The effect of multiplayer dynamic difficulty adjustment on the player experience of video games

Multiplayer Dynamic Difficulty Adjustment (mDDA) is a method of reducing the difference in player performance and subsequent challenge in competitive multiplayer video games. As a balance of between player skill and challenge experienced is necessary for optimal player experience, this experimental study investigates the effects of mDDA and awareness of its presence on player performance and experience using subjective and biometric measures. Early analysis indicates that mDDA normalizes performance and challenge as expected, but awareness of its presence can reduce its effectiveness.

Hunting and gathering : new imperatives in mapping and collecting student learning data to assure quality outcomes

Assurance of learning (AOL) is a quality enhancement and quality assurance process used in higher education. It involves a process of determining programme learning outcomes and standards, and systematically gathering evidence to measure students' performance on these. The systematic assessment of whole-of-programme outcomes provides a basis for curriculum development and management, continuous improvement, and accreditation. To better understand how AOL processes operate, a national study of university practices across one discipline area, business and management, was undertaken. To solicit data on AOL practice, interviews were undertaken with a sample of business school representatives (n = 25). Two key processes emerged: (1) mapping of graduate attributes and (2) collection of assurance data. External drivers such as professional accreditation and government legislation were the primary reasons for undertaking AOL outcomes but intrinsic motivators in relation to continuous improvement were also evident. The facilitation of academic commitment was achieved through an embedded approach to AOL by the majority of universities in the study. A sustainable and inclusive process of AOL was seen to support wider stakeholder engagement in the development of higher education learning outcomes.

Classifying natural aerial scenery for autonomous aircraft emergency landing

In this paper, we present an approach for image-based surface classification using multi-class Support Vector Machine (SVM). Classifying surfaces in aerial images is an important step towards an increased aircraft autonomy in emergency landing situations. We design a one-vs-all SVM classifier and conduct experiments on five data sets. Results demonstrate consistent overall performance figures over 88% and approximately 8% more accurate to those published on multi-class SVM on the KTH TIPS data set. We also show per-class performance values by using normalised confusion matrices. Our approach is designed to be executed online using a minimum set of feature attributes representing a feasible and ready-to-deploy system for onboard execution.

Translations of industry-based student learning and academic performances

We hypothesized that Industry based learning and teaching, especially through industry assigned student projects or training programs, is an integral part of science, technology, engineering and mathematics (STEM) education. In this paper we show that industry-based student training and experience increases students’ academic performances independent to the organizational parameters and contexts. The literature on industry-based student training focuses on employability and the industry dimension, and neglects in many ways the academic dimension. We observed that the association factors between academic attributes and contributions of industry-based student training are central and vital to the technological learning experiences. We explore international initiatives and statistics collected of student projects in two categories: Industry based learning performances and on campus performances. The data collected were correlated to five (5) universities in different industrialized countries, e.g., Australia N=545, Norway N=279, Germany N=74, France N=107 and Spain N=802 respectively. We analyzed industry-based student training along with company assigned student projects compared with in comparisons to campus performance. The data that suggests a strong correlation between industry-based student training per se and improved performance profiles or increasing motivation shows that industry-based student training increases student academic performance independent of organizational parameters and contexts. The programs we augmented were orthogonal to each other however, the trend of the students’ academic performances are identical. An isolated cohort for the reported countries that opposed our hypothesis warrants further investigation.

Contribution of industry-based student learning performance for the STEM education

We hypothesized that Industry based learning and teaching, especially through company assigned student projects or training programs, is an integral part of science, technology, engineering and mathematics (STEM) education. In this paper we show that industry-based student training and experience increases students’ academic performances independent to the organizational parameters and contexts. The literature on industry-based student training focuses on employability and the industry dimension, and neglects in many ways the academic dimension. We observed that the association factors between academic attributes and contributions of industry-based student training are central and vital to the technological learning experiences. We explore international initiatives and statistics collected of student projects in two categories: Industry based learning performances and on campus performances. The data collected were correlated to five (5) universities in different industrialized countries, e.g., Australia N=545 projects, Norway N=279, Germany N=74, France N=107 and Spain N=802. We analyzed industry-based student training along with company assigned student projects compared with in comparisons to campus performance. The data that suggests a strong correlation between industry-based student training per se and improved performance profiles or increasing motivation shows that industry-based student training increases student academic performance independent of organizational parameters and contexts. The programs we augmented were orthogonal to each other however, the trend of the students’ academic performances are identical. An isolated cohort for the reported countries that opposed our hypothesis warrants further investigation.

Beyond tasks and gateways: discovering BPMN models with subprocesses, boundary events and activity markers

Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.

Epithelial mesenchymal transition traits in human breast cancer cell lines parallel the CD44HI/CD24lO/-stem cell phenotype in human breast cancer

We review here the recently emerging relationship between epithelial-mesenchymal transition (EMT) and breast cancer stem cells (BCSC), and provide analyses of published data on human breast cancer cell lines, supporting their utility as a model for the EMT/BCSC state. Genome-wide transcriptional profiling of these cell lines has confirmed the existence of a subgroup with mesenchymal tendencies and enhanced invasive properties ('Basal B'/Mesenchymal), distinct from subgroups with either predominantly luminal ('Luminal') or mixed basal/luminal ('Basal A') features (Neve et al. Cancer Cell, 2006). A literature-derived EMT gene signature has shown specific enrichment within the Basal B subgroup of cell lines, consistent with their over-expression of various EMT transcriptional drivers. Basal B cell lines are found to resemble BCSC, being CD44highCD24low. Moreover, gene products that distinguish Basal B from Basal A and Luminal cell lines (Basal B Discriminators) showed close concordance with those that define BCSC isolated from clinical material, as reported by Shipitsin et al. (Cancer Cell, 2007). CD24 mRNA levels varied across Basal B cell lines, correlating with other Basal B Discriminators. Many gene products correlating with CD24 status in Basal B cell lines were also differentially expressed in isolated BCSC. These findings confirm and extend the importance of the cellular product of the EMT with Basal B cell lines, and illustrate the value of analysing these cell lines for new leads that may improve breast cancer outcomes. Gene products specific to Basal B cell lines may serve as tools for the detection, quantification, and analysis of BCSC/EMT attributes.

Epithelial-to-mesenchymal transitions and circulating tumor cells

Epithelial-to-mesenchymal transition (EMT) phenomena endow epithelial cells with enhanced migratory and invasive potential, and as such, have been implicated in many physiological and pathological processes requiring cell migration/invasion. Although their involvement in the metastatic cascade is still a subject of debate, data are accumulating to demonstrate the existence of EMT phenotypes in primary human tumors, describe enhanced metastatic potential of EMT derivatives in animal models, and report EMT attributes in circulating tumor cells (CTCs). The relationships between EMT and CTCs remain largely unexplored, and we review here in vitro and in vivo data supporting a putative role of EMT processes in CTC generation and survival.

Implication of collagen type I-induced membrane-type 1-matrix metalloproteinase expression and matrix metalloproteinase-2 activation in the metastatic progression of breast carcinoma

We have previously demonstrated that fibroblasts and invasive human breast carcinoma (HBC) cells specifically activate matrix metalloproteinase- 2 (MMP-2) when cultured on 3-dimensional gels of type I collagen but not a range of other substrates. We show here the constitutive expression of membrane-type 1 (MT1)-MMP in both fibroblasts, and invasive HBC cell lines, that have fibroblastic attributes presumably acquired through an epithelial- to-mesenchymal transition (EMT). Treatment with collagen type I increased the steady-state MT1-MMP mRNA levels in these cells but did not induce either MT1-MMP expression or MMP-2 activation in noninvasive breast carcinoma cell lines, which retain epithelial features. Basal MT3-MMP mRNA expression had a pattern similar to that of MT1-MMP but was not up-regulated by collagen. MT4- MMP mRNA was seen in both invasive and noninvasive HBC cell lines and was also not collagen-regulated, and MT2-MMP mRNA was not detected in any of the HBC cell lines tested. These data support a role for MT1-MMP in the collagen- induced MMP-2-activation seen in these cells. In situ hybridization analysis of archival breast cancer specimens revealed a close parallel in expression of both collagen type I and MT1-MMP mRNA in peritumoral fibroblasts, which was correlated with aggressiveness of the lesion. Relatively high levels of expression of both mRNA species were seen in fibroblasts close to invasive tumor nests and, although only focally, in certain areas close to preinvasive tumors. These foci may represent hot spots for local degradation and invasive progression. Collectively, these results implicate MT1-MMP in collagen- stimulated MMP-2 activation and suggest that this mechanism may be employed in vivo by both tumor-associated fibroblasts and EMT-derived carcinoma cells to facilitate increased invasion and/or metastasis.

Spatial prediction on a river network

This article develops methods for spatially predicting daily change of dissolved oxygen (Dochange) at both sampled locations (134 freshwater sites in 2002 and 2003) and other locations of interest throughout a river network in South East Queensland, Australia. In order to deal with the relative sparseness of the monitoring locations in comparison to the number of locations where one might want to make predictions, we make a classification of the river and stream locations. We then implement optimal spatial prediction (ordinary and constrained kriging) from geostatistics. Because of their directed-tree structure, rivers and streams offer special challenges. A complete approach to spatial prediction on a river network is given, with special attention paid to environmental exceedances. The methodology is used to produce a map of Dochange predictions for 2003. Dochange is one of the variables measured as part of the Ecosystem Health Monitoring Program conducted within the Moreton Bay Waterways and Catchments Partnership.

Combined analysis of categorical and numerical descriptors of Australian groundnut accessions using nonlinear principal component analysis

For users of germplasm collections, the purpose of measuring characterization and evaluation descriptors, and subsequently using statistical methodology to summarize the data, is not only to interpret the relationships between the descriptors, but also to characterize the differences and similarities between accessions in relation to their phenotypic variability for each of the measured descriptors. The set of descriptors for the accessions of most germplasm collections consists of both numerical and categorical descriptors. This poses problems for a combined analysis of all descriptors because few statistical techniques deal with mixtures of measurement types. In this article, nonlinear principal component analysis was used to analyze the descriptors of the accessions in the Australian groundnut collection. It was demonstrated that the nonlinear variant of ordinary principal component analysis is an appropriate analytical tool because subspecies and botanical varieties could be identified on the basis of the analysis and characterized in terms of all descriptors. Moreover, outlying accessions could be easily spotted and their characteristics established. The statistical results and their interpretations provide users with a more efficient way to identify accessions of potential relevance for their plant improvement programs and encourage and improve the usefulness and utilization of germplasm collections.

A comparison of spatially explicit landscape representation methods and their relationship to stream condition

1. Biodiversity, water quality and ecosystem processes in streams are known to be influenced by the terrestrial landscape over a range of spatial and temporal scales. Lumped attributes (i.e. per cent land use) are often used to characterise the condition of the catchment; however, they are not spatially explicit and do not account for the disproportionate influence of land located near the stream or connected by overland flow. 2. We compared seven landscape representation metrics to determine whether accounting for the spatial proximity and hydrological effects of land use can be used to account for additional variability in indicators of stream ecosystem health. The landscape metrics included the following: a lumped metric, four inverse-distance-weighted (IDW) metrics based on distance to the stream or survey site and two modified IDW metrics that also accounted for the level of hydrologic activity (HA-IDW). Ecosystem health data were obtained from the Ecological Health Monitoring Programme in Southeast Queensland, Australia and included measures of fish, invertebrates, physicochemistry and nutrients collected during two seasons over 4 years. Linear models were fitted to the stream indicators and landscape metrics, by season, and compared using an information-theoretic approach. 3. Although no single metric was most suitable for modelling all stream indicators, lumped metrics rarely performed as well as other metric types. Metrics based on proximity to the stream (IDW and HA-IDW) were more suitable for modelling fish indicators, while the HA-IDW metric based on proximity to the survey site generally outperformed others for invertebrates, irrespective of season. There was consistent support for metrics based on proximity to the survey site (IDW or HA-IDW) for all physicochemical indicators during the dry season, while a HA-IDW metric based on proximity to the stream was suitable for five of the six physicochemical indicators in the post-wet season. Only one nutrient indicator was tested and results showed that catchment area had a significant effect on the relationship between land use metrics and algal stable isotope ratios in both seasons. 4. Spatially explicit methods of landscape representation can clearly improve the predictive ability of many empirical models currently used to study the relationship between landscape, habitat and stream condition. A comparison of different metrics may provide clues about causal pathways and mechanistic processes behind correlative relationships and could be used to target restoration efforts strategically.

Conceptualising, evaluating and reporting social resilience in vulnerable regional and remote communities facing climate change in tropical Queensland : marine and tropical sciences research facility transition project final report

Regional and remote communities in tropical Queensland are among Australia’s most vulnerable in the face of climate change. At the same time, these socially and economically vulnerable regions house some of Australia’s most significant biodiversity values. Past approaches to terrestrial biodiversity management have focused on tackling biophysical interventions through the use of biophysical knowledge. An equally important focus should be placed on building regional-scale community resilience if some of the worst biodiversity impacts of climate change are to be avoided or mitigated. Despite its critical need, more systemic or holistic approaches to natural resource management have been rarely trialed and tested in a structured way. Currently, most strategic interventions in improving regional community resilience are ad hoc, not theory-based and short term. Past planning approaches have not been durable, nor have they been well informed by clear indicators. Research into indicators for community resilience has been poorly integrated within adaptive planning and management cycles. This project has aimed to resolve this problem by: * Reviewing the community and social resilience and adaptive planning literature to reconceptualise an improved framework for applying community resilience concepts; * Harvesting and extending work undertaken in MTSRF Phase 1 to identifying the learnings emerging from past MTSRF research; * Distilling these findings to identify new theoretical and practical approaches to the application of community resilience in natural resource use and management; * Reconsidering the potential interplay between a region’s biophysical and social planning processes, with a focus on exploring spatial tools to communicate climate change risk and its consequent environmental, economic and social impacts, and; * Trialling new approaches to indicator development and adaptive planning to improve community resilience, using a sub-regional pilot in the Wet Tropics. In doing so, we also looked at ways to improve the use and application of relevant spatial information. Our theoretical review drew upon the community development, psychology and emergency management literature to better frame the concept of community resilience relative to aligned concepts of social resilience, vulnerability and adaptive capacity. Firstly, we consider community resilience as a concept that can be considered at a range of scales (e.g. regional, locality, communities of interest, etc.). We also consider that overall resilience at higher scales will be influenced by resilience levels at lesser scales (inclusive of the resilience of constituent institutions, families and individuals). We illustrate that, at any scale, resilience and vulnerability are not necessarily polar opposites, and that some understanding of vulnerability is important in determining resilience. We position social resilience (a concept focused on the social characteristics of communities and individuals) as an important attribute of community resilience, but one that needs to be considered alongside economic, natural resource, capacity-based and governance attributes. The findings from the review of theory and MTSRF Phase 1 projects were synthesized and refined by the wider project team. Five predominant themes were distilled from this literature, research review and an expert analysis. They include the findings that: 1. Indicators have most value within an integrated and adaptive planning context, requiring an active co-research relationship between community resilience planners, managers and researchers if real change is to be secured; 2. Indicators of community resilience form the basis for planning for social assets and the resilience of social assets is directly related the longer term resilience of natural assets. This encourages and indeed requires the explicit development and integration of social planning within a broader natural resource planning and management framework; 3. Past indicator research and application has not provided a broad picture of the key attributes of community resilience and there have been many attempts to elicit lists of “perfect” indicators that may never be useful within the time and resource limitations of real world regional planning and management. We consider that modeling resilience for proactive planning and prediction purposes requires the consideration of simple but integrated clusters of attributes; 4. Depending on time and resources available for planning and management, the combined use of well suited indicators and/or other lesser “lines of evidence” is more flexible than the pursuit of perfect indicators, and that; 5. Index-based, collaborative and participatory approaches need to be applied to the development, refinement and reporting of indicators over longer time frames. We trialed the practical application of these concepts via the establishment of a collaborative regional alliance of planners and managers involved in the development of climate change adaptation strategies across tropical Queensland (the Gulf, Wet Tropics, Cape York and Torres Strait sub-regions). A focus on the Wet Tropics as a pilot sub-region enabled other Far North Queensland sub-region’s to participate and explore the potential extension of this approach. The pilot activities included: * Further exploring ways to innovatively communicate the region’s likely climate change scenarios and possible environmental, economic and social impacts. We particularly looked at using spatial tools to overlay climate change risks to geographic communities and social vulnerabilities within those communities; * Developing a cohesive first pass of a State of the Region-style approach to reporting community resilience, inclusive of regional economic viability, community vitality, capacitybased and governance attributes. This framework integrated a literature review, expert (academic and community) and alliance-based contributions; and * Early consideration of critical strategies that need to be included in unfolding regional planning activities with Far North Queensland. The pilot assessment finds that rural, indigenous and some urban populations in the Wet Tropics are highly vulnerable and sensitive to climate change and may require substantial support to adapt and become more resilient. This assessment finds that under current conditions (i.e. if significant adaptation actions are not taken) the Wet Tropics as a whole may be seriously impacted by the most significant features of climate change and extreme climatic events. Without early and substantive action, this could result in declining social and economic wellbeing and natural resource health. Of the four attributes we consider important to understanding community resilience, the Wet Tropics region is particularly vulnerable in two areas; specifically its economic vitality and knowledge, aspirations and capacity. The third and fourth attributes, community vitality and institutional governance are relatively resilient but are vulnerable in some key respects. In regard to all four of these attributes, however, there is some emerging capacity to manage the possible shocks that may be associated with the impacts of climate change and extreme climatic events. This capacity needs to be carefully fostered and further developed to achieve broader community resilience outcomes. There is an immediate need to build individual, household, community and sectoral resilience across all four attribute groups to enable populations and communities in the Wet Tropics region to adapt in the face of climate change. Preliminary strategies of importance to improve regional community resilience have been identified. These emerging strategies also have been integrated into the emerging Regional Development Australia Roadmap, and this will ensure that effective implementation will be progressed and coordinated. They will also inform emerging strategy development to secure implementation of the FNQ 2031 Regional Plan. Of most significance in our view, this project has taken a co-research approach from the outset with explicit and direct importance and influence within the region’s formal planning and management arrangements. As such, the research: * Now forms the foundations of the first attempt at “Social Asset” planning within the Wet Tropics Regional NRM Plan review; * Is assisting Local government at regional scale to consider aspects of climate change adaptation in emerging planning scheme/community planning processes; * Has partnered the State government (via the Department of Infrastructure and Planning and Regional Managers Coordination Network Chair) in progressing the Climate Change adaptation agenda set down within the FNQ 2031 Regional Plan; * Is informing new approaches to report on community resilience within the GBRMPA Outlook reporting framework; and * Now forms the foundation for the region’s wider climate change adaptation priorities in the Regional Roadmap developed by Regional Development Australia. Through the auspices of Regional Development Australia, the outcomes of the research will now inform emerging negotiations concerning a wider package of climate change adaptation priorities with State and Federal governments. Next stage research priorities are also being developed to enable an ongoing alliance between researchers and the region’s climate change response.

Corporate governance and securities class actions

This study investigates the governance attributes of firms that have been subject to securities class actions (SCAs). There has been a recent sizable increase in the number of firms subject to SCAs in Australia. We examine a sample of firms that have been subject to SCAs due to disclosure breaches and match the firms by industry and size to a control sample. First, we examine the compliance culture of the SCA firms via the frequency of Australian Securities Exchange (ASX)queries of the firm and find that the frequency of ASX queries is positively associated with the occurrence of a SCA. Secondly, we provide evidence that SCA firms exhibit weaker levels of corporate governance than the matched control sample. In addition, we contribute to the understanding of firms subject to SCAs and their corporate governance attributes. Our results suggest the presence of a nomination committee may be associated with higher agency costs and that the influence of CEO duality may reduce the effectiveness of a nomination committee.

Evaluations of BIM : frameworks and perspectives

This paper examines the evaluation of BIM-enabled projects. It provides a critical review of the three main areas of measurement, namely technology, organization/people and process. Using two documented case studies of BIM implementation, the paper illustrates the benefits realized by project owners and contractors, and illustrates a lack of attention relative to contextual factors affecting the adoption and deployment of BIM. The paper has three main contributions. First, it identifies and discusses the lack of and difficulty surrounding standardized assessment methods for evaluating BIM-enabled projects. Second, it proposes a conceptual model that includes contextual attributes and demonstrates how the proposed framework reaches beyond simple evaluation to encompass the documentation of BIM’s benefits, lessons learned, challenges and adopted solutions. Third, it shows how the framework can account for existing business processes, organizational process assets, and enterprise level factors. The paper aims to provide a conceptual basis for evaluation and a starting point for benchmarking.