Numerical Modelling of Tsunami Propagation in the South East Arabian Sea (SEAS) and Inundation along the Kerala Coast

Tsunamis are water waves generated by a sudden vertical displacement of the water surface. They are waves generated in the ocean by the disturbance associated with seismic activity, under sea volcanic eruptions, submarine landslides, nuclear explosion or meteorite impacts with the ocean. These waves are generated in the ocean and travel into coastal bays, gulfs, estuaries and rivers. These waves travel as gravity waves with a velocity dependent on water depth. The term tsunami is Japanese and means harbour (tsu) and wave (nami). It has been named so because such waves often develop resonant phenomena in harbours after offshore earthquakes.

The Aesthetics Of Paul Verlaine And Changampuzha Krishnapillai - A Comparative Perspective

The present study is entitled The Aesthetics of Paul Verlaine and Changampuzha Krishnapillai - a comparative perspective. The purpose of the study is to compare the poetic genius of the French poet Paul Verlaine (1844-1896) and that of the Malayalam poet Changampuzha Krishnapillai (1911-1948), within a descriptive framework. The investigation will hopefully answer the questions- Has Changampuzha been indeed influenced by Verlaine, if so, to what extent? Can the aesthetic appreciation be justified in both poets as illustrated in their works? The comparative methodology of juxtaposing the selected oeuvres of the poets is largely adopted in the study. Since the span of analysis is across national and linguistic borders, the distinguishing as well as exclusive traits of the individual poets will be of much importance in formulating the comparative assumption in this work. The vastly differing geographical, linguistic and cultural milieus of these two poets,-one a national French poet and the other, a regional Indian poet writing in Malayalam prima facie,endow the theme of the dissertation with an innate hue of diversity. Such an ambitious task would naturally entail a renewed research into the dedication of the poets to their muses and their ultimate contributions to poetics. The analysis, while attempting to illuminate from a fresh angle, the amply researched oeuvre of Verlaine and the lesser studied one of Changampuzha, cannot but be aware of the limitations of the task at hand. The present study is the first of its kind on the specific theme of analysis, and is hoped that it would be of relevance since no work has so far been known to have been undertaken on the topic. At a time when the birth centenary celebrations of Changampuzha have just concluded, this study is hoped to assume significance as it would help in isolating the originality of the poet's works, extricating the garb of the French influence. Ultimately, this study aims at creating a wider appreciation of the impact that the French writers have had on Malayalam writers, thus shedding new light on the benign foreign influences that served to enhance the beauty of our cultural heritage

COMBINED FEATURE EXTRACTION TECHNIQUES AND NAIVE BAYES CLASSIFIER FOR SPEECH RECOGNITION

Speech processing and consequent recognition are important areas of Digital Signal Processing since speech allows people to communicate more natu-rally and efficiently. In this work, a speech recognition system is developed for re-cognizing digits in Malayalam. For recognizing speech, features are to be ex-tracted from speech and hence feature extraction method plays an important role in speech recognition. Here, front end processing for extracting the features is per-formed using two wavelet based methods namely Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Naive Bayes classifier is used for classification purpose. After classification using Naive Bayes classifier, DWT produced a recognition accuracy of 83.5% and WPD produced an accuracy of 80.7%. This paper is intended to devise a new feature extraction method which produces improvements in the recognition accuracy. So, a new method called Dis-crete Wavelet Packet Decomposition (DWPD) is introduced which utilizes the hy-brid features of both DWT and WPD. The performance of this new approach is evaluated and it produced an improved recognition accuracy of 86.2% along with Naive Bayes classifier.

A Comparative Study of Wavelet Based Feature Extraction Techniques in Recognizing Isolated Spoken Words

Speech is a natural mode of communication for people and speech recognition is an intensive area of research due to its versatile applications. This paper presents a comparative study of various feature extraction methods based on wavelets for recognizing isolated spoken words. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. This work includes two speech recognition methods. First one is a hybrid approach with Discrete Wavelet Transforms and Artificial Neural Networks and the second method uses a combination of Wavelet Packet Decomposition and Artificial Neural Networks. Features are extracted by using Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Training, testing and pattern recognition are performed using Artificial Neural Networks (ANN). The proposed method is implemented for 50 speakers uttering 20 isolated words each. The experimental results obtained show the efficiency of these techniques in recognizing speech

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.

Design and Development of a Frame Based MT System for English-to-ISL

This paper presents the design and development of a frame based approach for speech to sign language machine translation system in the domain of railways and banking. This work aims to utilize the capability of Artificial intelligence for the improvement of physically challenged, deaf-mute people. Our work concentrates on the sign language used by the deaf community of Indian subcontinent which is called Indian Sign Language (ISL). Input to the system is the clerk’s speech and the output of this system is a 3D virtual human character playing the signs for the uttered phrases. The system builds up 3D animation from pre-recorded motion capture data. Our work proposes to build a Malayalam to ISL

Intelligent Agent-based Multilingual Information Retrieval System

The goal of this work is to develop an Open Agent Architecture for Multilingual information retrieval from Relational Database. The query for information retrieval can be given in plain Hindi or Malayalam; two prominent regional languages of India. The system supports distributed processing of user requests through collaborating agents. Natural language processing techniques are used for meaning extraction from the plain query and information is given back to the user in his/ her native language. The system architecture is designed in a structured way so that it can be adapted to other regional languages of India

On-Line Handwritten Character Recognition using Kohonen Networks

This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using Kohonen network. It would help in recognizing Malayalam text entered using pen-like devices. It will be more natural and efficient way for users to enter text using a pen than keyboard and mouse. To identify the difference between similar characters in Malayalam a novel feature extraction method has been adopted-a combination of context bitmap and normalized (x, y) coordinates. The system reported an accuracy of 88.75% which is writer independent with a recognition time of 15-32 milliseconds

A COMPARA'l‘IVE STUDY OF FOLK POETRY IN HINDI AND MALAYAIaA.M LITERATURE

HINDI

Mosquito larvae borne viruses from the central travancore region of kerala: isolation and characterization

The present study was initiated when several massive outbreaks of Chikungunya, Dengue and Japanese Encephalitis were frequently reported across the State of Kerala. Multiple symptoms persisted among the affected individuals and the public health officials were in search of aetiological agents responsible for the out breaks and, other than clinical samples no resources were available. In this context, a study was undertaken to focus on mosquito larvae to investigate the viruses borne by them which remain silently prevalent in the environment. The study was not a group specific investigation limited to either arbovirus or enterovirus, but had a broad spectrum approach. The study encompassed the viral pathogens that could be isolated, their impact when passaged through cell lines, growth kinetics, titer of the working stocks in specific cell line, the structure by means of transmission electron microscopy(TEM), the one step growth and molecular characterization using molecular tools.