Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two non-parametric transforms, namely, the rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

Quantitative evaluation of matching methods and validity measures for stereo vision

The authors present a qualitative and quantitative comparison of various similarity measures that form the kernel of common area-based stereo-matching systems. The authors compare classical difference and correlation measures as well as nonparametric measures based on the rank and census transforms for a number of outdoor images. For robotic applications, important considerations include robustness to image defects such as intensity variation and noise, the number of false matches, and computational complexity. In the absence of ground truth data, the authors compare the matching techniques based on the percentage of matches that pass the left-right consistency test. The authors also evaluate the discriminatory power of several match validity measures that are reported in the literature for eliminating false matches and for estimating match confidence. For guidance applications, it is essential to have and estimate of confidence in the three-dimensional points generated by stereo vision. Finally, a new validity measure, the rank constraint, is introduced that is capable of resolving ambiguous matches for rank transform-based matching.

The role of randomly mixed-layered chlorite/smectite in the transformation of smectite to chlorite

Vesicular and groundmass phyllosilicates in a hydrothermally altered basalt from the Point Sal ophiolite, California, have been studied using transmission electron microscopy (TEM). Pore-filling phyllosilicates are texturally characterized as having coherent, relatively thick and defect-free crystals of chlorite (14 Å) with occasional 24-Å periodicities. Groundmass phyllosilicates are texturally characterized as 1) randomly oriented crystals up to 200 Å in width and 2) larger, more coherent crystals up to 1000 Å in width. Small crystallites contain predominantly 14-Å layers with some 24-Å units. Large crystals show randomly interlayered chlorite/smectite (C/S), with approximately 50% chlorite on average. Adjacent smectite-like layers are not uncommon in the groundmass phyllosilicates. Electron microprobe analyses show that Fe/Mg ratios of both groundmass and vesicular phyllosilicates are fairly constant. Termination of brucite-like interlayers has been identified in some of the TEM images. The transformation mechanisms represented by these layer terminations are 1) growth of a brucite-like interlayer within smectite interlayer regions and 2) the dissolution and reprecipitation of elements to form chlorite layers. Both mechanisms require an increase in volume as smectite transforms to chlorite. The data, combined with that from previously published reports, suggest that randomly interlayered C/S is a metastable phase formed in microenvironments with low water/rock ratios. Chlorite forms in microenvironments in the same sample dominated by higher water/rock ratios. The relatively constant number of Mg's in the structure (Mg#) of both structures indicates that in both microenvironments the bulk rock composition has influence over the composition of phyllosilicates.

Fine-grained Y2Cu2O5 powder from a co-precipitated precursor

A co-precipitation process is utilized to manufacture Y2Cu2O5 precursor powders. Upon calcination at high temperatures, such as 800 degrees C, the co-precipitated powder transforms to Y2Cu2O5. By selective variation of calcination parameters, grain-growth can be controlled to yield different sized Y2Cu2O5 powder, including sub-micron average sizes. ICP analysis, X-ray diffraction, electron microscopy, a.c. magnetic susceptibility and FT Raman are used to characterize phase development, morphology and purity of the powders.

Visualising security incidents through event aggregation

Extracting and aggregating the relevant event records relating to an identified security incident from the multitude of heterogeneous logs in an enterprise network is a difficult challenge. Presenting the information in a meaningful way is an additional challenge. This paper looks at solutions to this problem by first identifying three main transforms; log collection, correlation, and visual transformation. Having identified that the CEE project will address the first transform, this paper focuses on the second, while the third is left for future work. To aggregate by correlating event records we demonstrate the use of two correlation methods, simple and composite. These make use of a defined mapping schema and confidence values to dynamically query the normalised dataset and to constrain result events to within a time window. Doing so improves the quality of results, required for the iterative re-querying process being undertaken. Final results of the process are output as nodes and edges suitable for presentation as a network graph.

Breast cancer detection from thermal images using bispectral invariant features

Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.

Unmasking workshop ecology in applied performance

This practice-led research enquiry identifies, develops and illustrates workshop ecology in Applied Performance. It explores how Applied Performance forms are applied in and transformed through action in two distinct community-learning settings. The research is undertaken in two performance sites. The first, involving an executive leadership program addressing complex project management for Australia's Defence Materiel Organisation in Canberra, Australia. The second, a sexual health, HIV and AIDS education program to raise awareness and encourage the prevention of transmission of sexual diseases within Karkar Island, Papua New Guinea. The research strategies draw upon a mixed method approach involving practice-led research participant observation. The findings from each performance site show how the workshop ecology shapes and transforms performance forms as they are applied and influences the degree to which they are effective. It is anticipated that the findings from this research will assist Applied Performance practitioners to more carefully consider workshop ecology in the design and delivery of Applied Performances.

Robust image hash functions using higher order spectra

Robust hashing is an emerging field that can be used to hash certain data types in applications unsuitable for traditional cryptographic hashing methods. Traditional hashing functions have been used extensively for data/message integrity, data/message authentication, efficient file identification and password verification. These applications are possible because the hashing process is compressive, allowing for efficient comparisons in the hash domain but non-invertible meaning hashes can be used without revealing the original data. These techniques were developed with deterministic (non-changing) inputs such as files and passwords. For such data types a 1-bit or one character change can be significant, as a result the hashing process is sensitive to any change in the input. Unfortunately, there are certain applications where input data are not perfectly deterministic and minor changes cannot be avoided. Digital images and biometric features are two types of data where such changes exist but do not alter the meaning or appearance of the input. For such data types cryptographic hash functions cannot be usefully applied. In light of this, robust hashing has been developed as an alternative to cryptographic hashing and is designed to be robust to minor changes in the input. Although similar in name, robust hashing is fundamentally different from cryptographic hashing. Current robust hashing techniques are not based on cryptographic methods, but instead on pattern recognition techniques. Modern robust hashing algorithms consist of feature extraction followed by a randomization stage that introduces non-invertibility and compression, followed by quantization and binary encoding to produce a binary hash output. In order to preserve robustness of the extracted features, most randomization methods are linear and this is detrimental to the security aspects required of hash functions. Furthermore, the quantization and encoding stages used to binarize real-valued features requires the learning of appropriate quantization thresholds. How these thresholds are learnt has an important effect on hashing accuracy and the mere presence of such thresholds are a source of information leakage that can reduce hashing security. This dissertation outlines a systematic investigation of the quantization and encoding stages of robust hash functions. While existing literature has focused on the importance of quantization scheme, this research is the first to emphasise the importance of the quantizer training on both hashing accuracy and hashing security. The quantizer training process is presented in a statistical framework which allows a theoretical analysis of the effects of quantizer training on hashing performance. This is experimentally verified using a number of baseline robust image hashing algorithms over a large database of real world images. This dissertation also proposes a new randomization method for robust image hashing based on Higher Order Spectra (HOS) and Radon projections. The method is non-linear and this is an essential requirement for non-invertibility. The method is also designed to produce features more suited for quantization and encoding. The system can operate without the need for quantizer training, is more easily encoded and displays improved hashing performance when compared to existing robust image hashing algorithms. The dissertation also shows how the HOS method can be adapted to work with biometric features obtained from 2D and 3D face images.

Iron nodules in ferric soils of the Fraser Coast, Australia : relicts of laterisation or features of contemporary weathering and pedogenesis?

The genesis of ferruginous nodules and pisoliths in soils and weathering profiles of coastal southern and eastern Australia has long been debated. It is not clear whether iron (Fe) nodules are redox accumulations, residues of Miocene laterite duricrust, or the products of contemporary weathering of Fe-rich sedimentary rocks. This study combines a catchment-wide survey of Fe nodule distribution in Poona Creek catchment (Fraser Coast, Queensland) with detailed investigations of a representative ferric soil profile to show that Fe nodules are derived from Fe-rich sandstones. Where these crop out, they are broken down, transported downslope by colluvial processes, and redeposited. Chemical and physical weathering transforms these eroded rock fragments into non-magnetic Fe nodules. Major features of this transformation include lower hematite/goethite and kaolinite/gibbsite ratios, increased porosity, etching of quartz grains, and development of rounded morphology and a smooth outer cortex. Iron nodules are commonly concentrated in ferric horizons. We show that these horizons form as the result of differential biological mixing of the soil. Bioturbation gradually buries nodules and rock fragments deposited at the surface of the soil, resulting in a largely nodule-free 'biomantle' over a ferric 'stone line'. Maghemite-rich magnetic nodules are a prominent feature of the upper half of the profile. These are most likely formed by the thermal alteration of non-magnetic nodules located at the top of the profile during severe bushfires. They are subsequently redistributed through the soil profile by bioturbation. Iron nodules occurring in the study area are products of contemporary weathering of Fe-rich rock units. They are not laterite duricrust residues nor are they redox accumulations, although redox-controlled dissolution/re-precipitation is an important component of post-depositional modification of these Fe nodules.

A simplified approach for calculating the moments of action for linear reaction-diffusion equations

The mean action time is the mean of a probability density function that can be interpreted as a critical time, which is a finite estimate of the time taken for the transient solution of a reaction-diffusion equation to effectively reach steady state. For high-variance distributions, the mean action time under-approximates the critical time since it neglects to account for the spread about the mean. We can improve our estimate of the critical time by calculating the higher moments of the probability density function, called the moments of action, which provide additional information regarding the spread about the mean. Existing methods for calculating the nth moment of action require the solution of n nonhomogeneous boundary value problems which can be difficult and tedious to solve exactly. Here we present a simplified approach using Laplace transforms which allows us to calculate the nth moment of action without solving this family of boundary value problems and also without solving for the transient solution of the underlying reaction-diffusion problem. We demonstrate the generality of our method by calculating exact expressions for the moments of action for three problems from the biophysics literature. While the first problem we consider can be solved using existing methods, the second problem, which is readily solved using our approach, is intractable using previous techniques. The third problem illustrates how the Laplace transform approach can be used to study coupled linear reaction-diffusion equations.

Platelet-derived endothelial cell growth factor expression and angiogenesis in cervical intraepithelial neoplasia and squamous cell carcinoma of the cervix

Growth and metastatic spread of invasive carcinoma depends on angiogenesis, the formation of new blood vessels. Platelet-derived endothelial cell growth factor (PD-ECGF) is an angiogenic growth factor for a number of solid tumors, including lung, bladder, colorectal, and renal cell cancer. Cervical intraepithelial neoplasia (CIN) is the precursor to squamous cell cervical carcinoma (SCC). Mean vessel density (MVD) increases from normal cervical tissue, through low- and high-grade CIN to SCC. We evaluated PD-ECGF immunoreactivity and correlated its expression with MVD in normal, premalignant, and malignant cervical tissue. PD-ECGF expression was assessed visually within the epithelial tissues and scored on the extent and intensity of staining. MVD was calculated by counting the number of vessels positive for von Willebrand factor per unit area subtending normal or CIN epithelium or within tumor hotspots for SCC. Cytoplasmic and/or nuclear PD-ECGF immunoreactivity was seen in normal epithelium. PD-ECGF expression significantly increased with histologic grade from normal, through low- and high-grade CIN, to SCC (P < .02). A progressive significant increase in the microvessel density was also seen, ranging from a mean of 28 vessels for normal tissue to 57 for SCC (P < .0005). No correlation was found between PD-ECGF expression and MVD (P = .45). We conclude that PD-ECGF expression and MVD increase as the cervix transforms from a normal to a malignant phenotype. PD-ECGF is thymidine phosphorylase, a key enzyme in the activation of fluoropyrimidines, including 5-fluorouracil. Evaluation of PD-ECGF thymidine phosphorylase expression may be important in designing future chemotherapeutic trials in cervical cancer. Copyright (C) 2000 by W.B. Saunders Company.

The velocity synchronous discrete Fourier transform for order tracking in the field of rotating machinery

Diagnostics of rotating machinery has developed significantly in the last decades, and industrial applications are spreading in different sectors. Most applications are characterized by varying velocities of the shaft and in many cases transients are the most critical to monitor. In these variable speed conditions, fault symptoms are clearer in the angular/order domains than in the common time/frequency ones. In the past, this issue was often solved by synchronously sampling data by means of phase locked circuits governing the acquisition; however, thanks to the spread of cheap and powerful microprocessors, this procedure is nowadays rarer; sampling is usually performed at constant time intervals, and the conversion to the order domain is made by means of digital signal processing techniques. In the last decades different algorithms have been proposed for the extraction of an order spectrum from a signal sampled asynchronously with respect to the shaft rotational velocity; many of them (the so called computed order tracking family) use interpolation techniques to resample the signal at constant angular increments, followed by a common discrete Fourier transform to shift from the angular domain to the order domain. A less exploited family of techniques shifts directly from the time domain to the order spectrum, by means of modified Fourier transforms. This paper proposes a new transform, named velocity synchronous discrete Fourier transform, which takes advantage of the instantaneous velocity to improve the quality of its result, reaching performances that can challenge the computed order tracking.

A security system based on human iris identification using wavelet transform

A security system based on the recognition of the iris of human eyes using the wavelet transform is presented. The zero-crossings of the wavelet transform are used to extract the unique features obtained from the grey-level profiles of the iris. The recognition process is performed in two stages. The first stage consists of building a one-dimensional representation of the grey-level profiles of the iris, followed by obtaining the wavelet transform zerocrossings of the resulting representation. The second stage is the matching procedure for iris recognition. The proposed approach uses only a few selected intermediate resolution levels for matching, thus making it computationally efficient as well as less sensitive to noise and quantisation errors. A normalisation process is implemented to compensate for size variations due to the possible changes in the camera-to-face distance. The technique has been tested on real images in both noise-free and noisy conditions. The technique is being investigated for real-time implementation, as a stand-alone system, for access control to high-security areas.

QUT Architecture Film Studio (Aus)

Research Statement: An urban film produced by Luke Harrison Mitchell Benham, Sharlene Anderson, Tristan Clark. RIVE NOIR explores the film noir tradition, shot on location in a dark urban space between high-rises and the river, sheltered by a highway. With an original score and striking cinematography, Rive Noir radically transforms the abandoned river’s edge through the production of an amplified reality ordinarily unseen in the Northbank. The work produced under my supervision was selected to appear in the Expanded Architecture Research Group’s International Architecture Film Festival and Panel Discussion in Sydney: The University of Sydney and Carriageworks Performance Space, 06 November 2011. QUT School of Design research submission was selected alongside exhibits by AA School of Architecture, London; The Bartlett School of Architecture, London; University of The Arts, London; Arrhaus School of Architecture, Denmark; Dublin as a Cinematic City, Ireland; Design Lab Screen Studio, Australia; and Sona Cinecity, The University of Melbourne. The exhibit included not only the screening of the film but the design project that derived from and extended the aesthetics of the urban film. The urban proposal and architectural intervention that followed the film was subsequently published in the Brisbane Times, after the urban proposal won first place in The Future of Brisbane architecture competition, which demonstrates the impact of the research project as a whole. EXPANDED ARCHITECTURE 2011 - 6th November Architecture Film Night + Panel Discussion @ Performance Space CarriageWorks was Sydney's first International Architectural Film Festival. With over 40 architectural films by local and international artists, film makers and architects. It was followed by Panel Discussion of esteemed academics and artists working in the field of architectural film.

Inflammation in lung carcinogenesis

It was Dvorak in 1986 that postulated 'tumours are wounds that do not heal' as they share common cellular and molecular mechanisms, which are active in both wounds and in cancer tissue. Inflammation is a crucial part of the innate immune system that protects against pathogens and initiates adaptive immunity. Acute inflammation is usually a rapid and self-limiting process, however it does not always resolve. This leads to the establishment of a chronic inflammatory state and provides the perfect environment for carcinogenesis. Inflammation and cancer have long had an association, going back as far as Virchow in 1863, when leucocytes were noted in neoplastic tissue. It has been estimated that approximately 25% of all malignancies are initiated or exacerbated by inflammation caused by infectious agents. Furthermore, inflammation is linked to all of the six hallmarks of cancer (evasion of apoptosis, insensitivity to anti-growth signals, unlimited replicative potential, angiogenesis, increase in survival factors and invasion and metastasis). It is thought that inflammation may play a critical role in lung carcinogenesis given that individuals with inflammatory lung conditions have an increased risk of lung cancer development. Cigarette smoking can also induce inflammation in the lung and smokers are at a higher risk of developing lung cancer than non-smokers. However, exposure to a number of environmental agents such as radon, have also been demonstrated as a causative factor in this disease. This chapter will focus on inflammation as a contributory factor in non small cell lung cancer (NSCLC), concentrating primarily on the pathological involvement of the pro-inflammatory cytokines, TNF-α, IL-1β, and the CXC (ELR+) chemokine family. Targeting of inflammatory mediators will also be discussed as a therapeutic strategy in this disease. © 2013 by Nova Science Publishers, Inc. All rights reserved.