Synthesis, Characterization and Properties of Ca5A2TiO12 (A=Nb, Ta) Ceramic Dielectric Materials for Applications in Microwave Telecommunication Systems

Microwave ceramic dielectric materials Ca5Nb2TiO12 and Ca5Ta2TiO12 have been prepared by a conventional solid-state ceramic process. The structure was studied by X-ray diffraction and the dielectric properties were characterized at microwave frequencies. The ceramics posses a relatively high dielectric constant, very low dielectric loss (Q5 x f > 30000GHz) and small temperature variation of resonant frequency. These materials are potential candidates for dielectric resonator applications in microwave integrated circuits. [DOI: 10. 1 143/JJAP.41.3834]

Studies on the Effect of Randomness on the Synchronization of Coupled Systems and on the Dynamics of Intermittently driven systems

Nonlinear dynamics has emerged into a prominent area of research in the past few Decades.Turbulence, Pattern formation,Multistability etc are some of the important areas of research in nonlinear dynamics apart from the study of chaos.Chaos refers to the complex evolution of a deterministic system, which is highly sensitive to initial conditions. The study of chaos theory started in the modern sense with the investigations of Edward Lorentz in mid 60's. Later developments in this subject provided systematic development of chaos theory as a science of deterministic but complex and unpredictable dynamical systems. This thesis deals with the effect of random fluctuations with its associated characteristic timescales on chaos and synchronization. Here we introduce the concept of noise, and two familiar types of noise are discussed. The classifications and representation of white and colored noise are introduced. Based on this we introduce the concept of randomness that we deal with as a variant of the familiar concept of noise. The dynamical systems introduced are the Rossler system, directly modulated semiconductor lasers and the Harmonic oscillator. The directly modulated semiconductor laser being not a much familiar dynamical system, we have included a detailed introduction to its relevance in Chaotic encryption based cryptography in communication. We show that the effect of a fluctuating parameter mismatch on synchronization is to destroy the synchronization. Further we show that the relation between synchronization error and timescales can be found empirically but there are also cases where this is not possible. Studies show that under the variation of the parameters, the system becomes chaotic, which appears to be the period doubling route to chaos.

Studies on some supported transition metal complex and metal oxide catalysts for oxidation reactions

Zeolite encapsulated transition metal complexes have received wide attention as an effective heterogenized system that combines the tremendous activity of the metal complexes and the attractive features of the zeolite structure. Zeolite encapsulated complexes offer a bright future for attempts to replace homogeneous systems retaining its catalytic activity and minimizing the technical problems. especially for the partial oxidation of organic compounds. Studies on some zeolite encapsulated transition metal complexes are presented in this thesis. The ligands selected are technically important in a bio-mimetic or structural perspective. Attempts have been made in this study to investigate the composition, structure and stability of encapsulated complexes using available techniques. The catalytic activity of encapsulated complexes was evaluated for the oxidation of some organic compounds. The recycling ability of the catalyst as a result of the encapsulation was also studied.Our studies on Cu-Cr/Al2O3, a typical metal oxide catalyst. illustrate the use of design techniques to modify the properties of such conventional catalysts. The catalytic activity of this catalyst for the oxidation of carbon monoxide was measured. The effect of additives like Ce02 or Ti02 on the activity and stability of this system was also investigated. The additive is potent to improve the activity and stability ofthe catalyst so as to be more effective in commercial usage.

Dynamical aspects of coupled Rossler systems: effects of noise

Nonlinear time series analysis is employed to study the complex behaviour exhibited by a coupled pair of Rossler systems. Dimensional analysis with emphasis on the topological correlation dimension and the Kolmogorov entropy of the system is carried out in the coupling parameter space. The regime of phase synchronization is identified and the extent of synchronization between the systems constituting the coupled system is quantified by the phase synchronization index. The effect of noise on the coupling between the systems is also investigated. An exhaustive study of the topological, dynamical and synchronization properties of the nonlinear system under consideration in its characteristic parameter space is attempted.

Design and Development of Instrumentation Systems to determine the Dry Rubber Content in Natural Rubber Latex

Hevea latex is a natural biological liquid of very complex composition .Besides rubber hydrocarbons,it contains many proteinous and resinous substances,carbohydrates,inorganic matter,water,and others.The Dry Rubber Content (DRC) of latex varies according to season, tapping system,weather,soil conditions ,clone,age of the tree etc. The true DRC of the latex must be determined to ensure fair prices for the latex during commercial exchange.The DRC of Hevea latex is a very familiar term to all in the rubber industry.It has been the basis for incentive payments to tappers who bring in more than the daily agreed poundage of latex.It is an important parameter for rubber and latex processing industries for automation and verious decesion making processes.This thesis embodies the efforts made by me to determine the DRC of rubber latex following different analytical tools such as MIR absorption,thermal analysis.dielectric spectroscopy and NIR reflectance.The rubber industry is still Looking for a compact instrument that is accurate economical,easy to use and environment friendly.I hope the results presented in this thesis will help to realise this goal in the near future.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Energy Management in Wireless Sensor Networks: A Crosslayer,Channel Adaptive Approach Towards Performance Optimization

The proliferation of wireless sensor networks in a large spectrum of applications had been spurered by the rapid advances in MEMS(micro-electro mechanical systems )based sensor technology coupled with low power,Low cost digital signal processors and radio frequency circuits.A sensor network is composed of thousands of low cost and portable devices bearing large sensing computing and wireless communication capabilities. This large collection of tiny sensors can form a robust data computing and communication distributed system for automated information gathering and distributed sensing.The main attractive feature is that such a sensor network can be deployed in remote areas.Since the sensor node is battery powered,all the sensor nodes should collaborate together to form a fault tolerant network so as toprovide an efficient utilization of precious network resources like wireless channel,memory and battery capacity.The most crucial constraint is the energy consumption which has become the prime challenge for the design of long lived sensor nodes.

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.

Studies on nonlinear dynamics of certain reaction systems

The nonlinear dynamics of certain important reaction systems are discussed and analysed in this thesis. The interest in the theoretical and the experimental studies of chemical reactions showing oscillatory dynamics and associated properties is increasing very rapidly. An attempt is made to study some nonlinear phenomena exhibited by the well known chemical oscillator, the BelousovZhabotinskii reaction whose mathematical properties are much in common with the properties of biological oscillators. While extremely complex, this reaction is still much simpler than biological systems at least from the modelling point of view. A suitable model [19] for the system is analysed and the researcher has studied the limit cycle behaviour of the system, for different values of the stoichiometric parameter f, by keeping the value of the reaction rate (k6) fixed at k6 = l. The more complicated three-variable model is stiff in nature.

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

A Multi-Objective Antenna Placement Genetic Algorithm for Matched Array Synthesis on Complex Platforms

A Multi-Objective Antenna Placement Genetic Algorithm (MO-APGA) has been proposed for the synthesis of matched antenna arrays on complex platforms. The total number of antennas required, their position on the platform, location of loads, loading circuit parameters, decoupling and matching network topology, matching network parameters and feed network parameters are optimized simultaneously. The optimization goal was to provide a given minimum gain, specific gain discrimination between the main and back lobes and broadband performance. This algorithm is developed based on the non-dominated sorting genetic algorithm (NSGA-II) and Minimum Spanning Tree (MST) technique for producing diverse solutions when the number of objectives is increased beyond two. The proposed method is validated through the design of a wideband airborne SAR

Development of Directionally Adaptive Techniques for Single Image Super-Resolution

Super Resolution problem is an inverse problem and refers to the process of producing a High resolution (HR) image, making use of one or more Low Resolution (LR) observations. It includes up sampling the image, thereby, increasing the maximum spatial frequency and removing degradations that arise during the image capture namely aliasing and blurring. The work presented in this thesis is based on learning based single image super-resolution. In learning based super-resolution algorithms, a training set or database of available HR images are used to construct the HR image of an image captured using a LR camera. In the training set, images are stored as patches or coefficients of feature representations like wavelet transform, DCT, etc. Single frame image super-resolution can be used in applications where database of HR images are available. The advantage of this method is that by skilfully creating a database of suitable training images, one can improve the quality of the super-resolved image. A new super resolution method based on wavelet transform is developed and it is better than conventional wavelet transform based methods and standard interpolation methods. Super-resolution techniques based on skewed anisotropic transform called directionlet transform are developed to convert a low resolution image which is of small size into a high resolution image of large size. Super-resolution algorithm not only increases the size, but also reduces the degradations occurred during the process of capturing image. This method outperforms the standard interpolation methods and the wavelet methods, both visually and in terms of SNR values. Artifacts like aliasing and ringing effects are also eliminated in this method. The super-resolution methods are implemented using, both critically sampled and over sampled directionlets. The conventional directionlet transform is computationally complex. Hence lifting scheme is used for implementation of directionlets. The new single image super-resolution method based on lifting scheme reduces computational complexity and thereby reduces computation time. The quality of the super resolved image depends on the type of wavelet basis used. A study is conducted to find the effect of different wavelets on the single image super-resolution method. Finally this new method implemented on grey images is extended to colour images and noisy images

Design and study of self-assembled functional organic and hybrid systems for biological applications

The focus of self-assembly as a strategy for the synthesis has been confined largely to molecules, because of the importance of manipulating the structure of matter at the molecular scale. We have investigated the influence of temperature and pH, in addition to the concentration of the capping agent used for the formation of the nano-bio conjugates. For example, the formation of the narrower size distribution of the nanoparticles was observed with the increase in the concentration of the protein, which supports the fact that γ-globulin acts both as a controller of nucleation as well as stabiliser. As analyzed through various photophysical, biophysical and microscopic techniques such as TEM, AFM, C-AFM, SEM, DLS, OPM, CD and FTIR, we observed that the initial photoactivation of γ-globulin at pH 12 for 3 h resulted in small protein fibres of ca. Further irradiation for 24 h, led to the formation of selfassembled long fibres of the protein of ca. 5-6 nm and observation of surface plasmon resonance band at around 520 nm with the concomitant quenching of luminescence intensity at 680 nm. The observation of light triggered self-assembly of the protein and its effect on controlling the fate of the anchored nanoparticles can be compared with the naturally occurring process such as photomorphogenesis.Furthermore,our approach offers a way to understand the role played by the self-assembly of the protein in ordering and knock out of the metal nanoparticles and also in the design of nano-biohybrid materials for medicinal and optoelectronic applications. Investigation of the potential applications of NIR absorbing and water soluble squaraine dyes 1-3 for protein labeling and anti-amyloid agents forms the subject matter of the third chapter of the thesis. The study of their interactions with various proteins revealed that 1-3 showed unique interactions towards serum albumins as well as lysozyme. 69%, 71% and 49% in the absorption spectra as well as significant quenching in the fluorescence intensity of the dyes 1-3, respectively. Half-reciprocal analysis of the absorption data and isothermal titration calorimetric (ITC) analysis of the titration experiments gave a 1:1 stoichiometry for the complexes formed between the lysozyme and squaraine dyes with association constants (Kass) in the range 104-105 M-1. We have determined the changes in the free energy (ΔG) for the complex formation and the values are found to be -30.78, -32.31 and -28.58 kJmol-1, respectively for the dyes 1, 2 and 3. Furthermore, we have observed a strong induced CD (ICD) signal corresponding to the squaraine chromophore in the case of the halogenated squaraine dyes 2 and 3 at 636 and 637 nm confirming the complex formation in these cases. To understand the nature of interaction of the squaraine dyes 1-3 with lysozyme, we have investigated the interaction of dyes 1-3 with different amino acids. These results indicated that the dyes 1-3 showed significant interactions with cysteine and glutamic acid which are present in the side chains of lysozyme. In addition the temperature dependent studies have revealed that the interaction of the dye and the lysozyme are irreversible. Furthermore, we have investigated the interactions of these NIR dyes 1-3 with β- amyloid fibres derived from lysozyme to evaluate their potential as inhibitors of this biologically important protein aggregation. These β-amyloid fibrils were insoluble protein aggregates that have been associated with a range of neurodegenerative diseases, including Huntington, Alzheimer’s, Parkinson’s, and Creutzfeldt-Jakob diseases. We have synthesized amyloid fibres from lysozyme through its incubation in acidic solution below pH 4 and by allowing to form amyloid fibres at elevated temperature. To quantify the binding affinities of the squaraine dyes 1-3 with β-amyloids, we have carried out the isothermal titration calorimetric (ITC) measurements. The association constants were determined and are found to be 1.2 × 105, 3.6× 105 and 3.2 × 105 M-1 for the dyes, 1-3, respectively. To gain more insights into the amyloid inhibiting nature of the squaraine dyes under investigations, we have carried out thioflavin assay, CD, isothermal titration calorimetry and microscopic analysis. The addition of the dyes 1-3 (5μM) led to the complete quenching in the apparent thioflavin fluorescence, thereby indicating the destabilization of β-amyloid fibres in the presence of the squaraine dyes. Further, the inhibition of the amyloid fibres by the squaraine dyes 1-3, has been evidenced though the DLS, TEM AFM and SAED, wherein we observed the complete destabilization of the amyloid fibre and transformation of the fibre into spherical particles of ca. These results demonstrate the fact that the squaraine dyes 1-3 can act as protein labeling agents as well as the inhibitors of the protein amyloidogenesis. The last chapter of the thesis describes the synthesis and investigation of selfassembly as well as bio-imaging aspects of a few novel tetraphenylethene conjugates 4-6.Expectedly, these conjugates showed significant solvatochromism and exhibited a hypsochromic shift (negative solvatochromism) as the solvent polarity increased, and these observations were justified though theoretical studies employing the B3LYP/6-31g method. We have investigated the self-assembly properties of these D-A conjugates though variation in the percentage of water in acetonitrile solution due to the formation of nanoaggregates. Further the contour map of the observed fluorescence intensity as a function of the fluorescence excitation and emission wavelength confirmed the formation of J-type aggregates in these cases. To have a better understanding of the type of self-assemblies formed from the TPE conjugates 4-6, we have carried out the morphological analysis through various microscopic techniques such as DLS, SEM and TEM. 70%, we observed rod shape architectures having ~ 780 nm in diameter and ~ 12 μM in length as evidenced through TEM and SEM analysis. We have made similar observations with the dodecyl conjugate 5 at ca. 70% and 50% water/acetonitrile mixtures, the aggregates formed from 4 and 5 were found to be highly crystalline and such structures were transformed to amorphous nature as the water fraction was increased to 99%. To evaluate the potential of the conjugate as bio-imaging agents, we have carried out their in vitro cytotoxicity and cellular uptake studies though MTT assay, flow cytometric and confocal laser scanning microscopic techniques. Thus nanoparticle of these conjugates which exhibited efficient emission, large stoke shift, good stability, biocompatibility and excellent cellular imaging properties can have potential applications for tracking cells as well as in cell-based therapies. In summary we have synthesized novel functional organic chromophores and have studied systematic investigation of self-assembly of these synthetic and biological building blocks under a variety of conditions. The investigation of interaction of water soluble NIR squaraine dyes with lysozyme indicates that these dyes can act as the protein labeling agents and the efficiency of inhibition of β-amyloid indicate, thereby their potential as anti-amyloid agents.

Investigations on the structural and operational changes of Ring Seine Fishing Systems of Kerala and its Life Cycle Assessment (lCA)

The study covers theFishing capture technology innovation includes the catching of aquatic animal, using any kind of gear techniques, operated from a vessel. Utilization of fishing techniques varies, depending upon the type of fisheries, and can go from a basic and little hook connected to a line to huge and complex mid water trawls or seines operated by large fishing vessels.The size and autonomy of a fishing vessel is largely determined by its ability to handle, process and store fish in good condition on board, and thus these two characteristics have been greatly influenced by the introduction and utilization of ice and refrigeration machinery. Other technological developments especially hydraulic hauling machinery, fish finding electronics and synthetic twines have also had a major impact on the efficiency and profitability of fishing vessels.A wide variety of fishing gears and practices ranging from small-scale artisanal to advanced mechanised systems are used for fish capture in Kerala. Most important among these fishing gears are trawls, seines, lines, gillnets and entangling nets and traps The modern sector was introduced in 1953 at Neendakara, Shakthikulangara region under the initiative of Indo-Norwegian project (INP). The novel facilities introduced in fishing industry by Indo- Norwegian project accordingly are mechanically operated new boats with new fishing nets. Soon after mechanization, motorization programme gained momentum in Kerala especially in Alleppey, Ernakulam and Kollam districts.

Designing in the real world is complex anyway - so what?

Designing is a heterogeneous, fuzzily defined, floating field of various activities and chunks of ideas and knowledge. Available theories about the foundations of designing as presented in "the basic PARADOX" (Jonas and Meyer-Veden 2004) have evoked the impression of Babylonian confusion. We located the reasons for this "mess" in the "non-fit", which is the problematic relation of theories and subject field. There seems to be a comparable interface problem in theory-building as in designing itself. "Complexity" sounds promising, but turns out to be a problematic and not really helpful concept. I will argue for a more precise application of systemic and evolutionary concepts instead, which - in my view - are able to model the underlying generative structures and processes that produce the visible phenomenon of complexity. It does not make sense to introduce a new fashionable meta-concept and to hope for a panacea before having clarified the more basic and still equally problematic older meta-concepts. This paper will take one step away from "theories of what" towards practice and doing and try to have a closer look at existing process models or "theories of how" to design instead. Doing this from a systemic perspective leads to an evolutionary view of the process, which finally allows to specify more clearly the "knowledge gaps" inherent in the design process. This aspect has to be taken into account as constitutive of any attempt at theory-building in design, which can be characterized as a "practice of not-knowing". I conclude, that comprehensive "unified" theories, or methods, or process models run aground on the identified knowledge gaps, which allow neither reliable models of the present, nor reliable projections into the future. Consolation may be found in performing a shift from the effort of adaptation towards strategies of exaptation, which means the development of stocks of alternatives for coping with unpredictable situations in the future.