Judicial Review of Academic Decisions

This thesis entitled “Judicial review of academic decisions.Education in India is being increasingly controlled and guided by the courts.This study makes an attempt to assess the involvement of the court in regulating education and its role or interference in the conventional concepts of ‘academic freedom’ and ‘university autonomy.The study mostly concentrates on the jurisdiction under Article 226 of the Constitution and its invocation in academic matters with particular reference to the decisions of the Kerala High Court.The concept of judicial review in the Constituent Assembly, initial approach of the Supreme Court of India towards the doctrine, gradual empowerment of Indian judiciary in this area and the resultant judicial activism.The study proceeds through the analysis of ‘academic freedom’ and ‘university autonomy’ in the 4"‘ chapter. This chapter attempts to probe academic freedom and university autonomy in India,England and United States and autonomy of Indian universities before and after independence.Basic principles and the jurisdictional parameters of judicial review in the area of academic decisions, as pronounced by the Apex Court, can be convincingly and consistently followed by the High Courts, which is possible only if special Academic Benches are constituted.

The Steady-State and Transient Characteristic Analysis of Thermal Fixing a Photorefractive Hologram Grating in Lithium Niobate

The transient interaction between a refraction index grating and light beams during simultaneous writing and thermal fixing of a photorefractive hologram is investigated. With a diffusion- and photovoltaic-dominated carrier transport mechanism and carrier thermal activation (temperature dependent) considered in Fe:LiNbO3 crystal, from the standpoint of field-material coupling, the theoretical thermal fixing time and the space-charge field buildup, spatial distribution, and temperature dependence are given numerically by combining the band transport model with mobile ions with the coupled-wave equation

Determination of the nature of the diperiodatocuprate(III) species in aqueous alkaline medium through a kinetic and mechanistic study on the oxidation of iodide ion

The nature of the diperiodatocuprate(III) (DPC) species present in aqueous alkaline medium has been investigated by a kinetic and mechanistic study on the oxidation of iodide by DPC. The reaction kinetics were studied over the 1.0 ´ 10)3±0.1 mol dm)3 alkali range. The reaction order with respect to DPC, as well as iodide, was found to be unity when [DPC] [I)]. In the 1.0 ´ 10)3±1.0 ´ 10)2 mol dm)3 alkali region, the rate decreased with increase in the alkali concentration and a plot of the pseudo-®rst order rate constant, k versus 1/[OH)] was linear. Above 5.0 ´ 10)2 mol dm)3, a plot of k versus [OH)] was also linear with a non-zero intercept. An increase in ionic strength of the reaction mixtures showed no e ect on k at low alkali concentrations, whereas at high concentrations an increase in ionic strength leads to an increase in k. A plot of 1/k versus [periodate] was linear with an intercept in both alkali ranges. Iodine was found to accelerate the reaction at the three di erent alkali concentrations employed. The observed results indicated the following equilibria for DPC.

Transition metal complexes of quinoxaline based Schiff base ligands: Synthesis,characterization and catalytic activity study

Schiff base complexes of transition metal ions have played a significant role in coordination chemistry.The convenient route of synthesis and thermal stability of Schiff base complexes have contributed significantly for their possible applications in catalysis,biology,medicine and photonics.Significant variations in cataltytic activity with structure and type are observed for these complexes.The thesis deals with synthsis and characterization of transition metal complexes of quinoxaline based Schiff base ligands and their catalytic activity study.The Schiff bases synthesized in the present study are quinoxaline-2-carboxalidine-2-amino-5-methylphenol,3-hydroxyquinoxaline-2-carboxalidine-2-amino-5-methylphenol,quinoxaline-2-aminothiophenol.They provide great structural diversity during complexation.To the best of our knowledge, the transition metal complexes of quinoxaline based Schiff bases are poorly utilised in academic and industrial research.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.