Equality of Opportunity in Public Employment : Judicial Perspectives on Backwardness

This thesis is a study of -Equality of Opportunity in Public Employment : Judicial Perspectives on Backwardness. This study is an attempt to evaluate the concept of backwardness and equality of opportunity in employment and to assess the judicial perspectives in relation to them. The study reveals that the recent review petition of the Constitution Bench did not assess the decision of Chakradhar and its import. The study reveals that the Indian judiciary could successfully locate and apply the above principles. It was-Justice Subba Rao's nascent attempt in Devadasan which marked the starting point of such a jurisprudential enquiry. Later Thomas developed the thoughts by a reading new meaning and content to equality provisions of the Constitution which included the elimination of inequalities as the positive content of Articles 14 and 16(1) and elevated reservation provision to the same status of equality principles under the Constitution. Soshit, Vasanth Kumar and Mandal supplemented further to the jurisprudential contents. In this process, the courts were guided by the theories of John Rawls, David Miller, Ronald Dworkin, Max Weber and Roscoe Pound. Thus there was a slow and steady process of transformation of the reservation provision. From an anti-meritarian, unenforceable and enabling provision, it reached a stage of equally relevant and explanatory part of fundamental right to equality. Mandal viewed it as a part of sharing of State power. Though this can be seen by rereading and re-joining thoughts of judges in this regard, the judicial approach lacks coherence and concerted efforts in evolving a jurisprudential basis for protective discrimination. The deliberations of the framers of the Constitution reveals that there was much confusion and indeterminacy with regard to the concept of Backwardness. The study shows that the judiciary has been keeping intact the framers’ expectation of having a reasonable quantum of reservation, preventing the undeserved sections from enjoying the benefit, avoiding its abuse and evolving a new criteria and rejecting the old ones.

Studies On The Synthesis Of Vitamin A And Related Compounds

In the present work different new approaches for the synthesis of Vitamin A are investigated. In these synthetic schemes, all the twenty carbon atoms of the target molecule are derived either fully from components isolated from common essential oils or partially from commercially available materials. By retrosynthetic analysis, Vitamin A molecule can be disconnected into a cyclic and a linear unit. Different methods for the synthesis of the linear and the cyclic components are described. The monoterpenes, geraniol and citral, major constituents of palmarosa and lemongrass oils, have the required basic carbon framework for consideration as starting materials for the synthesis of Vitamin A. The potential of these easily available naturally occurring compounds as promising starting materials for Vitamin A synthesis is demonstrated. Organoselenium and organosulfur mediated functional group transformations for the synthesis of the functionalised conjugated C10 linear components (ie., the dimethyloctatriene derivatives) are reported. The classical approaches as well as the attempted preparation of cyclic C10 and C13 units employed in the present study as intermediates for Vitamin A synthesis are described. The utility of commercially available materials namely 2-acetylbutyrolactone and levulinic acid in -the preparation of C5 intermediates for Vitamin A synthesis is demonstrated.

Studies on a syntax based approach for translation between structurally different languages and the development of a prototype for Malayalam to English translation

This thesis summarizes the results on the studies on a syntax based approach for translation between Malayalam, one of Dravidian languages and English and also on the development of the major modules in building a prototype machine translation system from Malayalam to English. The development of the system is a pioneering effort in Malayalam language unattempted by previous researchers. The computational models chosen for the system is first of its kind for Malayalam language. An in depth study has been carried out in the design of the computational models and data structures needed for different modules: morphological analyzer , a parser, a syntactic structure transfer module and target language sentence generator required for the prototype system. The generation of list of part of speech tags, chunk tags and the hierarchical dependencies among the chunks required for the translation process also has been done. In the development process, the major goals are: (a) accuracy of translation (b) speed and (c) space. Accuracy-wise, smart tools for handling transfer grammar and translation standards including equivalent words, expressions, phrases and styles in the target language are to be developed. The grammar should be optimized with a view to obtaining a single correct parse and hence a single translated output. Speed-wise, innovative use of corpus analysis, efficient parsing algorithm, design of efficient Data Structure and run-time frequency-based rearrangement of the grammar which substantially reduces the parsing and generation time are required. The space requirement also has to be minimised

Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations