ORCID Profile
0000-0002-8141-3362
Current Organisation
University of Melbourne
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Numerical and Computational Mathematics | Optimisation | Operations Research | Optimisation | Operations Research | Electrical and Electronic Engineering | Mining Engineering | Mining Engineering | Power and Energy Systems Engineering (excl. Renewable Power) | Applied Mathematics | Pure Mathematics | Systems Theory And Control | Wireless Communications | Combinatorics and Discrete Mathematics (excl. Physical Combinatorics) | Communications Technologies | Stochastic Analysis and Modelling | Electrical Engineering | Other Information, Computing And Communication Sciences
ANZSRC Socio-Economic Objective (SEO)
Expanding Knowledge in Engineering | Expanding Knowledge in the Mathematical Sciences | Combined operations | Energy Services and Utilities | Mining and Extraction of Precious (Noble) Metal Ores | Mining and Extraction of Copper Ores | Communication equipment not elsewhere classified | Information processing services | Native forests | Communication Networks and Services not elsewhere classified | Urban and Industrial Water Management | Industrial Energy Conservation and Efficiency | Energy Conservation and Efficiency in Transport |
Related Links
Publications
Curvature-constrained directional-cost paths in the plane
Publisher: Springer Science and Business Media LLC
Date: 31-05-2012
The Steiner ratio conjecture for six points
Publisher: Elsevier BV
Date: 09-1991
A note on distance-based geolocation in wireless sensor networks
Publisher: IEEE
Date: 2005
Minimum networks for four points in space
Publisher: Springer Science and Business Media LLC
Date: 2002
Network optimization for the design of underground mines
Publisher: Wiley
Date: 02-10-2007
DOI: 10.1002/NET.20140
Maximum parsimony, substitution model, and probability phylogenetic trees
Publisher: Mary Ann Liebert Inc
Date: 2011
Abstract: The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with ex les.
Canonical forms and algorithms for steiner trees in uniform orientation metrics
Publisher: Springer Science and Business Media LLC
Date: 30-09-2006
On making energy demand and network constraints compatible in the last mile of the power grid
Publisher: Elsevier BV
Date: 2014
Approximating minimum Steiner point trees in Minkowski planes
Publisher: Wiley
Date: 19-02-2010
DOI: 10.1002/NET.20376
Locally minimal uniformly oriented shortest networks
Publisher: Elsevier BV
Date: 12-2006
Optimising declines in underground mines
Publisher: Informa UK Limited
Date: 12-2003
Goal-directed control with cortical units that are gated by both top-down feedback and oscillatory coherence.
Publisher: Frontiers Media SA
Date: 08-08-2014
Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks III: Partially connected neurons driven by spontaneous activity.
Publisher: Springer Science and Business Media LLC
Date: 24-11-2009
DOI: 10.1007/S00422-009-0343-4
Abstract: In contrast to a feed-forward architecture, the weight dynamics induced by spike-timing-dependent plasticity (STDP) in a recurrent neuronal network is not yet well understood. In this article, we extend a previous study of the impact of additive STDP in a recurrent network that is driven by spontaneous activity (no external stimulating inputs) from a fully connected network to one that is only partially connected. The asymptotic state of the network is analyzed, and it is found that the equilibrium and stability conditions for the firing rates are similar for both full and partial connectivity: STDP causes the firing rates to converge toward the same value and remain quasi-homogeneous. However, when STDP induces strong weight competition, the connectivity affects the weight dynamics in that the distribution of the weights disperses more quickly for lower density than for higher density. The asymptotic weight distribution strongly depends upon that at the beginning of the learning epoch consequently, homogeneous connectivity alone is not sufficient to obtain homogeneous neuronal activity. In the absence of external inputs, STDP can nevertheless generate structure in the network through autocorrelation effects, for ex le, by introducing asymmetry in network topology.
Constructing minimum cost flow-dependent networks
Publisher: SPIE
Date: 03-09-2002
DOI: 10.1117/12.481078
A Market Mechanism for Electric Vehicle Charging under Network Constraints
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2016
Electric vehicle charging and grid constraints: Comparing distributed and centralized approaches
Publisher: IEEE
Date: 2013
Delay selection by spike-timing-dependent plasticity in recurrent networks of spiking neurons receiving oscillatory inputs.
Publisher: Public Library of Science (PLoS)
Date: 07-02-2013
Computing Steiner points for gradient-constrained minimum networks
Publisher: Elsevier BV
Date: 02-2010
The Steiner ratio conjecture for cocircular points
Publisher: Springer Science and Business Media LLC
Date: 1992
DOI: 10.1007/BF02187826
Graham's problem on shortest networks for points on a circle
Publisher: Springer Science and Business Media LLC
Date: 06-1992
DOI: 10.1007/BF01758758
Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. II. Input selectivity--symmetry breaking.
Publisher: Springer Science and Business Media LLC
Date: 18-06-2009
DOI: 10.1007/S00422-009-0320-Y
Abstract: Spike-timing-dependent plasticity (STDP) is believed to structure neuronal networks by slowly changing the strengths (or weights) of the synaptic connections between neurons depending upon their spiking activity, which in turn modifies the neuronal firing dynamics. In this paper, we investigate the change in synaptic weights induced by STDP in a recurrently connected network in which the input weights are plastic but the recurrent weights are fixed. The inputs are ided into two pools with identical constant firing rates and equal within-pool spike-time correlations, but with no between-pool correlations. Our analysis uses the Poisson neuron model in order to predict the evolution of the input synaptic weights and focuses on the asymptotic weight distribution that emerges due to STDP. The learning dynamics induces a symmetry breaking for the in idual neurons, namely for sufficiently strong within-pool spike-time correlation each neuron specializes to one of the input pools. We show that the presence of fixed excitatory recurrent connections between neurons induces a group symmetry-breaking effect, in which neurons tend to specialize to the same input pool. Consequently STDP generates a functional structure on the input connections of the network.
The steiner minimal network for convex configurations
Publisher: Springer Science and Business Media LLC
Date: 03-1993
DOI: 10.1007/BF02189325
A comparison study of commercial 18650-format lithium-ion battery cells
Publisher: The Electrochemical Society
Date: 2015
DOI: 10.1149/2.0721508JES
Optimum Steiner ratio for gradient-constrained networks connecting three points in 3-space, part I
Publisher: Wiley
Date: 17-12-2009
DOI: 10.1002/NET.20285
Comment on a comparative testing study of commercial 18650-format lithium-ion battery cells [J. Electrochem. Soc., 162, A1592 (2015)]
Publisher: The Electrochemical Society
Date: 2015
DOI: 10.1149/2.0241512JES
On the effect of component mismatches in inverter interfaced microgrids
Publisher: IEEE
Date: 09-2014
Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks V: self-organization schemes and weight dependence.
Publisher: Springer Science and Business Media LLC
Date: 29-09-2010
DOI: 10.1007/S00422-010-0405-7
Abstract: Spike-timing-dependent plasticity (STDP) determines the evolution of the synaptic weights according to their pre- and post-synaptic activity, which in turn changes the neuronal activity on a (much) slower time scale. This paper examines the effect of STDP in a recurrently connected network stimulated by external pools of input spike trains, where both input and recurrent synapses are plastic. Our previously developed theoretical framework is extended to incorporate weight-dependent STDP and dendritic delays. The weight dynamics is determined by an interplay between the neuronal activation mechanisms, the input spike-time correlations, and the learning parameters. For the case of two external input pools, the resulting learning scheme can exhibit a symmetry breaking of the input connections such that two neuronal groups emerge, each specialized to one input pool only. In addition, we show how the recurrent connections within each neuronal group can be strengthened by STDP at the expense of those between the two groups. This neuronal self-organization can be seen as a basic dynamical ingredient for the emergence of neuronal maps induced by activity-dependent plasticity.
Local measurements and virtual pricing signals for residential demand side management
Publisher: Elsevier BV
Date: 12-2015
Reconstruction of probability phylogenetic trees with substitution models
Publisher: IEEE
Date: 06-2009
Optimum steiner ratio for gradient-constrained networks connecting three points in 3-space, part II: The gradient-constraint m satisfies 1 ≤ m ≤ √3
Publisher: Wiley
Date: 10-2011
DOI: 10.1002/NET.20406
Maximizing the net present value of a Steiner tree
Publisher: Springer Science and Business Media LLC
Date: 22-10-2014
Solving the prize‐collecting Euclidean Steiner tree problem
Publisher: Wiley
Date: 05-08-2020
DOI: 10.1111/ITOR.12853
Abstract: The prize‐collecting Euclidean Steiner tree (PCEST) problem is a generalization of the well‐known Euclidean Steiner tree (EST) problem. All points given in an EST problem instance are connected by the shortest possible network in a solution. A solution can include additional points called Steiner points. A PCEST problem instance differs from an EST problem instance by the addition of weights for each given point. A PCEST solution connects a subset of the given points in order to maximize the net value of the network (the sum of the selected point weights, less than the length of the network). We present an algorithmic framework for solving the PCEST problem. Included in the framework are efficient methods to determine subsets of points that must be in every solution, and subsets of points that cannot be in any solution. Also included are methods to generate and concatenate full Steiner trees.
Gradient-Constrained Minimum Networks. III. Fixed Topology
Publisher: Springer Science and Business Media LLC
Date: 29-03-2012
Cost optimisation for underground mining networks
Publisher: Springer Science and Business Media LLC
Date: 06-2005
Improving underground mine access layouts using software tools
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 04-2014
Abstract: The authors have developed two software tools, PUNO and DOT, for optimally designing the layout of the system of tunnels in an underground mine, known as the access network for the mine. We recently applied these tools, which use principles from geometric optimization, to ore deposits at the Prominent Hill mine in South Australia and the Leeville gold mine in Nevada. When we compared the designs that the tools generated with the designs prepared by mining engineers, we found that our tools generated designs more quickly, were at least as cost efficient, and often revealed new design options by which the engineers’ original designs could be improved.
Modeling reversible self-discharge in series-connected Li-ion battery cells
Publisher: IEEE
Date: 04-2013
Representation of input structure in synaptic weights by spike-timing-dependent plasticity.
Publisher: American Physical Society (APS)
Date: 13-08-2010
Minimum Steiner trees on a set of concyclic points and their center
Publisher: Wiley
Date: 13-09-2021
DOI: 10.1111/ITOR.13055
Abstract: Consider a configuration of points comprising a point q and a set of concyclic points R that are all a given distance r from q in the Euclidean plane. In this paper, we investigate the relationship between the length of a minimum Steiner tree (MStT) on and a minimum spanning tree on R . We show that if the degree of q in the MStT is 1, then the difference between these two lengths is at least , and that this lower bound is tight. This bound can be applied as part of an efficient algorithm to find the solution to the prize‐collecting Euclidean Steiner tree problem, as outlined in an earlier paper.
Gradient-constrained discounted Steiner trees I: optimal tree configurations
Publisher: Springer Science and Business Media LLC
Date: 20-06-2016
The bottleneck 2-connected k
Publisher:
Elsevier BV
Date:
05-2012
Publisher: Elsevier BV
Date: 05-2012
Optimal curvature-constrained paths for general directional-cost functions
Publisher: Springer Science and Business Media LLC
Date: 17-12-2013
A variational approach to the Steiner network problem
Publisher: Springer Science and Business Media LLC
Date: 06-1991
DOI: 10.1007/BF02071984
Gradient-constrained minimum networks (II). Labelled or locally minimal Steiner points
Publisher: Springer Science and Business Media LLC
Date: 26-09-2008
Upper and lower bounds for the lengths of steiner trees in 3-space
Publisher: Springer Science and Business Media LLC
Date: 12-2004
Optimal charging of electric vehicles taking distribution network constraints into account
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2015
Minimal steiner trees for 2k × 2k square lattices
Publisher: Elsevier BV
Date: 1996
OPTIMAL LOCATION OF AN UNDERGROUND CONNECTOR USING DISCOUNTED STEINER TREE THEORY
Publisher: Cambridge University Press (CUP)
Date: 07-2020
DOI: 10.1017/S1446181120000231
Abstract: The objective of this paper is to demonstrate that the gradient-constrained discounted Steiner point algorithm (GCDSPA) described in an earlier paper by the authors is applicable to a class of real mine planning problems, by using the algorithm to design a part of the underground access in the Rubicon gold mine near Kalgoorlie in Western Australia. The algorithm is used to design a decline connecting two ore bodies so as to maximize the net present value (NPV) associated with the connector. The connector is to break out from the access infrastructure of one ore body and extend to the other ore body. There is a junction on the connector where it splits in two near the second ore body. The GCDSPA is used to obtain the optimal location of the junction and the corresponding NPV. The result demonstrates that the GCDSPA can be used to solve certain problems in mine planning for which currently available methods cannot provide optimal solutions.
Spike-timing dependent plasticity in recurrently connected networks with fixed external inputs
Publisher: Springer Berlin Heidelberg
Date: 2008
Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks IV: structuring synaptic pathways among recurrent connections.
Publisher: Springer Science and Business Media LLC
Date: 24-11-2009
DOI: 10.1007/S00422-009-0346-1
Abstract: In neuronal networks, the changes of synaptic strength (or weight) performed by spike-timing-dependent plasticity (STDP) are hypothesized to give rise to functional network structure. This article investigates how this phenomenon occurs for the excitatory recurrent connections of a network with fixed input weights that is stimulated by external spike trains. We develop a theoretical framework based on the Poisson neuron model to analyze the interplay between the neuronal activity (firing rates and the spike-time correlations) and the learning dynamics, when the network is stimulated by correlated pools of homogeneous Poisson spike trains. STDP can lead to both a stabilization of all the neuron firing rates (homeostatic equilibrium) and a robust weight specialization. The pattern of specialization for the recurrent weights is determined by a relationship between the input firing-rate and correlation structures, the network topology, the STDP parameters and the synaptic response properties. We find conditions for feed-forward pathways or areas with strengthened self-feedback to emerge in an initially homogeneous recurrent network.
Minimum cost flow-dependent communication networks
Publisher: Wiley
Date: 17-05-2006
DOI: 10.1002/NET.20118
Euclidean Steiner trees optimal with respect to swapping 4-point subtrees
Publisher: Springer Science and Business Media LLC
Date: 19-06-2014
Modeling and validation of an unbalanced LV network using Smart Meter and SCADA inputs
Publisher: IEEE
Date: 04-2013
On general matrix measures
Publisher: Oxford University Press (OUP)
Date: 1976
Decline design in underground mines using constrained path optimisation
Publisher: Informa UK Limited
Date: 06-2008
A polynomial algorithm for a constrained traveling salesman problem
Publisher: Wiley
Date: 14-08-2001
DOI: 10.1002/NET.1025
Minimal curvature-constrained paths in the plane with a constraint on arcs with opposite orientations
Publisher: World Scientific Pub Co Pte Lt
Date: 06-2013
DOI: 10.1142/S0218195913500064
Abstract: The declines that provide vehicle access in an underground mine are typically designed as paths formed by concatenating line segments and circular arcs. In order to reduce wear on the ore trucks and the road surfaces and to enhance driver safety, such paths may be subject to a further constraint: each pair of consecutive arcs with opposite orientations must be separated by a straight line segment of at least a certain specified length. In order to reduce the construction and operational costs of the mine, it is desirable to minimize the lengths of such paths between any given pair of directed points. Some necessary and sufficient conditions are obtained for paths of this form to be locally or globally minimal with respect to length. In particular, it is shown that there is always a globally minimal path that contains at most four circular arcs.
Forbidden Subpaths for Steiner Minimum Networks in Uniform Orientation Metrics
Publisher: Wiley
Date: 31-05-2002
DOI: 10.1002/NET.10025
The importance of spatial distribution when analysing the impact of electric vehicles on voltage stability in distribution networks
Publisher: Springer Science and Business Media LLC
Date: 22-04-2014
An exact algorithm for the bottleneck 2-connected k
Publisher: Elsevier BV
Date: 03-2016
A distributed electric vehicle charging management algorithm using only local measurements
Publisher: IEEE
Date: 02-2014
Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity--strengthening correlated input pathways.
Publisher: Springer Science and Business Media LLC
Date: 18-06-2009
DOI: 10.1007/S00422-009-0319-4
Abstract: Spike-timing-dependent plasticity (STDP) determines the evolution of the synaptic weights according to their pre- and post-synaptic activity, which in turn changes the neuronal activity. In this paper, we extend previous studies of input selectivity induced by (STDP) for single neurons to the biologically interesting case of a neuronal network with fixed recurrent connections and plastic connections from external pools of input neurons. We use a theoretical framework based on the Poisson neuron model to analytically describe the network dynamics (firing rates and spike-time correlations) and thus the evolution of the synaptic weights. This framework incorporates the time course of the post-synaptic potentials and synaptic delays. Our analysis focuses on the asymptotic states of a network stimulated by two homogeneous pools of "steady" inputs, namely Poisson spike trains which have fixed firing rates and spike-time correlations. The (STDP) model extends rate-based learning in that it can implement, at the same time, both a stabilization of the in idual neuron firing rates and a slower weight specialization depending on the input spike-time correlations. When one input pathway has stronger within-pool correlations, the resulting synaptic dynamics induced by (STDP) are shown to be similar to those arising in the case of a purely feed-forward network: the weights from the more correlated inputs are potentiated at the expense of the remaining input connections.
Gradient-constrained discounted Steiner trees II: optimally locating a discounted Steiner point
Publisher: Springer Science and Business Media LLC
Date: 24-06-2016
A geometric characterisation of the quadratic min-power centre
Publisher: Elsevier BV
Date: 02-2014
Power sharing correction in angle droop controlled inverter interfaced microgrids
Publisher: IEEE
Date: 07-2015
Generalised k-Steiner Tree Problems in Normed Planes
Publisher: Springer Science and Business Media LLC
Date: 19-04-2013
Gradient-constrained minimum networks. I. Fundamentals
Publisher: Springer Science and Business Media LLC
Date: 2001
Relay augmentation for lifetime extension of wireless sensor networks
Publisher: Institution of Engineering and Technology (IET)
Date: 06-2013
Probability Steiner trees and maximum parsimony in phylogenetic analysis
Publisher: Springer Science and Business Media LLC
Date: 25-06-2012
DOI: 10.1007/S00285-011-0442-4
Abstract: The phylogenetic tree (PT) problem has been studied by a number of researchers as an application of the Steiner tree problem, a well-known network optimisation problem. Of all the methods developed for phylogenies the maximum parsimony (MP) method is a simple and commonly used method because it relies on directly observable changes in the input nucleotide or amino acid sequences. In this paper we show that the non-uniqueness of the evolutionary pathways in the MP method leads us to consider a new model of PTs. In this so-called probability representation model, for each site a node in a PT is modelled by a probability distribution of nucleotide or amino acid states, and hence the PT at a given site is a probability Steiner tree, i.e. a Steiner tree in a high-dimensional vector space. In spite of the generality of the probability representation model, in this paper we restrict our study to constructing probability phylogenetic trees (PPT) using the parsimony criterion, as well as discussing and comparing our approach with the classical MP method. We show that for a given input set although the optimal topology as well as the total tree length of the PPT is the same as the PT constructed by the classical MP method, the inferred ancestral states and branch lengths are different and the results given by our method provide a plausible alternative to the classical ones.
A flow‐dependent quadratic steiner tree problem in the Euclidean plane
Publisher: Wiley
Date: 12-04-2014
DOI: 10.1002/NET.21553
Coexistence of reward and unsupervised learning during the operant conditioning of neural firing rates.
Publisher: Public Library of Science (PLoS)
Date: 27-01-2014
On the history of the Euclidean Steiner tree problem
Publisher: Springer Science and Business Media LLC
Date: 27-08-2013
Optimal curvature and gradient-constrained directional cost paths in 3-space
Publisher: Springer Science and Business Media LLC
Date: 15-10-2015
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University Of Oxford
Location: United Kingdom of Great Britain and Northern Ireland
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