In today’s world the internet and social media are omnipresent and information is accessible to everyone. This shifted the advantage from those who have access to information to those who do so first. Identifying new events as they emerge is of substantial value to financial institutions who consider realtime information in their decision making processes, as well as for journalists that report about breaking news and governmental agencies that collect information and respond to emergencies. First Story Detection is the task of identifying those documents in a stream of documents that talk about new events first. This seemingly simple task is non-trivial as the computational effort increases with every processed document. Standard approaches to solve First Story Detection determine a document’s novelty by comparing it to previously seen documents. This results in the highest reported accuracy but even the currently fastest system only scales to 10% of the Twitter stream. In this thesis, we propose a new algorithm family, called memory-based methods, able to scale to the full Twitter stream on a single core. Our memory-based method computes a document’s novelty up to two orders of magnitude faster than state-of-the-art systems without sacrificing accuracy. This thesis additional provides original work on the impact of processing unbounded data streams on detection accuracy. Our experiments reveal for the first time that the novelty scores of state-of-the-art comparison based and memory-based methods decay over time. We show how to counteract the discovered novelty decay and increase detection accuracy. Additionally, we show that memory-based methods are applicable beyond First Story Detection by building the first real time rumour detection system on social media streams.

The purpose of this thesis was to visualize the 1.7 billion stars released by the European Space Agency, as the second data release (DR2) of their Gaia mission, in the open source software OpenSpace with interactive framerates and also to be able to filter the data in real-time. An additional implementation goal was to streamline the data pipeline so that astronomers could use OpenSpace as a visualization tool in their research. An out-of-core rendering technique has been implemented where the data is streamed from disk during runtime. To be able to stream the data it first has to be read, sorted into an octree structure and then stored as binary files in a preprocess. The results of this report show that the entire DR2 dataset can be read from multiple files in a folder and stored as binary values in about seven hours. This step determines what values the user will be able to filter by and only has to be done once for a specific dataset. Then an octree can be created in about 5 to 60 minutes where the user can define if the stars should be filtered by any of the previously stored values. Only values used in the rendering will be stored in the octree. If the created octree can fit in the computer’s working memory then the entire octree will be loaded asynchronously on start-up otherwise only a binary file with the structure of the octree will be read during start-up while the actual star data will be streamed from disk during runtime. When the data have been loaded it is streamed to the GPU. Only stars that are visible are uploaded and the application also keeps track of which nodes that already have been uploaded to eliminate redundant updates. The inner nodes of the octree store the brightest stars in all its descendants as a level-of-detail cache that can be used when the nodes are small enough in screen space. The previous star rendering in OpenSpace has been improved by dividing the rendering phase into two passes. The first pass renders into a framebuffer object while the second pass then performs a tonemapping of the values. The rendering can be done either with billboard instancing or point splatting. The latter is generally the faster alternative. The user can also switch between using VBOs or SSBOs when updating the buffers. The latter is faster but requires OpenGL 4.3, which Apple products do not currently support. The rendering runs with interactive framerates for both flat and curved screen, such as domes/planetariums. The user can also switch dataset during render as well as render technique, buffer objects, color settings and many other properties. It is also possible to turn time on and see the stars move with their calculated space velocity, or transverse velocity if the star lacks radial velocity measurements. The calculations omits the gravitational rotation. The purpose of the thesis has been fulfilled as it is possible to fly through the entire DR2 dataset on a moderate desktop computer and filter the data in real-time. However, the main contribution of the project may be that the ground work has been laid in OpenSpace for astronomers to actually use it as a tool when visualizing their own datasets and also for continuing to explore the coming Gaia releases.

This report will be covering further development of the Realtime-Updated Dashboard made by two students for Flex Applications in VT2017. The task now is to integrate the Dashboard with Outlook calendar. A theoretical deepening into the General Data Protection Regulation was made due to recent development in the European Union. This was used to set strict guidelines for design, consent and security of the application.   The application is a back-end service written mostly in C#, however some TypeScript language was used with Angular 2 framework along with LESS and HTML5. The application is developed as a stand-alone project as the Realtime-Updated Dashboard is now live in the system and it would pose a security risk for Flex which was a great opportunity to study and learn more about ASP.NET MVC model along with TypeScript, Angular2, LESS and HTML5. Integrating with Outlook calendar was just the first step, more calendars will be added in time. The main point of the application is to give the Realtime-Updated Dashboard added value and prove/show integration with Outlook calendar was possible.

abstract: The prevalence of renewable generation will increase in the next several decades and offset conventional generation more and more. Yet this increase is not coming without challenges. Solar, wind, and even some water resources are intermittent and unpredictable, and thereby create scheduling challenges due to their inherent “uncontrolled” nature. To effectively manage these distributed renewable assets, new control algorithms must be developed for applications including energy management, bridge power, and system stability. This can be completed through a centralized control center though efforts are being made to parallel the control architecture with the organization of the renewable assets themselves—namely, distributed controls. Building energy management systems are being employed to control localized energy generation, storage, and use to reduce disruption on the net utility load. One such example is VOLTTRONTM, an agent-based platform for building energy control in real time. In this thesis, algorithms developed in VOLTTRON simulate a home energy management system that consists of a solar PV array, a lithium-ion battery bank, and the grid. Dispatch strategies are implemented to reduce energy charges from overall consumption ($/kWh) and demand charges ($/kW). Dispatch strategies for implementing storage devices are tuned on a month-to-month basis to provide a meaningful economic advantage under simulated scenarios to explore algorithm sensitivity to changing external factors. VOLTTRON agents provide automated real-time optimization of dispatch strategies to efficiently manage energy supply and demand, lower consumer costs associated with energy usage, and reduce load on the utility grid. / Dissertation/Thesis / Masters Thesis Engineering 2015

Matlab Simulink is a commonly used tool in the design process of control systems. To further take advantage of the Matlab Simulink models it is desirable to translate them for realtime use together with the possibility to read/write physical signals. Real-Time Workshop is an extension to Simulink that automatically generates code from a model to a variety of target platforms. RTAI and RTLinux are hard realtime operating systems, making use of Linux. To make automatically generated code run on RTAI and RTLinux an adaptation of the generation of code is necessary. To control, for example, an automotive engine a data acquisition card with an appropriate device driver is required. Comedi, an open source project, provides a number of device drivers for data acquisition cards. The developed system makes use of Simulink, Real-Time Workshop, RTAI or RTLinux, and the standard data acquisition card NI 6035E using a Comedi device driver. The Simulink models may be executed at frequencies up to 50 kHz on ordinary PC hardware. The evaluation of the system consisted of measuring the interrupt latency of the used motherboard's bus, measuring computation times running Simulink models with known complexity, running models developed at Vehicular Systems and a comparison of interfacing Simulink/Real-Time Workshop between RTAI and RTLinux. The recommended realtime operating system is RTAI due to the open source community support of it as a target platform for Real-Time Workshop.

The company where this thesis was formulated constructs VR applications for the medical environment. The hardware used is ordinary dektops with consumer level graphics cards and haptic devices. In medicin some operations require microscopes or cameras. In order to simulate these in a virtual reality environment for educational purposes, the effect of depth of field or focus have to be considered. A working algorithm that generates this optical occurence in realtime, stereo rendered computer graphics is presented in this thesis. The algorithm is implemented in OpenGL and C++ to later be combined with a VR application simulating eye-surgery which is built with OpenGL Optimizer. Several different approaches are described in this report. The call for realtime stereo rendering (~60 fps) means taking advantage of the graphics hardware to a great extent. In OpenGL this means using the extensions to a specific graphic chip for better performance, in this case the algorithm is implemented for a GeForce3 card. To increase the speed of the algorithm much of the workload is moved from the CPU to the GPU (Graphics Processing Unit). By re-defining parts of the ordinary OpenGL pipeline via vertex programs, a distance-from-focus map can be stored in the alpha channel of the final image with little time loss. This can effectively be used to blend a previously blurred version of the scene with a normal render. Different techniques to quickly blur a renderedimage is discussed, to keep the speed up solutions that require moving data from the graphics card is not an option.

Event-triggered real-time systems are desirable to use in environments where the arrival of events are hard to predict. The semantics of an event-triggered system is well mapped to the behaviour of an active database management system (ADBMS), specified using event-condition-action (ECA) rules. The benefits of using an active database, such as persistent data storage, concurrency control, timely response to event occurrences etc. highlights the need for a development method for event-triggered real-time systems using active databases. However, there are problems left to be solved before an ADBMS can be used with confidence in real-time environments. The behaviour of a real-time system must be predictable, which implies a thorough analysed specification with e.g. specified worst case execution times. The predictability requirement is an obstacle for specifying real-time systems as ECA rules, since the rules may affect each other in many intricate ways which makes them hard to analyse. The interaction between the rules implies that it is not enough to verify the correctness of single rules; an analysis must consider the behaviour of the entire rule set. In this dissertation, an approach for developing active applications is presented. A method is examined which starts with an analysed high-level timed automaton specification and transforms the specified behaviour into an implicitly analysed rule set. For this method to be useful, the transformation from timed automata to rules must preserve the exact behaviour of the high level specification. Hence, the aim of this dissertation is to verify transformations between timed automaton specifications and ECA rules. The contribution of this project is a structured set of general transformations between timed automata specifications and ECA rules. The transformations include both transformations of small timed automata constructs for deterministic environments and formally verified timed automata patterns specifying the behaviour of composite events in recent and chronicle context.

Today we are very much dependent on different kinds of real time systems. Usually,a real time system is a system which is interacting with a physical environmentwith sensors or activators. There are many advantages by replacing mechanicalcomponents with electrical ones. For instance, it is usually cheaper and possibleto add new functions to the device without replacing the electronic part, whichwould have been necessary with a mechanical one.The possibility of simulating a distributed system is used throughout the vehi-cle industry. With the simulation of connected sub systems, using modeled busesand real time kernels, one could increase the correctness of the behavior of the sys-tem and consequently decrease the amount of time spent later in the developingprocess.In this master thesis we used modeled CAN-buses and real time models tosimulate the connection and execution time of the systems. The simulation resultsare used to validate the functionality of the distributed system. Additionally, aworst-case response time analysis is made to set timing constraints on the systemto fulfill given deadlines.During the work, different settings of the network are tested to analyze thesystem frequency needed to sustain deadlines and correctness on the network.

The climate in the north is changing over time, which affects the nature in many ways. For instance, some microorganisms that cause infections might become more common. This might have negative consequences for reindeer husbandry. In Sweden, this is an industry that is relatively large. However, even though the reindeer is common in the north the knowledge about its diseases is limited.In this study the prevalence of microorganisms that may cause infection in reindeer was investigated. Comparisons between different sami villages and previous studies were performed to detect differences that could occur due to climate changes. The diseases and microorganisms that were analyzed with PCR were malignant catarrhal fever, herpes infections, Chlamydia sp. and bovine viral diarrhea (BVD). The cause of eye problems in reindeer was also investigated. BVD and bovine leukemia virus where analyzed with ELISA. Next generation sequencing where used for broader screening of samples for microorganisms that might be of interest of future analysis in more detailed follow-up studies.Since not enough samples were available at the time of this study findings could not be linked to changing climate. In the reindeer with eye infection Chlamydia sp., Moraxella sp. and Neisseria sp. can probably be involved causing disease. This should be further investigated to be able to determine whether it is true or not by analyzing samples from individuals without changes in the eyes. The prevalence of reindeers with antibodies against BVD has increased in Sweden since 2012. There will be further studies in this field with reindeers from other northern countries.

The thesis deals with the path planning and movement of the holonomic robot in a dynamic environment. The aim of this work is implementation of several algorithms based on Rapidly-explored random tree algorithm and their comparison in designed dynamic environment.