Investigations on some technologically important polymer nanocomposite films and semi crystalline Polypyrrole films

The present work deals with investigations on some technologically important polymer nanocomposite films and semi crystalline polypyrrole films.The work presented in the thesis deals with the realization of novel polymer nanocomposites with enhanced functionalities and prospects of applications in the fields related to nanophotonics. The development of inorganic/polymer nanocomposites is a rapidly expanding multidisciplinary research area with profound industrial applications. The incorporation of suitable inorganic nanoparticles can endow the resulting nanocomposites with excellent electrical, optical and mechanical properties. The first chapter gives a general introduction to nanotechnology, nanocomposites and conducting polymers. It also emphasizes the significance of ZnO among other semiconductor materials, which forms the inorganic filler in the polymer nanocomposites of the present study. This chapter also gives general ideas on the properties and applications of conducting polymers with special reference to polypyrrole. The objectives of the present investigations are also clearly addressed in this chapter. The second chapter deals with the theoretical aspects and details of all the experimental techniques used in the present work for the synthesis of polymer nanocomposites and polypyrrole samples and their various characterizations. Chapter 3 is based on the preparation and properties of ZnO/Polystyrene nanocomposite film samples. The optical properties of these nanocomoposite films are discussed in detail.Chapter 4 deals with the detailed investigations on the dependence of the optical properties of ZnO/PS nanocomposite films on the size of the nanostructured ZnO filler material. The excellent UV shielding properties of these nanocomposite films form the highlight of this chapter. Chapter 5 gives a detailed analysis of the nonlinear optical properties of ZnO/PS nanocomposite films using Z scan technique. The effect of ZnO particle size in the composite films on the nonlinear properties is discussed. The present study involves two phases of research activities. In the first phase, the linear and nonlinear optical properties of ZnO/polymer nanocomposites are investigated in detail. The second phase of work is centered on the synthesis and related studies on highly crystalline polypyrrole films. In the present study, nanosized ZnO is synthesized using wet chemical method at two different temperatures

Global Value Chain Linkages of Manufacturing Export Firms: A Study of The Kannur Home Textile Industry

The literature on the involvement of developing countries in trade has focused on the effects of different aspects of globalization on firms, regions and countries. The study attempts to examine how an export based industry, locallyembedded and originated on the basis of regional strengths has been inserted into the global trade framework. Though the unit of analysis is the manufacturing export firm in the region of Kannur, it represents the entire home textile export industry from the state of Kerala, as close to 90% of fabric exports in home furnishing material, textiles for upholstery and decoration and stitched or fused, and branded made ups are from the region. From a global perspective, how developing countries face newer trade restrictions and overcome non quota barriers by firm and region specific activities within a value chain framework is a major research area, which has already contributions from the Ludhiana woolen cluster (Tewari,1999 ) and the Tirupur cluster in India (Cawthorne, 1995). The study contributes to the value chain literature by examining the governance and upgrading as well as how firms benefit from linkages. India has a number of export oriented agglomerations or regions where firms have been serving export markets for many years. In many cases it is no longer the supply side policy actions that determine how they are able to penetrate new markets or expand existing market share. Based on this study it becomes possible to understand how the global value chain operates in these different industries to examine whether there is a danger of immiserisation of growth or low road growth

Chemically Modified Glassy Carbon Electrode as Sensors for Various Pharmaceuticals

Voltammetric methods are applicable for the determination of a wide variety of both organic and inorganic species. Its features are compact equipment, simple sample preparation, short analysis time, high accuracy and sensitivity. Voltammetry is especially suitable for laboratories in which only a few parameters have to be monitored with a moderate sample throughput. Of various electrode materials, glassy carbon electrode is particularly useful because of its high electrical conductivity, impermeability to gases, high chemical resistance, reasonable mechanical and dimensional stability and widest potential range of all carbonaceous electrodes. Electrode modification is a vigorous research area by which the electrochemical determination of various analyte species is facilitated. The scope of pharmaceutical analysis includes the analytical investigation of pure drug, drug formulations, impurities and degradation products of drugs, biological samples containing the drugs and their metabolites with the aim of obtaining data that can contribute to the maximal efficacy and maximal safety of drug therapy. This thesis presents the modification of glassy carbon electrode using metalloporphyrin and dyes and subsequently using these modified electrodes for the determination of various pharmaceuticals. The thesis consists of 9 chapters.

classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing