Machine recognition of hand-drawn circuit diagrams

An application of image processing techniques to recognition of hand-drawn circuit diagrams is presented. The scanned image of a diagram is pre-processed to remove noise and converted to bilevel. Morphological operations are applied to obtain a clean, connected representation using thinned lines. The diagram comprises of nodes, connections and components. Nodes and components are segmented using appropriate thresholds on a spatially varying object pixel density. Connection paths are traced using a pixel-stack. Nodes are classified using syntactic analysis. Components are classified using a combination of invariant moments, scalar pixel-distribution features, and vector relationships between straight lines in polygonal representations. A node recognition accuracy of 82% and a component recognition accuracy of 86% was achieved on a database comprising 107 nodes and 449 components. This recogniser can be used for layout “beautification” or to generate input code for circuit analysis and simulation packages

Postcode segmentation and recognition using projections and bispectral features

A system to segment and recognize Australian 4-digit postcodes from address labels on parcels is described. Images of address labels are preprocessed and adaptively thresholded to reduce noise. Projections are used to segment the line and then the characters comprising the postcode. Individual digits are recognized using bispectral features extracted from their parallel beam projections. These features are insensitive to translation, scaling and rotation, and robust to noise. Results on scanned images are presented. The system is currently being improved and implemented to work on-line.

Aerial image analysis using spiking neural networks with application to power line corridor monitoring

Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

Gait energy volumes and frontal gait recognition using depth images

Gait energy images (GEIs) and its variants form the basis of many recent appearance-based gait recognition systems. The GEI combines good recognition performance with a simple implementation, though it suffers problems inherent to appearance-based approaches, such as being highly view dependent. In this paper, we extend the concept of the GEI to 3D, to create what we call the gait energy volume, or GEV. A basic GEV implementation is tested on the CMU MoBo database, showing improvements over both the GEI baseline and a fused multi-view GEI approach. We also demonstrate the efficacy of this approach on partial volume reconstructions created from frontal depth images, which can be more practically acquired, for example, in biometric portals implemented with stereo cameras, or other depth acquisition systems. Experiments on frontal depth images are evaluated on an in-house developed database captured using the Microsoft Kinect, and demonstrate the validity of the proposed approach.

Pattern recognition using invariants defined from higher order spectra - one-dimensional inputs

A new approach to pattern recognition using invariant parameters based on higher order spectra is presented. In particular, invariant parameters derived from the bispectrum are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale and amplification invariant, as well. A minimal set of these invariants is selected as the feature vector for pattern classification, and a minimum distance classifier using a statistical distance measure is used to classify test patterns. The classification technique is shown to distinguish two similar, but different bolts given their one-dimensional profiles. Pattern recognition using higher order spectral invariants is fast, suited for parallel implementation, and has high immunity to additive Gaussian noise. Simulation results show very high classification accuracy, even for low signal-to-noise ratios.

On the behaviour of higher-order spectral features for object recognition in the presence of various types of noise

This paper presents results on the robustness of higher-order spectral features to Gaussian, Rayleigh, and uniform distributed noise. Based on cluster plots and accuracy results for various signal to noise conditions, the higher-order spectral features are shown to be better than moment invariant features.

Is the iPhone an accurate and useful tool for the monitoring of spinal deformity?

The progression of spinal deformity is traditionally monitored by spinal surgeons using the Cobb method on hardcopy radiographs with a protractor and pencil. The rotation of the spine and ribcage (rib hump) in scoliosis is measured with a simple hand-held inclinometer (Scoliometer). The iPhone and other smart phones have the capability to accurately sense inclination, and can therefore be used to measure Cobb angles and rib hump angulation. The purpose of this study was to quantify the performance of the iPhone compared to a standard protractor for measuring Cobb angles and the Scoliometer for measuring rib humps. The study concluded that the iPhone is a clinically equivalent measuring tool to the traditional protractor and Scoliometer

A multi-resolution image alignment technique based on direct methods for pose estimation of aerial vehicles

In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi- Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles’ state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle’s state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle’s state for more than one minute, at real-time frame rates based, only on visual information.

Hydrogen-bonding in the structures of the hydrated proton-transfer compounds of isonipecotamide with the isomeric indole-2 and indole-3-carboxylic acids

The structures of two hydrated proton-transfer compounds of 4-piperidinecarboxamide (isonipecotamide) with the isomeric heteroaromatic carboxylic acids indole-2-carboxylic acid and indole-3-carboxylic acid, namely 4-carbamoylpiperidinium indole-2-carboxylate dihydrate (1) and 4-carbamoylpiperidinium indole-3-carboxylate hemihydrate (2) have been determined at 200 K. Crystals of both 1 and 2 are monoclinic, space groups P21/c and P2/c respectively with Z = 4 in cells having dimensions a = 10.6811(4), b = 12.2017(4), c = 12.5456(5) Å, β = 96.000(4)o (1) and a = 15.5140(4), b = 10.2908(3), c = 9.7047(3) Å, β = 97.060(3)o (2). Hydrogen-bonding in 1 involves a primary cyclic interaction involving complementary cation amide N-H…O(carboxyl) anion and anion hetero N-H…O(amide) cation hydrogen bonds [graph set R22(9)]. Secondary associations involving also the water molecules of solvation give a two-dimensional network structure which includes weak water O-H…π interactions. In the three-dimensional hydrogen-bonded structure of 2, there are classic centrosymmetric cyclic head-to-head hydrogen-bonded amide-amide interactions [graph set R22(8)] as well as lateral cyclic amide-O linked amide-amide extensions [graph set R24(8)]. The anions and the water molecule, which lies on a twofold rotation axis, are involved in secondary extensions.

Iron biogeochemistry and associated greenhouse gas evolution in a forested subtropical Australian coastal catchment : Poona Creek, Southeast Queensland

Iron (Fe) is the fourth most abundant element in the Earth’s crust. Excess Fe mobilization from terrestrial into aquatic systems is of concern for deterioration of water quality via biofouling and nuisance algal blooms in coastal and marine systems. Substantial Fe dissolution and transport involve alternate Fe(II) oxidation followed by Fe(III) reduction, with a diversity of Bacteria and Archaea acting as the key catalyst. Microbially-mediated Fe cycling is of global significance with regard to cycles of carbon (C), sulfur (S) and manganese (Mn). However, knowledge regarding microbial Fe cycling in circumneutral-pH habitats that prevail on Earth has been lacking until recently. In particular, little is known regarding microbial function in Fe cycling and associated Fe mobilization and greenhouse (CO2 and CH4, GHG) evolution in subtropical Australian coastal systems where microbial response to ambient variations such as seasonal flooding and land use changes is of concern. Using the plantation-forested Poona Creek catchment on the Fraser Coast of Southeast Queensland (SEQ), this research aimed to 1) study Fe cycling-associated bacterial populations in diverse terrestrial and aquatic habitats of a representative subtropical coastal circumneutral-pH (4–7) ecosystem; and 2) assess potential impacts of Pinus plantation forestry practices on microbially-mediated Fe mobilization, organic C mineralization and associated GHG evolution in coastal SEQ. A combination of wet-chemical extraction, undisturbed core microcosm, laboratory bacterial cultivation, microscopy and 16S rRNA-based molecular phylogenetic techniques were employed. The study area consisted primarily of loamy sands, with low organic C and dissolved nutrients. Total reactive Fe was abundant and evenly distributed within soil 0–30 cm profiles. Organic complexation primarily controlled Fe bioavailability and forms in well-drained plantation soils and water-logged, native riparian soils, whereas tidal flushing exerted a strong “seawater effect” in estuarine locations and formed a large proportion of inorganic Fe(III) complexes. There was a lack of Fe(II) sources across the catchment terrestrial system. Mature, first-rotation plantation clear-felling and second-rotation replanting significantly decreased organic matter and poorly crystalline Fe in well-drained soils, although variations in labile soil organic C fractions (dissolved organic C, DOC; and microbial biomass C, MBC) were minor. Both well-drained plantation soils and water-logged, native-vegetation soils were inhabited by a variety of cultivable, chemotrophic bacterial populations capable of C, Fe, S and Mn metabolism via lithotrophic or heterotrophic, (micro)aerobic or anaerobic pathways. Neutrophilic Fe(III)-reducing bacteria (FeRB) were most abundant, followed by aerobic, heterotrophic bacteria (heterotrophic plate count, HPC). Despite an abundance of FeRB, cultivable Fe(II)-oxidizing bacteria (FeOB) were absent in associated soils. A lack of links between cultivable Fe, S or Mn bacterial densities and relevant chemical measurements (except for HPC correlated with DOC) was likely due to complex biogeochemical interactions. Neither did variations in cultivable bacterial densities correlate with plantation forestry practices, despite total cultivable bacterial densities being significantly lower in estuarine soils when compared with well-drained plantation soils and water-logged, riparian native-vegetation soils. Given that bacterial Fe(III) reduction is the primary mechanism of Fe oxide dissolution in soils upon saturation, associated Fe mobilization involved several abiotic and biological processes. Abiotic oxidation of dissolved Fe(II) by Mn appeared to control Fe transport and inhibit Fe dissolution from mature, first-rotation plantation soils post-saturation. Such an effect was not observed in clear-felled and replanted soils associated with low SOM and potentially low Mn reactivity. Associated GHG evolution post-saturation mainly involved variable CO2 emissions, with low, but consistently increasing CH4 effluxes in mature, first-rotation plantation soil only. In comparison, water-logged soils in the riparian native-vegetation buffer zone functioned as an important GHG source, with high potentials for Fe mobilization and GHG, particularly CH4 emissions in riparian loam soils associated with high clay and crystalline Fe fractions. Active Fe–C cycling was unlikely to occur in lower-catchment estuarine soils associated with low cultivable bacterial densities and GHG effluxes. As a key component of bacterial Fe cycling, neutrophilic FeOB widely occurred in diverse aquatic, but not terrestrial, habitats of the catchment study area. Stalked and sheathed FeOB resembling Gallionella and Leptothrix were limited to microbial mat material deposited in surface fresh waters associated with a circumneutral-pH seep, and clay-rich soil within riparian buffer zones. Unicellular, Sideroxydans-related FeOB (96% sequence identity) were ubiquitous in surface and subsurface freshwater environments, with highest abundance in estuary-adjacent shallow coastal groundwater water associated with redox transition. The abundance of dissolved C and Fe in the groundwater-dependent system was associated with high numbers of cultivable anaerobic, heterotrophic FeRB, microaerophilic, putatively lithotrophic FeOB and aerobic, heterotrophic bacteria. This research represents the first study of microbial Fe cycling in diverse circumneutral-pH environments (terrestrial–aquatic, freshwater–estuarine, surface–subsurface) of a subtropical coastal ecosystem. It also represents the first study of its kind in the southern hemisphere. This work highlights the significance of bacterial Fe(III) reduction in terrestrial, and bacterial Fe(II) oxidation in aquatic catchment Fe cycling. Results indicate the risk of promotion of Fe mobilization due to plantation clear-felling and replanting, and GHG emissions associated with seasonal water-logging. Additional significant outcomes were also achieved. The first direct evidence for multiple biomineralization patterns of neutrophilic, microaerophilic, unicellular FeOB was presented. A putatively pure culture, which represents the first cultivable neutrophilic FeOB from the southern hemisphere, was obtained as representative FeOB ubiquitous in diverse catchment aquatic habitats.

Effects of surgical joint destabilization on load sharing between ligamentous structures in the thoracic spine : a finite element investigation

Background: In vitro investigations have demonstrated the importance of the ribcage in stabilising the thoracic spine. Surgical alterations of the ribcage may change load-sharing patterns in the thoracic spine. Computer models are used in this study to explore the effect of surgical disruption of the rib-vertebrae connections on ligament load-sharing in the thoracic spine. Methods: A finite element model of a T7-8 motion segment, including the T8 rib, was developed using CT-derived spinal anatomy for the Visible Woman. Both the intact motion segment and the motion segment with four successive stages of destabilization (discectomy and removal of right costovertebral joint, right costotransverse joint and left costovertebral joint) were analysed for a 2000Nmm moment in flexion/extension, lateral bending and axial rotation. Joint rotational moments were compared with existing in vitro data and a detailed investigation of the load sharing between the posterior ligaments carried out. Findings: The simulated motion segment demonstrated acceptable agreement with in vitro data at all stages of destabilization. Under lateral bending and axial rotation, the costovertebral joints were of critical importance in resisting applied moments. In comparison to the intact joint, anterior destabilization increases the total moment contributed by the posterior ligaments. Interpretation: Surgical removal of the costovertebral joints may lead to excessive rotational motion in a spinal joint, increasing the risk of overload and damage to the remaining ligaments. The findings of this study are particularly relevant for surgical procedures involving rib head resection, such as some techniques for scoliosis deformity correction.

A study of environmental and management drivers of non-CO2 greenhouse gas emissions in Australian agro-ecosystems

Australian climate, soils and agricultural management practices are significantly different from those of the northern hemisphere nations. Consequently, experimental data on greenhouse gas production from European and North American agricultural soils and its interpretation are unlikely to be directly applicable to Australian systems. A programme of studies of non-CO2 greenhouse gas emissions from agriculture has been established that is designed to reduce uncertainty of non-CO2 greenhouse gas emissions in the Australian National Greenhouse Gas Inventory and provide outputs that will enable better on-farm management practices for reducing non-CO2 greenhouse gas emissions, particularly nitrous oxide. The systems being examined and their locations are irrigated pasture (Kyabram Victoria), irrigated cotton (Narrabri, NSW), irrigated maize (Griffith, NSW), rain-fed wheat (Rutherglen, Victoria) and rain-fed wheat (Cunderdin, WA). The field studies include treatments with and without fertilizer addition, stubble burning versus stubble retention, conventional cultivation versus direct drilling and crop rotation to determine emission factors and treatment possibilities for best management options. The data to date suggest that nitrous oxide emissions from nitrogen fertilizer, applied to irrigated dairy pastures and rain-fed winter wheat, appear much lower than the average of northern hemisphere grain and pasture studies. More variable emissions have been found in studies of irrigated cotton/vetch/wheat rotation and substantially higher emissions from irrigated maize.

On the application of the probabilistic linear discriminant analysis to face recognition across expression

Facial expression is one of the main issues of face recognition in uncontrolled environments. In this paper, we apply the probabilistic linear discriminant analysis (PLDA) method to recognize faces across expressions. Several PLDA approaches are tested and cross-evaluated on the Cohn-Kanade and JAFFE databases. With less samples per gallery subject, high recognition rates comparable to previous works have been achieved indicating the robustness of the approaches. Among the approaches, the mixture of PLDAs has demonstrated better performances. The experimental results also indicate that facial regions around the cheeks, eyes, and eyebrows are more discriminative than regions around the mouth, jaw, chin, and nose.

The economics of happiness : a lifetime perspective

The three studies in this thesis focus on happiness and age and seek to contribute to our understanding of happiness change over the lifetime. The first study contributes by offering an explanation for what was evolving to a ‘stylised fact’ in the economics literature, the U-shape of happiness in age. No U-shape is evident if one makes a visual inspection of the age happiness relationship in the German socio-economic panel data, and, it seems counter-intuitive that we just have to wait until we get old to be happy. Eliminating the very young, the very old, and the first timers from the analysis did not explain away regression results supporting the U-shape of happiness in age, but fixed effect analysis did. Analysis revealed found that reverse causality arising from time-invariant individual traits explained the U-shape of happiness in age in the German population, and the results were robust across six econometric methods. Robustness was added to the German fixed effect finding by replicating it with the Australian and the British socio-economic panel data sets. During analysis of the German data an unexpected finding emerged, an exceedingly large negative linear effect of age on happiness in fixed-effect regressions. There is a large self-reported happiness decline by those who remain in the German panel. A similar decline over time was not evident in the Australian or the British data. After testing away age, time and cohort effects, a time-in-panel effect was found. Germans who remain in the panel for longer progressively report lower levels of happiness. Because time-in-panel effects have not been included in happiness regression specifications, our estimates may be biased; perhaps some economics of the happiness studies, that used German panel data, need revisiting. The second study builds upon the fixed-effect finding of the first study and extends our view of lifetime happiness to a cohort little visited by economists, children. Initial analysis extends our view of lifetime happiness beyond adulthood and revealed a happiness decline in adolescent (15 to 23 year-old) Australians that is twice the size of the happiness decline we see in older Australians (75 to 86 yearolds), who we expect to be unhappy due to declining income, failing health and the onset of death. To resolve a difference of opinion in the literature as to whether childhood happiness decreases, increases, or remains flat in age; survey instruments and an Internet-based survey were developed and used to collect data from four hundred 9 to 14 year-old Australian children. Applying the data to a Model of Childhood Happiness revealed that the natural environment life-satisfaction domain factor did not have a significant effect on childhood happiness. However, the children’s school environment and interactions with friends life-satisfaction domain factors explained over half a steep decline in childhood happiness that is three times larger than what we see in older Australians. Adding personality to the model revealed what we expect to see with adults, extraverted children are happier, but unexpectedly, so are conscientious children. With the steep decline in the happiness of young Australians revealed and explanations offered, the third study builds on the time-invariant individual trait finding from the first study by applying the Australian panel data to an Aggregate Model of Average Happiness over the lifetime. The model’s independent variable is the stress that arises from the interaction between personality and the life event shocks that affect individuals and peers throughout their lives. Interestingly, a graphic depiction of the stress in age relationship reveals an inverse U-shape; an inverse U-shape that looks like the opposite of the U-shape of happiness in age we saw in the first study. The stress arising from life event shocks is found to explain much of the change in average happiness over a lifetime. With the policy recommendations of economists potentially invoking unexpected changes in our lives, the ensuing stress and resulting (un)happiness warrant consideration before economists make policy recommendations.

Design of fixed order robust power oscillation damper for TCSC

This paper illustrates robust fixed order power oscillation damper design for mitigating power systems oscillations. From implementation and tuning point of view, such low and fixed structure is common practice for most practical applications, including power systems. However, conventional techniques of optimal and robust control theory cannot handle the constraint of fixed-order as it is, in general, impossible to ensure a target closed-loop transfer function by a controller of any given order. This paper deals with the problem of synthesizing or designing a feedback controller of dynamic order for a linear time-invariant plant for a fixed plant, as well as for an uncertain family of plants containing parameter uncertainty, so that stability, robust stability and robust performance are attained. The desired closed-loop specifications considered here are given in terms of a target performance vector representing a desired closed-loop design. The performance of the designed controller is validated through non-linear simulations for a range of contingencies.