Nearest neighbour decoding with pilot-assisted channel estimation for fading multiple-access channels

This paper studies a noncoherent multiple-input multiple-output (MIMO) fading multiple-access channel (MAC). The rate region that is achievable with nearest neighbour decoding and pilot-assisted channel estimation is analysed and the corresponding pre-log region, defined as the limiting ratio of the rate region to the logarithm of the signal-to-noise ratio (SNR) as the SNR tends to infinity, is determined. © 2011 IEEE.

On-going generation of multiple forms of HIV-1 intersubtype recombinants in the Yunnan Province of China

Objectives: To investigate the molecular epidemiology of HIV in China's Yunnan Province, where the initial HIV-1 outbreak among injecting drug users (IDU) occurred in 1989, and to analyse the genesis and interrelationship of the epidemic with that in surrounding areas. Design: A molecular epidemiological investigation was conducted among IDU in three prefectures in Yunnan Province, including Wenshan (east), Honghe (southeast) and Dehong (west). Methods: Thirty-nine specimens were collected from consenting IDU in 2000-2001. The nucleotide sequences of 2.6 kb gag-RT and 340 base pair (bp) env (C2/V3) regions were determined. Phylogenetic tree and recombination breakpoint analyses were performed. Results: The circulating recombinant form (CRF), CRF08_BC, predominated in east Yunnan near Guangxi Province (89% in Wenshan and 81% in Honghe), whereas it was not detected in Dehong(0/14) in the west. In contrast, 71% (10/14) of the Dehong isolates were unique recombinant forms (URF), mostly between subtypes B' (Thailand variant of subtype B) and C, with distinct profiles of recombination breakpoints. The subtype B' accounts for the remaining 29% (4/14) of Dehong isolates. Interestingly, two Honghe isolates (2/16) shared some of the precise B'/C recombination breakpoints with CRF07_BC. Conclusion: New recombinant strains are arising continually in west Yunnan near the Myanmar border. Some appeared to be secondary recombinants derived from CRF07_BC that had further recombined with other strains. The uneven distribution of subtypes, CRF and URF, suggests the presence of independent transmission networks and clusters among IDU in Yunnan. (C) 2002 Lippincott Williams Wilkins.

2D PIV measurements in the near field of grid turbulence using stitched fields from multiple cameras

We present measurements of grid turbulence using 2D particle image velocimetry taken immediately downstream from the grid at a Reynolds number of Re M = 16500 where M is the rod spacing. A long field of view of 14M x 4M in the down- and cross-stream directions was achieved by stitching multiple cameras together. Two uniform biplanar grids were selected to have the same M and pressure drop but different rod diameter D and crosssection. A large data set (10 4 vector fields) was obtained to ensure good convergence of second-order statistics. Estimations of the dissipation rate ε of turbulent kinetic energy (TKE) were found to be sensitive to the number of meansquared velocity gradient terms included and not whether the turbulence was assumed to adhere to isotropy or axisymmetry. The resolution dependency of different turbulence statistics was assessed with a procedure that does not rely on the dissipation scale η. The streamwise evolution of the TKE components and ε was found to collapse across grids when the rod diameter was included in the normalisation. We argue that this should be the case between all regular grids when the other relevant dimensionless quantities are matched and the flow has become homogeneous across the stream. Two-point space correlation functions at x/M = 1 show evidence of complex wake interactions which exhibit a strong Reynolds number dependence. However, these changes in initial conditions disappear indicating rapid cross-stream homogenisation. On the other hand, isotropy was, as expected, not found to be established by x/M = 12 for any case studied. © Springer-Verlag 2012.

Compression techniques applied to multiple speech recognition systems

Speech recognition systems typically contain many Gaussian distributions, and hence a large number of parameters. This makes them both slow to decode speech, and large to store. Techniques have been proposed to decrease the number of parameters. One approach is to share parameters between multiple Gaussians, thus reducing the total number of parameters and allowing for shared likelihood calculation. Gaussian tying and subspace clustering are two related techniques which take this approach to system compression. These techniques can decrease the number of parameters with no noticeable drop in performance for single systems. However, multiple acoustic models are often used in real speech recognition systems. This paper considers the application of Gaussian tying and subspace compression to multiple systems. Results show that two speech recognition systems can be modelled using the same number of Gaussians as just one system, with little effect on individual system performance. Copyright © 2009 ISCA.

Multiple color reflection in a single unit cell using double-layer electrochromic reaction

Multiple color states have been realized in single unit cell using double electrochromic (EC) reaction. The precise control of bistability in EC compounds which can maintain several colors on the two separated electrodes allows this new type of pixel to be realized. The specific electrical driving gives a way to maintain both sides in the reduced EC states and this colors overlapping in the vertical view direction can achieve the black state. The four color states (G, B, W, BK) in one cell/pixel can make a valuable progress to achieve a high quality color devices such like electronic paper, outdoor billboard, smart window and flexible display using external light source. © 2012 Optical Society of America.

MCBoost: Multiple classifier boosting for perceptual co-clustering of images and visual features

We present a new co-clustering problem of images and visual features. The problem involves a set of non-object images in addition to a set of object images and features to be co-clustered. Co-clustering is performed in a way that maximises discrimination of object images from non-object images, thus emphasizing discriminative features. This provides a way of obtaining perceptual joint-clusters of object images and features. We tackle the problem by simultaneously boosting multiple strong classifiers which compete for images by their expertise. Each boosting classifier is an aggregation of weak-learners, i.e. simple visual features. The obtained classifiers are useful for object detection tasks which exhibit multimodalities, e.g. multi-category and multi-view object detection tasks. Experiments on a set of pedestrian images and a face data set demonstrate that the method yields intuitive image clusters with associated features and is much superior to conventional boosting classifiers in object detection tasks.

Correlating Multiple 2D Vision Trackers for 3D Object Tracking on Construction Sites

Tracking methods have the potential to retrieve the spatial location of project related entities such as personnel and equipment at construction sites, which can facilitate several construction management tasks. Existing tracking methods are mainly based on Radio Frequency (RF) technologies and thus require manual deployment of tags. On construction sites with numerous entities, tags installation, maintenance and decommissioning become an issue since it increases the cost and time needed to implement these tracking methods. To address these limitations, this paper proposes an alternate 3D tracking method based on vision. It operates by tracking the designated object in 2D video frames and correlating the tracking results from multiple pre-calibrated views using epipolar geometry. The methodology presented in this paper has been implemented and tested on videos taken in controlled experimental conditions. Results are compared with the actual 3D positions to validate its performance.

Bayesian correlated clustering to integrate multiple datasets.

MOTIVATION: The integration of multiple datasets remains a key challenge in systems biology and genomic medicine. Modern high-throughput technologies generate a broad array of different data types, providing distinct-but often complementary-information. We present a Bayesian method for the unsupervised integrative modelling of multiple datasets, which we refer to as MDI (Multiple Dataset Integration). MDI can integrate information from a wide range of different datasets and data types simultaneously (including the ability to model time series data explicitly using Gaussian processes). Each dataset is modelled using a Dirichlet-multinomial allocation (DMA) mixture model, with dependencies between these models captured through parameters that describe the agreement among the datasets. RESULTS: Using a set of six artificially constructed time series datasets, we show that MDI is able to integrate a significant number of datasets simultaneously, and that it successfully captures the underlying structural similarity between the datasets. We also analyse a variety of real Saccharomyces cerevisiae datasets. In the two-dataset case, we show that MDI's performance is comparable with the present state-of-the-art. We then move beyond the capabilities of current approaches and integrate gene expression, chromatin immunoprecipitation-chip and protein-protein interaction data, to identify a set of protein complexes for which genes are co-regulated during the cell cycle. Comparisons to other unsupervised data integration techniques-as well as to non-integrative approaches-demonstrate that MDI is competitive, while also providing information that would be difficult or impossible to extract using other methods.