Enhancing pathways for ACE learners : Building the capacity of Adult and Community Education (ACE) providers to offer non-accredited courses and VET modules with pathways into VET programs.

This report presents findings from a project that considered a) the current capacity of Adult and Community Education (ACE) providers to offer non-accredited courses and single modules of accredited learning that provide pathways into full scale accredited VET programs, and b) the factors that aid and inhibit this from occurring. Based on the findings, suggestions are made as to what needs to be done to extend this capacity and thereby to achieve the goals outlined in the 2008 Ministerial Declaration on Adult Community Education.

Realisation of ternary sigma-delta modulated arithmetic processing modules

Sigma-delta modulated systems have a number of very appealing properties and are, therefore, heavily used in analog to digital converters, amplifiers, and modulators. This paper presents new results which indicate that they may also have significant potential for general purpose arithmetic processing.

Evaluation of an intervention to promote protective infant feeding practices to prevent childhood obesity : outcomes of the NOURISH RCT at 14 months of age and 6 months post the first of two intervention modules

OBJECTIVE: To evaluate a universal obesity prevention intervention, which commenced at infant age 4-6 months, using outcome data assessed 6-months after completion of the first of two intervention modules and 9 months from baseline. DESIGN: Randomised controlled trial of a community-based early feeding intervention. SUBJECTS AND METHODS: 698 first-time mothers (mean age 30±5 years) with healthy term infants (51% male) aged 4.3±1.0 months at baseline. Mothers and infants were randomly allocated to self-directed access to usual care or to attend two group education modules, each delivered over three months, that provided anticipatory guidance on early feeding practices. Outcome data reported here were assessed at infant age 13.7±1.3 months. Anthropometrics were expressed as z-scores (WHO reference). Rapid weight gain was defined as change in weight-for-age z-score (WAZ) > +0.67. Maternal feeding practices were assessed via self-administered questionnaire. RESULTS: There were no differences according to group allocation on key maternal and infant characteristics. At follow up (n=598 [86%]) the intervention group infants had lower BMIZ (0.42±0.85 vs 0.23±0.93, p=0.009) and infants in the control group were more likely to show rapid weight gain from baseline to follow up (OR=1.5 CI95%1.1-2.1, p=0.014). Mothers in the control group were more likely to report using non- responsive feeding practices that fail to respond to infant satiety cues such as encouraging eating by using food as a reward (15% vs 4%, p=0.001) or using games ( 67% vs 29%, p<0.001). CONCLUSIONS: These results provide early evidence that anticipatory guidance targeting the ‘when, what and how’ of solid feeding can be effective in changing maternal feeding practices and, at least in the short term, reducing anthropometric indicators of childhood obesity risk. Analyses of outcomes at later ages are required to determine if these promising effects can be sustained.

Cascaded DC-DC converter connection of photovoltaic modules

New residential scale photovoltaic (PV) arrays are commonly connected to the grid by a single dc-ac inverter connected to a series string of pv panels, or many small dc-ac inverters which connect one or two panels directly to the ac grid. This paper proposes an alternative topology of nonisolated per-panel dc-dc converters connected in series to create a high voltage string connected to a simplified dc-ac inverter. This offers the advantages of a "converter-per-panel" approach without the cost or efficiency penalties of individual dc-ac grid connected inverters. Buck, boost, buck-boost, and Cu´k converters are considered as possible dc-dc converters that can be cascaded. Matlab simulations are used to compare the efficiency of each topology as well as evaluating the benefits of increasing cost and complexity. The buck and then boost converters are shown to be the most efficient topologies for a given cost, with the buck best suited for long strings and the boost for short strings. While flexible in voltage ranges, buck-boost, and Cu´k converters are always at an efficiency or alternatively cost disadvantage.

Cascaded DC-DC converter connection of photovoltaic modules

New residential scale photovoltaic (PV) arrays are commonly connected to the grid by a single DC-AC inverter connected to a series string of PV modules, or many small DC-AC inverters which connect one or two modules directly to the AC grid. This paper shows that a "converter-per-module" approach offers many advantages including individual module maximum power point tracking, which gives great flexibility in module layout, replacement, and insensitivity to shading; better protection of PV sources, and redundancy in the case of source or converter failure; easier and safer installation and maintenance; and better data gathering. Simple nonisolated per-module DC-DC converters can be series connected to create a high voltage string connected to a simplified DC-AC inverter. These advantages are available without the cost or efficiency penalties of individual DC-AC grid connected inverters. Buck, boost, buck-boost and Cuk converters are possible cascadable converters. The boost converter is best if a significant step up is required, such as with a short string of 12 PV modules. A string of buck converters requires many more modules, but can always deliver any combination of module power. The buck converter is the most efficient topology for a given cost. While flexible in voltage ranges, buck-boost and Cuk converters are always at an efficiency or alternatively cost disadvantage

Predicting fault-prone software modules with rank sum classification

The detection and correction of defects remains among the most time consuming and expensive aspects of software development. Extensive automated testing and code inspections may mitigate their effect, but some code fragments are necessarily more likely to be faulty than others, and automated identification of fault prone modules helps to focus testing and inspections, thus limiting wasted effort and potentially improving detection rates. However, software metrics data is often extremely noisy, with enormous imbalances in the size of the positive and negative classes. In this work, we present a new approach to predictive modelling of fault proneness in software modules, introducing a new feature representation to overcome some of these issues. This rank sum representation offers improved or at worst comparable performance to earlier approaches for standard data sets, and readily allows the user to choose an appropriate trade-off between precision and recall to optimise inspection effort to suit different testing environments. The method is evaluated using the NASA Metrics Data Program (MDP) data sets, and performance is compared with existing studies based on the Support Vector Machine (SVM) and Naïve Bayes (NB) Classifiers, and with our own comprehensive evaluation of these methods.

Combining word semantics within complex Hilbert space for information retrieval

Complex numbers are a fundamental aspect of the mathematical formalism of quantum physics. Quantum-like models developed outside physics often overlooked the role of complex numbers. Specifically, previous models in Information Retrieval (IR) ignored complex numbers. We argue that to advance the use of quantum models of IR, one has to lift the constraint of real-valued representations of the information space, and package more information within the representation by means of complex numbers. As a first attempt, we propose a complex-valued representation for IR, which explicitly uses complex valued Hilbert spaces, and thus where terms, documents and queries are represented as complex-valued vectors. The proposal consists of integrating distributional semantics evidence within the real component of a term vector; whereas, ontological information is encoded in the imaginary component. Our proposal has the merit of lifting the role of complex numbers from a computational byproduct of the model to the very mathematical texture that unifies different levels of semantic information. An empirical instantiation of our proposal is tested in the TREC Medical Record task of retrieving cohorts for clinical studies.

Privacy enhancements for hardware-based security modules

The increasing growth in the use of Hardware Security Modules (HSMs) towards identification and authentication of a security endpoint have raised numerous privacy and security concerns. HSMs have the ability to tie a system or an object, along with its users to the physical world. However, this enables tracking of the user and/or an object associated with the HSM. Current systems do not adequately address the privacy needs and as such are susceptible to various attacks. In this work, we analyse various security and privacy concerns that arise when deploying such hardware security modules and propose a system that allow users to create pseudonyms from a trusted master public-secret key pair. The proposed system is based on the intractability of factoring and finding square roots of a quadratic residue modulo a composite number, where the composite number is a product of two large primes. Along with the standard notion of protecting privacy of an user, the proposed system offers colligation between seemingly independent pseudonyms. This new property when combined with HSMs that store the master secret key is extremely beneficial to a user, as it offers a convenient way to generate a large number of pseudonyms using relatively small storage requirements.

Calculate excess mortality during heatwaves using Hilbert-Huang transform algorithm

Background Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data. Methods Special R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series. Results The Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors. Conclusions The HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.