@inproceedings{BeranDlask, author = {Beran, V{\´a}clav and Dlask, Petr}, title = {CONSTRUCTION SPEED AND CASH FLOW OPTIMISATION}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, doi = {10.25643/bauhaus-universitaet.2926}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170327-29269}, pages = {10}, abstract = {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.}, subject = {Architektur }, language = {en} } @inproceedings{BeranHromada, author = {Beran, V{\´a}clav and Hromada, E.}, title = {SOFTWARE FOR PROJECT RELIABILITY ESTIMATION AND RISK EVALUATION}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, doi = {10.25643/bauhaus-universitaet.2925}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170327-29255}, pages = {16}, abstract = {The contribution presents a model that is able to simulate construction duration and cost for a building project. This model predicts set of expected project costs and duration schedule depending on input parameters such as production speed, scope of work, time schedule, bonding conditions and maximum and minimum deviations from scope of work and production speed. The simulation model is able to calculate, on the basis of input level of probability, the adequate construction cost and time duration of a project. The reciprocal view attends to finding out the adequate level of probability for construction cost and activity durations. Among interpretive outputs of the application software belongs the compilation of a presumed dynamic progress chart. This progress chart represents the expected scenario of development of a building project with the mapping of potential time dislocations for particular activities. The calculation of a presumed dynamic progress chart is based on an algorithm, which calculates mean values as a partial result of the simulated building project. Construction cost and time models are, in many ways, useful tools in project management. Clients are able to make proper decisions about the time and cost schedules of their investments. Consequently, building contractors are able to schedule predicted project cost and duration before any decision is finalized.}, subject = {Architektur }, language = {en} } @inproceedings{BertholdMilbradt, author = {Berthold, Tim and Milbradt, Peter}, title = {ARTIFICIAL NEURONAL NETWORKS IN ENVIRONMENTAL ENGINEERING: THEORY AND APPLICATIONS}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2830}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28304}, pages = {14}, abstract = {Models in the context of engineering can be classified in process based and data based models. Whereas the process based model describes the problem by an explicit formulation, the data based model is often used, where no such mapping can be found due to the high complexity of the problem. Artificial Neuronal Networks (ANN) is a data based model, which is able to "learn" a mapping from a set of training patterns. This paper deals with the application of ANN in time dependent bathymetric models. A bathymetric model is a geometric representation of the sea bed. Typically, a bathymetry is been measured and afterwards described by a finite set of measured data. Measuring at different time steps leads to a time dependent bathymetric model. To obtain a continuous surface, the measured data has to be interpolated by some interpolation method. Unlike the explicitly given interpolation methods, the presented time dependent bathymetric model using an ANN trains the approximated surface in space and time in an implicit way. The ANN is trained by topographic measured data, which consists of the location (x,y) and time t. In other words the ANN is trained to reproduce the mapping h = f(x,y,t) and afterwards it is able to approximate the topographic height for a given location and date. In a further step, this model is extended to take meteorological parameters into account. This leads to a model of more predictive character.}, subject = {Angewandte Informatik}, language = {en} } @inproceedings{Bilchuk, author = {Bilchuk, Irina}, title = {GEOMETRIC IDENTIFICATION OF OBJECTS IN CIVIL ENGINEERING APPLICATIONS}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, doi = {10.25643/bauhaus-universitaet.2927}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170327-29274}, pages = {21}, abstract = {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.}, subject = {Architektur }, language = {en} } @inproceedings{BockGuerlebeck, author = {Bock, Sebastian and G{\"u}rlebeck, Klaus}, title = {A Coupled Ritz-Galerkin Approach Using Holomorphic and Anti-holomorphic Functions}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, doi = {10.25643/bauhaus-universitaet.2928}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170327-29281}, pages = {14}, abstract = {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.}, subject = {Architektur }, language = {en} } @inproceedings{BombasaroBucher, author = {Bombasaro, Emanuel and Bucher, Christian}, title = {INVESTIGATION OF MODELING ERRORS OF DIFFERENT RANDOM FIELD BASED WIND LOAD FORMULATIONS}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2831}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28318}, pages = {11}, abstract = {In this paper the influence of changes in the mean wind velocity, the wind profile power-law coefficient, the drag coefficient of the terrain and the structural stiffness are investigated on different complex structural models. This paper gives a short introduction to wind profile models and to the approach by Davenport A. G. to compute the structural reaction of wind induced vibrations. Firstly with help of a simple example (a skyscraper) this approach is shown. Using this simple example gives the reader the possibility to study the variance differences when changing one of the above mentioned parameters on this very easy example and see the influence of different complex structural models on the result. Furthermore an approach for estimation of the needed discretization level is given. With the help of this knowledge the structural model design methodology can be base on deeper understanding of the different behavior of the single models.}, subject = {Angewandte Informatik}, language = {en} } @inproceedings{BrackxDeKnockDeSchepper, author = {Brackx, Fred and De Knock, B. and De Schepper, Hennie}, title = {A MULTI--DIMENSIONAL HILBERT TRANSFORM IN ANISOTROPIC CLIFFORD ANALYSIS}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, doi = {10.25643/bauhaus-universitaet.2929}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170327-29297}, pages = {15}, abstract = {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.}, subject = {Architektur }, language = {en} } @inproceedings{BrackxDeSchepperDeSchepperetal., author = {Brackx, Fred and De Schepper, Hennie and De Schepper, Nele and Sommen, Frank}, title = {HERMITIAN CLIFFORD-HERMITE WAVELETS}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, doi = {10.25643/bauhaus-universitaet.2931}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170327-29313}, pages = {13}, abstract = {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.}, subject = {Architektur }, language = {en} } @inproceedings{BrackxDeSchepperLunaElizararrasetal., author = {Brackx, Fred and De Schepper, Hennie and Luna-Elizararras, Maria Elena and Shapiro, Michael}, title = {INTEGRAL REPRESENTATIONS IN HERMITEAN CLIFFORD ANALYSIS}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2832}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28326}, pages = {13}, abstract = {Euclidean Clifford analysis is a higher dimensional function theory offering a refinement of classical harmonic analysis. The theory is centered around the concept of monogenic functions, i.e. null solutions of a first order vector valued rotation invariant differential operator called the Dirac operator, which factorizes the Laplacian. More recently, Hermitean Clifford analysis has emerged as a new and successful branch of Clifford analysis, offering yet a refinement of the Euclidean case; it focusses on the simultaneous null solutions, called Hermitean (or h-) monogenic functions, of two Hermitean Dirac operators which are invariant under the action of the unitary group. In Euclidean Clifford analysis, the Clifford-Cauchy integral formula has proven to be a corner stone of the function theory, as is the case for the traditional Cauchy formula for holomorphic functions in the complex plane. Previously, a Hermitean Clifford-Cauchy integral formula has been established by means of a matrix approach. This formula reduces to the traditional Martinelli-Bochner formula for holomorphic functions of several complex variables when taking functions with values in an appropriate part of complex spinor space. This means that the theory of Hermitean monogenic functions should encompass also other results of several variable complex analysis as special cases. At present we will elaborate further on the obtained results and refine them, considering fundamental solutions, Borel-Pompeiu representations and the Teoderescu inversion, each of them being developed at different levels, including the global level, handling vector variables, vector differential operators and the Clifford geometric product as well as the blade level were variables and differential operators act by means of the dot and wedge products. A rich world of results reveals itself, indeed including well-known formulae from the theory of several complex variables.}, subject = {Angewandte Informatik}, language = {en} } @inproceedings{BrackxDeSchepperSommen, author = {Brackx, Fred and De Schepper, Nele and Sommen, Frank}, title = {Clifford-Hermite and Two-Dimensional Clifford-Gabor Filters For Early Vision}, editor = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten}, organization = {Bauhaus-Universit{\"a}t Weimar}, doi = {10.25643/bauhaus-universitaet.2930}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170327-29303}, pages = {22}, abstract = {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.}, subject = {Architektur }, language = {en} }