Statistical modelling of artificial neural network for sorting temporally synchronous spikes

Artificial neural network (ANN) models are able to predict future events based on current data. The usefulness of an ANN lies in the capacity of the model to learn and adjust the weights following previous errors during training. In this study, we carefully analyse the existing methods in neuronal spike sorting algorithms. The current methods use clustering as a basis to establish the ground truths, which requires tedious procedures pertaining to feature selection and evaluation of the selected features. Even so, the accuracy of clusters is still questionable. Here, we develop an ANN model to specially address the present drawbacks and major challenges in neuronal spike sorting. New enhancements are introduced into the conventional backpropagation ANN for determining the network weights, input nodes, target node, and error calculation. Coiflet modelling of noise is employed to enhance the spike shape features and overshadow noise. The ANN is used in conjunction with a special spiking event detection technique to prioritize the targets. The proposed enhancements are able to bolster the training concept, and on the whole, contributing to sorting neuronal spikes with close approximations.

Modeling, parameter measurement and sensorless speed estimation of IPM synchronous generator for direct drive variable speed wind turbine application

This paper presents simple methods of determining parameters of interior permanent magnet (IPM) synchronous generator such as magnet flux (λM), d-axis inductance (Ld) and q-axis inductance (Lq) of IPM synchronous generator, which are used to control the wind turbine generator. These methods are simple and do not require any complex theory, signal injection or special equipment. Moreover, a sensorless speed estimator is proposed to estimate the speed of the generator without using speed sensor. The measured parameters are used in this speed estimator. The elimination of speed sensor will enhance the system robustness and reduce the design complexity and system cost for a small-scale wind turbine considered in this paper. The effectiveness of parameter measurement methods and sensorless speed estimator is demonstrated by experimental results. Experimental results show that the proposed speed estimator that uses the measured parameters can estimate the generator speed with a small error.

Building virtual learning communities

This chapter introduces the concept of virtual learning communities and discusses and further enhances the theory and definitions presented in related literature. A model comprising four criteria essential to virtual learning communities is presented and discussed in detail. Theory and case studies relating to the impact of virtual learning communities on distance education and students from diverse cultural groups are also examined. In addition, this chapter investigates the enabling technologies and facilitation that is required to build virtual learning communities. Other case studies are used to illustrate the process of building virtual learning communities. Emerging technologies such as wikis and video lectures are also analysed to determine the effects they have on building and sustaining effective virtual learning communities.

The role of trading partner relationships in determining innovation performance: an empirical examination

This paper examines the respective roles of trading partner relationships and innovation management practices in predicting product and process related innovation performance. The empirical data were drawn from 194 Australian managers. Data analysis using structural equation modelling indicates that supplier relationships and customer relationships have less impact on product and process innovation performance than do knowledge and creativity management. However, the results also indicate that trading partner relationships have a strong and positive association with innovation management practices, meaning that organisations commonly implement both in a synchronous manner.

Asynchronous patterns of reproduction for the sympatric scallops Chlamys bifrons and Chlamys asperrima (Bivalvia : Pectinidae) in South Australia

Patterns of spawning activity were assessed by monitoring gonad states over 2.5 years for Chlamys asperrima and Chlamys bifrons at two sites in Gulf St Vincent, South Australia. Chlamys asperrima appeared to have a minor spawning in June, followed by a major spawning starting in late August. In contrast, the gonads of C. bifrons were regressed only during winter and it appeared that C. bifrons spawned for a long period, from late spring (September) until early autumn (March). At one site where sampling was frequent, there was evidence of three series of C. bifrons spawning events during the summer of 1994/95 and at least two series of events during 1995/96. Build-up and decrease in gonad weight was quick, but there was strong evidence of serial spawning for both species. Subsequently, we once observed C. asperrima spawning in situ at Edithburgh Jetty, at a time when gonad weights had been decreasing in previous years, but also long after the time when peak gonad weights had usually occurred. Only patches within the population were seen spawning, with scallops not spawning observed less than 100 m away from those that were. Indirect sampling of gonad condition also suggested that spawning in C. bifrons at Largs Bay was not always synchronous among patches of scallops within a population, nor always between sexes within patches.

A pHMM-ANN based discriminative approach to promoter identification in prokaryote genomic contexts

The computational approach for identifying promoters on increasingly large genomic sequences has led to many false positives. The biological significance of promoter identification lies in the ability to locate true promoters with and without prior sequence contextual knowledge. Prior approaches to promoter modelling have involved artificial neural networks (ANNs) or hidden Markov models (HMMs), each producing adequate results on small scale identification tasks, i.e. narrow upstream regions. In this work, we present an architecture to support prokaryote promoter identification on large scale genomic sequences, i.e. not limited to narrow upstream regions. The significant contribution involved the hybrid formed via aggregation of the profile HMM with the ANN, via Viterbi scoring optimizations. The benefit obtained using this architecture includes the modelling ability of the profile HMM with the ability of the ANN to associate elements composing the promoter. We present the high effectiveness of the hybrid approach in comparison to profile HMMs and ANNs when used separately. The contribution of Viterbi optimizations is also highlighted for supporting the hybrid architecture in which gains in sensitivity (+0.3), specificity (+0.65) and precision (+0.54) are achieved over existing approaches.

Teaching and learning: flexible modes and technology applications

Australian universities face many challenges In providing postgraduate midwifery education opportunities for registered nurses, particularly for those residing in rural areas. This paper will describe the measures implemented by a team of midwifery academics of Deakin university, Melbourne campus, specifically for units of study within the Graduate Diploma of Midwifery. As a consequence of these measures, student travel to a campus of the university and separation from their families and communities have been reduced. These innovative measures include a blended teaching approach incorporating face-to-face and online teaching consisting of Deakin Studies Online based in Web CT Vista, and Elluminate Live, an interactive online synchronous communication tool. Over the past 20 years in Australia, Deakin university has led the way in computer mediated learning methods and the challenge was to provide appropriate teaching strategies for course content to meet the requirements of the regulatory authority, the Nurses Board of Victoria (NBV), while promoting pedagogical methods of teaching and learning.

Speed of adjustment within currency markets

One measure of market efficiency is the speed at which prices adjust to fundamental value with the arrival of information. This paper examines this issue by estimating speed of adjustment coefficients using three  methodologies for eight currencies for the entire year of 1996 using half hourly non-overlapping return intervals. We find that the bulk of adjustment to fundamental value for all currencies occurs within the hour but then quickly deteriorates. Within the hour adjustment is sufficiently quick to be considered efficient but the lack of full adjustment to fundamental value is not what would be predicted within an efficient market. There is no evidence for any of the currencies studied of a tendency to over react. There is also little difference in the speeds of adjustment between actively and less actively traded  currencies. There is however a definite difference in the speed at which currencies adjustment depending on whether they are free floating or managed exchange rates. Free floating rates adjust much quicker. Government intervention slows adjustment to fundamental value.

An evaluation of contemporary hidden Markov model genefinders with a predicted exon taxonomy

We present an independent evaluation of six recent hidden Markov model (HMM) genefinders. Each was tested on the new dataset (FSH298), the results of which showed no dramatic improvement over the genefinders tested five years ago. In addition, we introduce a comprehensive taxonomy of predicted exons and classify each resulting exon accordingly. These results are useful in measuring (with finer granularity) the effects of changes in a genefinder. We present an analysis of these results and identify four patterns of inaccuracy common in all HMM-based results.

Individual variation in the pup attraction call produced by female Australian fur seals during early lactation

Otariid seals (fur seals and sea lions) are colonial breeders with large numbers of females giving birth on land during a synchronous breeding period. Once pups are born, females alternate between feeding their young ashore and foraging at sea. Upon return, both mother and pup must relocate each other and it is thought to be primarily facilitated by vocal recognition. Vocalizations of thirteen female Australian fur seals (Arctocephalus pusillus doriferus) were recorded during the breeding seasons of December 2000 and 2001, when pups are aged from newborns to one month. The pup attraction call was examined to determine whether females produce individually distinct calls which could be used by pups as a basis for vocal recognition. Potential for individual coding, discriminant function analysis (DFA), and classification and regression tree analysis were used to determine which call features were important in separating individuals. Using the results from all three analyses: F0, MIN F and DUR were considered important in separating individuals. In 76% of cases, the PAC was classified to the correct caller, using DFA, suggesting that there is sufficient stereotypy within individual calls, and sufficient variation between them, to enable vocal recognition by pups of this species.

Application of podcasting in online engineering education

Applications of mobile technologies for engineering education can be found in the literature, but, many of the reported applications are aimed at the online (wirelessly), on-campus, synchronous and proximal use of mobile technologies. Mobile technologies in engineering education can encompass more than the proximal teaching and learning environment-they can be offline, asynchronous and at a distance from the classroom. This paper reports on the initial application of `podcasting' in a wholly online engineering study unit. It presents the rationale for, technical development details of, and, limited evaluation of this initial podcasting trial.

Generalised 2D-correlation NMR analysis of a wine fermentation

A wine fermentation has been monitored on a daily basis by 1H NMR spectroscopy. Following data pre-processing that includes synthesis of the spectra to ensure all peaks are of constant half-width, the series of spectra were examined using generalised two-dimensional correlation techniques. Synchronous and asynchronous data maps have been generated and employed to interpret the changes in the fermentation process as a function of time. The results illustrate the potential of high resolution NMR with multivariate data analysis as a tool for process monitoring and the manner in which two-dimensional correlation mapping can aid in data interpretation.

Research into cyberbullying : student perspectives on cybersafe learning environments

This paper reports a qualitative study designed to investigate the issues of cybersafety and cyberbullying and report how students are coping with them. Through discussion with 74 students, aged from 10 to 17, in focus groups divided into three age levels, data were gathered in three schools in Victoria, Australia, where few such studies had been set. Social networking sites and synchronous chat sites were found to be the places where cyberbullying most commonly occurred, with email and texting on mobile phones also used for bullying. Grades 8 and 9 most often reported cyberbullying and also reported behaviours and internet contacts that were cybersafety risks. Most groups preferred to handle these issues themselves or with their friends rather then alert parents and teachers who may limit their technology access. They supported education about these issues for both adults and school students and favoured a structured mediation group of their peers to counsel and advise victims.

Bearing-only localization using geometrically constrained optimization

We examine the problem of optimal bearing-only localization of a single target using synchronous measurements from multiple sensors. We approach the problem by forming geometric relationships between the measured parameters and their corresponding errors in the relevant emitter localization scenarios. Specifically, we derive a geometric constraint equation on the measurement errors in such a scenario. Using this constraint, we formulate the localization task as a constrained optimization problem that can be performed on the measurements in order to provide the optimal values such that the solution is consistent with the underlying geometry. We illustrate and confirm the advantages of our approach through simulation, offering detailed comparison with traditional maximum likelihood (TML) estimation.

Population structure and life history characteristics of euastacus bispinosus and cherax destructor (Parastacidae) in the Grampians National Park, Australia

Despite being the most widely distributed and cultured freshwater crayfish species in Australia, relatively little is known about the ecology of Cherax destructor outside of captivity. Similarly, few ecological studies have been conducted on the large and threatened stream dwelling Australian freshwater crayfish Euastacus bispinosus. A series of seasonal sampling surveys over two years investigated the population structure, life history and reproductive timing of C. destructor in fire dam habitats, and of E. bispinosus in channel (stream) habitats, in the Grampians National Park in south-west Victoria, Australia. Cherax destructor individuals in the largest size class (50 – 59.95 mm OCL) were not abundant during the study, while those belonging to the 0 – 9.95 mm OCL size class were more frequent in summer than at other times of year, suggesting synchronous recruitment in fire dam habitats. Individuals in the reproductively active mid-size classes were also frequent in summer. For E. bispinosus, sex ratios in spring always favoured females, although there were no clear trends for other times of year. Gravid E. bispinosus females were found in winter and spring throughout the study, and were sexually mature at a smaller size than has previously been reported.