The impact of survey length, interactivity and participant involvement on intentions and satisfaction across multiple panels

This study examines how survey design characteristics impact on participant satisfaction, future intentions to complete surveys, and intention to recommend the survey to others, based on panel members, extracted from three different panels, who randomly received one out of eight developed surveys, varying length, involvement and interactivity. The experiment was designed for an Australian industry client. The multivariate analysis of covariance (MANCOVA hereafter) results suggest that there are differences based on the panels used, and longer surveys are viewed more positively. Interaction occurs between panels and involvement, but other two way interaction effects are insignificant. Implications for survey design and future research are discussed.

Recognition and response to human movement contained in motion capture data using the Self Organising Map

Neural Networks have been used successfully for recognition of human gestures in many applications including analysis of motion capture data. This paper investigates the potential for using the same methods for both recognition and synthesising responses in relation to movement contained in motion capture sequences.

A comparative study of supervised learning techniques for data-driven haptic simulation

This paper focuses on the choice of a supervised learning algorithm and possible data preprocessing in the domain of data-driven haptic simulation. This is done through a comparison of the performance of different supervised learning techniques with and without data preprocessing. The simulation of haptic interactions with deformable objects using data-driven methods has emerged as an alternative to parametric methods. The accuracy of the simulation depends on the empirical data and the learning method. Several methods were suggested in the literature and here we provide a comparison between their performance and applicability to this domain. We selected four examples to be compared: singular learning mechanism which is artificial neural networks (ANN), attribute selection followed by ANN learning process, ensemble of multiple learning techniques, and attribute selection followed by the learning ensemble. These methods performance was compared in the domain of simulating multiple interactions with a deformable object with nonlinear material behavior.

Real-time detection of parked vehicles from multiple image streams

We present a system to detect parked vehicles in a typical commercial parking complex using multiple streams of images captured through IP connected devices. Compared to traditional object detection techniques and machine learning methods, our approach is significantly faster in detection speed in the presence of multiple image streams. It is also capable of comparable accuracy when put to test against existing methods. And this is achieved without the need to train the system that machine learning methods require. Our approach uses a combination of psychological insights obtained from human detection and an algorithm replicating the outcomes of a SVM learner but without the noise that compromises accuracy in the normal learning process. The result is faster detection with comparable accuracy. Our experiments on images captured from a local test site shows very promising results for an implementation that is not only effective and low cost but also opens doors to new parking applications when combined with other technologies.

Recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association

Recognising behaviours of multiple people, especially high-level behaviours, is an important task in surveillance systems. When the reliable assignment of people to the set of observations is unavailable, this task becomes complicated. To solve this task, we present an approach, in which the hierarchical hidden Markov model (HHMM) is used for modeling the behaviour of each person and the joint probabilistic data association filters (JPDAF) is applied for data association. The main contributions of this paper lie in the integration of multiple HHMMs for recognising high-level behaviours of multiple people and the construction of the Rao-Blackwellised particle filters (RBPF) for approximate inference. Preliminary experimental results in a real environment show the robustness of our integrated method in behaviour recognition and its advantage over the use of Kalman filter in tracking people.

Predicting landscape-genetic consequences of habitat loss, fragmentation and mobility for multiple species of woodland birds

Inference concerning the impact of habitat fragmentation on dispersal and gene flow is a key theme in landscape genetics. Recently, the ability of established approaches to identify reliably the differential effects of landscape structure (e.g. land-cover composition, remnant vegetation configuration and extent) on the mobility of organisms has been questioned. More explicit methods of predicting and testing for such effects must move beyond post hoc explanations for single landscapes and species. Here, we document a process for making a priori predictions, using existing spatial and ecological data and expert opinion, of the effects of landscape structure on genetic structure of multiple species across replicated landscape blocks. We compare the results of two common methods for estimating the influence of landscape structure on effective distance: least-cost path analysis and isolation-by-resistance. We present a series of alternative models of genetic connectivity in the study area, represented by different landscape resistance surfaces for calculating effective distance, and identify appropriate null models. The process is applied to ten species of sympatric woodland-dependant birds. For each species, we rank a priori the expectation of fit of genetic response to the models according to the expected response of birds to loss of structural connectivity and landscape-scale tree-cover. These rankings (our hypotheses) are presented for testing with empirical genetic data in a subsequent contribution. We propose that this replicated landscape, multi-species approach offers a robust method for identifying the likely effects of landscape fragmentation on dispersal.

Effects of time since fire on birds : how informative are generalized fire response curves for conservation management?

Fire is both a widespread natural disturbance that affects the distribution of species and a tool that can be used to manage habitats for species. Knowledge of temporal changes in the occurrence of species after fire is essential for conservation management in fire-prone environments. Two key issues are: whether postfire responses of species are idiosyncratic or if multiple species show a limited number of similar responses; and whether such responses to time since fire can predict the occurrence of species across broad spatial scales. We examined the response of bird species to time since fire in semiarid shrubland in southeastern Australia using data from surveys at 499 sites representing a 100-year chronosequence. We used nonlinear regression to model the probability of occurrence of 30 species with time since fire in two vegetation types, and compared species' responses with generalized response shapes from the literature. The occurrence of 16 species was significantly influenced by time since fire: they displayed six main responses consistent with generalized response shapes. Of these 16 species, 15 occurred more frequently in mid- or later-successional vegetation (>20 years since fire), and only one species occurred more often in early succession (<5 years since fire). The models had reasonable predictive ability for eight species, some predictive ability for seven species, and were little better than random for one species. Bird species displayed a limited range of responses to time since fire; thus a small set of fire ages should allow the provision of habitat for most species. Postfire successional changes extend for decades and management of the age class distribution of vegetation will need to reflect this timescale. Response curves revealed important seral stages for species and highlighted the importance of mid- to late-successional vegetation (>20 years). Although time since fire clearly influences the distribution of numerous bird species, predictive models of the spatial distribution of species in fire-prone landscapes need to incorporate other factors in addition to time since fire.

Response to comment on "Illusions promote mating success in great bowerbirds"

Borgia et al. raise some questions about our recent study showing that great bowerbirds create visual illusions that are used in mate choice. We address them by providing further details about our methods and results. We also provide detailed descriptions of our geometric calculations to address their measurement and analysis questions.

Does the choice of neighbourhood supermarket access measure influence associations with individual-level fruit and vegetable consumption? A case study from Glasgow

Background
Previous studies have provided mixed evidence with regards to associations between food store access and dietary outcomes. This study examines the most commonly applied measures of locational access to assess whether associations between supermarket access and fruit and vegetable consumption are affected by the choice of access measure and scale.

Method
Supermarket location data from Glasgow, UK (n = 119), and fruit and vegetable intake data from the 'Health and Well-Being' Survey (n = 1041) were used to compare various measures of locational access. These exposure variables included proximity estimates (with different points-of-origin used to vary levels of aggregation) and density measures using three approaches (Euclidean and road network buffers and Kernel density estimation) at distances ranging from 0.4 km to 5 km. Further analysis was conducted to assess the impact of using smaller buffer sizes for individuals who did not own a car. Associations between these multiple access measures and fruit and vegetable consumption were estimated using linear regression models.

Results
Levels of spatial aggregation did not impact on the proximity estimates. Counts of supermarkets within Euclidean buffers were associated with fruit and vegetable consumption at 1 km, 2 km and 3 km, and for our road network buffers at 2 km, 3 km, and 4 km. Kernel density estimates provided the strongest associations and were significant at a distance of 2 km, 3 km, 4 km and 5 km. Presence of a supermarket within 0.4 km of road network distance from where people lived was positively associated with fruit consumption amongst those without a car (coef. 0.657; s.e. 0.247; p0.008).

Conclusions
The associations between locational access to supermarkets and individual-level dietary behaviour are sensitive to the method by which the food environment variable is captured. Care needs to be taken to ensure robust and conceptually appropriate measures of access are used and these should be grounded in a clear a priori reasoning.

Sex-related differences in the organismal and cellular stress response in juvenile salmon exposed to treated bleached kraft mill effluent

Exposure of fish to stressors can elicit biochemical and organismal changes at multiple levels of biological organization collectively known as stress responses. The organismal (plasma glucose and cortisol levels) and cellular (hepatic hsp70) stress responses in fish have been studied in several species, but little is known about sex-related differences in these responses. In this study, we exposed sexually immature juvenile chinook salmon (Oncorhynchus tshawytscha) to bleached kraft mill effluent (BKME: 0%, 1%, and 10% v/v) for 30 days and then measured components of their organismal and cellular stress responses. Males exposed to 1% BKME had higher levels of plasma glucose than females. Plasma cortisol levels were unaffected in females exposed to BKME, but males exposed to 10% BKME had significantly higher levels of plasma cortisol relative to non-exposed males. While exposure to BKME did not affect hsp70 levels in males, females exposed to 1% BKME had higher levels of hsp70 relative to non-exposed and 10% BKME groups. Within any given treatment, females had higher levels of hsp70 relative to males. This study demonstrates that sex-related differences exist in commonly used indicators of stress in fish, and points out the importance of considering the sex of the fish in stress research.

The high seas (C’s) of music piracy in information systems : cost, convenience and choice

Systems and technologies used for unauthorised file sharing have received little attention in the Information Systems literature. This paper attempts to fill this gap by presenting a critical, qualitative study on the motivations for using unauthorised file sharing systems. Based on 30 interviews with music consumers, musicians, and the music industry, this paper reports on the decision of music consumers to ‘pirate or purchase’. This paper highlights file sharing from multiple perspectives of users, musicians, and representatives from the music recording industry. Three main themes emerged on the cost, convenience and choice as motivators for unauthorised file sharing.

Processing multiple image streams for real-time monitoring of parking lots

We present a system to detect parked vehicles in a typical parking complex using multiple streams of images captured through IP connected devices. Compared to traditional object detection techniques and machine learning methods, our approach is significantly faster in detection speed in the presence of multiple image streams. It is also capable of comparable accuracy when put to test against existing methods. And this is achieved without the need to train the system that machine learning methods require. Our approach uses a combination of psychological insights obtained from human detection and an algorithm replicating the outcomes of a SVM learner but without the noise that compromises accuracy in the normal learning process. Performance enhancements are made on the algorithm so that it operates well in the context of multiple image streams. The result is faster detection with comparable accuracy. Our experiments on images captured from a local test site shows very promising results for an implementation that is not only effective and low cost but also opens doors to new parking applications when combined with other technologies.

Cumulative morbidity and prognostic staging of illness in the systematic treatment enhancement program for Bipolar Disorder (STEP-BD)

Objective: Staging models may provide heuristic utility for intervention selection in psychiatry. Although a few proposals have been put forth, there is a need for empirical validation if they are to be adopted. Using data from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD), we tested a previously elaborated hypothesis on the utility of using the number of previous episodes as a relevant prognostic variable for staging in bipolar disorder.

Methods: This report utilizes data from the multisite, prospective, open-label study ‘Standard Care Pathways’ and the subset of patients with acute depressive episodes who participated in the randomized trial of adjunctive antidepressant treatment. Outpatients meeting DSM-IV diagnostic criteria for bipolar disorder (n = 3345) were included. For the randomized pathway, patients met criteria for an acute depressive episode (n = 376). The number of previous episodes was categorized as less than 5, 5–10 and more than 10. We used disability at baseline, number of days well in the first year and longitudinal scores of depressive and manic symptoms, quality of life and functioning as validators of models constructed a priori.

Results: Patients with multiple previous episodes had consistently poorer cross-sectional and prospective outcomes. Functioning and quality of life were worse, disability more common, and symptoms more chronic and severe. There was no significant effect for staging with regard to antidepressant response in the randomized trial.

Conclusions: These findings confirm that bipolar disorder can be staged with prognostic validity. Stages can be used to stratify subjects in clinical trials and develop specific treatments.

Ghosts in the machine : do the dead live on in Facebook?

Of the many ways in which identity is constructed and performed online, few are as strongly ‘anchored’ to existing offline relationships as in online social networks like Facebook and Myspace. These networks utilise profiles that extend our practical, psychological and even corporeal identity in ways that give them considerable phenomenal presence in the lives of spatially distant people. This raises interesting questions about the persistence of identity when these online profiles survive the deaths of the users behind them, via the practice of ‘memorialising’ social network profile pages. I situate these practices within a phenomenology of grief that accounts for the ways in which the dead can persist as moral patients, and show how online survival in this case illuminates an important difference between persons and selves within contemporary philosophy of personal identity. Ultimately, the online persistence of the dead helps bring into view a deep ontological contradiction implicit in our dealings with death: the dead both live on as objects of duty and yet completely cease to exist.

Latent patient profile modelling and applications with mixed-variate restricted Boltzmann machine

Efficient management of chronic diseases is critical in modern health care. We consider diabetes mellitus, and our ongoing goal is to examine how machine learning can deliver information for clinical efficiency. The challenge is to aggregate highly heterogeneous sources including demographics, diagnoses, pathologies and treatments, and extract similar groups so that care plans can be designed. To this end, we extend our recent model, the mixed-variate restricted Boltzmann machine (MV.RBM), as it seamlessly integrates multiple data types for each patient aggregated over time and outputs a homogeneous representation called "latent profile" that can be used for patient clustering, visualisation, disease correlation analysis and prediction. We demonstrate that the method outperforms all baselines on these tasks - the primary characteristics of patients in the same groups are able to be identified and the good result can be achieved for the diagnosis codes prediction.