Role of trace element of the growth and Physiology of selected microalgae

The main objective of the study is primarily to determine the magnitude of selected trace elements, the concentrations of which would possibly accelerate growth resulting in larger biomass and sustained period of exponential phase for economically viable harvest. The study on the effect of three trace elements namely Cu, Mn and Zn on two species of algae,ISOChrySiS galbana Parke and Synechocystib salina Wislouch under different conditions of salinity, PH and temperature involves several combinations for each metal, from which the relative set of conditions has been adduced. The scheme of the experiments was statistically designed for interpretation of data and factors were assessed and graded according to relative importance. The methodology adopted for data interpretation is analysis of variance by split-plot design method. The thesis has been divided into five chapters. The introductory chapter explains the relevance of the research work undertaken. Chapter 11 gives a review on the work pertaining to the above mentioned three trace elements in relation to nutrition as well as on the toxic aspects about which there is an abundance of literature. Chapter Ill presents a detailed description of the material and specialised methods followed for the study. The results and conclusions of the various experiments on effect of metals on growth and other physiological activities are discussed in Chapters IV and V.

Institutional Repositories: New Horizon of Science & Technology Knowledge Transactions

Today higher education system and R&D in science & Technology has undergone tremendous changes from the traditional class room learning system and scholarly communication. Huge volume of Academic output and scientific communications are coming in electronic format. Knowledge management is a key challenge in the current century .Due to the advancement of ICT, Open access movement, Scholarly communications, Institutional repositories, ontology, semantic web, web 2.0 etc has revolutionized knowledge transactions and knowledge management in the field of science & technology. Today higher education has moved into a stage where competitive advantage is gained not just through access of infonnation but more importantly from new Knowledge creations.This paper examines the role of institutional repository in knowledge transactions in current scenario of Higher education.

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

Handwritten Character Recognition of South Indian Scripts: A Review

Handwritten character recognition is always a frontier area of research in the field of pattern recognition and image processing and there is a large demand for OCR on hand written documents. Even though, sufficient studies have performed in foreign scripts like Chinese, Japanese and Arabic characters, only a very few work can be traced for handwritten character recognition of Indian scripts especially for the South Indian scripts. This paper provides an overview of offline handwritten character recognition in South Indian Scripts, namely Malayalam, Tamil, Kannada and Telungu