Managing process model complexity via concrete syntax modifications

While Business Process Management (BPM) is an established discipline, the increased adoption of BPM technology in recent years has introduced new challenges. One challenge concerns dealing with the ever-growing complexity of business process models. Mechanisms for dealing with this complexity can be classified into two categories: 1) those that are solely concerned with the visual representation of the model and 2) those that change its inner structure. While significant attention is paid to the latter category in the BPM literature, this paper focuses on the former category. It presents a collection of patterns that generalize and conceptualize various existing mechanisms to change the visual representation of a process model. Next, it provides a detailed analysis of the degree of support for these patterns in a number of state-of-the-art languages and tools. This paper concludes with the results of a usability evaluation of the patterns conducted with BPM practitioners.

Developing research data management services at QUT

QUT Library and the High Performance Computing and Research Support (HPC) Team have been collaborating on developing and delivering a range of research support services, including those designed to assist researchers to manage their data. QUT’s Management of Research Data policy has been available since 2010 and is complemented by the Data Management Guidelines and Checklist. QUT has partnered with the Australian Research Data Service (ANDS) on a number of projects including Seeding the Commons, Metadata Hub (with Griffith University) and the Data Capture program. The HPC Team has also been developing the QUT Research Data Repository based on the Architecta Mediaflux system and have run several pilots with faculties. Library and HPC staff have been trained in the principles of research data management and are providing a range of research data management seminars and workshops for researchers and HDR students.

newYAWL : Towards Workflow 2.0

The field of workflow technology has burgeoned in recent years providing a variety of means of automating business processes. It is a great source of opportunity for organisations seeking to streamline and optimise their operations. Despite these advantages however, the current generation of workflow technologies are subject to a variety of criticisms, in terms of their restricted view of what comprises a business process, their imprecise definition and their general inflexibility. As a remedy to these potential difficulties, in this paper we propose a series of development goals for the next generation of workflow technology. We also present newYAWL, a formally defined, multi-perspective reference language for workflow systems.

Experiential ethics education for IT professionals

This chapter presents a new approach to IT ethics education that may be used by teachers in academic institutions, employees responsible for promoting ethics in organisations and individuals wanting to pursue their own professional development. Experiential ethics education emphasises deep learning that prompts a changed experience of ethics. We first consider how this approach complements other ways of engaging in ethics education. We then explore what it means to strive for experiential change and offer a model which may be useful in pursuing IT professional ethics education in this way.

Reliable representations for association rules

Association rule mining has contributed to many advances in the area of knowledge discovery. However, the quality of the discovered association rules is a big concern and has drawn more and more attention recently. One problem with the quality of the discovered association rules is the huge size of the extracted rule set. Often for a dataset, a huge number of rules can be extracted, but many of them can be redundant to other rules and thus useless in practice. Mining non-redundant rules is a promising approach to solve this problem. In this paper, we first propose a definition for redundancy, then propose a concise representation, called a Reliable basis, for representing non-redundant association rules. The Reliable basis contains a set of non-redundant rules which are derived using frequent closed itemsets and their generators instead of using frequent itemsets that are usually used by traditional association rule mining approaches. An important contribution of this paper is that we propose to use the certainty factor as the criterion to measure the strength of the discovered association rules. Using this criterion, we can ensure the elimination of as many redundant rules as possible without reducing the inference capacity of the remaining extracted non-redundant rules. We prove that the redundancy elimination, based on the proposed Reliable basis, does not reduce the strength of belief in the extracted rules. We also prove that all association rules, their supports and confidences, can be retrieved from the Reliable basis without accessing the dataset. Therefore the Reliable basis is a lossless representation of association rules. Experimental results show that the proposed Reliable basis can significantly reduce the number of extracted rules. We also conduct experiments on the application of association rules to the area of product recommendation. The experimental results show that the non-redundant association rules extracted using the proposed method retain the same inference capacity as the entire rule set. This result indicates that using non-redundant rules only is sufficient to solve real problems needless using the entire rule set.

Information and communication technology for E-regions

Information and communication technologies (ICTs) are essential components of the knowledge economy, and have an immense complementary role in innovation, education, knowledge creation, and relations with government, civil society, and business within city regions. The ability to create, distribute, and exploit knowledge has become a major source of competitive advantage, wealth creation, and improvements in the new regional policies. Growing impact of ICTs on the economy and society, rapid application of recent scientific advances in new products and processes, shifting to more knowledge-intensive industry and services, and rising skill requirements have become crucial concepts for urban and regional competitiveness. Therefore, harnessing ICTs for knowledge-based urban development (KBUD) has a significant impact on urban and regional growth (Yigitcanlar, 2005). In this sense, e-region is a novel concept utilizing ICTs for regional development. Since the Helsinki European Council announced Turkey as a candidate for European Union (EU) membership in 1999, the candidacy has accelerated the speed of regional policy enhancements and adoption of the European regional policy standards. These enhancements and adoption include the generation of a new regional spatial division, NUTS-II statistical regions; a new legislation on the establishment of regional development agencies (RDAs); and new orientations in the field of high education, science, and technology within the framework of the EU’s Lisbon Strategy and the Bologna Process. The European standards posed an ambitious new agenda in the development and application of contemporary regional policy in Turkey (Bilen, 2005). In this sense, novel regional policies in Turkey necessarily endeavor to include information society objectives through efficient use of new technologies such as ICTs. Such a development seeks to be based on tangible assets of the region (Friedmann, 2006) as well as the best practices deriving from grounding initiatives on urban and local levels. These assets provide the foundation of an e-region that harnesses regional development in an information society context. With successful implementations, the Marmara region’s local governments in Turkey are setting the benchmark for the country in the implementation of spatial information systems and e-governance, and moving toward an e-region. Therefore, this article aims to shed light on organizational and regional realities of recent practices of ICT applications and their supply instruments based on evidence from selected local government organizations in the Marmara region. This article also exemplifies challenges and opportunities of the region in moving toward an e-region and provides a concise review of different ICT applications and strategies in a broader urban and regional context. The article is organized in three parts. The following section scrutinizes the e-region framework and the role of ICTs in regional development. Then, Marmara’s opportunities and challenges in moving toward an e-region are discussed in the context of ICT applications and their supply instruments based on public-sector projects, policies, and initiatives. Subsequently, the last section discusses conclusions and prospective research.

Shrinking neighborhood evolution : a novel stochastic algorithm for numerical optimization

Focusing on the conditions that an optimization problem may comply with, the so-called convergence conditions have been proposed and sequentially a stochastic optimization algorithm named as DSZ algorithm is presented in order to deal with both unconstrained and constrained optimizations. The principle is discussed in the theoretical model of DSZ algorithm, from which we present the practical model of DSZ algorithm. Practical model efficiency is demonstrated by the comparison with the similar algorithms such as Enhanced simulated annealing (ESA), Monte Carlo simulated annealing (MCS), Sniffer Global Optimization (SGO), Directed Tabu Search (DTS), and Genetic Algorithm (GA), using a set of well-known unconstrained and constrained optimization test cases. Meanwhile, further attention goes to the strategies how to optimize the high-dimensional unconstrained problem using DSZ algorithm.

Religious information literacy : using information to learn in church community

What informs members of the church community as they learn? Do the ways people engage with information differ according to the circumstances in which they learn? Informed learning, or the ways in which people use information in the learning experience and the degree to which they are aware of that, has become a focus of contemporary information literacy research. This essay explores the nature of informed learning in the context of the church as a learning community. It is anticipated that insights resulting from this exploration may help church organisations, church leaders and lay people to consider how information can be used to grow faith, develop relationships, manage the church and respond to religious knowledge, which support the pursuit of spiritual wellness and the cultivation of lifelong learning. Information professionals within the church community and the broader information profession are encouraged to foster their awareness of the impact that engagement with information has in the learning experience and in the prioritising of lifelong learning in community contexts.

Data and process requirements for product recall coordination

When an organisation becomes aware that one of its products may pose a safety risk to customers, it must take appropriate action as soon as possible or it can be held liable. The ability to automatically trace potentially dangerous goods through the supply chain would thus help organisations fulfill their legal obligations in a timely and effective manner. Furthermore, product recall legislation requires manufacturers to separately notify various government agencies, the health department and the public about recall incidents. This duplication of effort and paperwork can introduce errors and data inconsistencies. In this paper, we examine traceability and notification requirements in the product recall domain from two perspectives: the activities carried out during the manufacturing and recall processes and the data collected during the enactment of these processes. We then propose a workflow-based coordination framework to support these data and process requirements.

Determinants and consequences of information sharing with key suppliers

The economic environment of today can be characterized as highly dynamic and competitive if not being in a constant flux. Globalization and the Information Technology (IT) revolution are perhaps the main contributing factors to this observation. While companies have to some extent adapted to the current business environment, new pressures such as the recent increase in environmental awareness and its likely effects on regulations are underway. Hence, in the light of market and competitive pressures, companies must constantly evaluate and if necessary update their strategies to sustain and increase the value they create for shareholders (Hunt and Morgan, 1995; Christopher and Towill, 2002). One way to create greater value is to become more efficient in producing and delivering goods and services to customers, which can lead to a strategy known as cost leadership (Porter, 1980). Even though Porter (1996) notes that in the long run cost leadership may not be a sufficient strategy for competitive advantage, operational efficiency is certainly necessary and should therefore be on the agenda of every company. ----- ----- ----- Better workflow management, technology, and resource utilization can lead to greater internal operational efficiency, which explains why, for example, many companies have recently adopted Enterprise Resource Planning (ERP) Systems: integrated softwares that streamline business processes. However, as today more and more companies are approaching internal operational excellence, the focus for finding inefficiencies and cost saving opportunities is moving beyond the boundaries of the firm. Today many firms in the supply chain are engaging in collaborative relationships with customers, suppliers, and third parties (services) in an attempt to cut down on costs related to for example, inventory, production, as well as to facilitate synergies. Thus, recent years have witnessed fluidity and blurring regarding organizational boundaries (Coad and Cullen, 2006). ----- ----- ----- The Information Technology (IT) revolution of the late 1990’s has played an important role in bringing organizations closer together. In their efforts to become more efficient, companies first integrated their information systems to speed up transactions such as ordering and billing. Later collaboration on a multidimensional scale including logistics, production, and Research & Development became evident as companies expected substantial benefits from collaboration. However, one could also argue that the recent popularity of the concepts falling under Supply Chain Management (SCM) such as Vendor Managed Inventory, Collaborative Planning, Replenishment, and Forecasting owe to the marketing efforts of software vendors and consultants who provide these solutions. Nevertheless, reports from professional organizations as well as academia indicate that the trend towards interorganizational collaboration is gaining wider ground. For example, the ARC Advisory Group, a research organization on supply chain solutions, estimated that the market for SCM, which includes various kinds of collaboration tools and related services, is going to grow at an annual rate of 7.4% during the years 2004-2008, reaching to $7.4 billion in 2008 (Engineeringtalk 2004).

Scaling acoustic data analysis through collaboration and automation

Monitoring and assessing environmental health is becoming increasingly important as human activity and climate change place greater pressure on global biodiversity. Acoustic sensors provide the ability to collect data passively, objectively and continuously across large areas for extended periods of time. While these factors make acoustic sensors attractive as autonomous data collectors, there are significant issues associated with large-scale data manipulation and analysis. We present our current research into techniques for analysing large volumes of acoustic data effectively and efficiently. We provide an overview of a novel online acoustic environmental workbench and discuss a number of approaches to scaling analysis of acoustic data; collaboration, manual, automatic and human-in-the loop analysis.

Effective pattern discovery for text mining

Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase) based approaches should perform better than the term-based ones, but many experiments did not support this hypothesis. This paper presents an innovative technique, effective pattern discovery which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance.

Comparison of standard image segmentation methods for segmentation of brain tumors from 2D MR images

In the analysis of medical images for computer-aided diagnosis and therapy, segmentation is often required as a preliminary step. Medical image segmentation is a complex and challenging task due to the complex nature of the images. The brain has a particularly complicated structure and its precise segmentation is very important for detecting tumors, edema, and necrotic tissues in order to prescribe appropriate therapy. Magnetic Resonance Imaging is an important diagnostic imaging technique utilized for early detection of abnormal changes in tissues and organs. It possesses good contrast resolution for different tissues and is, thus, preferred over Computerized Tomography for brain study. Therefore, the majority of research in medical image segmentation concerns MR images. As the core juncture of this research a set of MR images have been segmented using standard image segmentation techniques to isolate a brain tumor from the other regions of the brain. Subsequently the resultant images from the different segmentation techniques were compared with each other and analyzed by professional radiologists to find the segmentation technique which is the most accurate. Experimental results show that the Otsu’s thresholding method is the most suitable image segmentation method to segment a brain tumor from a Magnetic Resonance Image.

Information accountability for online healthcare social networks

Online social networking has become one of the most popular Internet applications in the modern era. They have given the Internet users, access to information that other Internet based applications are unable to. Although many of the popular online social networking web sites are focused towards entertainment purposes, sharing information can benefit the healthcare industry in terms of both efficiency and effectiveness. But the capability to share personal information; the factor which has made online social networks so popular, is itself a major obstacle when considering information security and privacy aspects. Healthcare can benefit from online social networking if they are implemented such that sensitive patient information can be safeguarded from ill exposure. But in an industry such as healthcare where the availability of information is crucial for better decision making, information must be made available to the appropriate parties when they require it. Hence the traditional mechanisms for information security and privacy protection may not be suitable for healthcare. In this paper we propose a solution to privacy enhancement in online healthcare social networks through the use of an information accountability mechanism.

Maintenance chain integration using Petri-net enabled multiagent system modeling and implementation approach

Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.