Occlusive Components Analysis

We study unsupervised learning in a probabilistic generative model for occlusion. The model uses two types of latent variables: one indicates which objects are present in the image, and the other how they are ordered in depth. This depth order then determines how the positions and appearances of the objects present, specified in the model parameters, combine to form the image. We show that the object parameters can be learnt from an unlabelled set of images in which objects occlude one another. Exact maximum-likelihood learning is intractable. However, we show that tractable approximations to Expectation Maximization (EM) can be found if the training images each contain only a small number of objects on average. In numerical experiments it is shown that these approximations recover the correct set of object parameters. Experiments on a novel version of the bars test using colored bars, and experiments on more realistic data, show that the algorithm performs well in extracting the generating causes. Experiments based on the standard bars benchmark test for object learning show that the algorithm performs well in comparison to other recent component extraction approaches. The model and the learning algorithm thus connect research on occlusion with the research field of multiple-causes component extraction methods.

Calibrating the Gaussian multi-target tracking model

We present novel batch and online (sequential) versions of the expectation-maximisation (EM) algorithm for inferring the static parameters of a multiple target tracking (MTT) model. Online EM is of particular interest as it is a more practical method for long data sets since in batch EM, or a full Bayesian approach, a complete browse of the data is required between successive parameter updates. Online EM is also suited to MTT applications that demand real-time processing of the data. Performance is assessed in numerical examples using simulated data for various scenarios. For batch estimation our method significantly outperforms an existing gradient based maximum likelihood technique, which we show to be significantly biased. © 2014 Springer Science+Business Media New York.

The complete mitochondrial genome of the ridgetail white prawn Exopalaemon carinicauda Holthuis, 1950 (Crustacean: Decapoda: Palaemonidae) revealed a novel rearrangement of tRNA genes

The complete mitochondrial (mt) DNA sequence was determined for a ridgetail white prawn, Exopalaemon carinicauda Holthuis, 1950 (Crustacea: Decopoda: Palaemonidae). The mt genome is 15,730 bp in length, encoding a standard set of 13 protein-coding genes, 2 ribosomal RNA genes, and 22 transfer RNA genes, which is typical for metazoans. The majority-strand consists of 33.6% A, 23.0% C, 13.4% G, and 30.0% T bases (AT skew = 0.057: GC skew = -0.264). A total of 1045 bp of non-coding nucleotides were observed in 16 intergenic regions,,including a major A+ T rich (79.7%) noncoding region (886 bp). A novel translocation of tRNA(Pro) and tRNA(Thr) was found when comparing this genome with the pancrustacean ground pattern indicating that gene order is not conserved among caridean mitochondria. Furthermore, the rate of Ka/Ks in 13 protein-coding genes between three caridean species is Much less than 1, which indicates a strong Purifying selection within this group. To investigate the phylogenetic relationship within Malacostraca, phylogenetic trees based oil Currently available malacostracan complete mitochondrial sequences were built with the maximum likelihood and Bayesian models. All analyses based oil nucleotide and amino acid data strongly support the monophyly of Decapoda. The Penaeidae, Reptantia, Caridea, and Meiura clades were also recovered as monophyletic groups with Strong Statistical Support. However, the phylogenetic relationships within Pleocyemata are unstable, as represented by the inclusion or exclusion of Caridea. (C) 2009 Elsevier B.V. All rights reserved.

Cellular automata: Simulating alpine tundra vegetation dynamics in response to global warming

This study attempts to model alpine tundra vegetation dynamics in a tundra region in the Qinghai Province of China in response to global warming. We used Raster-based cellular automata and a Geographic Information System to study the spatial and temporal vegetation dynamics. The cellular automata model is implemented with IDRISI's Multi-Criteria Evaluation functionality to simulate the spatial patterns of vegetation change assuming certain scenarios of global mean temperature increase over time. The Vegetation Dynamic Simulation Model calculates a probability surface for each vegetation type, and then combines all vegetation types into a composite map, determined by the maximum likelihood that each vegetation type should distribute to each raster unit. With scenarios of global temperature increase of I to 3 degrees C, the vegetation types such as Dry Kobresia Meadow and Dry Potentilla Shrub that are adapted to warm and dry conditions tend to become more dominant in the study area.

Convergence Results for the EM Approach to Mixtures of Experts Architectures

The Expectation-Maximization (EM) algorithm is an iterative approach to maximum likelihood parameter estimation. Jordan and Jacobs (1993) recently proposed an EM algorithm for the mixture of experts architecture of Jacobs, Jordan, Nowlan and Hinton (1991) and the hierarchical mixture of experts architecture of Jordan and Jacobs (1992). They showed empirically that the EM algorithm for these architectures yields significantly faster convergence than gradient ascent. In the current paper we provide a theoretical analysis of this algorithm. We show that the algorithm can be regarded as a variable metric algorithm with its searching direction having a positive projection on the gradient of the log likelihood. We also analyze the convergence of the algorithm and provide an explicit expression for the convergence rate. In addition, we describe an acceleration technique that yields a significant speedup in simulation experiments.

Virtual Visual Hulls: Example-Based 3D Shape Estimation from a Single Silhouette

Recovering a volumetric model of a person, car, or other object of interest from a single snapshot would be useful for many computer graphics applications. 3D model estimation in general is hard, and currently requires active sensors, multiple views, or integration over time. For a known object class, however, 3D shape can be successfully inferred from a single snapshot. We present a method for generating a ``virtual visual hull''-- an estimate of the 3D shape of an object from a known class, given a single silhouette observed from an unknown viewpoint. For a given class, a large database of multi-view silhouette examples from calibrated, though possibly varied, camera rigs are collected. To infer a novel single view input silhouette's virtual visual hull, we search for 3D shapes in the database which are most consistent with the observed contour. The input is matched to component single views of the multi-view training examples. A set of viewpoint-aligned virtual views are generated from the visual hulls corresponding to these examples. The 3D shape estimate for the input is then found by interpolating between the contours of these aligned views. When the underlying shape is ambiguous given a single view silhouette, we produce multiple visual hull hypotheses; if a sequence of input images is available, a dynamic programming approach is applied to find the maximum likelihood path through the feasible hypotheses over time. We show results of our algorithm on real and synthetic images of people.

Optymalizacja metod analizy Főrsterowskiego rezonansowego przeniesienia energii (FRET) pojedynczych cząsteczek

Wydział Chemii: Zakład Chemii Fizycznej

Newly resolved relationships in an early land plant lineage: Bryophyta class Sphagnopsida (peat mosses).

UNLABELLED: PREMISE OF THE STUDY: The Sphagnopsida, an early-diverging lineage of mosses (phylum Bryophyta), are morphologically and ecologically unique and have profound impacts on global climate. The Sphagnopsida are currently classified in two genera, Sphagnum (peat mosses) with some 350-500 species and Ambuchanania with one species. An analysis of phylogenetic relationships among species and genera in the Sphagnopsida were conducted to resolve major lineages and relationships among species within the Sphagnopsida. • METHODS: Phylogenetic analyses of nucleotide sequences from the nuclear, plastid, and mitochondrial genomes (11 704 nucleotides total) were conducted and analyzed using maximum likelihood and Bayesian inference employing seven different substitution models of varying complexity. • KEY RESULTS: Phylogenetic analyses resolved three lineages within the Sphagnopsida: (1) Sphagnum sericeum, (2) S. inretortum plus Ambuchanania leucobryoides, and (3) all remaining species of Sphagnum. Sister group relationships among these three clades could not be resolved, but the phylogenetic results indicate that the highly divergent morphology of A. leucobryoides is derived within the Sphagnopsida rather than plesiomorphic. A new classification is proposed for class Sphagnopsida, with one order (Sphagnales), three families, and four genera. • CONCLUSIONS: The Sphagnopsida are an old lineage within the phylum Bryophyta, but the extant species of Sphagnum represent a relatively recent radiation. It is likely that additional species critical to understanding the evolution of peat mosses await discovery, especially in the southern hemisphere.

Bivariate distribution modeling with tree diameter and height data

The Logit-Logistic (LL), Johnson's SB, and the Beta (GBD) are flexible four-parameter probability distribution models in terms of the (skewness-kurtosis) region covered, and each has been used for modeling tree diameter distributions in forest stands. This article compares bivariate forms of these models in terms of their adequacy in representing empirical diameter-height distributions from 102 sample plots. Four bivariate models are compared: SBB, the natural, well-known, and much-used bivariate generalization of SB; the bivariate distributions with LL, SB, and Beta as marginals, constructed using Plackett's method (LL-2P, etc.). All models are fitted using maximum likelihood, and their goodness-of-fits are compared using minus log-likelihood (equivalent to Akaike's Information Criterion, the AIC). The performance ranking in this case study was SBB, LL-2P, GBD-2P, and SB-2P

The Richit-Richards family of distributions and its use in forestry

Johnson's SB and the logit-logistic are four-parameter distribution models that may be obtained from the standard normal and logistic distributions by a four-parameter transformation. For relatively small data sets, such as diameter at breast height measurements obtained from typical sample plots, distribution models with four or less parameters have been found to be empirically adequate. However, in situations in which the distributions are complex, for example in mixed stands or when the stand has been thinned or when working with aggregated data, then distribution models with more shape parameters may prove to be necessary. By replacing the symmetric standard logistic distribution of the logit-logistic with a one-parameter “standard Richards” distribution and transforming by a five-parameter Richards function, we obtain a new six-parameter distribution model, the “Richit-Richards”. The Richit-Richards includes the “logit-Richards”, the “Richit-logistic”, and the logit-logistic as submodels. Maximum likelihood estimation is used to fit the model, and some problems in the maximum likelihood estimation of bounding parameters are discussed. An empirical case study of the Richit-Richards and its submodels is conducted on pooled diameter at breast height data from 107 sample plots of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.). It is found that the new models provide significantly better fits than the four-parameter logit-logistic for large data sets.

Triply differential single ionization cross sections in coplanar and non-coplanar geometry for fast heavy ion-atom collisions

We have performed a kinematically complete experiment and calculations on single ionization in 100 MeV/amu C6+ + He collisions. For electrons ejected into the scattering plane (defined by the initial and final projectile momentum vectors) our first- and higher-order calculations are in good agreement with the data. In the plane perpendicular to the scattering plane and containing the initial projectile axis a strong forward-backward asymmetry is observed. In this plane both the first-order and the higher-order calculations do not provide good agreement neither with the data nor amongst each other.

Object tracking using SIFT features and mean shift

A scale invariant feature transform (SIFT) based mean shift algorithm is presented for object tracking in real scenarios. SIFT features are used to correspond the region of interests across frames. Meanwhile, mean shift is applied to conduct similarity search via color histograms. The probability distributions from these two measurements are evaluated in an expectation–maximization scheme so as to achieve maximum likelihood estimation of similar regions. This mutual support mechanism can lead to consistent tracking performance if one of the two measurements becomes unstable. Experimental work demonstrates that the proposed mean shift/SIFT strategy improves the tracking performance of the classical mean shift and SIFT tracking algorithms in complicated real scenarios.

Measurements, modeling and simulation of the off-body radio channel for the implementation of bodyworn antenna diversity at 868 MHz

This paper presents a systematic measurement campaign of diversity reception techniques for use in multiple-antenna wearable systems operating at 868 MHz. The experiments were performed using six time-synchronized bodyworn receivers and considered mobile off-body communications in an anechoic chamber, open office area and a hallway. The cross-correlation coefficient between the signal fading measured by bodyworn receivers was dependent upon the local environment and typically below 0.7. All received signal envelopes were combined in post-processing to study the potential benefits of implementing receiver diversity based upon selection combination, equal-gain and maximal-ratio combining. It is shown that, in an open office area, the 5.7 dB diversity gain obtained using a dual-branch bodyworn maximal-ratio diversity system may be further improved to 11.1 dB if a six-branch system was used. First-and second-order theoretical equations for diversity reception techniques operating in Nakagami fading conditions were used to model the postdetection combined envelopes. Maximum likelihood estimates of the Nakagami-parameter suggest that the fading conditions encountered in this study were generally less severe than Rayleigh. The paper also describes an algorithm that may be used to simulate the measured output of an M-branch diversity combiner operating in independent and identically-distributed Nakagami fading environments.

An experimental investigation into the influence of user state and environment on fading characteristics in wireless body area networks at 2.45 GHz

Using seven strategically placed, time-synchronized bodyworn receivers covering the head, upper front and back torso, and the limbs, we have investigated the effect of user state: stationary or mobile and local environment: anechoic chamber, open office area and hallway upon first and second order statistics for on-body fading channels. Three candidate models were considered: Nakagami, Rice and lognormal. Using maximum likelihood estimation and the Akaike information criterion it was established that the Nakagami-m distribution best described small-scale fading for the majority of on-body channels over all the measurement scenarios. When the user was stationary, Nakagami-m parameters were found to be much greater than 1, irrespective of local surroundings. For mobile channels, Nakagami-m parameters significantly decreased, with channels in the open office area and hallway experiencing the worst fading conditions.

Organizational culture predicts job satisfaction and perceived clinical effectiveness in pediatric primary care practices

Background: In recent years, there has been a growing understanding that organizational culture is related to an organization's performance. However, fewstudies have examined organizational culture in medical group practices. Objectives: The purpose of this study was to examine the relationship of organizational culture on provider job satisfaction and perceived clinical effectiveness in primary care pediatric practices. Research Design: This cross-sectional study included 36 primary care pediatric practices located in Connecticut. Participants: There were 374 participants in this study, which included 127 clinicians and 247 nonclinicians. Measures: Office managers completed a questionnaire that recorded staff and practice characteristics; all participants completed the Organizational Culture Scale, a questionnaire that assessed the practice on four cultural domains (i.e., group, developmental, rational, and hierarchical), and the Primary Care Organizational Questionnaire that evaluated perceived effectiveness and job satisfaction. Results: Hierarchical linear models using a restricted maximum likelihood estimation method were used to evaluate whether the practice culture types predicted job satisfaction and perceived effectiveness. Group culture was positively associated with both satisfaction and perceived effectiveness. In contrast, hierarchical and rational culture were negatively associated with both job satisfaction and perceived effectiveness. These relationships were true for clinicians, nonclinicians, and the practice as a whole. Conclusions: Our study demonstrates that practice culture is associated with job satisfaction and perceived clinical effectiveness and that a group culture was associated with high job satisfaction and perceived effectiveness. Copyright © 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins.