Extraction of keyphrases from individual documents is a research area in which one try to extract a small set of keyphrases that describe the content of a single document. The advantages with this form of extraction is that it retains most of the semantic context from the document.In this thesis we focus on the news article domain and use the structure of a news article to improve the quality of the extracted keyphrases. An existing individual document keyphrase extraction algorithm is used as the basis. This algorithm is enhanced by implementing a weighting system based upon the structure of news articles. In addition some other common methods for keyword extraction is applied. The effects of these changes are tested extensively in the evaluation phase.In the evaluation of the implemented prototype we find that the introduction of a weight based system yields results that are equal to the basic algorithm and that few improvements can be made. We do however find that an automatically generated stopword list based on the corpus improves the results by 1-2%.

This thesis studies the use of iPad in a Norwegian classroom. The aim of this thesis is to evaluate how suitable the iPad is in a classroom, what are the advantages and disadvantages of using it and if it can produce increased motivation towards learning among students. To conduct this evaluation in a realistic setting, a class with 15 students together with 5 teachers were each provided with 1 iPad. A set of qualitative data gathering activities were selected; observations, focus group meetings and interviews. Through these activities empirical data was obtained for further analysis and discussion.Abstract The findings indicate that the iPad hold many advantages in a classroom, but not without disadvantages. iPad's convenient size made reading easier for the students. Multiple means of content representation and possible ways of expression provided students with options in learning. It was found an increase in motivation among several of the students. The disadvantages are that the iPad requires extensive training, if it would be used to it fullest potential and not as another substitute to a laptop computer. Lack of educational content, such as multimedia enriched books is needed to increase learning, simply because PDF versions of textbooks does not bring anything new except increased portability. Abstract The main challenge in this project was the balancing act of two somewhat conflicting goals: Acquiring knowledge of the pedagogical advantages of the iPad, thus covering the breadth of its features, while at the same time being constrained by very strict network restrictions, which resulted in that not all of iPad's features could be used. Abstract From this work, the project team has gained deep insight in how the iPad should be integrated into schools. We are particularly pleased with how many of the students used the iPad to solve tasks and used it with their schoolwork. The teachers in this thesis are positive towards the iPad's educational capabilities, and this thesis will provide useful information for anyone considering using the iPad in school and what kind of experiences and difficulties to expect.

JavaScript has gained increased usage and attention the last years, but development and testing methods is still lagging behind.To mitigate some of these issues, this thesis brings together unit testing and JavaScript, using test-driven development as a methodology. Through exploration of these topics, the differentiators in a unit testing framework are considered. Existing frameworks are also discussed and how the terminology in JavaScript differs from traditional xUnit family frameworks.By creating and running a set of four test cases, both the general and unique features of JavaScript are tested in hand-picked frameworks, which were decided through an evaluation process. One of the contributions is based on this; a recommendation for a minimum set of test library features for a JavaScript unit testing framework.Various factors were found to differentiate the frameworks, and so the thesis also provides a Discovery test case to emphasize some of these aspects. This test case provides practitioners with a quick option for learning a new framework. The set of test cases can be applied to new frameworks to assess their functionality.As the thesis explores an area with little current research, suggestions for further work present several topics, ranging from system level JavaScript testing to quantitative studies building on the set of test cases.

This project has implemented SimiLite, a plug-in to SQLite which en-ables the usage of metric indices in SQL tables. SimiLite can easily beextended with different indices, and the indices LAESA and SSSTreehas been implemented and verified.This project has also implemented a framework for easy comparisonof the indices within SimiLite.It was found that while SimiLite causes a slow-down of about 5-10compared to the reference solution for a light metric, this will balanceout quickly once the cost of the metric increases.

This thesis is an investigation into how the signature quadratic form distance can be used to search in music.Using the method used for images by Beecks, Uysal and Seidl as a starting point,I create feature signatures from sound clips by clustering features from their frequency representations.I compare three different feature types, based on Fourier coefficients, mel frequency cepstrum coefficients (MFCCs), and the chromatic scale.Two search applications are considered.First, an audio fingerprinting system, where a music file is located by a short recorded clip from the song.I run experiments to see how the system's parameters affect the search quality, and show that it achieves some robustness to noise in the queries, though less so that comparable state-of-the-art methods.Second, a query-by-humming system where humming or singing by one user is used to search in humming/singing by other users.Here none of the tested feature types achieve satisfactory search performance. I identify and discuss some possible limitations of the selected feature types for this task.I believe that this thesis serves to demonstrate the versatility of the feature clustering approach, and may serve as a starting point for further research.

A desired trend within high energy physics is to increase particle accelerator luminosities,leading to production of more collision data and higher probabilities of finding interestingphysics results. A central data analysis technique used to determine whether results areinteresting or not is the maximum likelihood method, and the corresponding evaluation ofthe negative log-likelihood, which can be computationally expensive. As the amount of datagrows, it is important to take benefit from the parallelism in modern computers. This, inessence, means to exploit vector registers and all available cores on CPUs, as well as utilizingco-processors as GPUs.This thesis describes the work done to optimize and parallelize a prototype of a centraldata analysis tool within the high energy physics community. The work consists of optimiza-tions for multicore processors, GPUs, as well as a mechanism to balance the load betweenboth CPUs and GPUs with the aim to fully exploit the power of modern commodity comput-ers. We explore the OpenCL standard thoroughly and we give an overview of its limitationswhen used in a large real-world software package. We reach a single-core speedup of ∼ 7.8xcompared to the original implementation of the toolkit for the physical model we use through-out this thesis. On top of that follows an increase of ∼ 3.6x with 4 threads on a commodityIntel processor, as well as almost perfect scalability on NUMA systems when thread affinityis applied. GPUs give varying speedups depending on the complexity of the physics modelused. With our model, price-comparable GPUs give a speedup of ∼ 2.5x compared to amodern Intel CPU utilizing 8 SMT threads.The balancing mechanism is based on real timings of each device and works optimally forlarge workloads when the API calls to the OpenCL implementation impose a small overheadand when computation timings are accurate.

Modern chip multi-processors offer increased computing power through hardware parallelism. However, for applications to exploit this parallelism, they have to be either designed for or adapted to the new processor architectures. Seismic processing applications usually handle large amounts of data that are well suited for the task-level parallelism found in multi-core shared memory computer systems. In this thesis, a large production code for seismic inversion is profiled and analyzed to find areas of the code suitable for parallel optimization. These code fragments are then optimized through parallelization and by using highly optimized multi-threaded libraries. Our parallelizations of the linearized AVO seismic inversion algorithm used in the application, scales up to 24 cores, with almost linear speedup up to 16 cores, on a quad twelve-core AMD Opteron system. Overall, our optimization efforts result in a performance increase of about 60 % on a dual quad-core AMD Opteron system.The optimization efforts are guided by the Seven Dwarfs taxonomy and proposed benchmarks. This thesis thus serves as a case study of their applicability to real-world applications.This work is done in collaborations with Statoil and builds on previous works by Andreas Hysing, a former HPC-Lab master student, and by the author.

Smidig systemutvikling har i løpet av de siste årene blitt en svært populær utviklingsmetode for utarbeidelse av IT-systemer. Denne oppgaven ser nærmere på hvordan man integrerer arbeid med brukeropplevelse i en smidig utviklingsprosess. Selve studiet er todelt og bygger videre på arbeidet som ble gjennomført høsten 2010 i forstudiet <i>Brukervennlighet i smidig systemutvikling</i>.I første del av oppgaven ser vi på samspillet mellom kunde og leverandør for de tre prosjektene som ble studert i forprosjektet, og da spesielt med hensyn på brukerinvolvering. Informasjon om dette er hentet inn gjennom intervjuer med prosjektledere for utviklingsprosjektene og tilhørende representanter fra kundesiden. Studiet viser at utviklingsprosjekter er en svært kompleks prosess, der man har mange elementer å forholde seg til. Et viktig element som kom frem i dette studiet er at kunderepresentanten har en svært sentral rolle. Det kreves et godt samarbeid mellom kunderepresentanten og utviklere, med god to-veis kommunikasjon, for at utviklingsprosjektet skal bli vellykket. Med bakgrunn i resultatene i fra undersøkelsene om samspillet mellom kunde og utviklere ønsket vi i den andre delen av oppgaven å se nærmere på de generelle mulighetene og utfordringene som eksisterer mellom disiplinene brukeropplevelse og smidig utvikling. Dette innebar å intervjue noen representanter fra de to fagmiljøene for smidig utvikling og brukeropplevelse i Norge. Resultatene av intervjuene viste at det er et stort engasjement i begge fagmiljøene rundt denne problematikken. Det kom frem at dagens beste praksis er å alltid involvere brukeropplevelse tidlig i utviklingsprosessen. I tillegg vil det i en del tilfeller være hensiktsmessig å la brukeropplevelse ligge en iterasjon i forkant, da brukeropplevelse ønsker å ha et holistisk overblikk, mens utviklerne ønsker å fokusere mer på detaljene.Studiet viser også at det fortsatt eksisterer utfordringer i samspillet mellom brukeropplevelse og smidige utviklere, men at man er på riktig spor i forhold til å skape det gode samarbeidet. Dette har sammenheng med at smidig utvikling er relativt ungt, og er i en modningsfase der man søker å finne den optimale prosessen.

Artificial intelligence and learning is a growing field. There are many ways of making a computer program learn, in most cases one have a specific problem one wants to solve and do not really care how it is solved. This thesis have a specific problem, but the main focus is on how it is solved. One of the most exciting ways to learn is by the so called unsupervised learning methods, where programs/agents learn without any human interaction. Psychologists and Neurologists have long tried to understand how the human brain works, but due to its complexity there are still some obstacles left before we will be able to simulate the different functionalities. This thesis is an attempt to get one step closer to solving the problem of how learning happens and memories form. If we were to be able to simulate human learning in a machine there is no telling where it could end. Jørn Hokland has put forward three learning rules that may describe how learning happens. These rules will be examined and then used in an artificial neural network with the intention to control a simulated robot. Artificial neural networks (ANNs) are more or less inspired by the biological neural networks (BNNs) found in humans and animals. As we will see this thesis seeks to be one of the more biologically inspired.

The Creek system has an architecture that facilitates combined case-based and model-based reasoning. The jColibri system, developed by the CBR group of Universidad Complutense in Madrid, contains a library of CBR system components intended for sharing and reuse. The system also contains an ontology (CBROnto) of CBR tasks and methods for explicit modelling of a CBR systems, in addition to general CBR terminology. In this master degree project, Creek and jColibri are compared with the aim of developing a mechanism for importing jColibri components to Creek, so that they can be integrated into a running Creek system. The mechanism is exemplified through selection of a few specific components, and integration of these components into an implemented demonstrator system. In addition, efforts needed to bring Creek into the jColibri framework are identified.