The master thesis deals with the issue of a single-wheeled robot, especially its construction and movement in more difficult terrain with the possibility of collecting samples. A variant of the robot balanced by a pair of gyroscopes was chosen as the most suitable construction. The robot is able to move in a space with an inclination of up to 24° and is equipped with its own manipulator design.

Subjekt of this diploma thesis is createing of 3D model of a balancing shafts and a dynamic model of the balancing shaft and needle roller or plain bearings. To decide from the results of dynamic analysis in MBS (Multi-Body-System), which type of bearing is the best for storage the balancing shaft in the engine Zetor type series III.

The share of intermittent weather-based renewable electricity sources has risen and will keep on rising in the Nordic electricity system, which will increase the need of balancing power in the Nordics. The previously developed concept of balancing contributions is used to look at the historic contribution of different power sources to the balancing on the grid. Three different time scales are taken into account: Daily variations, (bi-)weekly variations, and seasonal/yearly variations. This will aid in the understanding of the synergy of different sources on the grid, which, together with a deeper knowledge of the electricity market, might make it possible in the future to quantify the potential for balancing of sources within the Nordic grid. As a method to analyse the balancing contributions, a previously set-up online visualisation tool was used as an example, and this existing tool was revamped with a new software back-end using a database and automatic data collection. This allows one to be able to use a larger dataset, and for more functionality in the future, such as real-time updates and easier implementation of additional visualisations. Production and consumption data was gathered from Entso-e and SvK: the former has issues with data quality and the latter publishes data with a three-week delay which can only be obtained manually. The results from the previous research have been replicated, and a bigger dataset has been used to do the calculations, encompassing the years 2015-2018. The overall results show great similarity to that of the previous work. For the first time it was possible to plot the intrayear balancing contributions as a time series, which showed especially that the contributions of hydro power and electricity trade have changed over the period 2015-2018. There is a difference in hydro power balancing contributions based on geographical location, where Finnish hydro power is mainly a daily and—to a lesser extent—weekly regulator, Swedish hydro and especially Norwegian hydro have larger contributions on a yearly basis as well. There are even differences within countries, as the balancing contribution of hydro in bidding area SE2 has changed much more over time than hydro in SE1, for example. Other examples of interesting situations on the grid have also been highlighted using the online visualisation tool.

In den vergangenen Jahren hat das neu entstandene Paradigma Infrastructure as a Service die IT-Welt massiv verändert. Die Bereitstellung von Recheninfrastruktur durch externe Dienstleister bietet die Möglichkeit, bei Bedarf in kurzer Zeit eine große Menge von Rechenleistung, Speicherplatz und Bandbreite ohne Vorabinvestitionen zu akquirieren. Gleichzeitig steigt sowohl die Menge der frei verfügbaren als auch der in Unternehmen zu verwaltenden Daten dramatisch an. Die Notwendigkeit zur effizienten Verwaltung und Auswertung dieser Datenmengen erforderte eine Weiterentwicklung bestehender IT-Technologien und führte zur Entstehung neuer Forschungsgebiete und einer Vielzahl innovativer Systeme. Ein typisches Merkmal dieser Systeme ist die verteilte Speicherung und Datenverarbeitung in großen Rechnerclustern bestehend aus Standard-Hardware. Besonders das MapReduce-Programmiermodell hat in den vergangenen zehn Jahren zunehmend an Bedeutung gewonnen. Es ermöglicht eine verteilte Verarbeitung großer Datenmengen und abstrahiert von den Details des verteilten Rechnens sowie der Behandlung von Hardwarefehlern. Innerhalb dieser Dissertation steht die Nutzung des MapReduce-Konzeptes zur automatischen Parallelisierung rechenintensiver Entity Resolution-Aufgaben im Mittelpunkt. Entity Resolution ist ein wichtiger Teilbereich der Informationsintegration, dessen Ziel die Entdeckung von Datensätzen einer oder mehrerer Datenquellen ist, die dasselbe Realweltobjekt beschreiben. Im Rahmen der Dissertation werden schrittweise Verfahren präsentiert, welche verschiedene Teilprobleme der MapReduce-basierten Ausführung von Entity Resolution-Workflows lösen. Zur Erkennung von Duplikaten vergleichen Entity Resolution-Verfahren üblicherweise Paare von Datensätzen mithilfe mehrerer Ähnlichkeitsmaße. Die Auswertung des Kartesischen Produktes von n Datensätzen führt dabei zu einer quadratischen Komplexität von O(n²) und ist deswegen nur für kleine bis mittelgroße Datenquellen praktikabel. Für Datenquellen mit mehr als 100.000 Datensätzen entstehen selbst bei verteilter Ausführung Laufzeiten von mehreren Stunden. Deswegen kommen sogenannte Blocking-Techniken zum Einsatz, die zur Reduzierung des Suchraums dienen. Die zugrundeliegende Annahme ist, dass Datensätze, die eine gewisse Mindestähnlichkeit unterschreiten, nicht miteinander verglichen werden müssen. Die Arbeit stellt eine MapReduce-basierte Umsetzung der Auswertung des Kartesischen Produktes sowie einiger bekannter Blocking-Verfahren vor. Nach dem Vergleich der Datensätze erfolgt abschließend eine Klassifikation der verglichenen Kandidaten-Paare in Match beziehungsweise Non-Match. Mit einer steigenden Anzahl verwendeter Attributwerte und Ähnlichkeitsmaße ist eine manuelle Festlegung einer qualitativ hochwertigen Strategie zur Kombination der resultierenden Ähnlichkeitswerte kaum mehr handhabbar. Aus diesem Grund untersucht die Arbeit die Integration maschineller Lernverfahren in MapReduce-basierte Entity Resolution-Workflows. Eine Umsetzung von Blocking-Verfahren mit MapReduce bedingt eine Partitionierung der Menge der zu vergleichenden Paare sowie eine Zuweisung der Partitionen zu verfügbaren Prozessen. Die Zuweisung erfolgt auf Basis eines semantischen Schlüssels, der entsprechend der konkreten Blocking-Strategie aus den Attributwerten der Datensätze abgeleitet ist. Beispielsweise wäre es bei der Deduplizierung von Produktdatensätzen denkbar, lediglich Produkte des gleichen Herstellers miteinander zu vergleichen. Die Bearbeitung aller Datensätze desselben Schlüssels durch einen Prozess führt bei Datenungleichverteilung zu erheblichen Lastbalancierungsproblemen, die durch die inhärente quadratische Komplexität verschärft werden. Dies reduziert in drastischem Maße die Laufzeiteffizienz und Skalierbarkeit der entsprechenden MapReduce-Programme, da ein Großteil der Ressourcen eines Clusters nicht ausgelastet ist, wohingegen wenige Prozesse den Großteil der Arbeit verrichten müssen. Die Bereitstellung verschiedener Verfahren zur gleichmäßigen Ausnutzung der zur Verfügung stehenden Ressourcen stellt einen weiteren Schwerpunkt der Arbeit dar. Blocking-Strategien müssen stets zwischen Effizienz und Datenqualität abwägen. Eine große Reduktion des Suchraums verspricht zwar eine signifikante Beschleunigung, führt jedoch dazu, dass ähnliche Datensätze, z. B. aufgrund fehlerhafter Attributwerte, nicht miteinander verglichen werden. Aus diesem Grunde ist es hilfreich, für jeden Datensatz mehrere von verschiedenen Attributen abgeleitete semantische Schlüssel zu generieren. Dies führt jedoch dazu, dass ähnliche Datensätze unnötigerweise mehrfach bezüglich verschiedener Schlüssel miteinander verglichen werden. Innerhalb der Arbeit werden deswegen Algorithmen zur Vermeidung solch redundanter Ähnlichkeitsberechnungen präsentiert. Als Ergebnis dieser Arbeit wird das Entity Resolution-Framework Dedoop präsentiert, welches von den entwickelten MapReduce-Algorithmen abstrahiert und eine High-Level-Spezifikation komplexer Entity Resolution-Workflows ermöglicht. Dedoop fasst alle in dieser Arbeit vorgestellten Techniken und Optimierungen in einem nutzerfreundlichen System zusammen. Der Prototyp überführt nutzerdefinierte Workflows automatisch in eine Menge von MapReduce-Jobs und verwaltet deren parallele Ausführung in MapReduce-Clustern. Durch die vollständige Integration der Cloud-Dienste Amazon EC2 und Amazon S3 in Dedoop sowie dessen Verfügbarmachung ist es für Endnutzer ohne MapReduce-Kenntnisse möglich, komplexe Entity Resolution-Workflows in privaten oder dynamisch erstellten externen MapReduce-Clustern zu berechnen.

Software-Defined Wide Area Networking (SD-WAN) is an emerging technology that has the potential to satisfy the increasing demand for reliable and efficient Wide Area Networks (WANs) in the enterprise-network market. This thesis focuses on the main features of an SD-WAN network and on the technical challenges facing the design and implementation of an SD-WAN infrastructure. It also provides a detailed comparison between the SD-WAN and the otherWANs solutions such as MultiProtocol Label Switching (MPLS). The thesis is based on the project that is about the migration of network infrastructure that uses the MPLS technology to a network infrastructure that uses the SD-WAN technology. The migration process includes many phases such as the analysis of the existing MPLS based infrastructure, identification of suitable appliances based on customer requests, and the design of the SD-WAN infrastructure that can be implemented without disrupting the network functioning during the transition stage. The thesis provides a detailed description of these steps and it discusses the trade-offs that were made during the design phase of the project. The results presented in the thesis are obtained through on-site tests performed for the new SD-WAN infrastructure. The tests were performed with the objective to evaluate some of the main SD-WAN functionalities such as load balancing, traffic shaping, and high availability. The obtained results show the effective functioning of the network infrastructure and illustrate some of the main advantages that the new SD-WAN infrastructure has over the old MPLS infrastructure. Finally, this thesis could be of interest to network professionals and employees who consider SD-WAN as a possible solution for their company’s business. / Software-Defined Wide Area Networking (SD-WAN) är en framväxande teknik som har potential att tillgodose den ökande efterfrågan på tillförlitliga och effektiva Wide Area Networks (WAN) på företagsnätverksmarknaden. Denna avhandling fokuserar på huvudfunktionerna i ett SD-WAN-nätverk och på de tekniska utmaningarna för design och implementering av en SD-WAN-infrastruktur. Det ger också en detaljerad jämförelse mellan SD-WAN och andra WAN-lösningar som MultiProtocol Label Switching (MPLS). Avhandlingen bygger på projektet som handlar om migrering av nätverksinfrastruktur som använder MPLS-tekniken till en nätverksinfrastruktur som använder SD-WAN-tekniken. Migreringsprocessen omfattar många faser, till exempel analys av befintlig MPLS-baserad infrastruktur, identifiering av lämpliga apparater baserat på kundförfrågningar och utformningen av SD-WAN-infrastrukturen som kan implementeras utan att nätverket fungerar under övergångssteget. Avhandlingen ger en detaljerad beskrivning av dessa steg och diskuterar de avvägningar som gjordes under projektets designfas. Resultaten som presenteras i avhandlingen erhålls genom test på plats för den nya SD-WAN-infrastrukturen. Testerna utfördes i syfte att utvärdera några av de viktigaste SD-WAN-funktionerna som lastbalansering, trafikformning och hög tillgänglighet. De erhållna resultaten visar att nätinfrastrukturen fungerar effektivt och illustrerar några av de största fördelarna som den nya SD-WAN-infrastrukturen har jämfört med den gamla MPLS-infrastrukturen. Slutligen kan denna avhandling vara av intresse för nätverkspersonal och anställda som anser SD-WAN som en möjlig lösning för företagets verksamhet.

Latent Dirichlet Allocation (LDA), a total probability generative model, is a three-tier Bayesian model. LDA computes the latent topic structure of the data and obtains the significant information of documents. However, traditional LDA has several limitations in practical applications. LDA cannot be directly used in classification because it is a non-supervised learning model. It needs to be embedded into appropriate classification algorithms. LDA is a generative model as it normally generates the latent topics in the categories where the target documents do not belong to, producing the deviation in computation and reducing the classification accuracy. The number of topics in LDA influences the learning process of model parameters greatly. Noise samples in the training data also affect the final text classification result. And, the quality of LDA based classifiers depends on the quality of the training samples to a great extent. Although parallel LDA algorithms are proposed to deal with huge amounts of data, balancing computing loads in a computer cluster poses another challenge. This thesis presents a text classification method which combines the LDA model and Support Vector Machine (SVM) classification algorithm for an improved accuracy in classification when reducing the dimension of datasets. Based on Density-Based Spatial Clustering of Applications with Noise (DBSCAN), the algorithm automatically optimizes the number of topics to be selected which reduces the number of iterations in computation. Furthermore, this thesis presents a noise data reduction scheme to process noise data. When the noise ratio is large in the training data set, the noise reduction scheme can always produce a high level of accuracy in classification. Finally, the thesis parallelizes LDA using the MapReduce model which is the de facto computing standard in supporting data intensive applications. A genetic algorithm based load balancing algorithm is designed to balance the workloads among computers in a heterogeneous MapReduce cluster where the computers have a variety of computing resources in terms of CPU speed, memory space and hard disk space.

Diabetes is a rapidly growing health concern in the developed world. Hypoglycaemia is a major risk factor in people with diabetes. Each year, about 7000 calls relating to hypoglycaemia are made to the Scottish Ambulance Service (SAS), including a considerable number of repeat callers. Very little is known about people’s experiences and explanations of recurrent hypoglycaemia; in particular, why some individuals manage their recurrent hypoglycaemic episodes independently, while others require more direct healthcare support. This thesis investigated participants’ experiences and individual explanations of recurrent hypoglycaemic episodes, in order to understand their health help-seeking behaviour. To do this, it compared the experiences of people who had called the emergency services within one month prior to recruitment (SAS participants), with those people who had not done so (non-SAS participants). The study employed a multiple methods longitudinal approach to prospectively capture participants’ experiences of hypoglycaemic episodes, using qualitative semi-structured interviews, hypoglycaemia and blood glucose diaries and follow-up telephone interviews over a six month period. Thirty participants were involved in the study, recruited through the Scottish Ambulance Service, Diabetes UK (Scotland), and the University of Stirling. All participants resided in the central belt of Scotland. Qualitative data was analysed using the framework method, and quantitative data was analysed using descriptive statistics. This study found that hypoglycaemic episodes had a wide ranging impact on people’s everyday life. It was not only the actual hypoglycaemic episode that affected participants’ everyday life, but also fears and worries about future hypoglycaemic episodes, the preparations that participants engaged in, and the process of recovery. Hypoglycaemia unawareness was found to be a major problem for many people living with diabetes. It appeared to be associated with the likelihood of needing external help. There were differences between participant groups with regard to management of hypoglycaemia unawareness. Non-SAS participants adopted strategies to prepare for future hypoglycaemic episodes, and appeared to be more knowledgeable about their diabetes and its management, resulting in needing less external help. SAS participants experienced more severe hypoglycaemic episodes. Consequently, they relied more on external help. Findings of this study call for a re-conceptualisation of the previously recognised ‘balancing act’ of managing diabetes and hypoglycaemic episodes. This study introduces the concept of a hypoglycaemic episode balancing continuum (HEBC) which enables a deeper understanding of the factors involved in this balancing act: it demonstrates that people balance the various risks differently, depending on whether they prioritised their fear of hypoglycaemia over fears of long-term complications. People’s position on the continuum directly affected their management strategies for hypoglycaemic episodes. Most hypoglycaemic episodes were managed by the individual without requiring any external help. However, participants’ ability to self-care differed and deficits occurred, resulting in participants being more likely to need involvement of others (family/friends). When the capacity of others to help broke down, participants’ were more likely to need SAS emergency care. In order to explain how hypoglycaemic episodes are managed, this thesis has developed a hypoglycaemic episode help-seeking network (HEHS network), which helps to identify the various agents involved in helping to manage hypoglycaemic episodes. Findings from this study have implications for clinical practice. For example, looking at hypoglycaemia unawareness, this study has shown that current understanding may fail to take account of participants’ real experiences, which show hypoglycaemia unawareness to be a fluid phenomenon that can affect people at various times. If blood glucose levels can fail to predict onset of hypoglycaemic episodes, healthcare professionals may need to broaden the range of blood glucose readings that might indicate a hypoglycaemic episode and tailor specific advice to individual patients. To reduce the use of emergency services, more attention must be paid to hypoglycaemia unawareness and better advice provided about this condition. Also, more education should be provided for family members/carers, given the crucial role they play in the management of diabetes and hypoglycaemic episodes, and being a link in the process leading to increased use of emergency services. The HEBC could be developed into a useful ‘screening tool’ to help healthcare professionals identify those at greater risk of hypoglycaemic episodes and those at greater risk of long-term complications, and to target advice more specifically to these patient groups. Further research could explore family member/carer knowledge in more detail to better understand their role in helping to manage hypoglycaemic episodes.

This thesis analyses the aims and objectives of the EU Acquired Rights Directive (ARD) in the context of the larger evolution of EU labour law itself. The thesis presents the overall goal of the ARD as that of striking an appropriate balance between the employer’s prerogative to transfer the business and the employee’s interest in not having the security of the job unduly threatened by such transfers. Given the current complexity and incoherence of the law regulating economic dismissals in the context of transfers, the central argument of the thesis is that there is a need for a clearer conceptual framework for defining and understanding the rights and obligations in the Acquired Rights Directive (ARD). It is suggested that the principles of legitimate expectations and proportionality are ideally adapted to play this role. In analyzing the teleology of the ARD based on these principles, this study not only assists in understanding and explaining the ARD itself, but also has wider implications for understanding the challenges facing European social policy in the field of employment protection. In its attempts to reconcile fundamental economic freedoms of employers on the one hand, and fundamental rights of employees on the other, the Court of Justice has frequently relied upon the proportionality principle to achieve a ‘fair balance’ between both parties. Following the interpretations of ‘proportionality’ in Viking and Laval, there is admittedly a fear that the proportionality balancing is likely to accord an almost absolute priority to the employers’ economic freedoms. The thesis is cognizant of this danger, and therefore advocates a ‘symmetrical’ approach to balancing. In this way the thesis offers some insight into the potential for the ARD to remain continuously effective in times of economic crisis. The study therefore finds reason to be optimistic about the prospects for the ARD and other standard-setting directives in the future of social Europe.

Conventional wisdom states that, in response to a rising threat, weaker states may choose either to balance against, or to bandwagon with, the threat. However, the states in Southeast Asia, in response to a rising China, exhibit behavior that conforms neither to pure balancing nor bandwagoning. This senior thesis seeks to understand why that is the case, and argues that, in a world of ambiguity, the domestic level of analysis becomes of greater importance in explaining state behavior.

Distributed Hash Tables (DHTs) are protocols and frameworks used by peer-to-peer (P2P) systems. They are used as the organizational backbone for many P2P file-sharing systems due to their scalability, fault-tolerance, and load-balancing properties. These same properties are highly desirable in a distributed computing environment, especially one that wants to use heterogeneous components. We show that DHTs can be used not only as the framework to build a P2P file-sharing service, but as a P2P distributed computing platform. We propose creating a P2P distributed computing framework using distributed hash tables, based on our prototype system ChordReduce. This framework would make it simple and efficient for developers to create their own distributed computing applications. Unlike Hadoop and similar MapReduce frameworks, our framework can be used both in both the context of a datacenter or as part of a P2P computing platform. This opens up new possibilities for building platforms to distributed computing problems. One advantage our system will have is an autonomous load-balancing mechanism. Nodes will be able to independently acquire work from other nodes in the network, rather than sitting idle. More powerful nodes in the network will be able use the mechanism to acquire more work, exploiting the heterogeneity of the network. By utilizing the load-balancing algorithm, a datacenter could easily leverage additional P2P resources at runtime on an as needed basis. Our framework will allow MapReduce-like or distributed machine learning platforms to be easily deployed in a greater variety of contexts.