HFL micro inverter with front-end diode clamped multi-level inverter and half-wave cycloconverter

A high-frequency-link (HFL) micro inverter with a front-end diode clamped multi-level inverter and a grid-connected half-wave cycloconverter is proposed. The diode clamped multi-level inverter with an auxiliary capacitor is used to generate high-frequency (HF) three level quasi square-wave output and it is fed into a series resonant tank to obtain high frequency continuous sinusoidal current. The obtained continuous sinusoidal current is modulated by using the grid-connected half-wave cycloconverter to obtain grid synchronized output current in phase with the grid voltage. The phase shift power modulation is used with auxiliary capacitor at the front-end multi-level inverter to have soft-switching. The phase shift between the HFL resonant current and half-wave cycloconverter input voltage is modulated to obtain grid synchronized output current.

What is the apparent angle of a Kelvin ship wave pattern?

While the half-angle which encloses a Kelvin ship wave pattern is commonly accepted to be 19.47 degrees, recent observations and calculations for sufficiently fast-moving ships suggest that the apparent wake angle decreases with ship speed. One explanation for this decrease in angle relies on the assumption that a ship cannot generate wavelengths much greater than its hull length. An alternative interpretation is that the wave pattern that is observed in practice is defined by the location of the highest peaks; for wakes created by sufficiently fast-moving objects, these highest peaks no longer lie on the outermost divergent waves, resulting in a smaller apparent angle. In this paper, we focus on the problems of free surface flow past a single submerged point source and past a submerged source doublet. In the linear version of these problems, we measure the apparent wake angle formed by the highest peaks, and observe the following three regimes: a small Froude number pattern, in which the divergent waves are not visible; standard wave patterns for which the maximum peaks occur on the outermost divergent waves; and a third regime in which the highest peaks form a V-shape with an angle much less than the Kelvin angle. For nonlinear flows, we demonstrate that nonlinearity has the effect of increasing the apparent wake angle so that some highly nonlinear solutions have apparent wake angles that are greater than Kelvin's angle. For large Froude numbers, the effect on apparent wake angle can be more dramatic, with the possibility of strong nonlinearity shifting the wave pattern from the third regime to the second. We expect our nonlinear results will translate to other more complicated flow configurations, such as flow due to a steadily moving closed body such as a submarine.

Great expectations : a project by Boxcopy for Federation Square, Next Wave Festival 2008

Part of the Next Wave MEMBRANE Project, Great Expectations draws attention to the parallels between our expectations of art and new technology to make the world a better place. The theme of the 2008 Next Wave Festival, ‘Closer Together’, refers to the way society is ― for the better or for the worse ― becoming increasingly connected by media and communication technologies. Sceptical of the acclaimed social achievements of new technologies, Boxcopy: Contemporary Art Space, a Brisbane-based artist-run initiative, explores the futility of human activities, including art production and consumption, with a collection of works created by young and emerging Brisbane artists. Works for this project include: Early machines such as the Commodore 64 were tape-based, and hence had their games distributed on ordinary cassettes (2009) by Tim Kerr & Extra Features (2008) by Tim Woodward; Spine (2008), Joseph Briekers; Whiteout (2008), Channon Goodwin; Explosive Revelations (2008), Daniel McKewen.

Suggestions for the next wave of BPM research : strengthening the theoretical core and exploring the protective belt

In this essay, I present a reflective and generative analysis of Business Process Management research, in which I analyze process management and the surrounding research program from the viewpoint of a theoretical paradigm embracing analytical, empirical, explanatory and design elements. I argue that this view not only reconciles different perceptions of BPM and different research streams, but that it also informs ways in which the BPM research program could develop into a much richer, more inclusive and overall more significant body of work than it has to date. I define three perspectives on a BPM research agenda, give several examples of exciting existing research, and offer key opportunities for further research that can (a) strengthen the core of BPM, (b) generate novel theory from BPM in relevant and topical big issue domains, and (c) explore more rigorously and comprehensively the protective belt of BPM assumptions that much of the present research abides by. The essay ends with some recommendations for continuing the debate about what constitutes BPM and some suggestions for how future research in this area might be carried out.

Food for Thought (Next Wave Festival)

Food for Thought embraces the notion that a revolution can start at the dinner table. Drawing inspiration from Judy Chicago’s seminal artwork ‘The Dinner Party’, LEVEL Artist Run Initiative hosted a series of dinner party events in order to create vibrant discussions concerning the role of women and feminism in the twenty-first century. The work consisted of a reading room, four dinner party events, and four public talks covering the topics: 'Women and the arts';'Generations: plurality and difference'; 'Women in the media'; and 'How can art contribute to political change for women in the 21st century?'

Method for planning and executing obstacle-free paths for rotating excavation machinery

This invention concerns the control of rotating excavation machinery, for instance to avoid collisions with obstacles. In a first aspect the invention is a control system for autonomous path planning in excavation machinery, comprising: A map generation subsystem to receive data from an array of disparate and complementary sensors to generate a 3-Dimensional digital terrain and obstacle map referenced to a coordinate frame related to the machine's geometry, during normal operation of the machine. An obstacle detection subsystem to find and identify obstacles in the digital terrain and obstacle map, and then to refine the map by identifying exclusion zones that are within reach of the machine during operation. A collision detection subsystem that uses knowledge of the machine's position and movements, as well as the digital terrain and obstacle map, to identify and predict possible collisions with itself or other obstacles, and then uses a forward motion planner to predict collisions in a planned path. And, a path planning subsystem that uses information from the other subsystems to vary planned paths to avoid obstacles and collisions. In other aspects the invention is excavation machinery including the control system; a method for control of excavation machinery; and firmware and software versions of the control system.

HFL PV micro-inverter with front-end current-fed converter and half-wave cycloconverter

A high-frequency-link micro inverter is proposed with a front-end dual inductor push-pull converter and a grid-connected half-wave cycloconverter. Pulse width modulation is used to control the front-end converter and phase shift modulation is used at the back-end converter to obtain grid synchronized output current. A series resonant circuit and high-frequency transformer are used to interface the front-end and the back-end converters. The operation of the proposed micro-inverter in grid-connected mode is validated using MATLAB/Simpower simulation. Experimental results are provided to further validate the operation.

Remaining useful life prediction of rotating equipment using covariate-based hazard models : industry applications

The ability to estimate the expected Remaining Useful Life (RUL) is critical to reduce maintenance costs, operational downtime and safety hazards. In most industries, reliability analysis is based on the Reliability Centred Maintenance (RCM) and lifetime distribution models. In these models, the lifetime of an asset is estimated using failure time data; however, statistically sufficient failure time data are often difficult to attain in practice due to the fixed time-based replacement and the small population of identical assets. When condition indicator data are available in addition to failure time data, one of the alternate approaches to the traditional reliability models is the Condition-Based Maintenance (CBM). The covariate-based hazard modelling is one of CBM approaches. There are a number of covariate-based hazard models; however, little study has been conducted to evaluate the performance of these models in asset life prediction using various condition indicators and data availability. This paper reviews two covariate-based hazard models, Proportional Hazard Model (PHM) and Proportional Covariate Model (PCM). To assess these models’ performance, the expected RUL is compared to the actual RUL. Outcomes demonstrate that both models achieve convincingly good results in RUL prediction; however, PCM has smaller absolute prediction error. In addition, PHM shows over-smoothing tendency compared to PCM in sudden changes of condition data. Moreover, the case studies show PCM is not being biased in the case of small sample size.

A review on prognostic techniques for non-stationary and non-linear rotating systems

The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

The dual nature of information systems in enabling a new wave of hardware ventures: Towards a theory

Hardware ventures are emerging entrepreneurial firms that create new market offerings based on development of digital devices. These ventures are important elements in the global economy but have not yet received much attention in the literature. Our interest in examining hardware ventures is specifically in the role that information system (IS) resources play in enabling them. We ask how the role of IS resources for hardware ventures can be conceptualized and develop a framework for assessment. Our framework builds on the distinction of operand and operant resources and distinguishes between two key lifecycle stages of hardware ventures: start-up and growth. We show how this framework can be used to discuss the role, nature, and use of IS for hardware ventures and outline empirical research strategies that flow from it. Our work contributes to broadening and enriching the IS field by drawing attention to its role in significant and novel phenomena.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

Fiber Bragg grating accelerometer based on a transversely rotating stick

Fiber Bragg Grating (FBG) accelerometers using transverse forces with an inertial object placed at the middle of the FBG have a high sensitivity but low resonant frequency. The resonant frequency 26 Hz and sensitivity at 6 Hz 1.29 nm/g were reported based on a 50mm-long FBG accelerometer. We demonstrate that the first FBG accelerometer based on a transversely rotating stick, which can, at the same or even larger size, keep the high sensitivity and significantly increase the low resonant frequency. In our experiments, a 77.5mm-long FBG accelerometer has achieved a similar sensitivity but 65% higher resonant frequency. This novel structure not only significantly widens the potential applications of FBG accelerometers by increasing their resonant frequencies but also provides a new route to design other accelerometers, e.g. micro accelerometers.

Facing the wave of change: Stakeholder perspectives on climate adaptation for Australian seafood supply chains

Climate change is one of the most important issues confronting the sustainable supply of seafood, with projections suggesting major effects on wild and farmed fisheries worldwide. While climate change has been a consideration for Australian fisheries and aquaculture management, emphasis in both research and adaptation effort has been at the production end of supply chains—impacts further along the chain have been overlooked to date. A holistic biophysical and socio-economic system view of seafood industries, as represented by end-to-end supply chains, may lead to an additional set of options in the face of climate change, thus maximizing opportunities for improved fishery profitability, while also reducing the potential for maladaptation. In this paper, we explore Australian seafood industry stakeholder perspectives on potential options for adaptation along seafood supply chains based on future potential scenarios. Stakeholders, representing wild capture and aquaculture industries, provided a range of actions targeting different stages of the supply chain. Overall, proposed strategies were predominantly related to the production end of the supply chain, suggesting that greater attention in developing adaptation options is needed at post-production stages. However, there are chain-wide adaptation strategies that can present win–win scenarios, where commercial objectives beyond adaptation can also be addressed alongside direct or indirect impacts of climate. Likewise, certain adaptation strategies in place at one stage of the chain may have varying implications on other stages of the chain. These findings represent an important step in understanding the role of supply chains in effective adaptation of fisheries and aquaculture industries to climate change.