Global reconfiguration of a team of networked mobile robots among obstacles

This paper presents a full system demonstration of dynamic sensorbased reconfiguration of a networked robot team. Robots sense obstacles in their environment locally and dynamically adapt their global geometric configuration to conform to an abstract goal shape. We present a novel two-layer planning and control algorithm for team reconfiguration that is decentralised and assumes local (neighbour-to-neighbour) communication only. The approach is designed to be resource-efficient and we show experiments using a team of nine mobile robots with modest computation, communication, and sensing. The robots use acoustic beacons for localisation and can sense obstacles in their local neighbourhood using IR sensors. Our results demonstrate globally-specified reconfiguration from local information in a real robot network, and highlight limitations of standard mesh networks in implementing decentralised algorithms.

Nanomorphology influence on the light conversion mechanisms in highly efficient diketopyrrolopyrrole based organic solar cells

In this work, diketopyrrolopyrrole-based polymer bulk heterojunction solar cells with inverted and regular architecture have been investigated. The influence of the polymer:fullerene ratio on the photoactive film nanomorphology has been studied in detail. Transmission Electron Microscopy and Atomic Force Microscopy reveal that the resulting film morphology strongly depends on the fullerene ratio. This fact determines the photocurrent generation and governs the transport of free charge carriers. Slight variations on the PCBM ratio respect to the polymer show great differences on the electrical behavior of the solar cell. Once the polymer:fullerene ratio is accurately adjusted, power conversion efficiencies of 4.7% and 4.9% are obtained for inverted and regular architectures respectively. Furthermore, by correlating the optical and morphological characterization of the polymer:fullerene films and the electrical behavior of solar cells, an ad hoc interpretation is proposed to explain the photovoltaic performance as a function of this polymer:blend composition.

High mobility organic thin film transistor and efficient photovoltaic devices using versatile donor-acceptor polymer semiconductor by molecular design

In this work, we report a novel donor-acceptor based solution processable low band gap polymer semiconductor, PDPP-TNT, synthesized via Suzuki coupling using condensed diketopyrrolopyrrole (DPP) as an acceptor moiety with a fused naphthalene donor building block in the polymer backbone. This polymer exhibits p-channel charge transport characteristics when used as the active semiconductor in organic thin-film transistor (OTFT) devices. The hole mobilities of 0.65 cm2 V-1 s-1 and 0.98 cm2 V -1 s-1 are achieved respectively in bottom gate and dual gate OTFT devices with on/off ratios in the range of 105 to 10 7. Additionally, due to its appropriate HOMO (5.29 eV) energy level and optimum optical band gap (1.50 eV), PDPP-TNT is a promising candidate for organic photovoltaic (OPV) applications. When this polymer semiconductor is used as a donor and PC71BM as an acceptor in OPV devices, high power conversion efficiencies (PCE) of 4.7% are obtained. Such high mobility values in OTFTs and high PCE in OPV make PDPP-TNT a very promising polymer semiconductor for a wide range of applications in organic electronics.

4-hexylbithieno[3,2-b:2′3′-e]pyridine: An efficient electron-accepting unit in fluorene and indenofluorene copolymers for light-emitting devices

4-Hexylbithienopyridine has been prepared as a novel electron-accepting monomer for conjugated polymers. To test its electronic properties, alternating copolymers with fluorene and indenofluorene polymers have been prepared. The copolymers displayed reduction potentials about 0.5 V lower than for the corresponding fluorene and indenofluorene homopolymers, indicating much improved electron-accepting properties. Analysis of the microscopic morphology of thin films of the copolymers by AFM shows that they lack the extensive supramolecular order seen with the homopolymers, which is attributed to the bithienopyridine units disrupting the π-stacking. LEDs using these polymers as the emitting layer produce blue-green emission with low turn-on voltages with aluminum electrodes confirming their improved electron affinity. The indenofluorene copolymer displayed an irreversible red shift in emission at high voltages, which is attributed to oxidation of the indenofluorene units. This red shift occurred at higher potentials than for indenofluorene homopolymers in LEDs, suggesting that the heterocyclic moieties offer some protection against electrically promoted oxidation.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

STAC living. Promoting efficient multi-residential buildings in subtropical climates.

STAC is a mobile application (app) designed to promote the benefits of climate-aware urban development in Subtropical environments. Although, STAC is primarily tool for understanding climate efficient buildings in Brisbane, Australia, it also demonstrates how other exemplary buildings operate in other subtropical cities of the world. The STAC research and development team applied research undertaken by the Centre for Subtropical Design (Brisbane) to profile buildings past and present that have contributed to the creation of a vibrant society, a viable economy, a healthy environment, and an authentic sense of place. In collaboration with researchers from the field of Interaction Design, this knowledge and data was collated, processed and curated for presentation via a custom mobile application designed to distribute this important research for review and consideration on-location in local settings and for comparison across all other global subtropical regions and projects identified by this research. This collaboration adopted a Design-based Research (DBR) Methodology guided by the main tenets of research and design iteration and cross-discipline collaboration in real-world settings, resulting in the formulation of contextually-sensitive design principles, theories, and tools for design intervention. Combined with significant context review of available technology and data and subsequent case study analysis of exemplar design applications.

Submission: Towards a Stronger and More Efficient IP Rights System : Getting the Balance Right

1. In March 2009, the Australian Government, through IP Australia its administrator of Intellectual Property Rights (IPR) acquired by registration or grant, issued two consultation papers for comment by interested stakeholders. 2. The Consultation Papers have invited written submissions directed towards the object of the paper, namely encouraging discussion on certain proposed changes and their impact on business and innovation. 3. I understand the invitation to make written submissions is predominantly in the areas raised by the Consultation Papers and the questions posed. However, I have made a brief reference to several other areas of concern with the current Australian patent law, which in my opinion inhibit innovation and therefore come under the wider agenda of the government to work toward a stronger and more efficient IP rights system. 4. In this regard, the Consultation Papers indicate that if the IPR are less likely to be invalidated and more likely to be enforced, this confidence will reflect in a greater investment in research leading to innovation. 5. This submission relates to the Balance Paper.

Mission path planning of aerial survey tasks using hybrid game evolutionary algorithm

The work presented in this report is aimed to implement a cost-effective offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. Understandably, the objectives of a practical optimisation problem are conflicting each other and the minimisation of one of them necessarily implies the impossibility to minimise the other ones. This leads to the need to find a set of optimal solutions for the problem; once such a set of available options is produced, the mission planning problem is reduced to a decision making problem for the mission specialists, who will choose the solution which best fit the requirements of the mission. The goal of this work is then to develop a Multi-Objective optimisation tool able to provide the mission specialists a set of optimal solutions for the inspection task amongst which the final trajectory will be chosen, given the environment data, the mission requirements and the definition of the objectives to minimise. All the possible optimal solutions of a Multi-Objective optimisation problem are said to form the Pareto-optimal front of the problem. For any of the Pareto-optimal solutions, it is impossible to improve one objective without worsening at least another one. Amongst a set of Pareto-optimal solutions, no solution is absolutely better than another and the final choice must be a trade-off of the objectives of the problem. Multi-Objective Evolutionary Algorithms (MOEAs) are recognised to be a convenient method for exploring the Pareto-optimal front of Multi-Objective optimization problems. Their efficiency is due to their parallelism architecture which allows to find several optimal solutions at each time

Ultrathin hematite films deposited layer-by-layer on TiO2 underlayer for efficient water splitting under visible light

Ultrathin hematite (α-Fe2O3) film deposited on a TiO2 underlayer as a photoanode for photoelectrochemical water splitting was described. The TiO2 underlayer was coated on conductive fluorine-doped tin oxide (FTO) glass by spin coating. The hematite films were formed layer-by-layer by repeating the separated two-phase hydrolysis-solvothermal reaction of iron(III) acetylacetonate and aqueous ammonia. A photocurrent density of 0.683 mA cm−2 at +1.5 V vs. RHE (reversible hydrogen electrode) was obtained under visible light (>420 nm, 100 mW cm−2) illumination. The TiO2 underlayer plays an important role in the formation of hematite film, acting as an intermediary to alleviate the dead layer effect and as a support of large surface areas to coat greater amounts of Fe2O3. The as-prepared photoanodes are notably stable and highly efficient for photoelectrochemical water splitting under visible light. This study provides a facile synthesis process for the controlled production of highly active ultrathin hematite film and a simple route for photocurrent enhancement using several photoanodes in tandem.

Making optimal and justifiable asset maintenance decisions

Maintenance decisions for large-scale asset systems are often beyond an asset manager's capacity to handle. The presence of a number of possibly conflicting decision criteria, the large number of possible maintenance policies, and the reality of budget constraints often produce complex problems, where the underlying trade-offs are not apparent to the asset manager. This paper presents the decision support tool "JOB" (Justification and Optimisation of Budgets), which has been designed to help asset managers of large systems assess, select, interpret and optimise the effects of their maintenance policies in the presence of limited budgets. This decision support capability is realized through an efficient, scalable backtracking- based algorithm for the optimisation of maintenance policies, while enabling the user to view a number of solutions near this optimum and explore tradeoffs with other decision criteria. To assist the asset manager in selecting between various policies, JOB also provides the capability of Multiple Criteria Decision Making. In this paper, the JOB tool is presented and its applicability for the maintenance of a complex power plant system.

Approximate Bayesian Computation for astronomical model analysis : a case study in galaxy demographics and morphological transformation at high redshift

Approximate Bayesian Computation’ (ABC) represents a powerful methodology for the analysis of complex stochastic systems for which the likelihood of the observed data under an arbitrary set of input parameters may be entirely intractable – the latter condition rendering useless the standard machinery of tractable likelihood-based, Bayesian statistical inference [e.g. conventional Markov chain Monte Carlo (MCMC) simulation]. In this paper, we demonstrate the potential of ABC for astronomical model analysis by application to a case study in the morphological transformation of high-redshift galaxies. To this end, we develop, first, a stochastic model for the competing processes of merging and secular evolution in the early Universe, and secondly, through an ABC-based comparison against the observed demographics of massive (Mgal > 1011 M⊙) galaxies (at 1.5 < z < 3) in the Cosmic Assembly Near-IR Deep Extragalatic Legacy Survey (CANDELS)/Extended Groth Strip (EGS) data set we derive posterior probability densities for the key parameters of this model. The ‘Sequential Monte Carlo’ implementation of ABC exhibited herein, featuring both a self-generating target sequence and self-refining MCMC kernel, is amongst the most efficient of contemporary approaches to this important statistical algorithm. We highlight as well through our chosen case study the value of careful summary statistic selection, and demonstrate two modern strategies for assessment and optimization in this regard. Ultimately, our ABC analysis of the high-redshift morphological mix returns tight constraints on the evolving merger rate in the early Universe and favours major merging (with disc survival or rapid reformation) over secular evolution as the mechanism most responsible for building up the first generation of bulges in early-type discs.

Rapid and highly efficient growth of graphene on copper by chemical vapor deposition of ethanol

The growth of graphene by chemical vapor deposition on metal foils is a promising technique to deliver large-area films with high electron mobility. Nowadays, the chemical vapor deposition of hydrocarbons on copper is the most investigated synthesis method, although many other carbon precursors and metal substrates are used too. Among these, ethanol is a safe and inexpensive precursor that seems to offer favorable synthesis kinetics. We explored the growth of graphene on copper from ethanol, focusing on processes of short duration (up to one min). We investigated the produced films by electron microscopy, Raman and X-ray photoemission spectroscopy. A graphene film with high crystalline quality was found to cover the entire copper catalyst substrate in just 20 s, making ethanol appear as a more efficient carbon feedstock than methane and other commonly used precursors.