Semiparametric estimation of count regression models

This paper develops a semiparametric estimation approach for mixed count regression models based on series expansion for the unknown density of the unobserved heterogeneity. We use the generalized Laguerre series expansion around a gamma baseline density to model unobserved heterogeneity in a Poisson mixture model. We establish the consistency of the estimator and present a computational strategy to implement the proposed estimation techniques in the standard count model as well as in truncated, censored, and zero-inflated count regression models. Monte Carlo evidence shows that the finite sample behavior of the estimator is quite good. The paper applies the method to a model of individual shopping behavior. © 1999 Elsevier Science S.A. All rights reserved.

Decision strategies for automated visual collision avoidance

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.

Close-quarters Quadrotor flying for a pole inspection with position based visual servoing and high-speed vision

This paper presents a 100 Hz monocular position based visual servoing system to control a quadrotor flying in close proximity to vertical structures approximating a narrow, locally linear shape. Assuming the object boundaries are represented by parallel vertical lines in the image, detection and tracking is achieved using Plücker line representation and a line tracker. The visual information is fused with IMU data in an EKF framework to provide fast and accurate state estimation. A nested control design provides position and velocity control with respect to the object. Our approach is aimed at high performance on-board control for applications allowing only small error margins and without a motion capture system, as required for real world infrastructure inspection. Simulated and ground-truthed experimental results are presented.

Long-term exploration and tours for energy constrained robots with online proprioceptive traversability estimation

This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore and ultimately converge on minimum energy tours of the environment. We provide results of detailed simulations and parameter studies that show the efficacy of this approach for a robot moving over terrain with unknown traversability as well as a number of a priori unknown hard obstacles.

Empirical modelling of rolling shutter effect

We propose and evaluate a novel methodology to identify the rolling shutter parameters of a real camera. We also present a model for the geometric distortion introduced when a moving camera with a rolling shutter views a scene. Unlike previous work this model allows for arbitrary camera motion, including accelerations, is exact rather than a linearization and allows for arbitrary camera projection models, for example fisheye or panoramic. We show the significance of the errors introduced by a rolling shutter for typical robot vision problems such as structure from motion, visual odometry and pose estimation.

Determining the material properties for heavily over-consolidated bagasse through parameter estimation

A better understanding of the behaviour of prepared cane and bagasse, and the ability to model the mechanical behaviour of bagasse as it is squeezed in a milling unit to extract juice, would help identify how to improve the current process. For example, there are opportunities to decrease bagasse moisture from a milling unit. Also, the behaviour of bagasse in chutes is poorly understood. Previous investigations have shown that juice flow through bagasse obeys Darcy’s permeability law, that the grip of the rough surface of the grooves on the bagasse can be represented by the Mohr-Coulomb failure criterion for soils, and that the internal mechanical behaviour of the bagasse is critical state behaviour similar to that for sand and clay. Progress has been made in the last ten years towards implementing a mechanical model for bagasse in finite element software. The objective has been to be able to simulate simple mechanical loading conditions measured in the laboratory, which, when combined together, have a high probability of reproducing the complicated stress conditions in a milling unit. This paper reports on the successful simulation of part of the fifth and final (and most challenging) loading condition, the shearing of heavily over-consolidated bagasse, and determining material property values through the use of powerful and free parameter estimation software.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions

The issue of using informative priors for estimation of mixtures at multiple time points is examined. Several different informative priors and an independent prior are compared using samples of actual and simulated aerosol particle size distribution (PSD) data. Measurements of aerosol PSDs refer to the concentration of aerosol particles in terms of their size, which is typically multimodal in nature and collected at frequent time intervals. The use of informative priors is found to better identify component parameters at each time point and more clearly establish patterns in the parameters over time. Some caveats to this finding are discussed.

Improving the accuracy of mine site water balances through improved estimation of runoff volumes

A mine site water balance is important for communicating information to interested stakeholders, for reporting on water performance, and for anticipating and mitigating water-related risks through water use/demand forecasting. Gaining accuracy over the water balance is therefore crucial for sites to achieve best practice water management and to maintain their social license to operate. For sites that are located in high rainfall environments the water received to storage dams through runoff can represent a large proportion of the overall inputs to site; inaccuracies in these flows can therefore lead to inaccuracies in the overall site water balance. Hydrological models that estimate runoff flows are often incorporated into simulation models used for water use/demand forecasting. The Australian Water Balance Model (AWBM) is one example that has been widely applied in the Australian context. However, the calibration of AWBM in a mining context can be challenging. Through a detailed case study, we outline an approach that was used to calibrate and validate AWBM at a mine site. Commencing with a dataset of monitored dam levels, a mass balance approach was used to generate an observed runoff sequence. By incorporating a portion of this observed dataset into the calibration routine, we achieved a closer fit between the observed vs. simulated dataset compared with the base case. We conclude by highlighting opportunities for future research to improve the calibration fit through improving the quality of the input dataset. This will ultimately lead to better models for runoff prediction and thereby improve the accuracy of mine site water balances.

Collective motion of dimers

We consider a discrete agent-based model on a one-dimensional lattice and a two-dimensional square lattice, where each agent is a dimer occupying two sites. Agents move by vacating one occupied site in favor of a nearest-neighbor site and obey either a strict simple exclusion rule or a weaker constraint that permits partial overlaps between dimers. Using indicator variables and careful probability arguments, a discrete-time master equation for these processes is derived systematically within a mean-field approximation. In the continuum limit, nonlinear diffusion equations that describe the average agent occupancy of the dimer population are obtained. In addition, we show that multiple species of interacting subpopulations give rise to advection-diffusion equations. Averaged discrete simulation data compares very well with the solution to the continuum partial differential equation models. Since many cell types are elongated rather than circular, this work offers insight into population-level behavior of collective cellular motion.

Stature estimation of a contemporary Australian sub-population: An evaluation of the Trotter and Gleser method using computed tomography of the femur

Utilising computed tomography scans to allow a virtual analysis of three-dimensional reconstructions of the femur, this project confirms that the traditional 1952 Trotter and Gleser stature estimation equations are inapplicable for a contemporary Queensland population. Therefore, this study introduces modern stature estimation equations for femoral length and fragmentary femoral remains using Bayesian statistics for application in forensic anthropological casework. In addition, it was found that caution needs to be applied when comparing estimated stature to reported stature on the missing persons database due to inaccuracy in Queensland drivers' licences.

Facial motion engages predictive visual mechanisms

We employed a novel cuing paradigm to assess whether dynamically versus statically presented facial expressions differentially engaged predictive visual mechanisms. Participants were presented with a cueing stimulus that was either the static depiction of a low intensity expressed emotion; or a dynamic sequence evolving from a neutral expression to the low intensity expressed emotion. Following this cue and a backwards mask, participants were presented with a probe face that displayed either the same emotion (congruent) or a different emotion (incongruent) with respect to that displayed by the cue although expressed at a high intensity. The probe face had either the same or different identity from the cued face. The participants' task was to indicate whether or not the probe face showed the same emotion as the cue. Dynamic cues and same identity cues both led to a greater tendency towards congruent responding, although these factors did not interact. Facial motion also led to faster responding when the probe face was emotionally congruent to the cue. We interpret these results as indicating that dynamic facial displays preferentially invoke predictive visual mechanisms, and suggest that motoric simulation may provide an important basis for the generation of predictions in the visual system.

Minimizing the effects of overfitting and collinearity in construction cost estimation : a new hybird approach

Research problem: Overfitting and collinearity problems commonly exist in current construction cost estimation applications and obstruct researchers and practitioners in achieving better modelling results. Research objective and method: A hybrid approach of Akaike information criterion (AIC) stepwise regression and principal component regression (PCR) is proposed to help solve overfitting and collinearity problems. Utilization of this approach in linear regression is validated by comparing it with other commonly used approaches. The mean square error obtained by leave-one-out cross validation (MSELOOCV) is used in model selection in deciding predictive variables.