Development of Hierarchical Clustering Techniques for Gridded Data from Mixed Data Sequences

Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially useful and ultimately understandable patterns from data. The term Data mining refers to the process which does the exploratory analysis on the data and builds some model on the data. To infer patterns from data, data mining involves different approaches like association rule mining, classification techniques or clustering techniques. Among the many data mining techniques, clustering plays a major role, since it helps to group the related data for assessing properties and drawing conclusions. Most of the clustering algorithms act on a dataset with uniform format, since the similarity or dissimilarity between the data points is a significant factor in finding out the clusters. If a dataset consists of mixed attributes, i.e. a combination of numerical and categorical variables, a preferred approach is to convert different formats into a uniform format. The research study explores the various techniques to convert the mixed data sets to a numerical equivalent, so as to make it equipped for applying the statistical and similar algorithms. The results of clustering mixed category data after conversion to numeric data type have been demonstrated using a crime data set. The thesis also proposes an extension to the well known algorithm for handling mixed data types, to deal with data sets having only categorical data. The proposed conversion has been validated on a data set corresponding to breast cancer. Moreover, another issue with the clustering process is the visualization of output. Different geometric techniques like scatter plot, or projection plots are available, but none of the techniques display the result projecting the whole database but rather demonstrate attribute-pair wise analysis

Development of Electrochemical and Fluorescent Sensors

Chemical sensors have growing interest in the determination of food additives, which are creating toxicity and may cause serious health concern, drugs and metal ions. A chemical sensor can be defined as a device that transforms chemical information, ranging from the concentration of a specific sample component to total composition analysis, into an analytically useful signal. The chemical information may be generated from a chemical reaction of the analyte or from a physical property of the system investigated. Two main steps involved in the functioning of a chemical sensor are recognition and transduction. Chemical sensors employ specific transduction techniques to yield analyte information. The most widely used techniques employed in chemical sensors are optical absorption, luminescence, redox potential etc. According to the operating principle of the transducer, chemical sensors may be classified as electrochemical sensors, optical sensors, mass sensitive sensors, heat sensitive sensors etc. Electrochemical sensors are devices that transform the effect of the electrochemical interaction between analyte and electrode into a useful signal. They are very widespread as they use simple instrumentation, very good sensitivity with wide linear concentration ranges, rapid analysis time and simultaneous determination of several analytes. These include voltammetric, potentiometric and amperometric sensors. Fluorescence sensing of chemical and biochemical analytes is an active area of research. Any phenomenon that results in a change of fluorescence intensity, anisotropy or lifetime can be used for sensing. The fluorophores are mixed with the analyte solution and excited at its corresponding wavelength. The change in fluorescence intensity (enhancement or quenching) is directly related to the concentration of the analyte. Fluorescence quenching refers to any process that decreases the fluorescence intensity of a sample. A variety of molecular rearrangements, energy transfer, ground-state complex formation and collisional quenching. Generally, fluorescence quenching can occur by two different mechanisms, dynamic quenching and static quenching. The thesis presents the development of voltammetric and fluorescent sensors for the analysis of pharmaceuticals, food additives metal ions. The developed sensors were successfully applied for the determination of analytes in real samples. Chemical sensors have multidisciplinary applications. The development and application of voltammetric and optical sensors continue to be an exciting and expanding area of research in analytical chemistry. The synthesis of biocompatible fluorophores and their use in clinical analysis, and the development of disposable sensors for clinical analysis is still a challenging task. The ability to make sensitive and selective measurements and the requirement of less expensive equipment make electrochemical and fluorescence based sensors attractive.