ORCID Profile
0000-0002-7254-2808
Current Organisations
University of Calgary Cumming School of Medicine
,
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)
Applied Statistics | Pattern Recognition and Data Mining | Applied Mathematics | Operations Research | Statistics |
ANZSRC Socio-Economic Objective (SEO)
Emerging Defence Technologies | Computer Software and Services not elsewhere classified | National Security | Expanding Knowledge in the Mathematical Sciences | Library and Archival Services
Related Links
Publications
Landscape characterization of numerical optimization problems using biased scattered data
Publisher: IEEE
Date: 06-2012
Bifidelity Surrogate Modelling: Showcasing the Need for New Test Instances
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 11-2022
Abstract: In recent years, multifidelity expensive black-box (Mf-EBB) methods have received increasing attention due to their strong applicability to industrial design problems. The challenge, however, is that knowledge of the relationship between decisions and objective values is limited to a small set of s le observations of variable quality. In the field of Mf-EBB, a problem instance consists of an expensive yet accurate source of information, and one or more cheap yet less accurate sources of information. The field aims to provide techniques either to accurately explain how decisions affect design outcome, or to find the best decisions to optimise design outcomes. Many techniques that use surrogate models have been developed to provide solutions to both aims. Only in recent years, however, have researchers begun to explore the conditions under which these new techniques are reliable, often focusing on problems with a single low-fidelity function, known as bifidelity expensive black-box (Bf-EBB) problems. This study extends the existing Bf-EBB test instances found in the literature, as well as the features used to determine when the low-fidelity information source should be used. A literature test suite is constructed and augmented with new instances to demonstrate the potentially misleading results that could be reached using only the instances currently found in the literature, and to expose the criticality of a more heterogeneous test suite for algorithm assessment. Addressing the shortcomings of the existing literature, a new set of features is presented, as well as a new instance creation procedure, and a study of their impact on algorithm assessment is conducted. The low-fidelity information source is shown to be valuable if it is often locally accurate, even when its overall accuracy is relatively low. This contradicts the existing literature guidelines, which indicate the low-fidelity information is only useful if it has a high overall accuracy. History: Accepted by Antonio Frangioni, Area Editor for Design & Analysis of Algorithms – Continuous. Funding: This work was supported by Australian Research Council [Grant IC200100009] for the ARC Training Centre in Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA), and the University of Melbourne Research Computing Services and Petascale C us Initiative. N. Andrés-Thió is also supported by a Research Training Program scholarship from the University of Melbourne. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplementary Information [ oi/suppl/10.1287/ijoc.2022.1217 ] or is available from the IJOC GitHub software repository ( github.com/INFORMSJoC ) at [ 0.5281/zenodo.6578060 ].
Enhanced instance space analysis for the maximum flow problem
Publisher: Elsevier BV
Date: 2023
Sampling Effects on Algorithm Selection for Continuous Black-Box Optimization
Publisher: MDPI AG
Date: 11-01-2021
DOI: 10.3390/A14010019
Abstract: In this paper, we investigate how systemic errors due to random s ling impact on automated algorithm selection for bound-constrained, single-objective, continuous black-box optimization. We construct a machine learning-based algorithm selector, which uses exploratory landscape analysis features as inputs. We test the accuracy of the recommendations experimentally using res ling techniques and the hold-one-instance-out and hold-one-problem-out validation methods. The results demonstrate that the selector remains accurate even with s ling noise, although not without trade-offs.
On normalization and algorithm selection for unsupervised outlier detection
Publisher: Springer Science and Business Media LLC
Date: 21-11-2020
Non-parametric model of the space of continuous black-box optimization problems
Publisher: ACM
Date: 15-07-2017
A comparison of optimization methods and knee joint degrees of freedom on muscle force predictions during single-leg hop landings
Publisher: Elsevier BV
Date: 09-2014
DOI: 10.1016/J.JBIOMECH.2014.07.027
Abstract: The aim of this paper was to compare the effect of different optimisation methods and different knee joint degrees of freedom (DOF) on muscle force predictions during a single legged hop. Nineteen subjects performed single-legged hopping manoeuvres and subject-specific musculoskeletal models were developed to predict muscle forces during the movement. Muscle forces were predicted using static optimisation (SO) and computed muscle control (CMC) methods using either 1 or 3 DOF knee joint models. All sagittal and transverse plane joint angles calculated using inverse kinematics or CMC in a 1 DOF or 3 DOF knee were well-matched (RMS error<3°). Biarticular muscles (hamstrings, rectus femoris and gastrocnemius) showed more differences in muscle force profiles when comparing between the different muscle prediction approaches where these muscles showed larger time delays for many of the comparisons. The muscle force magnitudes of vasti, gluteus maximus and gluteus medius were not greatly influenced by the choice of muscle force prediction method with low normalised root mean squared errors (<48%) observed in most comparisons. We conclude that SO and CMC can be used to predict lower-limb muscle co-contraction during hopping movements. However, care must be taken in interpreting the magnitude of force predicted in the biarticular muscles and the soleus, especially when using a 1 DOF knee. Despite this limitation, given that SO is a more robust and computationally efficient method for predicting muscle forces than CMC, we suggest that SO can be used in conjunction with musculoskeletal models that have a 1 or 3 DOF knee joint to study the relative differences and the role of muscles during hopping activities in future studies.
Implementation of a Distributed Control Experimentation Platform
Publisher: IEEE
Date: 2005
Instance spaces for machine learning classification
Publisher: Springer Science and Business Media LLC
Date: 28-12-2017
On the diversity and robustness of parameterised multi-objective test suites
Publisher: Elsevier BV
Date: 10-2021
Performance Analysis of Continuous Black-Box Optimization Algorithms via Footprints in Instance Space
Publisher: MIT Press
Date: 12-2017
DOI: 10.1162/EVCO_A_00194
Abstract: This article presents a method for the objective assessment of an algorithm’s strengths and weaknesses. Instead of examining the performance of only one or more algorithms on a benchmark set, or generating custom problems that maximize the performance difference between two algorithms, our method quantifies both the nature of the test instances and the algorithm performance. Our aim is to gather information about possible phase transitions in performance, that is, the points in which a small change in problem structure produces algorithm failure. The method is based on the accurate estimation and characterization of the algorithm footprints, that is, the regions of instance space in which good or exceptional performance is expected from an algorithm. A footprint can be estimated for each algorithm and for the overall portfolio. Therefore, we select a set of features to generate a common instance space, which we validate by constructing a sufficiently accurate prediction model. We characterize the footprints by their area and density. Our method identifies complementary performance between algorithms, quantifies the common features of hard problems, and locates regions where a phase transition may lie.
A Meta-learning Prediction Model of Algorithm Performance for Continuous Optimization Problems
Publisher: Springer Berlin Heidelberg
Date: 2012
Parameter estimation for a point-source diffusion-decay morphogen model.
Publisher: Springer Science and Business Media LLC
Date: 25-04-2020
Simplifying the Bacteria Foraging Optimization Algorithm
Publisher: IEEE
Date: 07-2010
An Instance Space Analysis of Constrained Multiobjective Optimization Problems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2023
Informing Multiobjective Optimization Benchmark Construction Through Instance Space Analysis
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2022
Ant Colony Optimization for Dynamical Resource Allocation in a Multizone Temperature Experimentation Platform
Publisher: IEEE
Date: 09-2006
Instance Space Analysis of Search-Based Software Testing
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances
Publisher: ACM
Date: 12-07-2023
Ant Colony Optimization for Dynamical Resource Allocation in a Multizone Temperature Experimentation Platform
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2007
A system dynamics model for sustainable corporate strategic planning
Publisher: FapUNIFESP (SciELO)
Date: 2022
Bacteria Swarm Foraging Optimization for Dynamical Resource Allocation in a Multizone Temperature Experimentation Platform
Publisher: Springer Berlin Heidelberg
Date: 2007
Biomechanical Markers of Forward Hop-Landing After ACL-Reconstruction
Publisher: Springer Science and Business Media LLC
Date: 31-01-2022
DOI: 10.1007/S10439-022-02921-4
Abstract: Biomechanical changes after anterior cruciate ligament reconstruction (ACLR) may be detrimental to long-term knee-joint health. We used pattern recognition to characterise biomechanical differences during the landing phase of a single-leg forward hop after ACLR. Experimental data from 66 in iduals 12-24 months post-ACLR (28.2 ± 6.3 years) and 32 controls (25.2 ± 4.8 years old) were input into a musculoskeletal modelling pipeline to calculate joint angles, joint moments and muscle forces. These waveforms were transformed into principal components (features), and input into a pattern recognition pipeline, which found 10 main distinguishing features (and 8 associated features) between ACLR and control landing biomechanics at significance $$\\alpha =0.05$$ α = 0.05 . Our process identified known biomechanical characteristics post-ACLR: smaller knee flexion angle less knee extensor moment lower vasti, rectus femoris and hamstrings forces. Importantly, we found more novel and less well-understood adaptations: smaller ankle plantar flexor moment lower soleus forces and altered patterns of knee rotation angle, hip rotator moment and knee abduction moment. Crucially, we identified, with high certainty, subtle aberrations indicating landing instability in the ACLR group for: knee flexion and internal rotation angles and moments hip rotation angles and moments and lumbar rotator and bending moments. Our findings may benefit rehabilitation and assessment for return-to-sport 12–24 months post-ACLR.
Exploratory Landscape Analysis of Continuous Space Optimization Problems Using Information Content
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2015
Analyzing randomness effects on the reliability of exploratory landscape analysis
Publisher: Springer Science and Business Media LLC
Date: 12-02-2021
Algorithm selection for black-box continuous optimization problems: A survey on methods and challenges
Publisher: Elsevier BV
Date: 10-2015
Mechanisms of neuromuscular fatigue and recovery in unilateral versus bilateral maximal voluntary contractions
Publisher: American Physiological Society
Date: 04-2020
DOI: 10.1152/JAPPLPHYSIOL.00651.2019
Abstract: The aim of this study was to investigate differences in neuromuscular function and corticospinal excitability in response to sustained unilateral (UNIL) and bilateral (BIL) isometric maximal voluntary contraction (IMVC) of the knee extensors. Eleven men performed a 1-min sustained IMVC of the knee extensors with one or both legs. Central and peripheral measures of neuromuscular function and corticospinal excitability were assessed via surface electromyography (EMG), peripheral nerve stimulation, and transcranial magnetic stimulation before, immediately after, and during recovery from IMVC. IMVC force and root-mean-squared EMG decreased during the fatiguing 1-min IMVC, with a larger decrease in EMG during BIL. All neuromuscular function indexes decreased significantly after the IMVC ( P 0.005), but the magnitude of these decreases did not differ between conditions. Changes in corticospinal excitability (motor evoked potential) and inhibition (silent period) did not differ between conditions. In contrast to previous studies utilizing submaximal exercise, no more peripheral fatigue was found after UNIL vs. BIL conditions, even though central drive was lower after BIL 1-min IMVC. Corticospinal excitability and inhibition were not found to be different between UNIL and BIL conditions, in line with maximal voluntary activation. NEW & NOTEWORTHY The present experiment used peripheral nerve stimulation and transcranial magnetic stimulations during a sustained isometric maximal voluntary contraction to investigate the influence of muscle mass on neuromuscular fatigue. Contrary to previous studies that used submaximal exercise, peripheral fatigue was not found to be greater in unilateral vs. bilateral knee extensions even though central drive was lower during bilateral contractions. Corticospinal excitability and inhibition were not found to be different between unilateral and bilateral conditions.
Generating New Space-Filling Test Instances for Continuous Black-Box Optimization
Publisher: MIT Press - Journals
Date: 09-2020
DOI: 10.1162/EVCO_A_00262
Abstract: This article presents a method to generate erse and challenging new test instances for continuous black-box optimization. Each instance is represented as a feature vector of exploratory landscape analysis measures. By projecting the features into a two-dimensional instance space, the location of existing test instances can be visualized, and their similarities and differences revealed. New instances are generated through genetic programming which evolves functions with controllable characteristics. Convergence to selected target points in the instance space is used to drive the evolutionary process, such that the new instances span the entire space more comprehensively. We demonstrate the method by generating two-dimensional functions to visualize its success, and ten-dimensional functions to test its scalability. We show that the method can recreate existing test functions when target points are co-located with existing functions, and can generate new functions with entirely different characteristics when target points are located in empty regions of the instance space. Moreover, we test the effectiveness of three state-of-the-art algorithms on the new set of instances. The results demonstrate that the new set is not only more erse than a well-known benchmark set, but also more challenging for the tested algorithms. Hence, the method opens up a new avenue for developing test instances with controllable characteristics, necessary to expose the strengths and weaknesses of algorithms, and drive algorithm development.
On the selection of fitness landscape analysis metrics for continuous optimization problems
Publisher: IEEE
Date: 12-2014
An artificial beehive algorithm for continuous optimization
Publisher: Hindawi Limited
Date: 11-2009
DOI: 10.1002/INT.20376
Early Detection of Vegetation Ignition Due to Powerline Faults
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
SelfAdaptive Bacteria Swarm for Optimization
Publisher: IEEE
Date: 09-2008
Instance Space Analysis for Algorithm Testing: Methodology and Software Tools
Publisher: Association for Computing Machinery (ACM)
Date: 02-03-2023
DOI: 10.1145/3572895
Abstract: Instance Space Analysis (ISA) is a recently developed methodology to (a) support objective testing of algorithms and (b) assess the ersity of test instances. Representing test instances as feature vectors, the ISA methodology extends Rice’s 1976 Algorithm Selection Problem framework to enable visualization of the entire space of possible test instances, and gain insights into how algorithm performance is affected by instance properties. Rather than reporting algorithm performance on average across a chosen set of test problems, as is standard practice, the ISA methodology offers a more nuanced understanding of the unique strengths and weaknesses of algorithms across different regions of the instance space that may otherwise be hidden on average. It also facilitates objective assessment of any bias in the chosen test instances and provides guidance about the adequacy of benchmark test suites. This article is a comprehensive tutorial on the ISA methodology that has been evolving over several years, and includes details of all algorithms and software tools that are enabling its worldwide adoption in many disciplines. A case study comparing algorithms for university timetabling is presented to illustrate the methodology and tools.
Effect of blood flow occlusion on neuromuscular fatigue following sustained maximal isometric contraction
Publisher: Canadian Science Publishing
Date: 07-2020
Abstract: Sustained isometric maximal voluntary contractions (IMVCs) have blood flow occlusive effects on the microvasculature. However, it is unknown if this effect would be magnified with additional blood flow restriction via a cuff and what the influence on fatigue development would be. Twelve healthy male participants performed a 1-min IMVC of the knee extensors with and without additional blood flow occlusion induced by pneumatic cuff in counterbalanced order on separate days. Vastus lateralis muscle deoxygenation was estimated via near-infrared spectroscopy–derived tissue oxygen saturation (SmO 2 ) throughout the fatiguing contraction. Central and peripheral measures of neuromuscular fatigue (NMF) were assessed via surface electromyography (EMG) and force responses to voluntary contractions and peripheral nerve/transcranial magnetic stimulations before, immediately after, and throughout an 8-min recovery period. SmO 2 , force, and EMG litude decreased during the 1-min IMVC, but there were no between-condition differences. Similarly, no significant (p 0.05) between-condition differences were detected for any dependent variable immediately after the fatiguing contraction. Transcranial magnetic stimulation (TMS)-derived voluntary activation was lower (p 0.05) in the no-cuff condition during the recovery period. Sustained IMVC results in a similar degree of muscle deoxygenation and NMF as IMVCs with additional occlusion, providing further evidence that a sustained IMVC induces full ischemia. Novelty NMF etiology, muscle oxygenation, and corticospinal factors during an IMVC are similar with or without an occlusion cuff. Contrary to all other measures, TMS-evaluated voluntary activation returned to baseline faster following the occluded condition.
Effects of function translation and dimensionality reduction on landscape analysis
Publisher: IEEE
Date: 05-2015
Optimal construction of montages from mathematical functions on a spectrum of order–disorder preference
Publisher: Informa UK Limited
Date: 02-10-2022
ICARUS: Identification of complementary algorithms by uncovered sets
Publisher: IEEE
Date: 07-2016
Toward a dynamic evaluation of mineral criticality: Introducing the framework of criticality systems
Publisher: Wiley
Date: 20-05-2019
DOI: 10.1111/JIEC.12920
Related Organisations
Cumming School Of Medicine, University Of Calgary
Location: No location found
University Of Brighton
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
Linkage Projects - Grant ID: LP160101885
Start Date: 09-2017
End Date: 09-2019
Amount: $204,000.00
Funder: Australian Research Council
View Funded ActivityAustralian Laureate Fellowships - Grant ID: FL140100012
Start Date: 12-2014
End Date: 12-2020
Amount: $2,830,000.00
Funder: Australian Research Council
View Funded Activity