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Dive into the research topics where Matthew G. Falk is active.

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Featured researches published by Matthew G. Falk.


Environmental Science & Technology | 2011

Exposure to Particles from Laser Printers Operating within Office Workplaces

Peter D. McGarry; Lidia Morawska; Congrong He; Rohan Jayaratne; Matthew G. Falk; Quang Tran; Hao Wang

While recent research has provided valuable information as to the composition of laser printer particles, their formation mechanisms, and explained why some printers are emitters while others are low emitters, questions relating to the potential exposure of office workers remained unanswered. In particular, (i) what impact does the operation of laser printers have on the background particle number concentration (PNC) of an office environment over the duration of a typical working day? (ii) What is the airborne particle exposure to office workers in the vicinity of laser printers? (iii) What influence does the office ventilation have upon the transport and concentration of particles? (iv) Is there a need to control the generation of, and/or transport of particles arising from the operation of laser printers within an office environment? (v) What instrumentation and methodology is relevant for characterizing such particles within an office location? We present experimental evidence on printer temporal and spatial PNC during the operation of 107 laser printers within open plan offices of five buildings. The 8 h time-weighted average printer particle exposure is significantly less than the 8 h time-weighted local background particle exposure, but that peak printer particle exposure can be greater than 2 orders of magnitude higher than local background particle exposure. The particle size range is predominantly ultrafine (<100 nm diameter). In addition we have established that office workers are constantly exposed to nonprinter derived particle concentrations, with up to an order of magnitude difference in such exposure among offices, and propose that such exposure be controlled along with exposure to printer derived particles. We also propose, for the first time, that peak particle reference values be calculated for each office area analogous to the criteria used in Australia and elsewhere for evaluating exposure excursion above occupational hazardous chemical exposure standards. A universal peak particle reference value of 2.0 × 10(4) particles cm(-3) has been proposed.


Environmental and Ecological Statistics | 2011

The Bayesian conditional independence model for measurement error: applications in ecology

Robert Denham; Matthew G. Falk; Kerrie Mengersen

The measurement error model is a well established statistical method for regression problems in medical sciences, although rarely used in ecological studies. While the situations in which it is appropriate may be less common in ecology, there are instances in which there may be benefits in its use for prediction and estimation of parameters of interest. We have chosen to explore this topic using a conditional independence model in a Bayesian framework using a Gibbs sampler, as this gives a great deal of flexibility, allowing us to analyse a number of different models without losing generality. Using simulations and two examples, we show how the conditional independence model can be used in ecology, and when it is appropriate.


Environmental and Ecological Statistics | 2014

Sampling designs on stream networks using the pseudo-Bayesian approach

Matthew G. Falk; James McGree; Anthony N. Pettitt

Monitoring stream networks through time provides important ecological information. The sampling design problem is to choose locations where measurements are taken so as to maximise information gathered about physicochemical and biological variables on the stream network. This paper uses a pseudo-Bayesian approach, averaging a utility function over a prior distribution, in finding a design which maximizes the average utility. We use models for correlations of observations on the stream network that are based on stream network distances and described by moving average error models. Utility functions used reflect the needs of the experimenter, such as prediction of location values or estimation of parameters. We propose an algorithmic approach to design with the mean utility of a design estimated using Monte Carlo techniques and an exchange algorithm to search for optimal sampling designs. In particular we focus on the problem of finding an optimal design from a set of fixed designs and finding an optimal subset of a given set of sampling locations. As there are many different variables to measure, such as chemical, physical and biological measurements at each location, designs are derived from models based on different types of response variables: continuous, counts and proportions. We apply the methodology to a synthetic example and the Lake Eacham stream network on the Atherton Tablelands in Queensland, Australia. We show that the optimal designs depend very much on the choice of utility function, varying from space filling to clustered designs and mixtures of these, but given the utility function, designs are relatively robust to the type of response variable.


Environmental and Ecological Statistics | 2011

Spatially stratified sampling using auxiliary information for geostatistical mapping

Matthew G. Falk; Robert Denham; Kerrie Mengersen

This paper presents a method of spatial sampling based on stratification by Local Moran’s Ii calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.


Environmental and Ecological Statistics | 2015

Recent Bayesian approaches for spatial analysis of 2-D images with application to environmental modelling

Matthew G. Falk; Clair L. Alston; Clare A. McGrory; Sam Clifford; Elizabeth A. Heron; Daniela Leonte; Matthew T. Moores; Cathal Walsh; Anthony N. Pettitt; Kerrie Mengersen

From remote sensing of the environment, to brain scans in medicine, the growth in the use of image data has motivated a parallel increase in statistical techniques for analysing these images. A particular area of growth has been in Bayesian models and corresponding computational methods. Bayesian approaches have been proposed to address the gamut of supervised and unsupervised inferential aims in image analysis. In this article we provide a general review of these approaches, with a focus on unsupervised analysis of 2-D images. Four exemplar methods that canvas the broad aims of image modelling and analysis are described. An exposition of these approaches is provided by applying them to an environmental case study involving the use of satellite data to assess water quality in the Great Barrier Reef, Australia. The techniques considered in detail are hidden Markov random fields (MRF), Gaussian MRF, Poisson/gamma random fields, and Voronoi tessellations. We also consider a variety of enabling computational algorithms, including MCMC, variational Bayes and integrated nested Laplace approximations. We compare the different aims and inferential capabilities of the models and discuss the advantages and drawbacks of the corresponding computational algorithms.


Journal of the Scholarship of Teaching and Learning | 2012

Factors affecting timely completion of a PhD : a complex systems approach

Jegar Pitchforth; Stephanie Beames; Aleysha Thomas; Matthew G. Falk; Charisse Farr; Susan Gasson; Sri Astuti Thamrin; Kerrie Mengersen


Journal of Agricultural Biological and Environmental Statistics | 2010

Estimating Uncertainty in the Revised Universal Soil Loss Equation via Bayesian Melding

Matthew G. Falk; Robert Denham; Kerrie Mengersen


Journal of Stored Products Research | 2016

Resistance to phosphine in Sitophilus oryzae in Australia: A national analysis of trends and frequencies over time and geographical spread

Joanne C. Holloway; Matthew G. Falk; Robert N. Emery; Patrick J. Collins; Manoj K. Nayak


Journal of Stored Products Research | 2017

Monitoring resistance to phosphine in the lesser grain borer, Rhyzopertha dominica, in Australia: A national analysis of trends, storage types and geography in relation to resistance detections

Patrick J. Collins; Matthew G. Falk; Manoj K. Nayak; Robert N. Emery; Joanne C. Holloway


Journal of Stored Products Research | 2017

An analysis of trends, frequencies and factors influencing the development of resistance to phosphine in the red flour beetle Tribolium castaneum (Herbst) in Australia

Manoj K. Nayak; Matthew G. Falk; Robert N. Emery; Patrick J. Collins; Joanne C. Holloway

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Kerrie Mengersen

Queensland University of Technology

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Lidia Morawska

Queensland University of Technology

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Congrong He

Queensland University of Technology

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Manoj K. Nayak

Cooperative Research Centre

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Patrick J. Collins

Cooperative Research Centre

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Joanne C. Holloway

Cooperative Research Centre

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Luke D. Knibbs

University of Queensland

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Robert Denham

Queensland University of Technology

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Robert N. Emery

Cooperative Research Centre

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Tran Ngoc Quang

National University of Civil Engineering

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