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The service-oriented architecture supports the dynamic assembly and runtime reconfiguration of complex open IT landscapes by means of runtime binding of service contracts, launching of new components and termination of outdated ones. Furthermore, the evolution of these IT landscapes is not restricted to exchanging components with other ones using the same service contracts, as new services contracts can be added as well. However, current approaches for modeling and verification of service-oriented architectures do not support these important capabilities to their full extend.In this report we present an extension of the current OMG proposal for service modeling with UML - SoaML - which overcomes these limitations. It permits modeling services and their service contracts at different levels of abstraction, provides a formal semantics for all modeling concepts, and enables verifying critical properties. Our compositional and incremental verification approach allows for complex properties including communication parameters and time and covers besides the dynamic binding of service contracts and the replacement of components also the evolution of the systems by means of new service contracts. The modeling as well as verification capabilities of the presented approach are demonstrated by means of a supply chain example and the verification results of a first prototype are shown.
This work presents mathematical and computational approaches to cover various aspects of metabolic network modelling, especially regarding the limited availability of detailed kinetic knowledge on reaction rates. It is shown that precise mathematical formulations of problems are needed i) to find appropriate and, if possible, efficient algorithms to solve them, and ii) to determine the quality of the found approximate solutions. Furthermore, some means are introduced to gain insights on dynamic properties of metabolic networks either directly from the network structure or by additionally incorporating steady-state information. Finally, an approach to identify key reactions in a metabolic networks is introduced, which helps to develop simple yet useful kinetic models. The rise of novel techniques renders genome sequencing increasingly fast and cheap. In the near future, this will allow to analyze biological networks not only for species but also for individuals. Hence, automatic reconstruction of metabolic networks provides itself as a means for evaluating this huge amount of experimental data. A mathematical formulation as an optimization problem is presented, taking into account existing knowledge and experimental data as well as the probabilistic predictions of various bioinformatical methods. The reconstructed networks are optimized for having large connected components of high accuracy, hence avoiding fragmentation into small isolated subnetworks. The usefulness of this formalism is exemplified on the reconstruction of the sucrose biosynthesis pathway in Chlamydomonas reinhardtii. The problem is shown to be computationally demanding and therefore necessitates efficient approximation algorithms. The problem of minimal nutrient requirements for genome-scale metabolic networks is analyzed. Given a metabolic network and a set of target metabolites, the inverse scope problem has as it objective determining a minimal set of metabolites that have to be provided in order to produce the target metabolites. These target metabolites might stem from experimental measurements and therefore are known to be produced by the metabolic network under study, or are given as the desired end-products of a biotechological application. The inverse scope problem is shown to be computationally hard to solve. However, I assume that the complexity strongly depends on the number of directed cycles within the metabolic network. This might guide the development of efficient approximation algorithms. Assuming mass-action kinetics, chemical reaction network theory (CRNT) allows for eliciting conclusions about multistability directly from the structure of metabolic networks. Although CRNT is based on mass-action kinetics originally, it is shown how to incorporate further reaction schemes by emulating molecular enzyme mechanisms. CRNT is used to compare several models of the Calvin cycle, which differ in size and level of abstraction. Definite results are obtained for small models, but the available set of theorems and algorithms provided by CRNT can not be applied to larger models due to the computational limitations of the currently available implementations of the provided algorithms. Given the stoichiometry of a metabolic network together with steady-state fluxes and concentrations, structural kinetic modelling allows to analyze the dynamic behavior of the metabolic network, even if the explicit rate equations are not known. In particular, this sampling approach is used to study the stabilizing effects of allosteric regulation in a model of human erythrocytes. Furthermore, the reactions of that model can be ranked according to their impact on stability of the steady state. The most important reactions in that respect are identified as hexokinase, phosphofructokinase and pyruvate kinase, which are known to be highly regulated and almost irreversible. Kinetic modelling approaches using standard rate equations are compared and evaluated against reference models for erythrocytes and hepatocytes. The results from this simplified kinetic models can simulate acceptably the temporal behavior for small changes around a given steady state, but fail to capture important characteristics for larger changes. The aforementioned approach to rank reactions according to their influence on stability is used to identify a small number of key reactions. These reactions are modelled in detail, including knowledge about allosteric regulation, while all other reactions were still described by simplified reaction rates. These so-called hybrid models can capture the characteristics of the reference models significantly better than the simplified models alone. The resulting hybrid models might serve as a good starting point for kinetic modelling of genome-scale metabolic networks, as they provide reasonable results in the absence of experimental data, regarding, for instance, allosteric regulations, for a vast majority of enzymatic reactions.
The business problem of having inefficient processes, imprecise process analyses, and simulations as well as non-transparent artificial neuronal network models can be overcome by an easy-to-use modeling concept. With the aim of developing a flexible and efficient approach to modeling, simulating, and optimizing processes, this paper proposes a flexible Concept of Neuronal Modeling (CoNM). The modeling concept, which is described by the modeling language designed and its mathematical formulation and is connected to a technical substantiation, is based on a collection of novel sub-artifacts. As these have been implemented as a computational model, the set of CoNM tools carries out novel kinds of Neuronal Process Modeling (NPM), Neuronal Process Simulations (NPS), and Neuronal Process Optimizations (NPO). The efficacy of the designed artifacts was demonstrated rigorously by means of six experiments and a simulator of real industrial production processes.
The scope of this study is to investigate the environmental change in the German part of the Elbe river basin, whereby the focus is on two water related problems: having too little water and having water of poor quality. The Elbe region is representative of humid to semi-humid landscapes in central Europe, where water availability during the summer season is the limiting factor for plant growth and crop yields, especially in the loess areas, where the annual precipitation is lower than 500 mm. It is most likely that water quantity problems will accelerate in future, because both the observed and the projected climate trend show an increase in temperature and a decrease in annual precipitation, especially in the summer. Another problem is nutrient pollution of rivers and lakes. In the early 1990s, the Elbe was one of the most heavily polluted rivers in Europe. Even though nutrient emissions from point sources have notably decreased in the basin due to reduction of industrial sources and introduction of new and improved sewage treatment facilities, the diffuse sources of pollution are still not sufficiently controlled. The investigations have been done using the eco-hydrological model SWIM (Soil and Water Integrated Model), which has been embedded in a model framework of climate and agro-economic models. A global scenario of climate and agro-economic change has been regionalized to generate transient climate forcing data and land use boundary conditions for the model. The model was used to transform the climate and land use changes into altered evapotranspiration, groundwater recharge, crop yields and river discharge, and to investigate the development of water quality in the river basin. Particular emphasis was given to assessing the significance of the impacts on the hydrology, taking into account in the analysis the inherent uncertainty of the regional climate change as well as the uncertainty in the results of the model. The average trend of the regional climate change scenario indicates a decrease in mean annual precipitation up to 2055 of about 1.5 %, but with high uncertainty (covering the range from -15.3 % to +14.8 %), and a less uncertain increase in temperature of approximately 1.4 K. The relatively small change in precipitation in conjunction with the change in temperature leads to severe impacts on groundwater recharge and river flow. Increasing temperature induces longer vegetation periods, and the seasonality of the flow regime changes towards longer low flow spells in summer. As a results the water availability will decrease on average of the scenario simulations by approximately 15 %. The increase in temperatures will improve the growth conditions for temperature limited crops like maize. The uncertainty of the climate trend is particularly high in regions where the change is the highest. The simulation results for the Nuthe subbasin of the Elbe indicate that retention processes in groundwater, wetlands and riparian zones have a high potential to reduce the nitrate concentrations of rivers and lakes in the basin, because they are located at the interface between catchment area and surface water bodies, where they are controlling the diffuse nutrient inputs. The relatively high retention of nitrate in the Nuthe basin is due to the long residence time of water in the subsurface (about 40 years), with good conditions for denitrification, and due to nitrate retention and plant uptake in wetlands and riparian zones. The concluding result of the study is that the natural environment and communities in parts of Central Europe will have considerably lower water resources under scenario conditions. The water quality will improve, but due to the long residence time of water and nutrients in the subsurface, this improvement will be slower in areas where the conditions for nutrient turn-over in the subsurface are poor.
Lake ecosystems across the globe have responded to climate warming of recent decades. However, correctly attributing observed changes to altered climatic conditions is complicated by multiple anthropogenic influences on lakes. This thesis contributes to a better understanding of climate impacts on freshwater phytoplankton, which forms the basis of the food chain and decisively influences water quality. The analyses were, for the most part, based on a long-term data set of physical, chemical and biological variables of a shallow, polymictic lake in north-eastern Germany (Müggelsee), which was subject to a simultaneous change in climate and trophic state during the past three decades. Data analysis included constructing a dynamic simulation model, implementing a genetic algorithm to parameterize models, and applying statistical techniques of classification tree and time-series analysis. Model results indicated that climatic factors and trophic state interactively determine the timing of the phytoplankton spring bloom (phenology) in shallow lakes. Under equally mild spring conditions, the phytoplankton spring bloom collapsed earlier under high than under low nutrient availability, due to a switch from a bottom-up driven to a top-down driven collapse. A novel approach to model phenology proved useful to assess the timings of population peaks in an artificially forced zooplankton-phytoplankton system. Mimicking climate warming by lengthening the growing period advanced algal blooms and consequently also peaks in zooplankton abundance. Investigating the reasons for the contrasting development of cyanobacteria during two recent summer heat wave events revealed that anomalously hot weather did not always, as often hypothesized, promote cyanobacteria in the nutrient-rich lake studied. The seasonal timing and duration of heat waves determined whether critical thresholds of thermal stratification, decisive for cyanobacterial bloom formation, were crossed. In addition, the temporal patterns of heat wave events influenced the summer abundance of some zooplankton species, which as predators may serve as a buffer by suppressing phytoplankton bloom formation. This thesis adds to the growing body of evidence that lake ecosystems have strongly responded to climatic changes of recent decades. It reaches beyond many previous studies of climate impacts on lakes by focusing on underlying mechanisms and explicitly considering multiple environmental changes. Key findings show that climate impacts are more severe in nutrient-rich than in nutrient-poor lakes. Hence, to develop lake management plans for the future, limnologists need to seek a comprehensive, mechanistic understanding of overlapping effects of the multi-faceted human footprint on aquatic ecosystems.
Die Projektierung und Abwicklung sowie die statische und dynamische Analyse von Geschäftsprozessen im Bereich des Verwaltens und Regierens auf kommunaler, Länder- wie auch Bundesebene mit Hilfe von Informations- und Kommunikationstechniken beschäftigen Politiker und Strategen für Informationstechnologie ebenso wie die Öffentlichkeit seit Langem.
Der hieraus entstandene Begriff E-Government wurde in der Folge aus den unterschiedlichsten technischen, politischen und semantischen Blickrichtungen beleuchtet.
Die vorliegende Arbeit konzentriert sich dabei auf zwei Schwerpunktthemen:
• Das erste Schwerpunktthema behandelt den Entwurf eines hierarchischen Architekturmodells, für welches sieben hierarchische Schichten identifiziert werden können. Diese erscheinen notwendig, aber auch hinreichend, um den allgemeinen Fall zu beschreiben.
Den Hintergrund hierfür liefert die langjährige Prozess- und Verwaltungserfahrung als Leiter der EDV-Abteilung der Stadtverwaltung Landshut, eine kreisfreie Stadt mit rund 69.000 Einwohnern im Nordosten von München. Sie steht als Repräsentant für viele Verwaltungsvorgänge in der Bundesrepublik Deutschland und ist dennoch als Analyseobjekt in der Gesamtkomplexität und Prozessquantität überschaubar.
Somit können aus der Analyse sämtlicher Kernabläufe statische und dynamische Strukturen extrahiert und abstrakt modelliert werden.
Die Schwerpunkte liegen in der Darstellung der vorhandenen Bedienabläufe in einer Kommune. Die Transformation der Bedienanforderung in einem hierarchischen System, die Darstellung der Kontroll- und der Operationszustände in allen Schichten wie auch die Strategie der Fehlererkennung und Fehlerbehebung schaffen eine transparente Basis für umfassende Restrukturierungen und Optimierungen.
Für die Modellierung wurde FMC-eCS eingesetzt, eine am Hasso-Plattner-Institut für Softwaresystemtechnik GmbH (HPI) im Fachgebiet Kommunikationssysteme entwickelte Methodik zur Modellierung zustandsdiskreter Systeme unter Berücksichtigung möglicher Inkonsistenzen (Betreuer: Prof. Dr.-Ing. Werner Zorn [ZW07a, ZW07b]).
• Das zweite Schwerpunktthema widmet sich der quantitativen Modellierung und Optimierung von E-Government-Bediensystemen, welche am Beispiel des Bürgerbüros der Stadt Landshut im Zeitraum 2008 bis 2015 durchgeführt wurden. Dies erfolgt auf Basis einer kontinuierlichen Betriebsdatenerfassung mit aufwendiger Vorverarbeitung zur Extrahierung mathematisch beschreibbarer Wahrscheinlichkeitsverteilungen.
Der hieraus entwickelte Dienstplan wurde hinsichtlich der erzielbaren Optimierungen im dauerhaften Echteinsatz verifiziert.
[ZW07a] Zorn, Werner: «FMC-QE A New Approach in Quantitative Modeling», Vortrag anlässlich: MSV'07- The 2007 International Conference on Modeling, Simulation and Visualization Methods WorldComp2007, Las Vegas, 28.6.2007.
[ZW07b] Zorn, Werner: «FMC-QE, A New Approach in Quantitative Modeling», Veröffentlichung, Hasso-Plattner-Institut für Softwaresystemtechnik an der Universität Potsdam, 28.6.2007.
Im Zuge der Covid-19 Pandemie werden zwei Werte täglich diskutiert: Die zuletzt gemeldete Zahl der neu Infizierten und die sogenannte Reproduktionsrate. Sie gibt wieder, wie viele weitere Menschen ein an Corona erkranktes Individuum im Durchschnitt ansteckt. Für die Schätzung dieses Wertes gibt es viele Möglichkeiten - auch das Robert Koch-Institut gibt in seinem täglichen Situationsbericht stets zwei R-Werte an: Einen 4-Tage-R-Wert und einen weniger schwankenden 7-Tage-R-Wert. Diese Arbeit soll eine weitere Möglichkeit vorstellen, einige Aspekte der Pandemie zu modellieren und die Reproduktionsrate zu schätzen.
In der ersten Hälfte der Arbeit werden die mathematischen Grundlagen vorgestellt, die man für die Modellierung benötigt. Hierbei wird davon ausgegangen, dass der Leser bereits ein Basisverständnis von stochastischen Prozessen hat. Im Abschnitt Grundlagen werden Verzweigungsprozesse mit einigen Beispielen eingeführt und die Ergebnisse aus diesem Themengebiet, die für diese Arbeit wichtig sind, präsentiert. Dabei gehen wir zuerst auf einfache Verzweigungsprozesse ein und erweitern diese dann auf Verzweigungsprozesse mit mehreren Typen. Um die Notation zu erleichtern, beschränken wir uns auf zwei Typen. Das Prinzip lässt sich aber auf eine beliebige Anzahl von Typen erweitern.
Vor allem soll die Wichtigkeit des Parameters λ herausgestellt werden. Dieser Wert kann als durchschnittliche Zahl von Nachfahren eines Individuums interpretiert werden und bestimmt die Dynamik des Prozesses über einen längeren Zeitraum. In der Anwendung auf die Pandemie hat der Parameter λ die gleiche Rolle wie die Reproduktionsrate R.
In der zweiten Hälfte dieser Arbeit stellen wir eine Anwendung der Theorie über Multitype Verzweigungsprozesse vor. Professor Yanev und seine Mitarbeiter modellieren in ihrer Veröffentlichung Branching stochastic processes as models of Covid-19 epidemic development die Ausbreitung des Corona Virus' über einen Verzweigungsprozess mit zwei Typen. Wir werden dieses Modell diskutieren und Schätzer daraus ableiten: Ziel ist es, die Reproduktionsrate zu ermitteln. Außerdem analysieren wir die Möglichkeiten, die Dunkelziffer (die Zahl nicht gemeldeter Krankheitsfälle) zu schätzen. Wir wenden die Schätzer auf die Zahlen von Deutschland an und werten diese schließlich aus.
The development of rural areas concerning food security, sustainability and social-economic stability is key issue to the globalized community. Regarding the current state of climatic change, especially semi-arid regions in uenced by monsoon or El Niño are prone to extreme weather events. Droughts, ooding, erosion, degradation of soils and water quality and deserti cation are some of the common impacts. State of the art in hydrologic environmental modeling is generally operating under a reductionist paradigm (Sivapalan 2005). Even an enormous quantity of process-oriented models exists, we fail in due reproduction of complexly interacting processes in their effective scale in the space-time-continuum, as they are described through deterministic small-scale process theories (e.g. Beven 2002). Yet large amounts of parameters - with partly doubtful physical expression - and input data are needed. In contradiction to that most soft information about patterns and organizing principles cannot be employed (Seibert and McDonnell 2002). For an analysis of possible strategies on the one hand towards integrated hydrologic modeling as decision support and on the other hand for sustainable land use development the 512 km2 large catchment of the Mod river in Jhabua, Madhya Pradesh, India has been chosen. It is characterized by a setting of common problems of peripheral rural semi-arid human-eco-systems with intensive agriculture, deforestation, droughts and general hardship for the people. Scarce data and missing gauges are adding to the requirements of data acquisition and process description. The study at hand presents a methodical framework to combine eld scale data analysis and remote sensing for the setup of a database focusing plausibility over strict data accuracy. The catena-based hydrologic model WASA (Güntner 2002) employes this database. It is expanded by a routine for crop development simulation after the de Wit approach (e.g. in Bouman et al. 1996). For its application as decision support system an agentbased land use algorithm is developed which decides on base of site speci cations and certain constraints (like maximum pro t or best local adaptation) about the cropping. The new model is employed to analyze (some) land use strategies. Not anticipated and a priori de ned scenarios will account for the realization of the model but the interactions within the system. This study points out possible approaches to enhance the situation in the catchment. It also approaches central questions of ways towards due integrated hydrological modeling on catchment scale for ungauged conditions and to overcome current paradigms.
Modelling and simulation of light propagation in non-aged and aged step-index polymer optical fibres
(2004)
This thesis discusses theoretical and practical aspects of modelling of light propagation in non-aged and aged step-index polymer optical fibres (POFs). Special attention has been paid in describing optical characteristics of non-ideal fibres, scattering and attenuation, and in combining application-oriented and theoretical approaches. The precedence has been given to practical issues, but much effort has been also spent on the theoretical analysis of basic mechanisms governing light propagation in cylindrical waveguides. As a result a practically usable general POF model based on the raytracing approach has been developed and implemented. A systematic numerical optimisation of its parameters has been performed to obtain the best fit between simulated and measured optical characteristics of numerous non-aged and aged fibre samples. The model was verified by providing good agreement, especially for the non-aged fibres. The relations found between aging time and optimal values of model parameters contribute to a better understanding of the aging mechanisms of POFs.
This thesis discusses theoretical and practical aspects of modelling of light propagation in non-aged and aged step-index polymer optical fibres (POFs). Special attention has been paid in describing optical characteristics of non-ideal fibres, scattering and attenuation, and in combining application-oriented and theoretical approaches. The precedence has been given to practical issues, but much effort has been also spent on the theoretical analysis of basic mechanisms governing light propagation in cylindrical waveguides.As a result a practically usable general POF model based on the raytracing approach has been developed and implemented. A systematic numerical optimisation of its parameters has been performed to obtain the best fit between simulated and measured optical characteristics of numerous non-aged and aged fibre samples. The model was verified by providing good agreement, especially for the non-aged fibres. The relations found between aging time and optimal values of model parameters contribute to a better understanding of the aging mechanisms of POFs.