Preparation and characterization of micro and nano fiber reinforced natural rubber composites by latex stage processing

Use of short fibers as reinforcing fillers in rubber composites is on an increasing trend. They are popular due to the possibility of obtaining anisotropic properties, ease of processing and economy. In the preparation of these composites short fibers are incorporated on two roll mixing mills or in internal mixers. This is a high energy intensive time consuming process. This calls for developing less energy intensive and less time consuming processes for incorporation and distribution of short fibers in the rubber matrix. One method for this is to incorporate fibers in the latex stage. The present study is primarily to optimize the preparation of short fiber- natural rubber composite by latex stage compounding and to evaluate the resulting composites in terms of mechanical, dynamic mechanical and thermal properties. A synthetic fiber (Nylon) and a natural fiber (Coir) are used to evaluate the advantages of the processing through latex stage. To extract the full reinforcing potential of the coir fibers the macro fibers are converted to micro fibers through chemical and mechanical means. The thesis is presented in 7 chapters

Investigations on Nonlinear and Radiative Properties of Certain Phatonic Materials

Light in its physical and philosophical sense has captured the imagination of human mind right from the dawn of civilization. The invention of lasers in the 60’s caused a renaissance in the field of optics. This intense, monochromatic, highly directional radiation created new frontiers in science and technology. The strong oscillating electric field of laser radiation creates a. polarisation response that is nonlinear in character in the medium through which it passes and the medium acts as a new source of optical field with alternate properties. It was in this context, that the field of optoelectronics which encompasses the generation, modulation, transmission etc. of optical radiation has gained tremendous importance. Organic molecules and polymeric systems have emerged as a class of promising materials of optoelectronics because they offer the flexibility, both at the molecular and bulk levels, to optimize the nonlinearity and other suitable properties for device applications. Organic nonlinear optical media, which yield large third-order nonlinearities, have been widely studied to develop optical devices like high speed switches, optical limiters etc. Transparent polymeric materials have found one of their most promising applicationsin lasers, in which they can be used as active elements with suitable laser dyes doped in it. The solid-matrix dye lasers make possible combination of the advantages of solid state lasers with the possibility of tuning the radiation over a broad spectral range. The polymeric matrices impregnated with organic dyes have not yet widely used because of the low resistance of the polymeric matrices to laser damage, their low dye photostability, and low dye stability over longer time of operation and storage. In this thesis we investigate the nonlinear and radiative properties of certain organic materials and doped polymeric matrix and their possible role in device development

Rapid and Proactive Approach on Exploration of Database Vulnerabilities

In today's complicated computing environment, managing data has become the primary concern of all industries. Information security is the greatest challenge and it has become essential to secure the enterprise system resources like the databases and the operating systems from the attacks of the unknown outsiders. Our approach plays a major role in detecting and managing vulnerabilities in complex computing systems. It allows enterprises to assess two primary tiers through a single interface as a vulnerability scanner tool which provides a secure system which is also compatible with the security compliance of the industry. It provides an overall view of the vulnerabilities in the database, by automatically scanning them with minimum overhead. It gives a detailed view of the risks involved and their corresponding ratings. Based on these priorities, an appropriate mitigation process can be implemented to ensure a secured system. The results show that our approach could effectively optimize the time and cost involved when compared to the existing systems

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

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.

Statistical evaluation of texture analysis from the biocrystallization method

The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

Genetic Programming meets Model-Driven Development

Genetic programming is known to provide good solutions for many problems like the evolution of network protocols and distributed algorithms. In such cases it is most likely a hardwired module of a design framework that assists the engineer to optimize specific aspects of the system to be developed. It provides its results in a fixed format through an internal interface. In this paper we show how the utility of genetic programming can be increased remarkably by isolating it as a component and integrating it into the model-driven software development process. Our genetic programming framework produces XMI-encoded UML models that can easily be loaded into widely available modeling tools which in turn posses code generation as well as additional analysis and test capabilities. We use the evolution of a distributed election algorithm as an example to illustrate how genetic programming can be combined with model-driven development. This example clearly illustrates the advantages of our approach – the generation of source code in different programming languages.

The Surface Plasmon Resonance of Supported Noble Metal Nanoparticles: Characterization, Laser Tailoring, and SERS Application

This work deals with the optical properties of supported noble metal nanoparticles, which are dominated by the so-called Mie resonance and are strongly dependent on the particles’ morphology. For this reason, characterization and control of the dimension of these systems are desired in order to optimize their applications. Gold and silver nanoparticles have been produced on dielectric supports like quartz glass, sapphire and rutile, by the technique of vapor deposition under ultra-high vacuum conditions. During the preparation, coalescence is observed as an important mechanism of cluster growth. The particles have been studied in situ by optical transmission spectroscopy and ex situ by atomic force microscopy. It is shown that the morphology of the aggregates can be regarded as oblate spheroids. A theoretical treatment of their optical properties, based on the quasistatic approximation, and its combination with results obtained by atomic force microscopy give a detailed characterization of the nanoparticles. This method has been compared with transmission electron microscopy and the results are in excellent agreement. Tailoring of the clusters’ dimensions by irradiation with nanosecond-pulsed laser light has been investigated. Selected particles are heated within the ensemble by excitation of the Mie resonance under irradiation with a tunable laser source. Laser-induced coalescence prevents strongly tailoring of the particle size. Nevertheless, control of the particle shape is possible. Laser-tailored ensembles have been tested as substrates for surface-enhanced Raman spectroscopy (SERS), leading to an improvement of the results. Moreover, they constitute reproducible, robust and tunable SERS-substrates with a high potential for specific applications, in the present case focused on environmental protection. Thereby, these SERS-substrates are ideally suited for routine measurements.

Autonomes Performance-Management in dienstorientierten Architekturen

Die Bedeutung des Dienstgüte-Managements (SLM) im Bereich von Unternehmensanwendungen steigt mit der zunehmenden Kritikalität von IT-gestützten Prozessen für den Erfolg einzelner Unternehmen. Traditionell werden zur Implementierung eines wirksamen SLMs Monitoringprozesse in hierarchischen Managementumgebungen etabliert, die einen Administrator bei der notwendigen Rekonfiguration von Systemen unterstützen. Auf aktuelle, hochdynamische Softwarearchitekturen sind diese hierarchischen Ansätze jedoch nur sehr eingeschränkt anwendbar. Ein Beispiel dafür sind dienstorientierte Architekturen (SOA), bei denen die Geschäftsfunktionalität durch das Zusammenspiel einzelner, voneinander unabhängiger Dienste auf Basis deskriptiver Workflow-Beschreibungen modelliert wird. Dadurch ergibt sich eine hohe Laufzeitdynamik der gesamten Architektur. Für das SLM ist insbesondere die dezentrale Struktur einer SOA mit unterschiedlichen administrativen Zuständigkeiten für einzelne Teilsysteme problematisch, da regelnde Eingriffe zum einen durch die Kapselung der Implementierung einzelner Dienste und zum anderen durch das Fehlen einer zentralen Kontrollinstanz nur sehr eingeschränkt möglich sind. Die vorliegende Arbeit definiert die Architektur eines SLM-Systems für SOA-Umgebungen, in dem autonome Management-Komponenten kooperieren, um übergeordnete Dienstgüteziele zu erfüllen: Mithilfe von Selbst-Management-Technologien wird zunächst eine Automatisierung des Dienstgüte-Managements auf Ebene einzelner Dienste erreicht. Die autonomen Management-Komponenten dieser Dienste können dann mithilfe von Selbstorganisationsmechanismen übergreifende Ziele zur Optimierung von Dienstgüteverhalten und Ressourcennutzung verfolgen. Für das SLM auf Ebene von SOA Workflows müssen temporär dienstübergreifende Kooperationen zur Erfüllung von Dienstgüteanforderungen etabliert werden, die sich damit auch über mehrere administrative Domänen erstrecken können. Eine solche zeitlich begrenzte Kooperation autonomer Teilsysteme kann sinnvoll nur dezentral erfolgen, da die jeweiligen Kooperationspartner im Vorfeld nicht bekannt sind und – je nach Lebensdauer einzelner Workflows – zur Laufzeit beteiligte Komponenten ausgetauscht werden können. In der Arbeit wird ein Verfahren zur Koordination autonomer Management-Komponenten mit dem Ziel der Optimierung von Antwortzeiten auf Workflow-Ebene entwickelt: Management-Komponenten können durch Übertragung von Antwortzeitanteilen untereinander ihre individuellen Ziele straffen oder lockern, ohne dass das Gesamtantwortzeitziel dadurch verändert wird. Die Übertragung von Antwortzeitanteilen wird mithilfe eines Auktionsverfahrens realisiert. Technische Grundlage der Kooperation bildet ein Gruppenkommunikationsmechanismus. Weiterhin werden in Bezug auf die Nutzung geteilter, virtualisierter Ressourcen konkurrierende Dienste entsprechend geschäftlicher Ziele priorisiert. Im Rahmen der praktischen Umsetzung wird die Realisierung zentraler Architekturelemente und der entwickelten Verfahren zur Selbstorganisation beispielhaft für das SLM konkreter Komponenten vorgestellt. Zur Untersuchung der Management-Kooperation in größeren Szenarien wird ein hybrider Simulationsansatz verwendet. Im Rahmen der Evaluation werden Untersuchungen zur Skalierbarkeit des Ansatzes durchgeführt. Schwerpunkt ist hierbei die Betrachtung eines Systems aus kooperierenden Management-Komponenten, insbesondere im Hinblick auf den Kommunikationsaufwand. Die Evaluation zeigt, dass ein dienstübergreifendes, autonomes Performance-Management in SOA-Umgebungen möglich ist. Die Ergebnisse legen nahe, dass der entwickelte Ansatz auch in großen Umgebungen erfolgreich angewendet werden kann.

Akzeptanz und Motivation beim selbstregulierten Lernen unter Einsatz von neuen Medien in der berufsbegleitenden Weiterbildung

Das Ziel der Dissertation war die Untersuchung des Computereinsatzes zur Lern- und Betreuungsunterstützung beim selbstgesteuerten Lernen in der Weiterbildung. In einem bisher konventionell durchgeführten Selbstlernkurs eines berufsbegleitenden Studiengangs, der an das Datenmanagement der Bürodatenverarbeitung heranführt, wurden die Kursunterlagen digitalisiert, die Betreuung auf eine online-basierte Lernbegleitung umgestellt und ein auf die neuen Lernmedien abgestimmtes Lernkonzept entwickelt. Dieses neue Lernkonzept wurde hinsichtlich der Motivation und der Akzeptanz von digitalen Lernmedien evaluiert. Die Evaluation bestand aus zwei Teilen: 1. eine formative, den Entwicklungsprozess begleitende Evaluation zur Optimierung der entwickelten Lernsoftware und des eingeführten Lernkonzeptes, 2. eine sowohl qualitative wie quantitative summative Evaluation der Entwicklungen. Ein zentraler Aspekt der Untersuchung war die freie Wahl der Lernmedien (multimediale Lernsoftware oder konventionelles Begleitbuch) und der Kommunikationsmedien (online-basierte Lernplattform oder die bisher genutzten Kommunikationskanäle: E-Mail, Telefon und Präsenztreffen). Diese Zweigleisigkeit erlaubte eine differenzierte Gegenüberstellung von konventionellen und innovativen Lernarrangements. Die Verbindung von qualitativen und quantitativen Vorgehensweisen, auf Grund derer die subjektiven Einstellungen der Probanden in das Zentrum der Betrachtung rückten, ließen einen Blickwinkel auf den Nutzen und die Wirkung der Neuen Medien in Lernprozessen zu, der es erlaubte einige in der Literatur als gängig angesehene Interpretationen in Frage zu stellen und neu zu diskutieren. So konnten durch eine Kategorisierung des Teilnehmerverhaltens nach online-typisch und nicht online-typisch die Ursache-Wirkungs-Beziehungen der in vielen Untersuchungen angeführten Störungen in Online-Seminaren verdeutlicht werden. In den untersuchten Kursen zeigte sich beispielsweise keine Abhängigkeit der Drop-out-Quote von den Lern- und Betreuungsformen und dass diese Quote mit dem neuen Lernkonzept nur geringfügig beeinflusst werden konnte. Die freie Wahl der Lernmedien führte zu einer gezielten Nutzung der multimedialen Lernsoftware, wodurch die Akzeptanz dieses Lernmedium stieg. Dagegen war die Akzeptanz der Lernenden gegenüber der Lernbegleitung mittels einer Online-Lernplattform von hoch bis sehr niedrig breit gestreut. Unabhängig davon reichte in allen Kursdurchgängen die Online-Betreuung nicht aus, so dass Präsenztreffen erbeten wurde. Hinsichtlich der Motivation war die Wirkung der digitalen Medien niedriger als erwartet. Insgesamt bieten die Ergebnisse Empfehlungen für die Planung und Durchführung von computerunterstützten, online-begleiteten Kursen.

Quality Governance based on Enterprise Engineering Method and Six Sigma Approach

Enterprise Modeling (EM) is currently in operation either as a technique to represent and understand the structure and behavior of the enterprise, or as a technique to analyze business processes, and in many cases as support technique for business process reengineering. However, EM architectures and methods for Enterprise Engineering can also used to support new management techniques like SIX SIGMA, because these new techniques need a clear, transparent and integrated definition and description of the business activities of the enterprise to be able to build up, optimize and operate an successful enterprise. The main goal of SIX SIGMA is to optimize the performance of processes. A still open question is: "What are the adequate Quality criteria and methods to ensure such performance? What must we do to get Quality governance?" This paper describes a method including an Enterprise Engineering method and SIX SIGMA strategy to reach Quality Governance

Enterprise Engineering Method supporting Six Sigma Approach

Enterprise Modeling (EM) is currently in operation either as a technique to represent and understand the structure and behavior of the enterprise, or as a technique to analyze business processes, and in many cases as support technique for business process reengineering. However, EM architectures and methodes for Enterprise Engineering can also used to support new management techniques like SIX SIGMA, because these new techniques need a clear, transparent and integrated definition and description of the business activities of the enterprise to be able to build up, to optimize and to operate an successful enterprise.

Verfahren zur echtzeitfähigen Simulation dynamischer Emissionsverläufe ausgewählter Schadstoffe von Ottomotoren

Im Rahmen dieser Arbeit werden Modellbildungsverfahren zur echtzeitfähigen Simulation wichtiger Schadstoffkomponenten im Abgasstrom von Verbrennungsmotoren vorgestellt. Es wird ein ganzheitlicher Entwicklungsablauf dargestellt, dessen einzelne Schritte, beginnend bei der Ver-suchsplanung über die Erstellung einer geeigneten Modellstruktur bis hin zur Modellvalidierung, detailliert beschrieben werden. Diese Methoden werden zur Nachbildung der dynamischen Emissi-onsverläufe relevanter Schadstoffe des Ottomotors angewendet. Die abgeleiteten Emissionsmodelle dienen zusammen mit einer Gesamtmotorsimulation zur Optimierung von Betriebstrategien in Hybridfahrzeugen. Im ersten Abschnitt der Arbeit wird eine systematische Vorgehensweise zur Planung und Erstellung von komplexen, dynamischen und echtzeitfähigen Modellstrukturen aufgezeigt. Es beginnt mit einer physikalisch motivierten Strukturierung, die eine geeignete Unterteilung eines Prozessmodells in einzelne überschaubare Elemente vorsieht. Diese Teilmodelle werden dann, jeweils ausgehend von einem möglichst einfachen nominalen Modellkern, schrittweise erweitert und ermöglichen zum Abschluss eine robuste Nachbildung auch komplexen, dynamischen Verhaltens bei hinreichender Genauigkeit. Da einige Teilmodelle als neuronale Netze realisiert werden, wurde eigens ein Verfah-ren zur sogenannten diskreten evidenten Interpolation (DEI) entwickelt, das beim Training einge-setzt, und bei minimaler Messdatenanzahl ein plausibles, also evidentes Verhalten experimenteller Modelle sicherstellen kann. Zum Abgleich der einzelnen Teilmodelle wurden statistische Versuchs-pläne erstellt, die sowohl mit klassischen DoE-Methoden als auch mittels einer iterativen Versuchs-planung (iDoE ) generiert wurden. Im zweiten Teil der Arbeit werden, nach Ermittlung der wichtigsten Einflussparameter, die Model-strukturen zur Nachbildung dynamischer Emissionsverläufe ausgewählter Abgaskomponenten vor-gestellt, wie unverbrannte Kohlenwasserstoffe (HC), Stickstoffmonoxid (NO) sowie Kohlenmono-xid (CO). Die vorgestellten Simulationsmodelle bilden die Schadstoffkonzentrationen eines Ver-brennungsmotors im Kaltstart sowie in der anschließenden Warmlaufphase in Echtzeit nach. Im Vergleich zur obligatorischen Nachbildung des stationären Verhaltens wird hier auch das dynami-sche Verhalten des Verbrennungsmotors in transienten Betriebsphasen ausreichend korrekt darge-stellt. Eine konsequente Anwendung der im ersten Teil der Arbeit vorgestellten Methodik erlaubt, trotz einer Vielzahl von Prozesseinflussgrößen, auch hier eine hohe Simulationsqualität und Ro-bustheit. Die Modelle der Schadstoffemissionen, eingebettet in das dynamische Gesamtmodell eines Ver-brennungsmotors, werden zur Ableitung einer optimalen Betriebsstrategie im Hybridfahrzeug ein-gesetzt. Zur Lösung solcher Optimierungsaufgaben bieten sich modellbasierte Verfahren in beson-derer Weise an, wobei insbesondere unter Verwendung dynamischer als auch kaltstartfähiger Mo-delle und der damit verbundenen Realitätsnähe eine hohe Ausgabequalität erreicht werden kann.

Effect of rural transportation system on agricultural productivity in Oyo State, Nigeria

Food farming in Oyo North, Nigeria is characterised by an increasing use of Intermediary Mode of Transportation (IMT) to ease inputs and outputs mobility and farm access. To assess the influence on food farmer’s productivity, a random sample of 230 respondents was selected and data collected on their socio-economic and farm specific characteristics. Descriptive statistics, Herfindhal Index and Technical Efficiency Approach were used to analyse the data. The results indicate that majority of food farmers were in their middle age with mean age of 50 years and most of them used one plot at a location between 5 and 10km to their village of residence. They acquired land by inheritance and practiced intensive crop diversification as risk management strategy. The transportation modes used in addition to walking include bicycle, motorcycle, and car with increasing trend in the use of motorcycle. The mean Technical Efficiency (TE) of food farmers was 0.82 with significant inefficiency effects. The inefficiency analysis indicates positive effect of distance, crop diversification and un-tarred type of road on farmer’s productivity, while poor level of education among farmers, use of bicycle; trekking and weekly working time negatively affect farmer’s efficiency. The negative effect of trekking and use of bicycle and the excess working time suggest the adoption of more IMT of motorized type to optimize farming time and increase farmer’s productivity.

Development of directly modulated high speed telecommunication lasers based on surface defined feedback gratings

High-speed semiconductor lasers are an integral part in the implemen- tation of high-bit-rate optical communications systems. They are com- pact, rugged, reliable, long-lived, and relatively inexpensive sources of coherent light. Due to the very low attenuation window that exists in the silica based optical fiber at 1.55 μm and the zero dispersion point at 1.3 μm, they have become the mainstay of optical fiber com- munication systems. For the fabrication of lasers with gratings such as, distributed bragg reflector or distributed feedback lasers, etching is the most critical step. Etching defines the lateral dimmensions of the structure which determines the performance of optoelectronic devices. In this thesis studies and experiments were carried out about the exist- ing etching processes for InP and a novel dry etching process was de- veloped. The newly developed process was based on Cl2/CH4/H2/Ar chemistry and resulted in very smooth surfaces and vertical side walls. With this process the grating definition was significantly improved as compared to other technological developments in the respective field. A surface defined grating definition approach is used in this thesis work which does not require any re-growth steps and makes the whole fabrication process simpler and cost effective. Moreover, this grating fabrication process is fully compatible with nano-imprint lithography and can be used for high throughput low-cost manufacturing. With usual etching techniques reported before it is not possible to etch very deep because of aspect ratio dependent etching phenomenon where with increasing etch depth the etch rate slows down resulting in non-vertical side walls and footing effects. Although with our de- veloped process quite vertical side walls were achieved but footing was still a problem. To overcome the challenges related to grating defini- tion and deep etching, a completely new three step gas chopping dry etching process was developed. This was the very first time that a time multiplexed etching process for an InP based material system was demonstrated. The developed gas chopping process showed extra ordinary results including high mask selectivity of 15, moderate etch- ing rate, very vertical side walls and a record high aspect ratio of 41. Both the developed etching processes are completely compatible with nano imprint lithography and can be used for low-cost high-throughput fabrication. A large number of broad area laser, ridge waveguide laser, distributed feedback laser, distributed bragg reflector laser and coupled cavity in- jection grating lasers were fabricated using the developed one step etch- ing process. Very extensive characterization was done to optimize all the important design and fabrication parameters. The devices devel- oped have shown excellent performance with a very high side mode suppression ratio of more than 52 dB, an output power of 17 mW per facet, high efficiency of 0.15 W/A, stable operation over temperature and injected currents and a threshold current as low as 30 mA for almost 1 mm long device. A record high modulation bandwidth of 15 GHz with electron-photon resonance and open eye diagrams for 10 Gbps data transmission were also shown.