Spatial mapping and map exploitation : a bio-inspired engineering perspective

Probabilistic robot mapping techniques can produce high resolution, accurate maps of large indoor and outdoor environments. However, much less progress has been made towards robots using these maps to perform useful functions such as efficient navigation. This paper describes a pragmatic approach to mapping system development that considers not only the map but also the navigation functionality that the map must provide. We pursue this approach within a bio-inspired mapping context, and use esults from robot experiments in indoor and outdoor environments to demonstrate its validity. The research attempts to stimulate new research directions in the field of robot mapping with a proposal for a new approach that has the potential to lead to more complete mapping and navigation systems.

Multi-robot control in highly dynamic, competitive environments

The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navigation module, and (iv) a low level dynamic motion control system. The multi-robot coordination system assigns each robot a role and a sub-goal. Each robots action execution system then assumes the assigned role and attempts to achieve the specified sub-goal. The robots navigation system directs the robot to specific goal locations while ensuring that the robot avoids any obstacles. The motion system maps the heading and speed information from the navigation system to force-constrained motion. This multi-robot system has been extensively tested and applied in the robot soccer domain using both centralized and distributed coordination.

Large area noise evaluation

A software tool (DRONE) has been developed to evaluate road traffic noise in a large area with the consideration of network dynamic traffic flow and the buildings. For more precise estimation of noise in urban network where vehicles are mainly in stop and go running conditions, vehicle sound power level (for acceleration/deceleration cruising and ideal vehicle) is incorporated in DRONE. The calculation performance of DRONE is increased by evaluating the noise in two steps of first estimating the unit noise database and then integrating it with traffic simulation. Details of the process from traffic simulation to contour maps are discussed in the paper and the implementation of DRONE on Tsukuba city is presented

Development and implementation of the areawide Dynamic ROad traffic NoisE (DRONE) simulator

This paper discusses the areawide Dynamic ROad traffic NoisE (DRONE) simulator, and its implementation as a tool for noise abatement policy evaluation. DRONE involves integrating a road traffic noise estimation model with a traffic simulator to estimate road traffic noise in urban networks. An integrated traffic simulation-noise estimation model provides an interface for direct input of traffic flow properties from simulation model to noise estimation model that in turn estimates the noise on a spatial and temporal scale. The output from DRONE is linked with a geographical information system for visual representation of noise levels in the form of noise contour maps.

Integration of a road traffic noise model (ASJ) and traffic simulation (AVENUE) for a built-up area

A road traffic noise prediction model (ASJ MODEL-1998) has been integrated with a road traffic simulator (AVENUE) to produce the Dynamic areawide Road traffic NoisE simulator-DRONE. This traffic-noise-GIS based integrated tool is upgraded to predict noise levels in built-up areas. The integration of traffic simulation with a noise model provides dynamic access to traffic flow characteristics and hence automated and detailed predictions of traffic noise. The prediction is not only on the spatial scale but also on temporal scale. The linkage with GIS gives a visual representation to noise pollution in the form of dynamic areawide traffic noise contour maps. The application of DRONE on a real world built-up area is also presented.

BLAST Atlas : a function based multiple genome browser

BLAST Atlas is a visual analysis system for comparative genomics that supports genome-wide gene characterisation, functional assignment and function-based browsing of one or more chromosomes. Inspired by applications such as the WorldWide Telescope, Bing Maps 3D and Google Earth, BLAST Atlas uses novel three-dimensional gene and function views that provide a highly interactive and intuitive way for scientists to navigate, query and compare gene annotations. The system can be used for gene identification and functional assignment or as a function-based multiple genome comparison tool which complements existing position based comparison and alignment viewers.

Applying the open innovation system concept to infrastructure projects

Purpose: The goal of this conceptual paper is to provide tools to help maximise the value delivered by infrastructure projects, by developing methods to increase adoption of innovative products during construction. Methods: The role of knowledge flows in determining innovation adoption rates is conceptually examined. A promising new approach is developed. Open innovation system theory is extended, by reviewing the role of three frameworks: (1) knowledge intermediaries, (2) absorptive capacity and (3) governance arrangements. Originality: We develop a novel open innovation system model to guide further research in the area of adoption of innovation on infrastructure projects. The open innovation system model currently lacks definition of core concepts, especially with regard to the impact of different degrees and types of openness. The three frameworks address this issue and add substance to the open innovation system model, addressing widespread criticism that it is underdeveloped. The novelty of our model is in the combination of the three frameworks to explore the system. These frameworks promise new insights into system dynamics and facilitate the development of new methods to optimise the diffusion of innovation. Practical Implications: The framework will help to reveal gaps in knowledge flows that impede the uptake of innovations. In the past, identifying these gaps has been difficult given the lack of nuance in existing theory. The knowledge maps proposed will enable informed policy advice to effectively harness the power of knowledge networks, increase innovation diffusion and improve the performance of infrastructure projects. The models developed in this paper will be used in planned empirical research into innovation on large scale infrastructure projects in the Australian built environment.

A comparative study of interactive rockclimbing guidebooks and conventional hardcopy guidebooks

Climbing guidebooks have been in existence ever since people started climbing cliffs for recreation. It has only been recently that these guidebooks have started to include photographs to help identification of climbs. To date, there are very few interactive guidebooks that are available online which include the ability to filter climbs and climbing areas based upon specific characteristics. Being able to interrogate a database of climbs and climbing areas by grade, style of climbing, quality of climbing,and length of climbs would be a significant addition to the guidebooks that are currently available. Integrating a fully illustrated database of climbs with open source mapping software such as Google Maps would extend the utility of current guidebooks significantly. As portable devices become more commonplace, the ability to further combine these guidebooks with GPS technology would make the location and identification of climbs much simpler. This study compares conventional hardcopy guidebooks with several online guidebooks. In addition, several Decision Support Systems are analysed to assess the ways in which Geographic Information Systems are integrated to assist in decision making. A prototype interactive guidebook was developed after presenting a survey to a group of climbers to assess what they would find useful in an online resource. This survey found that most climbers would like to see climbs represented on a map of the climbing site in order to aid in locating them. They also suggested that being able to filter climbs by various criteria would be useful. These features were subsequently integrated into the prototype. After review by several climbers it was found that this system has many benefits over conventional hardcopy guidebooks; however, it was also noted that to be even more useful further work needed to be done to improve the functionality of the prototypes. This work would include an ability to print a selection of climbs from those ranges searched.

Mapping the Australian networked public sphere

This article reports on a research program that has developed new methodologies for mapping the Australian blogosphere and tracking how information is disseminated across it. The authors improve on conventional web crawling methodologies in a number of significant ways: First, the authors track blogging activity as it occurs, by scraping new blog posts when such posts are announced through Really Simple Syndication (RSS) feeds. Second, the authors use custom-made tools that distinguish between the different types of content and thus allow us to analyze only the salient discursive content provided by bloggers. Finally, the authors are able to examine these better quality data using both link network mapping and textual analysis tools, to produce both cumulative longer term maps of interlinkages and themes, and specific shorter term snapshots of current activity that indicate current clusters of heavy interlinkage and highlight their key themes. In this article, the authors discuss findings from a yearlong observation of the Australian political blogosphere, suggesting that Australian political bloggers consistently address current affairs, but interpret them differently from mainstream news outlets. The article also discusses the next stage of the project, which extends this approach to an examination of other social networks used by Australians, including Twitter, YouTube, and Flickr. This adaptation of our methodology moves away from narrow models of political communication, and toward an investigation of everyday and popular communication, providing a more inclusive and detailed picture of the Australian networked public sphere.

An intelligent data mining technique for product quality improvement

Advances in data mining have provided techniques for automatically discovering underlying knowledge and extracting useful information from large volumes of data. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large complex databases. Application of data mining to manufacturing is relatively limited mainly because of complexity of manufacturing data. Growing self organizing map (GSOM) algorithm has been proven to be an efficient algorithm to analyze unsupervised DNA data. However, it produced unsatisfactory clustering when used on some large manufacturing data. In this paper a data mining methodology has been proposed using a GSOM tool which was developed using a modified GSOM algorithm. The proposed method is used to generate clusters for good and faulty products from a manufacturing dataset. The clustering quality (CQ) measure proposed in the paper is used to evaluate the performance of the cluster maps. The paper also proposed an automatic identification of variables to find the most probable causative factor(s) that discriminate between good and faulty product by quickly examining the historical manufacturing data. The proposed method offers the manufacturers to smoothen the production flow and improve the quality of the products. Simulation results on small and large manufacturing data show the effectiveness of the proposed method.

Spatial analysis of notified dengue fever infections

This study aimed to investigate the spatial clustering and dynamic dispersion of dengue incidence in Queensland, Australia. We used Moran’s I statistic to assess the spatial autocorrelation of reported dengue cases. Spatial empirical Bayes smoothing estimates were used to display the spatial distribution of dengue in postal areas throughout Queensland. Local indicators of spatial association (LISA) maps and logistic regression models were used to identify spatial clusters and examine the spatio-temporal patterns of the spread of dengue. The results indicate that the spatial distribution of dengue was clustered during each of the three periods of 1993–1996, 1997–2000 and 2001–2004. The high-incidence clusters of dengue were primarily concentrated in the north of Queensland and low-incidence clusters occurred in the south-east of Queensland. The study concludes that the geographical range of notified dengue cases has significantly expanded in Queensland over recent years.

Vision only pose estimation and scene reconstruction on airborne platforms

We aim to demonstrate unaided visual 3D pose estimation and map reconstruction using both monocular and stereo vision techniques. To date, our work has focused on collecting data from Unmanned Aerial Vehicles, which generates a number of significant issues specific to the application. Such issues include scene reconstruction degeneracy from planar data, poor structure initialisation for monocular schemes and difficult 3D reconstruction due to high feature covariance. Most modern Visual Odometry (VO) and related SLAM systems make use of a number of sensors to inform pose and map generation, including laser range-finders, radar, inertial units and vision [1]. By fusing sensor inputs, the advantages and deficiencies of each sensor type can be handled in an efficient manner. However, many of these sensors are costly and each adds to the complexity of such robotic systems. With continual advances in the abilities, small size, passivity and low cost of visual sensors along with the dense, information rich data that they provide our research focuses on the use of unaided vision to generate pose estimates and maps from robotic platforms. We propose that highly accurate (�5cm) dense 3D reconstructions of large scale environments can be obtained in addition to the localisation of the platform described in other work [2]. Using images taken from cameras, our algorithm simultaneously generates an initial visual odometry estimate and scene reconstruction from visible features, then passes this estimate to a bundle-adjustment routine to optimise the solution. From this optimised scene structure and the original images, we aim to create a detailed, textured reconstruction of the scene. By applying such techniques to a unique airborne scenario, we hope to expose new robotic applications of SLAM techniques. The ability to obtain highly accurate 3D measurements of an environment at a low cost is critical in a number of agricultural and urban monitoring situations. We focus on cameras as such sensors are small, cheap and light-weight and can therefore be deployed in smaller aerial vehicles. This, coupled with the ability of small aerial vehicles to fly near to the ground in a controlled fashion, will assist in increasing the effective resolution of the reconstructed maps.

An analytical method to solve a general class of nonlinear reactive transport models

Three recent papers published in Chemical Engineering Journal studied the solution of a model of diffusion and nonlinear reaction using three different methods. Two of these studies obtained series solutions using specialized mathematical methods, known as the Adomian decomposition method and the homotopy analysis method. Subsequently it was shown that the solution of the same particular model could be written in terms of a transcendental function called Gauss’ hypergeometric function. These three previous approaches focused on one particular reactive transport model. This particular model ignored advective transport and considered one specific reaction term only. Here we generalize these previous approaches and develop an exact analytical solution for a general class of steady state reactive transport models that incorporate (i) combined advective and diffusive transport, and (ii) any sufficiently differentiable reaction term R(C). The new solution is a convergent Maclaurin series. The Maclaurin series solution can be derived without any specialized mathematical methods nor does it necessarily involve the computation of any transcendental function. Applying the Maclaurin series solution to certain case studies shows that the previously published solutions are particular cases of the more general solution outlined here. We also demonstrate the accuracy of the Maclaurin series solution by comparing with numerical solutions for particular cases.

HapMap tag-SNP analysis confirms a role for COMT in schizophrenia risk and reveals a novel association

Catechol-O-methyl transferase (COMT) encodes an enzyme involved in the metabolism of dopamine and maps to a commonly deleted region that increases schizophrenia risk. A non-synonymous polymorphism (rs4680) in COMT has been previously found to be associated with schizophrenia and results in altered activity levels of COMT. Using a haplotype block-based gene-tagging approach we conducted an association study of seven COMT single nucleotide polymorphisms (SNPs) in 160 patients with a DSM-IV diagnosis of schizophrenia and 250 controls in an Australian population. Two polymorphisms including rs4680 and rs165774 were found to be significantly associated with schizophrenia. The rs4680 results in a Val/Met substitution but the strongest association was shown by the novel SNP, rs165774, which may still be functional even though it is located in intron five. Individuals with schizophrenia were more than twice as likely to carry the GG genotype compared to the AA genotype for both the rs165774 and rs4680 SNPs. This association was slightly improved when males were analysed separately possibly indicating a degree of sexual dimorphism. Our results confirm that COMT is a good candidate for schizophrenia risk, by replicating the association with rs4680 and identifying a novel SNP association.

Technical report : acoustic analysis of the natural environment

This technical report is concerned with one aspect of environmental monitoring—the detection and analysis of acoustic events in sound recordings of the environment. Sound recordings offer ecologists the advantage of cheaper and increased sampling but make available so much data that automated analysis becomes essential. The report describes a number of tools for automated analysis of recordings, including noise removal from spectrograms, acoustic event detection, event pattern recognition, spectral peak tracking, syntactic pattern recognition applied to call syllables, and oscillation detection. These algorithms are applied to a number of animal call recognition tasks, chosen because they illustrate quite different modes of analysis: (1) the detection of diffuse events caused by wind and rain, which are frequent contaminants of recordings of the terrestrial environment; (2) the detection of bird and calls; and (3) the preparation of acoustic maps for whole ecosystem analysis. This last task utilises the temporal distribution of events over a daily, monthly or yearly cycle.