Extending the task of diarization to speaker attribution

In this paper we extend the concept of speaker annotation within a single-recording, or speaker diarization, to a collection wide approach we call speaker attribution. Accordingly, speaker attribution is the task of clustering expectantly homogenous intersession clusters obtained using diarization according to common cross-recording identities. The result of attribution is a collection of spoken audio across multiple recordings attributed to speaker identities. In this paper, an attribution system is proposed using mean-only MAP adaptation of a combined-gender UBM to model clusters from a perfect diarization system, as well as a JFA-based system with session variability compensation. The normalized cross-likelihood ratio is calculated for each pair of clusters to construct an attribution matrix and the complete linkage algorithm is employed to conduct clustering of the inter-session clusters. A matched cluster purity and coverage of 87.1% was obtained on the NIST 2008 SRE corpus.

Manipulating task constraints to improve tactical knowledge and collective decision-making in rugby union

In team sports such as rugby union, a myriad of decisions and actions occur within the boundaries that compose the performance perceptual- motor workspace. The way that these performance boundaries constrain decision making and action has recently interested researchers and has involved developing an understanding of the concept of constraints. Considering team sports as complex dynamical systems, signifies that they are composed of multiple, independent agents (i.e. individual players) whose interactions are highly integrated. This level of complexity is characterized by the multiple ways that players in a rugby field can interact. It affords the emergence of rich patterns of behaviour, such as rucks, mauls, and collective tactical actions that emerge due to players’ adjustments to dynamically varying competition environments. During performance, the decisions and actions of each player are constrained by multiple causes (e.g. technical and tactical skills, emotional states, plans, thoughts, etc.) that generate multiple effects (e.g. to run or pass, to move forward to tackle or maintain position and drive the opponent to the line), a prime feature in a complex systems approach to team games performance (Bar- Yam, 2004). To establish a bridge between the complexity sciences and learning design in team sports like rugby union, the aim of practice sessions is to prepare players to pick up and explore the information available in the multiple constraints (i.e. the causes) that influence performance. Therefore, learning design in training sessions should be soundly based on the interactions amongst players (i.e.teammates and opponents) that will occur in rugby matches. To improve individual and collective decision making in rugby union, Passos and colleagues proposed in previous work a performer- environment interaction- based approach rather than a traditional performer- based approach (Passos, Araújo, Davids & Shuttleworth, 2008).

Path planning, guidance and control for a UAV forced landing

A forced landing is an unscheduled event in flight requiring an emergency landing, and is most commonly attributed to engine failure, failure of avionics or adverse weather. Since the ability to conduct a successful forced landing is the primary indicator for safety in the aviation industry, automating this capability for unmanned aerial vehicles (UAVs) will help facilitate their integration into, and subsequent routine operations over civilian airspace. Currently, there is no commercial system available to perform this task; however, a team at the Australian Research Centre for Aerospace Automation (ARCAA) is working towards developing such an automated forced landing system. This system, codenamed Flight Guardian, will operate onboard the aircraft and use machine vision for site identification, artificial intelligence for data assessment and evaluation, and path planning, guidance and control techniques to actualize the landing. This thesis focuses on research specific to the third category, and presents the design, testing and evaluation of a Trajectory Generation and Guidance System (TGGS) that navigates the aircraft to land at a chosen site, following an engine failure. Firstly, two algorithms are developed that adapts manned aircraft forced landing techniques to suit the UAV planning problem. Algorithm 1 allows the UAV to select a route (from a library) based on a fixed glide range and the ambient wind conditions, while Algorithm 2 uses a series of adjustable waypoints to cater for changing winds. A comparison of both algorithms in over 200 simulated forced landings found that using Algorithm 2, twice as many landings were within the designated area, with an average lateral miss distance of 200 m at the aimpoint. These results present a baseline for further refinements to the planning algorithms. A significant contribution is seen in the design of the 3-D Dubins Curves planning algorithm, which extends the elementary concepts underlying 2-D Dubins paths to account for powerless flight in three dimensions. This has also resulted in the development of new methods in testing for path traversability, in losing excess altitude, and in the actual path formation to ensure aircraft stability. Simulations using this algorithm have demonstrated lateral and vertical miss distances of under 20 m at the approach point, in wind speeds of up to 9 m/s. This is greater than a tenfold improvement on Algorithm 2 and emulates the performance of manned, powered aircraft. The lateral guidance algorithm originally developed by Park, Deyst, and How (2007) is enhanced to include wind information in the guidance logic. A simple assumption is also made that reduces the complexity of the algorithm in following a circular path, yet without sacrificing performance. Finally, a specific method of supplying the correct turning direction is also used. Simulations have shown that this new algorithm, named the Enhanced Nonlinear Guidance (ENG) algorithm, performs much better in changing winds, with cross-track errors at the approach point within 2 m, compared to over 10 m using Park's algorithm. A fourth contribution is made in designing the Flight Path Following Guidance (FPFG) algorithm, which uses path angle calculations and the MacCready theory to determine the optimal speed to fly in winds. This algorithm also uses proportional integral- derivative (PID) gain schedules to finely tune the tracking accuracies, and has demonstrated in simulation vertical miss distances of under 2 m in changing winds. A fifth contribution is made in designing the Modified Proportional Navigation (MPN) algorithm, which uses principles from proportional navigation and the ENG algorithm, as well as methods specifically its own, to calculate the required pitch to fly. This algorithm is robust to wind changes, and is easily adaptable to any aircraft type. Tracking accuracies obtained with this algorithm are also comparable to those obtained using the FPFG algorithm. For all three preceding guidance algorithms, a novel method utilising the geometric and time relationship between aircraft and path is also employed to ensure that the aircraft is still able to track the desired path to completion in strong winds, while remaining stabilised. Finally, a derived contribution is made in modifying the 3-D Dubins Curves algorithm to suit helicopter flight dynamics. This modification allows a helicopter to autonomously track both stationary and moving targets in flight, and is highly advantageous for applications such as traffic surveillance, police pursuit, security or payload delivery. Each of these achievements serves to enhance the on-board autonomy and safety of a UAV, which in turn will help facilitate the integration of UAVs into civilian airspace for a wider appreciation of the good that they can provide. The automated UAV forced landing planning and guidance strategies presented in this thesis will allow the progression of this technology from the design and developmental stages, through to a prototype system that can demonstrate its effectiveness to the UAV research and operations community.

Dietary modification for women after breast cancer treatment : a narrative review

Diet is thought to account for about 25% of cancers in developed countries. It is well documented that the risks associated with both the breast cancer itself and its treatments are important for women previously treated for breast cancer. Women are at risk of recurrence of the primary disease and prone to develop treatment-induced co-morbidities, some of which are thought to be modified by diet. With a view to making dietary recommendations for the breast cancer patients we encounter in our clinical nursing research, we mined the literature to scope the most current robust evidence concerning the role of the diet in protecting women against the recurrence of breast cancer and its potential to ameliorate some of the longer-term morbidities associated with the disease. We found that the evidence about the role of the diet in breast cancer recurrence is largely inconclusive. However, drawing on international guidelines enabled us to make three definitive recommendations. Women at risk of breast cancer recurrence, or who experience co-morbidities as a result of treatment, should limit their exposure to alcohol, moderate their nutritional intake so it does not contribute to postmenopausal weight gain, and should adhere to a balanced diet. Nursing education planned for breast cancer patients about dietary issues should ideally be individually tailored, based on a good understanding of the international recommendations and the evidence underpinning them

Emergent task-specific object semantics through distributed experience networks

Autonomous development of sensorimotor coordination enables a robot to adapt and change its action choices to interact with the world throughout its lifetime. The Experience Network is a structure that rapidly learns coordination between visual and haptic inputs and motor action. This paper presents methods which handle the high dimensionality of the network state-space which occurs due to the simultaneous detection of multiple sensory features. The methods provide no significant increase in the complexity of the underlying representations and also allow emergent, task-specific, semantic information to inform action selection. Experimental results show rapid learning in a real robot, beginning with no sensorimotor mappings, to a mobile robot capable of wall avoidance and target acquisition.

The relationship between parents’ self-efficacy beliefs, outcome expectations, child behaviour, and management of atopic dermatitis

Atopic dermatitis (AD) is a chronic inflammatory skin condition, characterized by intense pruritis, with a complex aetiology comprising multiple genetic and environmental factors. It is a common chronic health problem among children, and along with other allergic conditions, is increasing in prevalence within Australia and in many countries worldwide. Successful management of childhood AD poses a significant and ongoing challenge to parents of affected children. Episodic and unpredictable, AD can have profound effects on children’s physical and psychosocial wellbeing and quality of life, and that of their caregivers and families. Where concurrent child behavioural problems and parenting difficulties exist, parents may have particular difficulty achieving adequate and consistent performance of the routine management tasks that promote the child’s health and wellbeing. Despite frequent reports of behaviour problems in children with AD, past research has neglected the importance of child behaviour to parenting confidence and competence with treatment. Parents of children with AD are also at risk of experiencing depression, anxiety, parenting stress, and parenting difficulties. Although these factors have been associated with difficulty in managing other childhood chronic health conditions, the nature of these relationships in the context of child AD management has not been reported. This study therefore examined relationships between child, parent, and family variables, and parents’ management of child AD and difficult child behaviour, using social cognitive and self-efficacy theory as a guiding framework. The study was conducted in three phases. It employed a quantitative, cross-sectional study design, accessing a community sample of 120 parents of children with AD, and a sample of 64 child-parent dyads recruited from a metropolitan paediatric tertiary referral centre. In Phase One, instruments designed to measure parents’ self-reported performance of AD management tasks (Parents’ Eczema Management Scale – PEMS) and parents’ outcome expectations of task performance (Parents’ Outcome Expectations of Eczema Management Scale – POEEMS) were adapted from the Parental Self-Efficacy with Eczema Care Index (PASECI). In Phase Two, these instruments were used to examine relationships between child, parent, and family variables, and parents’ self-efficacy, outcome expectations, and self-reported performance of AD management tasks. Relationships between child, parent, and family variables, parents’ self-efficacy for managing problem behaviours, and reported parenting practices, were also examined. This latter focus was explored further in Phase Three, in which relationships between observed child and parent behaviour, and parent-reported self-efficacy for managing both child AD and problem behaviours, were explored. Phase One demonstrated the reliability of both PEMS and POEEMS, and confirmed that PASECI was reliable and valid with modification as detailed. Factor analyses revealed two-factor structures for PEMS and PASECI alike, with both scales containing factors related to performing routine management tasks, and managing the child’s symptoms and behaviour. Factor analysis was also applied to POEEMS resulting in a three-factor structure. Factors relating to independent management of AD by the parent, involving healthcare professionals in management, and involving the child in management of AD were found. Parents’ self-efficacy and outcome expectations had a significant influence on self-reported task performance. In Phase Two, relationships emerged between parents’ self-efficacy and self-reported performance of AD management tasks, and AD severity, child behaviour difficulties, parent depression and stress, conflict over parenting issues, and parents’ relationship satisfaction. Using multiple linear regressions, significant proportions of variation in parents’ self-efficacy and self-reported performance of AD management tasks were explained by child behaviour difficulties and parents’ formal education, and self-efficacy emerged as a likely mediator for the relationships between both child behaviour and parents’ education, and performance of AD management tasks. Relationships were also found between parents’ self-efficacy for managing difficult child behaviour and use of dysfunctional parenting strategies, and child behaviour difficulties, parents’ depression and stress, conflict over parenting issues, and relationship satisfaction. While significant proportions of variation in self-efficacy for managing child behaviour were explained by both child behaviour and family income, family income was the only variable to explain a significant proportion of variation in parent-reported use of dysfunctional parenting strategies. Greater use of dysfunctional parenting strategies (both lax and authoritarian parenting) was associated with more severe AD. Parents reporting lower self-efficacy for managing AD also reported lower self-efficacy for managing difficult child behaviour; likewise, less successful self-reported performance of AD management tasks was associated with greater use of dysfunctional parenting strategies. When child and parent behaviour was directly observed in Phase Three, more aversive child behaviour was associated with lower self-efficacy, less positive outcome expectations, and poorer self-reported performance of AD management tasks by parents. Importantly, there were strong positive relationships between these variables (self-efficacy, outcome expectations, and self-reported task performance) and parents’ observed competence when providing treatment to their child. Less competent performance was also associated with greater parent-reported child behaviour difficulties, parent depression and stress, parenting conflict, and relationship dissatisfaction. Overall, this study revealed the importance of child behaviour to parents’ confidence and practices in the contexts of child AD and child behaviour management. Parents of children with concurrent AD and behavioural problems are at particular risk of having low self-efficacy for managing their child’s AD and difficult behaviour. Children with more severe AD are also at higher risk of behaviour problems, and thus represent a high-risk group of children whose parents may struggle to manage the disease successfully. As one of the first studies to examine the role and correlates of parents’ self-efficacy in child AD management, this study identified a number of potentially modifiable factors that can be targeted to enhance parents’ self-efficacy, and improve parent management of child AD. In particular, interventions should focus on child behaviour and parenting issues to support parents caring for children with AD and improve child health outcomes. In future, findings from this research will assist healthcare teams to identify parents most in need of support and intervention, and inform the development and testing of targeted multidisciplinary strategies to support parents caring for children with AD.

A Regularization Approach to Metrical Task Systems

We address the problem of constructing randomized online algorithms for the Metrical Task Systems (MTS) problem on a metric δ against an oblivious adversary. Restricting our attention to the class of “work-based” algorithms, we provide a framework for designing algorithms that uses the technique of regularization. For the case when δ is a uniform metric, we exhibit two algorithms that arise from this framework, and we prove a bound on the competitive ratio of each. We show that the second of these algorithms is ln n + O(loglogn) competitive, which is the current state-of-the art for the uniform MTS problem.

A task-oriented approach to search engine usability studies

Usability is a multi-dimensional characteristic of a computer system. This paper focuses on usability as a measurement of interaction between the user and the system. The research employs a task-oriented approach to evaluate the usability of a meta search engine. This engine encourages and accepts queries of unlimited size expressed in natural language. A variety of conventional metrics developed by academic and industrial research, including ISO standards,, are applied to the information retrieval process consisting of sequential tasks. Tasks range from formulating (long) queries to interpreting and retaining search results. Results of the evaluation and analysis of the operation log indicate that obtaining advanced search engine results can be accomplished simultaneously with enhancing the usability of the interactive process. In conclusion, we discuss implications for interactive information retrieval system design and directions for future usability research. © 2008 Academy Publisher.

Effect of topic domain and task type on Web image searching

Many user studies in Web information searching have found the significant effect of task types on search strategies. However, little attention was given to Web image searching strategies, especially the query reformulation activity despite that this is a crucial part in Web image searching. In this study, we investigated the effects of topic domains and task types on user’s image searching behavior and query reformulation strategies. Some significant differences in user’s tasks specificity and initial concepts were identified among the task domains. Task types are also found to influence participant’s result reviewing behavior and query reformulation strategies.

Overview of the NTCIR-9 crosslink task : cross-lingual link discovery

This paper presents an overview of NTCIR-9 Cross-lingual Link Discovery (Crosslink) task. The overview includes: the motivation of cross-lingual link discovery; the Crosslink task definition; the run submission specification; the assessment and evaluation framework; the evaluation metrics; and the evaluation results of submitted runs. Cross-lingual link discovery (CLLD) is a way of automatically finding potential links between documents in different languages. The goal of this task is to create a reusable resource for evaluating automated CLLD approaches. The results of this research can be used in building and refining systems for automated link discovery. The task is focused on linking between English source documents and Chinese, Korean, and Japanese target documents.