Strategies for comparing decimal numbers with the same whole-number part

The strategies employed by 130 Grade 5 Brisbane students in comparing decimal numbers which have the same whole-number part were compared with those identified in similar studies conducted in the USA, France and Israel. Three new strategies were identified. Similar to USA results, the most common comparison errors stemmed from the incorrect whole-number strategy in which length is confused with size. The findings of this present study tend to support Resnick et al.’s (1989) hypothesis that the introduction of decimal-fraction recording before common-fraction recording seems to promote better comparison of decimal numbers.

Adaptive dual control of topic-based information retrieval

Information Retrieval is an important albeit imperfect component of information technologies. A problem of insufficient diversity of retrieved documents is one of the primary issues studied in this research. This study shows that this problem leads to a decrease of precision and recall, traditional measures of information retrieval effectiveness. This thesis presents an adaptive IR system based on the theory of adaptive dual control. The aim of the approach is the optimization of retrieval precision after all feedback has been issued. This is done by increasing the diversity of retrieved documents. This study shows that the value of recall reflects this diversity. The Probability Ranking Principle is viewed in the literature as the “bedrock” of current probabilistic Information Retrieval theory. Neither the proposed approach nor other methods of diversification of retrieved documents from the literature conform to this principle. This study shows by counterexample that the Probability Ranking Principle does not in general lead to optimal precision in a search session with feedback (for which it may not have been designed but is actively used). Retrieval precision of the search session should be optimized with a multistage stochastic programming model to accomplish the aim. However, such models are computationally intractable. Therefore, approximate linear multistage stochastic programming models are derived in this study, where the multistage improvement of the probability distribution is modelled using the proposed feedback correctness method. The proposed optimization models are based on several assumptions, starting with the assumption that Information Retrieval is conducted in units of topics. The use of clusters is the primary reasons why a new method of probability estimation is proposed. The adaptive dual control of topic-based IR system was evaluated in a series of experiments conducted on the Reuters, Wikipedia and TREC collections of documents. The Wikipedia experiment revealed that the dual control feedback mechanism improves precision and S-recall when all the underlying assumptions are satisfied. In the TREC experiment, this feedback mechanism was compared to a state-of-the-art adaptive IR system based on BM-25 term weighting and the Rocchio relevance feedback algorithm. The baseline system exhibited better effectiveness than the cluster-based optimization model of ADTIR. The main reason for this was insufficient quality of the generated clusters in the TREC collection that violated the underlying assumption.

Whatever it takes : an exploration of writing tools and strategies for completing a novel

This thesis consists of a novel written with the express purpose of exploring what practices and strategies are most useful in writing novel-length fiction as well as an exegesis which discusses the process. By its very nature, an undergraduate degree in Creative Writing is broad and general in approach. The Creative Writing undergraduate is being trained to manage many and varying writing tasks but none of them larger than can be readily marked and assessed in class quantities. This does not prepare the writing graduate for the gargantuan task of managing a project as large as a single title novel which can be up to 100,000 words and often is more. This study explores the question of what writing tools and practices best equip an emerging writer to begin, write and manage a long narrative within a deadline.

Bushfire responsive architecture : strategies for reconciling bushfire and biodiversity with daily life

My perspective on the problems associated with building in bushfire prone landscapes comes from 12 years of study of the biophysical and cultural landscapes in the Great Southern Region of WA which resulted in the design and construction of the ‘Hhouse’ at Bremer Bay. The house was developed using a ‘ground up’ approach whereby I conducted a topographical survey and worked with a local botanist and a bushfire risk consultant to ascertain the level of threat that fire presented to this particular site. My intention from the outset however, was not to design a bushfire resistant house per se, but to develop a design which would place the owners in close proximity to the highly biodiverse heath vegetation of the site. I was also seeking a means—through architectural design—of linking the patterns of usage of the house with other site specific conditions related to the prevailing winds, solar orientation and seasonal change.

A multicast routing scheme for efficient safety message dissemination in VANET

Vehicular ad hoc network (VANET) is a wireless ad hoc network that operates in a vehicular environment to provide communication between vehicles. VANET can be used by a diverse range of applications to improve road safety. Cooperative collision warning system (CCWS) is one of the safety applications that can provide situational awareness and warning to drivers by exchanging safety messages between cooperative vehicles. Currently, the routing strategies for safety message dissemination in CCWS are scoped broadcast. However, the broadcast schemes are not efficient as a warning message is sent to a large number of vehicles in the area, rather than only the endangered vehicles. They also cannot prioritize the receivers based on their critical time to avoid collision. This paper presents a more efficient multicast routing scheme that can reduce unnecessary transmissions and also use adaptive transmission range. The multicast scheme involves methods to identify an abnormal vehicle, the vehicles that may be endangered by the abnormal vehicle, and the latest time for each endangered vehicle to receive the warning message in order to avoid the danger. We transform this multicast routing problem into a delay-constrained minimum Steiner tree problem. Therefore, we can use existing algorithms to solve the problem. The advantages of our multicast routing scheme are mainly its potential to support various road traffic scenarios, to optimize the wireless channel utilization, and to prioritize the receivers.

Property development cycle and acquisition strategies

This presenation is part of the UDIA (Qld) Property Development Essentials program, which is a two-day introductory course designed for new entrants to the property industry. The course provides practical advice and direction for those looking to take the first steps into the development industry. This presentation identifies economic factors and their influence on land acquisitions, as well as providing an understanding the property development and business cycles and their impacts on acquisition strategies (long v. short term projects)

Adaptive depth estimation in image based visual servo control of dynamic systems

This paper considers the question of designing a fully image based visual servo control for a dynamic system. The work is motivated by the ongoing development of image based visual servo control of small aerial robotic vehicles. The observed targets considered are coloured blobs on a flat surface to which the normal direction is known. The theoretical framework is directly applicable to the case of markings on a horizontal floor or landing field. The image features used are a first order spherical moment for position and an image flow measurement for velocity. A fully non-linear adaptive control design is provided that ensures global stability of the closed-loop system. © 2005 IEEE.

Biologically inspired joint control for a humanoid robot

The GuRoo is a 1.2 m tall, 23 degree of freedom humanoid constructed at the University of Queensland for research into humanoid robotics. The key challenge being addressed by the GuRoo project is the development of appropriate learning strategies for control and coordination of the robot's many joints. The development of learning strategies is seen as a way to side-step the inherent intricacy of modeling a multi-DOF biped robot. This paper outlines the approach taken to generate an appropriate control scheme for the joints of the GuRoo. The paper demonstrates the determination of local feedback control parameters using a genetic algorithm. The feedback loop is then augmented by a predictive modulator that learns a form of feed-forward control to overcome the irregular loads experienced at each joint during the gait cycle. The predictive modulator is based on the CMAC architecture. Results from tests on the GuRoo platform show that both systems provide improvements in stability and tracking of joint control.

Modeling and exploiting behavior patterns in dynamic environments

This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup).

Intergroup relations and Muslims’ mental health in Western societies

This review article proposes that theories and research of intergroup contact, prejudice, and acculturation, enhance understanding of the current intercultural relations between Muslims and non-Muslims in Western societies, such as in Australia. The actual and perceived prejudice that many Muslims studying, working, and living in the West have been experiencing following the 2001 terrorist attacks, adds an additional layer of stress to the psychosocial adjustment of Muslim immigrants and sojourners, affecting their cross-cultural adaptation and mental health. Stephan and colleagues’ Integrated Threat Theory argues that the perceived threat experienced by all parties, explains the acts of prejudice. Berry’s acculturation framework highlights that adaptive acculturation is determined by congruent host nation policies and practices and immigrant acculturation strategies. Implications for multicultural policy, intercultural training, and mental health practice, and suggestions for future research, are discussed.

Design optimisation using advanced artificial intelligent system coupled to hybrid-game strategies

One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.