propose two novel caching strategies for CCN based on popularity. First, we study popularity of content and we present Most Popular Caching (MPC) strategy. MPC privileges distribution of popular caches into the caches and thus, it overcomes other caching strategies. Second, we present an alternative caching strategy based on social networks: Socially-Aware Caching Strategy (SACS). SACS privileges distribution of content published by influential users into the network. Both caching strategies overcome state of the art mechanisms and, to the best of our knowledge, we are the first to use social information to build caching strategies

Ce travail illustre comment les tendances actuelles d'utilisation dominantes sur Internet motivent la recherche sur des architectures futures de réseau plus orientées vers le contenu. Parmi les architectures émergentes pour l'Internet du futur, le paradigme du Information-Centric Networking (ICN) est présenté. ICN vise à redéfinir les protocoles de base d'Internet afin d'y introduire un changement sémantique des hôtes vers les contenus. Parmi les architectures ICN, le Named-Data Networking (NDN) prévoit que les demandes nommées de contenus des utilisateurs soient transmises par leur nom dans les routeurs le long du chemin d'un consommateur à une ou plusieurs sources de contenus. Ces demandes de contenus laissent des traces dans les routeurs traversés qui sont ensuite suivis par les paquets de contenus demandés. La table d'intérêt en attente (PIT) est le composant du plan de données de l'NDN qui enregistre temporairement les demandes de contenus acheminés dans les routeurs. D'une part, ce travail explique que le mécanisme d'acheminement à états de la PIT permet des propriétés comme l'agrégation de requêtes, le multicast de réponses et le contrôle natif de flux hop-by-hop. D'autre part, ce travail illustre comment l'acheminement à états de la PIT peut facilement être mal utilisé par des attaquants pour monter des attaques de déni de service distribué (DDoS) disruptives, appelées Interest Flooding Attacks (IFAs). Dans les IFAs, des botnets vaguement coordonnés peuvent inonder le réseau d'une grande quantité de demandes difficiles à satisfaire dans le but de surcharger soit l'infrastructure du réseau soit les producteurs de contenus. Ce travail de thèse prouve que bien que des contre-mesures contre les IFAs aient été proposées, il manque une compréhension complète de leur efficacité réelle puisque celles-ci ont été testées sous des hypothèses simplistes sur les scénarios d'évaluation. Dans l'ensemble, le travail présenté dans ce manuscrit permet de mieux comprendre les implications des IFAs et les opportunités d'améliorer les mécanismes de défense existants contre ces attaques. Les principales contributions de ce travail de thèse tournent autour d'une analyse de sécurité du plan d'acheminement dans l'architecture NDN. En particulier, ce travail définit un modèle d'attaquant plus robuste pour les IFAs à travers l'identification des failles dans les contre-mesures IFA existantes. Ce travail introduit un nouvel ensemble d'IFAs basé sur le modèle d'attaquant proposé. Les nouveaux IFAs sont utilisés pour réévaluer les plus efficaces contre-mesures IFA existantes. Les résultats de cette évaluation réfutent l'efficacité universelle des mécanismes de défense existants contre l'IFA et, par conséquent, appellent à différentes contre-mesures pour protéger le NDN contre cette menace de sécurité. Pour surmonter le problème révélé, ce travail définit également des contre-mesures proactives contre l'IFA, qui sont de nouveaux mécanismes de défense contre les IFA inspirés par les problèmes rencontrés dans l'état de l'art. Ce travail présente Charon, une nouvelle contre-mesure proactive contre l'IFA, et la teste contre les nouvelles IFAs. Ce travail montre que Charon est plus efficace que les contre-mesures IFA réactives existantes. Enfin, ce travail illustre la conception NDN.p4, c'est-à-dire la première implémentation d'un protocole ICN écrit dans le langage de haut niveau pour les processeurs de paquets P4. Le travail NDN.p4 est la première tentative dans la littérature visant à tirer parti des nouveaux techniques de réseaux programmables pour tester et évaluer différentes conceptions de plan de données NDN. Cette dernière contribution classe également les mécanismes alternatifs d'acheminement par rapport à un ensemble de propriétés cardinales de la PIT. Le travail souligne qu'il vaut la peine d'explorer d'autres mécanismes d'acheminement visant à concevoir un plan de données NDN moins vulnérable à la menace IFA / This work illustrates how today's Internet dominant usage trends motivate research on more content-oriented future network architectures. Among the emerging future Internet proposals, the promising Information-Centric Networking (ICN) research paradigm is presented. ICN aims to redesign Internet's core protocols to promote a shift in focus from hosts to contents. Among the ICN architectures, the Named-Data Networking (NDN) envisions users' named content requests to be forwarded by their names in routers along the path from one consumer to 1-or-many sources. NDN's requests leave trails in traversed routers which are then followed backwards by the requested contents. The Pending Interest Table (PIT) is the NDN's data-plane component which temporarily records forwarded content requests in routers. On one hand, this work explains that the PIT stateful mechanism enables properties like requests aggregation, multicast responses delivery and native hop-by-hop control flow. On the other hand, this work illustrates how the PIT stateful forwarding behavior can be easily abused by malicious users to mount disruptive distributed denial of service attacks (DDoS), named Interest Flooding Attacks (IFAs). In IFAs, loosely coordinated botnets can flood the network with a large amount of hard to satisfy requests with the aim to overload both the network infrastructure and the content producers. This work proves that although countermeasures against IFAs have been proposed, a fair understanding of their real efficacy is missing since those have been tested under simplistic assumptions about the evaluation scenarios. Overall, the work presented in this manuscript shapes a better understanding of both the implications of IFAs and the possibilities of improving the state-of-the-art defense mechanisms against these attacks. The main contributions of this work revolves around a security analysis of the NDN's forwarding plane. In particular, this work defines a more robust attacker model for IFAs by identifying flaws in the state-of-the-art IFA countermeasures. This work introduces a new set of IFAs built upon the proposed attacker model. The novel IFAs are used to re-assess the most effective existing IFA countermeasures. Results of this evaluation disproves the universal efficacy of the state-of-the-art IFA defense mechanisms and so, call for different countermeasures to protect the NDN against this threat. To overcome the revealed issue, this work also defines proactive IFA countermeasures, which are novel defense mechanisms against IFAs inspired by the issues with the state-of-the-art ones. This work introduces Charon, a novel proactive IFA countermeasure, and tests it against the novel IFA attacks. This work shows Charon counteracts latest stealthy IFAs better than the state-of-the-art reactive countermeasures. Finally, this work illustrates the NDN.p4 design, that is, the first implementation of an ICN protocol written in the high-level language for packet processors P4. The NDN.p4 work is the first attempt in the related literature to leverage novel programmable-networks technologies to test and evaluate different NDN forwarding plane designs. This last contribution also classifies existing alternative forwarding mechanisms with respect to a set of PIT cardinal properties. The work outlines that it is worth to explore alternative forwarding mechanisms aiming to design an NDN forwarding plane less vulnerable to the IFA threat

Undersökningens avsikt är att granska video-centric webbplatsers användning bland Karlstads universitets studenter, varför och hur studenter använder webbplatserna. Undersökningen är baserad på Uses and Gratifications modellen.

Convergence is a topic that many point to as the driving force behind modern product development. The merger of similar devices into a single product form can create a number of advantages for both producers and consumers, but successful design must take more than just this into account. Convergence is the evolution of a product through a disruptive and uncertain environment of technology and user needs. While the digital revolution has certainly been the biggest recent disrupter to society and design, there are signs of convergence in both form and function that have occurred across many products, and product categories. Producers and consumers always clamor for devices that are useful and convenient, take advantage of the latest technologies, and yet remain intuitive, attractive, and easy to use. This paper will dissect the meaning of convergence in product design and provide a framework for understanding and dialog. Combined with an extensive survey and product mapping, this definition will then be used to delineate approaches and principles for the effective design of evolving products in today's changing environment. The findings of this paper will help designers make decisions when considering the trade-offs between aesthetics, functionality, and ease of use in technology based products.

Η eXtensible Markup Language (XML) είναι εμφανώς το επικρατέστερο πρότυπο για αναπαράσταση δεδομένων στον Παγκόσμιο Ιστό. Αποτελεί μια γλώσσα περιγραφής δεδομένων, κατανοητή τόσο από τον άνθρωπο, όσο και από τη μηχανή. Η χρήση της σε αρχικό στάδιο περιορίστηκε στην ανταλλαγή δεδομένων, αλλά λόγω της εκφραστικότητάς της (σε αντίθεση με το σχεσιακό μοντέλο) μπορεί να αποτελέσει ένα αποτελεσματικό \"όχημα\" μεταφοράς και αποθήκευσης πληροφορίας. Οι σύγχρονες εφαρμογές κάνουν χρήση της τεχνολογίας XML εξυπηρετώντας ανάγκες διαλειτουργικότητας και επικοινωνίας. Ωστόσο, θεωρείται βέβαιο ότι η χρήση της σε επίπεδο υποδομής θα ενδυναμώσει περαιτέρω τις σύγχρονες εφαρμογές. Σε επίπεδο υποδομής, μια βάση δεδομένων που διαχειρίζεται την γλώσσα XML είναι σε θέση να πολλαπλασιάσει την αποδοτικότητά της, εφόσον η βάση δεδομένων μετατρέπεται σε βάση πληροφορίας. Έτσι, όσο οι εφαρμογές γίνονται πιο σύνθετες και απαιτητικές, η ενδυνάμωση των βάσεων δεδομένων με τεχνολογίες που φέρουν/εξυπηρετούν τη σημασιολογία των προβλημάτων υπόσχεται αποτελεσματικότερη αντιμετώπιση στο παραπάνω μέτωπο. Αλλά ποιος είναι ο καλύτερος τρόπος αποδοτικού χειρισμού των XML εγγράφων (XML documents); Με μια πρώτη ματιά η απάντηση είναι προφανής. Εφόσον ένα XML έγγραφο αποτελεί παράδειγμα μιας σχετικά νέας τεχνολογίας, γιατί να μη χρησιμοποιηθούν ειδικά συστήματα για το χειρισμό της; Αυτό είναι πράγματι μια βιώσιμη προσέγγιση και υπάρχει σημαντική δραστηριότητα στην κοινότητα των βάσεων δεδομένων που εστιάζει στην εκμετάλλευση αυτής της προσέγγισης. Μάλιστα, για το σκοπό αυτό, έχουν δημιουργηθεί ειδικά συστήματα βάσεων δεδομένων, οι επονομαζόμενες \"Εγγενείς XML Βάσεις Δεδομένων\" (Native XML Databases). Όμως, το μειονέκτημα της χρήσης τέτοιων συστημάτων είναι ότι αυτή η προσέγγιση δεν αξιοποιεί την πολυετή ερευνητική δραστηριότητα που επενδύθηκε για την τεχνολογία των σχεσιακών βάσεων δεδομένων. Είναι πράγματι γεγονός ότι δεν αρκεί η σχεσιακή τεχνολογία και επιβάλλεται η ανάγκη για νέες τεχνικές; Ή μήπως με την κατάλληλη αξιοποίηση των υπαρχόντων συστημάτων μπορεί να επιτευχθεί ποιοτική ενσωμάτωση της XML; Σε αυτήν την εργασία γίνεται μια μελέτη που αφορά στην πιθανή χρησιμοποίηση των σχεσιακών συστημάτων βάσεων δεδομένων για το χειρισμό των XML εγγράφων. Αφού αναλυθούν θεωρητικά οι τρόποι με τους οποίους γίνεται αυτό, στη συνέχεια εκτιμάται πειραματικά η απόδοση σε δύο από τα πιο δημοφιλή σχεσιακά συστήματα βάσεων δεδομένων. Σκοπός είναι η χάραξη ενός πλαισίου αναφοράς για την αποτίμηση και την αξιολόγηση των σχεσιακών βάσεων δεδομένων που υποστηρίζουν XML (XML-enabled RDBMSs). / The eXtensible Markup Language (XML) is obviously the prevailing model for data representation in the World Wide Web (WWW). It is a data description language comprehensible by both humans and computers. Its usage in an initial stage was limited to the exchange of data, but it can constitute an effective \"vehicle\" for transporting, handling and storing of information, due to its expressiveness (contrary to the relational model). Contemporary applications make heavy use of the XML technology in order to support communication and interoperability . However, supporting XML at the infrastructure level would reduce application development time, would make applications almost automatically complient to standards and would make them less error prone. In terms of infrastructure, a database able to handle XML properly would be beneficial to a wide range of applications thus multiplying its efficiency. In this way, as long as the applications become more complex and demanding, the strengthening of databases with technologies that serve the nature of problems, promises more effective confrontation with this topic. But how can XML documents be supported at the infrastructure level? At a first glance, the question is rhetorical. Since XML constitutes a relatively new technology, new XML-aware infrastructures can be built from scratch. This is indeed a viable approach and there is a considerable activity in the research community of databases, which focuses on the exploitation of this approach. In particular, this is the reason why special database systems have been created, called \"Native XML Databases\". However, the disadvantage of using such systems is that this approach does not build on existing knowledge currently present in the relational database field. The research question would be whether relational technology is able to support correctly XML data. In this thesis, we present a study concerned with the question whether relational database management systems (RDBMSs) provide suitable ground for handling XML documents. Having theoretically analyzed the ways with which RDBMSs handle XML, the performance in two of the most popular relational database management systems is then experimentally assessed. The aim is to draw a frame of report on the assessment and the evaluation of relational database management systems that support XML (XML-enabled RDBMSs).

No description available.