RFID is an up-and-coming technology holding promise of closing information gaps in the supply chain. Information is probably the biggest driver of performance in supply chains today and information control is seen as a huge advantage in management. This report addresses how RFID may contribute to improve management and supply chain within warehouse management. By doing a case study of three Norwegian businesses the report finds processes in management and logistics. An evaluation of where a theoretical RFID implementation may impact show that RFID increases data and data collection in almost all identified processes. Both management and logistics in general have the potential of automating several processes and collected data results in increased information sharing. When businesses handle identified challenges in the technology RFID have huge possibilities in improving warehouse management and the supply chain in general.

Vector graphics provide smooth, resolution-independent images and are used for user interfaces, illustrations,fonts and more in a wide range of applications.During the last years, handheld devices have become increasingly powerful and feature-rich. It is expectedthat an increasing number of devices will contain dedicated GPUs (graphics processing units)capable of high quality 3d graphics for games. It is of interest to use the same hardware for acceleratingvector graphics.OpenVG is a new API for vector graphics rendering on a wide range of devices from desktop to handheld.Implementations can use different algorithms and ways of accelerating the rendering process in hardware,transparent from the user application.State of the art vector graphics solutions perform much processing in the CPU, transfer large amounts ofvertex and polygon data from the CPU to GPU, and generally use the GPU in a suboptimal way. Moreefficient approaches are desirable.Recently developed algorithms provide efficient curve rendering with little CPU overhead and a significantreduction in vertex and polygon count. Some issues remain before the approach can be used forrendering in an OpenVG implementation.This thesis builds on these algorithms to develop an approach that can be used for a conformant OpenVGimplementation. A number of issues, mainly related to precision, robustness and missing features, areidentified. Solutions are suggested and either implemented in a prototype or left as future work.Preliminary tests compare the new approach to traditional approximation with line segments.Vertex and triangle count as well as the simulated tile list counts are lowered significantly and CPUoverhead from subdivision is avoided or greatly reduced in many common cases. CPU overhead fromtessellation is eliminated through the use of an improved stencil buffer technique.Data-sets with different properties show varying amounts of improvement from the new approach. Forsome data-sets, vertex and triangle count is lowered by up to 70% and subdivision is completely avoided,while for others there is no improvement.

Today's games are social on a level that could only be imagined before. With modern games putting a stronger emphasis on social networking than ever before, the identity in the game often becomes on par with the one in real life. Yet many games lack the really strong networking tools, especially when networking regarding players of different games is concerned.Geelix is a project which tries to enhance the social gaming aspect by providing sharing of what has been aptly named: gaming experiences. The motivation for this goal is to enable stronger support for letting friends take part in your online, or even offline, experiences. It is the belief that sharing gaming experiences is a key element in building strong social networks in games. This master thesis was written in relation to the Geelix project, where the focus was on enhancing the Geelix live sharing experience with advanced methods for video compression and streaming.

You can see sliding doors everywhere, be it at the grocery store or the hospital. These doors are today mostly based on naive, motion sensing, and hence not very intelligent in deciding to open or not. I propose a solution by replacing the traditional sensor with the more sophisticated Microsoft Kinect depth mapping sensor allowing for skeletal tracking and feature extraction. I have applied hidden markov models to the behavioural features to understand the human intentions. Combined with a few simple rules, this solution proved to be accurate in 4 out of 5 times in understanding the user's intention in a controlled laboratory test.

Lung cancer is one of the deadliest and most common types of cancer inNorway. Early and precise diagnosis is crucial for improving the survivalrate. Diagnosis is often done by extracting a tissue sample in the lung throughthe mouth and throat. It is difficult to navigate to the tissue because of thecomplexity of the airways inside the lung and the reduced visibility. Our goalis to make a program that can automatically extract a map of the Airwaysdirectly from X-ray Computer Tomography(CT) images of the patient. Thisis a complex task and requires time consuming processing.In this thesis we explore different methods for extracting the Airways fromCT images. We also investigate parallel processing and the usage of moderngraphic processing units for speeding up the computations. We rate severalmethods in terms of reported performance and the possibility of parallelprocessing. The best rated method is implemented in a parallel frameworkcalled Open Computing Language.The results shows that our implementation is able to extract large parts ofthe Airway Tree, but struggles with the smaller airways and airways thatdeviate from a perfect circular cross-section. Our implementation is ableto process a full CT scan using less than a minute with a modern graphicprocessing units. The implementation is very general and is able to extractother tubular structures as well. To show this we also run our implementationon a Magnetic Resonance Angio dataset for finding blood vessels in the brainand achieve good results.We see a lot of potential in this method for extracting tubular structures. Themethod struggles the most with noise handling and tubes that deviate froma circular cross-sectional shape. We believe that this can be improved byusing another method than ridge traversal for the centerline extraction step.Because this is a local greedy algorithm, it often terminates prematurely dueto noise and other image artifacts.

This project follows the design science research methodology and uses an extended version of the technology acceptance model (TAM) to study the acceptance of a mobile augmented reality application with historical photographs and information. A prototype application was developed in accordance with general principles for usability design, and a street survey was conducted, where 42 participants out on the street got the opportunity to try the application before answering a questionnaire. A modified version of the same questionnaire was later on used in a web survey with 200 participants that watched a short video demonstration before answering the questionnaire.The results show that there is an interest in mobile augmented reality applications with historical pictures and information. Both perceived usefulness and perceived enjoyment have a direct impact on the intention to use this type of application. This finding suggests that institutions developing this type of applications can benefit from focusing on both the fun and the useful aspect of their applications.

This thesis discusses the possibilities and limitations when developing mobile ap- plications natively vs. HTML5. Research has been carried out to understand how mobile devices can be utilized to its fullest when running applications, and a native iPad application was developed to help in discovering unforeseen challenges. It was developed with a client-server architecture to decrease the amount of work it would take to implement the application natively as a client for all the different mobile platforms.The native approach combined with the client-server architecture is not cross platform by nature, but the study shows that its benefits outweighs the limitations in many cases. It is also shown that time- and cost of the development of an appli- cation favours the HTML5 approach. HTML5 was concluded to be a solution that solves the cross platform problem, but it lacks both performance and API access. However, the type of application developed should be the deciding factor of what solution to choose.

A dream about evolvable structures that change to fit its environment could be a peak into the future.Cellular automata (CA) being a simple discrete model, it has the ability to simulate biology by growing, reproducing and dying. Along with genetic algorithms, they both simulates biological systems that can be used to realize this dream.In this thesis, a skyscraper is grown using multiple cellular automata. The skyscraper is grown in a CA simulator and visualizer made for this thesis. The result is a stable structure containing floors, walls, windows and ceilings with lights.Genetic algorithms have been used to grow electrical wiring from a power source in the basement up to power outlets on each floor, powering the lights.The dream is a house that covers all your needs.This thesis is a proof of concept, that it is possible to grow a stable skyscraper using a CA with multiple sub-CAs growing lights and electrical wiring inside.The project is in the area of unconventional computation, done at NTNU Trondheim.

Since the release of BWAPI in 2009, StarCraft has taken the position as the leading platform for research in artificial intelligence in real-time strategy games. With competitions being held annually at AIIDE and CIG, there is much prestige in having an agent compete and do well. This thesis is aimed at presenting a model for doing opponent modeling and strategic reasoning in StarCraft.We present a method for constructing a model based on strategies, on the form of build orders, learned from expert demonstrations. This model is aimed at recognizing the strategy of the opponent and selecting a strategy that is capable of countering the recognized strategy. The method puts weight on the ordering and timing of buildings in order to do advanced recognition.

Counting and classifying fish moving upstream in rivers to spawn is a useful way of monitoring the population of different species. Today, there exist some commercial solutions, along with some research that addresses the area. Case-based reasoning is a process that can be used to solve new problems based on previous problems. This thesis studies the possibilities of combining image processing techniques and case-based reasoning to classify species of fish which are similar to each other in both shape, size and color. Methods for image preprocessing are discussed, and tested. Methods for feature extraction and a case-based reasoning prototype are proposed, implemented and tested with promising results.