International examples of large-scale systems-theory and practice IV: B2B e-commerce implementation in the Australian context

Two of the most commonly used classifications in IS research are the factor approach and the process approach. While many studies of IS implementation are undertaken using a factor approach, little research so far examines the process of e-commerce implementation, especially in relation to the implementation of e-commerce in business-to-business (B2B) relationships. A holistic understanding of implementation which combines both the factor and process approaches using a case study method, is suggested as particularly suitable because of its ability to capture the reality of e-commerce implementation in an organisation's natural environment and in much greater detail than is possible using one of these approaches alone. In this paper, therefore, we endeavour to contribute to what we perceive as a gap in the body of theory surrounding the implementation process in the business-to-business e-commerce literature. We describe the findings of multiple case studies involving ten major Australian e-commerce initiators. In addition to confirming our earlier finding of the importance of non-technical factors for the success of the implementation process we also present, through our case studies, the various management and business issues associated with the success or failure of B2B e-commerce implementation.

Full-order observer design for nonlinear complex large-scale systems with unknown time-varying delayed interactions

This article is concerned with the problem of state observer for complex large-scale systems with unknown time-varying delayed interactions. The class of large-scale interconnected systems under consideration is subjected to interval time-varying delays and nonlinear perturbations. By introducing a set of argumented Lyapunov–Krasovskii functionals and using a new bounding estimation technique, novel delay-dependent conditions for existence of state observers with guaranteed exponential stability are derived in terms of linear matrix inequalities (LMIs). In our design approach, the set of full-order Luenberger-type state observers are systematically derived via the use of an efficient LMI-based algorithm. Numerical examples are given to illustrate the effectiveness of the result

Low-order estimation scheme for large-scale systems with interconnection delays

This paper deals with the practical aspects of reduced-order distributed functional state observers design for interconnected linear systems subject to time delays in the interconnections. Contrary to some estimation strategies which only take the ideal instantaneous output information into account, the proposed scheme incorporates output information that is inevitably encountered with time delays in the course of its transmission from the distanced subsystems. It is proved that such estimator possesses less restrictive existence conditions with the acceptance of measurement data from other interrelated subsystems. Upon the satisfaction of the established existence conditions, it will be demonstrated through a simple design procedure and simulation results that a feasible observer can be realized for a given numerical system.

New results on H∞ filtering for nonlinear large-scale systems with interconnected time-varying delays

This paper proposes a new design method of H∞ filtering for nonlinear large-scale systems with interconnected time-varying delays. The interaction terms with interval time-varying delays are bounded by nonlinear bounding functions including all states of the subsystems. A stable linear filter is designed to ensure that the filtering error system is exponentially stable with a prescribed convergence rate. By constructing a set of improved Lyapunov functions and using generalized Jensen inequality, new delay-dependent conditions for designing H∞ filter are obtained in terms of linear matrix inequalities. Finally, an example is provided to illustrate the effectiveness of the proposed result.

An efficient adaptive scheduling policy for high-performance computing

The advent of commodity-based high-performance clusters has raised parallel and distributed computing to a new level. However, in order to achieve the best possible performance improvements for large-scale computing problems as well as good resource utilization, efficient resource management and scheduling is required. This paper proposes a new two-level adaptive space-sharing scheduling policy for non-dedicated heterogeneous commodity-based high-performance clusters. Using trace-driven simulation, the performance of the proposed scheduling policy is compared with existing adaptive space-sharing policies. Results of the simulation show that the proposed policy performs substantially better than the existing policies.

Predicting climate warming effects on green turtle hatchling viability and dispersal performance

Ectotherms are taxa considered highly sensitive to rapid climate warming. This is because body temperature profoundly governs their performance, fitness and life history. Yet, while several modelling approaches currently predict thermal effects on some aspects of life history and demography, they do not consider how temperature simultaneously affects developmental success and offspring phenotypic performance, two additional key attributes that are needed to comprehensively understand species responses to climate warming. Here, we developed a stepwise, individual-level modelling approach linking biophysical and developmental models with empirically derived performance functions to predict the effects of temperature-induced changes to offspring viability, phenotype and performance, using green sea turtle hatchlings as an ectotherm model. Climate warming is expected to particularly threaten sea turtles, as their life-history traits may preclude them from rapid adaptation. Under conservative and extreme warming, our model predicted large effects on performance attributes key to dispersal, as well as a reduction in offspring viability. Forecast sand temperatures produced smaller, weaker hatchlings, which were up to 40% slower than at present, albeit with increased energy stores. Conversely, increases in sea surface temperatures aided swimming performance. Our exploratory study points to the need for further development of integrative individual-based modelling frameworks to better understand the complex outcomes of climate change for ectotherm species. Such advances could better serve ecologists to highlight the most vulnerable species and populations, encouraging prioritization of conservation effort to the most threatened systems.

Revisiting associations between student performance outcomes and formative assessment opportunities: is there any impact on student learning?

This project developed as a result of some inconclusive data from an investigation of whether a relationship existed between the use of formative assessment opportunities and performance, as measured by final grade. We were expecting to show our colleagues and students that use of formative assessment resources had the potential to improve performance. This first study, done in semester 1 2002, indicated that there was no apparent relationship even though the students reported how useful they found the resources. This led us to ask if there was a transition effect
such that students were not yet working in an independent way and making full use of the resources, and/or whether in order to see an effect we needed to persuade non-users of the resources to become users before investigating if use can be correlated with improvement in performance. With the 2002-3 NextEd ASCILITE Research Grant we set out to repeat our project and to look at use and usefulness of resources in both first and second semester, to encourage non-users to become users and to investigate use with performance. Now our story has a different ending.

Challenges in health services and health systems research

The relationship between emerging trends in healthcare systems and the consequent research priorities will be explored.

Governments and policy makers in developed countries are increasingly focused on the management of chronic disease, reflecting demographic changes and shifts in the burden of disease. Systems of quality improvement and reward are increasingly based on performance in chronic disease management. There is some evidence that countries with well-developed systems of primary care, such as Australia, achieve better health outcomes at less cost. In the past 15 years, almost all developed countries have undergone some type of health care reform. There has been a major focus on reducing costs; often involving shifting services from secondary to primary care. While there are few international comparisons, most suggest a complex relationship between the strength of primary care within the overall health services system and good performance, particularly with regard to lower costs of care and particularly relevant measures of health.

Aims for 21st century health systems
What, then, are the issues which are shaping contemporary general practice in developed countries? There are several imperatives: Safety, effectiveness, patient-centredness, timeliness, efficiency and equity. A study by the Nuffield Trust (Dargie, 1999) projected the shape of healthcare for the first fifteen years of this century. The study identified six issues that need to be addressed in the process of formulating health systems policies:

• Peoples’ expectations and financial sustainability
• Demography and ageing
• Information and knowledge management
• Scientific advance and new technology
• Workforce education and training
• Systems performance and quality (efficiency, effectiveness, economy
and equity)

Each of these six issues requires innovative thinking and priority setting on the part of the health sector, such as the delivery of health services in new and creative ways. Furthermore, there is a clear need for a finely tuned research, development and evaluation strategies to match these goals.

Online context recognition in multisensor systems using Dynamic Time Warping

In this paper, we present our system for online context recognition of multimodal sequences acquired from multiple sensors. The system uses Dynamic Time Warping (DTW) to recognize multimodal sequences of different lengths, embedded in continuous data streams. We evaluate the performance of our system on two real world datasets: 1) accelerometer data acquired from performing two hand gestures and 2) NOKIA's benchmark dataset for context recognition. The results from both datasets demonstrate that the system can perform online context recognition efficiently and achieve high recognition accuracy.

Effect of speculative prefetching on network load in distributed systems

Previous studies in speculative prefetching focus on building and evaluating access models for the purpose of access prediction. This paper on the other hand investigates the performance of speculative prefetching. When prefetching is performed speculatively, there is bound to be an increase in the network load. Furthermore, the prefetched items must compete for space with existing cache occupants. These two factors-increased load and eviction of potentially useful cache entries-are considered in the analysis. We obtain the following conclusion: to maximise the improvement in access time, prefetch exclusively all items with access probabilities exceeding a certain threshold.

Workflow scheduling on distributed systems

Growing evidence shows that in obtaining high performance, a well-managed time-constrained workflow scheduling is needed. Efficient workflow scheduling is critical for achieving high performance especially in heterogeneous computing system. However, it is a great challenge to improve performance and to optimize several objectives simultaneously. We propose a workflow scheduling algorithm that minimizes the makespan of the workflow application modeled by a Directed Acyclic Graph (DAG). The new proposed scheduling algorithm is named Multi Dependency Joint (MDJ) Algorithm. The performance of MDJ is compared with existing algorithms such as, Highest Level First with Estimated Time (HLFET), Modified Critical Path (MCP) and Earliest Time First (ETF). As a result, the experiments show that our proposed MDJ algorithm outperforms HLEFT, MCP, and EFT with a 7% lower overall completion time.

Spatial reasoning by active observation

The problem of deriving spatial relationships between objects in general requires high lever' abstract representation, and it would pose difficulties even for human observer. Based on a formalism for spatial layouts proposed earlier, we present methods for deducing spatial relations between objects by an active, sighted agent in a large-scale environment. The deduction of spatial relations is based on simple visual clues, and thus this technique is more feasible than schemes that rely on complex object recognition.

Deduction of high level spatial relations

The problem of deriving spatial relationships between objects in general requires high level abstract representation, and it would pose difficulties even for human observer. Based on a formalism for spatial layouts proposed earlier [KiV92, VeK921, we present methods for deducing high level spatial relations between objects by an active, sighted agent in a large-scale environment. The deduction of spatial relations is based on simple visual clues, and thus this technique is more feasible than schemes that rely on complex object recognition.