The subtropical residential tower: An investigation by Design Charrette

QUT's Centre for Subtropical Design (CSD) partnered with a major developer to bring together some of Brisbane’s most experienced and creative architects and designers in a two-day intensive design charrette to propose innovative design strategies for naturally-ventilated high rise residential buildings. An inner-urban renewal site in Queensland’s capital city Brisbane gave four multi-disciplinary teams the opportunity to address a raft of issues that developers and consultants will confront more and more in the future in warm humid climates. The quest to release apartment dwellers from dependence on energy-hungry air-conditioning and artificial lighting was central to the design brief for the towers. Mentored by Richard Hassell of WOHA, the creative teams focussed on climate-responsive design principles for passive climate control including orientation, cross-ventilation and outdoor living in order to reduce greenhouse gas emissions and offset occupants’ rising energy costs. This article discusses how outcomes of the charrette take their cue from the city’s subtropical climate and demonstrate how high-density high-rise living can be attractive, affordable and sustainable through positive engagement with the subtropical climate’s natural attributes.

Resilience by design: A participatory approach to designing an interactive digital application for promoting children's resilience

The promotion of resilience (the capacity of an individual or community to bounce back and recover from adversity) has become an important area of public health. In recent years it has expanded into the digital domain, and many online applications have been developed to promote children's resilience. In this study, it is argued that the majority of existing applications are limited because they take a didactic approach, and conceive of interaction as providing navigational choices. Because they simply provide information about resilience or replicate offline, scenario-based strategies, the understanding of resilience they provide is confined to a few, predetermined factors. In this study I propose a new, experiential approach to promoting resilience digitally. I define resilience as an emergent, situated and context-specific phenomenon. Using a Participatory Design model in combination with a salutogenic (strength-based) health methodology, this project has involved approximately 50 children as co-designers and co-researchers over two years. The children have contributed to the design of a new set of interactive resilience tools, which facilitate resilience promotion through dialogic and experiential learning. The major outcomes of this study include a new methodology for developing digital resilience tools, a new set of tools that have been developed and evaluated in collaboration with children and a set of design principles to guide future development. Beyond these initial and tangible outcomes, this study has also established that the benefits of introducing Participatory Design into a health promoting model rests primarily in the change of the role of children from "users" of technology and education to co-designers, where they assume a leadership role in both designing the tools and in directing their resilience learning.

An intervention study to improve pain management by nurses : normative beliefs and perceived control

Based on a predictive model of nurses' intentions regarding pain management, an intervention was developed to improve nurses' pain management. The intervention involved a series of workshops with cohorts of nurses working in acute care wards to address the important antecedents to their intentions: normative beliefs and perceived control. Pre- and post-intervention measures demonstrate the effectiveness of the intervention. The effectiveness of this intervention in improving the management of patients' pain is compared with a patient education program group and a control group. The findings provide support for further developing interventions based on the theory of planned behavior.

Privacy by Design : Does it matter for social networks?

Privacy is an important component of freedom and plays a key role in protecting fundamental human rights. It is becoming increasingly difficult to ignore the fact that without appropriate levels of privacy, a person’s rights are diminished. Users want to protect their privacy - particularly in “privacy invasive” areas such as social networks. However, Social Network users seldom know how protect their own privacy through online mechanisms. What is required is an emerging concept that provides users legitimate control over their own personal information, whilst preserving and maintaining the advantages of engaging with online services such as Social Networks. This paper reviews “Privacy by Design (PbD)” and shows how it applies to diverse privacy areas. Such an approach will move towards mitigating many of the privacy issues in online information systems and can be a potential pathway for protecting user’s personal information. The research has posed many questions in need of further investigation for different open source distributed Social Networks. Findings from this research will lead to a novel distributed architecture that provides more transparent and accountable privacy for the users of online information systems.

Redisplacement by design

Recently, researchers have noted that traditional knowledge systems (TKSs) can inspire technology design. They have also noted that the interdependency between Aboriginal culture and “landscape” provides insight into an embodied approach to HCI [1]: People’s experience of place and construction of space does not separate the mind, the body, and the surroundings [2]. However, we notice that increased recognition of Aboriginal TKS is no easy panacea for the constraints on design prescribed by the way the “technology race” (pun intended) abstracts spaces. Instead, paradoxes for the cultural “localization” of technology, mentioned in previous columns in this series, emerge from complex power relations between TKSs and dominant knowledge.

Privacy by design for social networks

This research has established a new privacy framework, privacy model, and privacy architecture to create more transparent privacy for social networking users. The architecture is designed into three levels: Business, Data, and Technology, which is based on The Open Group Architecture Framework (TOGAF®). This framework and architecture provides a novel platform for investigating privacy in Social Networks (SNs). This approach mitigates many current SN privacy issues, and leads to a more controlled form of privacy assessment. Ultimately, more privacy will encourage more connections between people across SN services.

Preventive orientation and caries management by Iranian dentists

Ehkäisypainotteisuus karieksen hoidossa: iranilaishammaslääkärien hoitovalinnat Karies aiheuttaa hampaiden kovan pinnan ja hammasluun syöpymistä, joka lopulta näkyy ”reikänä”. Iästä riippumatta kariesvaara vaanii kaikkia hampaiden omistajia, vauvasta vaariin, ja lähes kaikilla aikuisilla on suussaan merkkejä karieksesta. Karies etenee yleensä hitaasti ja antaa siten aikaa ehkäisevälle hoidolle. Tämä etsikkoaika jää usein käyttämättä, ja karieksen hoito painottuu reikien paikkaamiseen. Karies voitaisiin pitää kurissa sen ehkäisyyn kehitetyillä monipuolisilla keinoilla. Hammaslääkärit ovat avainasemassa, sillä he tekevät kauaskantoisia valintoja — hoidetaanko kariesta paikkaamalla vai valitaanko ehkäisevä hoito? Valintojen taustalla ovat hammaslääkärin tietotaso, asenteet ja omat terveystavat sekä potilaiden ja vastaanoton aiheuttamiksi koetut esteet. Tämä kyselytutkimus selvitti karieksen hoitovalintoja ja niiden taustoja Iranissa. Kysymyslomakkeet jaettiin kahdessa hammaslääkärien kongressissa Teheranissa (2004─2005) ja palautettiin nimettöminä. Kysely kartoitti hammaslääkärien tietoja karieksen ehkäisykeinoista ja asenteita ehkäisyä kohtaan sekä koettuja esteitä sen toteuttamisessa. Hoitovalintoja selvitettiin tarkasti kuvattujen esimerkkipotilaiden avulla. Kysely kartoitti myös hammaslääkärien omat terveystavat: suun omahoidon, tupakoinnin ja hammaslääkärissä käynnin. Aineisto käsitti 980 iältään keskimäärin 37-vuotiasta hammaslääkäriä, joista 64 % oli miehiä. Iranilaishammaslääkärien tiedot karieksen ehkäisystä olivat fluorihammastahnan merkitystä lukuun ottamatta hyvät ja heidän asenteensa ehkäisyä kohtaan valtaosin myönteiset. Tästä huolimatta 77 % heistä olisi valinnut suuren kariesvaaran potilaalle hammaskiilteessä olevan reiän hoidoksi paikkauksen. Ehkäisyhoidoksi tarjotuista 8:sta keinosta lähes kaikki hammaslääkärit valitsivat suuren kariesvaaran potilaalle hoidoksi harjausopetuksen ja säännölliset hammastarkastukset, noin 80 % valitsi hampaiden puhdistamisen vastaanotolla ja ravintoneuvonnan, 70 % ohjeet fluorihuuhteluista kotona ja 53 % vastaanotolla tehtävän fluorikäsittelyn. Potilaiden vastustavat mielipiteet arvioitiin suurimmaksi esteeksi ehkäisevän hoidon toteuttamiselle. Hammaslääkäreistä 59 % ilmoitti harjaavansa hampaansa kahdesti päivässä; 76 % ei tupakoinut ja 56 % kertoi aina ehdottavansa tupakoivalle potilaalle tupakoinnin lopettamista. Hammaslääkärien ehkäisypainotteisuus karieshoidossa oli naisilla vahvempi kuin miehillä. Tulosten perusteella voi päätellä, että Iranissa tulisi nykyistä selvemmin suosia ehkäisevää linjaa karieksen hoitovalintoja tehtäessä ja hammaslääkäreitä koulutettaessa. Potilastyössä koettujen ehkäisyhoidon esteiden syvällisempi ymmärtäminen edesauttaisi niiden poistamisessa.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

Network congestion management by fuzzy inference using virtual flows

Effective network overload alleviation is very much essential in order to maintain security and integrity from the operational viewpoint of deregulated power systems. This paper aims at developing a methodology to reschedule the active power generation from the sources in order to manage the network congestion under normal/contingency conditions. An effective method has been proposed using fuzzy rule based inference system. Using virtual flows concept, which provides partial contributions/counter flows in the network elements is used as a basis in the proposed method to manage network congestions to the possible extent. The proposed method is illustrated on a sample 6 bus test system and on modified IEEE 39 bus system.