Road network extraction with new vectorization and pruning from high-resolution RS images

With the increasing resolution of remote sensing images, road network can be displayed as continuous and homogeneity regions with a certain width rather than traditional thin lines. Therefore, road network extraction from large scale images refers to reliable road surface detection instead of road line extraction. In this paper, a novel automatic road network detection approach based on the combination of homogram segmentation and mathematical morphology is proposed, which includes three main steps: (i) the image is classified based on homogram segmentation to roughly identify the road network regions; (ii) the morphological opening and closing is employed to fill tiny holes and filter out small road branches; and (iii) the extracted road surface is further thinned by a thinning approach, pruned by a proposed method and finally simplified with Douglas-Peucker algorithm. Lastly, the results from some QuickBird images and aerial photos demonstrate the correctness and efficiency of the proposed process.

Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement

Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

Psychological predictors of young adults' use of social networking sites

Young people are increasingly using social networking sites (SNSs), like Myspace and Facebook, to engage with others. The use of SNSs can have both positive and negative effects on the individual; however, few research studies identify the types of people who frequent these Internet sites. This study sought to predict young adults’ use of SNSs and addictive tendency towards the use of SNSs from their personality characteristics and levels of self-esteem. University students (N = 201), aged 17 to 24 years, reported their use of SNSs and addictive tendencies for SNSs use, and completed the NEO Five-Factor Personality Inventory 1 and the Coopersmith Self-Esteem Inventory.2 Multiple regression analyses revealed that, as a group, the personality and self-esteem factors significantly predicted both level of SNS use and addictive tendency but did not explain a large amount of variance in either outcome measure. The findings indicated that extraverted and unconscientious individuals reported higher levels of both SNS use and addictive tendencies. Future research should attempt to identify which other psychosocial characteristics explain young people’s level of use and propensity for addictive tendencies for these popular Internet sites.

Rephrasing voice : art, practice-led research and the limits and sites of articulacy

While my PhD is practice-led research, it is my contention that such an inquiry cannot develop as long as it tries to emulate other models of research. I assert that practice-led research needs to account for an epistemological unknown or uncertainty central to the practice of art. By focusing on what I call the artist's 'voice,' I will show how this 'voice' is comprised of a dual motivation—'articulate' representation and 'inarticulate' affect—which do not even necessarily derive from the artist. Through an analysis of art-historical precedents, critical literature (the work of Jean-François Lyotard and Andrew Benjamin, the critical methods of philosophy, phenomenology and psychoanalysis) as well as of my own painting and digital arts practice, I aim to demonstrate how this unknown or uncertain aspect of artistic inquiry can be mapped. It is my contention that practice-led research needs to address and account for this dualistic 'voice' in order to more comprehensively articulate its unique contribution to research culture.

Dating and intimacy in the 21st century : the use of online dating sites in Australia

This article examines the growing phenomenon of online dating and intimacy in the 21st century. The exponential rise of communications technologies, which is both reflective and constitutive of an increasingly networked and globalized society, has the potential to significantly influence the nature of intimacy in everyday life. Yet, to date, there has been a minimal response by sociologists to seek, describe and understand this influence. In this article, we present some of the key findings of our research on online dating in Australia, in order to foster a debate about the sociological impacts on intimacy in the postmodern world. Based on a web audit of more than 60 online dating sites and in-depth interviews with 23 users of online dating services, we argue that recent global trends are influencing the uptake of online technologies for the purposes of forming intimate relations. Further, some of the mediating effects of these technologies – in particular, the hypercommunication – may have specific implications for the nature of intimacy in the global era.

How Australia’s Indigenous people are positioned within health service sites by our presence and by our absence

De Certeau (1984) constructs the notion of belonging as a sentiment which develops over time through the everyday activities. He explains that simple everyday activities are part of the process of appropriation and territorialisation and suggests that over time belonging and attachment are established and built on memory, knowledge and the experiences of everyday activities. Based on the work of de Certeau, non-Indigenous Australians have developed attachment and belonging to places based on the dispossession of Aboriginal people and on their everyday practices over the past two hundred years. During this time non-Indigenous people have marked their appropriation and territorialisation with signs, symbols, representations and images. In marking their attachment, they also define how they position Australia’s Indigenous people by both our presence and our absence. This paper will explore signs and symbols within spaces and places in health services and showcase how they reflect the historical, political, cultural, social and economic values, and power relations of broader society. It will draw on the voices of Aboriginal women to demonstrate their everyday experiences of such sites. It will conclude by highlighting how Aboriginal people assert their identities and un-ceded sovereignty within such health sites and actively resist on-going white epistemological notions of us and the logic of patriarchal white sovereignty.

Off-world robotic excavation for Large-scale habitat construction and resource extraction

This paper describes technologies we have developed to perform autonomous large-scale off-world excavation. A scale dragline excavator of size similar to that required for lunar excavation was made capable of autonomous control. Systems have been put in place to allow remote operation of the machine from anywhere in the world. Algorithms have been developed for complete autonomous digging and dumping of material taking into account machine and terrain constraints and regolith variability. Experimental results are presented showing the ability to autonomously excavate and move large amounts of regolith and accurately place it at a specified location.

Predicting adolescents’ use of social networking sites from an extended theory of planned behaviour perspective

The popularity of social networking sites (SNSs) among adolescents has grown exponentially, with little accompanying research to understand the influences on adolescent engagement with this technology. The current study tested the validity of an extended theory of planned behaviour model (TPB), incorporating the additions of group norm and self-esteem influences, to predict frequent SNS use. Adolescents (N = 160) completed measures assessing the standard TPB constructs of attitude, subjective norm, perceived behavioural control (PBC), and intention, as well as group norm and self-esteem. One week later, participants reported their SNS use during the previous week. Support was found for the standard TPB variables of attitude and PBC, as well as group norm, in predicting intentions to use SNS frequently, with intention, in turn, predicting behaviour. These findings provide an understanding of the factors influencing frequent engagement in what is emerging as a primary tool for adolescent socialisation.

Fingerprint analysis using wavelet transform with application to compression and feature extraction

The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.

GYAN: A methodology for rule extraction from artificial neural networks

Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.

The determination of three selected sites for the construction and operation of a low level radioactive waste storage and burial facility

Radioactive wastes are by-products of the use of radiation technologies. As with many technologies, the wastes are required to be disposed of in a safe manner so as to minimise risk to human health. This study examines the requirements for a hypothetical repository and develops techniques for decision making to permit the establishment of a shallow ground burial facility to receive an inventory of low-level radioactive wastes. Australia’s overall inventory is used as an example. Essential and desirable siting criteria are developed and applied to Australia's Northern Territory resulting in the selection of three candidate sites for laboratory investigations into soil behaviour. The essential quantifiable factors which govern radionuclide migration and ultimately influence radiation doses following facility closure are reviewed. Simplified batch and column procedures were developed to enable laboratory determination of distribution and retardation coefficient values for use in one-dimensional advection-dispersion transport equations. Batch and column experiments were conducted with Australian soils sampled from the three identified candidate sites using a radionuclide representative of the current national low-level radioactive waste inventory. The experimental results are discussed and site soil performance compared. The experimental results are subsequently used to compare the relative radiation health risks between each of the three sites investigated. A recommendation is made as to the preferred site to construct an engineered near-surface burial facility to receive the Australian low-level radioactive waste inventory.