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.

Laser Spectroscopy: TDLAS instrumentation and NIR analysis of some organic materials

Near-infrared spectroscopy can be a workhorse technique for materials analysis in industries such as agriculture, pharmaceuticals, chemicals and polymers. A near-infrared spectrum represents combination bands and overtone bands that are harmonics of absorption frequencies in the mid-infrared. Near-infrared absorption includes a combination-band region immediately adjacent to the mid-infrared and three overtone regions. All four near-infrared regions contain "echoes" of the fundamental mid-infrared absorptions. For example, vibrations in the mid-infrared due to the C-H stretches will produce four distinct bands in each of the overtone and combination regions. As the bands become more removed from the fundamental frequencies they become more widely separated from their neighbors, more broadened and are dramatically reduced in intensity. Because near-infrared bands are much less intense, more of the sample can be used to produce a spectra and with near-infrared, sample preparation activities are greatly reduced or eliminated so more of the sample can be utilized. In addition, long path lengths and the ability to sample through glass in the near-infrared allows samples to be measured in common media such as culture tubes, cuvettes and reaction bottles. This is unlike mid-infrared where very small amounts of a sample produce a strong spectrum; thus sample preparation techniques must be employed to limit the amount of the sample that interacts with the beam. In the present work we describe the successful the fabrication and calibration of a linear high resolution linear spectrometer using tunable diode laser and a 36 m path length cell and meuurement of a highly resolved structure of OH group in methanol in the transition region A v =3. We then analyse the NIR spectrum of certain aromatic molecules and study the substituent effects using local mode theory

Automated synthesis of delay-reduced Reed-Muller universal logic module networks

This paper presents a new approach to implement Reed-Muller Universal Logic Module (RM-ULM) networks with reduced delay and hardware for synthesizing logic functions given in Reed-Muller (RM) form. Replication of single control line RM-ULM is used as the only design unit for defining any logic function. An algorithm is proposed that does exhaustive branching to reduce the number of levels and modules required to implement any logic function in RM form. This approach attains a reduction in delay, and power over other implementations of functions having large number of variables.

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

Automated Transcription System for Malayalam Language

Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction. It is trained with 21 male and female speakers in the age group ranging from 20 to 40 years. The system obtained a word recognition accuracy of 87.4% and a sentence recognition accuracy of 84%, when tested with a set of continuous speech data.