Smart resource control in distribution network to improve the integration level of PV

This project was an innovative approach in developing smart coordination of available energy resources to improve the integration level of PV in distribution network. Voltage and loading issues are considered as the main concerns for future electricity grid which need to be avoided using such resources. A distributed control structure was proposed for the resources in distribution network to avoid noted power quality issues.

Scrapping the Australia network affects more than the ABC

The termination in the 2014 budget of the ABC’s international television broadcasting contract to run the federal government’s Australia Network service, barely a year into its ten-year term, was hardly a surprise. “Soft power” or “soft diplomacy” initiatives such as the Australia Network and international aid schemes have been hit especially hard in this budget. If, as Treasurer Hockey has repeatedly claimed, this was a budget for the nation, then what do these decisions say about the value this government places on Australia’s international cultural image and internationalism more generally?

Spatial prediction on a river network

This article develops methods for spatially predicting daily change of dissolved oxygen (Dochange) at both sampled locations (134 freshwater sites in 2002 and 2003) and other locations of interest throughout a river network in South East Queensland, Australia. In order to deal with the relative sparseness of the monitoring locations in comparison to the number of locations where one might want to make predictions, we make a classification of the river and stream locations. We then implement optimal spatial prediction (ordinary and constrained kriging) from geostatistics. Because of their directed-tree structure, rivers and streams offer special challenges. A complete approach to spatial prediction on a river network is given, with special attention paid to environmental exceedances. The methodology is used to produce a map of Dochange predictions for 2003. Dochange is one of the variables measured as part of the Ecosystem Health Monitoring Program conducted within the Moreton Bay Waterways and Catchments Partnership.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.

Imputing a continuous income variable from a bracketed income variable with special attention to missing observations

This paper proposes a method, based on polychotomous discrete choice methods, to impute a continuous measure of income when only a bracketed measure of income is available and for only a subset of the obsevations. The method is shown to perform well with CP5 data. © 1991.

Cryptology and network security

This book constitutes the refereed proceedings of the 11th International Conference on Cryptology and Network Security, CANS 2012, held in Darmstadt, Germany, in December 2012. The 22 revised full papers, presented were carefully reviewed and selected from 99 submissions. The papers are organized in topical sections on cryptanalysis; network security; cryptographic protocols; encryption; and s-box theory.

SWIRLnet : portable anemometer network for wind speed measurements of land-falling tropical cyclones

Wind speed measurement systems are sparse in the tropical regions of Australia. Tropical cyclone wind speeds impacting communities are often ‘guestimated’ from analyzing damaged structures. A re-locatable anemometer system is required to enable measurements of wind speeds. This paper discusses design criteria of the tripods and tie down system, proposed deployment of the anemometers, instrumentation, and data logging. Preliminary assessment of the anemometer response indicates a reliable system for 1 second response, however, it is noted that the Australian building code and wind loading standard uses a moving average time of approximately 0.2 seconds for its wind speed design criteria.

Molecular network analysis using reverse phase protein microarrays for patient tailored therapy.

The practice of medicine has always aimed at individualized treatment of disease. The relationship between patient and physician has always been a personal one, and the physician's choice of treatment has been intended to be the best fit for the patient's needs. The necessary pooling/grouping of disease families and their assignment to a number of drugs or treatment methods has, consequently, led to an increase in the number of effective therapies. However, given the heterogeneity of most human diseases, and cancer specifically, it is currently impossible for the treating clinician to effectively predict a patient's response and outcome based on current technologies, much less the idiosyncratic resistances and adverse effects associated with the limited therapeutic options.

Wind speed measurements of land-falling tropical cyclones using SWIRLnet, a portable anemometer network

Wind speed measurement systems are sparse in the tropical regions of Australia. Given this, tropical cyclone wind speeds impacting communities are seldom measured and often only ‘guestimated’ by analysing the extent of damage to structures. In an attempt to overcome this dearth of data, a re-locatable network of anemometers to be deployed prior to tropical cyclone landfall is currently being developed. This paper discusses design criteria of the network’s tripods and tie down system, proposed deployment of the anemometers, instrumentation and data logging. Preliminary assessment of the anemometer response indicates a reliable system for measuring the spectral component of wind with frequencies of approximately 1 Hz. This system limitation highlights an important difference between the capabilities of modern instrumentation and that of the Dines anemometer (around 0.2 seconds) that was used to develop much of the design criteria within the Australian building code and wind loading standard.

Cholesterol regulates Syntaxin 6 trafficking at trans-Golgi network endosomal boundaries.

Inhibition of cholesterol export from late endosomes causes cellular cholesterol imbalance, including cholesterol depletion in the trans-Golgi network (TGN). Here, using Chinese hamster ovary (CHO) Niemann-Pick type C1 (NPC1) mutant cell lines and human NPC1 mutant fibroblasts, we show that altered cholesterol levels at the TGN/endosome boundaries trigger Syntaxin 6 (Stx6) accumulation into VAMP3, transferrin, and Rab11-positive recycling endosomes (REs). This increases Stx6/VAMP3 interaction and interferes with the recycling of αVβ3 and α5β1 integrins and cell migration, possibly in a Stx6-dependent manner. In NPC1 mutant cells, restoration of cholesterol levels in the TGN, but not inhibition of VAMP3, restores the steady-state localization of Stx6 in the TGN. Furthermore, elevation of RE cholesterol is associated with increased amounts of Stx6 in RE. Hence, the fine-tuning of cholesterol levels at the TGN-RE boundaries together with a subset of cholesterol-sensitive SNARE proteins may play a regulatory role in cell migration and invasion.

Demonstration of nonlinear absorption in Au semi-continuous film by electrical measurement

We have demonstrated the nonlinear absorption at 532 nm wavelength in an Au semi-continuous film (SF) resulting from smearing of the Fermi distribution and diffusion of conduction electrons into the substrate. The Au SF was irradiated by a pulsed laser with 8 ns pulse width at 532 nm in near resonance with the interband transition of the Au. We determined the temperature increase in the SF for different intensities by electrical measurement. We calculated the temperature increase by using a 1D heat transport equation; comparing the results of the calculation with measured values for the temperature increase, revealed the nonlinear absorption in the Au SF. We employed this deviation from linear behaviour to determine the nonlinear absorption coefficient.

Unidirectional arrays of vertically standing graphenes in reactive plasmas

The possibility for the switch-over of the growth mode from a continuous network to unidirectional arrays of well-separated, self-organized, vertically oriented graphene nanosheets has been demonstrated using a unique, yet simple plasma-based approach. The process enables highly reproducible, catalyst-free synthesis of arrays of graphene nanosheets with reactive open graphitic edges facing upwards. Effective control over the nanosheet length, number density, and the degree of alignment along the electric field direction is achieved by a simple variation of the substrate bias. These results are of interest for environment-friendly fabrication of next-generation nanodevices based on three-dimensional, ordered self-organized nanoarrays of active nanostructures with very large surface areas and aspect ratios, highly reactive edges, and controlled density on the substrate. Our simple and versatile plasma-based approach paves the way for direct integration of such nanoarrays directly into the Si-based nanodevice platform.

Use of reverse phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma

Cancer can be defined as a deregulation or hyperactivity in the ongoing network of intracellular and extracellular signaling events. Reverse phase protein microarray technology may offer a new opportunity to measure and profile these signaling pathways, providing data on post-translational phosphorylation events not obtainable by gene microarray analysis. Treatment of ovarian epithelial carcinoma almost always takes place in a metastatic setting since unfortunately the disease is often not detected until later stages. Thus, in addition to elucidation of the molecular network within a tumor specimen, critical questions are to what extent do signaling changes occur upon metastasis and are there common pathway elements that arise in the metastatic microenvironment. For individualized combinatorial therapy, ideal therapeutic selection based on proteomic mapping of phosphorylation end points may require evaluation of the patient's metastatic tissue. Extending these findings to the bedside will require the development of optimized protocols and reference standards. We have developed a reference standard based on a mixture of phosphorylated peptides to begin to address this challenge.

Brain decoding based on functional magnetic resonance imaging using machine learning : a comparative study

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.