928 resultados para spacial ordering
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Wydział Fizyki: Zakład Optyki
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Two new notions of reduction for terms of the λ-calculus are introduced and the question of whether a λ-term is beta-strongly normalizing is reduced to the question of whether a λ-term is merely normalizing under one of the new notions of reduction. This leads to a new way to prove beta-strong normalization for typed λ-calculi. Instead of the usual semantic proof style based on Girard's "candidats de réductibilité'', termination can be proved using a decreasing metric over a well-founded ordering in a style more common in the field of term rewriting. This new proof method is applied to the simply-typed λ-calculus and the system of intersection types.
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Modal matching is a new method for establishing correspondences and computing canonical descriptions. The method is based on the idea of describing objects in terms of generalized symmetries, as defined by each object's eigenmodes. The resulting modal description is used for object recognition and categorization, where shape similarities are expressed as the amounts of modal deformation energy needed to align the two objects. In general, modes provide a global-to-local ordering of shape deformation and thus allow for selecting which types of deformations are used in object alignment and comparison. In contrast to previous techniques, which required correspondence to be computed with an initial or prototype shape, modal matching utilizes a new type of finite element formulation that allows for an object's eigenmodes to be computed directly from available image information. This improved formulation provides greater generality and accuracy, and is applicable to data of any dimensionality. Correspondence results with 2-D contour and point feature data are shown, and recognition experiments with 2-D images of hand tools and airplanes are described.
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Under high loads, a Web server may be servicing many hundreds of connections concurrently. In traditional Web servers, the question of the order in which concurrent connections are serviced has been left to the operating system. In this paper we ask whether servers might provide better service by using non-traditional service ordering. In particular, for the case when a Web server is serving static files, we examine the costs and benefits of a policy that gives preferential service to short connections. We start by assessing the scheduling behavior of a commonly used server (Apache running on Linux) with respect to connection size and show that it does not appear to provide preferential service to short connections. We then examine the potential performance improvements of a policy that does favor short connections (shortest-connection-first). We show that mean response time can be improved by factors of four or five under shortest-connection-first, as compared to an (Apache-like) size-independent policy. Finally we assess the costs of shortest-connection-first scheduling in terms of unfairness (i.e., the degree to which long connections suffer). We show that under shortest-connection-first scheduling, long connections pay very little penalty. This surprising result can be understood as a consequence of heavy-tailed Web server workloads, in which most connections are small, but most server load is due to the few large connections. We support this explanation using analysis.
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We introduce a view-point invariant representation of moving object trajectories that can be used in video database applications. It is assumed that trajectories lie on a surface that can be locally approximated with a plane. Raw trajectory data is first locally approximated with a cubic spline via least squares fitting. For each sampled point of the obtained curve, a projective invariant feature is computed using a small number of points in its neighborhood. The resulting sequence of invariant features computed along the entire trajectory forms the view invariant descriptor of the trajectory itself. Time parametrization has been exploited to compute cross ratios without ambiguity due to point ordering. Similarity between descriptors of different trajectories is measured with a distance that takes into account the statistical properties of the cross ratio, and its symmetry with respect to the point at infinity. In experiments, an overall correct classification rate of about 95% has been obtained on a dataset of 58 trajectories of players in soccer video, and an overall correct classification rate of about 80% has been obtained on matching partial segments of trajectories collected from two overlapping views of outdoor scenes with moving people and cars.
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A neural network model of 3-D visual perception and figure-ground separation by visual cortex is introduced. The theory provides a unified explanation of how a 2-D image may generate a 3-D percept; how figures pop-out from cluttered backgrounds; how spatially sparse disparity cues can generate continuous surface representations at different perceived depths; how representations of occluded regions can be completed and recognized without usually being seen; how occluded regions can sometimes be seen during percepts of transparency; how high spatial frequency parts of an image may appear closer than low spatial frequency parts; how sharp targets are detected better against a figure and blurred targets are detector better against a background; how low spatial frequency parts of an image may be fused while high spatial frequency parts are rivalrous; how sparse blue cones can generate vivid blue surface percepts; how 3-D neon color spreading, visual phantoms, and tissue contrast percepts are generated; how conjunctions of color-and-depth may rapidly pop-out during visual search. These explanations arise derived from an ecological analysis of how monocularly viewed parts of an image inherit the appropriate depth from contiguous binocularly viewed parts, as during DaVinci stereopsis. The model predicts the functional role and ordering of multiple interactions within and between the two parvocellular processing streams that join LGN to prestriate area V4. Interactions from cells representing larger scales and disparities to cells representing smaller scales and disparities are of particular importance.
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In this thesis we relate the formal description of various cold atomic systems in the energy eigenbasis, to the observable spatial mode dynamics. Herein the `spatial mode dynamics' refers to the direction of photon emission following the spontaneous emission of an excited fermion in the presence of a same species and spin ideal anisotropic Fermi sea in its internal ground state. Due to the Pauli principle, the presence of the ground state Fermi sea renders the phase space, anisotropic and only partially accessible, thereby a ecting the direction of photon emission following spontaneous emission. The spatial and energetic mode dynamics also refers to the quantum `tunneling' interaction between localised spatial modes, synonymous with double well type potentials. Here we relate the dynamics of the wavefunction in both the energetic and spatial representations. Using this approach we approximate the relationship between the spatial and energetic representations of a wavefunction spanning three spatial and energetic modes. This is extended to a process known as Spatial Adiabatic Passage, which is a technique to transport matter waves between localised spatial modes. This approach allows us to interpret the transport of matter waves as a signature of a geometric phase acquired by the one of the internal energy eigenstates of the system during the cyclical evolution. We further show that this geometric phase may be used to create spatial mode qubit and qutrit states.
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Cerium dioxide (ceria) nanoparticles have been the subject of intense academic and industrial interest. Ceria has a host of applications but academic interest largely stems from their use in the modern automotive catalyst but it is also of interest because of many other application areas notably as the abrasive in chemical-mechanical planarisation of silicon substrates. Recently, ceria has been the focus of research investigating health effects of nanoparticles. Importantly, the role of non-stoichiometry in ceria nanoparticles is implicated in their biochemistry. Ceria has well understood non-stoichiometry based around the ease of formation of anion vacancies and these can form ordered superstructures based around the fluorite lattice structure exhibited by ceria. The anion vacancies are associated with localised or small polaron states formed by the electrons that remain after oxygen desorption. In simple terms these electrons combine with Ce4+ states to form Ce3+ states whose larger ionic radii is associated with a lattice expansion compared to stoichiometric CeO2. This is a very simplistic explanation and greater defect chemistry complexity is suggested by more recent work. Various authors have shown that vacancies are mobile and may result in vacancy clustering. Ceria nanoparticles are of particular interest because of the high activity and surface area of small particulates. The sensitivity of the cerium electronic band structure to environment would suggest that changes in the properties of ceria particles at nanoscale dimensions might be expected. Notably many authors report a lattice expansion with reducing particle size (largely confined to sub-10 nm particles). Most authors assign increased lattice dimensions to the presence of a surface stable Ce2O3 type layer at low nanoparticle dimensions. However, our understanding of oxide nanoparticles is limited and their full and quantitative characterisation offers serious challenges. In a series of chemical preparations by ourselves we see little evidence of a consistent model emerging to explain lattice parameter changes with nanoparticle size. Based on these results and a review of the literature it is worthwhile asking if a model of surface enhanced defect concentration is consistent with known cerium/cerium oxide chemistries, whether this is applicable to a range of different synthesis methods and if a more consistent description is possible. In Chapter one the science of cerium oxide is outlined including the crystal structure, defect chemistry and different oxidation states available. The uses and applications of cerium oxide are also discussed as well as modelling of the lattice parameter and the doping of the ceria lattice. Chapter two describes both the synthesis techniques and the analytical methods employed to execute this research. Chapter three focuses on high surface area ceria nano-particles and how these have been prepared using a citrate sol-gel precipitation method. Changes to the particle size have been made by calcining the ceria powders at different temperatures. X-ray diffraction methods were used to determine their lattice parameters. The particles sizes were also assessed using transmission electron microscopy (TEM), scanning electron microscopy (SEM), and BET, and, the lattice parameter was found to decrease with decreasing particle size. The results are discussed in light of the role played by surface tension effects. Chapter four describes the morphological and structural characterization of crystalline CeO2 nanoparticles prepared by forward and reverse precipitation techniques and compares these by powder x-ray diffraction (PXRD), nitrogen adsorption (BET) and high resolution transmission electron microscopy (HRTEM) analysis. The two routes give quite different materials although in both cases the products are essentially highly crystalline, dense particulates. It was found that the reverse precipitation technique gave the smallest crystallites with the narrowest size dispersion. This route also gave as-synthesised materials with higher surface areas. HRTEM confirmed the observations made from PXRD data and showed that the two methods resulted in quite different morphologies and surface chemistries. The forward route gives products with significantly greater densities of Ce3+ species compared to the reverse route. Data are explained using known precipitation chemistry and kinetic effects. Chapter five centres on the addition of terbia to ceria and has been investigated using XRD, XRF, XPS and TEM. Good solid solutions were formed across the entire composition range and there was no evidence for the formation of mixed phases or surface segregation over either the composition or temperature range investigated. Both Tb3+ and Tb4+ ions exist within the solution and the ratios of these cations are consistent with the addition of Tb8O15 to the fluorite ceria structure across a wide range of compositions. Local regions of anion vacancy ordering may be visible for small crystallites. There is no evidence of significant Ce3+ ion concentrations formed at the surface or in the bulk by the addition of terbia. The lattice parameter of these materials was seen to decrease with decreasing crystallite size. This is consistent with increased surface tension effects at small dimension. Chapter six reviews size related lattice parameter changes and surface defects in ceria nanocrystals. Ceria (CeO2) has many important applications, notably in catalysis. Many of its uses rely on generating nanodimensioned particles. Ceria has important redox chemistry where Ce4+ cations can be reversibly reduced to Ce3+ cations and associated anion vacancies. The significantly larger size of Ce3+ (compared with Ce4+) has been shown to result in lattice expansion. Many authors have observed lattice expansion in nanodimensioned crystals (nanocrystals), and these have been attributed to the presence of stabilized Ce3+ -anion vacancy combinations in these systems. Experimental results presented here show (i) that significant, but complex changes in the lattice parameter with size can occur in 2-500 nm crystallites, (ii) that there is a definitive relationship between defect chemistry and the lattice parameter in ceria nanocrystals, and (iii) that the stabilizing mechanism for the Ce3+ -anion vacancy defects at the surface of ceria nanocrystals is determined by the size, the surface status, and the analysis conditions. In this work, both lattice expansion and a more unusual lattice contraction in ultrafine nanocrystals are observed. The lattice deformations seen can be defined as a function of both the anion vacancy (hydroxyl) concentration in the nanocrystal and the intensity of the additional pressure imposed by the surface tension on the crystal. The expansion of lattice parameters in ceria nanocrystals is attributed to a number of factors, most notably, the presence of any hydroxyl moieties in the materials. Thus, a very careful understanding of the synthesis combined with characterization is required to understand the surface chemistry of ceria nanocrystals.
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This thesis involved researching normative family discourses which are mediated through educational settings. The traditional family, consisting of father, mother and children all living together in one house is no longer reflective of the home situation of many Irish students (Lunn and Fahey, 2011). My study problematizes the dominant discourses which reflect how family differences are managed and recognised in schools. A framework using Foucauldian post structural critical analysis traces family stratification through the organisation of institutional and interpersonal relations at micro level in four post-primary schools. Standardising procedures such as the suppression of intimate relations between and among teacher and student, as well as the linear ordering of intergenerational relations, such as teacher/student and adult/child are critiqued. Normalising discourses operate in practices such as notes home which presume two parents together. Teacher assumptions about heterosexual two-parent families make it difficult for students to be open about a family setup that is constructed as different to the rest of the schools'. The management of family difference and deficit through pastoral care structures suggests a school-based politics of family adjustment. These practices beg the question whether families are better off not telling the school about their family identity. My thesis will be of interest to educational research and educational policy because it highlights how changing demographics such as family compositions are mis-conceptualised in schools, as well as revealing the changing forms of family governance through regimes such as pastoral care. This analysis allows for the existence of, and a valuing for, alternative modes of family existence, so that future curricular and legal discourses can be challenged in the interest of equity and social justice.
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In decision making problems where we need to choose a particular decision or alternative from a set of possible choices, we often have some preferences which determine if we prefer one decision over another. When these preferences give us an ordering on the decisions that is complete, then it is easy to choose the best or one of the best decisions. However it often occurs that the preferences relation is partially ordered, and we have no best decision. In this thesis, we look at what happens when we have such a partial order over a set of decisions, in particular when we have multiple orderings on a set of decisions, and we present a framework for qualitative decision making. We look at the different natural notions of optimal decision that occur in this framework, which gives us different optimality classes, and we examine the relationships between these classes. We then look in particular at a qualitative preference relation called Sorted-Pareto Dominance, which is an extension of Pareto Dominance, and we give a semantics for this relation as one that is compatible with any order-preserving mapping of an ordinal preference scale to a numerical one. We apply Sorted-Pareto dominance to a Soft Constraints setting, where we solve problems in which the soft constraints associate qualitative preferences to decisions in a decision problem. We also examine the Sorted-Pareto dominance relation in the context of our qualitative decision making framework, looking at the relevant optimality classes for the Sorted-Pareto case, which gives us classes of decisions that are necessarily optimal, and optimal for some choice of mapping of an ordinal scale to a quantitative one. We provide some empirical analysis of Sorted-Pareto constraints problems and examine the optimality classes that result.
Development of large-scale colloidal crystallisation methods for the production of photonic crystals
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Colloidal photonic crystals have potential light manipulation applications including; fabrication of efficient lasers and LEDs, improved optical sensors and interconnects, and improving photovoltaic efficiencies. One road-block of colloidal selfassembly is their inherent defects; however, they can be manufactured cost effectively into large area films compared to micro-fabrication methods. This thesis investigates production of ‘large-area’ colloidal photonic crystals by sonication, under oil co-crystallization and controlled evaporation, with a view to reducing cracking and other defects. A simple monotonic Stöber particle synthesis method was developed producing silica particles in the range of 80 to 600nm in a single step. An analytical method assesses the quality of surface particle ordering in a semiquantitative manner was developed. Using fast Fourier transform (FFT) spot intensities, a grey scale symmetry area method, has been used to quantify the FFT profiles. Adding ultrasonic vibrations during film formation demonstrated large areas could be assembled rapidly, however film ordering suffered as a result. Under oil cocrystallisation results in the particles being bound together during film formation. While having potential to form large areas, it requires further refinement to be established as a production technique. Achieving high quality photonic crystals bonded with low concentrations (<5%) of polymeric adhesives while maintaining refractive index contrast, proved difficult and degraded the film’s uniformity. A controlled evaporation method, using a mixed solvent suspension, represents the most promising method to produce high quality films over large areas, 75mm x 25mm. During this mixed solvent approach, the film is kept in the wet state longer, thus reducing cracks developing during the drying stage. These films are crack-free up to a critical thickness, and show very large domains, which are visible in low magnification SEM images as Moiré fringe patterns. Higher magnification reveals separation between alternate fringe patterns are domain boundaries between individual crystalline growth fronts.
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In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on ϵ-coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.
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This thesis presents several routes towards achieving artificial opal templates by colloidal self-assembly of polystyrene (PS) or poly(methyl methacrylate) (PMMA) spheres and the use of these template for the fabrication of V2O5 inverse opals as cathode materials for lithium ion battery applications. First, through the manipulation of different experimental factors, several methods of affecting or directing opal growth towards realizing different structures, improving order and/or achieving faster formation on a variety of substrates are presented. The addition of the surfactant sodium dodecyl sulphate (SDS) at a concentration above the critical micelle concentration for SDS to a 5 wt% solution of PMMA spheres before dip-coating is presented as a method of achieving ordered 2D PhC monolayers on hydrophobic Au-coated silicon substrates at fast and slow rates of withdrawal. The effect that the degree of hydrophilicity of glass substrates has on the ordering of PMMA spheres is next investigated for a slow rate of withdrawal under noise agitation. Heating of the colloidal solution is also presented as a means of affecting order and thickness of opal deposits formed using fast rate dip coating. E-beam patterned substrates are shown as a means of altering the thermodynamically favoured FCC ordering of polystyrene spheres (PS) when dip coated at slow rate. Facile routes toward the synthesis of ordered V2O5 inverse opals are presented with direct infiltration of polymer sphere templates using liquid precursor. The use of different opal templates, both 2D and 3D partially ordered templates, is compared and the composition and arrangement of the subsequent IO structures post infiltration and calcination for various procedures is characterised. V2O5 IOs are also synthesised by electrodeposition from an aqueous VOSO4 solution at constant voltage. Electrochemical characterisation of these structures as cathode material for Li-ion batteries is assessed in a half cell arrangement for samples deposited on stainless steel foil substrates. Improved rate capabilities are demonstrated for these materials over bulk V2O5, with the improvement attributed to the shorter Li ion diffusion distances and increased electrolyte infiltration provided by the IO structure.
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Copper is the main interconnect material in microelectronic devices, and a 2 nm-thick continuous Cu film seed layer needs to be deposited to produce microelectronic devices with the smallest features and more functionality. Atomic layer deposition (ALD) is the most suitable method to deposit such thin films. However, the reaction mechanism and the surface chemistry of copper ALD remain unclear, which is deterring the development of better precursors and design of new ALD processes. In this thesis, we study the surface chemistries during ALD of copper by means of density functional theory (DFT). To understand the effect of temperature and pressure on the composition of copper with substrates, we used ab initio atomistic thermodynamics to obtain phase diagram of the Cu(111)/SiO2(0001) interface. We found that the interfacial oxide Cu2O phases prefer high oxygen pressure and low temperature while the silicide phases are stable at low oxygen pressure and high temperature for Cu/SiO2 interface, which is in good agreement with experimental observations. Understanding the precursor adsorption on surfaces is important for understanding the surface chemistry and reaction mechanism of the Cu ALD process. Focusing on two common Cu ALD precursors, Cu(dmap)2 and Cu(acac)2, we studied the precursor adsorption on Cu surfaces by means of van der Waals (vdW) inclusive DFT methods. We found that the adsorption energies and adsorption geometries are dependent on the adsorption sites and on the method used to include vdW in the DFT calculation. Both precursor molecules are partially decomposed and the Cu cations are partially reduced in their chemisorbed structure. It is found that clean cleavage of the ligand−metal bond is one of the requirements for selecting precursors for ALD of metals. 2 Bonding between surface and an atom in the ligand which is not coordinated with the Cu may result in impurities in the thin film. To have insight into the reaction mechanism of a full ALD cycle of Cu ALD, we proposed reaction pathways based on activation energies and reaction energies for a range of surface reactions between Cu(dmap)2 and Et2Zn. The butane formation and desorption steps are found to be extremely exothermic, explaining the ALD reaction scheme of original experimental work. Endothermic ligand diffusion and re-ordering steps may result in residual dmap ligands blocking surface sites at the end of the Et2Zn pulse, and in residual Zn being reduced and incorporated as an impurity. This may lead to very slow growth rate, as was the case in the experimental work. By investigating the reduction of CuO to metallic Cu, we elucidated the role of the reducing agent in indirect ALD of Cu. We found that CuO bulk is protected from reduction during vacuum annealing by the CuO surface and that H2 is required in order to reduce that surface, which shows that the strength of reducing agent is important to obtain fully reduced metal thin films during indirect ALD processes. Overall, in this thesis, we studied the surface chemistries and reaction mechanisms of Cu ALD processes and the nucleation of Cu to form a thin film.
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In some supply chains, materials are ordered periodically according to local information. This paper investigates how to improve the performance of such a supply chain. Specifically, we consider a serial inventory system in which each stage implements a local reorder interval policy; i.e., each stage orders up to a local basestock level according to a fixed-interval schedule. A fixed cost is incurred for placing an order. Two improvement strategies are considered: (1) expanding the information flow by acquiring real-time demand information and (2) accelerating the material flow via flexible deliveries. The first strategy leads to a reorder interval policy with full information; the second strategy leads to a reorder point policy with local information. Both policies have been studied in the literature. Thus, to assess the benefit of these strategies, we analyze the local reorder interval policy. We develop a bottom-up recursion to evaluate the system cost and provide a method to obtain the optimal policy. A numerical study shows the following: Increasing the flexibility of deliveries lowers costs more than does expanding information flow; the fixed order costs and the system lead times are key drivers that determine the effectiveness of these improvement strategies. In addition, we find that using optimal batch sizes in the reorder point policy and demand rate to infer reorder intervals may lead to significant cost inefficiency. © 2010 INFORMS.