Feeds werden unter anderem eingesetzt, um Nutzer in einem einheitlichen Format und in aggregierter Form über Aktualisierungen oder neue Beiträge auf Webseiten zu informieren. Da bei Feeds in der Regel keine Benachrichtigungsfunktionalitäten angeboten werden, müssen Interessenten Feeds regelmäßig auf Aktualisierungen überprüfen. Die Betrachtung entsprechender Techniken bildet den Kern der Arbeit. Die in den verwandten Domänen Web Crawling und Web Caching eingesetzten Algorithmen zur Vorhersage der Zeitpunkte von Aktualisierungen werden aufgearbeitet und an die spezifischen Anforderungen der Domäne Feeds angepasst. Anschließend wird ein selbst entwickelter Algorithmus vorgestellt, der bereits ohne den Einsatz spezieller Konfigurationsparameter und ohne Trainingsphase im Durchschnitt bessere Vorhersagen trifft, als die übrigen betrachteten Algorithmen. Auf Basis der Analyse verschiedener Metriken zur Beurteilung der Qualität von Vorhersagen erfolgt die Definition eines zusammenfassenden Gütemaßes, welches den Vergleich von Algorithmen anhand eines einzigen Wertes ermöglicht. Darüber hinaus werden abfragespezifische Attribute der Feed-Formate untersucht und es wird empirisch gezeigt, dass die auf der partiellen Historie der Feeds basierende Vorhersage von Änderungen bereits bessere Ergebnisse erzielt, als die Einbeziehung der von den Diensteanbietern bereitgestellten Werte in die Berechnung ermöglicht. Die empirischen Evaluationen erfolgen anhand eines breitgefächerten, realen Feed-Datensatzes, welcher der wissenschaftlichen Gemeinschaft frei zur Verfügung gestellt wird, um den Vergleich mit neuen Algorithmen zu erleichtern.

Les bases de données présentent des problèmes de passage à l’échelle. Ceci est principalement dû à la compétition pour les ressources et au coût du contrôle de la concurrence. Une alternative consiste à centraliser les écritures afin d’éviter les conflits. Cependant, cette solution ne présente des performances satisfaisantes que pour les applications effectuant majoritairement des lectures. Une autre solution est d’affaiblir les propriétés transactionnelles mais cela complexifie le travail des développeurs d’applications. Notre solution, Gargamel, répartie les transactions effectuant des écritures sur différentes répliques de la base de données tout en gardant de fortes propriétés transactionnelles. Toutes les répliques de la base de donnée s’exécutent séquentiellement, à plein débit; la synchronisation entre les répliques reste minime. Les évaluations effectuées avec notre prototype montrent que Gargamel permet d’améliorer le temps de réponse et la charge d’un ordre de grandeur quand la compétition est forte (systèmes très chargés avec ressources limitées) et que dans les autres cas le ralentissement est négligeable. / Databases often scale poorly in distributed configurations, due to the cost of concurrency control and to resource contention. The alternative of centralizing writes works well only for read-intensive workloads, whereas weakening transactional properties is problematic for application developers. Our solution spreads non-conflicting update transactions to different replicas, but still provides strong transactional guarantees. In effect, Gargamel partitions the database dynamically according to the update workload. Each database replica runs sequentially, at full bandwidth; mutual synchronisation between replicas remains minimal. Our prototype show that Gargamel improves both response time and load by an order of magnitude when contention is high (highly loaded system with bounded resources), and that otherwise slow-down is negligible.

[pt] Na área de dados interligados, usuários frequentemente utilizam ferramentas de descoberta de links para materializar links sameAs entre diferentes base de dados. No entanto, pode ser difícil especificar as regras de ligação nas ferramentas, se as bases de dados tiverem modelos complexos. Uma possível solução para esse problema seria estimular os administradores das base de dados a publicarem visões simples, que funcionem como catálogos de recursos. Uma vez que os links estão materializados, um segundo problema que surge é como manter esses links atualizados quando as bases de dados são atualizadas. Para ajudar a resolver o segundo problema, este trabalho apresenta um framework para a manutenção de visões e links materializados, utilizando uma estratégia incremental. A ideia principal da estratégia é recomputar apenas os links dos recursos que foram atualizadas e que fazem parte da visão. Esse trabalho também apresenta um experimento para comparar a performance da estratégia incremental com a recomputação total das visões e dos links materializados. / [en] In the Linked Data field, data publishers frequently materialize sameAs links between two different datasets using link discovery tools. However, it may be difficult to specify linking conditions, if the datasets have complex models. A possible solution lies in stimulating dataset administrators to publish simple predefined views to work as resource catalogues. A second problem is related to maintaining materialized sameAs linksets, when the source datasets are updated. To help solve this second problem, this work presents a framework for maintaining views and linksets using an incremental strategy. The key idea is to re-compute only the set of updated resources that are part of the view. This work also describes an experiment to compare the performance of the incremental strategy with the full re-computation of views and linksets.

This study investigates the possibilities of using mesh networking in underground mines. It is of utmost importance to investigate the safety and ethical aspects of implementing new systems in mines, namely mesh networking. Simulations and calculations have been made to analyze and arrive at findings of update intervals for a potential mesh network. Semi-structured interviews have been conducted with responsible staff at underground mine sites, and this study has followed a qualitative approach. Theoretical concepts such as Locatilization infrastructures in underground mines and Personal security and work environment laws in underground mines have been analyzed and discussed in relation to empirical results using thematic analysis. Due to the importance of safety aspects of emergency notifications and real time location tracking, our findings show that mesh networks may not be a viable replacement for a fully connected network in a mine network infrastructure. However, mesh networks or hybrid networks may be a more viable way to improve safety for certain mines that do not have an existing network infrastructure, or as a temporary extension to a fully connected network infrastructure.

The Internet of Things (IoT) is a concept where sensors combined with microcontrollers enhance our everyday life. In the year 2050, there will be around 30 billion connected IoT systems, for developing this large amount of systems and maintaining them there will be a need to use over-the-air updates (OTA). With the increasing growth of IoT systems, there will also rise more OTA update solutions as tools for maintaining and enhancing IoT systems. In this bachelor's degree project, evaluations and comparisons of different OTA update techniques supporting microcontrollers of the type ESP32 are done by using controlled experiments. This study focuses on testing the update procedure with experiments that test OTA update deployment time and update rollback functionality.

This paper investigates alternative scheduling for game objects in a game engine by using priority based algorithms and comparing different priority assigning methods. Research concerning commercial game engines, game loops, concurrency and scheduling was performed. Three different scheduling algorithms were created and tested using a varying amount of game objects between two different testing scenarios. The results showed that using priority based scheduling gave a slight increase in average frames  per second (FPS) as well as boosting logical update performance of prioritized objects, however overall performance was decreased. The reason this decrease in performance occurred could have been due to the way the scheduler was implemented, and despite the decrease in performance using a priority based scheduling system was considered feasible within certain game engines. / Denna uppsats undersöker alternativa sätt för schemaläggning av spelobjekt i en spelmotor genom att använda prioriteringsbaserade algoritmer och jämföra olika tilldelningssätt för prioritetsmetoder. Forskning gällande kommersiella spelmotorer, ''game loops'', parallellisering och schemaläggning utfördes. Tre olika schemaläggningsalgoritmer skapades och testades med ett varierande antal spelobjekt i två olika testscenarion. Resultaten visade att användning av prioritetsbaserad schemaläggning gav en lätt ökning av det genomsnittliga antalet bilder per sekund (FPS) och gav bättre logikuppdateringsprestanda för prioriterade objekt. Den totala prestandan minskade dock. Anledningen till att denna minskning i prestanda skedde kan bero på hur schemaläggaren implementerades, men trots denna prestandaminskning ansågs schemaläggningssystemet vara möjlig inom vissa spelmotorer.

As the automotive industry becomes increasingly reliant on digital systems it is of utmost importance that these systems are secure. Secure systems are of interest both for the general public as well as manufactures. This Master’s thesis evaluates potential cybersecurity solutions for a proposed damper system prototype developed by Öhlins Racing AB. A systematic literature study was performed to identify known vulnerabilities of similar systems as well as potential cybersecurity solutions. A threat model was constructed using vehicleLang, the Meta Attack Language, and securiCAD. The model was created utilizing preexisting assets from vehicleLang and a newly implemented Bluetooth asset. The result from the systematic literature study was used to validate preexisting attack steps and also to create the Bluetooth asset. To validate the model, experts in the field of automotive security and/or threat modeling were asked to assess the model. Using Cochran’s Equation, a target of eight expert evaluations were decided. Unfortunately, only seven evaluations were obtained, equivalent to an increase in the error margin from 25% to 26.6%. However, of the seven expert evaluations obtained none indicated the existence of critical flaws within the model. The model was therefore considered a good reflection of the damper system and its security aspects. Critical defenses included the utilization of cryptography, mutual authentication, and on-the-fly decryption. These defenses were shown to prevent unauthorized modifications of firmware and protect Öhlins intellectual property in form of source code. While it was not possible to defend against all attacks the identified defenses would increase the safety and security of the system, benefiting not only Öhlins but also overall road users. / Allt eftersom fordonsindustrins beroende av digitala system ökar är det av yttersta vikt att dessa system är säkra. Säkra system är av intresse för både allmänheten likväl som för systemtillverkarna. Denna masteruppsats evaluerar potentiella cybersäkerhetslösningar för en föreslagen stötdämparprototyp utvecklad av Öhlins Racing AB. En systematisk litteraturöversikt skapades med syfte att identifiera kända sårbarheter av liknande system och potentiella cybersäkerhetslösningar. En hotmodell skapades med hjälp av vehicleLang, the Meta Attack Language, och securiCAD. Hotmodellen skapades med existerande komponenter från vehicleLang och en nyskapad Bluetooth komponent. Resultaten från den systematiska litteraturöversikten användes för att validera existerande komponenter från vehicleLang och för implementationen av Bluetooth komponenten. För att evaluera modellen bads experter inom fordonssäkerhet och/eller hotmodellering utvärdera modellen. Genom Cochran’s ekvation beslutades att åtta expert utvärderingar skull införskaffas. Tyvärr erhölls enbart sju utvärderingar, vilket motsvarar en ökning av felmarginalen från 25% till 25.6%. Av de sju experter som utvärderade modellen identifierades dock inga kritiska brister. Kritiska säkerhetslösningar inkluderade användandet av: kryptografi, ömsesidig autentisering, och on-the-fly decryption. Dessa försvar anses kunna skydda mot obehörig modifiering av programvara, samt skydda Öhlins intellektuella egendom i form av källkod. Trots att det inte var möjligt att förhindra alla attacker skulle de identifierade försvaren öka systemets säkerhet, vilket är fördelaktigt inte bara för Öhlins utan även trafikanter i allmänhet.

No description available.

[pt] A otimização online de portfólios é um problema de engenharia financeira que consiste na escolha sequencial de alocação de capital entre um conjunto de ativos, com o objetivo de maximizar o retorno acumulado no longo prazo. Com o avanço dos estudos de modelos de machine learning, diversos algorítmos estão sendo utilizados para resolver esse problema. Uma série de algoritmos seguem a metodologia Follow-the-winner (FTW) , onde o peso de ações com boa performance é aumentado baseado na hipótese de que a tendência de alta será mantida; outros seguem a metodologia inversa Follow-the-loser (FTL), em que ações com má performance tem seu peso aumentado apostando em uma reversão dos preços. Algoritmos estado-da-arte do tipo FTW possuem garantia teórica de se aproximar da performance da melhor ação escolhida de antemão, entretanto, algoritmos do tipo FTL tem performance superior observada empiricamente. Nosso trabalho busca explorar a ideia de aprender quando utilizar cada uma das duas categorias. Os mecanismos utilizados são algoritmos de online learning com flexibilidade para assumir ambos comportamentos. Foi realizado um estudo da literatura sobre indicadores de memória em séries financeiras e sua possível utilização de forma explícita para escolha entre FTL e FTW. Posteriormente, propomos um método de se realizar o aprendizado entre essas duas categorias de forma online e de forma dinâmica para utilização em algoritmos de online learning. Em nossos experimentos, o método proposto supera o benchmark estabelecido UCRP com excesso de retorno de 36.76 por cento. / [en] Online portfolio selection is a financial engineering problem which aims to sequentially allocate capital among a set of assets in order to maximize long-term return. With the recent advances in the field of machine learning, several models have been proposed to address this problem. Some algorithms approach the problem with a Follow-the-winner (FTW) methodology, which increases the weights of more successful stocks based on their historical performance. Contrarily, a second approach, Follow-theloser (FTW), increases the weights of less successful stocks, betting on the reversal of their prices. Some state-of-the-art FTW type algorithms have the guarantee to asymptotically approach the same performance as the best stock chosen in hindsight, while FTL algorithms have empirical evidence of overperforming the previous. Our goal is to explore the idea of learning when to use each of those two algorithm categories. We do this by using online learning algorithms that are capable of switching between the described regimes. We review the literature for existing measures of time series memory and predictability, and explicitly use this information for chosing between FTW and FTL. Later, we propose a method for choosing between this two types of algorithms in an online and dynamic manner for usage together with online learning algorithms. The method outperforms the chosen benchmark UCRP in our experiments with 36.76 percent excess returns.

There is a need for a fuel-optimal required time of arrival (RTA) mode for aircraft flight management systems capable of enabling controlled time of arrival functionality in the presence of wind speed forecast uncertainty. A computationally tractable two-stage stochastic algorithm utilizing a data-driven, location-specific forecast uncertainty model to generate forecast uncertainty scenarios is proposed as a solution. Three years of Aircraft Communications Addressing and Reporting Systems (ACARS) wind speed reports are used in conjunction with corresponding wind speed forecasts from the Rapid Update Cycle (RUC) forecast product to construct an inhomogeneous Markov model quantifying forecast uncertainty characteristics along specific route through the national airspace system. The forecast uncertainty modeling methodology addresses previously unanswered questions regarding the regional uncertainty characteristics of the RUC model, and realizations of the model demonstrate a clear tendency of the RUC product to be positively biased along routes following the normal contours of the jet stream. A two-stage stochastic algorithm is then developed to calculate the fuel optimal stage one cruise speed given a required time of arrival at a destination waypoint and wind forecast uncertainty scenarios generated using the inhomogeneous Markov model. The algorithm utilizes a quadratic approximation of aircraft fuel flow rate as a function of cruising Mach number to quickly search for the fuel-minimum stage one cruise speed while keeping computational footprint small and ensuring RTA adherence. Compared to standard approaches to the problem utilizing large scale linear programming approximations, the algorithm performs significantly better from a computational complexity standpoint, providing solutions in fractional power time while maintaining computational tractability in on-board systems.