Science and technology of rubber reclamation with special attention to NR-based waste latex products

A comprehensive overview of reclamation of cured rubber with special emphasis on latex reclamation is depicted in this paper. The latex industry has expanded over the years to meet the world demands for gloves, condoms, latex thread, etc. Due to the strict specifications for the products and the unstable nature of the latex as high as 15% of the final latex products are rejected. As waste latex rubber (WLR) represents a source of high-quality rubber hydrocarbon, it is a potential candidate for generating reclaimed rubber of superior quality. The role of the different components in the reclamation recipe is explained and the reaction mechanism and chemistry during reclamation are discussed in detail. Different types of reclaiming processes are described with special reference to processes, which selectively cleave the cross links in the vulcanized rubber. The state-of-the-art techniques of reclamation with special attention on latex treatment are reviewed. An overview of the latest development concerning the fundamental studies in the field of rubber recycling by means of low-molecular weight compounds is described. A mathematical model description of main-chain and crosslink scission during devulcanization of a rubber vulcanizate is also given.

Design And Development Of A Named Entity Based Question Answering System For Malayalam Language

This is a Named Entity Based Question Answering System for Malayalam Language. Although a vast amount of information is available today in digital form, no effective information access mechanism exists to provide humans with convenient information access. Information Retrieval and Question Answering systems are the two mechanisms available now for information access. Information systems typically return a long list of documents in response to a user’s query which are to be skimmed by the user to determine whether they contain an answer. But a Question Answering System allows the user to state his/her information need as a natural language question and receives most appropriate answer in a word or a sentence or a paragraph. This system is based on Named Entity Tagging and Question Classification. Document tagging extracts useful information from the documents which will be used in finding the answer to the question. Question Classification extracts useful information from the question to determine the type of the question and the way in which the question is to be answered. Various Machine Learning methods are used to tag the documents. Rule-Based Approach is used for Question Classification. Malayalam belongs to the Dravidian family of languages and is one of the four major languages of this family. It is one of the 22 Scheduled Languages of India with official language status in the state of Kerala. It is spoken by 40 million people. Malayalam is a morphologically rich agglutinative language and relatively of free word order. Also Malayalam has a productive morphology that allows the creation of complex words which are often highly ambiguous. Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker, Named Entity Tagger, and Compound Word Splitter are developed as a part of this research work. No such tools were available for Malayalam language. Finite State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the design of these document preprocessing tools. This research work describes how the Named Entity is used to represent the documents. Single sentence questions are used to test the system. Overall Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be extended in several directions. The coverage of non-factoid questions can be increased and also it can be extended to include open domain applications. Reference Resolution and Word Sense Disambiguation techniques are suggested as the future enhancements