Development of energy saving forms of natural rubber

Although the physical and technological properties of modified rubbers were compared with those of conventional rubbers in the earlier studies reviewed above, the extent of energy saving possible by their use has not been quantified. In the present work it is proposed to determine the energy saving possible by using the following forms of natural rubber: 1. Oil extended natural rubber, 2. peptised natural rubber, 3. latex stage compounds. The process of production and quality control of the above types of processed rubbers are proposed to be standardised. It is also planned to work out a methodology for utilising field coagula for production of constant viscosity rubbers. The variation in processing properties of rubber from popular Indian clones will be examined and those with energy advantages in the processing stage will be identified. In conclusion a recommendation for adoption of a commercially advantageous processing procedure among Indian rubber plantation industry is also given.

Molecular breakdown of different forms of natural rubber and its influence on properties of their mixes and vulcanizates

The forms of natural rubber studied were sheet [RSS 4 and RSS 5], ISNR 20 and EBC. In the case of the latter two forms samples from estate and nonestate sectors were included. The samples were collected from different locations at specified intervals, for a particular period. The effect of the extent of mastication on raw rubber properties as well as the properties of the compounds and vulcanizates also studied. The consistency in raw rubber properties and breakdown behavior of skim rubber were studied by collecting samples periodically from selected processing units. The effect of incorporation of skim with ISNR 20 has also been investigated

Waste Water Treatment Using Low Cost Natural Adsorbents

Heavy metals are major toxic pollutants with severe health effects on humans. They are released into the environment from a variety of industrial activities. Cadmium, lead, zinc, chromium and copper are the most toxic metals of widespread use in industries such as tanning, electroplating, electronic equipment manufacturing and chemical processing plants. Heavy metals contribute to a variety of adverse health environmental effects due to their acute and chronic exposure through air, water and food chain. Conventional treatment methods of metal removal are often limited by their cost and ineffectiveness at low concentrations. Adsorption, the use of inactivated biomass as adsorbents offers an attractive potential alternative to their conventional methods. Mango peel and Alisma plantago aquatica are naturally occurring and abundant biomass can offer an economical solution for metal removal.The Cd(II), Pb(II), Zn(II), Cr(III) and Cu(II) adsorption by milled adsorbents of mango peel and Alisma plantago aquatica were evaluated in batches.

A Hybrid Architecture for Recognising Speech Signals in Malayalam

Speech is the primary, most prominent and convenient means of communication in audible language. Through speech, people can express their thoughts, feelings or perceptions by the articulation of words. Human speech is a complex signal which is non stationary in nature. It consists of immensely rich information about the words spoken, accent, attitude of the speaker, expression, intention, sex, emotion as well as style. The main objective of Automatic Speech Recognition (ASR) is to identify whatever people speak by means of computer algorithms. This enables people to communicate with a computer in a natural spoken language. Automatic recognition of speech by machines has been one of the most exciting, significant and challenging areas of research in the field of signal processing over the past five to six decades. Despite the developments and intensive research done in this area, the performance of ASR is still lower than that of speech recognition by humans and is yet to achieve a completely reliable performance level. The main objective of this thesis is to develop an efficient speech recognition system for recognising speaker independent isolated words in Malayalam.