Sol-Gel Mesoporous Silica Aerogels and Bio Hybrids for Functional Applications

The thesis covers a systematic investigation on the synthesis of silica aerogels and microspheres with tailored porosity, at ambient conditions by varying the experimental parameters as well as using organic templates. Organically modified silica-gelatin and silica-chitosan hybrids were developed for the first time using alkylalkoxysilanes such as MTMS and VTMS. Application of novel silica-biopolymer antiwetting coatings on different substrates such as glass, leather and textile is also demonstrated in the thesis.

PSWT Based Linear Predictive Coding and Development of a Parallel Multiple Subsequence Structure for DWT Computation

During 1990's the Wavelet Transform emerged as an important signal processing tool with potential applications in time-frequency analysis and non-stationary signal processing.Wavelets have gained popularity in broad range of disciplines like signal/image compression, medical diagnostics, boundary value problems, geophysical signal processing, statistical signal processing,pattern recognition,underwater acoustics etc.In 1993, G. Evangelista introduced the Pitch- synchronous Wavelet Transform, which is particularly suited for pseudo-periodic signal processing.The work presented in this thesis mainly concentrates on two interrelated topics in signal processing,viz. the Wavelet Transform based signal compression and the computation of Discrete Wavelet Transform. A new compression scheme is described in which the Pitch-Synchronous Wavelet Transform technique is combined with the popular linear Predictive Coding method for pseudo-periodic signal processing. Subsequently,A novel Parallel Multiple Subsequence structure is presented for the efficient computation of Wavelet Transform. Case studies also presented to highlight the potential applications.

Polyphenolic Compounds Liberated during Coir Retting in a Bio-reactor: Separation, Characterisation and Possible Applications

School of environmental studies, Cochin University of Science and Technology

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.

Synthesis of Bio-Compatible SPION–based Aqueous Ferrofluids and Evaluation of RadioFrequency Power Loss for Magnetic Hyperthermia

Bio-compatible magnetic fluids having high saturation magnetization find immense applications in various biomedical fields. Aqueous ferrofluids of superparamagnetic iron oxide nanoparticles with narrow size distribution, high shelf life and good stability is realized by controlled chemical co-precipitation process. The crystal structure is verified by X-ray diffraction technique. Particle sizes are evaluated by employing Transmission electron microscopy. Room temperature and low-temperature magnetic measurements were carried out with Superconducting Quantum Interference Device. The fluid exhibits good magnetic response even at very high dilution (6.28 mg/cc). This is an advantage for biomedical applications, since only a small amount of iron is to be metabolised by body organs. Magnetic field induced transmission measurements carried out at photon energy of diode laser (670 nm) exhibited excellent linear dichroism. Based on the structural and magnetic measurements, the power loss for the magnetic nanoparticles under study is evaluated over a range of radiofrequencies.

Bio-chemical changes associated with processing of shell fishes and flavour constituents of body meat and claw meat'of crab

In this thesis all these aspects are taken into consideration. Extensive studies were conducted on all aspects of processing of crabs, mussels and clams. The species taken for studies are commercially used ones namely Scylla sereta, perna viridis, and villorita cyprinoids. In Chapter 4.1 with regard to crab) the following aspects on their handling and processing are reported seasonal variation of chemical constituents, changes taking place during ice storage, freezing, canning etc. In Chapter 4._2 with regard to mussel, the relation between age (size) and chemical constituents, changes taking place during ice storage, freezing, canning etc. are reported and in Chapter 4.3 the changes taking place in clam muscle during icing and freezing are reported and the ame rebility of ice stored clams for canning purpose is reported.The interference of high concentration of glycogen in mussel and clam muscles during the colour development of ribose (Me-jbaum's method) is observed and remedial step are taken to minimise the interference.

Investigations On The Development Of An Ann Model & Visual Manipulation Approach For 2-D Dft Computation In Image Processing

This thesis is an outcome of the investigations carried out on the development of an Artificial Neural Network (ANN) model to implement 2-D DFT at high speed. A new definition of 2-D DFT relation is presented. This new definition enables DFT computation organized in stages involving only real addition except at the final stage of computation. The number of stages is always fixed at 4. Two different strategies are proposed. 1) A visual representation of 2-D DFT coefficients. 2) A neural network approach. The visual representation scheme can be used to compute, analyze and manipulate 2D signals such as images in the frequency domain in terms of symbols derived from 2x2 DFT. This, in turn, can be represented in terms of real data. This approach can help analyze signals in the frequency domain even without computing the DFT coefficients. A hierarchical neural network model is developed to implement 2-D DFT. Presently, this model is capable of implementing 2-D DFT for a particular order N such that ((N))4 = 2. The model can be developed into one that can implement the 2-D DFT for any order N upto a set maximum limited by the hardware constraints. The reported method shows a potential in implementing the 2-D DF T in hardware as a VLSI / ASIC

Investigations on novel polymer nano composites and bio-compatible manganese doped ZnS nanocrystals for photonic and bio-imaging applications

Fluorescence is a powerful tool in biological research, the relevance of which relies greatly on the availability of sensitive and selective fluorescent probes. Nanometer sized fluorescent semiconductor materials have attracted considerable attention in recent years due to the high luminescence intensity, low photobleaching, large Stokes’ shift and high photochemical stability. The optical and spectroscopic features of nanoparticles make them very convincing alternatives to traditional fluorophores in a range of applications. Efficient surface capping agents make these nanocrystals bio-compatible. They can provide a novel platform on which many biomolecules such as DNA, RNA and proteins can be covalently linked. In the second phase of the present work, bio-compatible, fluorescent, manganese doped ZnS (ZnS:Mn) nanocrystals suitable for bioimaging applications have been developed and their cytocompatibility has been assessed. Functionalization of ZnS:Mn nanocrystals by safe materials results in considerable reduction of toxicity and allows conjugation with specific biomolecules. The highly fluorescent, bio-compatible and water- dispersible ZnS:Mn nanocrystals are found to be ideal fluorescent probes for biological labeling

Median computation in graphs using consensus strategies

Following the Majority Strategy in graphs, other consensus strategies, namely Plurality Strategy, Hill Climbing and Steepest Ascent Hill Climbing strategies on graphs are discussed as methods for the computation of median sets of pro¯les. A review of algorithms for median computation on median graphs is discussed and their time complexities are compared. Implementation of the consensus strategies on median computation in arbitrary graphs is discussed

Studies On Strength Characteristics Of Soil Mixed With Bio-Waste

Researches are always in quest for finding innovative methods for ground improvement using sustainable and environmental friendly solutions. Theproduction of large quantity of biowastes all over the world faces serious problems of handling and disposal. Coir pith is a biowaste from coir industry and sugarcane baggase is another biowaste obtained after extractingjuice from sugar cane. So the present study is an investigation into the effect of coir pith and sugarcane baggase on some geotechnical properties of red earth. The investigation includes study on variation of properties such as O.M.C, maximum dry density, C.B.R. values,unconfined compressive strength and permeability when these materials are included in soil. Several conclusions are arrived at, on the basis of the experiments conducted and it may be helpful for predicting the behavior of such soil matrix

Design and Development of Fiber Grating Based Chemical and Bio-Sensors

International School of Photonics

Biochemical Characterization and Bio-evaluation of Collagen and Collagen Peptides Extracted and Purified from Fish Skin: In vitro and In vivo Studies on Antiarthritic and Wound Healing Properties

In fish processing plants, there is huge amount of skin that is left as the waste. When this skin is taken and processed into fish collagen, it will save large amount of money that is used for extraction of collagen from other animal s.Fish collagen can be used as an alternative to replace mammalian collagen, especially collagen extracted from bovine, when we consider the outbreak of bovine spongiform encephalopathy (BSE), transmissible spongiform encephalopathy (TSE) and the foot - and-mouth disease (FMD) issues. BSE and TSE are progressive neurological disorders affecting cattles caused by proteinacious infectious particles called prions.The study aims in producing collagen that has been extracted from fish skin to replace other animal collagen so as to overcome the problem of other animal collagen issues. Also the study utilized the abandoned fish waste produced by fish processing industry since bone, skin, fin and scales of fish can be a useful source of collagen.