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1	Energy-Efficient Interactive Ray Tracing of Static Scenes on Programmable Mobile GPUs Lohrmann, Peter J 11 January 2007 (has links) Mobile technology is improving in quality and capability faster now than ever before. When first introduced, cell phones were strictly used to make voice calls; now, they play satellite radio, MP3s, streaming television, have GPS and navigation capabilities, and have multi-megapixel video cameras. In the near future, cell phones will have programmable graphics processing units (GPU) that will allow users to play games similar to those currently available for top-of-the-line game consoles. Personal digital assistants enable users with full email, scheduling, and internet browsing capabilities in addition to those features offered on cell phones. Underlying all this mobile technology and entertainment is a battery whose technology has just barely tripled in the past 15 years, compared to available disk capacity that has increased over 1,000-fold. Ray tracing is a rendering technique used to generate photorealistic images that include reflections, refraction, participating media, and can fairly easily be extended to include photon mapping for indirect illumination and caustics. In recent years, ray tracing has been implemented on the GPU using various acceleration structures to facilitate rendering. Until now, all studies have used build time and achievable frame rates to determine which acceleration structure is best for ray tracing. We present the very first results comparing both CPU and GPU raytracing using various acceleration structures in terms of energy consumption. By exploring per-pixel costs, we provide insight on the energy consumption and frame rates that can be experienced on cell phones and other mobile devices based on currently available screen resolutions. Our results show that the choice in processing unit has the greatest affect on energy and time costs of ray tracing, followed by the size of the viewport used, and the choice of acceleration structure has the least impact on efficiency. For mobile devices enabled with a programmable GPU, whether it is a cell phone, PDA, or laptop computer, a bounding volume hierarchy implemented on the GPU is the most energy-efficient acceleration structure for ray tracing. Ray tracing on cellular phones with smaller screen resolutions is most energy-efficient using a CPU-based Kd-Tree implementation. mobile devices uniform grid KdTree BVH mobile GPGPU energy GPU computer graphics ray tracing Mobile communication systems Energy consumption Ray tracing
2	Indexování databází: SP-GiST pro PostGIS / Database Indexing: SP-GiST for PostGIS Matula, Lukáš January 2016 (has links) The goal of the master ́s thesis is to study index methods, spatial data type objects in PostgreSQL database systems and to create SP-GiST index by quadtree in the PostGIS. The PostGIS is spatial database, which extends of PostgreSQL. PostGIS adds support for geographic and spatial objects. It is a big benefit. PostGIS has its own data types, methods and GiST index too, but there is SP-GiST index missing, therefore master's thesis was created.
3	Discovering Implant Terms in Medical Records Jerdhaf, Oskar January 2021 (has links) Implant terms are terms like "pacemaker" which indicate the presence of artifacts in the body of a human. These implant terms are key to determining if a patient can safely undergo Magnetic Resonance Imaging (MRI). However, to identify these terms in medical records is time-consuming, laborious and expensive, but necessary for taking the correct precautions before an MRI scan. Automating this process is of great interest to radiologists as it ideally saves time, prevents mistakes and as a result saves lives. The electronic medical records (EMR) contain the documented medical history of a patient, including any implants or objects that an individual would have inside their body. Information about such objects and implants are of great interest when determining if and how a patient can be scanned using MRI. This information is unfortunately not easily extracted through automatic means. Due to their sparse presence and the unusual structure of medical records compared to most written text, makes it very difficult to automate using simple means. By leveraging the recent advancements in Artificial Intelligence (AI), this thesis explores the ability to identify and extract such terms automatically in Swedish EMRs. For the task of identifying implant terms in medical records a generally trained Swedish Bidirectional Encoder Representations from Transformers (BERT) model is used, which is then fine-tuned on Swedish medical records. Using this model a variety of approaches are explored two of which will be covered in this thesis. Using this model a variety of approaches are explored, namely BERT-KDTree, BERT-BallTree, Cosine Brute Force and unsupervised NER. The results show that BERT-KDTree and BERT-BallTree are the most rewarding methods. Results from both methods have been evaluated by domain experts and appear promising for such an early stage, given the difficulty of the task. The evaluation of BERT-BallTree shows that multiple methods of extraction may be preferable as they provide different but still useful terms. Cosine brute force is deemed to be an unrealistic approach due to computational and memory requirements. The NER approach was deemed too impractical and laborious to justify for this study, yet is potentially useful if not more suitable given a different set of conditions and goals. While there is much to be explored and improved, these experiments are a clear indication that automatic identification of implant terms is possible, as a large number of implant terms were successfully discovered using automated means. AI Machine Learning Medical Records Patient Records Medical Record Electronic Records Electronic Medical Records BERT EMR Implant Terms Implants Term Terms Term Discovery Artificial Intelligence Word Similarity Word Similarity word-similarity embeddings word embeddings word-embeddings transformers KDTREE BALLTREE NER AI Artificiel Intelligens Maskininlärning Patient Journal Medicinsk Journal Elektronisk Medicinsk Journal Termer BERT KDTREE BALLTREE NER liknande ord transformers EMR

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