Effectiveness of community-based nonpharmacological interventions for early-stage dementia : conclusions and recommendations

In 2007, a comprehensive review of the extant research on nonpharmacological interventions for persons with early-stage dementia was conducted. More than 150 research reports, centered on six major domains, were included: early-stage support groups, cognitive training and enhancement programs, exercise programs, exemplar programs, health promotion programs, and “other” programs not fitting into previous categories. Theories of neural regeneration and plasticity were most often used to support the tested interventions. Recommendations for practice, research, and health policy are outlined, including evidence-based, nonpharmacological treatment protocols for persons with mild cognitive impairment and early-stage dementia. A tested, community-based, multimodal treatment program is also described. Overall, findings identify well-supported nonpharmacological treatments for persons with early-stage dementia and implications for a national health care agenda to optimize outcomes for this growing population of older adults.

Consumer-based brand equity for Australia as a long haul tourism destination in an emerging market

Purpose: Although the branding literature emerged during the 1940s, research relating to tourism destination branding has only gained momentum since the late 1990s. There remains a lack of theory in particular that addresses the measurement of the effectiveness of destination branding over time. The purpose of the research was to test the effectiveness of a model of consumer-based brand equity (CBBE) for a country destination.---------- Design/methodology: A model of consumer-based brand equity was adapted from the marketing literature and applied to a nation context. The model was tested by using structural equation modelling with data from a large Chilean sample (n=845), comprising a mix of previous visitors and non-visitors. The model fits the data well. Findings: This paper reports the results of an investigation into brand equity for Australia as a long haul destination in an emerging market. The research took place just before the launch of the nation’s fourth new brand campaign in six years. The results indicate Australia is a well known but not compelling destination brand for tourists in Chile, which reflects the lower priority the South American market has been given by the national tourism office (NTO).---------- Practical implications: It is suggested that CBBE measures could be analysed at various points in time to track any strengthening or weakening of market perceptions in relation to brand objectives. A standard CBBE instrument could provide long-term effectiveness performance measures regardless of changes in destination marketing organisation (DMO) staff, advertising agency, other stakeholders, and budget.---------- Originality/value: This study contributes to the nation-branding literature by being one of the first to test the efficacy of a model of consumer-based brand equity for a tourism destination brand.

Data-driven background dataset selection for SVM-based speaker verification

The recently proposed data-driven background dataset refinement technique provides a means of selecting an informative background for support vector machine (SVM)-based speaker verification systems. This paper investigates the characteristics of the impostor examples in such highly-informative background datasets. Data-driven dataset refinement individually evaluates the suitability of candidate impostor examples for the SVM background prior to selecting the highest-ranking examples as a refined background dataset. Further, the characteristics of the refined dataset were analysed to investigate the desired traits of an informative SVM background. The most informative examples of the refined dataset were found to consist of large amounts of active speech and distinctive language characteristics. The data-driven refinement technique was shown to filter the set of candidate impostor examples to produce a more disperse representation of the impostor population in the SVM kernel space, thereby reducing the number of redundant and less-informative examples in the background dataset. Furthermore, data-driven refinement was shown to provide performance gains when applied to the difficult task of refining a small candidate dataset that was mis-matched to the evaluation conditions.

Evaluation of community participation for the development of culture-based fisheries in village reservoirs of Sri Lanka

In this paper an attempt is made to identify the socioeconomic characteristics of a community that influences the development and management of culture-based fisheries in village reservoirs of Sri Lanka. Socioeconomic data were collected from 46 agricultural farming communities associated with 47 village reservoirs in Sri Lanka. Principal component analysis indicated that scores of the first principal component were positively influenced by socioeconomic characteristics that are favorable for making collective decisions. These included leadership of the officers, age of the group, percentage of active members of the group, percentage of kinship of the group, percentage of common interest of the group, and percentage of participation of the group. The size of the group had negative effect on the first principal component. The principal component scores of communication were positively related to willingness to pay (P< 0.001). The communities with socioeconomic characteristics favouring collective decision making were in favor of culture-based fisheries. Homogeneity of group characteristics facilitated successful development of culture-based fisheries.

Knowledge, attitudes and beliefs towards injury prevention : a population based telephone survey

Public knowledge and beliefs about injury prevention are currently poorly understood. A total of 1030 residents in the State of Queensland, Australia responded to questions about injury prevention in or around the home, on the roads, in or on the water, at work, deliberate injury, and responsibility for preventing deliberate injury allowing comparison with published injury prevalence data. Overall the youngest members of society were identified as being the most vulnerable to deliberate injury with young adults accounting for 59% of responses aligning with published data. However, younger adults failed to indicate an awareness of their own vulnerability to deliberate injury in alcohol environments even though 61% of older respondents were aware of this trend. Older respondents were the least inclined to agree that they could make a difference to their own safety in or around the home but were more inclined to agree that they could make a difference to their own safety at work. The results are discussed with a view to using improved awareness of public beliefs about injury to identify barriers to the uptake of injury prevention strategies (e.g. low perceived injury risk) as well as areas where injury prevention strategies may receive public support.

Choice of image features for depth-axis control in image based visual servo control

This paper is concerned with choosing image features for image based visual servo control and how this choice influences the closed-loop dynamics of the system. In prior work, image features tend to be chosen on the basis of image processing simplicity and noise sensitivity. In this paper we show that the choice of feature directly influences the closed-loop dynamics in task-space. We focus on the depth axis control of a visual servo system and compare analytically various approaches that have been reported recently in the literature. The theoretical predictions are verified by experiment.

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.

If it's encrypted it's secure! The viability of US state-based encryption exemptions

US state-based data breach notification laws have unveiled serious corporate and government failures regarding the security of personal information. These laws require organisations to notify persons who may be affected by an unauthorized acquisition of their personal information. Safe harbours to notification exist if personal information is encrypted. Three types of safe harbour have been identified in the literature: exemptions, rebuttable presumptions and factors. The underlying assumption of exemptions is that encrypted personal information is secure and therefore unauthorized access does not pose a risk. However, the viability of this assumption is questionable when examined against data breaches involving encrypted information and the demanding practical requirements of effective encryption management. Recent recommendations by the Australian Law Reform Commission (ALRC) would amend the Privacy Act 1988 (Cth) to implement a data breach scheme that includes a different type of safe harbour, factor based analysis. The authors examine the potential capability of the ALRC’s proposed encryption safe harbour in relation to the US experience at the state legislature level.

Vision-based detection and tracking of aerial targets for UAV collision avoidance

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved (as opposed to radar). This paper describes the development and evaluation of a vision-based collision detection algorithm suitable for fixed-wing aerial robotics. The system was evaluated using highly realistic vision data of the moments leading up to a collision. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We make use of the enormous potential of graphic processing units to achieve processing rates of 30Hz (for images of size 1024-by- 768). Currently, integration in the final platform is under way.

Evidence-based practice : information professionals' experience of information literacy in the workplace

Evidence-based practice is increasingly being recognised as an important issue in a range of professional contexts including education, nursing, occupational therapy and librarianship. Many of these professions have observed a relationship or interface between evidence-based practice and information literacy. Using a phenomenographic approach this research explores variation in the how library and information professionals are experiencing evidence-based practice as part of their professional work. The findings of the research provide a basis for arguing that evidence-based practice represents the professional's enactment of information literacy in the workplace.

Airborne vision-based collision-detection system

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of vision sensors (as opposed to radar and TCAS). This paper describes the development and evaluation of a real-time vision-based collision detection system suitable for fixed-wing aerial robotics. Using two fixed-wing UAVs to recreate various collision-course scenarios, we were able to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. This type of image data is extremely scarce and was invaluable in evaluating the detection performance of two candidate target detection approaches. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We overcame the challenge of achieving real-time computational speeds by exploiting the parallel processing architectures of graphics processing units found on commercially-off-the-shelf graphics devices. Our chosen GPU device suitable for integration onto UAV platforms can be expected to handle real-time processing of 1024 by 768 pixel image frames at a rate of approximately 30Hz. Flight trials using manned Cessna aircraft where all processing is performed onboard will be conducted in the near future, followed by further experiments with fully autonomous UAV platforms.

Featureless vehicle-based visual SLAM with a consumer camera

The Simultaneous Localisation And Mapping (SLAM) problem is one of the major challenges in mobile robotics. Probabilistic techniques using high-end range finding devices are well established in the field, but recent work has investigated vision-only approaches. We present an alternative approach to the leading existing techniques, which extracts approximate rotational and translation velocity information from a vehicle-mounted consumer camera, without tracking landmarks. When coupled with an existing SLAM system, the vision module is able to map a 45 metre long indoor loop and a 1.6 km long outdoor road loop, without any parameter or system adjustment between tests. The work serves as a promising pilot study into ground-based vision-only SLAM, with minimal geometric interpretation of the environment.

Augmenting RatSLAM using FAB-MAP-based visual data association

This paper investigates the use of the FAB-MAP appearance-only SLAM algorithm as a method for performing visual data association for RatSLAM, a semi-metric full SLAM system. While both systems have shown the ability to map large (60-70km) outdoor locations of approximately the same scale, for either larger areas or across longer time periods both algorithms encounter difficulties with false positive matches. By combining these algorithms using a mapping between appearance and pose space, both false positives and false negatives generated by FAB-MAP are significantly reduced during outdoor mapping using a forward-facing camera. The hybrid FAB-MAP-RatSLAM system developed demonstrates the potential for successful SLAM over large periods of time.

Supervising practice based research

Practice based research appears to have emerged within several Higher Education agendas including the professional doctorates and the teacher as researcher. One way of thinking about this methodological approach is to consider its research paradigm – a practice based epistemology, and from this perspective to consider what special application to research supervision the paradigm invites. Within a “supervision as pedagogy” agenda these applications can be considered as pedagogies. This paper has been written in the style of practice based research, drawing on the author’s own experiences of supervising students undertaking practice based research. It adopts a position that research supervision is pedagogy and draws on the model of ‘Productive Pedagogies” to articulate strategies to help novice research students develop a research proposal.