Fading-ratio-based selection for massive MIMO systems under line-of-sight propagation

Wireless Networks - Massive multiple-input multiple-output (MIMO) enables increased throughput by using spatial multiplexing. However, the throughput may severely degrade when the number of users...     

Feature-combination hybrid recommender systems for automated music playlist continuation

User Modeling and User-Adapted Interaction - Music recommender systems have become a key technology to support the interaction of users with the increasingly larger music catalogs of on-line music...     

Hierarchical Bucket Queuing for Fine‐Grained Priority Scheduling on the GPU

While the modern graphics processing unit (GPU) offers massive parallel compute power, the ability to influence the scheduling of these immense resources is severely limited. Therefore, the GPU is widely considered to be only suitable as an externally controlled co‐processor for homogeneous workloads which greatly restricts the potential applications of GPU computing. To address this issue, we present a new method to achieve fine‐grained priority scheduling on the GPU: hierarchical bucket queuing. By carefully distributing the workload among multiple queues and efficiently deciding which queue to draw work from next, we enable a variety of scheduling strategies. These strategies include fair‐scheduling, earliest‐deadline‐first scheduling and user‐defined dynamic priority scheduling. In a comparison with a sorting‐based approach, we reveal the advantages of hierarchical bucket queuing over previous work. Finally, we demonstrate the benefits of using priority scheduling in real‐world applications by example of path tracing and foveated micropolygon rendering.     

ShapeGenetics: Using Genetic Algorithms for Procedural Modeling

In this paper, we show that genetic algorithms (GA) can be used to control the output of procedural modeling algorithms. We propose an efficient way to encode the choices that have to be made during a procedural generation as a hierarchical genome representation. In combination with mutation and reproduction operations specifically designed for controlled procedural modeling, our GA can evolve a population of individual models close to any high‐level goal. Possible scenarios include a volume that should be filled by a procedurally grown tree or a painted silhouette that should be followed by the skyline of a procedurally generated city. These goals are easy to set up for an artist compared to the tens of thousands of variables that describe the generated model and are chosen by the GA. Previous approaches for controlled procedural modeling either use Reversible Jump Markov Chain Monte Carlo (RJMCMC) or Stochastically‐Ordered Sequential Monte Carlo (SOSMC) as workhorse for the optimization. While RJMCMC converges slowly, requiring multiple hours for the optimization of larger models, it produces high quality models. SOSMC shows faster convergence under tight time constraints for many models, but can get stuck due to choices made in the early stages of optimization. Our GA shows faster convergence than SOSMC and generates better models than RJMCMC in the long run.     

Makeup Lamps: Live Augmentation of Human Faces via Projection

We propose the first system for live dynamic augmentation of human faces. Using projector‐based illumination, we alter the appearance of human performers during novel performances. The key challenge of live augmentation is latency — an image is generated according to a specific pose, but is displayed on a different facial configuration by the time it is projected. Therefore, our system aims at reducing latency during every step of the process, from capture, through processing, to projection. Using infrared illumination, an optically and computationally aligned high‐speed camera detects facial orientation as well as expression. The estimated expression blendshapes are mapped onto a lower dimensional space, and the facial motion and non‐rigid deformation are estimated, smoothed and predicted through adaptive Kalman filtering. Finally, the desired appearance is generated interpolating precomputed offset textures according to time, global position, and expression. We have evaluated our system through an optimized CPU and GPU prototype, and demonstrated successful low latency augmentation for different performers and performances with varying facial play and motion speed. In contrast to existing methods, the presented system is the first method which fully supports dynamic facial projection mapping without the requirement of any physical tracking markers and incorporates facial expressions.     

Similarity-based prioritization of test case automation

The importance of efficient software testing procedures is driven by an ever increasing system complexity as well as global competition. In the particular case of manual test cases at the system integration level, where thousands of test cases may be executed before release, time must be well spent in order to test the system as completely and as efficiently as possible. Automating a subset of the manual test cases, i.e, translating the manual instructions to automatically executable code, is one way of decreasing the test effort. It is further common that test cases exhibit similarities, which can be exploited through reuse when automating a test suite. In this paper, we investigate the potential for reducing test effort by ordering the test cases before such automation, given that we can reuse already automated parts of test cases. In our analysis, we investigate several approaches for prioritization in a case study at a large Swedish vehicular manufacturer. The study analyzes the effects with respect to test effort, on four projects with a total of 3919 integration test cases constituting 35,180 test steps, written in natural language. The results show that for the four projects considered, the difference in expected manual effort between the best and the worst order found is on average 12 percentage points. The results also show that our proposed prioritization method is nearly as good as more resource demanding meta-heuristic approaches at a fraction of the computational time. Based on our results, we conclude that the order of automation is important when the set of test cases contain similar steps (instructions) that cannot be removed, but are possible to reuse. More precisely, the order is important with respect to how quickly the manual test execution effort decreases for a set of test cases that are being automated.     

Electrocatalytic applications of platinum-decorated TiO<Subscript>2</Subscript> nanotubes prepared by a fully wet-chemical synthesis

Pt-decorated \(\hbox {TiO}_{2}\) nanotubes Pt@TiO₂ are prepared only by applying a set of facile wet-chemical redox reactions to ion track-etched polycarbonate templates. First, a homogeneous layer of Pt nanoparticles is deposited onto the complex template surface by reducing potassium tetrachloroplatinate with absorbed dimethylaminoborane. Second, the template is coated with a conformal \(\hbox {TiO}_{2}\) layer, using a chemical bath deposition reaction based on titanium(III) chloride. After the removal of the template, the rutile-type \(\hbox {TiO}_{2}\) nanotubes remain decorated with Pt nanoparticles and nanoparticle-clusters on their outside. During the process, neither vacuum techniques nor external current sources or addition of heat are employed. The crystallinity, composition, and morphology of the composite nanotubes are analysed by X-ray diffraction, scanning and transmission electron microscopy as well as by energy-dispersive X-ray spectroscopy. Finally, the obtained materials are examplarily applied in the electrooxidation of ethanol and formic acid, and their performances have been evaluated. Compared to conventional carbon black-supported Pt nanoparticles, the Pt@TiO₂ nanotubes show higher reaction rates. Mass activities of 2.36 \(\hbox {A}\hbox { mg}_{\rm Pt}^{-1}\hbox { cm}^{-2}\) are reached in ethanol oxidation and 7.56 \(\hbox {A}\hbox { mg}_{\rm Pt}^{-1}\hbox { cm}^{-2}\) in the formic acid oxidation. The present structures are able to exploit the synergy of Pt and \(\hbox {TiO}_{2}\) with a bifunctional mechanism to result in powerful but easy-to-fabricate catalyst structures. They represent an easily producible type of composite nanostructures which can be applied in various fields such as in catalytics and sensor technology.     

Local Magnetic Measurements of Trapped Flux Through a Permanent Current Path in Graphite

Temperature- and field-dependent measurements of the electrical resistance of different natural graphite samples suggest the existence of superconductivity at room temperature in some regions of the samples. To verify whether dissipationless electrical currents are responsible for the trapped magnetic flux inferred from electrical resistance measurements, we localized them using magnetic force microscopy on a natural graphite sample in remanent state after applying a magnetic field. The obtained evidence indicates that at room temperature a permanent current flows at the border of the trapped flux region. The current path vanishes at the same transition temperature \(T_c\approx 370\) K as the one obtained from electrical resistance measurements on the same sample. This sudden decrease in the phase is different from what is expected for a ferromagnetic material. Time-dependent measurements of the signal show the typical behavior of flux creep of a permanent current flowing in a superconductor. The overall results support the existence of room-temperature superconductivity at certain regions in the graphite structure and indicate that magnetic force microscopy is suitable to localize them. Magnetic coupling is excluded as origin of the observed phase signal.