Exploiting geometry for improved hybrid AOA/TDOA-based localization

In this paper we examine the geometrically constrained optimization approach to localization with hybrid bearing (angle of arrival, AOA) and time difference of  arrival (TDOA) sensors. In particular, we formulate a constraint on the measurement errors which is then used along with constraint-based optimization tools in order to estimate the maximum likelihood values of the errors given an appropriate cost function. In particular we focus on deriving a localization algorithm for stationary target localization in the so-called adverse localization geometries where the relative positioning of the sensors and the target do not readily permit accurate or convergent localization using traditional approaches. We illustrate this point via simulation and we compare our approach to a number of different techniques that are discussed in the literature.

Optimal range-difference-based localization considering geometrical constraints

This paper proposes a new type of algorithm aimed at finding the traditional maximum-likelihood (TML) estimate of the position of a target given time-difference-of-arrival (TDOA) information, contaminated by noise. The novelty lies in the fact that a performance index, akin to but not identical with that in maximum likelihood (ML), is a minimized subject to a number of constraints, which flow from geometric constraints inherent in the underlying problem. The minimization is in a higher dimensional space than for TML, and has the advantage that the algorithm can be very straightforwardly and systematically initialized. Simulation evidence shows that failure to converge to a solution of the localization problem near the true value is less likely to occur with this new algorithm than with TML. This makes it attractive to use in adverse geometric situations.

Phylogenetic relationships among nine scallop species (Bivalvia : Pectinidae) inferred from nucleotide sequences of one mitochondrial and three nuclear gene regions

Current knowledge of the evolutionary relationships among scallop species (Mollusca: Bivalvia: Pectinidae) in the Indo-Pacific region is rather scanty. To enhance the understanding of the relationships within this group, phylogenies of nine species of scallops with the majority from coastal regions of Thailand, were reconstructed by maximum parsimony, maximum likelihood, and Bayesian methods using sequences of the 16S rRNA of the mitochondrial genome, and a fragment containing the ITS1, 5.8S and ITS2 genes of the nuclear DNA. The trees that resulted from the three methods of analysis were topologically identical, however, gained different levels of support at some nodes. Nine species were clustered into two major clades, corresponding to two subfamilies (Pectininae and Chlamydinae) of the three currently recognized subfamilies within Pectinidae. Overall, the relationships reported herein are mostly in accordance with the previous molecular studies that used sequences of the mtDNA cytochrome oxidase subunit I, and the classification system based on microsculpture of shell features and morphological characteristics of juveniles. Levels of divergences were different among genes (i.e., the 5.8S gene showed the lowest levels of nucleotide divergence at all levels, whereas the 16S rRNA showed the highest level of variation within species, and ITS2 gene revealed the highest level of divergence at higher levels).

Selection of working correlation structure and best model in GEE analyses of longitudinal data

The Generalized Estimating Equations (GEE) method is one of the most commonly used statistical methods for the analysis of longitudinal data in epidemiological studies. A working correlation structure for the repeated measures of the outcome variable of a subject needs to be specified by this method. However, statistical criteria for selecting the best correlation structure and the best subset of explanatory variables in GEE are only available recently because the GEE method is developed on the basis of quasi-likelihood theory. Maximum likelihood based model selection methods, such as the widely used Akaike Information Criterion (AIC), are not applicable to GEE directly. Pan (2001) proposed a selection method called QIC which can be used to select the best correlation structure and the best subset of explanatory variables. Based on the QIC method, we developed a computing program to calculate the QIC value for a range of different distributions, link functions and correlation structures. This program was written in Stata software. In this article, we introduce this program and demonstrate how to use it to select the most parsimonious model in GEE analyses of longitudinal data through several representative examples.

Regressive logistic and proportional hazards disease models for within-family analyses of measured genotypes, with application to a CYP17 polymorphism and breast cancer

Various statistical methods have been proposed to evaluate associations between measured genetic variants and disease, including some using family designs. For breast cancer and rare variants, we applied a modified segregation analysis method that uses the population cancer incidence and population-based case families in which a mutation is known to be segregating. Here we extend the method to a common polymorphism, and use a regressive logistic approach to model familial aggregation by conditioning each individual on their mother's breast cancer history. We considered three models: 1) class A regressive logistic model; 2) age-of-onset regressive logistic model; and 3) proportional hazards familial model. Maximum likelihood estimates were calculated using the software MENDEL. We applied these methods to data from the Australian Breast Cancer Family Study on the CYP17 5UTR TC MspA1 polymorphism measured for 1,447 case probands, 787 controls, and 213 relatives of case probands found to have the CC genotype. Breast cancer data for first- and second-degree relatives of case probands were used. The three methods gave consistent estimates. The best-fitting model involved a recessive inheritance, with homozygotes being at an increased risk of 47% (95% CI, 28-68%). The cumulative risk of the disease up to age 70 years was estimated to be 10% or 22% for a CYP17 homozygote whose mother was unaffected or affected, respectively. This analytical approach is well-suited to the data that arise from population-based case-control-family studies, in which cases, controls and relatives are studied, and genotype is measured for some but not all subjects.

Variation of fibre diameter coefficient of variation and fibre curvature across mohair fleeces: Implications for animal selection, genetic selection and fleece evaluation

The presentwork aimed to determine howthe average fibre diameter coefficient of variation (CVD) and fibre curvature (FC) differences between nine sampling sites vary between sex and flock, to identify differences in variability between sampling sites as a result of between animal and between sire variability and to determine correlations between sampling sites in between animal and between sire variability. Australian Angoras (n = 313) from two farms in southern Australia were sampled at 12 and 18 months of age at nine sites (mid side, belly, brisket, hind flank, hip, hock, mid back, neck, shoulder). Staples were taken prior to shearing at skin level and CVD and FC determined. For each shearing, differences in CVD and FC between sampling sites, how these differences were affected by farm, sex, and sire, and the covariance between sites for sire and individual animal effects were investigated by restricted maximum likelihood (REML) analyses. The median mid side CVD at 12 and 18 months of age ranged from 23.6 to 25.1% but the actual range was 16.8–34.2%. The median mid side FC at 12 and 18 months of age ranged from 14.4 to 18.6◦/mm but the actual range was 10.5–26.3◦/mm. The general pattern for CVDwas for the mid back, hip and neck sites to have similar CVD, the brisket, hind flank and hock sites to have larger CVD and the belly to have smaller CVD than the mid side site. The between animal variation for CVD was lowest at the mid back site. This implies that the mid back would be the most effective site for between animal selection for CVD. Heritabilities for CVD (range at 18 months 0.18–0.30) were only about half the heritabilities for mean fibre diameter in the same study. There was a marked anterior–posterior increase in FC at both farms and with both ages. The results give no clear indication of the best site for between animal selection for FC, other than that the hock should be avoided. Heritabilities for FC are moderate to high (range at 18 months 0.44–0.77) and the genetic correlations are high except for the hock. Thus genetic selection for FC at any site, other than the hock, should be effective for changing FC over the entire fleece. There was more variability between animals than between sites and sires. These results are put into context with associated research on variation in mean fibre diameter and staple length.

Variation of mohair staple length across Angora goat fleeces : implications for animal selection and fleece evaluation

The present study aimed to determine how the average mohair staple length (SL) differences between nine sampling sites vary between sex and flock, to identify differences in SL variability between sampling sites as a result of between-animal and between-sire variability and to determine SL correlations between sampling sites in between-animal and between-sire variability. Australian Angora goats (n=301) from two farms in southern Australia were sampled at 12 and 18 months of age at nine sites (mid side, belly, brisket, hind flank, hip, hock, mid back, neck and shoulder). Staples were taken prior to shearing at skin level and stretched SL determined. For each shearing, differences in SL between sampling sites, how these differences were affected by farm, sex and sire, and the covariance between sites for sire and individual animal effects were investigated by restricted maximum likelihood (REML) analyses. The median mid-side SL at 12 and 18 months of age was 110 and 130 mm, respectively, but the actual range in mid-side SL was 65–165 mm. There was an anterior–posterior decline in SL with the hock being particularly short. There was no evidence that the between-site correlation of the sire effects differed from 1, indicating that genetic selection for SL at one site will be reflected in SL over the whole fleece. However, low heritabilities of SL at the hock, belly and brisket or at any site at 12 months of age were obtained. There was more variability between sites than between sires, but the between-animal variation was greater. The hip and mid-back sites can be recommended for within-flock (culling) and genetic selection for SL due to their low sampling variability, moderate heritability and ease of location.

Aggregation functions based on penalties

This article studies a large class of averaging aggregation functions based on minimizing a distance from the vector of inputs, or equivalently, minimizing a penalty imposed for deviations of individual inputs from the aggregated value. We provide a systematization of various types of penalty based aggregation functions, and show how many special cases arise as the result. We show how new aggregation functions can be constructed either analytically or numerically and provide many examples. We establish connection with the maximum likelihood principle, and present tools for averaging experimental noisy data with distinct noise distributions.

OWA operators in linear regression and detection of outliers

We consider the use of Ordered Weighted Averaging (OWA) in linear regression. Our goal is to replace the traditional least squares, least absolute deviation, and maximum likelihood criteria with an OWA function of the residuals. We obtain several high breakdown robust regression methods as special cases (least median, least trimmed squares, trimmed likelihood methods). We also present new formulations of regression problem. OWA-based regression is particularly useful in the presence of outliers.

OWA operators in regression problems

We consider an application of fuzzy logic connectives to statistical regression. We replace the standard least squares, least absolute deviation, and maximum likelihood criteria with an ordered weighted averaging (OWA) function of the residuals. Depending on the choice of the weights, we obtain the standard regression problems, high-breakdown robust methods (least median, least trimmed squares, and trimmed likelihood methods), as well as new formulations. We present various approaches to numerical solution of such regression problems. OWA-based regression is particularly useful in the presence of outliers, and we illustrate the performance of the new methods on several instances of linear regression problems with multiple outliers.

Range size-abundance relationships in Australian passerines

Aim  To investigate the relationship between geographical range size and abundance (population density) in Australian passerines.
Location  Australia (including Tasmania).
Methods   We analysed the relationship between range size and local abundance for 272 species of Australian passerines, across the whole order and within families. We measured abundance as mean and maximum abundance, and used a phylogenetic generalized least-squares regression method within a maximum-likelihood framework to control for effects of phylogeny. We also analysed the relationship within seven different habitat types.
Results  There was no correlation between range size and abundance for the whole set of species across all habitats. Analyses within families revealed some strong correlations but showed no consistent pattern. Likewise we found little evidence for any relationship or conflicting patterns in different habitats, except that woodland/forest habitat species exhibit a negative correlation between mean abundance and range size, whilst species in urban habitats exhibit a significant positive relationship between maximum abundance and range size. Despite the general lack of correlation, the raw data plots of range size and abundance in this study occupied a triangular space, with narrowly distributed species exhibiting a greater variation in abundances than widely distributed species. However, using a null model analysis, we demonstrate that this was due to a statistical artefact generated by the frequency distributions for the individual variables.
Conclusions   We find no evidence for a positive range size-abundance relationship among Australian passerines. This absence of a relationship cannot be explained by any conflicting effects introduced by comparing across different habitats, nor is it explained by the fact that large proportions of Australia are arid. We speculate that the considerable isolation and evolutionary age of Australian passerines may be an explanatory factor.

Blood mineral, trace-element and vitamin concentrations in Huacaya alpacas and Merino sheep grazing the same pasture

We aimed to determine whether the concentration of minerals and trace constituents in blood of Merino sheep and Huacaya alpacas grazing the same pasture differed with species and time of sampling. Blood samples and pasture samples were collected at frequent intervals over a period of 2 years for mineral and trace-nutrient assay. The concentration of the minerals and trace nutrients in the grazed pasture usually met the dietary needs of sheep at maintenance, apart from potassium, sulfur, cobalt and Vitamin E in occasional samples. Restricted maximum likelihood mixed model analysis indicated a significant (P < 0.001) species by month by year interaction for all blood constituents assayed, a significant (P < 0.05) species by coat shade interaction for plasma Vitamin D, E and B12 and a significant (P < 0.001) species by month by Vitamin D interaction for plasma phosphorus concentrations. In general, plasma calcium concentrations were greater in sheep than in alpacas but plasma magnesium concentrations were greater in alpacas than in sheep. There was no consistent difference between the two species in plasma phosphorus concentrations although low values were recorded in individual sheep and alpacas. Plasma Vitamin D concentrations were more responsive to increasing hours of sunlight in alpacas than they were in sheep. Sheep had consistently higher concentrations of plasma copper, zinc and Vitamin B12 and higher concentrations of blood selenium but lower concentrations of plasma selenium and Vitamin A, than did alpacas. No consistent difference was observed between the two species in plasma Vitamin E concentrations.

The hidden permutation model and location-based activity recognition

Permutation modeling is challenging because of the combinatorial nature of the problem. However, such modeling is often required in many real-world applications, including activity recognition where subactivities are often permuted and partially ordered. This paper introduces a novel Hidden Permutation Model (HPM) that can learn the partial ordering constraints in permuted state sequences. The HPM is parameterized as an exponential family distribution and is flexible so that it can encode constraints via different feature functions. A chain-flipping Metropolis-Hastings Markov chain Monte Carlo (MCMC) is employed for inference to overcome the O(n!) complexity. Gradient-based maximum likelihood parameter learning is presented for two cases when the permutation is known and when it is hidden. The HPM is evaluated using both simulated and real data from a location-based activity recognition domain. Experimental results indicate that the HPM performs far better than other baseline models, including the naive Bayes classifier, the HMM classifier, and Kirshner's multinomial permutation model. Our presented HPM is generic and can potentially be utilized in any problem where the modeling of permuted states from noisy data is needed.

The effect of humidity and temperature on Wool Comfort Meter assessment of single jersey wool fabrics

The Wool ComfortMeter provides an objective measurement of the fabric-evoked prickle discomfort rating provided by wearers. This work aimed to quantify the sensitivity of the Wool ComfortMeter over a range of different temperature and humidity conditions to determine the recommended test conditions for its operation. The design was: three temperatures (notionally 20, 25 and 30°C) at three relative humidities (RHs, notionally 50, 65 and 80%) each with two replicates, using six different wool single jersey knits (mean fibre diameter 19.5–27.0 µm). As it was difficult to achieve exactly some of the extreme combinations of temperature and RH, some combinations were repeated, providing a total of 23 different assessment conditions. Data were analysed using restricted maximum likelihood mixed model analysis. The best fixed model included RH, RH2, temperature and the interaction of temperature and RH, accounting for 95% of the variation in Wool ComfortMeter readings. Wool ComfortMeter values were almost constant at 55–60% RH. Generally, the Wool ComfortMeter value reduced with increasing RH > 60% at temperatures of 25°C and 28.5°C as the regain of the fabric increased. However, at 20°C little change was detected as RH was increased from 50 to 80% as there were only small changes in fabric regain. The observed effects were in a good agreement with existing knowledge on the effect of regain on the mechanical properties of wool fibre. Wool ComfortMeter is best operated under standard conditions for textile testing of 65% RH and 20°C.

Production, properties and processing of American bison (Bison bison) wool grown in southern Australia

American bison grow a thick coat of fibres which assists them to withstand severe climatic conditions. Bison fibre was traditionally used in textiles by native North Americans. This study aimed to quantify the production, fibre attributes and dehairing processing of bison fibre produced from bison grazed in north-eastern Victoria. Three age/sex classes were sampled (n = 16) at seven body positions in spring. The fibre growing area was measured. Fibre was tested for diameter distribution, clean washing yield, proportion of fine fibres <36µm and fine fibre length, and processed by cashmere dehairing. Bison were 12 years of age, liveweights 160450 kg and had mean fibre growing area of 1.4 m². They produced an average 1184 g (range 5301640 g) of fine fibre with mean fibre diameter 18.5µm, clean washing yield 76.5%, wax content 9.8%, suint content 14.5%, clean fine fibre yield 56.4%, fine fibre length 37 mm and fibre curvature was 93/mm. Mid-side fibre had a crimp frequency of 6.5/cm and mean resistance to compression of 6.6 kPa. Fibre had a tenacity of 8.7 cN/tex and an extension of 39.3%. Restricted maximum likelihood mixed model analysis showed age/sex class and sampling site significantly affected all fibre attributes. Finer and longer fibre was produced in anterior sites and in younger bison. Fibre curvature declined 5.3°/mm for each 1-µm increase in mean fibre diameter. Dehaired fibre had a mean fibre diameter of 17.8 µm and mid-length of 28 mm, suitable for woollen spinning. The production by bison of coats containing significant amounts of fibre indicates that careful harvesting of fibre could form an important source of income in bison enterprises.