Learnings, case studies and guidelines for establishing shared and collaborative service delivery in the non-government sector: Evaluation of the Multi-Tenant Service Centre (MTSC) Pilots Project

This report presents learnings, case studies, guidelines and resources for non-government organisations that are planning to implement shared or collaborative arrangements with other agencies. It summarises results from an evaluation of the implementation phase of the Multi-Tenant Service Centre (MTSC) Pilots Project, which was completed in June 2008. This evaluation shows that developing and implementing shared and collaborative arrangements is a complex process that presents many risks, challenges and barriers to success, but can have many potential benefits for non government organisations. As this report makes clear, there is no ‘one size fits all’ approach to this process. The MTSC Pilots Project was conducted by the Department of Communities (DoC), Queensland Government, as part of its Strengthening Non-Government Organisations strategy. The objective of the MTSC Pilots initiative was to co-locate separate service providers in an appropriately located centre, operating with effective and transparent management, which enabled service providers to improve client services. Three MTSC consortiums in Mackay, Caboolture and Toowoomba were selected as the pilots over a four year period from 2006 – 2010.

NEU-MODEL : a multi-level object-oriented dynamic emulation laboratory

Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.

Multi-level neural modelling : an application of object-oriented software engineering

Neu-Model, an ongoing project aimed at developing a neural simulation environment that is extremely computationally powerful and flexible, is described. It is shown that the use of good Software Engineering techniques in Neu-Model’s design and implementation is resulting in a high performance system that is powerful and flexible enough to allow rigorous exploration of brain function at a variety of conceptual levels.

Acoustic emission activity from the two main types of small multi-cylinder diesel engine fuel injection systems

Effective fuel injector operation and efficient combustion are two of the most critical aspects when Diesel engine performance, efficiency and reliability are considered. Indeed, it is widely acknowledged that fuel injection equipment faults lead to increased fuel consumption, reduced power, greater levels of exhaust emissions and even unexpected engine failure. Previous investigations have identified fuel injector related acoustic emission activity as being caused by mechanisms such as fuel line pressure build-up; fuel flow through injector nozzles, injector needle opening and closing impacts and premixed combustion related pulses. Few of these investigations however, have attempted to categorise the close association and interrelation that exists between fuel injection equipment function and the acoustic emission generating mechanisms. Consequently, a significant amount of ambiguity remains in the interpretation and categorisation of injector related AE activity with respect to the functional characteristics of specific fuel injection equipment. The investigation presented addresses this ambiguity by detailing a study in which AE signals were recorded and analysed from two different Diesel engines employing the two commonly encountered yet fundamentally different types of fuel injection equipment. Results from tests in which faults were induced into fuel injector nozzles from both indirect-injection and direct-injection engines show that functional differences between the main types of fuel injection equipment results in acoustic emission activity which can be specifically related to the type of fuel injection equipment used.

Job satisfaction of preventive medicine workers in northern Vietnam : a multi-method approach

In the health care industry, Job Satisfaction (JS) is linked with work performance, psychological well-being and employee turnover. Although research into JS among health professionals has a long history worldwide, there has been very little analysis in Vietnam. No study has addressed JS of preventive medicine workers in Vietnam, and there is no reliable and valid instrument in Vietnamese language and context for evaluation of JS in this group. This project was conducted to fill these gaps. The findings contribute evidence regarding factors that influence JS in this sector of the health industry that should be applied to personnel management policies and practices in Vietnam.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

The second chance project: A multi-level examination of secondary prevention practices for Saudi people following a recent cardiac event

The study examined the health-related behaviours of Saudi people following a recent cardiac event and identified the factors that influence these behaviours using McLeroy et al.'s (1988) Ecological Model of Health Behaviours as a guiding framework. The study was one of the first in Saudi Arabia to examine the health-related behaviours of Saudi people following a recent cardiac event. The study findings emphasise the importance of a program that integrates secondary prevention practices, educational approaches and targeted supportive services in cardiac care in Saudi Arabia.

Multi-objective models and techniques for analysing the absolute capacity of railway networks

Railway capacity determination and expansion are very important topics. In prior research, the competition between different entities such as train services and train types, on different network corridors however have been ignored, poorly modelled, or else assumed to be static. In response, a comprehensive set of multi-objective models have been formulated in this article to perform a trade-off analysis. These models determine the total absolute capacity of railway networks as the most equitable solution according to a clearly defined set of competing objectives. The models also perform a sensitivity analysis of capacity with respect to those competing objectives. The models have been extensively tested on a case study and their significant worth is shown. The models were solved using a variety of techniques however an adaptive E constraint method was shown to be most superior. In order to identify only the best solution, a Simulated Annealing meta-heuristic was implemented and tested. However a linearization technique based upon separable programming was also developed and shown to be superior in terms of solution quality but far less in terms of computational time.

Multi-action recognition via stochastic modelling of optical flow and gradients

In this paper we propose a novel approach to multi-action recognition that performs joint segmentation and classification. This approach models each action using a Gaussian mixture using robust low-dimensional action features. Segmentation is achieved by performing classification on overlapping temporal windows, which are then merged to produce the final result. This approach is considerably less complicated than previous methods which use dynamic programming or computationally expensive hidden Markov models (HMMs). Initial experiments on a stitched version of the KTH dataset show that the proposed approach achieves an accuracy of 78.3%, outperforming a recent HMM-based approach which obtained 71.2%.

Maximum principle and numerical method for the multi-term time–space Riesz–Caputo fractional differential equations

The maximum principle for the space and time–space fractional partial differential equations is still an open problem. In this paper, we consider a multi-term time–space Riesz–Caputo fractional differential equations over an open bounded domain. A maximum principle for the equation is proved. The uniqueness and continuous dependence of the solution are derived. Using a fractional predictor–corrector method combining the L1 and L2 discrete schemes, we present a numerical method for the specified equation. Two examples are given to illustrate the obtained results.

Multi-layered model of individual HIV infection progression and mechanisms of phenotypical expression

Cite as: Perrin, Dimitri (2008) Multi-layered model of individual HIV infection progression and mechanisms of phenotypical expression. PhD thesis, Dublin City University.

Contracted site: Artist on paper, drawing

Traditionally the notion of drawing in-situ has suggested the physical presence of the artist in the environment under scrutiny. The assumption here of enhanced connectivity, however, is hasty in light of the idea that situation implies a relative spatial value determined by the interplay of subject and location, where the possibility of not being “in-situ” is problematic. The fact that traditional drawing in-situ, such as the rendering of landscape, requires a framing of the world “out there” suggests a distance between the perceived object of representation and the drawing surface. Rather than suggesting that some drawing is situated and other sorts of drawing are not, however, I argue that situation or site is variously extended and intensified depending on the nature of mediation between surface and environment. The suggestion here is that site is not so much a precondition as a performative function, developed in the act of drawing and always implicating the drawing surface. In my discussion I focus on specific works by Toba Khedoori and Cameron Robbins. As well, in using my own recent drawing practice as a case study, I argue that the geography of site is delimited neither by horizon nor the boundaries of the paper. Rather, I propose that site and drawing surface coincide in variously intensive and extensive ways.