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Reconstruction of incomplete decoded videos for use in objective quality metrics

Many full-reference objective metrics require that the original and the degraded video contain the same number of frames. Most codecs are not able to decode the video properly when the video is subject to packet losses and produce incomplete video files with lower number of frames than the original video. In this paper we present a simple method to reconstruct the degraded videos so that it has th

MIMO systems and antennas for terminals

MIMO technology has facilitated tremendous performance improvements in wireless communications, allowing the data rate to increase linearly with the number of antennas used, at no additional expense in transmit power or spectrum. However, the tremendous performance gain can only be achieved by multi-antenna designs that provide low coupling and correlation, as well as high total efficiency. Such d

Analysis of User Demand Patterns and Locality for Youtube traffic

Video content constitutes a large share of residential Internet traffic. The major source of video content as of today is YouTube. In this paper, we analyse the user demand patterns for YouTube in two metropolitan access networks with more than 1 million requests over three consecutive weeks in the first network and more than 600,000 requests over four consecutive weeks in the second network. In p

Increasing Robotic Machining Accuracy Using Offline Compensation Based on Joint-Motion Simulation

In this paper an approach for improving robot machining accuracy through simulation-assisted path planning within Computer-Aided Manufacturing (CAM) tools is investigated. The method comprises modeling of dynamic robot behaviour under influence of process forces and a subsequent simulation of the robot motion which results in an offline prediction of deflection errors during the machining task. Th

Hierarchical stochastic motion blur rasterization

We present a hierarchical traversal algorithm for stochastic rasterization of motion blur, which efficiently reduces the number of inside tests needed to resolve spatio-temporal visibility. Our method is based on novel tile against moving primitive tests that also provide temporal bounds for the overlap. The algorithm works entirely in homogeneous coordinates, supports MSAA, facilitates efficient

Design and Novel Uses of Higher-Dimensional Rasterization

This paper assumes the availability of a very fast higher-dimensional rasterizer in future graphics processors. Working in up to five dimensions, i.e., adding time and lens parameters, it is well-known that this can be used to render scenes with both motion blur and depth of field. Our hypothesis is that such a rasterizer can also be used as a flexible tool for other, less conventional, usage area

Distributed constraint programming with agents

Many combinatorial optimization problems lend themselves to be modeled as distributed constraint optimization problems (DisCOP). Problems such as job shop scheduling have an intuitive matching between agents and machines. In distributed constraint problems, agents control variables and are connected via constraints. We have equipped these agents with a full constraint solver. This makes it possibl

Realizing Efficient Execution of Dataflow Actors on Manycores

Embedded DSP computing is currently shifting towards manycore architectures in order to cope with the ever growing computational demands. Actor based dataflow languages are being considered as a programming model. In this paper we present a code generator for CAL, one such dataflow language. We propose to use a compilation tool with two intermediate representations. We start from a machine model o

Impact of gas-to-particle partitioning approaches on the simulated radiative effects of biogenic secondary organic aerosol

The oxidation of biogenic volatile organic compounds (BVOCs) gives a range of products, from semi-volatile to extremely low-volatility compounds. To treat the interaction of these secondary organic vapours with the particle phase, global aerosol microphysics models generally use either a thermodynamic partitioning approach (assuming instant equilibrium between semi-volatile oxidation products and

Adaptive texture space shading for stochastic rendering

When rendering effects such as motion blur and defocus blur, shading can become very expensive if done in a naive way, i.e. shading each visibility sample. To improve performance, previous work often decouple shading from visibility sampling using shader caching algorithms. We present a novel technique for reusing shading in a stochastic rasterizer. Shading is computed hierarchically and sparsely

Filtered Stochastic Shadow Mapping Using a Layered Approach

Given a stochastic shadow map rendered with motion blur, our goal is to render an image from the eye with motion-blurred shadows with as little noise as possible. We use a layered approach in the shadow map and reproject samples along the average motion vector, and then perform lookups in this representation. Our results include substantially improved shadow quality compared to previous work and a

Biocatalytic polyester acrylation-process optimization and enzyme stability.

An OH-functional polyester has been acrylated via transesterification of ethyl acrylate, catalyzed by Candida antarctica lipase B (CalB) in two different preparations: Novozym(R) 435 and immobilized on Accurel(R) MP1000. The batch process resulted in incomplete acrylation as well as severe degradation of the polyester. A high degree of acrylation was achieved by optimization through the applicatio

Constraint Programming Approach to Reconfigurable Processor Extension Generation and Application Compilation

Abstract in UndeterminedIn this article, we present a constraint programming approach for solving hard design problems present when automatically designing specialized processor extensions. Specifically, we discuss our approach for automatic selection and synthesis of processor extensions as well as efficient application compilation for these newly generated extensions. The discussed approach is i

Measured adaptive matching performance of a MIMO terminal with user effects

Absorption and impedance mismatch due to the proximity of a user as well as certain propagation channel characteristics can severely degrade the multiple-input multiple-output (MIMO) performance of multi-antenna terminals in real usage scenarios. In this context, we investigated the potential of adaptive impedance matching (AIM) to mitigate performance degradation from these effects based on chann

Detecting region transitions for human augmented mapping

In this paper, we describe a concise method for the feature-based representation of regions in an indoor environment and show how it can also be applied for door-passage-independent detection of transitions between regions to improve communication with a human user.

Nonlinear approximation of functions in two dimensions by sums of exponential functions

We consider the problem of approximating a given function in two dimensions by a sum of exponential functions, with complex-valued exponents and coefficients. In contrast to Fourier representations where the exponentials are fixed, we consider the nonlinear problem of choosing both the exponents and coefficients. In this way we obtain accurate approximations with only few terms. Our approach is bu

Stochastic Depth Buffer Compression using Generalized Plane Encoding

In this paper, we derive compact representations of the depth function for a triangle undergoing motion or defocus blur. Unlike a static primitive, where the depth function is planar, the depth function is a rational function in time and the lens parameters. Furthermore, we show how these compact depth functions can be used to design an efficient depth buffer compressor/decompressor, which signifi

Efficient Adaptive and Dynamic Mesh Refinement Based on a Non-recursive Strategy

In this paper, we present a meshing scheme for the implementation of an adaptive tessellation of triangular meshes on the graphics processing unit (GPU). Tessellation is performed according to a local test to generate primitives dynamically. The refinement procedure does not require the pre-computation of any refinement pattern. The resulting adaptive procedure is efficient and simple, and generat

Per-Vertex Defocus Blur for Stochastic Rasterization

We present user-controllable and plausible defocus blur for a stochastic rasterizer. We modify circle of confusion coefficients per vertex to express more general defocus blur, and show how the method can be applied to limit the foreground blur, extend the in-focus range, simulate tilt-shift photography, and specify per-object defocus blur. Furthermore, with two simplifying assumptions, we show th