Optimised wheat root architecture for increased yield and yield stability in the face of a changing climate.

This project provided information, selection techniques and strategies to facilitate the development of high-yielding, stay-green wheat varieties for Australian growers through: a) Improved understanding of the relationships between seminal root traits and other root- and shoot-related traits in determining high-yielding, stay-green phenotypes. b). Molecular markers and rapid phenotypic screening methods that allow selection in breeding programs and identification of genetic regions controlling favourable traits. c). Identification of traits leading to high-yielding, stay-green phenotypes for particular target populations of environments using computer simulation studies.

Enhancing bioactive fatty acids of the meat from lambs reared in intensive systems through nutritional modulation

Tese de Doutoramento em Ciências Veterinárias, especialidade de Produção Animal

Identifying the knowledge management structures in enterprise systems projects

Enterprise System (ES) implementation and management are knowledge intensive tasks that inevitably draw upon the experience of a wide range of people with diverse knowledge capabilities. Knowledge Management (KM) has been identified as a critical success factor in ES projects. Despite the recognized importance of managing knowledge for ES benefits realization, systematic attempts to conceptualize KM-structures have been few. Where the adequacy of KM-structures is assessed, the process and measures are typically idiosyncratic and lack credibility. Using the ‘KM-process’, itself based in sociology of knowledge, this paper conceptualizes four main constructs to measure the adequacy of KM-structures. The SEM model is tested using 310 responses gathered from 27 ES installations that had implemented SAP R/3. The findings reveal six constructs for KM-structure. Furthermore, the paper demonstrates the application of KM-structures in the context of ES using the Adaptive Structuration Theory. The results demonstrate that having adequate KM-structures in place, while necessary, is not sufficient. These rules and resources must be appropriated to have greater positive influence on the Enterprise System. Furthermore, the study provides empirical support for knowledge-based theory by illustrating the importance of knowledge use/re-use (vs. knowledge creation) as the most important driver in the process of KM.

Dynamics of multi-articular coordination in neurobiological systems

Although previous work in nonlinear dynamics on neurobiological coordination and control has provided valuable insights from studies of single joint movements in humans, researchers have shown increasing interest in coordination of multi-articular actions. Multi-articular movement models have provided valuable insights on neurobiological systems conceptualised as degenerate, adaptive complex systems satisfying the constraints of dynamic environments. In this paper, we overview empirical evidence illustrating the dynamics of adaptive movement behavior in a range of multi-articular actions including kicking, throwing, hitting and balancing. We model the emergence of creativity and the diversity of neurobiological action in the meta-stable region of self organising criticality. We examine the influence on multi-articular actions of decaying and emerging constraints in the context of skill acquisition. We demonstrate how, in this context, transitions between preferred movement patterns exemplify the search for and adaptation of attractor states within the perceptual motor workspace as a function of practice. We conclude by showing how empirical analyses of neurobiological coordination and control have been used to establish a nonlinear pedagogical framework for enhancing acquisition of multi-articular actions.

Estimation and compensation of clipping noise in OFDMA systems

We propose an efficient and low-complexity scheme for estimating and compensating clipping noise in OFDMA systems. Conventional clipping noise estimation schemes, which need all demodulated data symbols, may become infeasible in OFDMA systems where a specific user may only know his own modulation scheme. The proposed scheme first uses equalized output to identify a limited number of candidate clips, and then exploits the information on known subcarriers to reconstruct clipped signal. Simulation results show that the proposed scheme can significantly improve the system performance.

A role mining inspired approach to representing user behaviour in ERP systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the most predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.