Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering

Semi-supervised clustering is the task of clustering data points into clusters where only a fraction of the points are labelled. The true number of clusters in the data is often unknown and most models require this parameter as an input. Dirichlet process mixture models are appealing as they can infer the number of clusters from the data. However, these models do not deal with high dimensional data well and can encounter difficulties in inference. We present a novel nonparameteric Bayesian kernel based method to cluster data points without the need to prespecify the number of clusters or to model complicated densities from which data points are assumed to be generated from. The key insight is to use determinants of submatrices of a kernel matrix as a measure of how close together a set of points are. We explore some theoretical properties of the model and derive a natural Gibbs based algorithm with MCMC hyperparameter learning. The model is implemented on a variety of synthetic and real world data sets.

Identification of the steering control behaviour of five test subjects following a randomly curving path in a driving simulator

The paper is concerned with the identification of theoretical preview steering controllers using data obtained from five test subjects in a fixed-base driving simulator. An understanding of human steering control behaviour is relevant to the design of autonomous and semi-autonomous vehicle controls. The driving task involved steering a linear vehicle along a randomly curving path. The theoretical steering controllers identified from the data were based on optimal linear preview control. A direct-identification method was used, and the steering controllers were identified so that the predicted steering angle matched as closely as possible the measured steering angle of the test subjects. It was found that identification of the driver's time delay and noise is necessary to avoid bias in identification of the controller parameters. Most subjects' steering behaviour was predicted well by a theoretical controller based on the lateral/yaw dynamics of the vehicle. There was some evidence that an inexperienced driver's steering action was better represented by a controller based on a simpler model of the vehicle dynamics, perhaps reflecting incomplete learning by the driver. Copyright © 2014 Inderscience Enterprises Ltd.

Determination of the rheological parameters of self-compacting concrete matrix using slump flow test

The classification of a concrete mixture as self-compacting (SCC) is performed by a series of empirical characterization tests that have been designed to assess not only the flowability of the mixture but also its segregation resistance and filling ability. The objective of the present work is to correlate the rheological parameters of SCC matrix, yield stress and plastic viscosity, to slump flow measurements. The focus of the slump flow test investigation was centered on the fully yielded flow regime and an empirical model relating the yield stress to material and flow parameters is proposed. Our experimental data revealed that the time for a spread of 500 mm which is used in engineering practice as reference for measurement parameters, is an arbitrary choice. Our findings indicate that the non-dimensional final spread is linearly related to the non-dimensional yield-stress. Finally, there are strong indications that the non-dimensional viscosity of the mixture is associated with the non-dimensional final spread as well as the stopping time of the slump flow; this experimental data set suggests an exponential decay of the final spread and stopping time with viscosity. © Appl. Rheol.

Bayesian parameter identification for vibro-acoustic models with nonparametric uncertainty

Vibration and acoustic analysis at higher frequencies faces two challenges: computing the response without using an excessive number of degrees of freedom, and quantifying its uncertainty due to small spatial variations in geometry, material properties and boundary conditions. Efficient models make use of the observation that when the response of a decoupled vibro-acoustic subsystem is sufficiently sensitive to uncertainty in such spatial variations, the local statistics of its natural frequencies and mode shapes saturate to universal probability distributions. This holds irrespective of the causes that underly these spatial variations and thus leads to a nonparametric description of uncertainty. This work deals with the identification of uncertain parameters in such models by using experimental data. One of the difficulties is that both experimental errors and modeling errors, due to the nonparametric uncertainty that is inherent to the model type, are present. This is tackled by employing a Bayesian inference strategy. The prior probability distribution of the uncertain parameters is constructed using the maximum entropy principle. The likelihood function that is subsequently computed takes the experimental information, the experimental errors and the modeling errors into account. The posterior probability distribution, which is computed with the Markov Chain Monte Carlo method, provides a full uncertainty quantification of the identified parameters, and indicates how well their uncertainty is reduced, with respect to the prior information, by the experimental data. © 2013 Taylor & Francis Group, London.

Chronic effects of water-borne PFOS exposure on growth, survival and hepatotoxicity in zebrafish: A partial life-cycle test

Perfluorooctane sulfonate (PFOS) is widely distributed and persistent in the environment and wildlife. The main aim of this study was to investigate the impact of long-term exposure to low concentrations of PFOS in zebrafish. Zebrafish fry (F-0, 14d post-fertilization, dpf) were exposed via the water for 70d to 0 (control), 10, 50 and 250 mu g L-1 PFOS, followed by a further 30d to assess recovery in clean water. The effects on survival and growth parameters and liver histopathology were assessed. Although growth suppression (weight and length) was observed in fish treated with high concentrations PFOS during the exposure period, no mortality was observed throughout the 70d experiment. Embryos and larvae (F-1) derived from maternal exposure suffered malformation and mortality. Exposure to 50 and 250 mu g L-1 PFOS could inhibit the growth of the gonads (GSI) in the female zebrafish. Histopathological alterations, primary with lipid droplets accumulation, were most prominently seen in the liver of males and the changes were not reversible, even after the fish were allowed to recover for 30d in clean water. The triiodothyronine (T-3)) levels were not significantly changed in any of the exposure groups. Hepatic vitellogenin (VTG) gene expression was significantly up-regulated in both male and female zebrafish, but the sex ratio was not altered. The overall results suggested that lower concentrations of PFOS in maternal exposure could result in offspring deformation and mortality. (c) 2008 Elsevier Ltd. All rights reserved.

Automatic construction and natural-language description of nonparametric regression models

Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper presents the beginnings of an automatic statistician, focusing on regression problems. Our system explores an open-ended space of statistical models to discover a good explanation of a data set, and then produces a detailed report with figures and natural- language text. Our approach treats unknown regression functions non- parametrically using Gaussian processes, which has two important consequences. First, Gaussian processes can model functions in terms of high-level properties (e.g. smoothness, trends, periodicity, changepoints). Taken together with the compositional structure of our language of models this allows us to automatically describe functions in simple terms. Second, the use of flexible nonparametric models and a rich language for composing them in an open-ended manner also results in state- of-the-art extrapolation performance evaluated over 13 real time series data sets from various domains.

Trial Test of a Bulk-Type Fully HTS Synchronous Motor

© 2013 IEEE. The world's first bulk-type fully high temperature superconducting synchronous motor (HTS-SM) was assembled and tested in our laboratory at the University of Cambridge. The fully HTS-SM was designed with 75 Y123 HTS bulks mounted on the surface of the rotor and six air core 2G HTS racetrack coils used for stator windings. We successfully applied a light fan load test for this fully HTS-SM at its operating temperature of 77 K. The detected decay of the trapped magnetic flux densities at the centre of the HTS bulks was up to 16.5% after 5 h of synchronous rotation. Due to the high current density of the HTS material, the ac stator field for the 2G HTS winding was 49.2% stronger compared with a comparable copper winding. In the meantime, we estimated that the efficiency was about 86% potentially under stable low frequency rotation at 150 r/min. The results show that the performance of this HTS motor is acceptable for practical applications.

Biogeography and molecular phylogeny of the genus Schizothorax (Teleostei : Cyprinidae) in China inferred from cytochrome b sequences

Aim: To test a vicariant speciation hypothesis derived from geological evidence of large-scale changes in drainage patterns in the late Miocene that affected the drainages in the south-eastern Tibetan Plateau. Location: The Tibetan Plateau and adjacent areas. Methods: The cytochrome b DNA sequences of 30 species of the genus Schizothorax from nine different river systems were analysed. These DNA sequences were analysed using parsimony, maximum likelihood and Bayesian methods. The approximately unbiased and Shimodaira-Hasegawa tests were applied to evaluate the statistical significance of the shortest trees relative to alternative hypotheses. Dates of divergences between lineages were estimated using the nonparametric rate smoothing method, and confidence intervals of dates were obtained by parametric bootstrapping. Results: The phylogenetic relationships recovered from molecular data were inconsistent with traditional taxonomy, but apparently reflected geographical associations with rivers. Within the genus Schizothorax, we observed a divergence between the lineages from the Irrawaddy-Lhuit and Tsangpo-Parlung rivers, and tentatively dated this vicariant event back to the late Miocene (7.3-6.8 Ma). We also observed approximately simultaneous geographical splits within drainages of the south-eastern Tibetan Plateau, the Irrawaddy, the Yangtze and the Mekong-Salween rivers in the late Miocene (7.1-6.2 Ma). Main conclusions: Our molecular evidence tentatively highlights the importance of palaeoriver connections and the uplift of the Tibetan Plateau in understanding the evolution of the genus Schizothorax. Molecular estimates of divergence times allowed us to date these vicariant scenarios back to the late Miocene, which agrees with geological suggestions for the separation of these drainages caused by tectonic uplift in south-eastern Tibet. Our results indicated the substantial role of vicariant-based speciation in shaping the current distribution pattern of the genus Schizothorax.

A preliminary study on methods for retaining data quality problems in automatically generated test data

Data in an organisation often contains business secrets that organisations do not want to release. However, there are occasions when it is necessary for an organisation to release its data such as when outsourcing work or using the cloud for Data Quality (DQ) related tasks like data cleansing. Currently, there is no mechanism that allows organisations to release their data for DQ tasks while ensuring that it is suitably protected from releasing business related secrets. The aim of this paper is therefore to present our current progress on determining which methods are able to modify secret data and retain DQ problems. So far we have identified the ways in which data swapping and the SHA-2 hash function alterations methods can be used to preserve missing data, incorrectly formatted values, and domain violations DQ problems while minimising the risk of disclosing secrets. © (2012) by the AIS/ICIS Administrative Office All rights reserved.

Classification using log Gaussian Cox processes

McCullagh and Yang (2006) suggest a family of classification algorithms based on Cox processes. We further investigate the log Gaussian variant which has a number of appealing properties. Conditioned on the covariates, the distribution over labels is given by a type of conditional Markov random field. In the supervised case, computation of the predictive probability of a single test point scales linearly with the number of training points and the multiclass generalization is straightforward. We show new links between the supervised method and classical nonparametric methods. We give a detailed analysis of the pairwise graph representable Markov random field, which we use to extend the model to semi-supervised learning problems, and propose an inference method based on graph min-cuts. We give the first experimental analysis on supervised and semi-supervised datasets and show good empirical performance.

The Chinese rare minnow (Gobiocypris rarus) as an in vivo model for endocrine disruption in freshwater teleosts: a full life-cycle test with diethylstilbestrol

Chinese rare minnow (Gobiocypris rarus), a freshwater teleost,. was exposed to diethylstilbestrol (DES) at 0.05, 0.5, 1 and 5 mug/L from fertilized eggs for up to mature period under flow-through condition. Several endpoints that related to development, reproductive fitness and transgenerational effects were evaluated. It was found that body length and body weight were significantly reduced and vitellogenin (Via) levels were significantly increased for fish exposed to DES. Histological examination showed that the sex ratios of F-0 fish skewed to female and about 2% of the fish exposed to 0.05 mug/L DES developed testes-ova. The reproductive success, as determined from data on egg production, was reduced in female fish exposed to 0.05, 0.5, 1 and 5 mug/L DES. The lowest-observed-effect concentrations (LOEC) for chances of sex ratios, reproductive success and histology alteration of F-0 are 0.05 mug/L. In the offspring, transgenerational effects on egg hatching rate. egg fertilization and Vtg levels of juvenile individuals were not observed. However. survival of F, generation fry significantly declined. The analysis of sex steroid levels revealed a significant decrease of testosterone (T) in the whole body homogenates (WBH) of male progeny and somewhat elevation of estradiol (E-T) in the WBH of female offspring. These findings indicate that exposure to DES causes a variety of developmental, reproductive and transgenerational effects. (C) 2004 Elsevier B.V. All rights reserved.