Complete and interpretable conformance checking of business processes

This article presents a method for checking the conformance between an event log capturing the actual execution of a business process, and a model capturing its expected or normative execution. Given a business process model and an event log, the method returns a set of statements in natural language describing the behavior allowed by the process model but not observed in the log and vice versa. The method relies on a unified representation of process models and event logs based on a well-known model of concurrency, namely event structures. Specifically, the problem of conformance checking is approached by folding the input event log into an event structure, unfolding the process model into another event structure, and comparing the two event structures via an error-correcting synchronized product. Each behavioral difference detected in the synchronized product is then verbalized as a natural language statement. An empirical evaluation shows that the proposed method scales up to real-life datasets while producing more concise and higher-level difference descriptions than state-of-the-art conformance checking methods.

Understanding local processes: Contemplating franchisation

Increasing, there is growing acknowledgement of the importance of franchising within all modern global economies. Despite this, little is understood with regards the actual impact of franchising on local economies. This research aims to reframe the contribution of franchising by considering the process of franchisation. This study employed a mixed-method approach, utilizing critical realism to facilitate an outcomes-based explanation of firm survival. The focus of the study was upon generative mechanisms that were assumed to give rise to particular events from which (pizza) firm survival was enhanced vis-à-vis all other community members. A database of 2440 firms (or in excess of 21,000 company years) combined with archival records, interviews and the researcher’s observations provided the researcher with access to the nature of interaction occurring between firms. It was found that the survival of local firms was influenced positively by the day-to-day actions of franchise operators. However, it is argued that to understand how any such advantage my fall to local independent firms, we need too better appreciate the multitude of local processes related to such industries. This research re-examines several ecological concepts with the view of enabling a clearer investigation of underlying local processes. It also represents an authentic autecological approach to the study of firms.

Establishing turf grass increases soil greenhouse gas emissions in peri-urban environments

Urbanization is becoming increasingly important in terms of climate change and ecosystem functionality worldwide. We are only beginning to understand how the processes of urbanization influence ecosystem dynamics and how peri-urban environments contribute to climate change. Brisbane in South East Queensland (SEQ) currently has the most extensive urban sprawl of all Australian cities. This leads to substantial land use changes in urban and peri-urban environments and the subsequent gaseous emissions from soils are to date neglected for IPCC climate change estimations. This research examines how land use change effects methane (CH4) and nitrous oxide (N2O) fluxes from peri-urban soils and consequently influences the Global Warming Potential (GWP) of rural ecosystems in agricultural use undergoing urbanization. Therefore, manual and fully automated static chamber measurements determined soil gas fluxes over a full year and an intensive sampling campaign of 80 days after land use change. Turf grass, as the major peri-urban land cover, increased the GWP by 415 kg CO2-e ha 1 over the first 80 days after conversion from a well-established pasture. This results principally from increased daily average N2O emissions of 0.5 g N2O ha-1 d-1 from the pasture to 18.3 g N2O ha-1 d-1 from the turf grass due to fertilizer application during conversion. Compared to the native dry sclerophyll eucalypt forest, turf grass establishment increases the GWP by another 30 kg CO2-e ha 1. The results presented in this study clearly indicate the substantial impact of urbanization on soil-atmosphere gas exchange in form of non-CO2 greenhouse gas emissions particularly after turf grass establishment.

Organizational competencies and dynamic Accounting Information System capability: Impact on AIS processes and firm performance

Accounting information systems (AIS) capture and process accounting data and provide valuable information for decision-makers. However, in a rapidly changing environment, continual management of the AIS is necessary for organizations to optimise performance outcomes. We suggest that building a dynamic AIS capability enables accounting process and organizational performance. Using the dynamic capabilities framework (Teece 2007) we propose that a dynamic AIS capability can be developed through the synergy of three competencies: a flexible AIS, having a complementary business intelligence system and accounting professionals with IT technical competency. Using survey data, we find evidence of a positive association between a dynamic AIS capability, accounting process performance, and overall firm performance. The results suggest that developing a dynamic AIS resource can add value to an organization. This study provides guidance for organizations looking to leverage the performance outcomes of their AIS environment.

Standardization efforts: The relationship between knowledge dimensions, search processes and innovation outcomes

We explore how a standardization effort (i.e., when a firm pursues standards to further innovation) involves different search processes for knowledge and innovation outcomes. Using an inductive case study of Vanke, a leading Chinese property developer, we show how varying degrees of knowledge complexity and codification combine to produce a typology of four types of search process: active, integrative, decentralized and passive, resulting in four types of innovation outcome: modular, radical, incremental and architectural. We argue that when the standardization effort in a firm involves highly codified knowledge, incremental and architectural innovation outcomes are fostered, while modular and radical innovations are hindered. We discuss how standardization efforts can result in a second-order innovation capability, and conclude by calling for comparative research in other settings to understand how standardization efforts can be suited to different types of search process in different industry contexts.

A preliminary investigation into technology and processes facilitating the assurance of learning

This paper reports on the outcomes from a preliminary evaluation of technologies and processes intended to support the Assurance of Learning initiative in the business faculty of an Australian university. The study investigated how existing institutional information systems and operational processes could be used to support direct measures of student learning and the attainment of intended learning goals. The levels at which learning outcomes had been attained were extracted from the University Learning Management System (LMS), based on rubric data for three assessments in two units. Spreadsheets were used to link rubric criteria to the learning goals associated with the assessments as identified in a previous curriculum mapping exercise, and to aggregate the outcomes. Recommendations arising from this preliminary study are made to inform a more comprehensive pilot based on this approach, and manage the quality of student learning experiences in the context of existing processes and reporting structures.

Build-up of toxic metals on the impervious surfaces of a commercial seaport

In the context of increasing threats to the sensitive marine ecosystem by toxic metals, this study investigated the metal build-up on impervious surfaces specific to commercial seaports. The knowledge generated in this study will contribute to managing toxic metal pollution of the marine ecosystem. The study found that inter-modal operations and main access roadway had the highest loads followed by container storage and vehicle marshalling sites, while the quay line and short term storage areas had the lowest. Additionally, it was found that Cr, Al, Pb, Cu and Zn were predominantly attached to solids, while significant amount of Cu, Pb and Zn were found as nutrient complexes. As such, treatment options based on solids retention can be effective for some metal species, while ineffective for other species. Furthermore, Cu and Zn are more likely to become bioavailable in seawater due to their strong association with nutrients. Mathematical models to replicate the metal build-up process were also developed using experimental design approach and partial least square regression. The models for Cr and Pb were found to be reliable, while those for Al, Zn and Cu were relatively less reliable, but could be employed for preliminary investigations.

Assessing uncertainty in pollutant build-up and wash-off processes

Assessing build-up and wash-off process uncertainty is important for accurate interpretation of model outcomes to facilitate informed decision making for developing effective stormwater pollution mitigation strategies. Uncertainty inherent to pollutant build-up and wash-off processes influences the variations in pollutant loads entrained in stormwater runoff from urban catchments. However, build-up and wash-off predictions from stormwater quality models do not adequately represent such variations due to poor characterisation of the variability of these processes in mathematical models. The changes to the mathematical form of current models with the incorporation of process variability, facilitates accounting for process uncertainty without significantly affecting the model prediction performance. Moreover, the investigation of uncertainty propagation from build-up to wash-off confirmed that uncertainty in build-up process significantly influences wash-off process uncertainty. Specifically, the behaviour of particles <150µm during build-up primarily influences uncertainty propagation, resulting in appreciable variations in the pollutant load and composition during a wash-off event.

Integrating urban ecosystem sustainability assessment into policy-making: Insights from the Gold Coast City

This paper introduces a policy-making support tool called ‘Micro-level Urban ecosystem Sustainability IndeX (MUSIX)’. The index serves as a sustainability assessment model that monitors six aspects of urban ecosystems, hydrology, ecology, pollution, location, design, and efficiency based on parcel-scale indicators. This index is applied in a case study investigation in the Gold Coast City, Queensland, Australia. The outcomes reveal that there are major environmental problems caused by increased impervious surfaces from growing urban development in the study area. The findings suggest that increased impervious surfaces are linked to increased surface runoff, car dependency, transport-related pollution, poor public transport accessibility, and unsustainable built environment. This paper presents how the MUSIX outputs can be used to guide policy-making through the evaluation of existing policies.

Incorporating the interrelationship between primary and support processes in monitoring and optimising longwall coal mining efficiency

This thesis increased the researchers understanding of the relationship between operations and maintenance in underground longwall coal mines, using data from a Queensland underground coal mine. The thesis explores various relationships between recorded variables. Issues with human recorded data was uncovered, and results emphasised the significance of variables associated with conveyor operation to explain production.

Brief for GSDR - Emerging Contaminants in urban stormwater: Challenges and perspectives for sustainable water use

Emerging contaminants (ECs) are chemical compounds commonly present in water. It is only recently that this family of compounds is being recognized as significant water pollutants (. ECs include a wide variety of chemicals such as pharmaceutical and personal care products (PPCPs), pesticides, hydrocarbons and hormones, among others, that once released into the environment exert adverse impacts on the human and wildlife endocrine system. Natural attenuation and conventional treatment processes are not capable of removing these micro-pollutants detected in wastewater influent and effluent and surface and drinking water. The main challenges related with presence of ECs in stormwater in the context of reuse are: a) Development of suitable laboratory test methodologies and protocols for ECs identification and quantification b) Identification of the sources of ECs in the urban environment; c) Understanding their impacts on human and/or ecosystem health; and d). Development of cost-effective removal technologies which are appropriate for large as well as small-scale application.

Inflammation-driven bone formation in a mouse model of ankylosing spondylitis: Sequential not parallel processes

Background Ankylosing spondylitis (AS) is an immune-mediated arthritis particularly targeting the spine and pelvis and is characterised by inflammation, osteoproliferation and frequently ankylosis. Current treatments that predominately target inflammatory pathways have disappointing efficacy in slowing disease progression. Thus, a better understanding of the causal association and pathological progression from inflammation to bone formation, particularly whether inflammation directly initiates osteoproliferation, is required. Methods The proteoglycan-induced spondylitis (PGISp) mouse model of AS was used to histopathologically map the progressive axial disease events, assess molecular changes during disease progression and define disease progression using unbiased clustering of semi-quantitative histology. PGISp mice were followed over a 24-week time course. Spinal disease was assessed using a novel semi-quantitative histological scoring system that independently evaluated the breadth of pathological features associated with PGISp axial disease, including inflammation, joint destruction and excessive tissue formation (osteoproliferation). Matrix components were identified using immunohistochemistry. Results Disease initiated with inflammation at the periphery of the intervertebral disc (IVD) adjacent to the longitudinal ligament, reminiscent of enthesitis, and was associated with upregulated tumor necrosis factor and metalloproteinases. After a lag phase, established inflammation was temporospatially associated with destruction of IVDs, cartilage and bone. At later time points, advanced disease was characterised by substantially reduced inflammation, excessive tissue formation and ectopic chondrocyte expansion. These distinct features differentiated affected mice into early, intermediate and advanced disease stages. Excessive tissue formation was observed in vertebral joints only if the IVD was destroyed as a consequence of the early inflammation. Ectopic excessive tissue was predominantly chondroidal with chondrocyte-like cells embedded within collagen type II- and X-rich matrix. This corresponded with upregulation of mRNA for cartilage markers Col2a1, sox9 and Comp. Osteophytes, though infrequent, were more prevalent in later disease. Conclusions The inflammation-driven IVD destruction was shown to be a prerequisite for axial disease progression to osteoproliferation in the PGISp mouse. Osteoproliferation led to vertebral body deformity and fusion but was never seen concurrent with persistent inflammation, suggesting a sequential process. The findings support that early intervention with anti-inflammatory therapies will be needed to limit destructive processes and consequently prevent progression of AS.

Social processes of health and physical education teachers’ identity formation: Reproducing and changing culture

This paper examines Initial Teacher Education students’ experiences of participation in health and physical education (HPE) subject department offices and the impact on their understandings and identity formation. Pierre Bourdieu’s concepts of habitus, field, and practice along with Wenger’s communities of practice form the theoretical frame used in the paper. Data were collected using surveys and interviews with student‐teachers following their teaching practicum and analysed using coding and constant comparison. Emergent themes revealed students’ participation in masculine‐dominated sports, gendered body constructions, and repertoires of masculine domination. Findings are discussed in relation to their impact on student‐teachers’ learning, identity formation, and marginalizing practices in the department offices. Implications for teacher education and HPE are explored.

Metal nanoparticle photocatalysts: Emerging processes for green organic synthesis

Metal nanoparticle photocatalysts have attracted recent interest due to their strong absorption of visible and ultraviolet light. The energy absorbed by the metal conduction electrons and the intense electric fields in close proximity, created by the localized surface plasmon resonance effect, makes the crucial contribution of activating the molecules on the metal nanoparticles which facilitates chemical transformation. There are now many examples of successful reactions catalyzed by supported nanoparticles of pure metals and of metal alloys driven by light at ambient or moderate temperatures. These examples demonstrate these materials are a novel group of efficient photocatalysts for converting solar energy to chemical energy and that the mechanisms are distinct from those of semiconductor photocatalysts. We present here an overview of recent research on direct photocatalysis of supported metal nanoparticles for organic synthesis under light irradiation and discuss the significant reaction mechanisms that occur through light irradiation.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.