Brain fiber architecture, genetics, and intelligence: a high angular resolution diffusion imaging (HARDI) study

We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling the spherical fiber orientation distribution functions (ODFs) in appropriate Riemannian manifolds, after ODF regularization and sharpening. Fitting structural equation models (SEM) from quantitative genetics, we evaluated genetic influences on the Jensen-Shannon divergence (JSD), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (GFA) a measure of fiber integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (IQ). Fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.

Engaging decision makers in the business case for biophilic urbanism

The cognitive benefits of biophilia have been studied quite extensively, dating as far back as the 1980s, while studies into economic benefits are still in their infancy. Recent research has attempted to quantify a number of economic returns on biophilic elements; however knowledge in this field is still ad hoc and highly variable. Many studies acknowledge difficulties in discerning information such as certain social and aesthetic benefits. While conceptual understanding of the physiological and psychological effects of exposure to nature is widely recognised and understood, this has not yet been systematically translated into monetary terms. It is clear from the literature that further research is needed to both obtain data on the economics of biophilic urbanism, and to create the business case for biophilic urbanism. With this in mind, this paper will briefly highlight biophilic urbanism referencing previous work in the field. It will then explore a number of emergent gaps in the measurable economic understanding of these elements and suggest opportunities for engaging decision makers in the business case for biophilic urbanism. The paper concludes with recommendations for moving forward through targeted research and economic analysis.

Education critical to going beyond business as usual

As government and industry grapple with 21st century challenges, building the capacity to look at complex problems through fresh eyes is critical.

Text segmentation in unconstrained hand-drawings in whiteboard photos

In this paper we present a robust method to detect handwritten text from unconstrained drawings on normal whiteboards. Unlike printed text on documents, free form handwritten text has no pattern in terms of size, orientation and font and it is often mixed with other drawings such as lines and shapes. Unlike handwritings on paper, handwritings on a normal whiteboard cannot be scanned so the detection has to be based on photos. Our work traces straight edges on photos of the whiteboard and builds graph representation of connected components. We use geometric properties such as edge density, graph density, aspect ratio and neighborhood similarity to differentiate handwritten text from other drawings. The experiment results show that our method achieves satisfactory precision and recall. Furthermore, the method is robust and efficient enough to be deployed in a mobile device. This is an important enabler of business applications that support whiteboard-centric visual meetings in enterprise scenarios. © 2012 IEEE.

A service-oriented architecture for text analytics enabled business applications

Experiences showed that developing business applications that base on text analysis normally requires a lot of time and expertise in the field of computer linguistics. Several approaches of integrating text analysis systems with business applications have been proposed, but so far there has been no coordinated approach which would enable building scalable and flexible applications of text analysis in enterprise scenarios. In this paper, a service-oriented architecture for text processing applications in the business domain is introduced. It comprises various groups of processing components and knowledge resources. The architecture, created as a result of our experiences with building natural language processing applications in business scenarios, allows for the reuse of text analysis and other components, and facilitates the development of business applications. We verify our approach by showing how the proposed architecture can be applied to create a text analytics enabled business application that addresses a concrete business scenario. © 2010 IEEE.

Linking business goals to process models in semantic business process modeling

Broad knowledge is required when a business process is modeled by a business analyst. We argue that existing Business Process Management methodologies do not consider business goals at the appropriate level. In this paper we present an approach to integrate business goals and business process models. We design a Business Goal Ontology for modeling business goals. Furthermore, we devise a modeling pattern for linking the goals to process models and show how the ontology can be used in query answering. In this way, we integrate the intentional perspective into our business process ontology framework, enriching the process description and enabling new types of business process analysis. © 2008 IEEE.

The use of embodiments in distributed collaborative business process modelling

Remote networked collaboration with business model documentation has many communication problems. The aim of this project is to solve some of these communication problems by using digital 3D representations of human visual cues. Results from this project increased our understanding of the role and effects of visual cues in remote collaboration, specifically for validating business process models. Technology designs to support such cues across a distance have been proposed in this thesis with qualitative and quantitative methods of analysis being combined to analyse the impact of these cues on the communication, coordination and performance of a team collaborating remotely.

Global business services: Increasing specialization and integration of the world economy as drivers of economic growth

Purpose The purpose of this paper is to explore the contribution of global business services to improved productivity and economic growth of the world economy, which has gone largely unnoticed in service research. Design/methodology/approach The authors draw on macroeconomic data and industry reports, and link them to the non-ownership-concept in service research and theories of the firm. Findings Business services explain a large share of the growth of the global service economy. The fast growth of business services coincides with shifts from domestic production towards global outsourcing of services. A new wave of global business services are traded across borders and have emerged as important drivers of growth in the world’s service sector. Research limitations/implications This paper advances the understanding of non-ownership services in an increasingly global and specialized post-industrial economy. The paper makes a conceptual contribution supported by descriptive data, but without empirical testing. Originality/value The authors integrate the non-ownership concept and three related economic theories of the firm to explain the role of global business services in driving business performance and the international transformation of service economies.

Analysis of Business Process Variants in Apromore

In this paper we illustrate a set of features of the Apromore process model repository for analyzing business process variants. Two types of analysis are provided: one is static and based on differences on the process control flow, the other is dynamic and based on differences in the process behavior between the variants. These features combine techniques for the management of large process model collections with those for mining process knowledge from process execution logs. The tool demonstration will be useful for researchers and practitioners working on large process model collections and process execution logs, and specifically for those with an interest in understanding, managing and consolidating business process variants both within and across organizational boundaries.

Business Process Management: 13th International Conference, BPM 2015, Innsbruck, Austria, August 31 -- September 3, 2015, Proceedings

BPM 2015 was the 13th International Conference on Business Process Management. It provided a global forum for researchers to meet and exchange views over research topics and outcomes in business process management. BPM 2015 was hosted by the University of Innsbruck and took place August 31 to September 3.

Business model publicness and socialness of the social enterprise

Social enterprise is important. Yet, there has been diverse understanding of the phenomenon in the literature. This paper attempts to make sense of the social enterprise phenomenon in the literature from a two-layer framework of two-by-two matrices. The first layer juxtaposes social enterprise against other organizations (a typology of organizations) and the second layer classifies different types of social enterprises (a typology of social enterprise). This framework may provide researchers with tools to develop a clear and comprehensive definition of social enterprise. For practitioners, the ability to recognize structures of different types of social enterprises may offer them guideline to design the appropriate business model to serve their purposes.

ACE Research Vignette 047: What is the hard evidence on innovation and business productivity

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. This vignette, written by Professor Beth Webster at Swinburne University of Technology, examines how innovation in small and medium size businesses affect their productivity.

Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes

This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

Client learning and the performance of collaborative infrastructure projects

Australia is a leading user of collaborative procurement methods, which are used to deliver large and complex infrastructure projects. Project alliances, Early Contractor Involvement (ECI), and partnering are typical examples of collaborative procurement models. In order to increase procurement effectiveness and value for money (VfM), clients have adopted various learning strategies for new contract development. However client learning strategies and behaviours have not been systematically analysed before. Therefore, the current paper undertakes a literature review addressing the research question “How can client learning capabilities be effectively understood?”. From the resource-based and dynamic capability perspectives, this paper proposes that the collaborative learning capability (CLC) of clients drives procurement model evolution. Learning routines underpinning CLC carry out exploratory, transformative and exploitative learning phases associated with collaborative project delivery. This learning improves operating routines, and ultimately performance. The conceptualization of CLC and the three sequential learning phases is used to analyse the evidence in the construction management literature. The main contribution of this study is the presentation of a theoretical foundation for future empirical studies to unveil effective learning strategies, which help clients to improve the performance of collaborative projects in the dynamic infrastructure market.