Toward a fuzzy domain ontology extraction method for adaptive e-learning

With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.

Use of Probe Vehicles to Increase Traffic Estimation Accuracy in Brisbane

Traffic congestion is an increasing problem with high costs in financial, social and personal terms. These costs include psychological and physiological stress, aggressivity and fatigue caused by lengthy delays, and increased likelihood of road crashes. Reliable and accurate traffic information is essential for the development of traffic control and management strategies. Traffic information is mostly gathered from in-road vehicle detectors such as induction loops. Traffic Message Chanel (TMC) service is popular service which wirelessly send traffic information to drivers. Traffic probes have been used in many cities to increase traffic information accuracy. A simulation to estimate the number of probe vehicles required to increase the accuracy of traffic information in Brisbane is proposed. A meso level traffic simulator has been developed to facilitate the identification of the optimal number of probe vehicles required to achieve an acceptable level of traffic reporting accuracy. Our approach to determine the optimal number of probe vehicles required to meet quality of service requirements, is to simulate runs with varying numbers of traffic probes. The simulated traffic represents Brisbane’s typical morning traffic. The road maps used in simulation are Brisbane’s TMC maps complete with speed limits and traffic lights. Experimental results show that that the optimal number of probe vehicles required for providing a useful supplement to TMC (induction loop) data lies between 0.5% and 2.5% of vehicles on the road. With less probes than 0.25%, little additional information is provided, while for more probes than 5%, there is only a negligible affect on accuracy for increasingly many probes on the road. Our findings are consistent with on-going research work on traffic probes, and show the effectiveness of using probe vehicles to supplement induction loops for accurate and timely traffic information.

A distributed knowledge management infrastructure based on a Topic Map grid

Modern enterprise knowledge management systems typically require distributed approaches and the integration of numerous heterogeneous sources of information. A powerful foundation for these tasks can be Topic Maps, which not only provide a semantic net-like knowledge representation means and the possibility to use ontologies for modelling knowledge structures, but also offer concepts to link these knowledge structures with unstructured data stored in files, external documents etc. In this paper, we present the architecture and prototypical implementation of a Topic Map application infrastructure, the ‘Topic Grid’, which enables transparent, node-spanning access to different Topic Maps distributed in a network.

Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

Conveying identity with mobile content

A series of mobile phone prototypes called The Swarm have been developed in response to the user needs identified in a three-year empirical study of young people’s use of mobile phones. The prototypes take cues from user led innovation and provide multiple avatars that allow individuals to define and manage their own virtual identity. This paper briefly maps the evolution of the prototypes and then describes how the pre-defined, color coded avatars in the latest version are being given greater context and personalization through the use of digital images. This not only gives ‘serendipity a nudge’ by allowing groups to come together more easily, it provides contextual information that can reduce gratuitous contact.

The strategic mindset of Australian manufacturing managers : some missing links

Manufacturing managers have a measurable mindset (or frame) that structures their response to the manufacturing environment. Most importantly, this frame represents a set of assumptions about the relative prominence of concepts in the manufacturing domains, about the nature of people, and about the sensemaking processes required to understand the nature of the manufacturing environment as seen through the eyes of manufacturing managers. This paper uses work in the area of text analysis and extends the scope of a methodology that has been approached from two different directions by Carley ( Journal of Organizational Behavior , 18 (51), 533-558, 1997) and Gephart ( Journal of Organizational Behavior , 18 (51), 583-622, 1997). This methodology is termed collocate analysis. Based on the analysis of transcripts of interviews of Australian manufacturing managers mind maps of the concepts used by these managers have been constructed. From an analysis of these mind maps it is argued that strategy plays a minor role in their thinking second only to the improvement domain, whereas design and related concepts play a dominant role in their day-to-day thinking.

Vision-based topological mapping and localisation

Competent navigation in an environment is a major requirement for an autonomous mobile robot to accomplish its mission. Nowadays, many successful systems for navigating a mobile robot use an internal map which represents the environment in a detailed geometric manner. However, building, maintaining and using such environment maps for navigation is difficult because of perceptual aliasing and measurement noise. Moreover, geometric maps require the processing of huge amounts of data which is computationally expensive. This thesis addresses the problem of vision-based topological mapping and localisation for mobile robot navigation. Topological maps are concise and graphical representations of environments that are scalable and amenable to symbolic manipulation. Thus, they are well-suited for basic robot navigation applications, and also provide a representational basis for the procedural and semantic information needed for higher-level robotic tasks. In order to make vision-based topological navigation suitable for inexpensive mobile robots for the mass market we propose to characterise key places of the environment based on their visual appearance through colour histograms. The approach for representing places using visual appearance is based on the fact that colour histograms change slowly as the field of vision sweeps the scene when a robot moves through an environment. Hence, a place represents a region of the environment rather than a single position. We demonstrate in experiments using an indoor data set, that a topological map in which places are characterised using visual appearance augmented with metric clues provides sufficient information to perform continuous metric localisation which is robust to the kidnapped robot problem. Many topological mapping methods build a topological map by clustering visual observations to places. However, due to perceptual aliasing observations from different places may be mapped to the same place representative in the topological map. A main contribution of this thesis is a novel approach for dealing with the perceptual aliasing problem in topological mapping. We propose to incorporate neighbourhood relations for disambiguating places which otherwise are indistinguishable. We present a constraint based stochastic local search method which integrates the approach for place disambiguation in order to induce a topological map. Experiments show that the proposed method is capable of mapping environments with a high degree of perceptual aliasing, and that a small map is found quickly. Moreover, the method of using neighbourhood information for place disambiguation is integrated into a framework for topological off-line simultaneous localisation and mapping which does not require an initial categorisation of visual observations. Experiments on an indoor data set demonstrate the suitability of our method to reliably localise the robot while building a topological map.

Windscape

Windscape is a graphic work produced from information gathered in the field by the author. A number of measurement methods were employed including: Real Tine Kinematic Global Positioning System survey (RTKGPS), still photography, plant distribution studies and handheld GPS survey. This creative work is one outcome of the author’s research into a design methodology wherein the designer conducts their own measurements and then produces their own maps of sites. Windscape is a test of the hypothesis that such maps have greater relevance to the design process due to the manner in which they are created (site based research) and the information they depict, namely the relationships between landscape processes and structures.

Horizonal

Horizonal was derived from terrestrial laser scan data of a bio-diverse landscape on the SE coast of Western Australia. The digital three dimensional scan data has been converged with geospatial survey of the landform captured through RTKGPS survey technology. Also incorporated into the image is a series of photographs taken using a photogrammetric technique wherein the position and view angle of each photograph is measured relative to a geographic datum point. The primary intention behind the production of the work was to expand understandings on the relationship between scenic photography and geospatial maps of remote, bio-diverse landscapes which are experiencing urban development for the first time.

`Getting the city right' : the city as crucible for social reform

The connection between social reform and urban management is evident throughout the history of the city. This article maps out how ideas about social reform and social housing were established historically, during the development of the nineteenth century city. The second part examines contemporary shifts in thinking about homelessness through a case study of two Brisbane City Council initiatives in Brisbane: The Homeless Shelter Trial and Footprints along Kurilpa.

Performing composition : developing a computer assisted composition system through live coding performance

This thesis maps the author's journey from a music composition practice to a composition and performance practice. The work involves the development of a software library for the purpose of encapsulating compositional ideas in software, and realising these ideas in performance through a live coding computer music practice. The thesis examines what artistic practice emerges through live coding and software development, and does this permit a blurring between the activities of music composition and performance. The role that software design plays in affecting musical outcomes is considered to gain an insight into how software development contributes to artistic development. The relationship between music composition and performance is also examined to identify the means by which engaging in live coding and software development can bring these activities together. The thesis, situated within the discourse of practice led research, documents a journey which uses the experience of software development and performance as a means to guide the direction of the research. The journey serves as an experiment for the author in engaging an hitherto unfamiliar musical practice, and as a roadmap for others seeking to modify or broaden their artistic practice.

Assessing the impact of floods and flood legislation on residential property prices

The changing development and population sprawl in major cities, especially those located in high rainfall areas, has resulted in the need to review and re-assess potential flood impacts in these cities. In many cases these new flood lines and flood maps have placed residential property that was previously considered to be flood free to now be considered to be potentially flood liable. Previous research based in Sydney and the UK has identified the fact that residential property that has been subject to flooding has a decreased price and higher investment risk than flood free property in the same location. These studies have also shown that the greatest impact on residential property subject to flooding is just following a flood event. In June 2009, Brisbane City Council released revised flood maps for the Greater Brisbane region and these maps have identified areas that have not previously been considered flood liable. This paper will analyse the sale performance of flood liable streets in the main flood areas of Brisbane over the period January 1990 through to June 2009, to determine the variation in price for these flood liable areas to the residential property immediately adjoining them. The average sale price will be tracked on both a geographic location and socio-economic basis.

Spatial cognition for robots

The paper discusses robot navigation from biological inspiration. The authors sought to build a model of the rodent brain that is suitable for practical robot navigation. The core model, dubbed RatSLAM, has been demonstrated to have exactly the same advantages described earlier: it can build, maintain, and use maps simultaneously over extended periods of time and can construct maps of large and complex areas from very weak geometric information. The work contrasts with other efforts to embody models of rat brains in robots. The article describes the key elements of the known biology of the rat brain in relation to navigation and how the RatSLAM model captures the ideas from biology in a fashion suitable for implementation on a robotic platform. The paper then outline RatSLAM's performance in two difficult robot navigation challenges, demonstrating how a cognitive robotics approach to navigation can produce results that rival other state of the art approaches in robotics.

Persistent navigation and mapping using a biologically inspired SLAM system

The challenge of persistent navigation and mapping is to develop an autonomous robot system that can simultaneously localize, map and navigate over the lifetime of the robot with little or no human intervention. Most solutions to the simultaneous localization and mapping (SLAM) problem aim to produce highly accurate maps of areas that are assumed to be static. In contrast, solutions for persistent navigation and mapping must produce reliable goal-directed navigation outcomes in an environment that is assumed to be in constant flux. We investigate the persistent navigation and mapping problem in the context of an autonomous robot that performs mock deliveries in a working office environment over a two-week period. The solution was based on the biologically inspired visual SLAM system, RatSLAM. RatSLAM performed SLAM continuously while interacting with global and local navigation systems, and a task selection module that selected between exploration, delivery, and recharging modes. The robot performed 1,143 delivery tasks to 11 different locations with only one delivery failure (from which it recovered), traveled a total distance of more than 40 km over 37 hours of active operation, and recharged autonomously a total of 23 times.

Classifying an opponent’s behaviour in robot soccer

This paper illustrates the prediction of opponent behaviour in a competitive, highly dynamic, multi-agent and partially observable environment, namely RoboCup small size league robot soccer. The performance is illustrated in the context of the highly successful robot soccer team, the RoboRoos. The project is broken into three tasks; classification of behaviours, modelling and prediction of behaviours and integration of the predictions into the existing planning system. A probabilistic approach is taken to dealing with the uncertainty in the observations and with representing the uncertainty in the prediction of the behaviours. Results are shown for a classification system using a Naïve Bayesian Network that determines the opponent’s current behaviour. These results are compared to an expert designed fuzzy behaviour classification system. The paper illustrates how the modelling system will use the information from behaviour classification to produce probability distributions that model the manner with which the opponents perform their behaviours. These probability distributions are show to match well with the existing multi-agent planning system (MAPS) that forms the core of the RoboRoos system.