Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Traffic state estimation from partial Bluetooth and volume observations : case study in the Brisbane metropolitan area

The application of the Bluetooth (BT) technology to transportation has been enabling researchers to make accurate travel time observations, in freeway and arterial roads. The Bluetooth traffic data are generally incomplete, for they only relate to those vehicles that are equipped with Bluetooth devices, and that are detected by the Bluetooth sensors of the road network. The fraction of detected vehicles versus the total number of transiting vehicles is often referred to as Bluetooth Penetration Rate (BTPR). The aim of this study is to precisely define the spatio-temporal relationship between the quantities that become available through the partial, noisy BT observations; and the hidden variables that describe the actual dynamics of vehicular traffic. To do so, we propose to incorporate a multi- class traffic model into a Sequential Montecarlo Estimation algorithm. Our framework has been applied for the empirical travel time investigations into the Brisbane Metropolitan region.

A state-wide systems approach to embedding the learning and teaching of sustainability in teacher education

Education systems have a key role to play in preparing future citizens to engage in sustainable living practices and help create a more sustainable world. Many schools throughout Australia have begun to develop whole-school approaches to sustainability education that are supported by national and state policies and curriculum frameworks. Preservice teacher education, however, lags behind in building the capacity of new teachers to initiate and implement such approaches (ARIES, 2010). This proposed project seeks to develop a state-wide systems approach to embedding Education for Sustainability (EfS) in teacher education that is aligned with the Australian National Curriculum and the aspirations for EfS in the Melbourne Declaration and other national documents. Representatives from all teacher education institutions and other agents of change in the Queensland education system will be engaged in a multilevel systems approach, involving collaboration at the state, institutional and course levels, to develop curriculum practices that reflect a shared vision of EfS.

The Current State of BPM Education in Australia : Teaching and Research Challenges

As business processes, services and relationships, are now recognized as key organizational assets, the demand for the so-called boundaryspanning roles and process-aware professionals is continuing to grow. The world-wide demand for these roles will continue to increase, fueled by the unprecedented interest in Business Process Management (BPM) and the other emerging cross-functional disciplines. This, in turn, creates new opportunities, as well as some unforeseeable challenges for BPM education, both in university and industry. This paper reports on an analysis of the current BPM offerings of Australian universities. It presents a critical review of what is taught and how it is taught, and identifies a series of gaps and concerns. Explanations and recommendations are proposed and a call made for BPM educators worldwide, for urgent action.

The construction of parents as learners about pre-school children’s development

The concept of the lifelong learner—the idea that people should be active learners throughout the lifespan—has since the 1990s gained importance in public policy. Governments in relatively wealthy countries have made the argument that the economic future of nations is tied to the ongoing participation of citizens in learning opportunities that will assist them to participate fully in society and increase their chances of employment in changing workforce conditions. More recently, policy attention has focused on the other end of the lifespan, the first years of life. With the early years now recognised as crucial for later educational success, policy attention has also focused on the importance of parenting in the early years. In the UK and Australia, for example, the effects of state interventions to facilitate ‘good parenting’ and pre-school children’s ‘readiness’ for formal schooling have been felt in a range of settings including community health services, the home and the pre-school (Gillies, 2005; Nichols & Jurvansuu, 2008; Millei & Lee, 2007; Vincent, Ball & Braun, 2010). In Australia, government policy has explicitly proposed a model of parenting as a learning process, and has urged people to cultivate their identities as learners in order to carry out their responsibilities as parents. In part the policy objectives have been to support parents to ensure that all children get a healthy and successful start to life...

Spiritual wisdom of Taoism in business : through the lens of interpretation realism in a Cisco end-to-end case study

This paper explores how the amalgamated wisdom of East and West can instigate a wisdombased renaissance of humanistic epistemology (Rooney & McKenna, 2005) to provide a platform of harmony in managing knowledge-worker productivity, one of the biggest management challenges of the 21st century (Drucker, 1999). The paper invites further discussions from the social and business research communities on the significance of "interpretation realism" technique in comprehending philosophies of Lao Tzu Confucius and Sun Tzu (Lao/Confucius/Sun] written in "Classical Chinese." This paper concludes with a call to build prudent, responsible practices in management which affects the daily lives of many (Rooney & McKenna, 2005) in today's knowledgebased economy. Interpretation Realism will be applied to an analysis of three Chinese classics of Lao/Confucius/Sun which have been embodied in the Chinese culture for over 2,500 years. Comprehending Lao/Confucius/Sun's philosophies is the first step towards understanding Classical Chinese culture. However, interpreting Chinese subtlety in language and the yin and yang circular synthesis in their mode of thinking is very different to understanding Western thought with its open communication and its linear, analytical pattern of Aristotelian/Platonic wisdom (Zuo, 2012). Furthermore, Eastern ways of communication are relatively indirect and mediatory in culture. Western ways of communication are relatively direct and litigious in culture (Goh, 2002). Furthermore, Lao/Confucius/Sun's philosophies are difficult to comprehend as there are four written Chinese formats and over 250 dialects: Pre-classical Chinese Classical Chinese Literary Chinese and modern Vernacular Chinese Because Classical Chinese is poetic, comprehension requires a mixed approach of interpretation realism combining logical reasoning behind "word splitting word occurrences", "empathetic metaphor" and "poetic appreciation of word.

Biocompatibility, SiH lenses and the impact of hydration on comfort

Silicone hydrogel (SiH) contact lenses have been available for over a decade. During that time, these highly innovative materials and designs have continually improved and now represent a major percentage of fits within the global contact lens market.1 Their high oxygen transmissibility has drastically reduced the incidence of hypoxia-related conditions such as corneal edema, limbal hyperaemia, and corneal vascularisation.2,3 However, there remain significant challenges in the quest for the ideal contact lens. The silicone material used in SiH contact lenses is inherently more hydrophobic than the non-silicone hydrogel materials. SiH lens manufacturers must find ways to overcome lens surface hydrophobicity since it can create issues in terms of lens wettability and surface deposition. Achieving ideal lens water content presents yet another challenge since increasing water content in a silicone hydrogel lens can reduce oxygen transmissibility. This is because increasing water content results in decreased silicone content in the lens and silicone is a better transmitter of oxygen than water.

Blast response and failure analysis of pile foundations subjected to surface explosion

This paper presents the response of pile foundations to ground shocks induced by surface explosion using fully coupled and non-linear dynamic computer simulation techniques together with different material models for the explosive, air, soil and pile. It uses the Arbitrary Lagrange Euler coupling formulation with proper state material parameters and equations. Blast wave propagation in soil, horizontal pile deformation and pile damage are presented to facilitate failure evaluation of piles. Effects of end restraint of pile head and the number and spacing of piles within a group on their blast response and potential failure are investigated. The techniques developed and applied in this paper and its findings provide valuable information on the blast response and failure evaluation of piles and will provide guidance in their future analysis and design.

Inhibition of homogenous formation of calcium carbonate by poly (acrylic acid). The effect of molar mass and end-group functionality

The ability of poly(acrylic acid) (PAA) with different end groups and molar masses prepared by Atom Transfer Radical Polymerization (ATRP) to inhibit the formation of calcium carbonate scale at low and elevated temperatures was investigated. Inhibition of CaCO3 deposition was affected by the hydrophobicity of the end groups of PAA, with the greatest inhibition seen for PAA with hydrophobic end groups of moderate size (6–10 carbons). The morphologies of CaCO3 crystals were significantly distorted in the presence of these PAAs. The smallest morphological change was in the presence of PAA with long hydrophobic end groups (16 carbons) and the relative inhibition observed for all species were in the same order at 30 °C and 100 °C. As well as distorting morphologies, the scale inhibitors appeared to stabilize the less thermodynamically favorable polymorph, vaterite, to a degree proportional to their ability to inhibit precipitation.

Multifunctional agriculture in policy and practice? A comparative analysis of Norway and Australia

Ideals of productivist agriculture in the Western world have faded as the unintended consequences of intensive agriculture and pastoralism have contributed to rural decline and environmental problems. In Norway and Australia, there has been an increasing acceptance of the equal importance of social and environmental sustainability as well as economic sustainability. Alongside this shift is a belief that primary production needs to move away from an intensive, productivist-based agriculture to one that may be defined as post-productivist. In this paper, we argue that the dualism of productivism and post-productivism as concepts on agricultural policy regimes are too simplistic and discuss whether multifunctional agriculture is a better concept for a comparison of rural primary production at two extreme points of the scale, the market-oriented, liberalistic Australian agriculture and the market-protected small-scale Norwegian agriculture. We argue that multifunctionality in Australia rates relatively weakly as an ideology or policy and even less as a discourse or practice and hence is situated toward a ‘weak’ end of a continuum of a level of multifunctional agriculture. In Norwegian agriculture, multifunctional agriculture has thrived within a protectionist setting with the support of the public, the state and agricultural actors. In this sense it is very clearly a policy, practice and discourse that aims to preserve and conserve rural spaces, the cultural landscape, the farming way of life and food safety. Norway is as such situated toward a ‘strong’ end of a continuum of a level of multifunctional agriculture.

State Estimation in Smart Power Grids

In this chapter, the role of State Estimation (SE) in smart power grids is presented. The trend of SE error with respect to the increasing of the smart grids implementation investigated. The observability analysis as a prior task of SE is demonstrated and an analytical method to consider the impedance values of the branches is developed and discussed by examples. Since most principles of smart power grids are appropriate to distribution networks, the Distribution SE (DSE)considering load correlation is argued and illustrated by an example. The main features of smart grid SE, which is here named as “Smart Distributed SE” (SDSE), are discussed. Some characteristics of proposed SDES are distributed, hybrid, multi-micro grid and islanding support, Harmonic State Estimation (HSE), observability analysis and restore, error processing, and network parameter estimation. Distribution HSE (DHSE) and meter placement for SDSE are also presented.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

A novel algorithm based on honey bee mating optimization for distribution harmonic state estimation including distributed generators

This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics by minimizing the error between the measured values from phasor measurement units (PMUs) and the values computed from the estimated parameters during the estimation process. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).

Distribution harmonic state estimation based on a hybrid PSO and SA algorithm considering parameters uncertainty

This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.

Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.