Inter view motion vector prediction in multiview HEVC

2009

Large traffic network systems require handling huge amounts of data, often distributed over a large geographical region in space and time. Centralised processing is not then the right choice in such cases. In this paper we develop a parallelised Gaussian Mixture Model filter (GMMF) for traffic networks aimed to: 1) work with high amounts of data and heterogenous data (from different sensor modalities), 2) provide robustness in the presence of sparse and missing sensor data, 3) able to incorporate different models in different traffic segments and represent various traffic regimes, 4) able to cope with multimodalities (e.g., due to multimodal measurement likelihood or multimodal state probability density functions). The efficiency of the parallelised GMMF is investigated over traffic flows based on macroscopic modelling and compared with a centralised GMMF.

2014 IEEE Geoscience and Remote Sensing Symposium, 2014

This paper presents an elaboration of the ICA based ICTD, proposed in . The method is applied on three different datasets and three distinctive aspects of its performances are considered. Firstly, we challenge the initial choice of the ICA algorithm, by testing the suitability of two representative tensorial (fourth-order) and one second-order algorithm. Further, we demonstrate the invariance of the proposed decomposition with respect to both the rotation around the line of sight and the change of polarisation basis. Finally, we analyse the potential of supplementary information contained in the second most dominant component.

1996

Abstract Most previously proposed statistical models for the indoor multipath channel include only time of arrival characteristics. However, in order to use statistical models in simulating or analyzing the performance of systems employing spatial diversity combining, information about angle of arrival statistics is also required. Ideally, it would be desirable to characterize the full spare-time nature of the channel. In this paper, a system is described that was used to collect simultaneous time and angle of arrival data at 7 GHz.

Kalman Filter Recent Advances and Applications, 2009

Computer Vision and Pattern …, 2000

Accurate tracking can facilitate the automatic extraction of metric information from video analysis. Many tracking systems rely on a sufficiently accurate dynamic model. These dynamic models must be either known a priori or learnt. This paper addresses the ...

PLoS ONE, 2013

Sex chromosomes are an ideal system to study processes connected with suppressed recombination. We found evidence of microsatellite expansion, on the relatively young Y chromosome of the dioecious plant sorrel (Rumex acetosa, XY1Y2 system), but no such expansion on the more ancient Y chromosomes of liverwort (Marchantia polymorpha) and human. The most expanding motifs were AC and AAC, which also showed periodicity of array length, indicating the importance of beginnings and ends of arrays. Our data indicate that abundance of microsatellites in genomes depends on the inherent expansion potential of specific motifs, which could be related to their stability and ability to adopt unusual DNA conformations. We also found that the abundance of microsatellites is higher in the neighborhood of transposable elements (TEs) suggesting that microsatellites are probably targets for TE insertions. This evidence suggests that microsatellite expansion is an early event shaping the Y chromosome where this process is not opposed by recombination, while accumulation of TEs and chromosome shrinkage predominate later.

2009

Non-smooth optimization problems based on L 1 norms are investigated for smoothing of signals with noise or functions with sharp gradients.

IET Intelligent Transport Systems, 2012

In this paper, we formalize the simultaneous slot allocation problem. It is an extension of the problem currently tackled for allocating airport slots: it deals with all airports simultaneously and it enforces the respect of airspace sector capacities. By solving this novel problem, the system may overcome some major inefficiencies that characterize the current slot allocation process. We tackle the simultaneous slot allocation problem with two algorithms based on metaheuristics, namely Iterated Local Search and Variable Neighborhood Search, and with an integer linear programming model: for each of these three algorithms, we allow a fixed computation time, and we take the best solution found during that time as the final solution. We compare these algorithms on randomly generated instances, and we show that, when small instances are to be tackled, metaheuristics are competitive with the exact model. When medium or large instances are to be tackled, the exact model suffers some major issues in terms of memory and computation time requirements. Metaheuristics, instead, can deal with very large instances, achieving very high quality results.