Using Bayesian Mixture Models That Combine Expert Knowledge and GIS Data to Define Ecoregions

Conservation planning and management programs typically assume relatively homogeneous ecological landscapes. Such “ecoregions” serve multiple purposes: they support assessments of competing environmental values, reveal priorities for allocating scarce resources, and guide effective on-ground actions such as the acquisition of a protected area and habitat restoration. Ecoregions have evolved from a history of organism–environment interactions, and are delineated at the scale or level of detail required to support planning. Depending on the delineation method, scale, or purpose, they have been described as provinces, zones, systems, land units, classes, facets, domains, subregions, and ecological, biological, biogeographical, or environmental regions. In each case, they are essential to the development of conservation strategies and are embedded in government policies at multiple scales.

A recommendation system for predicting risks across multiple business process instances

This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

Go your own way : reporting of fundraising in Australian charity financial statements

Australian charities are facing increased public scrutiny of their financial reports, which must now be submitted to the national regulator, the Australian Charities and Not-for-profits Commission. Some may wish to use reports to create so-called 'fundraising efficiency league tables'. This article seeks to provide a description of current best practice in fundraising financial reporting by examining annual reports that have been recognised with industry awards. We find a wide variation in how terms have been used, with no patterns discernible. Moreoever, reporting is influenced by regulatory requirements in the relevant jurisdiction, which differ substantially. It is unlikely that league tables will be meaningful if constructed from charities' current annual financial statements.

Representing team behaviours from noisy data using player role

Due to their unobtrusive nature, vision-based approaches to tracking sports players have been preferred over wearable sensors as they do not require the players to be instrumented for each match. Unfortunately however, due to the heavy occlusion between players, variation in resolution and pose, in addition to fluctuating illumination conditions, tracking players continuously is still an unsolved vision problem. For tasks like clustering and retrieval, having noisy data (i.e. missing and false player detections) is problematic as it generates discontinuities in the input data stream. One method of circumventing this issue is to use an occupancy map, where the field is discretised into a series of zones and a count of player detections in each zone is obtained. A series of frames can then be concatenated to represent a set-play or example of team behaviour. A problem with this approach though is that the compressibility is low (i.e. the variability in the feature space is incredibly high). In this paper, we propose the use of a bilinear spatiotemporal basis model using a role representation to clean-up the noisy detections which operates in a low-dimensional space. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labeled data.

Virtual business role-play : leveraging familiar environments to prime stakeholder memory during process elicitation

Business process models have traditionally been an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach for process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions as they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. Empirical data obtained in this study suggests that this approach may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

On Merging Business Process Management and Geographic Information Systems : Modeling and Execution of Ecological Concerns in Processes

Business Process Management describes a holistic management approach for the systematic design, modeling, execution, validation, monitoring and improvement of organizational business processes. Traditionally, most attention within this community has been given to control-flow aspects, i.e., the ordering and sequencing of business activities, oftentimes in isolation with regards to the context in which these activities occur. In this paper, we propose an approach that allows executable process models to be integrated with Geographic Information Systems. This approach enables process models to take geospatial and other geographic aspects into account in an explicit manner both during the modeling phase and the execution phase. We contribute a structured modeling methodology, based on the well-known Business Process Model and Notation standard, which is formalized by means of a mapping to executable Colored Petri nets. We illustrate the feasibility of our approach by means of a sustainability-focused case example of a process with important ecological concerns.

A framework for qualitative analysis of focus group data in information systems

Focus groups are a popular qualitative research method for information systems researchers. However, compared with the abundance of research articles and handbooks on planning and conducting focus groups, surprisingly, there is little research on how to analyse focus group data. Moreover, those few articles that specifically address focus group analysis are all in fields other than information systems, and offer little specific guidance for information systems researchers. Further, even the studies that exist in other fields do not provide a systematic and integrated procedure to analyse both focus group ‘content’ and ‘interaction’ data. As the focus group is a valuable method to answer the research questions of many IS studies (in the business, government and society contexts), we believe that more attention should be paid to this method in the IS research. This paper offers a systematic and integrated procedure for qualitative focus group data analysis in information systems research.

Understanding, utilizing and valuing design tools in business

This chapter examines the tools and activities (referred to as approaches) used by a catalyst while facilitating a design-led transformation within an Australian manufacturing small to medium enterprise (SME). Design-led innovation (DLI) aids the use of design at a higher strategic level; however few existing studies investigate the relative influence of approaches used by a catalyst while helping a firm to make a transition in the utilisation of design, specifically from a styling tool to a strategic process. This paper identifies the triggers to encouraging a shift toward understanding, utilising and valuing the business level outcomes of design through a range of design tools and activities within the participating company. Through a 12 month action research program, staff interviews and a reflective journal were utilised as data collection techniques to assess the successfulness of the approaches used during this project. It was found that, through the use of both successful and unsuccessful approaches, the catalyst achieved two key outcomes within the firm: 1) Improvements in the firm’s ability to challenge internal assumptions and standard practices; and 2) the creation of an informed and accurate awareness of company and industry issues. Approaches that made a higher impact of the firm were deemed successful, and were generally relatable to the task at hand, as perceived by employees. Additionally, the sequence in which the approaches were utilised was found to have a direct influence on their successfulness. Learnings from this research will assist future catalysts to facilitate a design-led transformation within a manufacturing SME through the use of design tools and activities with greater effectiveness.

Effects of microfinance on poverty reduction in Vietnam : a pseudo-panel data analysis

The development of microfinance in Vietnam since 1990s has coincided with a remarkable progress in poverty reduction. Numerous descriptive studies have illustrated that microfinance is an effective tool to eradicate poverty in Vietnam but evidence from quantitative studies is mixed. This study contributes to the literature by providing new evidence on the impact of microfinance to poverty reduction in Vietnam using the repeated cross - sectional data from the Vietnam Living Standard s Survey (VLSS) during period 1992 - 2010. Our results show that micro - loans contribute significantly to household consumption.

Data as an asset: what the oil and gas sector can learn from other industries about “Big Data”

The upstream oil and gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data” is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil and gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This viewpoint examines existing data management practices in the upstream oil and gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the way in Big Data. The comparison shows that, in companies that are widely considered to be leaders in Big Data analytics, data is regarded as a valuable asset—but this is usually not true within the oil and gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how the industry could potentially extract more value from data, and concludes with a series of policy-related questions to this end.

Women at work! evaluating equal employment policies and outcomes in construction

Purpose The purpose of this paper is to examine equal employment policies in Australia’s male-dominated construction industry and categorise the types of activities undertaken against an equal employment typology to identify links to outcomes for women in the form of increased participation and management. Design/methodology/approach To explore the issue of low representation of women in construction through the content analysis of 83 construction organisations’ equal employment opportunity (EEO) reports. Findings This industry is not engaging with equal employment issues and the numbers of women working in the industry and/or management are based on individual decision rather than an institutional commitment to equality in diversity. Research limitations/implications Australian legislation mandates organisational reporting of relevant data and offers public access to this information offering a unique data set. Practical implications An ageing population means that the predominately older male workforce is leaving construction in greater numbers with fewer potential replacements making new labour markets a vital consideration. Social implications Legislation and organisational policies designed to promote EEO for women have existed in numerous countries for decades. One objective of this legislation was to reduce male domination in senior positions and industries/occupations where women were under-represented. Despite this, few women are employed in construction in operational or management roles worldwide. Originality/value This study offers a comprehensive analysis of a male-dominated industry in one jurisdiction rather than a few selected cases and uses a broader rigorous typology for analysis that acknowledges both equal and different treatment options.

Issues to consider when developing mandatory reporting legislation and policy to improve discovery of child abuse

In the United Kingdom, recent investigations into child sexual abuse occurring within schools, the Catholic Church and the British Broadcasting Corporation, have intensified debate on ways to improve the discovery of child sexual abuse, and child maltreatment generally. One approach adopted in other jurisdictions to better identify cases of severe child maltreatment is the introduction of some form of legislative mandatory reporting to require designated persons to report known and suspected cases. The debate in England has raised the prospect of whether adopting a strategy of some kind of mandatory reporting law is advisable. The purpose of this article is to add to this debate by identifying fundamental principles, issues and complexities underpinning policy and even legislative developments in the interests of children and society. The article will first highlight the data on the hidden nature of child maltreatment and the background to the debate. Secondly, it will identify some significant gaps in knowledge that need to be filled. Thirdly, the article will summarise the barriers to reporting abuse and neglect. Fourthly, we will identify a range of options for, and clarify the dilemmas in developing, legislative mandatory reporting, addressing two key issues: who should be mandated to report, and what types of child maltreatment should they be required to report? Finally, we draw attention to some inherently different goals and competing interests, both between and within the various institutions involved in the safeguarding of children and the criminal prosecution of some offenders. Based on this analysis we offer some concluding observations that we hope contribute to informed and careful debate about mandatory reporting.