Microwave remote sensing of snowpacks

The interaction mechanisms responsible for the microwave backscattering and emission behavior of snow were investigated, and models were developed relating the backscattering coefficient (sigma) and apparent temperature (T) to the physical parameters of the snowpack. The microwave responses to snow wetness, snow water equivalent, snow surface roughness, and to diurnal variations were investigated. Snow wetness was shown to have an increasing effect with increasing frequency and angle of incidence for both active and passive cases. Increasing snow wetness was observed to decrease the magnitude sigma and increase T. Snow water equivalent was also observed to exhibit a significant influence sigma and T. Snow surface configuration (roughness) was observed to be significant only for wet snow surface conditions. Diurnal variations were as large as 15 dB for sigma at 35 GHz and 120 K for T at 37 GHz. Simple models for sigma and T of a snowpack scene were developed in terms of the most significant ground-truth parameters. The coefficients for these models were then evaluated; the fits to the sigma and T measurements were generally good. Finally, areas of needed additional observations were outlined and experiments were specified to further the understanding of the microwave-snowpack interaction mechanisms

Phenomenological modeling of image irradiance for non-Lambertian surfaces under natural illumination.

Various vision tasks are usually confronted by appearance variations due to changes of illumination. For instance, in a recognition system, it has been shown that the variability in human face appearance is owed to changes to lighting conditions rather than person\u27s identity. Theoretically, due to the arbitrariness of the lighting function, the space of all possible images of a fixed-pose object under all possible illumination conditions is infinite dimensional. Nonetheless, it has been proven that the set of images of a convex Lambertian surface under distant illumination lies near a low dimensional linear subspace. This result was also extended to include non-Lambertian objects with non-convex geometry. As such, vision applications, concerned with the recovery of illumination, reflectance or surface geometry from images, would benefit from a low-dimensional generative model which captures appearance variations w.r.t. illumination conditions and surface reflectance properties. This enables the formulation of such inverse problems as parameter estimation. Typically, subspace construction boils to performing a dimensionality reduction scheme, e.g. Principal Component Analysis (PCA), on a large set of (real/synthesized) images of object(s) of interest with fixed pose but different illumination conditions. However, this approach has two major problems. First, the acquired/rendered image ensemble should be statistically significant vis-a-vis capturing the full behavior of the sources of variations that is of interest, in particular illumination and reflectance. Second, the curse of dimensionality hinders numerical methods such as Singular Value Decomposition (SVD) which becomes intractable especially with large number of large-sized realizations in the image ensemble. One way to bypass the need of large image ensemble is to construct appearance subspaces using phenomenological models which capture appearance variations through mathematical abstraction of the reflection process. In particular, the harmonic expansion of the image irradiance equation can be used to derive an analytic subspace to represent images under fixed pose but different illumination conditions where the image irradiance equation has been formulated in a convolution framework. Due to their low-frequency nature, irradiance signals can be represented using low-order basis functions, where Spherical Harmonics (SH) has been extensively adopted. Typically, an ideal solution to the image irradiance (appearance) modeling problem should be able to incorporate complex illumination, cast shadows as well as realistic surface reflectance properties, while moving away from the simplifying assumptions of Lambertian reflectance and single-source distant illumination. By handling arbitrary complex illumination and non-Lambertian reflectance, the appearance model proposed in this dissertation moves the state of the art closer to the ideal solution. This work primarily addresses the geometrical compliance of the hemispherical basis for representing surface reflectance while presenting a compact, yet accurate representation for arbitrary materials. To maintain the plausibility of the resulting appearance, the proposed basis is constructed in a manner that satisfies the Helmholtz reciprocity property while avoiding high computational complexity. It is believed that having the illumination and surface reflectance represented in the spherical and hemispherical domains respectively, while complying with the physical properties of the surface reflectance would provide better approximation accuracy of image irradiance when compared to the representation in the spherical domain. Discounting subsurface scattering and surface emittance, this work proposes a surface reflectance basis, based on hemispherical harmonics (HSH), defined on the Cartesian product of the incoming and outgoing local hemispheres (i.e. w.r.t. surface points). This basis obeys physical properties of surface reflectance involving reciprocity and energy conservation. The basis functions are validated using analytical reflectance models as well as scattered reflectance measurements which might violate the Helmholtz reciprocity property (this can be filtered out through the process of projecting them on the subspace spanned by the proposed basis, where the reciprocity property is preserved in the least-squares sense). The image formation process of isotropic surfaces under arbitrary distant illumination is also formulated in the frequency space where the orthogonality relation between illumination and reflectance bases is encoded in what is termed as irradiance harmonics. Such harmonics decouple the effect of illumination and reflectance from the underlying pose and geometry. Further, a bilinear approach to analytically construct irradiance subspace is proposed in order to tackle the inherent problem of small-sample-size and curse of dimensionality. The process of finding the analytic subspace is posed as establishing a relation between its principal components and that of the irradiance harmonics basis functions. It is also shown how to incorporate prior information about natural illumination and real-world surface reflectance characteristics in order to capture the full behavior of complex illumination and non-Lambertian reflectance. The use of the presented theoretical framework to develop practical algorithms for shape recovery is further presented where the hitherto assumed Lambertian assumption is relaxed. With a single image of unknown general illumination, the underlying geometrical structure can be recovered while accounting explicitly for object reflectance characteristics (e.g. human skin types for facial images and teeth reflectance for human jaw reconstruction) as well as complex illumination conditions. Experiments on synthetic and real images illustrate the robustness of the proposed appearance model vis-a-vis illumination variation. Keywords: computer vision, computer graphics, shading, illumination modeling, reflectance representation, image irradiance, frequency space representations, {hemi)spherical harmonics, analytic bilinear PCA, model-based bilinear PCA, 3D shape reconstruction, statistical shape from shading

Modular Logic Programming: Full Compositionality and Conflict Handling for Practical Reasoning

With the recent development of a new ubiquitous nature of data and the profusity of available knowledge, there is nowadays the need to reason from multiple sources of often incomplete and uncertain knowledge. Our goal was to provide a way to combine declarative knowledge bases – represented as logic programming modules under the answer set semantics – as well as the individual results one already inferred from them, without having to recalculate the results for their composition and without having to explicitly know the original logic programming encodings that produced such results. This posed us many challenges such as how to deal with fundamental problems of modular frameworks for logic programming, namely how to define a general compositional semantics that allows us to compose unrestricted modules. Building upon existing logic programming approaches, we devised a framework capable of composing generic logic programming modules while preserving the crucial property of compositionality, which informally means that the combination of models of individual modules are the models of the union of modules. We are also still able to reason in the presence of knowledge containing incoherencies, which is informally characterised by a logic program that does not have an answer set due to cyclic dependencies of an atom from its default negation. In this thesis we also discuss how the same approach can be extended to deal with probabilistic knowledge in a modular and compositional way. We depart from the Modular Logic Programming approach in Oikarinen & Janhunen (2008); Janhunen et al. (2009) which achieved a restricted form of compositionality of answer set programming modules. We aim at generalising this framework of modular logic programming and start by lifting restrictive conditions that were originally imposed, and use alternative ways of combining these (so called by us) Generalised Modular Logic Programs. We then deal with conflicts arising in generalised modular logic programming and provide modular justifications and debugging for the generalised modular logic programming setting, where justification models answer the question: Why is a given interpretation indeed an Answer Set? and Debugging models answer the question: Why is a given interpretation not an Answer Set? In summary, our research deals with the problematic of formally devising a generic modular logic programming framework, providing: operators for combining arbitrary modular logic programs together with a compositional semantics; We characterise conflicts that occur when composing access control policies, which are generalisable to our context of generalised modular logic programming, and ways of dealing with them syntactically: provided a unification for justification and debugging of logic programs; and semantically: provide a new semantics capable of dealing with incoherences. We also provide an extension of modular logic programming to a probabilistic setting. These goals are already covered with published work. A prototypical tool implementing the unification of justifications and debugging is available for download from http://cptkirk.sourceforge.net

A REST Model for High Throughput Scheduling in Computational Grids

Current grid computing architectures have been based on cluster management and batch queuing systems, extended to a distributed, federated domain. These have shown shortcomings in terms of scalability, stability, and modularity. To address these problems, this dissertation applies architectural styles from the Internet and Web to the domain of generic computational grids. Using the REST style, a flexible model for grid resource interaction is developed which removes the need for any centralised services or specific protocols, thereby allowing a range of implementations and layering of further functionality. The context for resource interaction is a generalisation and formalisation of the Condor ClassAd match-making mechanism. This set theoretic model is described in depth, including the advantages and features which it realises. This RESTful style is also motivated by operational experience with existing grid infrastructures, and the design, operation, and performance of a proto-RESTful grid middleware package named DIRAC. This package was designed to provide for the LHCb particle physics experiment's âﾜoff-lineâ computational infrastructure, and was first exercised during a 6 month data challenge which utilised over 670 years of CPU time and produced 98 TB of data through 300,000 tasks executed at computing centres around the world. The design of DIRAC and performance measures from the data challenge are reported. The main contribution of this work is the development of a REST model for grid resource interaction. In particular, it allows resource templating for scheduling queues which provide a novel distributed and scalable approach to resource scheduling on the grid

La Salle Magazine Fall 1999

https://digitalcommons.lasalle.edu/lasalle_magazine/1165/thumbnail.jp

The Other Radicalism: an Inquiry into Contemporary Australian Extreme Right Ideology, Politics and Organisation 1975-1995.

This Thesis examines the ideology, politics and organization of the Australian Extreme Right 1975-1995. Its central interpretative theme is the response of the Extreme Right to the development of the Australian State from a conservative Imperial structure into an American "anti-communist" client state, and ultimately into a liberal-internationalist machine which integrated Australia into a globalized capitalist order. The Extreme Right after 1975 differed from the various paramilitaries of the 1930's and the conservative anti-communist auxiliary organizations of the 1945-75 period. Post 1975, it lost its preoccupation with fighting the Left, and progressively grew as a challenger to liberal-internationalism. The abandonment of "White Australia" and consequent non-European immigration were the formative catalysts of a more diverse and complex Extreme Right. The Thesis uses a working definition of generic fascism as "palingenetic populist ultra-nationalism", to measure the degree of ideological and political radicalization achieved by the Extreme Right. This family of political ideas, independent of the State and mobilized beyond the limits of the former-period auxiliary conservatives, expressed itself in an array of organizational forms. The complexity of the Extreme Right can be demonstrated by using four typologies: Radical Nationalism, Neo-Nazism, Populist-Monarchism and Radical-Populism, each with specific points to make about social clienteles, geographical distribution, particular ideological heritages, and varied strategies and tactics. The Extreme Right could mobilize from different points of opportunity if political space became available. Inevitably a mutual delegitimization process between State and Extreme Right led to public inquiries and the emplacement of agencies and legislation to restrict the new radicalism. This was understandable since some Extreme Right groups employed violence or appeared to perform actions preparatory thereto. It also led to show-trials and para-State crime targeted against particular groups especially in the period 1988-91. Thereafter, Extreme Right organizations pursued strategies which led to electoral breakthroughs, both rural and urban as a style of Right-wing populist politics unfolded in the 1990's. It was in this period that the Extreme Right encouraged the co-optation by the State of the residual Left in the anti-racist fight. This seemed natural, as the Extreme Right's vocal references to popular democracy, national independence and the nativist heritage, had permitted it to occupy the Old Left's traditional ground. In that way too, it was "The Other Radicalism"