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Utilization of Correlation Matrices in Adaptive Array Processors for Time-Slotted CDMA Uplinks
(2002)
It is well known that the performance of mobile radio systems can be significantly enhanced by the application of adaptive antennas which consist of multi-element antenna arrays plus signal processing circuitry. In the thesis the utilization of such antennas as receive antennas in the uplink of mobile radio air interfaces of the type TD-CDMA is studied. Especially, the incorporation of covariance matrices of the received interference signals into the signal processing algorithms is investigated with a view to improve the system performance as compared to state of the art adaptive antenna technology. These covariance matrices implicitly contain information on the directions of incidence of the interference signals, and this information may be exploited to reduce the effective interference power when processing the signals received by the array elements. As a basis for the investigations, first directional models of the mobile radio channels and of the interference impinging at the receiver are developed, which can be implemented on the computer at low cost. These channel models cover both outdoor and indoor environments. They are partly based on measured channel impulse responses and, therefore, allow a description of the mobile radio channels which comes sufficiently close to reality. Concerning the interference models, two cases are considered. In the one case, the interference signals arriving from different directions are correlated, and in the other case these signals are uncorrelated. After a visualization of the potential of adaptive receive antennas, data detection and channel estimation schemes for the TD-CDMA uplink are presented, which rely on such antennas under the consideration of interference covariance matrices. Of special interest is the detection scheme MSJD (Multi Step Joint Detection), which is a novel iterative approach to multi-user detection. Concerning channel estimation, the incorporation of the knowledge of the interference covariance matrix and of the correlation matrix of the channel impulse responses is enabled by an MMSE (Minimum Mean Square Error) based channel estimator. The presented signal processing concepts using covariance matrices for channel estimation and data detection are merged in order to form entire receiver structures. Important tasks to be fulfilled in such receivers are the estimation of the interference covariance matrices and the reconstruction of the received desired signals. These reconstructions are required when applying MSJD in data detection. The considered receiver structures are implemented on the computer in order to enable system simulations. The obtained simulation results show that the developed schemes are very promising in cases, where the impinging interference is highly directional, whereas in cases with the interference directions being more homogeneously distributed over the azimuth the consideration of the interference covariance matrices is of only limited benefit. The thesis can serve as a basis for practical system implementations.
Microsystem technology has been a fast evolving field over the last few years. Its ability to handle volumes in the sub-microliter range makes it very interesting for potential application in fields such as biology, medicine and pharmaceutical research. However, the use of micro-fabricated devices for the analysis of liquid biological samples still has to prove its applicability for many particular demands of basic research. This is particularly true for samples consisting of complex protein mixtures. The presented study therefore aimed at evaluating if a commonly used glass-coating technique from the field of micro-fluidic technology can be used to fabricate an analysis system for molecular biology. It was ultimately motivated by the demand to develop a technique that allows the analysis of biological samples at the single-cell level. Gene expression at the transcription level is initiated and regulated by DNA-binding proteins. To fully understand these regulatory processes, it is necessary to monitor the interaction of specific transcription factors with other elements - proteins as well as DNA sites - in living cells. One well-established method to perform such analysis is the Chromatin Immunoprecipitation (CHIP) assay. To map protein-DNA interactions, living cells are treated with formaldehyde in vivo to cross-link DNA-binding proteins to their resident sites. The chromatin is then broken into small fragments, and specific antibodies against the protein of interest are used to immunopurify the chromatin fragments to which those factors are bound. After purification, the associated DNA can be detected and analyzed using Polymerase Chain Reaction (PCR). Current CHIP technology is limited as it needs a relatively large number of cells while there is increasing interest in monitoring DNA-protein interactions in very few, if not single cells. Most notably this is the case in research on early organism development (embryogenesis). To investigate if microsystem technology can be used to analyze DNA-protein complexes from samples containing chromatin from only few cells, a new setup for fluid transport in glass capillaries of 75 µm inner diameter has been developed, forming an array of micro-columns for parallel affinity chromatography. The inner capillary walls were antibody-coated using a silane-based protocol. The remaining surface was made chemically inert by saturating free binding sites with suitable biomolecules. Variations of this protocol have been tested. Furthermore, the sensitivity of the PCR method to detect immunoprecipitated protein-DNA complexes was improved, resulting in the reliable detection of about 100 DNA fragments from chromatin. The aim of the study was to successively decrease the amount of analyzed chromatin in order to investigate the lower limits of this technology in regard to sensitivity and specificity of detection. The Drosophila GAGA transcription factor was used as an established model system. The protein has already been analyzed in several large-scale CHIP experiments and antibodies of excellent specificity are available. The results of the study revealed that this approach is not easily applicable to "real-world" biological samples in regard to volume reduction and specificity. Particularly, material that non-specifically adsorbed to capillary surfaces outweighed the specific antibody-antigen interaction, the system was designed for. It became clear that complex biological structures, such as chromatin-protein compositions, are not as easily accessible by techniques based on chemically modified glass surfaces as pre-purified samples. In the case of the investigated system, it became evident that there is a need for more research that goes beyond the scope of this work. It is necessary to develop novel coatings and materials to prevent non-specific adsorption. In addition to improving existing techniques, fundamentally new concepts, such as microstructures in biocompatible polymers or liquid transport on hydrophobic stripes on planar substrates to minimize surface contact, may also help to advance the miniaturization of biological experiments.
This thesis builds a bridge between singularity theory and computer algebra. To an isolated hypersurface singularity one can associate a regular meromorphic connection, the Gauß-Manin connection, containing a lattice, the Brieskorn lattice. The leading terms of the Brieskorn lattice with respect to the weight and V-filtration of the Gauß-Manin connection define the spectral pairs. They correspond to the Hodge numbers of the mixed Hodge structure on the cohomology of the Milnor fibre and belong to the finest known invariants of isolated hypersurface singularities. The differential structure of the Brieskorn lattice can be described by two complex endomorphisms A0 and A1 containing even more information than the spectral pairs. In this thesis, an algorithmic approach to the Brieskorn lattice in the Gauß-Manin connection is presented. It leads to algorithms to compute the complex monodromy, the spectral pairs, and the differential structure of the Brieskorn lattice. These algorithms are implemented in the computer algebra system Singular.
Matrix Compression Methods for the Numerical Solution of Radiative Transfer in Scattering Media
(2002)
Radiative transfer in scattering media is usually described by the radiative transfer equation, an integro-differential equation which describes the propagation of the radiative intensity along a ray. The high dimensionality of the equation leads to a very large number of unknowns when discretizing the equation. This is the major difficulty in its numerical solution. In case of isotropic scattering and diffuse boundaries, the radiative transfer equation can be reformulated into a system of integral equations of the second kind, where the position is the only independent variable. By employing the so-called momentum equation, we derive an integral equation, which is also valid in case of linear anisotropic scattering. This equation is very similar to the equation for the isotropic case: no additional unknowns are introduced and the integral operators involved have very similar mapping properties. The discretization of an integral operator leads to a full matrix. Therefore, due to the large dimension of the matrix in practical applcation, it is not feasible to assemble and store the entire matrix. The so-called matrix compression methods circumvent the assembly of the matrix. Instead, the matrix-vector multiplications needed by iterative solvers are performed only approximately, thus, reducing, the computational complexity tremendously. The kernels of the integral equation describing the radiative transfer are very similar to the kernels of the integral equations occuring in the boundary element method. Therefore, with only slight modifications, the matrix compression methods, developed for the latter are readily applicable to the former. As apposed to the boundary element method, the integral kernels for radiative transfer in absorbing and scattering media involve an exponential decay term. We examine how this decay influences the efficiency of the matrix compression methods. Further, a comparison with the discrete ordinate method shows that discretizing the integral equation may lead to reductions in CPU time and to an improved accuracy especially in case of small absorption and scattering coefficients or if local sources are present.
In this work we present and estimate an explanatory model with a predefined system of explanatory equations, a so called lag dependent model. We present a locally optimal, on blocked neural network based lag estimator and theorems about consistensy. We define the change points in context of lag dependent model, and present a powerfull algorithm for change point detection in high dimensional high dynamical systems. We present a special kind of bootstrap for approximating the distribution of statistics of interest in dependent processes.
In the last decade, injection molding of long-fiber reinforced thermoplastics
(LFT) has been established as a low-cost, high volume technique for manufacturing
parts with complex shape without any post-treatment [1–3]. Applications
are mainly found in the automotive industry with a volume annually
growing by 10% to 15% [4].
While first applications were based on polyamide (PA6 and PA6.6), the market
share of glass fiber reinforced polypropylene (PP) is growing due to cost savings
and ease of processing. With the use of polypropylene, different processing
techniques such as gas-assisted injection molding [5] or injection compression
molding [6] have emerged in addition to injection molding [7, 8].
In order to overcome or justify higher materials costs when compared to short
fiber reinforced thermoplastics, the manufacturing techniques for LFT pellets
with fiber length greater than 10mm have evolved starting from pultrusion by
improving impregnation and throughput [9] or by direct addition of fiber strands
in the mold [10–12].
The benefit of long glass fiber reinforcement either in PP or PA is mainly due
to the enhanced resistance to fiber pull-out resulting in an increase in impact
properties and strength [13–19], even at low temperature levels [20]. Creep
and fatigue resistance are also substantially improved [21, 22].
The performance of fiber reinforced thermoplastics manufactured by injection
molding strongly depends on the flow-induced microstructure which is
driven by materials composition, processing conditions and part geometry.
The anisotropic microstructure is characterized by fiber fraction and dispersion,
fiber length and fiber orientation.
Facing the complexity of this processing technique, simulation becomes a precious
tool already in the concept phase for parts manufactured by injection
molding. Process simulation supports decisions with respect to choice of concepts
and materials. The part design is determined in terms of mold filling
including location of gates, vents and weld lines. Tool design requires the
determination of melt feeding, logistics and mold heating. Subsequently, performance
including prediction of shrinkage and warpage as well as structural
analysis is evaluated [23].
While simulation based on two-dimensional representation of three-dimensional
part geometry has been extensively used during the last two decades, the
complexity of the parts as well as the trend towards solid modelling in CAD
and CAE demands the step towards three-dimensional process simulation. The scope of this work is the prediction of flow-induced microstructure during
injection molding of long glass fiber reinforced polypropylene using threedimensional
process simulation. Modelling of the injection molding process in
three dimensions is supported experimentally by rheological characterization
in both shear and extensional flow and by two- and three-dimensional evaluation
of microstructure.
In chapter 2 the fundamentals of rheometry and rheology are presented with
respect to long fiber reinforced thermoplastics. The influence of parameters
on microstructure is described and approaches for modelling the state of microstructure
and its dynamics are discussed.
Chapter 3 introduces a rheometric technique allowing for rheological characterization
of polymer melts at processing conditions as encountered during
manufacturing. Using this rheometer, both shear and extensional viscosity of
long glass fiber reinforced polypropylene are measured with respect to composition
of materials, processing conditions and geometry of the cavity.
Chapter 4 contains the evaluation of microstructure of long glass fiber reinforced
polypropylene in terms of two-dimensional fiber orientation and its dependence
on materials parameters and processing condition. For the evaluation
of three-dimensional microstructure, a technique based on x-ray tomography
is introduced.
In chapter 5, modelling of microstructural dynamics is addressed. One-way
coupling of interactions between fluid and fibers is described macroscopically.
The flow behavior of fibers in the vicinity of cavity walls is evaluated experimentally.
From these observations, a model for treatment of fiber-wall interaction
with respect to numerical simulation is proposed.
Chapter 6 presents the application of three-dimensional simulation of the injection
molding process. Mold filling simulation is performed using a commercial
code while prediction of 3D fiber orientation is based on a proprietary module.
The rheological and thermal properties derived in chapter 3 are tested by
simulation of the experiments and comparison of predicted pressure and temperature
profile versus recorded results. The performance of fiber orientation
prediction is verified using analytical solutions of test examples from literature.
The capability of three-dimensional simulation is demonstrated based on the
simulation of mold filling and prediction of fiber orientation for an automotive
part.
thesis deals with the investigation of the dynamics of optically excited (hot) electrons in thin and ultra-thin layers. The main interests concern about the time behaviour of the dissipation of energy and momentum of the excited electrons. The relevant relaxation times occur in the femtosecond time region. The two-photon photoemission is known to be an adequate tool in order to analyse such dynamical processes in real-time. This work expands the knowledge in the fields of electron relaxation in ultra-thin silver layers on different substrates, as well as in adsorbate states in a bandgap of a semiconductor. It contributes facts to the comprehension of spin transport through an interface between a metal and a semiconductor. The primary goal was to prove the predicted theory by reducing the observed crystal in at least one direction. One expects a change of the electron relaxation behaviour while altering the crystal’s shape from a 3d bulk to a 2d (ultra-thin) layer. This is due to the fact that below a determined layer thickness, the electron gas transfers to a two-dimensional one. This behaviour could be proven in this work. In an about 3nm thin silver layer on graphite, the hot electrons show a jump to longer relaxation time all over the whole accessible energy range. It is the first time that the temporal evolution of the relaxation of excited electrons could be observed during the transition from a 3d to a 2d system. In order to reduce or even eliminate the influence coming from the substrate, the system of silver on the semiconductor GaAs, which has a bandgap of 1.5eV at the Gamma-point, was investigated. The observations of the relaxation behaviour of hot electron in different ultra-thin silver layers on this semiconductor could show, that at metal-insulator-junctions, plasmons in the silver and in the interface, as well as cascading electrons from higher lying energies, have a huge influence to the dissipation of momentum and energy. This comes mainly from the band bending of the semiconductor, and from the electrons, which are excited in GaAs. The limitation of the silver layer on GaAs in one direction led to the expected generation of quantum well states (QWS) in the bandgap. Those adsorbate states have quantised energy- and momentum values, which are directly connected to the layer thickness and the standing electron wave therein. With the experiments of this work, published values could not only be completed and proved, but it could also be determined the time evolution of such a QWS. It came out that this QWS might only be filled by electrons, which are moving from the lower edge of the conduction band of the semiconductor to the silver and suffer cascading steps there. By means of the system silver on GaAs, and of the known fact that an excitation of electrons in GaAs with circularly polarised light of the energy 1.5eV does produce spin polarised electrons in the conduction band, it became possible to bring a contribution to the hot topic of spin injection. The main target of spin injection is the transfer of spin polarised electrons out of a ferromagnet into a semiconductor, in order to develop spin dependent switches and memories. It could be demonstrated here that spin polarised electrons from GaAs can move through the interface into silver, could be photoemitted from there and their spin was still being detectable. As a third investigation system, ultra-thin silver layers were deposited on the insulator MgO, which has a bandgap of 7.8eV. Also in this system, one could recognize a change in the relaxation time while reducing the dimension of the silver layer from thick to ultra-thin. Additionally, it came out an extreme large relaxation time at a layer thickness of 0.6 – 1.2nm. This time is an order of magnitude longer than at thick films, and this is a consequence of two factors: first, the reduction of the phase space due to the confined electron gas in the z-direction, and second, the slowlier thermalisation of the electron gas due to less accessible scattering partners.
Based on the framework of continuum mechanics two different concepts to formulate phenomenological anisotropic inelasticity are developed in a thermodynamically consistent manner. On the one hand, special emphasis is placed on the incorporation of structural tensors while on the other hand, fictitious configurations are introduced. Substantial parts of this work deal with the numerical treatment of the presented theory within the finite element method.
Different aspects of geomagnetic field modelling from satellite data are examined in the framework of modern multiscale approximation. The thesis is mostly concerned with wavelet techniques, i.e. multiscale methods based on certain classes of kernel functions which are able to realize a multiscale analysis of the funtion (data) space under consideration. It is thus possible to break up complicated functions like the geomagnetic field, electric current densities or geopotentials into different pieces and study these pieces separately. Based on a general approach to scalar and vectorial multiscale methods, topics include multiscale denoising, crustal field approximation and downward continuation, wavelet-parametrizations of the magnetic field in Mie-representation as well as multiscale-methods for the analysis of time-dependent spherical vector fields. For each subject the necessary theoretical framework is established and numerical applications examine and illustrate the practical aspects.
Contributions to the application of adaptive antennas and CDMA code pooling in the TD CDMA downlink
(2002)
TD (Time Division)-CDMA is one of the partial standards adopted by 3GPP (3rd Generation Partnership Project) for 3rd Generation (3G) mobile radio systems. An important issue when designing 3G mobile radio systems is the efficient use of the available frequency spectrum, that is the achievement of a spectrum efficiency as high as possible. It is well known that the spectrum efficiency can be enhanced by utilizing multi-element antennas instead of single-element antennas at the base station (BS). Concerning the uplink of TD- CDMA, the benefits achievable by multi-element BS antennas have been quantitatively studied to a satisfactory extent. However, corresponding studies for the downlink are still missing. This thesis has the goal to make contributions to fill this lack of information. For near-to-reality directional mobile radio scenarios TD-CDMA downlink utilizing multi-element antennas at the BS are investigated both on the system level and on the link level. The system level investigations show how the carrier-to-interference ratio can be improved by applying such antennas. As the result of the link level investigations, which rely on the detection scheme Joint Detection (JD), the improvement of the bit er- ror rate by utilizing multi-element antennas at the BS can be quantified. Concerning the link level of TD-CDMA, a number of improvements are proposed which allow considerable performance enhancement of TD-CDMA downlink in connection with multi-element BS antennas. These improvements include * the concept of partial joint detection (PJD), in which at each mobile station (MS) only a subset of the arriving CDMA signals including those being of interest to this MS are jointly detected, * a blind channel estimation algorithm, * CDMA code pooling, that is assigning more than one CDMA code to certain con- nections in order to offer these users higher data rates, * maximizing the Shannon transmission capacity by an interleaving concept termed CDMA code interleaving and by advantageously selecting the assignment of CDMA codes to mobile radio channels, * specific power control schemes, which tackle the problem of different transmission qualities of the CDMA codes. As a comprehensive illustration of the advantages achievable by multi-element BS anten- nas in the TD-CDMA downlink, quantitative results concerning the spectrum efficiency for different numbers of antenna elements at the BS conclude the thesis.