PartSS : An efficient partition-based filtering for edit distance constraints

This paper introduces PartSS, a new partition-based fil- tering for tasks performing string comparisons under edit distance constraints. PartSS offers improvements over the state-of-the-art method NGPP with the implementation of a new partitioning scheme and also improves filtering abil- ities by exploiting theoretical results on shifting and scaling ranges, thus accelerating the rate of calculating edit distance between strings. PartSS filtering has been implemented within two major tasks of data integration: similarity join and approximate membership extraction under edit distance constraints. The evaluation on an extensive range of real-world datasets demonstrates major gain in efficiency over NGPP and QGrams approaches.

Bilingual asynchronous online discussion groups : design and delivery of an e-Learning distance study module for nurse academics in a developing country

The advent of eLearning has seen online discussion forums widely used in both undergraduate and postgraduate nursing education. This paper reports an Australian university experience of design, delivery and redevelopment of a distance education module developed for Vietnamese nurse academics. The teaching experience of Vietnamese nurse academics is mixed and frequently limited. It was decided that the distance module should attempt to utilise the experience of senior Vietnamese nurse academics - asynchronous online discussion groups were used to facilitate this. Online discussion occurred in both Vietnamese and English and was moderated by an Australian academic working alongside a Vietnamese translator. This paper will discuss the design of an online learning environment for foreign correspondents, the resources and translation required to maximise the success of asynchronous online discussion groups, as well as the rationale of delivering complex content in a foreign language. While specifically addressing the first iteration of the first distance module designed, this paper will also address subsequent changes made for the second iteration of the module and comment on their success. While a translator is clearly a key component of success, the elements of simplicity and clarity combined with supportive online moderation must not be overlooked.

Design and delivery of a distance education programme : educating Vietnamese nurse academics from Australia

In 2008 a move away from medical staff providing nursing education in Vietnam saw the employment of many new nurse academics. To assist in the instruction of these novice academics and provide them with sound teaching and learning practice as well as curriculum design and implementation skills, Queensland University of Technology (QUT) successfully tendered an international grant. One of QUT’s initiatives in educating the Vietnamese academics was a distance learning programme. Developed specifically for Vietnamese nurse academics, the programme was designed for Australian based delivery to academics in Vietnam. This paper will present an overview of why four separate modules were utilised for the delivery of content (modules were delivered at a rate of one per semester). It will address bilingual online discussion boards which were used in each of the modules and the process of moderating these given comments were posted in both Vietnamese and English. It will describe how content was scaffolded across four modules and how the modules themselves modelled new teaching delivery strategies. Lastly, it will discuss the considerations of programme delivery given the logistics of an Australian based delivery. Feedback from the Vietnamese nurse academics across their involvement in the programme (and at the conclusion of their fourth and final module) has been overwhelmingly positive. Feedback suggests the programme has altered teaching and assessment approaches used by some Vietnamese nurse academics. Additionally, Vietnamese nurse academics are reporting that they are engaging more with the application of their content indicating a cultural shift in the approach taken in Vietnamese nurse education.

Kernel analysis on Grassmann manifolds for action recognition

Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

Graph-based concept weighting for medical information retrieval

This paper presents a graph-based method to weight medical concepts in documents for the purposes of information retrieval. Medical concepts are extracted from free-text documents using a state-of-the-art technique that maps n-grams to concepts from the SNOMED CT medical ontology. In our graph-based concept representation, concepts are vertices in a graph built from a document, edges represent associations between concepts. This representation naturally captures dependencies between concepts, an important requirement for interpreting medical text, and a feature lacking in bag-of-words representations. We apply existing graph-based term weighting methods to weight medical concepts. Using concepts rather than terms addresses vocabulary mismatch as well as encapsulates terms belonging to a single medical entity into a single concept. In addition, we further extend previous graph-based approaches by injecting domain knowledge that estimates the importance of a concept within the global medical domain. Retrieval experiments on the TREC Medical Records collection show our method outperforms both term and concept baselines. More generally, this work provides a means of integrating background knowledge contained in medical ontologies into data-driven information retrieval approaches.

Towards persistent indoor appearance-based localization, mapping and navigation using CAT-Graph

The challenge of persistent appearance-based navigation and mapping is to develop an autonomous robotic vision system that can simultaneously localize, map and navigate over the lifetime of the robot. However, the computation time and memory requirements of current appearance-based methods typically scale not only with the size of the environment but also with the operation time of the platform; also, repeated revisits to locations will develop multiple competing representations which reduce recall performance. In this paper we present a solution to the persistent localization, mapping and global path planning problem in the context of a delivery robot in an office environment over a one-week period. Using a graphical appearance-based SLAM algorithm, CAT-Graph, we demonstrate constant time and memory loop closure detection with minimal degradation during repeated revisits to locations, along with topological path planning that improves over time without using a global metric representation. We compare the localization performance of CAT-Graph to openFABMAP, an appearance-only SLAM algorithm, and the path planning performance to occupancy-grid based metric SLAM. We discuss the limitations of the algorithm with regard to environment change over time and illustrate how the topological graph representation can be coupled with local movement behaviors for persistent autonomous robot navigation.

Expander graph based key distribution mechanisms in wireless sensor networks

Secure communications between large number of sensor nodes that are randomly scattered over a hostile territory, necessitate efficient key distribution schemes. However, due to limited resources at sensor nodes such schemes cannot be based on post deployment computations. Instead, pairwise (symmetric) keys are required to be pre-distributed by assigning a list of keys, (a.k.a. key-chain), to each sensor node. If a pair of nodes does not have a common key after deployment then they must find a key-path with secured links. The objective is to minimize the keychain size while (i) maximizing pairwise key sharing probability and resilience, and (ii) minimizing average key-path length. This paper presents a deterministic key distribution scheme based on Expander Graphs. It shows how to map the parameters (e.g., degree, expansion, and diameter) of a Ramanujan Expander Graph to the desired properties of a key distribution scheme for a physical network topology.

CAT-GRAPH+ : towards odometry-driven place consolidation in changing environments

Changing environments present a number of challenges to mobile robots, one of the most significant being mapping and localisation. This problem is particularly significant in vision-based systems where illumination and weather changes can cause feature-based techniques to fail. In many applications only sections of an environment undergo extreme perceptual change. Some range-based sensor mapping approaches exploit this property by combining occasional place recognition with the assumption that odometry is accurate over short periods of time. In this paper, we develop this idea in the visual domain, by using occasional vision-driven loop closures to infer loop closures in nearby locations where visual recognition is difficult due to extreme change. We demonstrate successful map creation in an environment in which change is significant but constrained to one area, where both the vanilla CAT-Graph and a Sum of Absolute Differences matcher fails, use the described techniques to link dissimilar images from matching locations, and test the robustness of the system against false inferences.

Analyzing the effectiveness of graph metrics for anomaly detection in online social networks

Online social networks can be modelled as graphs; in this paper, we analyze the use of graph metrics for identifying users with anomalous relationships to other users. A framework is proposed for analyzing the effectiveness of various graph theoretic properties such as the number of neighbouring nodes and edges, betweenness centrality, and community cohesiveness in detecting anomalous users. Experimental results on real-world data collected from online social networks show that the majority of users typically have friends who are friends themselves, whereas anomalous users’ graphs typically do not follow this common rule. Empirical analysis also shows that the relationship between average betweenness centrality and edges identifies anomalies more accurately than other approaches.

Rapid, long-distance dispersal by pumice rafting

Pumice is an extremely effective rafting agent that can dramatically increase the dispersal range of a variety of marine organisms and connect isolated shallow marine and coastal ecosystems. Here we report on a significant recent pumice rafting and long-distance dispersal event that occurred across the southwest Pacific following the 2006 explosive eruption of Home Reef Volcano in Tonga. We have constrained the trajectory, and rate, biomass and biodiversity of transfer, discovering more than 80 species and a substantial biomass underwent a .5000 km journey in 7–8 months. Differing microenvironmental conditions on the pumice, caused by relative stability of clasts at the sea surface, promoted diversity in biotic recruitment. Our findings emphasise pumice rafting as an important process facilitating the distribution of marine life, which have implications for colonisation processes and success, the management of sensitive marine environments, and invasive pest species.

Data requirements and graph data structures for a multi-modal, multi-objective trip planner

Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.

Enlarged stopping distance to improve vehicle discharge at urban signalised intersections

Normally, vehicles queued at an intersection reach maximum flow rate after the fourth vehicle and results in a start-up lost time. This research demonstrated that the Enlarged Stopping Distance (ESD) concept could assist in reducing the start-up time and therefore increase traffic flow capacity at signalised intersections. In essence ESD gives sufficient space for a queuing vehicle to accelerate simultaneously without having to wait for the front vehicle to depart, hence reducing start-up lost time. In practice, the ESD concept would be most effective when enlarged stopping distance between the first and second vehicle allowing faster clearance of the intersection.

A distance too far away : a novel and exegesis

This practice-led research examines the generative function of loss in fiction that explores themes of grief and longing. This research considers how loss may be understood as a structuring mechanism through which characters evaluate time, resolve loss and affect future change. The creative work is a work of literary fiction titled A Distance Too Far Away. Aubrey, the story’s protagonist, is a woman in her twenties living in Brisbane in the early 1980s, carving out an independent life for herself away from her family. Through a flashback narrative sequence, told from the perspective of the twelve year narrator, Aubrey retraces a significant point of rupture in her life following a series of family tragedies. A Distance Too Far Away explores the tension between belonging and freedom, and considers how the past provides a malleable space for illuminating desire in order to traverse the gap between the world as it is and the world as we want it to be. The exegetical component of this research considers an alternative critical frame for interpreting the work of American author Anne Tyler, a writer who has had a significant influence on my own practice. Frequently criticised for creating sentimental and inert characters, many critics observe that nothing happens in Tyler’s circular plots. This research challenges these assertions, and through a contextual analysis of Tyler’s Ladder of Years (1995) investigates how Tyler engages with memory and nostalgia in order to move across time and resolve loss.