CO2 emissions from the combustion of native Australian trees

Carbon dioxide (CO2), as a primary product of combustion, is a known factor affecting climate change and global warming. In Australia, CO2 emissions from biomass burning are a significant contributor to total carbon in the atmosphere and therefore, it is important to quantify the CO2 emission factors from biomass burning in order to estimate their magnitude and impact on the Australian atmosphere. This paper presents the quantification of CO2 emission factors for five common tree species found in South East Queensland forests, as well as several grasses taken from savannah lands in the Northern Territory of Australia, under controlled ‘fast burning’ and ‘slow burning’ laboratory conditions. The results showed that CO2 emission factors varied according to the type of vegetation and burning conditions, with emission factors for fast burning being 2574 ± 254 g/kg for wood, 394 ± 40 g/kg for branches and leaves, and 2181 ± 120 g/kg for grass. Under slow burning conditions, the CO2 emission factors were 218 ± 20 g/kg for wood, 392± 80 g/kg for branches and leaves, and 2027 ± 809 g/kg for grass.

Natural history of trees

Courtney Pedersen and Charles Robb's A Natural History of Trees was a installation mounted at Blindside ARI in Melbourne's CBD in 2012. The work took the form of a pine-panelled room containing a pair of life-sized tree trunks composed entirely of stacks of cut paper discs. A faux bois stool reinforced the sense of artificiality. Claustrophic and precarious, the installation was simultaneously a response to the complexity of our relationship with nature and place, and an evocation of the precarious quality of the collaborative process. The exhibition was accompanied by a catalogue with an essay by writer/curator, Jane O'Neill.

Trees along our travelling tracks

This creative non-fiction piece of writing speaks to the ‘tree’ themed edition of the About Place Journal. It begins with…“This tree stands steadfast along my inland travelling track, near the town of Mundubbera on the land of the Wakka Wakka people. It is in the region called North Burnett. When we travel, we follow the river systems and look out for distinct markers in the landscape. We acknowledge the lands of others as we move down to Booburrgan Ngmmunge (the language term used by many Aboriginal people to describe the Bunya Mountains) and beyond”. The piece includes photograph images also taken by the author.

A novel method for finding similarities between unordered trees using matrix data model

Trees are capable of portraying the semi-structured data which is common in web domain. Finding similarities between trees is mandatory for several applications that deal with semi-structured data. Existing similarity methods examine a pair of trees by comparing through nodes and paths of two trees, and find the similarity between them. However, these methods provide unfavorable results for unordered tree data and result in yielding NP-hard or MAX-SNP hard complexity. In this paper, we present a novel method that encodes a tree with an optimal traversing approach first, and then, utilizes it to model the tree with its equivalent matrix representation for finding similarity between unordered trees efficiently. Empirical analysis shows that the proposed method is able to achieve high accuracy even on the large data sets.

Campaigning for street trees, Sydney Botanic Gardens, 1890s to 1920s

Between the 1890s and 1920s street trees became a more prominent feature in streetscapes across New South Wales, Australia. The Sydney Botanic Gardens, with their extensive nursery system, were responsible for supplying seedlings to councils and municipalities for use as street trees. As such, this institution was a primary mover of what a street tree should be, how they should be used and what plants were best suited to this particular use in urban environments. This paper analyses the nurturing of this use of street trees by the Sydney Botanic Gardens and the Director Joseph Maiden. This institution was a place that moved not just stock and seedlings, but ideas about how nature's inclusion into urban environments had the capacity to influence and enhance the cultivation of civilised citizens. This was affected through access to transnational resources available to the Sydney Botanic Gardens.

Medieval knights amid the gum-trees : the experience of European heritage tourism in south-east Queensland, Australia

This paper is interested in the way in which the heritage of another place, time, and culture is repurposed for popular consumption in an experience economy, as well as the way in which the visitors experience their own past and the past of others. We trace the processes of engagement, education and nostalgia that occur when the European heritage is presented in a postcolonial context and an Australian environment. The information presented includes the results of qualitative and quantitative research conducted at the Abbey Museum over the December-Jan. period of 2012-13.

Rescaling clustering trees using impact ratios for robust hierarchical speaker clustering

We present a novel method for improving hierarchical speaker clustering in the tasks of speaker diarization and speaker linking. In hierarchical clustering, a tree can be formed that demonstrates various levels of clustering. We propose a ratio that expresses the impact of each cluster on the formation of this tree and use this to rescale cluster scores. This provides score normalisation based on the impact of each cluster. We use a state-of-the-art speaker diarization and linking system across the SAIVT-BNEWS corpus to show that our proposed impact ratio can provide a relative improvement of 16% in diarization error rate (DER).

Now we can “see the forest and the trees too” but there are risks : Camera trapping and privacy law in Australia

The use of camera traps in wildlife management is an increasingly common practice. A phenomenon which is also becoming more common is for such camera traps to unintentionally film individuals engaged in a variety of activities, ranging from the innocent to the nefarious and including lewd or potentially embarrassing behaviour. It is therefore possible for the use of camera traps to accidentally encroach upon the privacy rights of persons who venture into the area of surveillance. In this chapter we describe the legal framework of privacy in Australia and discuss the potential risk of this sleeping tiger for users of camera traps. We also present the results of a survey of camera trap users to assess the frequency of such unintended captures and the nature of activity being filmed before discussing the practical implications of these laws for camera traps users in this country and make recommendations.

Using decision trees to understand structure in missing data

Objectives Demonstrate the application of decision trees – classification and regression trees (CARTs), and their cousins, boosted regression trees (BRTs) – to understand structure in missing data. Setting Data taken from employees at three different industry sites in Australia. Participants 7915 observations were included. Materials and Methods The approach was evaluated using an occupational health dataset comprising results of questionnaires, medical tests, and environmental monitoring. Statistical methods included standard statistical tests and the ‘rpart’ and ‘gbm’ packages for CART and BRT analyses, respectively, from the statistical software ‘R’. A simulation study was conducted to explore the capability of decision tree models in describing data with missingness artificially introduced. Results CART and BRT models were effective in highlighting a missingness structure in the data, related to the Type of data (medical or environmental), the site in which it was collected, the number of visits and the presence of extreme values. The simulation study revealed that CART models were able to identify variables and values responsible for inducing missingness. There was greater variation in variable importance for unstructured compared to structured missingness. Discussion Both CART and BRT models were effective in describing structural missingness in data. CART models may be preferred over BRT models for exploratory analysis of missing data, and selecting variables important for predicting missingness. BRT models can show how values of other variables influence missingness, which may prove useful for researchers. Conclusion Researchers are encouraged to use CART and BRT models to explore and understand missing data.

Can’t see the trees for the forest? Why IS-ServQual items matter

Despite longstanding concern with the dimensionality of the service quality construct as measured by ServQual and IS-ServQual instruments, variations on the IS-ServQual instrument have been enduringly prominent in both academic research and practice in the field of IS. We explain the continuing popularity of the instrument based on the salience of the item set for predicting overall customer satisfaction, suggesting that the preoccupation with the dimensions has been a distraction. The implicit mutual exclusivity of the items suggests a more appropriate conceptualization of IS-ServQual as a formative index. This conceptualization resolves the paradox in IS-ServQual research, that of how an instrument with such well-known and well-documented weaknesses continue to be very influential and widely used by academics and practitioners. A formative conceptualization acknowledges and addresses the criticisms of IS-ServQual, while simultaneously explaining its enduring salience by focusing on the items rather than the “dimensions.” By employing an opportunistic sample and adopting the most recent IS-ServQual instrument published in a leading IS journal (virtually, any valid IS- ServQual sample in combination with a previously tested instrument variant would suffice for study purposes), we demonstrate that when re-specified as both first-order and second-order formatives, IS-ServQual has good model quality metrics and high predictive power on customer satisfaction. We conclude that this formative specification has higher practical use and is more defensible theoretically.

Decision trees for detection of activity intensity in youth with cerebral palsy

PURPOSE To develop and test decision tree (DT) models to classify physical activity (PA) intensity from accelerometer output and Gross Motor Function Classification System (GMFCS) classification level in ambulatory youth with cerebral palsy (CP); and 2) compare the classification accuracy of the new DT models to that achieved by previously published cut-points for youth with CP. METHODS Youth with CP (GMFCS Levels I - III) (N=51) completed seven activity trials with increasing PA intensity while wearing a portable metabolic system and ActiGraph GT3X accelerometers. DT models were used to identify vertical axis (VA) and vector magnitude (VM) count thresholds corresponding to sedentary (SED) (<1.5 METs), light PA (LPA) (>/=1.5 and <3 METs) and moderate-to-vigorous PA (MVPA) (>/=3 METs). Models were trained and cross-validated using the 'rpart' and 'caret' packages within R. RESULTS For the VA (VA_DT) and VM decision trees (VM_DT), a single threshold differentiated LPA from SED, while the threshold for differentiating MVPA from LPA decreased as the level of impairment increased. The average cross-validation accuracy for the VC_DT was 81.1%, 76.7%, and 82.9% for GMFCS levels I, II, and III, respectively. The corresponding cross-validation accuracy for the VM_DT was 80.5%, 75.6%, and 84.2%, respectively. Within each GMFCS level, the decision tree models achieved better PA intensity recognition than previously published cut-points. The accuracy differential was greatest among GMFCS level III participants, in whom the previously published cut-points misclassified 40% of the MVPA activity trials. CONCLUSION GMFCS-specific cut-points provide more accurate assessments of MVPA levels in youth with CP across the full spectrum of ambulatory ability.