16,000 km, 10 Gbits-1 soliton transmission over standard fibre by reduction of interactions through optimum amplifier positioning

We show that by optimizing the amplifier position in a two-stage dispersion map, the (dispersion-managed) soliton-soliton interaction can be reduced, enabling transmission of 10-Gbits-1 solitons over standard fiber over 16,000 km

10Gbit/s dispersion managed soliton transmission over 16,500km in standard fibre by reduction of soliton interactions

We show experimentally and numerically that in high-speed strongly dispersion-managed standard fiber soliton systems nonlinear interactions limit the propagation distance. We present results that show that the effect of these interactions can be significantly reduced by appropriate location of the amplifier within the dispersion map. Using this technique, we have been able to extend the propagation distance of 10-Gbit/s 231–1pseudorandom binary sequence soliton data to 16, 500km over standard fiber by use of dispersion compensation. To our knowledge this distance is the farthest transmission over standard fiber without active control ever reported, and it was achieved with the amplifier placed after the dispersion-compensating fiber in a recirculating loop.

Autosoliton propagation at 80 Gbit/s using concatenated nonlinear loop switches in standard fibre

Experimental observation of autosoliton propagation in a nonlinear switch-guided, dispersion-managed system operating at 80 Gbit/s is reported for the first time. The system is based on a strong dispersion map and supports autosoliton propagation over 3000 km.

10Gbit/s dispersion managed soliton transmission over 16,500km in standard fibre by reduction of soliton interactions

We show experimentally and numerically that in high-speed strongly dispersion-managed standard fiber soliton systems nonlinear interactions limit the propagation distance. We present results that show that the effect of these interactions can be significantly reduced by appropriate location of the amplifier within the dispersion map. Using this technique, we have been able to extend the propagation distance of 10-Gbit/s 231–1pseudorandom binary sequence soliton data to 16, 500km over standard fiber by use of dispersion compensation. To our knowledge this distance is the farthest transmission over standard fiber without active control ever reported, and it was achieved with the amplifier placed after the dispersion-compensating fiber in a recirculating loop.

16,000 km, 10 Gbits-1 soliton transmission over standard fibre by reduction of interactions through optimum amplifier positioning

We show that by optimizing the amplifier position in a two-stage dispersion map, the (dispersion-managed) soliton-soliton interaction can be reduced, enabling transmission of 10-Gbits-1 solitons over standard fiber over 16,000 km

Autosoliton propagation at 80Gbit/s in standard fibre using in-line nonlinear loop switches

Experimental observation of autosoliton propagation in a nonlinear switch-guided, dispersion-managed system operating at 80Gbit/s is reported for the first time. The system is based on a strong dispersion map and supports autosoliton propagation over 3,000km.

Does the Swedish Interactive Threshold Algorithm (SITA) accurately map visual field loss attributed to vigabatrin?

Background: Vigabatrin (VGB) is an anti-epileptic medication which has been linked to peripheral constriction of the visual field. Documenting the natural history associated with continued VGB exposure is important when making decisions about the risk and benefits associated with the treatment. Due to its speed the Swedish Interactive Threshold Algorithm (SITA) has become the algorithm of choice when carrying out Full Threshold automated static perimetry. SITA uses prior distributions of normal and glaucomatous visual field behaviour to estimate threshold sensitivity. As the abnormal model is based on glaucomatous behaviour this algorithm has not been validated for VGB recipients. We aim to assess the clinical utility of the SITA algorithm for accurately mapping VGB attributed field loss. Methods: The sample comprised one randomly selected eye of 16 patients diagnosed with epilepsy, exposed to VGB therapy. A clinical diagnosis of VGB attributed visual field loss was documented in 44% of the group. The mean age was 39.3 years∈±∈14.5 years and the mean deviation was -4.76 dB ±4.34 dB. Each patient was examined with the Full Threshold, SITA Standard and SITA Fast algorithm. Results: SITA Standard was on average approximately twice as fast (7.6 minutes) and SITA Fast approximately 3 times as fast (4.7 minutes) as examinations completed using the Full Threshold algorithm (15.8 minutes). In the clinical environment, the visual field outcome with both SITA algorithms was equivalent to visual field examination using the Full Threshold algorithm in terms of visual inspection of the grey scale plots, defect area and defect severity. Conclusions: Our research shows that both SITA algorithms are able to accurately map visual field loss attributed to VGB. As patients diagnosed with epilepsy are often vulnerable to fatigue, the time saving offered by SITA Fast means that this algorithm has a significant advantage for use with VGB recipients.

A large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling

With the exponential increasing demands and uses of GIS data visualization system, such as urban planning, environment and climate change monitoring, weather simulation, hydrographic gauge and so forth, the geospatial vector and raster data visualization research, application and technology has become prevalent. However, we observe that current web GIS techniques are merely suitable for static vector and raster data where no dynamic overlaying layers. While it is desirable to enable visual explorations of large-scale dynamic vector and raster geospatial data in a web environment, improving the performance between backend datasets and the vector and raster applications remains a challenging technical issue. This dissertation is to implement these challenging and unimplemented areas: how to provide a large-scale dynamic vector and raster data visualization service with dynamic overlaying layers accessible from various client devices through a standard web browser, and how to make the large-scale dynamic vector and raster data visualization service as rapid as the static one. To accomplish these, a large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling and a comprehensive performance improvement solution are proposed, designed and implemented. They include: the quadtree-based indexing and parallel map tiling, the Legend String, the vector data visualization with dynamic layers overlaying, the vector data time series visualization, the algorithm of vector data rendering, the algorithm of raster data re-projection, the algorithm for elimination of superfluous level of detail, the algorithm for vector data gridding and re-grouping and the cluster servers side vector and raster data caching.

Habitat Map for Lizard Island reef, Australia derived from a photo-transect survey field data collected in December 2011 and September/October 2012

An object based image analysis approach (OBIA) was used to create a habitat map of the Lizard Reef. Briefly, georeferenced dive and snorkel photo-transect surveys were conducted at different locations surrounding Lizard Island, Australia. For the surveys, a snorkeler or diver swam over the bottom at a depth of 1-2m in the lagoon, One Tree Beach and Research Station areas, and 7m depth in Watson's Bay, while taking photos of the benthos at a set height using a standard digital camera and towing a surface float GPS which was logging its track every five seconds. The camera lens provided a 1.0 m x 1.0 m footprint, at 0.5 m height above the benthos. Horizontal distance between photos was estimated by fin kicks, and corresponded to a surface distance of approximately 2.0 - 4.0 m. Approximation of coordinates of each benthic photo was done based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software (www.geospatialexperts.com). Coordinates of each photo were interpolated by finding the gps coordinates that were logged at a set time before and after the photo was captured. Dominant benthic or substrate cover type was assigned to each photo by placing 24 points random over each image using the Coral Point Count excel program (Kohler and Gill, 2006). Each point was then assigned a dominant cover type using a benthic cover type classification scheme containing nine first-level categories - seagrass high (>=70%), seagrass moderate (40-70%), seagrass low (<= 30%), coral, reef matrix, algae, rubble, rock and sand. Benthic cover composition summaries of each photo were generated automatically in CPCe. The resulting benthic cover data for each photo was linked to GPS coordinates, saved as an ArcMap point shapefile, and projected to Universal Transverse Mercator WGS84 Zone 56 South. The OBIA class assignment followed a hierarchical assignment based on membership rules with levels for "reef", "geomorphic zone" and "benthic community" (above).

Hydrologic unit map--1974, State of New Jersey.

Scale 1:500,000; 1 in. equals approx. 8 miles.

Simple approximate MAP inference for Dirichlet processes mixtures

The Dirichlet process mixture model (DPMM) is a ubiquitous, flexible Bayesian nonparametric statistical model. However, full probabilistic inference in this model is analytically intractable, so that computationally intensive techniques such as Gibbs sampling are required. As a result, DPMM-based methods, which have considerable potential, are restricted to applications in which computational resources and time for inference is plentiful. For example, they would not be practical for digital signal processing on embedded hardware, where computational resources are at a serious premium. Here, we develop a simplified yet statistically rigorous approximate maximum a-posteriori (MAP) inference algorithm for DPMMs. This algorithm is as simple as DP-means clustering, solves the MAP problem as well as Gibbs sampling, while requiring only a fraction of the computational effort. (For freely available code that implements the MAP-DP algorithm for Gaussian mixtures see http://www.maxlittle.net/.) Unlike related small variance asymptotics (SVA), our method is non-degenerate and so inherits the “rich get richer” property of the Dirichlet process. It also retains a non-degenerate closed-form likelihood which enables out-of-sample calculations and the use of standard tools such as cross-validation. We illustrate the benefits of our algorithm on a range of examples and contrast it to variational, SVA and sampling approaches from both a computational complexity perspective as well as in terms of clustering performance. We demonstrate the wide applicabiity of our approach by presenting an approximate MAP inference method for the infinite hidden Markov model whose performance contrasts favorably with a recently proposed hybrid SVA approach. Similarly, we show how our algorithm can applied to a semiparametric mixed-effects regression model where the random effects distribution is modelled using an infinite mixture model, as used in longitudinal progression modelling in population health science. Finally, we propose directions for future research on approximate MAP inference in Bayesian nonparametrics.