Parallel Genetic Algorithm for Document Image Compression Optimization

This work proposes a parallel genetic algorithm for compressing scanned document images. A fitness function is designed with Hausdorff distance which determines the terminating condition. The algorithm helps to locate the text lines. A greater compression ratio has achieved with lesser distortion

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

GA-based Optimization of a Fourth-order Sigma-delta Modulator for WLAN

Over-sampling sigma-delta analogue-to-digital converters (ADCs) are one of the key building blocks of state of the art wireless transceivers. In the sigma-delta modulator design the scaling coefficients determine the overall signal-to-noise ratio. Therefore, selecting the optimum value of the coefficient is very important. To this end, this paper addresses the design of a fourthorder multi-bit sigma-delta modulator for Wireless Local Area Networks (WLAN) receiver with feed-forward path and the optimum coefficients are selected using genetic algorithm (GA)- based search method. In particular, the proposed converter makes use of low-distortion swing suppression SDM architecture which is highly suitable for low oversampling ratios to attain high linearity over a wide bandwidth. The focus of this paper is the identification of the best coefficients suitable for the proposed topology as well as the optimization of a set of system parameters in order to achieve the desired signal-to-noise ratio. GA-based search engine is a stochastic search method which can find the optimum solution within the given constraints.

Optimization of parameters of chemical spray pyrolysis technique to get n and p-type layers of SnS

SnS thin films were prepared using automated chemical spray pyrolysis (CSP) technique. Single-phase, p-type, stoichiometric, SnS films with direct band gap of 1.33 eV and having very high absorption coefficient (N105/cm) were deposited at substrate temperature of 375 °C. The role of substrate temperature in determining the optoelectronic and structural properties of SnS films was established and concentration ratios of anionic and cationic precursor solutions were optimized. n-type SnS samples were also prepared using CSP technique at the same substrate temperature of 375 °C, which facilitates sequential deposition of SnS homojunction. A comprehensive analysis of both types of films was done using x-ray diffraction, energy dispersive x-ray analysis, scanning electron microscopy, atomic force microscopy, optical absorption and electrical measurements. Deposition temperatures required for growth of other binary sulfide phases of tin such as SnS2, Sn2S3 were also determined

Optimization of Lignin Peroxidase, Manganese Peroxidase, and Lac Production from Ganoderma lucidum Under Solid State Fermentation of Pineapple Leaf

This study was undertaken to isolate ligninase-producing white-rot fungi for use in the extraction of fibre from pineapple leaf agriwaste. Fifteen fungal strains were isolated from dead tree trunks and leaf litter. Ligninolytic enzymes (lignin peroxidase (LiP), manganese peroxidase (MnP), and laccase (Lac)), were produced by solid-state fermentation (SSF) using pineapple leaves as the substrate. Of the isolated strains, the one showing maximum production of ligninolytic enzymes was identified to be Ganoderma lucidum by 18S ribotyping. Single parameter optimization and response surface methodology of different process variables were carried out for enzyme production. Incubation period, agitation, and Tween-80 were identified to be the most significant variables through Plackett-Burman design. These variables were further optimized by Box-Behnken design. The overall maximum yield of ligninolytic enzymes was achieved by experimental analysis under these optimal conditions. Quantitative lignin analysis of pineapple leaves by Klason lignin method showed significant degradation of lignin by Ganoderma lucidum under SSF

Marine yeast Candida MCCF 101 as feed supplement in aquaculture: nutritional quality, optimization of large scale production and evaluation of its protective effect on Koi carp from Aeromonas infection

Marine yeast have been regarded as safe and showing a beneficial impact on biotechnological process. It provides better nutritional and dietary values indicating their potential application as feed supplements in aquaculture. Brown et al. (1996) evaluated all the marine yeasts characterised with high protein content, carbohydrate, good amino acid composition and high levels of saturated fats. However, there is paucity of information on marine yeasts as feed supplements and no feed formulation has been found either in literature or in market supplemented with them. This statement supported by Zhenming et al. (2006) reported still a lack of feed composed of single cell protein (SCP) from marine yeasts with high content of protein and other nutrients. Recent research has shown that marine yeasts also have highly potential uses in food, feed, medical and biofuel industries as well as marine biotechnology (Chi et al., 2009; 2010). Sajeevan et al. (2006; 2009a) and Sarlin and Philip (2011) demonstrates that the marine yeasts Candida sake served as a high quality, inexpensive nutrient source and it had proven immunostimulatory properties for cultured shrimps. This strain has been made part of the culture collection of National Centre for Aquatic Animal Health, Cochin University of Science and Technology as Candida MCCF 101. Over the years marine yeasts have been gaining increased attention in animal feed industry due to their nutritional value and immune boosting property.Therefore, the present study was undertaken, and focused on the nutritional quality, optimization of large scale production and evaluation of its protective effect on Koi carp from Aeromonas infection

Tailoring Magnetic Properties of Co-Fe Thin Films by Topographical Modifications Using Thermal Annealing and Swift Heavy Ion Irradiation and Fabrication of Magnetoelectric Multilayers for Device Applications

Magnetism and magnetic materials have been playing a lead role in improving the quality of life. They are increasingly being used in a wide variety of applications ranging from compasses to modern technological devices. Metallic glasses occupy an important position among magnetic materials. They assume importance both from a scientific and an application point of view since they represent an amorphous form of condensed matter with significant deviation from thermodynamic equilibrium. Metallic glasses having good soft magnetic properties are widely used in tape recorder heads, cores of high-power transformers and metallic shields. Superconducting metallic glasses are being used to produce high magnetic fields and magnetic levitation effect. Upon heat treatment, they undergo structural relaxation leading to subtle rearrangements of constituent atoms. This leads to densification of amorphous phase and subsequent nanocrystallisation. The short-range structural relaxation phenomenon gives rise to significant variations in physical, mechanical and magnetic properties. Magnetic amorphous alloys of Co-Fe exhibit excellent soft magnetic properties which make them promising candidates for applications as transformer cores, sensors, and actuators. With the advent of microminiaturization and nanotechnology, thin film forms of these alloys are sought after for soft under layers for perpendicular recording media. The thin film forms of these alloys can also be used for fabrication of magnetic micro electro mechanical systems (magnetic MEMS). In bulk, they are drawn in the form of ribbons, often by melt spinning. The main constituents of these alloys are Co, Fe, Ni, Si, Mo and B. Mo acts as the grain growth inhibitor and Si and B facilitate the amorphous nature in the alloy structure. The ferromagnetic phases such as Co-Fe and Fe-Ni in the alloy composition determine the soft magnetic properties. The grain correlation length, a measure of the grain size, often determines the soft magnetic properties of these alloys. Amorphous alloys could be restructured in to their nanocrystalline counterparts by different techniques. The structure of nanocrystalline material consists of nanosized ferromagnetic crystallites embedded in an amorphous matrix. When the amorphous phase is ferromagnetic, they facilitate exchange coupling between nanocrystallites. This exchange coupling results in the vanishing of magnetocrystalline anisotropy which improves the soft magnetic properties. From a fundamental perspective, exchange correlation length and grain size are the deciding factors that determine the magnetic properties of these nanocrystalline materials. In thin films, surfaces and interfaces predominantly decides the bulk property and hence tailoring the surface roughness and morphology of the film could result in modified magnetic properties. Surface modifications can be achieved by thermal annealing at various temperatures. Ion irradiation is an alternative tool to modify the surface/structural properties. The surface evolution of a thin film under swift heavy ion (SHI) irradiation is an outcome of different competing mechanism. It could be sputtering induced by SHI followed by surface roughening process and the material transport induced smoothening process. The impingement of ions with different fluence on the alloy is bound to produce systematic microstructural changes and this could effectively be used for tailoring magnetic parameters namely coercivity, saturation magnetization, magnetic permeability and remanence of these materials. Swift heavy ion irradiation is a novel and an ingenious tool for surface modification which eventually will lead to changes in the bulk as well as surface magnetic property. SHI has been widely used as a method for the creation of latent tracks in thin films. The bombardment of SHI modifies the surfaces or interfaces or creates defects, which induces strain in the film. These changes will have profound influence on the magnetic anisotropy and the magnetisation of the specimen. Thus inducing structural and morphological changes by thermal annealing and swift heavy ion irradiation, which in turn induce changes in the magnetic properties of these alloys, is one of the motivation of this study. Multiferroic and magneto-electrics is a class of functional materials with wide application potential and are of great interest to material scientists and engineers. Magnetoelectric materials combine both magnetic as well as ferroelectric properties in a single specimen. The dielectric properties of such materials can be controlled by the application of an external magnetic field and the magnetic properties by an electric field. Composites with magnetic and piezo/ferroelectric individual phases are found to have strong magnetoelectric (ME) response at room temperature and hence are preferred to single phasic multiferroic materials. Currently research in this class of materials is towards optimization of the ME coupling by tailoring the piezoelectric and magnetostrictive properties of the two individual components of ME composites. The magnetoelectric coupling constant (MECC) (_ ME) is the parameter that decides the extent of interdependence of magnetic and electric response of the composite structure. Extensive investigates have been carried out in bulk composites possessing on giant ME coupling. These materials are fabricated by either gluing the individual components to each other or mixing the magnetic material to a piezoelectric matrix. The most extensively investigated material combinations are Lead Zirconate Titanate (PZT) or Lead Magnesium Niobate-Lead Titanate (PMNPT) as the piezoelectric, and Terfenol-D as the magnetostrictive phase and the coupling is measured in different configurations like transverse, longitudinal and inplane longitudinal. Fabrication of a lead free multiferroic composite with a strong ME response is the need of the hour from a device application point of view. The multilayer structure is expected to be far superior to bulk composites in terms of ME coupling since the piezoelectric (PE) layer can easily be poled electrically to enhance the piezoelectricity and hence the ME effect. The giant magnetostriction reported in the Co-Fe thin films makes it an ideal candidate for the ferromagnetic component and BaTiO3 which is a well known ferroelectric material with improved piezoelectric properties as the ferroelectric component. The multilayer structure of BaTiO3- CoFe- BaTiO3 is an ideal system to understand the underlying fundamental physics behind the ME coupling mechanism. Giant magnetoelectric coupling coefficient is anticipated for these multilayer structures of BaTiO3-CoFe-BaTiO3. This makes it an ideal candidate for cantilever applications in magnetic MEMS/NEMS devices. SrTiO3 is an incipient ferroelectric material which is paraelectric up to 0K in its pure unstressed form. Recently few studies showed that ferroelectricity can be induced by application of stress or by chemical / isotopic substitution. The search for room temperature magnetoelectric coupling in SrTiO3-CoFe-SrTiO3 multilayer structures is of fundamental interest. Yet another motivation of the present work is to fabricate multilayer structures consisting of CoFe/ BaTiO3 and CoFe/ SrTiO3 for possible giant ME coupling coefficient (MECC) values. These are lead free and hence promising candidates for MEMS applications. The elucidation of mechanism for the giant MECC also will be the part of the objective of this investigation.

BIOPROCESS OPTIMIZATION AND CHARACTERIZATION OF PHYTASE FROM AN ENVIRONMENTAL ISOLATE BACILLUS MCCB 242

A study was undertaken to isolate phytase producers from environment and to segregate the most highly efficient phytase producer and to develop a bioprocess technology for commercial application. During this process, a potential phytase producer Bacillus MCCB 242 was isolated and characterized phenotypically and genotypically. Subsequently, phytase production was optimized, the enzyme purified and characterized and an appropriate downstream process also could be standardized.Precisely, through this work an environmental isolate Bacillus MCCB 242 could be brought out as phytase producer for commercial application. The enzyme production could be optimized and characterized, and an appropriate downstream process standardized. Cytotoxicity studies revealed the enzyme safe for feed application, especially in fish.

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.

Auf Basis umfangreicher Messdatensätze experimentell und numerisch validierte Regeln zur optimierten Auslegung von Luft-Erdwärmetauschern

Ein Luft-Erdwärmetauscher (L-EWT) kommt wegen seines niedrigen Energiebedarfs und möglicher guter Aufwandszahlen als umweltfreundliche Versorgungskomponente für Gebäude in Betracht. Dabei ist besonders vorteilhaft, dass ein L-EWT die Umgebungsluft je nach Jahreszeit vorwärmen oder auch kühlen kann. Dem zufolge sind L-EWT zur Energieeinsparung nicht nur für den Wohnhausbau interessant, sondern auch dort, wo immer noch große Mengen an fossiler Energie für die Raumkühlung benötigt werden, im Büro- und Produktionsgebäudesektor. Der Einsatzbereich eines L-EWT liegt zwischen Volumenströmen von 100 m3/h und mehreren 100.000 m3/h. Aus dieser Bandbreite und den instationären Randbedingungen entstehen erhebliche Schwierigkeiten, allgemeingültige Aussagen über das zu erwartende thermische Systemverhalten aus der Vielzahl möglicher Konstruktionsvarianten zu treffen. Hauptziel dieser Arbeit ist es, auf Basis umfangreicher, mehrjähriger Messungen an einer eigens konzipierten Testanlage und eines speziell angepassten numerischen Rechenmodells, Kennzahlen zu entwickeln, die es ermöglichen, die Betriebseigenschaften eines L-EWT im Planungsalltag zu bestimmen und ein technisch, ökologisch wie ökonomisch effizientes System zu identifizieren. Es werden die Kennzahlen elewt (Aufwandszahl), QV (Netto-Volumenleistung), ME (Meterertrag), sowie die Kombination aus v (Strömungsgeschwindigkeit) und VL (Metervolumenstrom) definiert, die zu wichtigen Informationen führen, mit denen die Qualität von Systemvarianten in der Planungsphase bewertet werden können. Weiterführende Erkenntnisse über die genauere Abschätzung von Bodenkennwerten werden dargestellt. Die hygienische Situation der durch den L-EWT transportierten Luft wird für die warme Jahreszeit, aufgrund auftretender Tauwasserbildung, beschrieben. Aus diesem Grund werden alle relevanten lufthygienischen Parameter in mehreren aufwendigen Messkampagnen erfasst und auf pathogene Wirkungen überprüft. Es wird über Sensitivitätsanalysen gezeigt, welche Fehler bei Annahme falscher Randbedingungen eintreten. Weiterhin werden in dieser Arbeit wesentliche, grundsätzliche Erkenntnisse aufbereitet, die sich aus der Betriebsbeobachtung und der Auswertung der umfangreich vorliegenden Messdaten mehrerer Anlagen ergeben haben und für die praktische Umsetzung und die Betriebsführung bedeutend sind. Hinweise zu Materialeigenschaften und zur Systemwirtschaftlichkeit sind detailliert aufgeführt.

Micro-electromechanical structural design and optimization of vertical cavity photonic devices with wide continuous tuning

Diese Arbeit umfaßt das elektromechanische Design und die Designoptimierung von weit durchstimmbaren optischen multimembranbasierten Bauelementen, mit vertikal orientierten Kavitäten, basierend auf der Finiten Element Methode (FEM). Ein multimembran InP/Luft Fabry-Pérot optischer Filter wird dargestellt und umfassend analysiert. In dieser Arbeit wird ein systematisches strukturelles Designverfahren dargestellt. Genaue analytische elektromechanischer Modelle für die Bauelemente sind abgeleitet worden. Diese können unschätzbare Werkzeuge sein, um am Anfang der Designphase schnell einen klaren Einblick zur Verfügung zu stellen. Mittels des FEM Programms ist der durch die nicht-lineare Verspannung hervorgerufene versteifende Effekt nachgeforscht und sein Effekt auf die Verlängerung der mechanischen Durchstimmungsstrecke der Bauelemente demonstriert worden. Interessant war auch die Beobachtung, dass die normierte Relation zwischen Ablenkung und Spannung ein unveränderliches Profil hat. Die Deformation der Membranflächen der in dieser Arbeit dargestellten Bauelementformen erwies sich als ein unerwünschter, jedoch manchmal unvermeidbarer Effekt. Es zeigt sich aber, dass die Wahl der Größe der strukturellen Dimensionen den Grad der Membrandeformation im Falle der Aktuation beeinflusst. Diese Arbeit stellt ein elektromechanisches in FEMLAB implementierte quasi-3D Modell, das allgemein für die Modellierung dünner Strukturen angewendet werden kann, dar; und zwar indem man diese als 2D-Objekte betrachtet und die dritte Dimension als eine konstante Größe (z.B. die Schichtdicke) oder eine Größe, welche eine mathematische Funktion ist, annimmt. Diese Annahme verringert drastisch die Berechnungszeit sowie den erforderlichen Arbeitsspeicherbedarf. Weiter ist es für die Nachforschung des Effekts der Skalierung der durchstimmbaren Bauelemente verwendet worden. Eine neuartige Skalierungstechnik wurde abgeleitet und verwendet. Die Ergebnisse belegen, dass das daraus resultierende, skalierte Bauelement fast genau die gleiche mechanische Durchstimmung wie das unskalierte zeigt. Die Einbeziehung des Einflusses von axialen Verspannungen und Gradientenverspannungen in die Berechnungen erforderte die Änderung der Standardimplementierung des 3D Mechanikberechnungsmodus, der mit der benutzten FEM Software geliefert wurde. Die Ergebnisse dieser Studie zeigen einen großen Einfluss der Verspannung auf die Durchstimmungseigenschaften der untersuchten Bauelemente. Ferner stimmten die Ergebnisse der theoretischen Modellrechnung mit den experimentellen Resultaten sehr gut überein.

Design, implementation and application of a generic framework for integrated regional land-use modeling

Land use is a crucial link between human activities and the natural environment and one of the main driving forces of global environmental change. Large parts of the terrestrial land surface are used for agriculture, forestry, settlements and infrastructure. Given the importance of land use, it is essential to understand the multitude of influential factors and resulting land use patterns. An essential methodology to study and quantify such interactions is provided by the adoption of land-use models. By the application of land-use models, it is possible to analyze the complex structure of linkages and feedbacks and to also determine the relevance of driving forces. Modeling land use and land use changes has a long-term tradition. In particular on the regional scale, a variety of models for different regions and research questions has been created. Modeling capabilities grow with steady advances in computer technology, which on the one hand are driven by increasing computing power on the other hand by new methods in software development, e.g. object- and component-oriented architectures. In this thesis, SITE (Simulation of Terrestrial Environments), a novel framework for integrated regional sland-use modeling, will be introduced and discussed. Particular features of SITE are the notably extended capability to integrate models and the strict separation of application and implementation. These features enable efficient development, test and usage of integrated land-use models. On its system side, SITE provides generic data structures (grid, grid cells, attributes etc.) and takes over the responsibility for their administration. By means of a scripting language (Python) that has been extended by language features specific for land-use modeling, these data structures can be utilized and manipulated by modeling applications. The scripting language interpreter is embedded in SITE. The integration of sub models can be achieved via the scripting language or by usage of a generic interface provided by SITE. Furthermore, functionalities important for land-use modeling like model calibration, model tests and analysis support of simulation results have been integrated into the generic framework. During the implementation of SITE, specific emphasis was laid on expandability, maintainability and usability. Along with the modeling framework a land use model for the analysis of the stability of tropical rainforest margins was developed in the context of the collaborative research project STORMA (SFB 552). In a research area in Central Sulawesi, Indonesia, socio-environmental impacts of land-use changes were examined. SITE was used to simulate land-use dynamics in the historical period of 1981 to 2002. Analogous to that, a scenario that did not consider migration in the population dynamics, was analyzed. For the calculation of crop yields and trace gas emissions, the DAYCENT agro-ecosystem model was integrated. In this case study, it could be shown that land-use changes in the Indonesian research area could mainly be characterized by the expansion of agricultural areas at the expense of natural forest. For this reason, the situation had to be interpreted as unsustainable even though increased agricultural use implied economic improvements and higher farmers' incomes. Due to the importance of model calibration, it was explicitly addressed in the SITE architecture through the introduction of a specific component. The calibration functionality can be used by all SITE applications and enables largely automated model calibration. Calibration in SITE is understood as a process that finds an optimal or at least adequate solution for a set of arbitrarily selectable model parameters with respect to an objective function. In SITE, an objective function typically is a map comparison algorithm capable of comparing a simulation result to a reference map. Several map optimization and map comparison methodologies are available and can be combined. The STORMA land-use model was calibrated using a genetic algorithm for optimization and the figure of merit map comparison measure as objective function. The time period for the calibration ranged from 1981 to 2002. For this period, respective reference land-use maps were compiled. It could be shown, that an efficient automated model calibration with SITE is possible. Nevertheless, the selection of the calibration parameters required detailed knowledge about the underlying land-use model and cannot be automated. In another case study decreases in crop yields and resulting losses in income from coffee cultivation were analyzed and quantified under the assumption of four different deforestation scenarios. For this task, an empirical model, describing the dependence of bee pollination and resulting coffee fruit set from the distance to the closest natural forest, was integrated. Land-use simulations showed, that depending on the magnitude and location of ongoing forest conversion, pollination services are expected to decline continuously. This results in a reduction of coffee yields of up to 18% and a loss of net revenues per hectare of up to 14%. However, the study also showed that ecological and economic values can be preserved if patches of natural vegetation are conservated in the agricultural landscape. -----------------------------------------------------------------------

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.

Theoretical study of magnetism, structure and chemical order in transition-metal alloy clusters

Research on transition-metal nanoalloy clusters composed of a few atoms is fascinating by their unusual properties due to the interplay among the structure, chemical order and magnetism. Such nanoalloy clusters, can be used to construct nanometer devices for technological applications by manipulating their remarkable magnetic, chemical and optical properties. Determining the nanoscopic features exhibited by the magnetic alloy clusters signifies the need for a systematic global and local exploration of their potential-energy surface in order to identify all the relevant energetically low-lying magnetic isomers. In this thesis the sampling of the potential-energy surface has been performed by employing the state-of-the-art spin-polarized density-functional theory in combination with graph theory and the basin-hopping global optimization techniques. This combination is vital for a quantitative analysis of the quantum mechanical energetics. The first approach, i.e., spin-polarized density-functional theory together with the graph theory method, is applied to study the Fe$_m$Rh$_n$ and Co$_m$Pd$_n$ clusters having $N = m+n \leq 8$ atoms. We carried out a thorough and systematic sampling of the potential-energy surface by taking into account all possible initial cluster topologies, all different distributions of the two kinds of atoms within the cluster, the entire concentration range between the pure limits, and different initial magnetic configurations such as ferro- and anti-ferromagnetic coupling. The remarkable magnetic properties shown by FeRh and CoPd nanoclusters are attributed to the extremely reduced coordination number together with the charge transfer from 3$d$ to 4$d$ elements. The second approach, i.e., spin-polarized density-functional theory together with the basin-hopping method is applied to study the small Fe$_6$, Fe$_3$Rh$_3$ and Rh$_6$ and the larger Fe$_{13}$, Fe$_6$Rh$_7$ and Rh$_{13}$ clusters as illustrative benchmark systems. This method is able to identify the true ground-state structures of Fe$_6$ and Fe$_3$Rh$_3$ which were not obtained by using the first approach. However, both approaches predict a similar cluster for the ground-state of Rh$_6$. Moreover, the computational time taken by this approach is found to be significantly lower than the first approach. The ground-state structure of Fe$_{13}$ cluster is found to be an icosahedral structure, whereas Rh$_{13}$ and Fe$_6$Rh$_7$ isomers relax into cage-like and layered-like structures, respectively. All the clusters display a remarkable variety of structural and magnetic behaviors. It is observed that the isomers having similar shape with small distortion with respect to each other can exhibit quite different magnetic moments. This has been interpreted as a probable artifact of spin-rotational symmetry breaking introduced by the spin-polarized GGA. The possibility of combining the spin-polarized density-functional theory with some other global optimization techniques such as minima-hopping method could be the next step in this direction. This combination is expected to be an ideal sampling approach having the advantage of avoiding efficiently the search over irrelevant regions of the potential energy surface.

Simulative Risikoanalyse von Biomethanprojekten

Im Zuge der Novellierung der Gasnetzzugangsverordnung sowie des Erneuerbare-Energien-Gesetzes entwickelte sich die Einspeisung von Biomethan in das Erdgasnetz als alternative Investitionsmöglichkeit der Erneuerbare-Energien-Branche. Als problematisch erweist sich dabei die Identifikation und Strukturierung einzelner Risikofaktoren zu einem Risikobereich, sowie die anschließende Quantifizierung dieser Risikofaktoren innerhalb eines Risikoportfolios. Darüber hinaus besteht die Schwierigkeit, diese Risikofaktoren in einem cashflowbasierten und den Ansprüchen der Investoren gewachsenem Risikomodell abzubilden. Zusätzlich müssen dabei Wechselwirkungen zwischen einzelnen Risikofaktoren berücksichtigt werden. Aus diesem Grund verfolgt die Dissertation das Ziel, die Risikosituation eines Biomethanprojektes anhand aggregierter und isolierter Risikosimulationen zu analysieren. Im Rahmen einer Diskussion werden Strategien und Instrumente zur Risikosteuerung angesprochen sowie die Implementierungsfähigkeit des Risikomodells in das Risikomanagementsystem von Investoren. Die Risikomaße zur Beschreibung der Risikoauswirkung betrachten die Shortfälle einer Verteilung. Dabei beziehen sich diese auf die geplanten Ausschüttungen sowie interne Verzinsungsansprüche der Investoren und die von Kreditinstituten geforderte minimale Schuldendienstdeckungsrate. Im Hinblick auf die Risikotragfähigkeit werden liquiditätsorientierte Kennzahlen hinzugezogen. Investoren interessieren sich vor dem Hintergrund einer gezielten Risikosteuerung hauptsächlich für den gefahrvollsten Risikobereich und innerhalb dessen für den Risikofaktor, der die größten Risikoauswirkungen hervorruft. Zudem spielt der Zeitpunkt maximaler Risikoauswirkung eine große Rolle. Als Kernaussage dieser Arbeit wird festgestellt, dass in den meisten Fällen die Aussagefähigkeit aggregierter Risikosimulationen durch Überlagerungseffekte negativ beeinträchtigt wird. Erst durch isoliert durchgeführte Risikoanalysen können diese Effekte eliminiert werden. Besonders auffällig gestalten sich dabei die Ergebnisse der isoliert durchgeführten Risikoanalyse des Risikobereichs »Politik«. So verursacht dieser im Vergleich zu den übrigen Risikobereichen, wie »Infrastruktur«, »Rohstoffe«, »Absatzmarkt« und »Finanzmarkt«, die geringsten Wahrscheinlichkeiten avisierte Planwerte der Investoren zu unterschreiten. Kommt es jedoch zu einer solchen Planwert-Unterschreitung, nehmen die damit verbundenen Risikoauswirkungen eine überraschende Position im Risikoranking der Investoren ein. Hinsichtlich der Aussagefähigkeit des Risikomodells wird deutlich, dass spezifische Risikosichtweisen der Investoren ausschlaggebend dafür sind, welche Strategien und Instrumente zur Risikosenkung umgesetzt werden. Darüber hinaus wird festgestellt, dass die Grenzen des Risikomodells in der Validität der Expertenmeinungen und dem Auffinden einer Optimallösung zu suchen sind.