Methodische Grundlagen zur Bewahrung und Wiederherstellung großräumig funktionsfähiger ökologischer Beziehungen in der räumlichen Umweltplanung

Mit der Verwirklichung ,Ökologischer Netzwerke‘ werden Hoffnungen zum Stopp des Verlustes der biologischen Vielfalt verknüpft. Sowohl auf gesamteuropäischer Ebene (Pan-European Ecological Network - PEEN) als auch in den einzelnen Staaten entstehen Pläne zum Aufbau von Verbundsystemen. Im föderalen Deutschland werden kleinmaßstäbliche Biotopverbundplanungen auf Landesebene aufgestellt; zum nationalen Biotopverbund bestehen erste Konzepte. Die vorliegende Arbeit ist auf diese überörtlichen, strategisch vorbereitenden Planungsebenen ausgerichtet. Ziele des Verbunds sind der Erhalt von Populationen insbesondere der gefährdeten Arten sowie die Ermöglichung von Ausbreitung und Wanderung. Aufgrund fehlender Datengrundlagen zu den Arten und Populationen ist es nicht ohne weiteres möglich, die Konzepte und Modelle der Populationsökologie in die überörtlichen Planungsebenen zu übertragen. Gemäß der o.g. Zielstellungen sollte sich aber die Planung von Verbundsystemen an den Ansprüchen der auf Verbund angewiesenen Arten orientieren. Ziel der Arbeit war die Entwicklung einer praktikablen GIS-gestützten Planungshilfe zur größtmöglichen Integration ökologischen Wissens unter der Bedingung eingeschränkter Informationsverfügbarkeit. Als Grundlagen dazu werden in Übersichtsform zunächst die globalen, europäisch-internationalen und nationalen Rahmenbedingungen und Anforderungen bezüglich des Aufbaus von Verbundsystemen zusammengestellt. Hier sind die Strategien zum PEEN hervorzuheben, die eine Integration ökologischer Inhalte insbesondere durch die Berücksichtigung räumlich-funktionaler Beziehungen fordern. Eine umfassende Analyse der landesweiten Biotopverbundplanungen der BRD zeigte die teilweise erheblichen Unterschiede zwischen den Länderplanungen auf, die es aktuell nicht ermöglichen, ein schlüssiges nationales Konzept zusammenzufügen. Nicht alle Länder haben landesweite Biotopverbundplanungen und Landeskonzepte, bei denen dem geplanten Verbund die Ansprüche von Arten zugrunde gelegt werden, gibt es nur ansatzweise. Weiterhin wurde eine zielgerichtete Eignungsprüfung bestehender GIS-basierter Modelle und Konzepte zum Verbund unter Berücksichtigung der regelmäßig in Deutschland verfügbaren Datengrundlagen durchgeführt. Da keine integrativen regelorientierten Ansätze vorhanden waren, wurde der vektorbasierte Algorithmus HABITAT-NET entwickelt. Er arbeitet mit ,Anspruchstypen‘ hinsichtlich des Habitatverbunds, die stellvertretend für unterschiedliche ökologische Gruppen von (Ziel-) Arten mit terrestrischer Ausbreitung stehen. Kombiniert wird die Fähigkeit zur Ausbreitung mit einer Grobtypisierung der Biotopbindung. Die wichtigsten Grundlagendaten bilden die jeweiligen (potenziellen) Habitate von Arten eines Anspruchstyps sowie die umgebende Landnutzung. Bei der Bildung von ,Lebensraumnetzwerken‘ (Teil I) werden gestufte ,Funktions- und Verbindungsräume‘ generiert, die zu einem räumlichen System verknüpft sind. Anschließend kann die aktuelle Zerschneidung der Netzwerke durch Verkehrstrassen aufgezeigt werden, um darauf aufbauend prioritäre Abschnitte zur Wiedervernetzung zu ermitteln (Teil II). Begleitend wird das Konzept der unzerschnittenen Funktionsräume (UFR) entworfen, mit dem die Indikation von Habitatzerschneidung auf Landschaftsebene möglich ist. Diskutiert werden schließlich die Eignung der Ergebnisse als kleinmaßstäblicher Zielrahmen, Tests zur Validierung, Vergleiche mit Verbundplanungen und verschiedene Setzungen im GIS-Algorithmus. Erläuterungen zu den Einsatzmöglichkeiten erfolgen beispielsweise für die Bereiche Biotopverbund- und Landschaftsplanung, Raumordnung, Strategische Umweltprüfung, Verkehrswegeplanung, Unterstützung des Konzeptes der Lebensraumkorridore, Kohärenz im Schutzgebietssystem NATURA 2000 und Aufbau von Umweltinformationssystemen. Schließlich wird ein Rück- und Ausblick mit der Formulierung des weiteren Forschungsbedarfs verknüpft.

Global Optimization Algorithms and their Application to Distributed Systems

In this report, we discuss the application of global optimization and Evolutionary Computation to distributed systems. We therefore selected and classified many publications, giving an insight into the wide variety of optimization problems which arise in distributed systems. Some interesting approaches from different areas will be discussed in greater detail with the use of illustrative examples.

Trend detection in folksonomies

As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.

Nitrogen and carbon dynamics in grassland soils and plants after application of digestate

A better understanding of effects after digestate application on plant community, soil microbial community as well as nutrient and carbon dynamics is crucial for a sustainable grassland management and the prevention of species and functional diversity loss. The specific research objectives of the thesis were: (i) to investigate effects after digestate application on grass species and soil microbial community, especially focussing on nitrogen dynamic in the plant-soil system and to examine the suitability of the digestate from the “integrated generation of solid fuel and biogas from biomass” (IFBB) system as fertilizer (Chapter 3). (ii) to investigate the relationship between plant community and functionality of soil microbial community of extensively managed meadows, taking into account temporal variations during the vegetation period and abiotic soil conditions (Chapter 4). (iii) to investigate the suitability of IFBB-concept implementation as grassland conservation measure for meadows and possible associated effects of IFBB digestate application on plant and soil microbial community as well as soil microbial substrate utilization and catabolic evenness (Chapter 5). Taken together the results indicate that the digestate generated during the IFBB process stands out from digestates of conventional whole crop digestion on the basis of higher nitrogen use efficiency and that it is useful for increasing harvestable biomass and the nitrogen content of the biomass, especially of L. perenne, which is a common species of intensively used grasslands. Further, a medium application rate of IFBB digestate (50% of nitrogen removed with harvested biomass, corresponding to 30 50 kg N ha-1 a-1) may be a possibility for conservation management of different meadows without changing the functional above- and belowground characteristic of the grasslands, thereby offering an ecologically worthwhile alternative to mulching. Overall, the soil microbial biomass and catabolic performance under planted soil was marginally affected by digestate application but rather by soil properties and partly by grassland species and legume occurrence. The investigated extensively managed meadows revealed a high soil catabolic evenness, which was resilient to medium IFBB application rate after a three-year period of application.

Investigation of Multiphase Power Converter using Integrated Coupled Inductor Regarding Electric Vehicle Application

The challenge of reducing carbon emission and achieving emission target until 2050, has become a key development strategy of energy distribution for each country. The automotive industries, as the important portion of implementing energy requirements, are making some related researches to meet energy requirements and customer requirements. For modern energy requirements, it should be clean, green and renewable. For customer requirements, it should be economic, reliable and long life time. Regarding increasing requirements on the market and enlarged customer quantity, EVs and PHEV are more and more important for automotive manufactures. Normally for EVs and PHEV there are two important key parts, which are battery package and power electronics composing of critical components. A rechargeable battery is a quite important element for achieving cost competitiveness, which is mainly used to story energy and provide continue energy to drive an electric motor. In order to recharge battery and drive the electric motor, power electronics group is an essential bridge to convert different energy types for both of them. In modern power electronics there are many different topologies such as non-isolated and isolated power converters which can be used to implement for charging battery. One of most used converter topology is multiphase interleaved power converter, pri- marily due to its prominent advantages, which is frequently employed to obtain optimal dynamic response, high effciency and compact converter size. Concerning its usage, many detailed investigations regarding topology, control strategy and devices have been done. In this thesis, the core research is to investigate some branched contents in term of issues analysis and optimization approaches of building magnetic component. This work starts with an introduction of reasons of developing EVs and PEHV and an overview of different possible topologies regarding specific application requirements. Because of less components, high reliability, high effciency and also no special safety requirement, non-isolated multiphase interleaved converter is selected as the basic research topology of founded W-charge project for investigating its advantages and potential branches on using optimized magnetic components. Following, all those proposed aspects and approaches are investigated and analyzed in details in order to verify constrains and advantages through using integrated coupled inductors. Furthermore, digital controller concept and a novel tapped-inductor topology is proposed for multiphase power converter and electric vehicle application.

An O(N) Algorithm for Three-Dimensional N-Body Simulations

We develop an algorithm that computes the gravitational potentials and forces on N point-masses interacting in three-dimensional space. The algorithm, based on analytical techniques developed by Rokhlin and Greengard, runs in order N time. In contrast to other fast N-body methods such as tree codes, which only approximate the interaction potentials and forces, this method is exact ?? computes the potentials and forces to within any prespecified tolerance up to machine precision. We present an implementation of the algorithm for a sequential machine. We numerically verify the algorithm, and compare its speed with that of an O(N2) direct force computation. We also describe a parallel version of the algorithm that runs on the Connection Machine in order 0(logN) time. We compare experimental results with those of the sequential implementation and discuss how to minimize communication overhead on the parallel machine.

On Convergence Properties of the EM Algorithm for Gaussian Mixtures

"Expectation-Maximization'' (EM) algorithm and gradient-based approaches for maximum likelihood learning of finite Gaussian mixtures. We show that the EM step in parameter space is obtained from the gradient via a projection matrix $P$, and we provide an explicit expression for the matrix. We then analyze the convergence of EM in terms of special properties of $P$ and provide new results analyzing the effect that $P$ has on the likelihood surface. Based on these mathematical results, we present a comparative discussion of the advantages and disadvantages of EM and other algorithms for the learning of Gaussian mixture models.

Hierarchical Mixtures of Experts and the EM Algorithm

We present a tree-structured architecture for supervised learning. The statistical model underlying the architecture is a hierarchical mixture model in which both the mixture coefficients and the mixture components are generalized linear models (GLIM's). Learning is treated as a maximum likelihood problem; in particular, we present an Expectation-Maximization (EM) algorithm for adjusting the parameters of the architecture. We also develop an on-line learning algorithm in which the parameters are updated incrementally. Comparative simulation results are presented in the robot dynamics domain.

An Equivalence Between Sparse Approximation and Support Vector Machines

In the first part of this paper we show a similarity between the principle of Structural Risk Minimization Principle (SRM) (Vapnik, 1982) and the idea of Sparse Approximation, as defined in (Chen, Donoho and Saunders, 1995) and Olshausen and Field (1996). Then we focus on two specific (approximate) implementations of SRM and Sparse Approximation, which have been used to solve the problem of function approximation. For SRM we consider the Support Vector Machine technique proposed by V. Vapnik and his team at AT&T Bell Labs, and for Sparse Approximation we consider a modification of the Basis Pursuit De-Noising algorithm proposed by Chen, Donoho and Saunders (1995). We show that, under certain conditions, these two techniques are equivalent: they give the same solution and they require the solution of the same quadratic programming problem.

A Conservative Front Tracking Algorithm

The discontinuities in the solutions of systems of conservation laws are widely considered as one of the difficulties in numerical simulation. A numerical method is proposed for solving these partial differential equations with discontinuities in the solution. The method is able to track these sharp discontinuities or interfaces while still fully maintain the conservation property. The motion of the front is obtained by solving a Riemann problem based on the state values at its both sides which are reconstructed by using weighted essentially non oscillatory (WENO) scheme. The propagation of the front is coupled with the evaluation of "dynamic" numerical fluxes. Some numerical tests in 1D and preliminary results in 2D are presented.

Performance-Driven Microfabrication-Oriented Methodology for MEMS Conceptual Design with Application in Microfluidic Device Design

Performance and manufacturability are two important issues that must be taken into account during MEMS design. Existing MEMS design models or systems follow a process-driven design paradigm, that is, design starts from the specification of process sequence or the customization of foundry-ready process template. There has been essentially no methodology or model that supports generic, high-level design synthesis for MEMS conceptual design. As a result, there lacks a basis for specifying the initial process sequences. To address this problem, this paper proposes a performance-driven, microfabrication-oriented methodology for MEMS conceptual design. A unified behaviour representation method is proposed which incorporates information of both physical interactions and chemical/biological/other reactions. Based on this method, a behavioural process based design synthesis model is proposed, which exploits multidisciplinary phenomena for design solutions, including both the structural components and their configuration for the MEMS device, as well as the necessary substances for the chemical/biological/other reactions. The model supports both forward and backward synthetic search for suitable phenomena. To ensure manufacturability, a strategy of using microfabrication-oriented phenomena as design knowledge is proposed, where the phenomena are developed from existing MEMS devices that have associated MEMS-specific microfabrication processes or foundry-ready process templates. To test the applicability of the proposed methodology, the paper also studies microfluidic device design and uses a micro-pump design for the case study.

Compositional hypotheses of subcompositional stability and specific perturbation change and their testing

In standard multivariate statistical analysis common hypotheses of interest concern changes in mean vectors and subvectors. In compositional data analysis it is now well established that compositional change is most readily described in terms of the simplicial operation of perturbation and that subcompositions replace the marginal concept of subvectors. To motivate the statistical developments of this paper we present two challenging compositional problems from food production processes. Against this background the relevance of perturbations and subcompositions can be clearly seen. Moreover we can identify a number of hypotheses of interest involving the specification of particular perturbations or differences between perturbations and also hypotheses of subcompositional stability. We identify the two problems as being the counterpart of the analysis of paired comparison or split plot experiments and of separate sample comparative experiments in the jargon of standard multivariate analysis. We then develop appropriate estimation and testing procedures for a complete lattice of relevant compositional hypotheses

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Use of decision trees in colour feature selection: application to object recognition in outdoor scenes

A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported

Proposal of a parallel architecture for a motion detection algorithm

This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed