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Design activity could be treated as state transition computationally. In stepwise processing, in-between form-states are not easily observed. However, in this research time-based concept is introduced and applied in order to bridge the gap. In architecture, folding is one method of form manipulation and architects also want to search for alternatives by this operation. Besides, folding operation has to be defined and parameterized before time factor is involved as a variable of folding. As a result, time-based transformation provides sequential form states and redirects design activity.
In this paper we study the structure of the solutions to higher dimensional Dirac type equations generalizing the known λ-hyperholomorphic functions, where λ is a complex parameter. The structure of the solutions to the system of partial differential equations (D- λ) f=0 show a close connection with Bessel functions of first kind with complex argument. The more general system of partial differential equations that is considered in this paper combines Dirac and Euler operators and emphasizes the role of the Bessel functions. However, contrary to the simplest case, one gets now Bessel functions of any arbitrary complex order.
Am Beispiel eines 3-feldrigen Durchlaufträgers wird die Versagenswahrscheinlichkeit von wechselnd belasteten Stahlbetonbalken bezüglich des Grenzzustandes der Adaption (Einspielen, shakedown) untersucht. Die Adaptionsanalyse erfolgt unter Berücksichtigung der beanspruchungschabhängigen Degradation der Biegesteifigkeit infolge Rissbildung. Die damit verbundene mechanische Problemstellung kann auf die Adaptionsanalyse linear elastisch - ideal plastischer Balkentragwerke mit unbekannter aber begrenzter Biegesteifigkeit zurückgeführt werden. Die Versagenswahrscheinlichkeit wird unter Berücksichtigung stochastischer Tragwerks- und Belastungsgrößen berechnet. Tragwerkseigenschaften und ständige Lasten gelten als zeitunabhängige Zufallsgrößen. Zeitlich veränderliche Lasten werden als nutzungsdauerbezogene Extremwerte POISSONscher Rechteck-Pulsprozesse unter Berücksichtigung zeitlicher Überlagerungseffekte modelliert, so dass die Versagenswahrscheinlichkeit ebenfalls eine nutzungsdauerbezogene Größe ist. Die mechanischen Problemstellungen werden numerisch mit der mathematischen Optimierung gelöst. Die Versagenswahrscheinlichkeit wird auf statistischem Weg mit der Monte-Carlo-Methode geschätzt.
Für eine gesicherte Planung im Bestand, sind eine Fülle verschiedenster Informationen zu berücksichtigen, welche oft erst während des Planungs- oder Bauprozesses gewonnen werden. Voraussetzung hierfür bildet immer eine Bestandserfassung. Zwar existieren Computerprogramme zur Unterstützung der Bestandserfassung, allerdings handelt es sich hierbei ausschließlich um Insellösungen. Der Export der aufgenommenen Daten in ein Planungssystem bedingt Informationsverluste. Trotz der potentiellen Möglichkeit aktueller CAAD/BIM Systeme zur Verwaltung von Bestandsdaten, sind diese vorrangig für die Neubauplanung konzipiert. Die durchgängige Bearbeitung von Sanierungsprojekten von der Erfassung des Bestandes über die Entwurfs- und Genehmigungsplanung bis zur Ausführungsplanung innerhalb eines CAAD/BIM Systems wird derzeit nicht adäquat unterstützt. An der Professur Informatik in der Architektur (InfAR) der Fakultät Architektur der Bauhaus-Universität Weimar entstanden im Rahmen des DFG Sonderforschungsbereich 524 "Werkzeuge und Konstruktionen für die Revitalisierung von Bauwerken" in den letzten Jahren Konzepte und Prototypen zur fachlich orientierten Unterstützung der Planung im Bestand. Der Fokus lag dabei in der Erfassung aller planungsrelevanter Bestandsdaten und der Abbildung dieser in einem dynamischen Bauwerksmodell. Aufbauend auf diesen Forschungsarbeiten befasst sich der Artikel mit der kontextbezogenen Weiterverwendung und gezielten Bereitstellung von Bestandsdaten im Prozess des Planens im Bestand und der Integration von Konzepten der planungsrelevanten Bestandserfassung in marktübliche CAAD/BIM Systeme.
The one-dimensional continuous wavelet transform is a successful tool for signal and image analysis, with applications in physics and engineering. Clifford analysis offers an appropriate framework for taking wavelets to higher dimension. In the usual orthogonal case Clifford analysis focusses on monogenic functions, i.e. null solutions of the rotation invariant vector valued Dirac operator ∂, defined in terms of an orthogonal basis for the quadratic space Rm underlying the construction of the Clifford algebra R0,m. An intrinsic feature of this function theory is that it encompasses all dimensions at once, as opposed to a tensorial approach with products of one-dimensional phenomena. This has allowed for a very specific construction of higher dimensional wavelets and the development of the corresponding theory, based on generalizations of classical orthogonal polynomials on the real line, such as the radial Clifford-Hermite polynomials introduced by Sommen. In this paper, we pass to the Hermitian Clifford setting, i.e. we let the same set of generators produce the complex Clifford algebra C2n (with even dimension), which we equip with a Hermitian conjugation and a Hermitian inner product. Hermitian Clifford analysis then focusses on the null solutions of two mutually conjugate Hermitian Dirac operators which are invariant under the action of the unitary group. In this setting we construct new Clifford-Hermite polynomials, starting in a natural way from a Rodrigues formula which now involves both Dirac operators mentioned. Due to the specific features of the Hermitian setting, four different types of polynomials are obtained, two types of even degree and two types of odd degree. These polynomials are used to introduce a new continuous wavelet transform, after thorough investigation of all necessary properties of the involved polynomials, the mother wavelet and the associated family of wavelet kernels.
Image processing has been much inspired by the human vision, in particular with regard to early vision. The latter refers to the earliest stage of visual processing responsible for the measurement of local structures such as points, lines, edges and textures in order to facilitate subsequent interpretation of these structures in higher stages (known as high level vision) of the human visual system. This low level visual computation is carried out by cells of the primary visual cortex. The receptive field profiles of these cells can be interpreted as the impulse responses of the cells, which are then considered as filters. According to the Gaussian derivative theory, the receptive field profiles of the human visual system can be approximated quite well by derivatives of Gaussians. Two mathematical models suggested for these receptive field profiles are on the one hand the Gabor model and on the other hand the Hermite model which is based on analysis filters of the Hermite transform. The Hermite filters are derivatives of Gaussians, while Gabor filters, which are defined as harmonic modulations of Gaussians, provide a good approximation to these derivatives. It is important to note that, even if the Gabor model is more widely used than the Hermite model, the latter offers some advantages like being an orthogonal basis and having better match to experimental physiological data. In our earlier research both filter models, Gabor and Hermite, have been developed in the framework of Clifford analysis. Clifford analysis offers a direct, elegant and powerful generalization to higher dimension of the theory of holomorphic functions in the complex plane. In this paper we expose the construction of the Hermite and Gabor filters, both in the classical and in the Clifford analysis framework. We also generalize the concept of complex Gaussian derivative filters to the Clifford analysis setting. Moreover, we present further properties of the Clifford-Gabor filters, such as their relationship with other types of Gabor filters and their localization in the spatial and in the frequency domain formalized by the uncertainty principle.
In earlier research, generalized multidimensional Hilbert transforms have been constructed in m-dimensional Euclidean space, in the framework of Clifford analysis. Clifford analysis, centred around the notion of monogenic functions, may be regarded as a direct and elegant generalization to higher dimension of the theory of the holomorphic functions in the complex plane. The considered Hilbert transforms, usually obtained as a part of the boundary value of an associated Cauchy transform in m+1 dimensions, might be characterized as isotropic, since the metric in the underlying space is the standard Euclidean one. In this paper we adopt the idea of a so-called anisotropic Clifford setting, which leads to the introduction of a metric dependent m-dimensional Hilbert transform, showing, at least formally, the same properties as the isotropic one. The Hilbert transform being an important tool in signal analysis, this metric dependent setting has the advantage of allowing the adjustment of the co-ordinate system to possible preferential directions in the signals to be analyzed. A striking result to be mentioned is that the associated anisotropic (m+1)-dimensional Cauchy transform is no longer uniquely determined, but may stem from a diversity of (m+1)-dimensional "mother" metrics.
The contribution focuses on the development of a basic computational scheme that provides a suitable calculation environment for the coupling of analytical near-field solutions with numerical standard procedures in the far-field of the singularity. The proposed calculation scheme uses classical methods of complex function theory, which can be generalized to 3-dimensional problems by using the framework of hypercomplex analysis. The adapted approach is mainly based on the factorization of the Laplace operator EMBED Equation.3 by the Cauchy-Riemann operator EMBED Equation.3 , where exact solutions of the respective differential equation are constructed by using an orthonormal basis of holomorphic and anti-holomorphic functions.
Objects for civil engineering applications can be identified with their reference in memory, their alpha-numeric name or their geometric location. Particularly in graphic user interfaces, it is common to identify objects geometrically by selection with the mouse. As the number of geometric objects in a graphic user interface grows, it becomes increasingly more important to treat the basic operations add, search and remove for geometric objects with great efficiency. Guttmann has proposed the Region-Tree (R-tree) for geometric identification in an environment which uses pages on disc as data structure. Minimal bounding rectangles are used to structure the data in such a way that neighborhood relations can be described effectively. The literature shows that the parameters which influence the efficiency of the R-trees have been studied extensively, but without conclusive results. The goal of the research which is reported in this paper is to determine reliably the parameters which significantly influence the efficiency of R-trees for geometric identification in technical drawings. In order to make this investigation conclusive, it must be performed with the best available software technology. Therefore an object-oriented software for the method is developed. This implementation is tested with technical drawings containing many thousands of geometric objects. These drawings are created automatically by a stochastic generator which is incorporated into a test bed consisting of an editor and a visualisor. This test bed is used to obtain statistics for the main factors which affect the efficiency of R-trees. The investigation shows that the following main factors which affect the efficiency can be identified reliably : number of geometric objects on the drawing the minimum und maximum number of children of a node of the tree the maximum width and height of the minimal bounding rectangles of the geometric objects relative to the size of the drawing.
Practical examples show that the improvement in cost flow and total amount of money spend in construction and further use may be cut significantly. The calculation is based on spreadsheets calculation, very easy to develop on most PC´s now a days. Construction works, are a field where the evaluation of Cash Flow can be and should be applied. Decisions about cash flow in construction are decisions with long-term impact and long-term memory. Mistakes from the distant past have a massive impact on situations in the present and into the far economic future of economic activities. Two approaches exist. The Just-in-Time (JIT) approach and life cycle costs (LCC) approach. The calculation example shows the dynamic results for the production speed in opposition to stable flow of production in duration of activities. More sophisticated rescheduling in optimal solution might bring in return extra profit. In the technologies and organizational processes for industrial buildings, railways and road reconstruction, public utilities and housing developments there are assembly procedures that are very appropriate for the given purpose, complicated research-, development-, innovation-projects are all very good aspects of these kinds of applications. The investors of large investments and all public invested money may be spent more efficiently if an optimisation speed-strategy can be calculated.