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11 Papers

Differential Addition in Edwards Coordinates Revisited and a Short Note on Doubling in Twisted Edwards Form

Topics: Applied Cryptography; Network Security; Network Security; Wireless Network Security

Author: Srinivasa Rao Subramanya Rao

Affiliation: The Australian National University, Australia

Digital Object Identifier: 10.5220/0005970603360343

Proceedings of SECRYPT 2016/ICETE, ISBN: 978-989-758-196-0

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Cryptographic algorithms in smart cards and other constrained environments increasingly rely on Elliptic Curves and thus it is desirable to have fast algorithms for elliptic curve arithmetic. In this paper, we provide (i) faster differential addition formulae for elliptic curve arithmetic on Generalized Edwards’ Curves improving upon the currently known formulae in the literature, proposed by Justus and Loebenberger at IWSEC 2010, (ii) more efficient affine differential addition formulae for a new model of Binary Edwards Curves proposed by Wu, Tang and Feng at INDOCRYPT 2012 and (iii) an algorithm for point doubling on Twisted Edwards Curves with a smaller footprint when the implementation is desired to work across Homogeneous Projective, Inverted and Extended Homogeneous Projective Coordinates.
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Applied Cryptography

Databases and Data Security

Network Security

Cryptographic Techniques and Key Management

Information and Systems Security

Wireless Network Security
Data Engineering

A Note on Schoenmakers Algorithm for Multi Exponentiation

Topics: Applied Cryptography; Security and Privacy in Mobile Systems

Author: Srinivasa Rao Subramanya Rao

Affiliation: The Australian National University, Australia

Digital Object Identifier: 10.5220/0005566903840391

Proceedings of SECRYPT 2015/ICETE, ISBN: 978-989-758-117-5

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In this paper, we provide a triple scalar multiplication analogue of the simultaneous double scalar Schoenmakers’ algorithm for multiexponentiation. We analyse this algorithm to show that on the average, the triple scalar Schoenmakers’ algorithm is more expensive than the straight forward method of computing the individual exponents and then computing the requisite product, thus making it undesirable for use in resource constrained environments. We also show the derivation of the Schoenmakers’ algorithm for simultaneous double scalar multiplication and this is then used to construct the triple scalar multiplication analogue.
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Applied Cryptography

Data Engineering

Information and Systems Security

Cryptographic Techniques and Key Management

Databases and Data Security

Security and Privacy in Mobile Systems

Can Evolutionary Rate Matrices be Estimated from Allele Frequencies?

Topics: Sequence Analysis; Biostatistics and Stochastic Models

Author: Conrad J. Burden

Affiliation: Australian National University, Australia

Digital Object Identifier: 10.5220/0005253701830188

Proceedings of BIOINFORMATICS 2015/BIOSTEC, ISBN: 978-989-758-070-3

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This paper is a work in progress in which aims to combine the principles of population genetics and continuous-time Markovian evolutionary models to estimate evolutionary rate matrices from the current observed state of a single genome. A model is proposed in which sections of the genome which are not susceptible to natural selection are considered to be a statistical ensemble of individual genomic sites. Each site is a representative from a stationary distribution of allele frequencies 0 = ? = 1 within the population. Simulations of this distribution via a finite-state Markov model based on a finite effective population size are compared with the stationary solution to the continuum Fokker-Planck equation. Parameters of the evolutionary rate matrix introduced via mutation rates within the Fokker-Planck equation are estimated for simulated data in a number of exploratory examples.
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Bioinformatics

Biostatistics and Stochastic Models

Sequence Analysis
Biomedical Engineering

Extreme Learning Machines with Simple Cascades

Topic: Neural Nets and Fuzzy Systems

Authors: Tom Gedeon and Anthony Oakden

Affiliation: The Australian National University, Australia

Digital Object Identifier: 10.5220/0005539502710278

Proceedings of SIMULTECH 2015, ISBN: 978-989-758-120-5

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We compare extreme learning machines with cascade correlation on a standard benchmark dataset for comparing cascade networks along with another commonly used dataset. We introduce a number of hybrid cascade extreme learning machine topologies ranging from simple shallow cascade ELM networks to full cascade ELM networks. We found that the simplest cascade topology provided surprising benefit with a cascade correlation style cascade for small extreme learning machine layers. Our full cascade ELM architecture achieved high performance with even a single neuron per ELM cascade, suggesting that our approach may have general utility, though further work needs to be done using more datasets. We suggest extensions of our cascade ELM approach, with the use of network analysis, addition of noise, and unfreezing of weights.
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Formal Methods

Neural Nets and Fuzzy Systems

Simulation and Modeling

The Distribution of Short Word Match Counts between Markovian Sequences

Topics: Sequence Analysis; Biostatistics and Stochastic Models; Pattern Recognition, Clustering and Classification

Authors: Conrad J. Burden , Paul Leopardi and Sylvain Forêt

Affiliation: Australian National University, Australia

Digital Object Identifier: 10.5220/0004203700250033

Proceedings of BIOINFORMATICS 2013/BIOSTEC, ISBN: 978-989-8565-35-8

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The D2 statistic, which counts the number of word matches between two given sequences, has long been proposed as a measure of similarity for biological sequences. Much of the mathematically rigorous work carried out to date on the properties of the D2 statistic has been restricted to the case of ‘Bernoulli’ sequences composed of identically and independently distributed letters. Here the properties of the distribution of this statistic for the biologically more realistic case of Markovian sequences is studied. The approach is novel in that Markovian dependency is defined for sequences with periodic boundary conditions, and this enables exact analytic formulae for the mean and variance to be derived. The formulae are confirmed using numerical simulations, and asymptotic approximations to the full distribution are tested.
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Bioinformatics

Biostatistics and Stochastic Models

Sequence Analysis
Biomedical Engineering

Pattern Recognition, Clustering and Classification

Global Optimal Solution to SLAM Problem with Unknown Initial Estimates

Topic: Optimization Algorithms

Authors: Usman Qayyum and Jonghyuk Kim

Affiliation: Australian National University, Australia

Digital Object Identifier: 10.5220/0004040100760083

Proceedings of ICINCO 2012, ISBN: 978-989-8565-21-1

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The paper presents a practical approach for finding the globally optimal solution to SLAM. Traditional methods are based upon local optimization based strategies and are highly susceptible to local minima due to non-convex nature of the SLAM problem. We employed the nonlinear global optimization based approach to SLAM by exploiting the theoretical limit on the numbers of local minima. Our work is not reliant on good initial guess, whereas existing approaches in SLAM literature assume good starting point to avoid local minima problem. The paper presents experimental results on different datasets to validate the robustness of the approach, finding the global basin of attraction with unknown initial guess.
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Informatics in Control, Automation and Robotics

Intelligent Control Systems and Optimization

Optimization Algorithms

High Repetition Frequency Mode-locked Semiconductor Disk Laser

Topic: Lasers and Photonic Components

Authors: Yanrong Song 1 , Peng Zhang 1 , Jinrong Tian 1 , Zhigang Zhang 2 , Hark Hoe Tan 3 and C. Jagadish 3

Affiliations: 1 Beijing University of Technology, China , 2 Peking University, China , 3 The Australian National University, Australia

Digital Object Identifier: 10.5220/0004022903610364

Proceedings of OPTICS 2012/ICETE, ISBN: 978-989-8565-23-5

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A compact passively mode-locked semiconductor disk laser with a high repetition frequency of 3GHz is demonstrated. 4.9ps pulse duration and 30mW average output power are obtained with 1.4W of 808nm incident pump power. The gain chip consists of 16 compressively strained InGaAs symmetrical step quantum wells in the active region.
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Lasers and Photonic Components

Optical Communication Systems

Telecommunications

IMPROVED ROBUST PERFORMANCE IN A SYSTEM FOR AUTOMATIC ADMINISTRATION OF A VASOACTIVE DRUG

Topics: Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics; Cardiovascular Signals

Authors: Nicolò Malagutti 1 , Arvin Dehghani 2 and Rodney A. Kennedy 1

Affiliations: 1 The Australian National University, Australia , 2 The University of Melbourne, Australia

Digital Object Identifier: 10.5220/0003794002820290

Proceedings of BIOSIGNALS 2012/BIOSTEC, ISBN: 978-989-8425-89-8

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The problem of automatic administration of vasoactive drugs to regulate mean arterial pressure in surgical and postsurgical patients can be considered as a setpoint tracking problem involving a system which is characterised by significant modelling uncertainty in the form of uncertain parameters, unmodelled dynamics and disturbances. Yet, specific levels of performance are required and patient safety must be guaranteed. As part of the development process of a novel Multiple-Model Adaptive Control (MMAC) architecture for this application, we have adopted a mixed-ì synthesis approach to controller design. Simulation results show that the new controllers are capable of improved disturbance rejection and robustness even in the face of large system delays and parametric uncertainty.
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Biomedical Engineering

Cardiovascular Signals

Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics
Biomedical Signal Processing

MUSIC GENRE CLASSIFICATION BASED ON DYNAMICAL MODELS

Authors: Alberto García-Durán 1 , Jerónimo Arenas-García 1 , Darío García-García 2 and Emilio Parrado-Hernández 1

Affiliations: 1 Universidad Carlos III de Madrid, Spain , 2 Australian National University, Australia

Digital Object Identifier: 10.5220/0003859002500256

Proceedings of ICPRAM 2012, ISBN: 978-989-8425-99-7

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This paper studies several alternatives to extract dynamical features from hidden Markov Models (HMMs) that are meaningful for music genre supervised classification. Songs are modelled using a three scale approach: a first stage of short term (milliseconds) features, followed by two layers of dynamical models: a multivariate AR that provides mid term (seconds) features for each song followed by an HMM stage that captures long term (song) features shared among similar songs. We study from an empirical point of view which features are relevant for the genre classification task. Experiments on a database including pieces of heavy metal, punk, classical and reggae music illustrate the advantages of each set of features.

Rigidity and Persistence of Three and Higher Dimensional Formations

Authors: Julien M. Hendrickx 1 , Barıș Fidan 2 , Changbin Yu 2 , Brian D. O. Anderson 2 and Vincent D. Blondel 1

Affiliations: 1 Université Catholique de Louvain, Belgium , 2 Australian National University, Australia

Digital Object Identifier: 10.5220/0001193600390046

Proceedings of MARS 2005/ICINCO, ISBN: 972-8865-34-1

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In this paper, we generalize the notion of persistence, which has been originally introduced for two-dimensional formations, to ℜd for d ≥ 3, seeking to provide a theoretical framework for real world applications, which often are in three-dimensional space as opposed to the plane. We verify that many of the properties of rigid and/or persistent formations established in ℜ2 are also valid for higher dimensions. Analysing the closed subgraphs and directed paths in persistent graphs, we derive some further properties of persistent formations. We also provide an easily checkable necessary condition for persistence.

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