Raised Floor System applications for refurbishing office spaces

While raised floors as a building component has been around since the 70's, its application in terms of a holistic system in the fit-out of commercial office buildings has not been fully embraced due to some inherent problems and negative perceptions of the stakeholders involved. Today, the new generation of raised floor systems(RFS) offers a suite of innovative and integrated products and solutions, and as such are not only suitable for the changing office space requirements, but also capable of meeting tbe smart and sustainable challenges, which are becoming the prerequisite in the refurbishment of existing buildings. As there has been a prediction for continued growth in refurbishment projects in major cities around the globe, RFS as an alternative methodology warrants new examination and highlight. This paper introduces research recently completed in Australia that provided a holistic approach to the application of RFS enabled by intelligent building technologies, and examined key issues of project development when refurbishing commercial office buildings. It focuses on the constructability of RFS, and how it will respond to smart feature requirements in buildings while extending service life, meeting new organisational change and workplace health needs for applications in today's office environment. It also introduces key project procurement issues and the integrated decision support when dealing with the refurbishment of office buildings. The paper recommends procurement strategies as well as the justification of adopting the RFS technology in the Australian office building sector. Given the current economic downturn, refitting as opposed to new build .projects will come onto the spotlight. This paper will provide valuable information for building owners and developers alike when contemplating the retrofit of office buildings.

Distributed orthogonal space-time block codes with adaptive diversity gain

In this paper we present a novel distributed coding protocol for multi-user cooperative networks. The proposed distributed coding protocol exploits the existing orthogonal space-time block codes to achieve higher diversity gain by repeating the code across time and space (available relay nodes). The achievable diversity gain depends on the number of relay nodes that can fully decode the signal from the source. These relay nodes then form space-time codes to cooperatively relay to the destination using number of time slots. However, the improved diversity gain is archived at the expense of the transmission rate. The design principles of the proposed space-time distributed code and the issues related to transmission rate and diversity trade off is discussed in detail. We show that the proposed distributed space-time coding protocol out performs existing distributed codes with a variable transmission rate.

Forecasting negative effects of monotony and sensation seeking on performance during a vigilance task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create hypovigilance and impair performance towards critical events. Identifying such impairment in monotonous conditions has been a major subject of research, but no research to date has attempted to predict it in real-time. This pilot study aims to show that performance decrements due to monotonous tasks can be predicted through mathematical modelling taking into account sensation seeking levels. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants‟ performance. The framework for prediction developed on this task could be extended to a monotonous driving task. A Hidden Markov Model (HMM) is proposed to predict participants‟ lapses in alertness. Driver‟s vigilance evolution is modelled as a hidden state and is correlated to a surrogate measure: the participant‟s reactions time. This experiment shows that the monotony of the task can lead to an important decline in performance in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

The embodied hybrid space : designing ubiquitous computing towards an amplification of situated real world experiences

The emergence of mobile and ubiquitous computing technology has created what is often referred to as the hybrid space – a virtual layer of digital information and interaction opportunities that sit on top of and augment the physical environment. Embodied media materialise digital information as observable and sometimes interactive parts of the physical environment. The aim of this work is to explore ways to enhance people’s situated real world experience, and to find out what the role and impact of embodied media in achieving this goal can be. The Edge, an initiative of the State Library of Queensland in Brisbane, Australia, and case study of this thesis, envisions to be a physical place for people to meet, explore, experience, learn and teach each other creative practices in various areas related to digital technology and arts. Guided by an Action Research approach, this work applies Lefebvre’s triad of space (1991) to investigate the Edge as a social space from a conceived, perceived and lived point of view. Based on its creators’ vision and goals on the conceived level, different embodied media are iteratively designed, implemented and evaluated towards shaping and amplifying the Edge’s visitor experience on the perceived and lived level.

XML documents clustering using tensor space model - A preliminary study

A hierarchical structure is used to represent the content of the semi-structured documents such as XML and XHTML. The traditional Vector Space Model (VSM) is not sufficient to represent both the structure and the content of such web documents. Hence in this paper, we introduce a novel method of representing the XML documents in Tensor Space Model (TSM) and then utilize it for clustering. Empirical analysis shows that the proposed method is scalable for a real-life dataset as well as the factorized matrices produced from the proposed method helps to improve the quality of clusters due to the enriched document representation with both the structure and the content information.

Flagging Spaces : exploring the myth of the Australian beach as an egalitarian space

The Australian beach is now accepted as a significant part of Australian national culture and identity. However, Huntsman (2001) and Booth (2001) both believe that the beach is dying: “intellectuals have failed to apply to the beach the attention they have lavished on the bush…” (Huntsman 2001, 218). Yet the beach remains a prominent image in contemporary literature and film; authors such as Tim Winton and Robert Drewe frequently set their stories in and around the coast. Although initially considered a space of myth (Fiske, Hodge, and Turner 1987), Meaghan Morris labelled the beach as ‘ordinary’ (1998), and as recently as 2001 in the wake of the Sydney Olympic Games, Bonner, McKee, and Mackay termed the beach ‘tacky’ and ‘familiar’. The beach, it appears, defies an easy categorisation. In fact, I believe the beach is more than merely mythic or ordinary, or a combination of the two. Instead it is an imaginative space, seamlessly shifting its metaphorical meanings dependent on readings of the texts. My studies examine the beach through five common beach myths; this paper will explore the myth of the beach as an egalitarian space. Contemporary Australian national texts no longer conform to these mythical representations – (in fact, was the beach ever a space of equality?), instead creating new definitions for the beach space that continually shifts in meaning. Recent texts such as Tim Winton’s Breath (2008) and Stephen Orr’s Time’s Long Ruin (2010) lay a more complex metaphorical meaning upon the beach space. This paper will explore the beach as a space of egalitarianism in conjunction with recent Australian fiction and films in order to discover how the contemporary beach is represented.

Empirical Bayes method in the study of traffic safety via heterogeneous negative multinomial model

In the study of traffic safety, expected crash frequencies across sites are generally estimated via the negative binomial model, assuming time invariant safety. Since the time invariant safety assumption may be invalid, Hauer (1997) proposed a modified empirical Bayes (EB) method. Despite the modification, no attempts have been made to examine the generalisable form of the marginal distribution resulting from the modified EB framework. Because the hyper-parameters needed to apply the modified EB method are not readily available, an assessment is lacking on how accurately the modified EB method estimates safety in the presence of the time variant safety and regression-to-the-mean (RTM) effects. This study derives the closed form marginal distribution, and reveals that the marginal distribution in the modified EB method is equivalent to the negative multinomial (NM) distribution, which is essentially the same as the likelihood function used in the random effects Poisson model. As a result, this study shows that the gamma posterior distribution from the multivariate Poisson-gamma mixture can be estimated using the NM model or the random effects Poisson model. This study also shows that the estimation errors from the modified EB method are systematically smaller than those from the comparison group method by simultaneously accounting for the RTM and time variant safety effects. Hence, the modified EB method via the NM model is a generalisable method for estimating safety in the presence of the time variant safety and the RTM effects.

Negative mood, implicit alcohol-related memory, and alcohol use in young adults: The moderating effect of alcohol expectancy

Objective Alcohol-related implicit (preconscious) cognitive processes are established and unique predictors of alcohol use, but most research in this area has focused on alcohol-related implicit cognition and anxiety. This study extends this work into the area of depressed mood by testing a cognitive model that combines traditional explicit (conscious and considered) beliefs, implicit alcohol-related memory associations (AMAs), and self-reported drinking behavior. Method Using a sample of 106 university students, depressed mood was manipulated using a musical mood induction procedure immediately prior to completion of implicit then explicit alcohol-related cognition measures. A bootstrapped two-group (weak/strong expectancies of negative affect and tension reduction) structural equation model was used to examine how mood changes and alcohol-related memory associations varied across groups. Results Expectancies of negative affect moderated the association of depressed mood and AMAs, but there was no such association for tension reduction expectancy. Conclusion Subtle mood changes may unconsciously trigger alcohol-related memories in vulnerable individuals. Results have implications for addressing subtle fluctuations in depressed mood among young adults at risk of alcohol problems.

Grounding action in visuo-haptic space using experience networks

Traditional approaches to the use of machine learning algorithms do not provide a method to learn multiple tasks in one-shot on an embodied robot. It is proposed that grounding actions within the sensory space leads to the development of action-state relationships which can be re-used despite a change in task. A novel approach called an Experience Network is developed and assessed on a real-world robot required to perform three separate tasks. After grounded representations were developed in the initial task, only minimal further learning was required to perform the second and third task.

Countering negative country of origin effects using imagery processing

A favorable product country of origin (e.g., an automobile made in Germany) is often considered an asset by marketers. Yet a challenge in today's competitive environment is how marketers of products from less favorably regarded countries can counter negative country of origin perceptions. Three studies investigate how mental imagery can be used to reduce the effects of negative country of origin stereotypes. Study 1 reveals that participants exposed to country of origin information exhibit automatic stereotype activation. Study 2 shows that self-focused counterstereotypical mental imagery (relative to other-focused mental imagery) significantly inhibits the automatic activation of negative country of origin stereotypes. Study 3 shows that this lessening of automatic negative associations persists when measured one day later. The results offer important implications for marketing theory and practice.

Increased traffic exposure and negative birth outcomes : a prospective cohort in Australia

Background: Pregnant women exposed to traffic pollution have an increased risk of negative birth outcomes. We aimed to investigate the size of this risk using a prospective cohort of 970 mothers and newborns in Logan, Queensland. ----- ----- Methods: We examined two measures of traffic: distance to nearest road and number of roads around the home. To examine the effect of distance we used the number of roads around the home in radii from 50 to 500 metres. We examined three road types: freeways, highways and main roads.----- ----- Results: There were no associations with distance to road. A greater number of freeways and main roads around the home were associated with a shorter gestation time. There were no negative impacts on birth weight, birth length or head circumference after adjusting for gestation. The negative effects on gestation were largely due to main roads within 400 metres of the home. For every 10 extra main roads within 400 metres of the home, gestation time was reduced by 1.1% (95% CI: -1.7, -0.5; p-value = 0.001).----- ----- Conclusions: Our results add weight to the association between exposure to traffic and reduced gestation time. This effect may be due to the chemical toxins in traffic pollutants, or because of disturbed sleep due to traffic noise.

Rural activity spaces and transport disadvantage : qualitative analysis of quantitative models integrating time and space

Current knowledge about the relationship between transport disadvantage and activity space size is limited to urban areas, and as a result, very little is known to date about this link in a rural context. In addition, although research has identified transport disadvantaged groups based on their size of activity spaces, these studies have, however, not empirically explained such differences and the result is often a poor identification of the problems facing disadvantaged groups. Research has shown that transport disadvantage varies over time. The static nature of analysis using the activity space concept in previous research studies has lacked the ability to identify transport disadvantage in time. Activity space is a dynamic concept; and therefore possesses a great potential in capturing temporal variations in behaviour and access opportunities. This research derives measures of the size and fullness of activity spaces for 157 individuals for weekdays, weekends, and for a week using weekly activity-travel diary data from three case study areas located in rural Northern Ireland. Four focus groups were also conducted in order to triangulate the quantitative findings and to explain the differences between different socio-spatial groups. The findings of this research show that despite having a smaller sized activity space, individuals were not disadvantaged because they were able to access their required activities locally. Car-ownership was found to be an important life line in rural areas. Temporal disaggregation of the data reveals that this is true only on weekends due to a lack of public transport services. In addition, despite activity spaces being at a similar size, the fullness of activity spaces of low-income individuals was found to be significantly lower compared to their high-income counterparts. Focus group data shows that financial constraint, poor connections both between public transport services and between transport routes and opportunities forced individuals to participate in activities located along the main transport corridors.

Redland Youth Space development: evaluation report

This report provides an evaluation of the Capalaba Youth Space.The evaluation included elements of process and impact evaluation and used a participatory action research approach informed by engagement processes, focus groups, a community survey, interviews and secondary analysis of existing data.

Asset life prediction and maintenance decision-making using a non-linear non-Gaussian state space model

Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.