Induction of Mitotic Chromosomal Aberrations by Lasers in Comparison to Gamma Radiations

Laser irradiation at wavelength 514 nm was used to study the effect, of lasers in inducing chromosomal aberrations at mitosis. This study offers a new radiation system which could be used for the induction of mutations. Results are compared with those obtained from studies using y-rays as irradiation source.

A compact dual-band modified T-shaped CPW-fed monopole antenna

A compact, dual band coplanar waveguide fed modified T-shaped uniplanar antenna is presented. The antenna has resonances at 1.77 and 5.54 GHz with a wide band from 1.47–1.97 GHz and from 5.13–6.48 GHz with an impedance bandwidth of 34% and 26%, respectively. Also the antenna has an average gain of 3 dBi in lower band and 3.5 dBi in higher band with an average efficiency of 90%.

ACS fed printed F-shaped uniplanar antenna for dual band WLAN applications

An asymmetric coplanar strip (ACS) fed dual band F-shaped antenna covering the 2.4/5.2 GHz WLAN bands is presented. The optimized dimensions of the proposed uniplanar antenna are 21 mm × 19 mm when printed on a substrate of dielectric constant 4.4 and height 1.6 mm. The dual band nature of the antenna is brought about by the various current paths in the F-shaped structure and the ground plane. The antenna exhibits nearly omnidirectional radiation characteristics and moderate gain in both the operating bands. Details of the antenna design, simulation, and experimental results are presented and discussed.

C-shaped slot loaded reconfigurable microstrip antenna

A new electronically reconfigurable dual frequency microstrip patch antenna with highly simplified varactor tuning circuitry is presented. The proposed design allows relatively independent selection of the two operating frequencies. Tuning ranges of 7.1 and 4.1% are realised for the two resonant frequencies without the use of any matching circuits.

Constraining the active tectonic deformation of Andaman-Nicobar Arc in the background of December 26,2004 Great Sumatra-Andaman Earthquake

The Andaman-Nicobar Islands in the Bay of Bengal lies in a zone where the Indian plate subducts beneath the Burmese microplate, and therefore forms a belt of frequent earthquakes. Few efforts, not withstanding the available historical and instrumental data were not effectively used before the Mw 9.3 Sumatra-Andaman earthquake to draw any inference on the spatial and temporal distribution of large subduction zone earthquakes in this region. An attempt to constrain the active crustal deformation of the Andaman-Nicobar arc in the background of the December 26, 2004 Great Sumatra-Andaman megathrust earthquake is made here, thereby presenting a unique data set representing the pre-seismic convergence and co-seismic displacement.Understanding the mechanisms of the subduction zone earthquakes is both challenging sCientifically and important for assessing the related earthquake hazards. In many subduction zones, thrust earthquakes may have characteristic patterns in space and time. However, the mechanism of mega events still remains largely unresolved.Large subduction zone earthquakes are usually associated with high amplitude co-seismic deformation above the plate boundary megathrust and the elastic relaxation of the fore-arc. These are expressed as vertical changes in land level with the up-dip part of the rupture surface uplifted and the areas above the down-dip edge subsided. One of the most characteristic pattern associated with the inter-seismic era is that the deformation is in an opposite sense that of co-seismic period.This work was started in 2002 to understand the tectonic deformation along the Andaman-Nicobar arc using seismological, geological and geodetic data. The occurrence of the 2004 megathrust earthquake gave a new dimension to this study, by providing an opportunity to examine the co-seismic deformation associated with the greatest earthquake to have occurred since the advent of Global Positioning System (GPS) and broadband seismometry. The major objectives of this study are to assess the pre-seismic stress regimes, to determine the pre-seismic convergence rate, to analyze and interpret the pattern of co-seismic displacement and slip on various segments and to look out for any possible recurrence interval for megathrust event occurrence for Andaman-Nicobar subduction zone. This thesis is arranged in six chapters with further subdivisions dealing all the above aspects.

Geodynamics of the Andaman - Sumatra - Java Trench - Arc System Based on Gravity and Seismotectonic Study

This work aims to study the variation in subduction zone geometry along and across the arc and the fault pattern within the subducting plate. Depth of penetration as well as the dip of the Benioff zone varies considerably along the arc which corresponds to the curvature of the fold- thrust belt which varies from concave to convex in different sectors of the arc. The entire arc is divided into 27 segments and depth sections thus prepared are utilized to investigate the average dip of the Benioff zone in the different parts of the entire arc, penetration depth of the subducting lithosphere, the subduction zone geometry underlying the trench, the arctrench gap, etc.The study also describes how different seismogenic sources are identified in the region, estimation of moment release rate and deformation pattern. The region is divided into broad seismogenic belts. Based on these previous studies and seismicity Pattern, we identified several broad distinct seismogenic belts/sources. These are l) the Outer arc region consisting of Andaman-Nicobar islands 2) the back-arc Andaman Sea 3)The Sumatran fault zone(SFZ)4)Java onshore region termed as Jave Fault Zone(JFZ)5)Sumatran fore arc silver plate consisting of Mentawai fault(MFZ)6) The offshore java fore arc region 7)The Sunda Strait region.As the Seismicity is variable,it is difficult to demarcate individual seismogenic sources.Hence, we employed a moving window method having a window length of 3—4° and with 50% overlapping starting from one end to the other. We succeeded in defining 4 sources each in the Andaman fore arc and Back arc region, 9 such sources (moving windows) in the Sumatran Fault zone (SFZ), 9 sources in the offshore SFZ region and 7 sources in the offshore Java region. Because of the low seismicity along JFZ, it is separated into three seismogenic sources namely West Java, Central Java and East Java. The Sunda strait is considered as a single seismogenic source.The deformation rates for each of the seismogenic zones have been computed. A detailed error analysis of velocity tensors using Monte—Carlo simulation method has been carried out in order to obtain uncertainties. The eigen values and the respective eigen vectors of the velocity tensor are computed to analyze the actual deformation pattem for different zones. The results obtained have been discussed in the light of regional tectonics, and their implications in terms of geodynamics have been enumerated.ln the light of recent major earthquakes (26th December 2004 and 28th March 2005 events) and the ongoing seismic activity, we have recalculated the variation in the crustal deformation rates prior and after these earthquakes in Andaman—Sumatra region including the data up to 2005 and the significant results has been presented.ln this chapter, the down going lithosphere along the subduction zone is modeled using the free air gravity data by taking into consideration the thickness of the crustal layer, the thickness of the subducting slab, sediment thickness, presence of volcanism, the proximity of the continental crust etc. Here a systematic and detailed gravity interpretation constrained by seismicity and seismic data in the Andaman arc and the Andaman Sea region in order to delineate the crustal structure and density heterogeneities a Io nagnd across the arc and its correlation with the seismogenic behaviour is presented.

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.

Modifications of secondary reflector antenna patterns due to shaped beams from flanged primary horn feeds

With the advent of satellite communication and radio astronomy, the need for large and efficient reflector antennas had triggered a widespread investigation in reflector feed design techniques. Major improvements sought are reduction in spill-over, cross polarization losses and the enhancement of aperture efficiency. The search for such a feed culminated in the corrugated horn. The main idea behind the present work is to use the H-plane sectoral horns fitted with,corrugated flanges as feeds of a paraboloid and see how the secondary pattern of the reflector antenna varies with different parameters of the feed. An offset paraboloid is used as the secondary reflector in order to avoid the adverse effect of aperture ‘blocking by the feed horn structure on the secondary radiation pattern. The measurements were repeated for three different H-plane sectoral horns with the same set of corrugated flanges at various X-band frequencies. The following parameters of the whole system are studied: (a) Beam shaping. (b) Gain. (c) Variation of VSWR and (d) Cross polarization

Studies on the induction of variation through in vitro culture in Jatropha curcas L

Given the economic importance of Jatropha curcas, and its limited availability in the wild, it would be desirable to establish plantations ofthe tree so as to obtain assured supply of raw material for extraction of phytochemicals, and seeds for production of biodiesel. However both seed propagation as well as propagation by cuttings is unsatisfactory in this tree species. Seeds have poor viability and are genetically heterozygous leading to genetic variability in terms of growth, biomass, seed yield, and oil content. Stern cuttings have poor roots and the trees are easily uprooted. Tissue culture techniques could possibly be gainfully employed in the propagation of elite plants ofJaIropha. When plant tissue is passaged through in vitro culture, there is possibility of induction of variations. An estimation of somaclonal variability is useful in a determination of culture protocols. Molecular markers could be employed to estimate the amount of variations induced in callus and regenerants by different honnonal combinations used in culture. In this context the present study aims to develop an in vitro propagation protocol for the production of plantlets and to evaluate the variation induced in callus and regenerants in comparison with mother plant by the use of molecular markers and by studying phytochemicals and bio active compounds present in callus and regenerated plants

Syntactic Based Machine Translation from English to Malayalam

Due to the emergence of multiple language support on the Internet, machine translation (MT) technologies are indispensable to the communication between speakers using different languages. Recent research works have started to explore tree-based machine translation systems with syntactical and morphological information. This work aims the development of Syntactic Based Machine Translation from English to Malayalam by adding different case information during translation. The system identifies general rules for various sentence patterns in English. These rules are generated using the Parts Of Speech (POS) tag information of the texts. Word Reordering based on the Syntax Tree is used to improve the translation quality of the system. The system used Bilingual English –Malayalam dictionary for translation.

A Framework of Statistical Machine Translator from English to Malayalam

In this paper we describe the methodology and the structural design of a system that translates English into Malayalam using statistical models. A monolingual Malayalam corpus and a bilingual English/Malayalam corpus are the main resource in building this Statistical Machine Translator. Training strategy adopted has been enhanced by PoS tagging which helps to get rid of the insignificant alignments. Moreover, incorporating units like suffix separator and the stop word eliminator has proven to be effective in bringing about better training results. In the decoder, order conversion rules are applied to reduce the structural difference between the language pair. The quality of statistical outcome of the decoder is further improved by applying mending rules. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics

Handling OOV Words in Phrase-Based Statistical Machine Translation for Malayalam

Statistical Machine Translation (SMT) is one of the potential applications in the field of Natural Language Processing. The translation process in SMT is carried out by acquiring translation rules automatically from the parallel corpora. However, for many language pairs (e.g. Malayalam- English), they are available only in very limited quantities. Therefore, for these language pairs a huge portion of phrases encountered at run-time will be unknown. This paper focuses on methods for handling such out-of-vocabulary (OOV) words in Malayalam that cannot be translated to English using conventional phrase-based statistical machine translation systems. The OOV words in the source sentence are pre-processed to obtain the root word and its suffix. Different inflected forms of the OOV root are generated and a match is looked up for the word variants in the phrase translation table of the translation model. A Vocabulary filter is used to choose the best among the translations of these word variants by finding the unigram count. A match for the OOV suffix is also looked up in the phrase entries and the target translations are filtered out. Structuring of the filtered phrases is done and SMT translation model is extended by adding OOV with its new phrase translations. By the results of the manual evaluation done it is observed that amount of OOV words in the input has been reduced considerably

Extension schemes for the Alignment Model of English-Malayalam Statistical Machine Translator

In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam sentence using statistical models. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set among the sentence pairs of the source and target language before subjecting them for training. This paper deals with certain techniques which can be adopted for improving the alignment model of SMT. Methods to incorporate the parts of speech information into the bilingual corpus has resulted in eliminating many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Presence of Malayalam words with predictable translations has also contributed in reducing the insignificant alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics.

Techniques to Improve the word alignments in Statistical Machine Translation from English to Malayalam

In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam translation using statistical models like translation model, language model and a decoder. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set up among the sentence pairs of the source and target language before subjecting them for training. This paper is deals with the techniques which can be adopted for improving the alignment model of SMT. Incorporating the parts of speech information into the bilingual corpus has eliminated many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics

Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective