Design and Development of an Adaptable Frame -Based System for Dravidian Language Processing

This work is aimed at building an adaptable frame-based system for processing Dravidian languages. There are about 17 languages in this family and they are spoken by the people of South India.Karaka relations are one of the most important features of Indian languages. They are the semabtuco-syntactic relations between verbs and other related constituents in a sentence. The karaka relations and surface case endings are analyzed for meaning extraction. This approach is comparable with the borad class of case based grammars.The efficiency of this approach is put into test in two applications. One is machine translation and the other is a natural language interface (NLI) for information retrieval from databases. The system mainly consists of a morphological analyzer, local word grouper, a parser for the source language and a sentence generator for the target language. This work make contributios like, it gives an elegant account of the relation between vibhakthi and karaka roles in Dravidian languages. This mapping is elegant and compact. The same basic thing also explains simple and complex sentence in these languages. This suggests that the solution is not just ad hoc but has a deeper underlying unity. This methodology could be extended to other free word order languages. Since the frame designed for meaning representation is general, they are adaptable to other languages coming in this group and to other applications.

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

Comparison of Statistical and Semantic Similarity Techniques for Paraphrase Identification

This paper compares statistical technique of paraphrase identification to semantic technique of paraphrase identification. The statistical techniques used for comparison are word set and word-order based methods where as the semantic technique used is the WordNet similarity matrix method described by Stevenson and Fernando in [3].

Investigations on Eco-friendly Natural Insecticides

Instead of developing easily degradable, and low-priced insecticides, we are going after highly sophisticated chemicals. Here, an attempt is being made to develop safer formulations of insecticides of botanical origin. Different parts of the plants were chosen based on their use in countryside and villages The dried plant materials were extracted with petroleum ether, and were applied on Tribolium castaneum. The results were statistically analysed. The active principles from Croton tigilium and Leea sambucina, the most potential plants, were isolated using Column Chromatography, TLC, and Hydrolysis. The isolated principles were analysed spectroscopically ( UV-Vis., IR, NMR, and MS ) to identify their chemical nature. The active principles from Leea and Croton were identified as a cholisterate derivative and a phorbol derivative respectively. In order to ascertain the environmental combatibility of the principles, degradation by soil bacteria was studied. The isolated principles were made into three type of formulations using stabilizers .The formulations were applied on Snake gourd semilooper, Pulse beetle, and mosquito larvae. Also the biocidal activity of the formulations was studied. Both Leea derivative and Croton derivative could be formulated effectively and were effective against a variety of pests. They are eco-friendly, as there is no artificial chemicals involved.

Tailoring Magnetic, Mechanical and Dielectric Properties of Magnetorheological Elastomers based on Natural Rubber and Iron by Magnetic Field Assisted Curing for Possible Applications

If magnetism is universal in nature, magnetic materials are ubiquitous. A life without magnetism is unthinkable and a day without the influence of a magnetic material is unimaginable. They find innumerable applications in the form of many passive and active devices namely, compass, electric motor, generator, microphone, loud speaker, maglev train, magnetic resonance imaging, data recording and reading, hadron collider etc. The list is endless. Such is the influence of magnetism and magnetic materials in ones day to day life. With the advent of nanoscience and nanotechnology, along with the emergence of new areas/fields such as spintronics, multiferroics and magnetic refrigeration, the importance of magnetism is ever increasing and attracting the attention of researchers worldwide. The search for a fluid which exhibits magnetism has been on for quite some time. However nature has not bestowed us with a magnetic fluid and hence it has been the dream of many researchers to synthesize a magnetic fluid which is thought to revolutionize many applications based on magnetism. The discovery of a magnetic fluid by Jacob Rabinow in the year 1952 paved the way for a new branch of Physics/Engineering which later became magnetic fluids. This gave birth to a new class of material called magnetorheological materials. Magnetorheological materials are considered superior to electrorheological materials in that magnetorheology is a contactless operation and often inexpensive.Most of the studies in the past on magnetorheological materials were based on magnetic fluids. Recently the focus has been on the solid state analogue of magnetic fluids which are called Magnetorheological Elastomers (MREs). The very word magnetorheological elastomer implies that the rheological properties of these materials can be altered by the influence of an external applied magnetic field and this process is reversible. If the application of an external magnetic field modifies the viscosity of a magnetic fluid, the effect of external magnetic stimuli on a magnetorheological elastomer is in the modification of its stiffness. They are reversible too. Magnetorheological materials exhibit variable stiffness and find applications in adaptive structures of aerospace, automotive civil and electrical engineering applications. The major advantage of MRE is that the particles are not able to settle with time and hence there is no need of a vessel to hold it. The possibility of hazardous waste leakage is no more with a solid MRE. Moreover, the particles in a solid MRE will not affect the performance and durability of the equipment. Usually MR solids work only in the pre yield region while MR fluids, typically work in the post yield state. The application of an external magnetic field modifies the stiffness constant, shear modulus and loss modulus which are complex quantities. In viscoelastic materials a part of the input energy is stored and released during each cycle and a part is dissipated as heat. The storage modulus G′ represents the capacity of the material to store energy of deformation, which contribute to material stiffness. The loss modulusG′′ represents the ability of the material to dissipate the energy of deformation. Such materials can find applications in the form of adaptive vibration absorbers (ATVAs), stiffness tunable mounts and variable impedance surfaces. MREs are an important material for automobile giants and became the focus of this research for eventual automatic vibration control, sound isolation, brakes, clutches and suspension systems