Low cost localisation for agricultural robotics

This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Towards bio-inspired place recognition over multiple spatial scales

This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.

Towards condition-invariant, top-down visual place recognition

In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.

The effect of nitroxides on swarming motility and biofilms, multicellular behaviors in Pseudomonas aeruginosa

The ability of NO to induce biofilm dispersion has been well established. Here we investigated the effect of nitroxides (sterically hindered nitric oxide analogues) on biofilm formation and swarming motility in Pseudomonas aeruginosa. A transposon mutant unable to produce nitric oxide endogenously (nirS) was deficient in swarming motility relative to wild type and the complemented strain. Moreover, expression of the nirS gene was up-regulated by 9.65-fold in wild type swarming cells when compared to planktonic cells. Wild type swarming levels were substantially restored upon exogenous addition of nitroxide containing compounds, consistent with the hypothesis that NO is necessary for swarming motility. Here, we showed that nitroxides not only mimicked the dispersal activity of NO, but also prevented biofilms from forming in flow cell chambers. In addition, a nirS transposon mutant was deficient in biofilm formation relative to wild type and the complemented strain, thus implicating NO in the formation of biofilms. Intriguingly despite its stand alone action in inhibiting biofilm formation and promoting dispersal, a nitroxide partially restored the ability of a nirS mutant to form biofilms.

Spin-coated carbon

We describe a novel and facile approach to covalently graft molecules containing stable free radicals onto carbon surfaces including graphene, carbon nanotubes, glassy carbon and carbon fibres. The new technique employs a stable aryl nitroxide radical diazonium tetrafluoroborate salt. The salt may be isolated and added to carbon surfaces in solution, suspension or electrochemically and represents a convenient, versatile and highly efficient means to adorn graphitic materials with large numbers of free radical spin systems

Validation of an instrument to measure governance and performance on collaborative infrastructure projects

Collaborative infrastructure projects use hybrid formal and informal governance structures to manage transactions. Based on previous desk-top research, the authors identified the key mechanisms underlying project governance, and posited the performance implications of the governance (Chen et al. 2012). The current paper extends that qualitative research by testing the veracity of those findings using data from 320 Australian construction organisations. The results provide, for the first time, reliable and valid scales to measure governance and performance of collaborative projects, and the relationship between them. The results confirm seven of seven hypothesised governance mechanisms; 30 of 43 hypothesised underlying actions; eight of eight hypothesised key performance indicators; and the dual importance of formal and informal governance. A startling finding of the study was that the implementation intensity of informal mechanisms (non-contractual conditions) is a greater predictor of project performance variance than that of formal mechanisms (contractual conditions). Further, contractual conditions do not directly impact project performance; instead their impact is mediated by the non-contractual features of a project. Obligations established under the contract are not sufficient to optimise project performance.

Social media, data analytics and videogames development : Halfbrick case study

Social media platforms are of interest to interactive entertainment companies for a number of reasons. They can operate as a platform for deploying games, as a tool for communicating with customers and potential customers, and can provide analytics on how players utilize the; game providing immediate feedback on design decisions and changes. However, as ongoing research with Australian developer Halfbrick, creators of $2 , demonstrates, the use of these platforms is not universally seen as a positive. The incorporation of Big Data into already innovative development practices has the potential to cause tension between designers, whilst the platform also challenges the traditional business model, relying on micro-transactions rather than an up-front payment and a substantial shift in design philosophy to take advantage of the social aspects of platforms such as Facebook.

Innovation & workplace culture in the Australian interactive entertainment industry : the Halfbrick story

A recent success story of the Australian videogames industry is Brisbane based Halfbrick Studios, developer of the hit game for mobile devices, Fruit Ninja. Halfbrick not only survived the global financial crisis and an associated downturn in the Australian industry, but grew strongly, moving rapidly from developing licensed properties for platforms such as Game Boy Advance, Nintendo DS, and Playstation Portable (PSP) to becoming an independent developer and publisher of in-house titles, generating revenue both through App downloads and merchandise sales. Amongst the reasons for Halfbrick’s success is their ability to adaptively transform by addressing different technical platforms, user dynamics, business models and market conditions. Our ongoing case-study research from 2010 into Halfbrick’s innovation processes, culminating with some 10 semi-structured interviews with senior managers and developers, has identified a strong focus on workplace organisational culture, with staff reflecting that the company is a flat, team-based organisation devolving as much control as possible to the development teams directly, and encouraging a work-life balance in which creativity can thrive. The success of this strategy is evidenced through Halfbrick’s low staff turnover; amongst our interviewees most of the developers had been with the company for a number of years, with all speaking positively of the workplace culture and sense of creative autonomy they enjoyed. Interviews with the CEO, Shainiel Deo, and team leaders highlighted the autonomy afforded to each team and the organisation and management of the projects on which they work. Deo and team leaders emphasised the collaboration and communication skills they require in the developers that they employ, and that these characteristics were considered just as significant in hiring decisions as technical skills. Halfbrick’s developers celebrate their workplace culture and insist it has contributed to their capacity for innovation and to their commercial success with titles such as Fruit Ninja. This model of organisational management is reflected in both Stark’s (2009) idea of heterarchy, and Neff’s (2012) concept of venture labour, and provides a different perspective on the industry than the traditional political economy critique of precarious labour exploited by gaming conglomerates. Nevertheless, throughout many of the interviews and in our informal discussions with Halfbrick developers there is also a sense that this rewarding culture is quite tenuous and precarious in the context of a rapidly changing and uncertain global videogames industry. Whether such a workplace culture represents the future of the games industry, or is merely a ‘Prague Spring’ before companies such as Halfbrick are swallowed by traditional players’ remains to be seen. However, as the process of rapid and uncertain transformation plays out across the videogames industry, it is important to pay attention to emerging modes of organisation and workplace culture, even whilst they remain at the margins of the industry. In this paper we investigate Halfbrick’s workplace culture and ask how sustainable is this kind of rewarding and creative workplace?

Improving short utterance i-vector speaker verification using utterance variance modelling and compensation techniques

This paper proposes techniques to improve the performance of i-vector based speaker verification systems when only short utterances are available. Short-length utterance i-vectors vary with speaker, session variations, and the phonetic content of the utterance. Well established methods such as linear discriminant analysis (LDA), source-normalized LDA (SN-LDA) and within-class covariance normalisation (WCCN) exist for compensating the session variation but we have identified the variability introduced by phonetic content due to utterance variation as an additional source of degradation when short-duration utterances are used. To compensate for utterance variations in short i-vector speaker verification systems using cosine similarity scoring (CSS), we have introduced a short utterance variance normalization (SUVN) technique and a short utterance variance (SUV) modelling approach at the i-vector feature level. A combination of SUVN with LDA and SN-LDA is proposed to compensate the session and utterance variations and is shown to provide improvement in performance over the traditional approach of using LDA and/or SN-LDA followed by WCCN. An alternative approach is also introduced using probabilistic linear discriminant analysis (PLDA) approach to directly model the SUV. The combination of SUVN, LDA and SN-LDA followed by SUV PLDA modelling provides an improvement over the baseline PLDA approach. We also show that for this combination of techniques, the utterance variation information needs to be artificially added to full-length i-vectors for PLDA modelling.

Effects of scaffold architecture on mechanical characteristics and osteoblast response to static and perfusion bioreactor cultures

Tissue engineering focuses on the repair and regeneration of tissues through the use of biodegradable scaffold systems that structurally support regions of injury whilst recruiting and/or stimulating cell populations to rebuild the target tissue. Within bone tissue engineering, the effects of scaffold architecture on cellular response have not been conclusively characterized in a controlled-density environment. We present a theoretical and practical assessment of the effects of polycaprolactone (PCL) scaffold architectural modifications on mechanical and flow characteristics as well as MC3T3-E1 preosteoblast cellular response in an in vitro static plate and custom-designed perfusion bioreactor model. Four scaffold architectures were contrasted, which varied in inter-layer lay-down angle and offset between layers, whilst maintaining a structural porosity of 60 ± 5%. We established that as layer angle was decreased (90° vs. 60°) and offset was introduced (0 vs. 0.5 between layers), structural stiffness, yield stress, strength, pore size and permeability decreased, whilst computational fluid dynamics-modeled wall shear stress was increased. Most significant effects were noted with layer offset. Seeding efficiencies in static culture were also dramatically increased due to offset (~45% to ~86%), with static culture exhibiting a much higher seeding efficiency than perfusion culture. Scaffold architecture had minimal effect on cell response in static culture. However, architecture influenced osteogenic differentiation in perfusion culture, likely by modifying the microfluidic environment.

Evaluation of two-view geometry methods with automatic ground-truth generation

A large number of methods have been published that aim to evaluate various components of multi-view geometry systems. Most of these have focused on the feature extraction, description and matching stages (the visual front end), since geometry computation can be evaluated through simulation. Many data sets are constrained to small scale scenes or planar scenes that are not challenging to new algorithms, or require special equipment. This paper presents a method for automatically generating geometry ground truth and challenging test cases from high spatio-temporal resolution video. The objective of the system is to enable data collection at any physical scale, in any location and in various parts of the electromagnetic spectrum. The data generation process consists of collecting high resolution video, computing accurate sparse 3D reconstruction, video frame culling and down sampling, and test case selection. The evaluation process consists of applying a test 2-view geometry method to every test case and comparing the results to the ground truth. This system facilitates the evaluation of the whole geometry computation process or any part thereof against data compatible with a realistic application. A collection of example data sets and evaluations is included to demonstrate the range of applications of the proposed system.

The impact of risk-reducing hysterectomy and bilateral salpingo-oophorectomy on survival in patients with a history of breast cancer – a population-based data linkage study

Prophylactic surgery including hysterectomy and bilateral salpingo-oophorectomy (BSO) is recommended in BRCA positive women, while in women from the general population, hysterectomy plus BSO may increase the risk of overall mortality. The effect of hysterectomy plus BSO on women previously diagnosed with breast cancer is unknown. We used data from a population-base data linkage study of all women diagnosed with primary breast cancer in Queensland, Australia between 1997 and 2008 (n=21,067). We fitted flexible parametric breast cancer specific and overall survival models with 95% confidence intervals (also known as Royston-Parmar models) to assess the impact of risk-reducing surgery (removal of uterus, one or both ovaries). We also stratified analyses by age 20-49 and 50-79 years, respectively. Overall, 1,426 women (7%) underwent risk-reducing surgery (13% of premenopausal women and 3% of postmenopausal women). No women who had risk-reducing surgery, compared to 171 who did not have risk-reducing surgery developed a gynaecological cancer. Overall, 3,165 (15%) women died, including 2,195 (10%) from breast cancer. Hysterectomy plus BSO was associated with significantly reduced risk of death overall (adjusted HR = 0.69, 95% CI 0.53-0.89; P =0.005). Risk reduction was greater among premenopausal women, whose risk of death halved (HR, 0.45; 95% CI, 0.25-0.79; P < 0.006). This was largely driven by reduction in breast cancer-specific mortality (HR, 0.43; 95% CI, 0.24-0.79; P < 0.006). This population-based study found that risk-reducing surgery halved the mortality risk for premenopausal breast cancer patients. Replication of our results in independent cohorts, and subsequently randomised trials are needed to confirm these findings.

A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters : theory and application to microfilaments

As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grained level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.

Demand response for residential appliances via Customer Reward Scheme

This paper proposes a reward based demand response algorithm for residential customers to shave network peaks. Customer survey information is used to calculate various criteria indices reflecting their priority and flexibility. Criteria indices and sensitivity based house ranking is used for appropriate load selection in the feeder for demand response. Customer Rewards (CR) are paid based on load shift and voltage improvement due to load adjustment. The proposed algorithm can be deployed in residential distribution networks using a two-level hierarchical control scheme. Realistic residential load model consisting of non-controllable and controllable appliances is considered in this study. The effectiveness of the proposed demand response scheme on the annual load growth of the feeder is also investigated. Simulation results show that reduced peak demand, improved network voltage performance, and customer satisfaction can be achieved.