137 research outputs found

    An Investigation into Animating Plant Structures within Real-time Constraints

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    This paper is an analysis of current developments in rendering botanical structures for scientic and entertainment purposes with a focus on visualising growth. The choices of practical investigations produce a novel approach for parallel parsing of difficult bracketed L-Systems, based upon the work of Lipp, Wonka and Wimmer (2010). Alongside this is a general overview of the issues involved when looking at growing systems, technical details involving programming for the Graphics Processing Unit (GPU) and other possible solutions for further work that also could achieve the project's goals

    Evidence for azimuthal variations of the oxygen abundance gradient tracing the spiral structure of the galaxy HCG91c

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    Context. The distribution of elements in galaxies forms an important diagnostic tool to characterize the system's formation and evolution. This tool is however complex to use in practice, as galaxies are subject to a range of simultaneous physical processes active from pc to kpc scales. This renders observations of the full optical extent of galaxies down to sub-kpc scales essential. Aims. Using the WiFeS integral field spectrograph, we previously detected abrupt and localized variations in the gas-phase oxygen abundance of the spiral galaxy HCG91c. Here, we follow-up on these observations to map HCG91c's disk out to ~2Re at a resolution of 600pc, and characterize the non-radial variations of the gas-phase oxygen abundance in the system. Methods. We obtained deep MUSE observations of the target under ~0.6 arcsec seeing conditions. We perform both a spaxel-based and aperture-based analysis of the data to map the spatial variations of 12+log(O/H) across the disk of the galaxy. Results. We confirm the presence of rapid variations of the oxygen abundance across the entire extent of the galaxy previously detected with WiFeS, for all azimuths and radii. The variations can be separated in two categories: a) localized and associated with individual HII regions, and b) extended over kpc scales, and occurring at the boundaries of the spiral structures in the galaxy. Conclusions. Our MUSE observations suggest that the enrichment of the interstellar medium in HGC91c has proceeded preferentially along spiral structures, and less efficiently across them. Our dataset highlights the importance of distinguishing individual star-forming regions down to scales of a few 100pc when using integral field spectrographs to spatially resolve the distribution of oxygen abundances in a given system, and accurately characterize azimuthal variations and intrinsic scatter.Comment: 12 pages, 11 figures, accepted for publication in A&A. Supplementary movie assocociated with Fig. 8 is available (until publication) at: http://www.sc.eso.org/~fvogt/supp_mat/HCG91c/O_gradient.mp

    Power domains and iterated function systems

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    We introduce the notion of weakly hyperbolic iterated function system (IFS) on a compact metric space, which generalises that of hyperbolic IFS. Based on a domain-theoretic model, which uses the Plotkin power domain and the probabilistic power domain respectively, we prove the existence and uniqueness of the attractor of a weakly hyperbolic IFS and the invariant measure of a weakly hyperbolic IFS with probabilities, extending the classic results of Hutchinson for hyperbolic IFSs in this more general setting. We also present finite algorithms to obtain discrete and digitised approximations to the attractor and the invariant measure, extending the corresponding algorithms for hyperbolic IFSs. We then prove the existence and uniqueness of the invariant distribution of a weakly hyperbolic recurrent IFS and obtain an algorithm to generate the invariant distribution on the digitised screen. The generalised Riemann integral is used to provide a formula for the expected value of almost everywh..

    Evolutionary algorithms in artificial intelligence: a comparative study through applications

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    For many years research in artificial intelligence followed a symbolic paradigm which required a level of knowledge described in terms of rules. More recently subsymbolic approaches have been adopted as a suitable means for studying many problems. There are many search mechanisms which can be used to manipulate subsymbolic components, and in recent years general search methods based on models of natural evolution have become increasingly popular. This thesis examines a hybrid symbolic/subsymbolic approach and the application of evolutionary algorithms to a problem from each of the fields of shape representation (finding an iterated function system for an arbitrary shape), natural language dialogue (tuning parameters so that a particular behaviour can be achieved) and speech recognition (selecting the penalties used by a dynamic programming algorithm in creating a word lattice). These problems were selected on the basis that each should have a fundamentally different interactions at the subsymbolic level. Results demonstrate that for the experiments conducted the evolutionary algorithms performed well in most cases. However, the type of subsymbolic interaction that may occur influences the relative performance of evolutionary algorithms which emphasise either top-down (evolutionary programming - EP) or bottom-up (genetic algorithm - GA) means of solution discovery. For the shape representation problem EP is seen to perform significantly better than a GA, and reasons for this disparity are discussed. Furthermore, EP appears to offer a powerful means of finding solutions to this problem, and so the background and details of the problem are discussed at length. Some novel constraints on the problem's search space are also presented which could be used in related work. For the dialogue and speech recognition problems a GA and EP produce good results with EP performing slightly better. Results achieved with EP have been used to improve the performance of a speech recognition system

    Investigation of key challenges facing aerogel composites development through multiscale approach

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    Error on title page. Date of award is 2022The aerogel particulate and fibre reinforced composites are becoming more and more popular due to their exceptional properties, nevertheless, they do face a range of challenges that need to be overcome for wider applications. The main ones include a lack of understanding of the interactions between aerogels and reinforcing fibre materials, lack of appropriate models to predict their performance, and finally, lack of property database, allowing for an informative selection of aerogel composites as a viable alternative to other materials. The primary goal of this work is to tackle those challenges and provide a better fundamental understanding of some cases of aerogel composites. In order to fulfil the thesis' goals, the aerogel influence on the various thermal and mechanical properties of epoxy and vinyl ester polymers were investigated. By incorporating various weight contents and sizes of silica and polyimide aerogel particles into these polymers, their thermal conductivity, compressive properties, and other thermomechanical properties in these particle-filled polymers have been evaluated. Overall, created composites presented a significant decrease in thermal conductivity, while the introduction of porous particles deteriorated composite mechanical response. Additionally, micromechanical testing of the interface between aerogel and fibre reinforcement has been performed for the first time to understand their bonding ability. By designing a method to deposit an aerogel droplet surrounding the fibre, the microbond tests were enabled, and the results revealed poor adhesion between aerogel and selected fibre type in general. In addition to the experimental part, this study also focused on modelling aerogels and aerogel composites, which provided insight into the interactions between aerogels and most common reinforcement materials using a multiscale approach. As a result, the nanoscale analysis using molecular dynamics allowed to estimate thermal and mechanical properties of low density silica and polyimide. What is more, the aerogel-fibre interfacial properties values have also been obtained though modelling. Finally, the microscale model was used to model the thermal and mechanical properties of epoxy composites. A close match between experimental and modelled thermal conductivity and compressive modulus of epoxy combined with low density silica or polyimide particles has been achieved by incorporating the nanoscale properties into the micromechanical model.The aerogel particulate and fibre reinforced composites are becoming more and more popular due to their exceptional properties, nevertheless, they do face a range of challenges that need to be overcome for wider applications. The main ones include a lack of understanding of the interactions between aerogels and reinforcing fibre materials, lack of appropriate models to predict their performance, and finally, lack of property database, allowing for an informative selection of aerogel composites as a viable alternative to other materials. The primary goal of this work is to tackle those challenges and provide a better fundamental understanding of some cases of aerogel composites. In order to fulfil the thesis' goals, the aerogel influence on the various thermal and mechanical properties of epoxy and vinyl ester polymers were investigated. By incorporating various weight contents and sizes of silica and polyimide aerogel particles into these polymers, their thermal conductivity, compressive properties, and other thermomechanical properties in these particle-filled polymers have been evaluated. Overall, created composites presented a significant decrease in thermal conductivity, while the introduction of porous particles deteriorated composite mechanical response. Additionally, micromechanical testing of the interface between aerogel and fibre reinforcement has been performed for the first time to understand their bonding ability. By designing a method to deposit an aerogel droplet surrounding the fibre, the microbond tests were enabled, and the results revealed poor adhesion between aerogel and selected fibre type in general. In addition to the experimental part, this study also focused on modelling aerogels and aerogel composites, which provided insight into the interactions between aerogels and most common reinforcement materials using a multiscale approach. As a result, the nanoscale analysis using molecular dynamics allowed to estimate thermal and mechanical properties of low density silica and polyimide. What is more, the aerogel-fibre interfacial properties values have also been obtained though modelling. Finally, the microscale model was used to model the thermal and mechanical properties of epoxy composites. A close match between experimental and modelled thermal conductivity and compressive modulus of epoxy combined with low density silica or polyimide particles has been achieved by incorporating the nanoscale properties into the micromechanical model

    Effect of fibre coating and geometry on the tensile properties of hybrid carbon nanotube coated carbon fibre reinforced composite

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    Hierarchically structured hybrid composites are ideal engineered materials to carry loads and stresses due to their high in-plane specific mechanical properties. Growing carbon nanotubes (CNTs) on the surface of high performance carbon fibres (CFs) provides a means to tailor the mechanical properties of the fibre-resin interface of a composite. The growth of CNT on CF was conducted via floating catalyst chemical vapor deposition (CVD). The mechanical properties of the resultant fibres, carbon nanotube (CNT) density and alignment morphology were shown to depend on the CNT growth temperature, growth time, carrier gas flow rate, catalyst amount, and atmospheric conditions within the CVD chamber. Carbon nanotube coated carbon fibre reinforced polypropylene (CNT-CF/PP) composites were fabricated and characterized. A combination of Halpin-Tsai equations, Voigt-Reuss model, rule of mixture and Krenchel approach were used in hierarchy to predict the mechanical properties of randomly oriented short fibre reinforced composite. A fractographic analysis was carried out in which the fibre orientation distribution has been analyzed on the composite fracture surfaces with Scanning Electron Microscope (SEM) and image processing software. Finally, the discrepancies between the predicted and experimental values are explained. (C) 2013 Elsevier Ltd. All rights reserved

    Iterated function systems and shape representation

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    We propose the use of iterated function systems as an isomorphic shape representation scheme for use in a machine vision environment. A concise description of the basic theory and salient characteristics of iterated function systems is presented and from this we develop a formal framework within which to embed a representation scheme. Concentrating on the problem of obtaining automatically generated two-dimensional encodings we describe implementations of two solutions. The first is based on a deterministic algorithm and makes simplifying assumptions which limit its range of applicability. The second employs a novel formulation of a genetic algorithm and is intended to function with general data input. Keywords: Machine Vision, Shape Representation, Iterated Function Systems, Genetic Algorithms

    δ-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis

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    Intuitionistic fuzzy set is capable of handling uncertainty with counterpart falsities which exist in nature. Proximity measure is a convenient way to demonstrate impractical significance of values of memberships in the intuitionistic fuzzy set. However, the related works of Pappis (Fuzzy Sets Syst 39(1):111–115, 1991), Hong and Hwang (Fuzzy Sets Syst 66(3):383–386, 1994), Virant (2000) and Cai (IEEE Trans Fuzzy Syst 9(5):738–750, 2001) did not model the measure in the context of the intuitionistic fuzzy set but in the Zadeh’s fuzzy set instead. In this paper, we examine this problem and propose new notions of δ-equalities for the intuitionistic fuzzy set and δ-equalities for intuitionistic fuzzy relations. Two fuzzy sets are said to be δ-equal if they are equal to an extent of δ. The applications of δ-equalities are important to fuzzy statistics and fuzzy reasoning. Several characteristics of δ-equalities that were not discussed in the previous works are also investigated. We apply the δ-equalities to the application of medical diagnosis to investigate a patient’s diseases from symptoms. The idea is using δ-equalities for intuitionistic fuzzy relations to find groups of intuitionistic fuzzified set with certain equality or similar degrees then combining them. Numerical examples are given to illustrate validity of the proposed algorithm. Further, we conduct experiments on real medical datasets to check the efficiency and applicability on real-world problems. The results obtained are also better in comparison with 10 existing diagnosis methods namely De et al. (Fuzzy Sets Syst 117:209–213, 2001), Samuel and Balamurugan (Appl Math Sci 6(35):1741–1746, 2012), Szmidt and Kacprzyk (2004), Zhang et al. (Procedia Eng 29:4336–4342, 2012), Hung and Yang (Pattern Recogn Lett 25:1603–1611, 2004), Wang and Xin (Pattern Recogn Lett 26:2063–2069, 2005), Vlachos and Sergiadis (Pattern Recogn Lett 28(2):197– 206, 2007), Zhang and Jiang (Inf Sci 178(6):4184–4191, 2008), Maheshwari and Srivastava (J Appl Anal Comput 6(3):772–789, 2016) and Support Vector Machine (SVM)
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