Food and interaction design [Extended Abstract]

Food and interaction design presents an interesting challenge to the HCI community in attending to the pervasive nature of food, the socio-cultural differences in food practices and a changing global foodscape. To design for meaningful and positive interactions it is essential to identify daily food practices and the opportunities for the design of technology to support such practices. This workshop brings together a community of researchers and practitioners in human-food interaction to attend to the practical and theoretical difficulties in designing for human-food interactions in everyday life. Through a practical field study and workshop we explore themes of food experiences, health and wellbeing, sustainability and alternative food cultures.

Assessment of flood-related recharge to alluvial aquifers of an irrigated catchment following extended drought conditions using 3D visualisation and environmental tracers, Lockyer Valley, southeast Queensland, Australia.

The Lockyer Valley in southeast Queensland, Australia, hosts an economically significant alluvial aquifer system which has been impacted by prolonged drought conditions (~1997 to ~ 2009). Throughout this time, the system was under continued groundwater extraction, resulting in severe aquifer depletion. By 2008, much of the aquifer was at <30% of storage but some relief occurred with rains in early 2009. However, between December 2010 and January 2011, most of southeast Queensland experienced unprecedented flooding, which generated significant aquifer recharge. In order to understand the spatial and temporal controls of groundwater recharge in the alluvium, a detailed 3D lithological property model of gravels, sands and clays was developed using GOCAD software. The spatial distribution of recharge throughout the catchment was assessed using hydrograph data from about 400 groundwater observation wells screened at the base of the alluvium. Water levels from these bores were integrated into a catchment-wide 3D geological model using the 3D geological modelling software GOCAD; the model highlights the complexity of recharge mechanisms. To support this analysis, groundwater tracers (e.g. major and minor ions, stable isotopes, 3H and 14C) were used as independent verification. The use of these complementary methods has allowed the identification of zones where alluvial recharge primarily occurs from stream water during episodic flood events. However, the study also demonstrates that in some sections of the alluvium, rainfall recharge and discharge from the underlying basement into the alluvium are the primary recharge mechanisms of the alluvium. This is indicated by the absence of any response to the flood, as well as the observed old radiocarbon ages and distinct basement water chemistry signatures at these locations. Within the 3D geological model, integration of water chemistry and time-series displays of water level surfaces before and after the flood suggests that the spatial variations of the flood response in the alluvium are primarily controlled by the valley morphology and lithological variations within the alluvium. The integration of time-series of groundwater level surfaces in the 3D geological model also enables the quantification of the volumetric change of groundwater stored in the unconfined sections of this alluvial aquifer during drought and following flood events. The 3D representation and analysis of hydraulic and recharge information has considerable advantages over the traditional 2D approach. For example, while many studies focus on singular aspects of catchment dynamics and groundwater-surface water interactions, the 3D approach is capable of integrating multiple types of information (topography, geological, hydraulic, water chemistry and spatial) into a single representation which provides valuable insights into the major factors controlling aquifer processes.

Bending and blurring blended learning boundaries [Extended Abstract]

This presentation presents a blended learning model that provides greater opportunity for learning to be self-managed and personalized.

The late discovery of adoptive and donor insemination offspring status : ethical implications for conceptual understandings of the ‘best interests of the child’ principle

Late discovery is a term used to describe the experience of discovering the truth of one’s genetic origins as an adult. Following discovery, late discoverers face a lack of recognition and acknowledgment of their concerns from family, friends, community and institutions. They experience pain, anger, loss, grief and frustration. This presentation shares the findings of the first qualitative study of both late discovery of adoptive and donor insemination offspring (heterosexual couple use only) experiences. It is also the first study of late discovery experiences undertaken from an ethical perspective. While this study recruited new participants, it also included an ethical re-analysis of existing late discovery accounts across both practices. The findings of this study (a) draws links between past adoption and current donor insemination (heterosexual couple only) practices, (b) reveals that late discoverers are demanding acknowledgment and recognition of the particularity of their experiences, and (c) offers insights into conceptual understandings of the ‘best interests of the child’ principle. These insights derive from the lived experiences of those whose biological and social worlds have been sundered and secrecy and denial of difference used to conceal this. It suggests that acknowledging the equal moral status of the child may be useful in strengthening conceptual understandings of the ‘best interests of the child’ principle. This equal moral status involves ensuring that personal autonomy and the ability to exercise free will is protected; that the integrity of the relationships of trust expected and demanded between parent/s and children is defended and supported; and that equal access to normative socio-cultural practices, that is; non-fictionalised birth certificates and open records, is guaranteed.

An extended theory of planned behavior intervention for older adults With Type 2 diabetes and cardiovascular disease

A randomized controlled trial evaluated the effectiveness of a 4-wk extended theory of planned behavior (TPB) intervention to promote regular physical activity and healthy eating among older adults diagnosed with Type 2 diabetes or cardiovascular disease (N = 183). Participants completed TPB measures of attitude, subjective norm, perceived behavioral control, and intention, as well as planning and behavior, at preintervention and 1 wk and 6 wk postintervention for each behavior. No significant time-by-condition effects emerged for healthy eating. For physical activity, significant time-by-condition effects were found for behavior, intention, planning, perceived behavioral control, and subjective norm. In particular, compared with control participants, the intervention group showed short-term improvements in physical activity and planning, with further analyses indicating that the effect of the intervention on behavior was mediated by planning. The results indicate that TPB-based interventions including planning strategies may encourage physical activity among older people with diabetes and cardiovascular disease.

The role of mindfulness in an extended TPB framework to understand drivers’ speeding intentions in school zones.

Many researchers have demonstrated the applicability of the Theory of Planned Behaviour (TPB) in predicting both intention to speed and actual speeding behaviour. However, there remain shortcomings in the explanatory power of the TPB, with research suggesting that even when drivers had reported an intention to not speed approximately 25% of drivers report behaviour that does not align with their intentions (i.e., they engaged in speeding, Elliott & Armitage, 2006). This research explores the role of a novel and promising construct, mindfulness, in enhancing the explanatory utility of the TPB for the understanding of drivers’ speeding behaviour in school zones. Mindfulness is a concept which has been widely used in studies of consciousness, but has recently been applied to the understanding of behaviour in other areas, including clinical psychology, physical activity, education and business. It has been suggested that mindfulness can also be applied to road safety, though its application within this context currently remains limited. This study was based on an e-survey of the general driving public (N=240). Overall, the results identified mindfulness as a construct which may aid understanding of the relationship between drivers’ intentions and behaviour. Theoretically, the findings may have implications in terms of identifying mindfulness as an additional explanatory construct within a TPB framework. In road safety practice, the findings suggest that efficacious countermeasures around school zones may be those that function to heighten drivers’ mindfulness, such as flashing lights and physical speed reduction measures.

Metacognitive narrative psychotherapy for people diagnosed with schizophrenia : an outline of a principle-based treatment manual

Schizophrenia is often characterised by diminished self-experience. This article describes the development and principles of a manual for a psychotherapeutic treatment model that aims to enhance self-experience in people diagnosed with schizophrenia. Metacognitive Narrative Psychotherapy draws upon dialogical theory of self and the work of Lysaker and colleagues, in conjunction with narrative principles of therapy as operationalised by Vromans. To date, no manual for a metacognitive narrative approach to the treatment of schizophrenia exists. After a brief description of narrative understandings of schizophrenia, the development of the manual is described. Five general phases of treatment are outlined: (1) developing a therapeutic relationship; (2) eliciting narratives; (3) enhancing metacognitive capacity; (4) enriching narratives, and; (5) living enriched narratives. Proscribed practices are also described. Examples of therapeutic interventions and dialogue are provided to further explain the application of interventions in-session. The manual has been piloted in a study investigating the effectiveness of Metacognitive Narrative Psychotherapy in the treatment of people diagnosed with schizophrenia spectrum disorders.

Emotional arousal of beginning physics teachers during extended experimental investigations

Teachers often have difficulty implementing inquiry-based activities, leading to the arousal of negative emotions. In this multicase study of beginning physics teachers in Australia, we were interested in the extent to which their expectations were realized and how their classroom experiences while implementing extended experimental investigations (EEIs) produced emotional states that mediated their teaching practices. Against rhetoric of fear expressed by their senior colleagues, three of the four teachers were surprised by the positive outcomes from their supervision of EEIs for the first time. Two of these teachers experienced high intensity positive emotions in response to their students’ success. When student actions / outcomes did not meet their teachers’ expectations, frustration, anger, and disappointment were experienced by the teachers, as predicted by a sociological theory of human emotions (Turner, 2007). Over the course of the EEI projects, the teachers’ practices changed along with their emotional states and their students’ achievements. We account for similarities and differences in the teachers’ emotional experiences in terms of context, prior experience, and expectations. The findings from this study provide insights into effective supervision practices that can be used to inform new and experienced teachers alike.

How to design extended finite state machine test models in Java

This chapter is a tutorial that teaches you how to design extended finite state machine (EFSM) test models for a system that you want to test. EFSM models are more powerful and expressive than simple finite state machine (FSM) models, and are one of the most commonly used styles of models for model-based testing, especially for embedded systems. There are many languages and notations in use for writing EFSM models, but in this tutorial we write our EFSM models in the familiar Java programming language. To generate tests from these EFSM models we use ModelJUnit, which is an open-source tool that supports several stochastic test generation algorithms, and we also show how to write your own model-based testing tool. We show how EFSM models can be used for unit testing and system testing of embedded systems, and for offline testing as well as online testing.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

Multifunctional porous graphene for nanoelectronics and hydrogen storage : new properties revealed by first principle calculations

The lack of an obvious “band gap” is a formidable hurdle for making a nanotransistor from graphene. Here, we use density functional calculations to demonstrate for the first time that porosity such as evidenced in recently synthesized porous graphene (http://www.sciencedaily.com/releases/2009/11/091120084337.htm) opens a band gap. The size of the band gap (3.2 eV) is comparable to most popular photocatalytic titania and graphitic C3N4 materials. In addition, the adsorption of hydrogen on Li-decorated porous graphene is much stronger than that in regular Li-doped graphene due to the natural separation of Li cations, leading to a potential hydrogen storage gravimetric capacity of 12 wt %. In light of the most recent experimental progress on controlled synthesis, these results uncover new potential for the practical application of porous graphene in nanoelectronics and clean energy.

Early adolescents’ helping behaviours when a friend is injured in a fight : the role of an extended Theory of Planned Behavior

This paper examines the role of first aid training in increasing adolescent helping behaviours when taught in a school-based injury prevention program, Skills for Preventing Injury in Youth (SPIY). The research involved the development and application of an extended Theory of Planned Behaviour (TPB), including “behavioural willingness in a fight situation,” “first aid knowledge” and “perceptions of injury seriousness”, to predict the relationship between participation in SPIY and helping behaviours when a friend is injured in a fight. From 35 Queensland high schools, 2500 Year 9 students (mean age = 13.5, 40% male) completed surveys measuring their attitudes, perceived behavioural control, subjective norms and behavioural intention, from the TPB, and added measures of behavioural willingness in a fight situation, perceptions of injury seriousness and first aid knowledge, to predict helping behaviours when a friend is injured in a fight. It is expected that the TPB will significantly contribute to understanding the relationship between participation in SPIY and helping behaviours when a friend is injured in a fight. Further analyses will determine whether the extension of the model significantly increases the variance explained in helping behaviours. The findings of this research will provide insight into the critical factors that may increase adolescent bystanders’ actions in injury situations.