Combining vocational and higher education studies to provide dual parallel qualifications – an Australian case study

Developing academic relationships between vocational colleges and universities in Australia has been problematic, with exchanges between the two sectors limited to linear articulation and prescribed credit transfer. Whilst some very good examples of collaboration exist, the two sectors generally operate independently of each other. The isolation of the sectors has meant frustration for students and employers who want a flexible, collaborative model to meet changing industry needs. This paper reports upon a pilot project in construction management at a Melbourne university that attempted to address these needs. It demonstrates how over a five year period, HE students completed electives in practical units within the VET sector. The overwhelming success of the project meant that practical electives were embedded in the construction management programme in 2007 and this paper reports on the third, final phase of the project in 2009/10 which saw construction management students graduate with a dual qualification – both a vocational qualification and a university degree. Interviews conducted in this final phase reveal that students and industry want the benefits of a practical and theoretical qualification. The paper raises critical questions about educational pathways and suggests long-term implications for construction and tertiary education in Australia and internationally.

Building the second generation of parallel/distributed virtual reality systems

We present the RhoVeR (Rhodes Virtual Reality) system and classify it as a second generation parallel/distributed virtual reality (DVR) system. We discuss the components of the system and thereby demonstrate its support for virtual reality application development, its configurable, parallel and distributed nature, and its synthesis of first generation DVR techniques.

Parallel developments in aprotic and protic ionic liquids : physical chemistry and applications

This Account covers research dating from the early 1960s in the field of low-melting molten salts and hydrates,which has recently become popular under the rubric of “ionic liquids”. It covers understanding gained in the principal author’s laboratories (initially in Australia, but mostly in the U.S.A.) from spectroscopic, dynamic, and thermodynamic studies and includes recent applications of this understanding in the fields of energy conversion and biopreservation. Both protic and aprotic varieties of ionic liquids are included, but recent studies have focused on the protic class because of the special applications made possible by the highly variable proton activities available in these liquids.

Backward modelling and look-ahead fuzzy energy management controller for a parallel hybrid vehicle

This paper focuses on a parallel hybrid electric vehicle. It first develops a model for the vehicle using the backward-looking approach where the flow of energy starts from wheels and spreads towards engine and electric motor. Next, a fuzzy logic-based strategy is developed to control the operation of the vehicle. The objectives of the controller include managing the energy flow from engine and electric motor, controlling transmission ratio, adjusting speed, and sustaining battery's state of charge. The controller examines current vehicle speed, demand torque, slope difference, state of charge of battery, and engine and electric motor rotation speeds. Then, it determines the best values for continuous variable transmission ratio, speed, and torque. A slope window scheme is also developed to take into account the look-ahead slope information and determine the best vehicle speed for better fuel economy. The developed model and control strategy are simulated. The simulation results are presented and discussed. It is shown that the use of the proposed fuzzy controller reduces fuel consumption.

Special issue: Building secure parallel and distributed networks and systems

Security and privacy have been the major concern when people build parallel and distributed networks and systems. While the attack systems have become more easy-to-use, sophisticated, and powerful, interest has greatly increased in the field of building more effective, intelligent, adaptive, active and high performance defense systems which are distributed and networked. This special issue focuses on the issues of building secure parallel and distributed networks and systems.

A family of planar parallel manipulators

A family of planar parallel manipulators is investigated and some novel members are proposed. The common feature of the studied manipulators is that the rotation axes of the actuated arms coincide. This feature makes it possible to rotate the whole arm system an infinite number of revolutions around the center of the manipulator. The result is a large workspace in relation to the footprint. Both 2- and 3-DOF variants are presented and the suitability of this family of manipulators for kinematic analysis is demonstrated. Thus, different methods to find optimal manipulability with respect to platform positioning and rotation have been analyzed.

Look-ahead intelligent energy management of a parallel hybrid electric vehicle

Improving fuel efficiency in vehicles can reduce the energy consumption concerns associated with operating the vehicles. This paper presents a model for a parallel hybrid electric vehicle. In the model, the flow of energy starts from wheels and spreads toward engine and electric motor. A fuzzy logic based control strategy is implemented for the vehicle. The controller manages the energy flow from the engine and the electric motor, controlling transmission ratio, adjusting speed, and sustaining battery's state of charge. The controller examines the vehicle speed, demand torque, slope difference, state of charge of battery, and engine and electric motor rotation speeds. It then determines the best values for continuous variable transmission ratio, speed, and torque. A slope window method is formed that takes into account the look-ahead slope information, and determines the best vehicle speed. The developed model and control strategy are simulated using real highway data relating to Nowra-Bateman Bay in Australia, and SAE Highway Fuel Economy Driving Schedule. The simulation results are presented and discussed. It is shown that the use of the proposed fuzzy controller reduces the fuel consumption of the vehicle.

Design of multiple sequence alignment algorithms on parallel, distributed memory supercomputers

The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.

Edge detection is a projection

A desirable property of any edge detector is that it be a projection in the mathematical sense, that is, that when it is applied to its own output it produces no further change. This report examines the behaviour of some conventional and some new operators when applied to line-drawings. The Marr-Hildreth and some gradient operators are among the conventional operators examined. Also a class of energy feature detectors is explored. It is shown that the energy feature detector is a true projection and does not proliferate edges when applied to a line-drawing, whereas several of the conventional operators do.

Electrospinning of nanofibres with parallel line surface texture for improvement of nerve cell growth

Nanofibres having a parallel line surface texture were electrospun from cellulose acetate butyrate solutions using a solvent mixture of acetone and N,N'-dimethylacetamide. The formation mechanism of the unusual surface feature was explored and attributed to the formation of voids on the jet surface at the early stage of electrospinning and subsequent elongation and solidification of the voids into a line surface structure. The fast evaporation of a highly volatile solvent, acetone, from the polymer solution was found to play a key role in the formation of surface voids, while the high viscosity of the residual solution after the solvent evaporation ensured the line surface to be maintained after the solidification. Based on this principle, nanofibres having a similar surface texture were also electrospun successfully from other polymers, such as cellulose acetate, polyvinylidene fluoride, poly(methyl methacrylate), polystyrene and poly(vinylidene fluoride-co-hexafluoropropene), either from the same or from different solvent systems. Polarized Fourier transform infrared spectroscopy was used to measure the polymer molecular orientation within nanofibres. Schwann cells were grown on both aligned and randomly oriented nanofibre mats. The parallel line surface texture assisted in the growth of Schwann cells especially at the early stage of cell culture regardless of the fibre orientation. In contrast, the molecular orientation within nanofibres showed little impact on the cell growth.

Parallel matrix inversion techniques

In this paper, we present techniques for inverting sparse, symmetric and positive definite matrices on parallel and distributed computers. We propose two algorithms, one for SIMD implementation and the other for MIMD implementation. These algorithms are modified versions of Gaussian elimination and they take into account the sparseness of the matrix. Our algorithms perform better than the general parallel Gaussian elimination algorithm. In order to demonstrate the usefulness of our technique, we implemented the snake problem using our sparse matrix algorithm. Our studies reveal that the proposed sparse matrix inversion algorithm significantly reduces the time taken for obtaining the solution of the snake problem. In this paper, we present the results of our experimental work.

Exploiting side information in locality preserving projection

Even if the class label information is unknown, side information represents some equivalence constraints between pairs of patterns, indicating whether pairs originate from the same class. Exploiting side information, we develop algorithms to preserve both the intra-class and inter-class local structures. This new type of locality preserving projection (LPP), called LPP with side information (LPPSI), preserves the data's local structure in the sense that the close, similar training patterns will be kept close, whilst the close but dissimilar ones are separated. Our algorithms balance these conflicting requirements, and we further improve this technique using kernel methods. Experiments conducted on popular face databases demonstrate that the proposed algorithm significantly outperforms LPP. Further, we show that the performance of our algorithm with partial side information (that is, using only small amount of pair-wise similarity/dissimilarity information during training) is comparable with that when using full side information. We conclude that exploiting side information by preserving both similar and dissimilar local structures of the data significantly improves performance.

Robust learning of discriminative projection for multicategory classification on the Stiefel manifold

Learning a robust projection with a small number of training samples is still a challenging problem in face recognition, especially when the unseen faces have extreme variation in pose, illumination, and facial expression. To address this problem, we propose a framework formulated under statistical learning theory that facilitates robust learning of a discriminative projection. Dimensionality reduction using the projection matrix is combined with a linear classifier in the regularized framework of lasso regression. The projection matrix in conjunction with the classifier parameters are then found by solving an optimization problem over the Stiefel manifold. The experimental results on standard face databases suggest that the proposed method outperforms some recent regularized techniques when the number of training samples is small.

Ridge regression for two dimensional locality preserving projection

Two Dimensional Locality Preserving Projection (2D-LPP) is a recent extension of LPP, a popular face recognition algorithm. It has been shown that 2D-LPP performs better than PCA, 2D-PCA and LPP. However, the computational cost of 2D-LPP is high. This paper proposes a novel algorithm called Ridge Regression for Two Dimensional Locality Preserving Projection (RR- 2DLPP), which is an extension of 2D-LPP with the use of ridge regression. RR-2DLPP is comparable to 2DLPP in performance whilst having a lower computational cost. The experimental results on three benchmark face data sets - the ORL, Yale and FERET databases - demonstrate the effectiveness and efficiency of RR-2DLPP compared with other face recognition algorithms such as PCA, LPP, SR, 2D-PCA and 2D-LPP.

Agents in adversarial domains - modelling environments in parallel

We present a model of an environment to evaluate the behavior of an agent trying to hide from a pursuer is presented. The model computes the direction and the amount of protection provided by the environment. The computational complexity of this problem is improved by using a parallel implementation of this algorithm.