Abstract: This paper proposes a “soft systems" approach to
domain-driven design of computer-based information systems. We
propose a systemic framework combining techniques from Soft
Systems Methodology (SSM), the Unified Modelling Language
(UML), and an implementation pattern known as “Naked Objects".
We have used this framework in action research projects that have
involved the investigation and modelling of business processes using
object-oriented domain models and the implementation of software
systems based on those domain models. Within the proposed
framework, Soft Systems Methodology (SSM) is used as a guiding
methodology to explore the problem situation and to generate a
ubiquitous language (soft language) which can be used as the basis
for developing an object-oriented domain model. The domain model
is further developed using techniques based on the UML and is
implemented in software following the “Naked Objects"
implementation pattern. We argue that there are advantages from
combining and using techniques from different methodologies in this
way.
The proposed systemic framework is overviewed and justified as
multimethodologyusing Mingers multimethodology ideas.
This multimethodology approach is being evaluated through a
series of action research projects based on real-world case studies. A
Peer-Tutoring case study is presented here as a sample of the
framework evaluation process
Abstract: This paper proposed a nonlinear model predictive
control (MPC) method for the control of gantry crane. One of the main
motivations to apply MPC to control gantry crane is based on its
ability to handle control constraints for multivariable systems. A
pre-compensator is constructed to compensate the input nonlinearity
(nonsymmetric dead zone with saturation) by using its inverse
function. By well tuning the weighting function matrices, the control
system can properly compromise the control between crane position
and swing angle. The proposed control algorithm was implemented for
the control of gantry crane system in System Control Lab of University
of Technology, Sydney (UTS), and achieved desired experimental
results.
Abstract: Networked schools have become a feature of
education systems in countries that seek to provide learning
opportunities in schools located beyond major centres of population.
The internet and e-learning have facilitated the development of
virtual educational structures that complement traditional schools,
encouraging collaborative teaching and learning to proceed. In rural
New Zealand and in the Atlantic Canadian province of
Newfoundland and Labrador, e-learning is able to provide new ways
of organizing teaching, learning and the management of educational
opportunities. However, the future of e-teaching and e-learning in
networked schools depends on the development of professional
education programs that prepare teachers for collaborative teaching
and learning environments in which both virtual and traditional face
to face instruction co-exist.
Abstract: Within the domain of Systems Engineering the need
to perform property aggregation to understand, analyze and manage
complex systems is unequivocal. This can be seen in numerous
domains such as capability analysis, Mission Essential Competencies
(MEC) and Critical Design Features (CDF). Furthermore, the need
to consider uncertainty propagation as well as the sensitivity of
related properties within such analysis is equally as important when
determining a set of critical properties within such a system.
This paper describes this property breakdown in a number of
domains within Systems Engineering and, within the area of CDFs,
emphasizes the importance of uncertainty analysis. As part of this, a
section of the paper describes possible techniques which may be used
within uncertainty propagation and in conclusion an example is
described utilizing one of the techniques for property and uncertainty
aggregation within an aircraft system to aid the determination of
Critical Design Features.
Abstract: This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial
Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water
flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by
sensors to construct an empirical model for time series prediction and
classification of events. These two components have been installed,
tested and verified in an experimental site in a UK water distribution
system. Verification of the system has been achieved from a series of
simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network
management.
Abstract: A study of various turbulent inflow generation methods
was performed to compare their relative effectiveness for LES
computations of turbulent boundary layers. This study confirmed
the quality of the turbulent information produced by the family of
recycling and rescaling methods which take information from within
the computational domain. Furthermore, more general inflow methods
also proved applicable to such simulations, with a precursor-like
inflow and a random inflow augmented with forcing planes showing
promising results.
Abstract: Computer-based decision support (CDSS) systems can
deliver real patient care and increase chances of long-term survival in
areas of chronic disease management prone to poor control. One such
CDSS, for the management of warfarin, is described in this paper and
the outcomes shown. Data is derived from the running system and
show a performance consistently around 20% better than the
applicable guidelines.