Visible-light-mediated synthesis of helicenes in batch and continuous flow systems

Le présent mémoire décrit le développement d’une méthode de synthèse des hélicènes catalysée par la lumière visible. Les conditions pour la formation de [5]hélicène ont été établies par une optimisation du photocatalyseur, du solvant, du système d’oxydation et du temps réactionnel. Suite aux études mécanistiques préliminaires, un mécanisme oxydatif est proposé. Les conditions optimisées ont été appliquées à la synthèse de [6]hélicènes pour laquelle la régiosélectivité a été améliorée en ajoutant des substituants sur la colonne hélicale. La synthèse de thiohélicènes a aussi été testée en utilisant les mêmes conditions sous irradiation par la lumière visible. La méthode a été inefficace pour la formation de benzodithiophènes et de naphtothiophènes, par contre elle permet la formation du phenanthro[3,4-b]thiophène avec un rendement acceptable. En prolongeant la surface-π de la colonne hélicale, le pyrène a été fusionné aux motifs de [4]- et [5]hélicène. Trois dérivés de pyrène-hélicène ont été synthétisés en utilisant les conditions optimisées pour la photocyclisation et leurs caractéristiques physiques ont été étudiées. La méthode de cyclisation sous l’action de la lumière visible a aussi été étudiée en flux continu. Une optimisation du montage expérimental ainsi que de la source lumineuse a été effectuée et les meilleures conditions ont été appliquées à la formation de [5]hélicène et des trois dérivés du pyrène-hélicène. Une amélioration ou conservation des rendements a été observée pour la plupart des produits formés en flux continu comparativement à la synthèse en batch. La concentration de la réaction a aussi été conservée et le temps réactionnel a été réduit par un facteur de dix toujours en comparaison avec la synthèse en batch.

Investigations on Ultrasonic Transducer Array Systems for NDE of Underwater Pipelines

The main objective of carrying out this investigation is to develop suitable transducer array systems so that underwater pipeline inspection could be carried out in a much better way, a focused beam and electronic steering can reduce inspection time as well. Better results are obtained by optimizing the array parameters. The spacing between the elements is assumed to be half the wavelength so that the interelement interaction is minimum. For NDT applications these arrays are operated at MHz range. The wavelengths become very small in these frequency ranges. Then the size of the array elements becomes very small, requiring hybrid construction techniques for their fabrication. Transducer elements have been fabricated using PVDF as the active, mild steel as the backing and conducting silver preparation as the bonding materials. The transducer is operated in the (3,3) mode. The construction of a high frequency array is comparatively complicated. The interelement spacing between the transducer elements becomes considerably small when high frequencies are considered. It becomes very difficult to construct the transducer manually. The electrode connections to the elements can produce significant loading effect. The array has to be fabricated using hybrid construction techniques. The active materials has to be deposited on a proper substrate and etching techniques are required to fabricate the array. The annular ring, annular cylindrical or other similar structural forms of arrays may also find applications in the near future in treatments were curved contours of the human body are affected.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Investigations on polyaniline based systems for technologically important applications and some novel polymers as prospective candidates for fabricating polymer light emitting diodes

Light emitting polymers (LEP) have drawn considerable attention because of their numerous potential applications in the field of optoelectronic devices. Till date, a large number of organic molecules and polymers have been designed and devices fabricated based on these materials. Optoelectronic devices like polymer light emitting diodes (PLED) have attracted wide-spread research attention owing to their superior properties like flexibility, lower operational power, colour tunability and possibility of obtaining large area coatings. PLEDs can be utilized for the fabrication of flat panel displays and as replacements for incandescent lamps. The internal efficiency of the LEDs mainly depends on the electroluminescent efficiency of the emissive polymer such as quantum efficiency, luminance-voltage profile of LED and the balanced injection of electrons and holes. Poly (p-phenylenevinylene) (PPV) and regio-regular polythiophenes are interesting electro-active polymers which exhibit good electrical conductivity, electroluminescent activity and high film-forming properties. A combination of Red, Green and Blue emitting polymers is necessary for the generation of white light which can replace the high energy consuming incandescent lamps. Most of these polymers show very low solubility, stability and poor mechanical properties. Many of these light emitting polymers are based on conjugated extended chains of alternating phenyl and vinyl units. The intra-chain or inter-chain interactions within these polymer chains can change the emitted colour. Therefore an effective way of synthesizing polymers with reduced π-stacking, high solubility, high thermal stability and high light-emitting efficiency is still a challenge for chemists. New copolymers have to be effectively designed so as to solve these issues. Hence, in the present work, the suitability of a few novel copolymers with very high thermal stability, excellent solubility, intense light emission (blue, cyan and green) and high glass transition temperatures have been investigated to be used as emissive layers for polymer light emitting diodes.

Hybrid Background Subtraction in Video using Bi-level CodeBook Model

Detection of Objects in Video is a highly demanding area of research. The Background Subtraction Algorithms can yield better results in Foreground Object Detection. This work presents a Hybrid CodeBook based Background Subtraction to extract the foreground ROI from the background. Codebooks are used to store compressed information by demanding lesser memory usage and high speedy processing. This Hybrid method which uses Block-Based and Pixel-Based Codebooks provide efficient detection results; the high speed processing capability of block based background subtraction as well as high Precision Rate of pixel based background subtraction are exploited to yield an efficient Background Subtraction System. The Block stage produces a coarse foreground area, which is then refined by the Pixel stage. The system’s performance is evaluated with different block sizes and with different block descriptors like 2D-DCT, FFT etc. The Experimental analysis based on statistical measurements yields precision, recall, similarity and F measure of the hybrid system as 88.74%, 91.09%, 81.66% and 89.90% respectively, and thus proves the efficiency of the novel system.

Hybrid Multiferroic Nanostructure with Magnetic−Dielectric Coupling

The development of methods to economically synthesize single wire structured multiferroic systems with room temperature spin−charge coupling is expected to be important for building next-generation multifunctional devices with ultralow power consumption. We demonstrate the fabrication of a single nanowire multiferroic system, a new geometry, exhibiting room temperature magnetodielectric coupling. A coaxial nanotube/nanowire heterostructure of barium titanate (BaTiO3, BTO) and cobalt (Co) has been synthesized using a template-assisted method. Room temperature ferromagnetism and ferroelectricity were exhibited by this coaxial system, indicating the coexistence of more than one ferroic interaction in this composite system

A Hybrid Architecture for Recognising Speech Signals in Malayalam

Speech is the primary, most prominent and convenient means of communication in audible language. Through speech, people can express their thoughts, feelings or perceptions by the articulation of words. Human speech is a complex signal which is non stationary in nature. It consists of immensely rich information about the words spoken, accent, attitude of the speaker, expression, intention, sex, emotion as well as style. The main objective of Automatic Speech Recognition (ASR) is to identify whatever people speak by means of computer algorithms. This enables people to communicate with a computer in a natural spoken language. Automatic recognition of speech by machines has been one of the most exciting, significant and challenging areas of research in the field of signal processing over the past five to six decades. Despite the developments and intensive research done in this area, the performance of ASR is still lower than that of speech recognition by humans and is yet to achieve a completely reliable performance level. The main objective of this thesis is to develop an efficient speech recognition system for recognising speaker independent isolated words in Malayalam.

Synthesis, Characterization and Applications of Hybrid Nanocomposites of TiO2 With Conducting Polymers

A nanocomposite is a multiphase solid material where one of the phases has one, two or three dimensions of less than 100 nanometers (nm), or structures having nano-scale repeat distances between the different phases that make up the material. In the broadest sense this definition can include porous media, colloids, gels and copolymers, but is more usually taken to mean the solid combination of a bulk matrix and nano-dimensional phase(s) differing in properties due to dissimilarities in structure and chemistry. The mechanical, electrical, thermal, optical, electrochemical, catalytic properties of the nanocomposite will differ markedly from that of the component materials. Size limits for these effects have been proposed, <5 nm for catalytic activity, <20 nm for making a hard magnetic material soft, <50 nm for refractive index changes, and <100 nm for achieving superparamagnetism, mechanical strengthening or restricting matrix dislocation movement. Conducting polymers have attracted much attention due to high electrical conductivity, ease of preparation, good environmental stability and wide variety of applications in light-emitting, biosensor chemical sensor, separation membrane and electronic devices. The most widely studied conducting polymers are polypyrrole, polyaniline, polythiophene etc. Conducting polymers provide tremendous scope for tuning of their electrical conductivity from semiconducting to metallic region by way of doping and are organic electro chromic materials with chemically active surface. But they are chemically very sensitive and have poor mechanical properties and thus possessing a processibility problem. Nanomaterial shows the presence of more sites for surface reactivity, they possess good mechanical properties and good dispersant too. Thus nanocomposites formed by combining conducting polymers and inorganic oxide nanoparticles possess the good properties of both the constituents and thus enhanced their utility. The properties of such type of nanocomposite are strongly depending on concentration of nanomaterials to be added. Conducting polymer composites is some suitable composition of a conducting polymer with one or more inorganic nanoparticles so that their desirable properties are combined successfully. The composites of core shell metal oxide particles-conducting polymer combine the electrical properties of the polymer shell and the magnetic, optical, electrical or catalytic characteristics of the metal oxide core, which could greatly widen their applicability in the fields of catalysis, electronics and optics. Moreover nanocomposite material composed of conducting polymers & oxides have open more field of application such as drug delivery, conductive paints, rechargeable batteries, toners in photocopying, smart windows, etc.The present work is mainly focussed on the synthesis, characterization and various application studies of conducting polymer modified TiO2 nanocomposites. The conclusions of the present work are outlined below, Mesoporous TiO2 was prepared by the cationic surfactant P123 assisted hydrothermal synthesis route and conducting polymer modified TiO2 nanocomposites were also prepared via the same technique. All the prepared systems show XRD pattern corresponding to anatase phase of TiO2, which means that there is no phase change occurring even after conducting polymer modification. Raman spectroscopy gives supporting evidence for the XRD results. It also confirms the incorporation of the polymer. The mesoporous nature and surface area of the prepared samples were analysed by N2 adsorption desorption studies and the mesoporous ordering can be confirmed by low angle XRD measurementThe morphology of the prepared samples was obtained from both SEM & TEM. The elemental analysis of the samples was performed by EDX analysisThe hybrid composite formation is confirmed by FT-IR spectroscopy and X-ray photoelectron spectroscopyAll the prepared samples have been used for the photocatalytic degradation of dyes, antibiotic, endocrine disruptors and some other organic pollutants. Photocatalytic antibacterial activity studies were also performed using the prepared systemsAll the prepared samples have been used for the photocatalytic degradation of dyes, antibiotic, endocrine disruptors and some other organic pollutants. Photocatalytic antibacterial activity studies were also performed using the prepared systems Polyaniline modified TiO2 nanocomposite systems were found to have good antibacterial activity. Thermal diffusivity studies of the polyaniline modified systems were carried out using thermal lens technique. It is observed that as the amount of polyaniline in the composite increases the thermal diffusivity also increases. The prepared systems can be used as an excellent coolant in various industrial purposes. Nonlinear optical properties (3rd order nonlinearity) of the polyaniline modified systems were studied using Z scan technique. The prepared materials can be used for optical limiting Applications. Lasing studies of polyaniline modified TiO2 systems were carried out and the studies reveal that TiO2 - Polyaniline composite is a potential dye laser gain medium.

Modelling and simulation of a photovoltaic fuel cell hybrid system

A stand-alone power system is an autonomous system that supplies electricity to the user load without being connected to the electric grid. This kind of decentralized system is frequently located in remote and inaccessible areas. It is essential for about one third of the world population which are living in developed or isolated regions and have no access to an electricity utility grid. The most people live in remote and rural areas, with low population density, lacking even the basic infrastructure. The utility grid extension to these locations is not a cost effective option and sometimes technically not feasible. The purpose of this thesis is the modelling and simulation of a stand-alone hybrid power system, referred to as “hydrogen Photovoltaic-Fuel Cell (PVFC) hybrid system”. It couples a photovoltaic generator (PV), an alkaline water electrolyser, a storage gas tank, a proton exchange membrane fuel cell (PEMFC), and power conditioning units (PCU) to give different system topologies. The system is intended to be an environmentally friendly solution since it tries maximising the use of a renewable energy source. Electricity is produced by a PV generator to meet the requirements of a user load. Whenever there is enough solar radiation, the user load can be powered totally by the PV electricity. During periods of low solar radiation, auxiliary electricity is required. An alkaline high pressure water electrolyser is powered by the excess energy from the PV generator to produce hydrogen and oxygen at a pressure of maximum 30bar. Gases are stored without compression for short- (hourly or daily) and long- (seasonal) term. A proton exchange membrane (PEM) fuel cell is used to keep the system’s reliability at the same level as for the conventional system while decreasing the environmental impact of the whole system. The PEM fuel cell consumes gases which are produced by an electrolyser to meet the user load demand when the PV generator energy is deficient, so that it works as an auxiliary generator. Power conditioning units are appropriate for the conversion and dispatch the energy between the components of the system. No batteries are used in this system since they represent the weakest when used in PV systems due to their need for sophisticated control and their short lifetime. The model library, ISET Alternative Power Library (ISET-APL), is designed by the Institute of Solar Energy supply Technology (ISET) and used for the simulation of the hybrid system. The physical, analytical and/or empirical equations of each component are programmed and implemented separately in this library for the simulation software program Simplorer by C++ language. The model parameters are derived from manufacturer’s performance data sheets or measurements obtained from literature. The identification and validation of the major hydrogen PVFC hybrid system component models are evaluated according to the measured data of the components, from the manufacturer’s data sheet or from actual system operation. Then, the overall system is simulated, at intervals of one hour each, by using solar radiation as the primary energy input and hydrogen as energy storage for one year operation. A comparison between different topologies, such as DC or AC coupled systems, is carried out on the basis of energy point of view at two locations with different geographical latitudes, in Kassel/Germany (Europe) and in Cairo/Egypt (North Africa). The main conclusion in this work is that the simulation method of the system study under different conditions could successfully be used to give good visualization and comparison between those topologies for the overall performance of the system. The operational performance of the system is not only depending on component efficiency but also on system design and consumption behaviour. The worst case of this system is the low efficiency of the storage subsystem made of the electrolyser, the gas storage tank, and the fuel cell as it is around 25-34% at Cairo and 29-37% at Kassel. Therefore, the research for this system should be concentrated in the subsystem components development especially the fuel cell.

Hybrid Power System Modelling - Simulation and Energy Management Unit Development

Weltweit leben mehr als 2 Milliarden Menschen in ländlichen Gebieten. Als Konzept für die elektrische Energieversorgung solcher Gebiete kommen dezentrale elektrische Energieversorgungseinheiten zum Einsatz, die lokal verfügbare erneuerbare Ressourcen nutzen. Stand der Technik bilden Einheiten, die auf PV-Diesel-Batterie System basieren. Die verwendeten Versorgungsskonzepte in Hybridsystemen sind durch den Einsatz von Batterien als Energiespeicher meist wenig zuverlässig und teuer. Diese Energiespeicher sind sehr aufwendig zu überwachen und schwerig zu entsorgen. Den Schwerpunkt dieser Arbeit bildet die Entwicklung eines neuen Hybridsystems mit einem Wasserreservoir als Energiespeicher. Dieses Konzept eignet sich für Bergregionen in Entwicklungsländern wie Nepal, wo z.B. neben der solaren Strahlung kleine Flüsse in großer Anzahl vorhanden sind. Das Hybridsystem verfügt über einen Synchrongenerator, der die Netzgrößen Frequenz und Spannung vorgibt und zusätzlich unterstützen PV und Windkraftanlage die Versorgung. Die Wasserkraftanlage soll den Anteil der erneuerbaren Energienutzung erhöhen. Die Erweiterung des Systems um ein Dieselaggregat soll die Zuverlässigkeit der Versorgung erhöhen. Das Hybridsystem inkl. der Batterien wird modelliert und simuliert. Anschließend werden die Simulations- und Messergebnisse verglichen, um eine Validierung des Modells zu erreichen. Die Regelungsstruktur ist aufgrund der hohen Anzahl an Systemen und Parametern sehr komplex. Sie wird mit dem Simulationstool Matlab/Simulink nachgebildet. Das Verhalten des Gesamtsystems wird unter verschiedene Lasten und unterschiedlichen meteorologischen Gegebenheiten untersucht. Ein weiterer Schwerpunkt dieser Arbeit ist die Entwicklung einer modularen Energiemanagementeinheit, die auf Basis der erneuerbaren Energieversorgung aufgebaut wird. Dabei stellt die Netzfrequenz eine wichtige Eingangsgröße für die Regelung dar. Sie gibt über die Wirkleistungsstatik die Leistungsänderung im Netz wider. Über diese Angabe und die meteorologischen Daten kann eine optimale wirtschaftliche Aufteilung der Energieversorgung berechnet und eine zuverlässige Versorgung gewährleistet werden. Abschließend wurde die entwickelte Energiemanagementeinheit hardwaretechnisch aufgebaut, sowie Sensoren, Anzeige- und Eingabeeinheit in die Hardware integriert. Die Algorithmen werden in einer höheren Programmiersprache umgesetzt. Die Simulationen unter verschiedenen meteorologischen und netztechnischen Gegebenheiten mit dem entwickelten Model eines Hybridsystems für die elektrische Energieversorgung haben gezeigt, dass das verwendete Konzept mit einem Wasserreservoir als Energiespeicher ökologisch und ökonomisch eine geeignete Lösung für Entwicklungsländer sein kann. Die hardwaretechnische Umsetzung des entwickelten Modells einer Energiemanagementeinheit hat seine sichere Funktion bei der praktischen Anwendung in einem Hybridsystem bestätigen können.

Economics of Hybrid Photovoltaic Power Plants

The global power supply stability is faced to several severe and fundamental threats, in particular steadily increasing power demand, diminishing and degrading fossil and nuclear energy resources, very harmful greenhouse gas emissions, significant energy injustice and a structurally misbalanced ecological footprint. Photovoltaic (PV) power systems are analysed in various aspects focusing on economic and technical considerations of supplemental and substitutional power supply to the constraint conventional power system. To infer the most relevant system approach for PV power plants several solar resources available for PV systems are compared. By combining the different solar resources and respective economics, two major PV systems are identified to be very competitive in almost all regions in the world. The experience curve concept is used as a key technique for the development of scenario assumptions on economic projections for the decade of the 2010s. Main drivers for cost reductions in PV systems are learning and production growth rate, thus several relevant aspects are discussed such as research and development investments, technical PV market potential, different PV technologies and the energetic sustainability of PV. Three major market segments for PV systems are identified: off-grid PV solutions, decentralised small scale on-grid PV systems (several kWp) and large scale PV power plants (tens of MWp). Mainly by application of ‘grid-parity’ and ‘fuel-parity’ concepts per country, local market and conventional power plant basis, the global economic market potential for all major PV system segments is derived. PV power plant hybridization potential of all relevant power technologies and the global power plant structure are analyzed regarding technical, economical and geographical feasibility. Key success criteria for hybrid PV power plants are discussed and comprehensively analysed for all adequate power plant technologies, i.e. oil, gas and coal fired power plants, wind power, solar thermal power (STEG) and hydro power plants. For the 2010s, detailed global demand curves are derived for hybrid PV-Fossil power plants on a per power plant, per country and per fuel type basis. The fundamental technical and economic potentials for hybrid PV-STEG, hybrid PV-Wind and hybrid PV-Hydro power plants are considered. The global resource availability for PV and wind power plants is excellent, thus knowing the competitive or complementary characteristic of hybrid PV-Wind power plants on a local basis is identified as being of utmost relevance. The complementarity of hybrid PV-Wind power plants is confirmed. As a result of that almost no reduction of the global economic PV market potential need to be expected and more complex power system designs on basis of hybrid PV-Wind power plants are feasible. The final target of implementing renewable power technologies into the global power system is a nearly 100% renewable power supply. Besides balancing facilities, storage options are needed, in particular for seasonal power storage. Renewable power methane (RPM) offers respective options. A comprehensive global and local analysis is performed for analysing a hybrid PV-Wind-RPM combined cycle gas turbine power system. Such a power system design might be competitive and could offer solutions for nearly all current energy system constraints including the heating and transportation sector and even the chemical industry. Summing up, hybrid PV power plants become very attractive and PV power systems will very likely evolve together with wind power to the major and final source of energy for mankind.

Interaction and Intelligent Behavior

We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, empirically evaluating, and combining behaviors from a basic set. We also introduce a general methodology for automatically constructing higher--level behaviors by learning to select from this set. Based on a formulation of reinforcement learning using conditions, behaviors, and shaped reinforcement, out approach makes behavior selection learnable in noisy, uncertain environments with stochastic dynamics. All described ideas are validated with groups of up to 20 mobile robots performing safe--wandering, following, aggregation, dispersion, homing, flocking, foraging, and learning to forage.

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Multidimensional Adaptations for Open Learning Management Systems

Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos