Liquid Business Process Model Collections

Many organizations realize that increasing amounts of data (“Big Data”) need to be dealt with intelligently in order to compete with other organizations in terms of efficiency, speed and services. The goal is not to collect as much data as possible, but to turn event data into valuable insights that can be used to improve business processes. However, data-oriented analysis approaches fail to relate event data to process models. At the same time, large organizations are generating piles of process models that are disconnected from the real processes and information systems. In this chapter we propose to manage large collections of process models and event data in an integrated manner. Observed and modeled behavior need to be continuously compared and aligned. This results in a “liquid” business process model collection, i.e. a collection of process models that is in sync with the actual organizational behavior. The collection should self-adapt to evolving organizational behavior and incorporate relevant execution data (e.g. process performance and resource utilization) extracted from the logs, thereby allowing insightful reports to be produced from factual organizational data.

Data driven and practice-based evidence : design and development of efficient and effective clinical decision support system

Decision-making is such an integral aspect in health care routine that the ability to make the right decisions at crucial moments can lead to patient health improvements. Evidence-based practice, the paradigm used to make those informed decisions, relies on the use of current best evidence from systematic research such as randomized controlled trials. Limitations of the outcomes from randomized controlled trials (RCT), such as “quantity” and “quality” of evidence generated, has lowered healthcare professionals’ confidence in using EBP. An alternate paradigm of Practice-Based Evidence has evolved with the key being evidence drawn from practice settings. Through the use of health information technology, electronic health records (EHR) capture relevant clinical practice “evidence”. A data-driven approach is proposed to capitalize on the benefits of EHR. The issues of data privacy, security and integrity are diminished by an information accountability concept. Data warehouse architecture completes the data-driven approach by integrating health data from multi-source systems, unique within the healthcare environment.

The role of the website in a magazine business: Revisiting old truths

This paper explores consumer behavioural patterns on a magazine website. By using a unique dataset of real-life click stream data from 295 magazine website visitors, interesting behavioural patterns are noted: most importantly, 86 % of all sessions only visit the blogs hosted by the magazine. This means that the visitors short-circuit the start page and are not exposed to any editorial content at all, and consequently not to any commercial content on those pages. Sessions visiting editorial content, commercial content or social media links actually represent only one (1) per cent or less of all sessions recorded. Consequently, the online platform gives very limited support for the business model. Our data questions the general assumption that online platforms are key components of a contemporary magazine’s business model.

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.

Increasing the rigour and trustworthiness of participatory evaluations : learnings from the field

Participatory evaluation and participatory action research (PAR) are increasingly used in community-based programs and initiatives and there is a growing acknowledgement of their value. These methodologies focus more on knowledge generated and constructed through lived experience than through social science (Vanderplaat 1995). The scientific ideal of objectivity is usually rejected in favour of a holistic approach that acknowledges and takes into account the diverse perspectives, values and interpretations of participants and evaluation professionals. However, evaluation rigour need not be lost in this approach. Increasing the rigour and trustworthiness of participatory evaluations and PAR increases the likelihood that results are seen as credible and are used to continually improve programs and policies.----- Drawing on learnings and critical reflections about the use of feminist and participatory forms of evaluation and PAR over a 10-year period, significant sources of rigour identified include:----- • participation and communication methods that develop relations of mutual trust and open communication----- • using multiple theories and methodologies, multiple sources of data, and multiple methods of data collection----- • ongoing meta-evaluation and critical reflection----- • critically assessing the intended and unintended impacts of evaluations, using relevant theoretical models----- • using rigorous data analysis and reporting processes----- • participant reviews of evaluation case studies, impact assessments and reports.

A national building products inventory

Australia has no nationally accepted building products life cycle inventory (LCI) database for use in building Ecologically Sustainable Development (ESD) assessment (BEA) tools. More information about the sustainability of the supply chain is limited by industry’s lack of real capacity to deliver objective information on process and product environmental impact. Recognition of these deficits emerged during compilation of a National LCI database to inform LCADesign, a prototype 3 dimensional object oriented computer aided design (3-D CAD) commercial building design tool. Development of this Australian LCI represents 24 staff years of effort here since 1995. Further development of LCADesign extensions is proposed as being essential to support key applications demanded from a more holistic theoretical framework calling for modules of new building and construction industry tools. A proposed tool, conceptually called LCADetails, is to serve the building product industries own needs as well as that of commercial building design amongst other industries’ prospective needs. In this paper, a proposition is examined that the existing national LCI database should be further expanded to serve Australian building product industries’ needs as well as to provide details for its client-base from a web based portal containing a module of practical supply and procurement applications. Along with improved supply chain assessment services, this proposed portal is envisaged to facilitate industry environmental life cycle improvement assessment and support decision-making to provide accredited data for operational reporting capabilities, load-based reasoning as well as BEA applications. This paper provides an overview of developments to date, including a novel 3-D CAD information and communications technology (ICT) platform for more holistic integration of existing tools for true cost assessment. Further conceptualisation of future prospects, based on a new holistic life cycle assessment framework LCADevelop, considering stakeholder relationships and their need for a range of complementary tools leveraging automated function off such ICT platforms to inform dimensionally defined operations for such as automotive, civil, transport and industrial applications are also explored.

Archiving nature’s heartbeat using smart phones

The impact of urban development and climate change has created the impetus to monitor changes in the environment, particularly, the behaviour, habitat and movement of fauna species. The aim of this chapter is to present the design and development of a sensor network based on smart phones to automatically collect and analyse acoustic and visual data for environmental monitoring purposes. Due to the communication and sophisticated programming facilities offered by smart phones, software tools can be developed to allow data to be collected, partially processed and sent to a remote server over the network for storage and further processing. This sensor network which employs a client-server architecture has been deployed in three applications: monitoring a rare bird species near Brisbane Airport, study of koalas behaviour at St Bees Island, and detection of fruit flies. The users of this system include scientists (e.g. ecologists, ornithologists, computer scientists) and community groups participating in data collection or reporting on the environment (e.g. students, bird watchers). The chapter focuses on the following aspects of our research: issues involved in using smart phones as sensors; the overall framework for data acquisition, data quality control, data management and analysis; current and future applications of the smart phone-based sensor network, and our future research directions.

Path planning, guidance and control for a UAV forced landing

A forced landing is an unscheduled event in flight requiring an emergency landing, and is most commonly attributed to engine failure, failure of avionics or adverse weather. Since the ability to conduct a successful forced landing is the primary indicator for safety in the aviation industry, automating this capability for unmanned aerial vehicles (UAVs) will help facilitate their integration into, and subsequent routine operations over civilian airspace. Currently, there is no commercial system available to perform this task; however, a team at the Australian Research Centre for Aerospace Automation (ARCAA) is working towards developing such an automated forced landing system. This system, codenamed Flight Guardian, will operate onboard the aircraft and use machine vision for site identification, artificial intelligence for data assessment and evaluation, and path planning, guidance and control techniques to actualize the landing. This thesis focuses on research specific to the third category, and presents the design, testing and evaluation of a Trajectory Generation and Guidance System (TGGS) that navigates the aircraft to land at a chosen site, following an engine failure. Firstly, two algorithms are developed that adapts manned aircraft forced landing techniques to suit the UAV planning problem. Algorithm 1 allows the UAV to select a route (from a library) based on a fixed glide range and the ambient wind conditions, while Algorithm 2 uses a series of adjustable waypoints to cater for changing winds. A comparison of both algorithms in over 200 simulated forced landings found that using Algorithm 2, twice as many landings were within the designated area, with an average lateral miss distance of 200 m at the aimpoint. These results present a baseline for further refinements to the planning algorithms. A significant contribution is seen in the design of the 3-D Dubins Curves planning algorithm, which extends the elementary concepts underlying 2-D Dubins paths to account for powerless flight in three dimensions. This has also resulted in the development of new methods in testing for path traversability, in losing excess altitude, and in the actual path formation to ensure aircraft stability. Simulations using this algorithm have demonstrated lateral and vertical miss distances of under 20 m at the approach point, in wind speeds of up to 9 m/s. This is greater than a tenfold improvement on Algorithm 2 and emulates the performance of manned, powered aircraft. The lateral guidance algorithm originally developed by Park, Deyst, and How (2007) is enhanced to include wind information in the guidance logic. A simple assumption is also made that reduces the complexity of the algorithm in following a circular path, yet without sacrificing performance. Finally, a specific method of supplying the correct turning direction is also used. Simulations have shown that this new algorithm, named the Enhanced Nonlinear Guidance (ENG) algorithm, performs much better in changing winds, with cross-track errors at the approach point within 2 m, compared to over 10 m using Park's algorithm. A fourth contribution is made in designing the Flight Path Following Guidance (FPFG) algorithm, which uses path angle calculations and the MacCready theory to determine the optimal speed to fly in winds. This algorithm also uses proportional integral- derivative (PID) gain schedules to finely tune the tracking accuracies, and has demonstrated in simulation vertical miss distances of under 2 m in changing winds. A fifth contribution is made in designing the Modified Proportional Navigation (MPN) algorithm, which uses principles from proportional navigation and the ENG algorithm, as well as methods specifically its own, to calculate the required pitch to fly. This algorithm is robust to wind changes, and is easily adaptable to any aircraft type. Tracking accuracies obtained with this algorithm are also comparable to those obtained using the FPFG algorithm. For all three preceding guidance algorithms, a novel method utilising the geometric and time relationship between aircraft and path is also employed to ensure that the aircraft is still able to track the desired path to completion in strong winds, while remaining stabilised. Finally, a derived contribution is made in modifying the 3-D Dubins Curves algorithm to suit helicopter flight dynamics. This modification allows a helicopter to autonomously track both stationary and moving targets in flight, and is highly advantageous for applications such as traffic surveillance, police pursuit, security or payload delivery. Each of these achievements serves to enhance the on-board autonomy and safety of a UAV, which in turn will help facilitate the integration of UAVs into civilian airspace for a wider appreciation of the good that they can provide. The automated UAV forced landing planning and guidance strategies presented in this thesis will allow the progression of this technology from the design and developmental stages, through to a prototype system that can demonstrate its effectiveness to the UAV research and operations community.

Implementation of ICD-11... perspectives from the Australian Bureau of Statistics

As the development of ICD-11 progresses, the Australian Bureau of Statistics is beginning to consider what will be required to successfully implement the new version of the classification. This paper will present early thoughts on the following: building understanding amongst the user community of upcoming changes and the implications of those changes; the need for training of coders and data users; development of analytical methods and conduct of comparability studies; processes to test, accept and implement new or updated coding software; assessment of coding quality; changes to data analyses and reporting processes; updates to regular publications; and assessing the resources required for successful implementation.

Identifying customer behaviour and dwell time using soft biometrics

In a commercial environment, it is advantageous to know how long it takes customers to move between different regions, how long they spend in each region, and where they are likely to go as they move from one location to another. Presently, these measures can only be determined manually, or through the use of hardware tags (i.e. RFID). Soft biometrics are characteristics that can be used to describe, but not uniquely identify an individual. They include traits such as height, weight, gender, hair, skin and clothing colour. Unlike traditional biometrics, soft biometrics can be acquired by surveillance cameras at range without any user cooperation. While these traits cannot provide robust authentication, they can be used to provide identification at long range, and aid in object tracking and detection in disjoint camera networks. In this chapter we propose using colour, height and luggage soft biometrics to determine operational statistics relating to how people move through a space. A novel average soft biometric is used to locate people who look distinct, and these people are then detected at various locations within a disjoint camera network to gradually obtain operational statistics

A decision table method for randomness measurement

Data quality has become a major concern for organisations. The rapid growth in the size and technology of a databases and data warehouses has brought significant advantages in accessing, storing, and retrieving information. At the same time, great challenges arise with rapid data throughput and heterogeneous accesses in terms of maintaining high data quality. Yet, despite the importance of data quality, literature has usually condensed data quality into detecting and correcting poor data such as outliers, incomplete or inaccurate values. As a result, organisations are unable to efficiently and effectively assess data quality. Having an accurate and proper data quality assessment method will enable users to benchmark their systems and monitor their improvement. This paper introduces a granules mining for measuring the random degree of error data which will enable decision makers to conduct accurate quality assessment and allocate the most severe data, thereby providing an accurate estimation of human and financial resources for conducting quality improvement tasks.

Learning domain-specific sentiment lexicons for predicting product sales

Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web

A Comprehensive Benchmarking Framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM

Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.

Using management objectives to specify management information systems : a contribution to MIS success

Data warehouse projects, today, are in an ambivalent situation. On the one hand, data warehouses are critical for a company’s success and various methodological and technological tools are sophisticatedly developed to implement them. On the other hand, a significant amount of data warehouse projects fails due to non-technical reasons such as insufficient management support or in-corporative employees. But management support and user participation can be increased dramatically with specification methods that are understandable to these user groups. This paper aims at overcoming possible non-technical failure reasons by introducing a user-adequate specification approach within the field of management information systems.

Corporate social responsibility in Japanese firms in transport sector

Corporate Social Responsibility (CSR) reporting has become common practice for large organisations globally, yet there is variance in the CSR related activities claimed in disclosures. CSR researchers argue that cultural and historical backgrounds are the influential drivers of CSR behaviour. However, the links between actual activities claimed in CSR reports and the cultural systems that underpin these reported activities is an under-explored area. This thesis discusses the uniqueness of Japanese socio-cultural aspects. While Japan is well-known for having the most advanced energy efficient technologies in the world, it is also known for being below international standards for gender equality in the workplace. Therefore, this thesis aims to explore and examine organisational behaviours through the lens of relativism in order to understand what organisations are reporting and how and why managers prioritise these activities. This thesis is based on longitudinal qualitative research focusing on the Japanese transport companies that published CSR reports between 2005 and 2009. The findings from manually coded content analysis revealed: (1) that activities related to providing public safety, waste management and the 3Rs (reduce, reuse and recycle), and environmental innovation were the top three most frequently reported CSR activities; and (2) complying with laws, career planning, flexible work practices, and providing public safety were the three categories that showed the most significant increase in reporting frequency from 2005-2009. This thesis extends the previous literature. Takagaki (2010b) identified that the transport industry, particularly the air and water sub-sectors, is the industry where the environmental problems are serious and require urgent attention. Takagaki (2010b) chose to explore the electronics industry as this industry is considered to be middle ground for its level of seriousness and urgency. This research: (1) examines the transport industry; (2) investigates the links between the actual activities reported, and the activities reported to be influential drivers of these activities.