Ni50.6Ti49.4 single and Ni52Ti48 polycrystalline shape memory alloy samples were subjected to aging under a uniaxial stress, to form a single Ni4Ti3 precipitate variant and to investigate the effects of single versus multi-variant coherent precipitates on the shape memory characteristics including two-way shape memory effect (TWSME). Shape memory and superelasticity properties along with the effects of stress and temperature on the transformation temperatures, strain, hysteresis, dimensional stability, and R-phase formation were investigated. This was accomplished through the use of isobaric thermal cycling and superelasticity experiments and various microscopy techniques that included transmission electron microscopy (TEM), scanning electron microscopy, and optical microcopy. The results showed that it is feasible to use constrained aging to bias R-phase martensite variants upon cooling from austenite without any external stress, however, accomplishing this with B19’martensite was much harder as complete TWSME was only found in the Ni50.6Ti49.4 single crystalline sample oriented along the [112] direction. The onset of irrecoverable strain corresponded to the R-phase temperature hysteresis increase in the single crystalline samples regardless of the aging conditions. Through TEM analysis it was discovered that [112] and [114] twins were found in austenite due to plastic deformation of martensite during the superelasticity experiments. Since [112] twins are theoretically impossible to form in austenite, and since martensite was plastically deformed, [112] austenite twins were attributed to the transformation of compound twins in martensite, in particular [113] martensite twins formed during the plastic deformation of martensite, into austenite twins. In the Ni52Ti48 polycrystalline samples, a compressive R-phase variant was biased through constrained aging under 100 and 200 MPa uniaxial tensile stresses at 400°C and 450°C. Aging, in all conditions, produced a high density of Ni4Ti3 precipitates that was most likely responsible for the small transformation strain observed, less that 2%, upon transformation to martensite. In the future, samples with compositions between 50.8 and 51.5 Ni atomic percent, in addition to altered solution and aging heat treatments as compared to those used in this study should be investigated as it is believed that samples with these compositions will yield better and consistent TWSME responses through constrained aging.

Ni-Mn-Ga is a ferromagnetic shape memory alloy that can be used for future sensors and actuators. It has been shown that magnetic field can induce phase transformation and consequently large strain in stoichiometric Ni2MnGa. Since then considerable progress has been made in understanding the underlying science of shape memory and ferromagnetic shape memory in bulk materials. Ni-Mn-Ga thin films, however is a relatively under explored area. Ferromagnetic shape memory alloy thin films are conceived as the future MEMS sensor and actuator materials. With a 9.5 percent strain rate reported from magnetic reorientation, Ni-Mn-Ga thin films hold great promise as actuator materials. Thin films come with a number of advantages and challenges as compared to their bulk counterparts. While properties like mechanical strength, uniformity are much better in thin film form, high stress and constraint from the substrate pose a significant challenge for reorientation and shape memory behavior. In either case, it is very important to understand their behavior and examine their properties. This thesis is an effort to contribute to the literature of Ni-Mn-Ga thin films as ferromagnetic shape memory alloys. The focus of this project is to develop a recipe for fabricating NiMnGa thin films with desired composition and microstructure and hence unique properties for future MEMS actuator materials and characterize their properties to aid better understanding of their behavior. In this project NiMnGa thin films have been fabricated using magnetron sputtering on a variety of substrates. Magnetron sputtering technique allows us to tailor the composition of films which is crucial for controlling the phase transformation properties of NiMnGa films. The composition is tailored by varying several deposition parameters. Microstructure of the films has been investigated by X-ray diffraction (XRD) and transmission electron microscopy (TEM) techniques. Mechanical properties of as-deposited films have been probed using nano-indentation technique. The chemistry of sputtered films is determined quantitatively by wavelength dispersive X-ray spectroscopy (WDS). Phase transformation is studied by using a combination of differential scanning calorimetry (DSC), in-situ heating in TEM and in-situ XRD instruments. Magnetic properties of films are examined using superconducting quantum interface device (SQUID).

Thesis (Ph.D.)--City University of Hong Kong, 2009. / "Submitted to Department of Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references (leaves [214]-224)

No description available.

This study presents a new shape representation scheme based on disconnected symmetry axes along with a matching framework to address the problem of generic shape recognition. The main idea is to define the relative spatial arrangement of local symmetry axes in a shape centered coordinate frame. The resulting descriptions are invariant to scale, rotation, small changes in viewpoint and articulations. Symmetry points are extracted from a surface whose level curves roughly mimic the motion by curvature. By increasing the amount of smoothing on the evolving curve, only those symmetry axes that correspond to the most prominent parts of a shape are extracted. The representation does not suffer from the common instability problems of the traditional connected skeletons. It captures the perceptual properties of shapes well. Therefore, finding the similarities and the differences among shapes becomes easier. The matching process is able to find the correct correspondence of parts under various visual transformations. Highly successful classification results are obtained on a moderate sized 2D shape database.

Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 249-257).

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Sistemas de recuperaÃÃo de imagens baseada em conteÃdo (do termo em inglÃs, Content-Based Image Retrieval - CBIR) que operam em bases com grande volume de dados constituem um problema relevante e desafiador em diferentes Ãreas do conhecimento, a saber, medicina, biologia, computaÃÃo, catalogaÃÃo em geral, etc. A indexaÃÃo das imagens nestas bases pode ser realizada atravÃs de conteÃdo visual como cor, textura e forma, sendo esta Ãltima caracterÃstica a traduÃÃo visual dos objetos em uma cena. Tarefas automatizadas em inspeÃÃo industrial, registro de marca, biometria e descriÃÃo de imagens utilizam atributos da forma, como os cantos, na geraÃÃo de descritores para representaÃÃo, anÃlise e reconhecimento da mesma, possibilitando ainda que estes descritores se adequem ao uso em sistemas de recuperaÃÃo. Esta tese aborda o problema da extraÃÃo de caracterÃsticas de formas planares binÃrias a partir de cantos, na proposta de um detector multiescala de cantos e sua aplicaÃÃo em um sistema CBIR. O mÃtodo de detecÃÃo de cantos proposto combina uma funÃÃo de angulaÃÃo do contorno da forma, a sua decomposiÃÃo nÃo decimada por transformada wavelet ChapÃu Mexicano e a correlaÃÃo espacial entre as escalas do sinal de angulaÃÃo decomposto. A partir dos resultados de detecÃÃo de cantos, foi realizado um experimento com o sistema CBIR proposto, em que informaÃÃes locais e globais extraÃdas dos cantos detectados da forma foram combinadas à tÃcnica DeformaÃÃo Espacial DinÃmica (do termo em inglÃs, Dynamic Space Warping), para fins de anÃlise de similaridade formas com tamanhos distintos. Ainda com este experimento foi traÃada uma estratÃgia de busca e ajuste dos parÃmetros multiescala de detectores de cantos, segundo a maximizaÃÃo de uma funÃÃo de custo. Na avaliaÃÃo de desempenho da metodologia proposta, e outras tÃcnicas de detecÃÃo de cantos, foram empregadas as medidas PrecisÃo e RevocaÃÃo. Estas medidas atestaram o bom desempenho da metodologia proposta na detecÃÃo de cantos verdadeiros das formas, em uma base pÃblica de imagens cujas verdades terrestres estÃo disponÃveis. Para a avaliaÃÃo do experimento de recuperaÃÃo de imagens, utilizamos a taxa Bullâs eye em trÃs bases pÃblicas. Os valores alcanÃados desta taxa mostraram que o experimento proposto foi bem sucedido na descriÃÃo e recuperaÃÃo das formas, dentre os demais mÃtodos avaliados. / Content-based image retrieval (CBIR) applied to large scale datasets is a relevant and challenging problem present in medicine, biology, computer science, general cataloging etc. Image indexing can be done using visual information such as colors, textures and shapes (the visual translation of objects in a scene). Automated tasks in industrial inspection, trademark registration, biostatistics and image description use shape attributes, e.g. corners, to generate descriptors for representation, analysis and recognition; allowing those descriptors to be used in image retrieval systems. This thesis explores the problem of extracting information from binary planar shapes from corners, by proposing a multiscale corner detector and its use in a CBIR system. The proposed corner detection method combines an angulation function of the shape contour, its non-decimated decomposition using the Mexican hat wavelet and the spatial correlation among scales of the decomposed angulation signal. Using the information provided by our corner detection algorithm, we made experiments with the proposed CBIR. Local and global information extracted from the corners detected on shapes was used in a Dynamic Space Warping technique in order to analyze the similarity among shapes of different sizes. We also devised a strategy for searching and refining the multiscale parameters of the corner detector by maximizing an objective function. For performance evaluation of the proposed methodology and other techniques, we employed the Precision and Recall measures. These measures proved the good performance of our method in detecting true corners on shapes from a public image dataset with ground truth information. To assess the image retrieval experiments, we used the Bullâs eye score in three public databases. Our experiments showed our method performed well when compared to the existing approaches in the literature.

Computing correspondences or maps between shapes is one of the oldest problems in Computer Graphics and Geometry Processing with a wide range of applications from deformation transfer, statistical shape analysis, to co-segmentation and exploration among a myriad others. A good map is supposed to be continuous, as-bijective-as-possible, accurate if there are ground-truth corresponding landmarks given, and lowdistortionw.r.t. different measures, for example as-conformal-as-possible to preserve the angles. This thesis contributes to the area of non-rigid shape matching and map space exploration in Geometry Processing. Specifically, we consider the discrete setting, where the shapes are discretized as amesh structure consisting of vertices, edges, and polygonal faces. In the simplest case, we only consider the graph structure with vertices and edges only. In this thesis, we design algorithms to compute soft correspondences between discrete shapes. Specifically, (1)we propose different regularizers, including orientation-preserving operator and the Resolvent Laplacian Commutativity operator, to promote the shape correspondences in the functional map framework. (2) We propose two refinement methods, namely BCICP and ZoomOut, to improve the accuracy, continuity, bijectivity and the coverage of given point-wisemaps. (3)We propose a tree structure and an enumeration algorithm to explore the map space between a pair of shapes that can update multiple high-quality dense correspondences.

No description available.

No / The complex formation of Islamic geometric Patterns (IGP) is one of the distinctive features in Islamic art and architecture. Many have attempted to reproduce these patterns in digital form, using various pattern generation techniques. Shape grammars are an effective pattern generation method, providing good aesthetic results. In this paper we present a novel approach in generating 3D IGP using an extended shape grammar: Parametrized Shape Grammar (PSG). PSG allows a user to generate both original and novel forms of Islamic geometric motifs (a repeated unit of a pattern). PSG is generalized to generate n-fold Islamic geometric motifs in a 3D environment, practically implemented as a 3D modeling tool within Autodesk Maya. The parametrization within each grammar rule is the key to generating numerous original and novel Islamic geometric motifs.