Comparison of Statistical and Semantic Similarity Techniques for Paraphrase Identification

This paper compares statistical technique of paraphrase identification to semantic technique of paraphrase identification. The statistical techniques used for comparison are word set and word-order based methods where as the semantic technique used is the WordNet similarity matrix method described by Stevenson and Fernando in [3].

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing

Studies on the Nature and Chemistry of Sediments and Water of Periyar and Chalakudy Rivers, Kerala, India

The present study is an attempt to address issues related to sediment properties like texture, mineralogy and geochemistry as well as water quality of two important rivers of central Kerala-the Periyar and the Chalakudy rivers. The main objectives of the study are to investigate the textural and mineralogical characteristics as well as transportation and depositional mechanisms of the sediments of Periyar and Chalakudy rivers, to find out the geochemical variability of organic carbon, phosphorus and certain major (Na,K,Ca and Mg) and minor/trace(Mn,Pb,Ni,Cr, and Zn) elements in the bulk sediments and mud fraction of these rivers, to evaluate the status of heavy metal pollution registered in the sediments of these rivers, to assess the physico-chemical characteristics and water quality of Periyar and Chalakudy rivers and to estimate the dissolved nutrient flux through the Periyar and Chalakudy rivers into the receiving coastal waters. The granulometric characteristics as well as statistical parameters of the sediments of Periyar and Chalakudy rivers depend on the flow pattern controlled by the gradient of the terrain. Compared to Periyar, fluctuations in the dispersal of particles are more in Chalakudy river. In Periyar river, the P and Fe in bulk sediments show a positive correlation with C-org, while in Chalakudy river, both the elements are related to THM concentration. In general, C-org, Fe and P Shows an increasing trend downstream. In Periyar river, the P and Fe in bulk sediments show a positive correlation with C-org, while in Chalakudy river, both the elements are related to THM concentration. Among these two rivers, the pollution of water is several fold higher in Periyar river due to influx due to influx of considerable quantity of liquid and solid wastes of industrial/domestic/urban origin. Nutrient analysis reveals 2-3 times increase in N and P during monsoon season whereas SiO2-Si shows a decreasing trend.

Fabrication and Characterization of Dye Sensitized Polymer Films for Holographic Applications

Holographic technology is at the dawn of quick evolution in various new areas including holographic data storage, holographic optical elements, artificial intelligence, optical interconnects, optical correlators, commerce, medical practice, holographic weapon sight, night vision goggles and games etc. One of the major obstacles for the success of holographic technology to a large extent is the lack of suitable recording medium. Compared with other holographic materials such as dichromated gelatin and silver halide emulsions, photopolymers have the great advantage of recording and reading holograms in real time and the spectral sensitivity could be easily shifted to the type of recording laser used by simply changing the sensitizing dye. Also these materials possess characteristics such as good light sensitivity, real time image development, large dynamic range, good optical properties, format flexibility, and low cost. This thesis describes the attempts made to fabricate highly economic photopolymer films for various holographic applications. In the present work, Poly (vinyl alcohol) (PVA) and poly (vinyl chloride) (PVC) are selected as the host polymer matrices and methylene blue (MB) is used as the photosensitizing dye. The films were fabricated using gravity settling method. No chemical treatment or pre/post exposures were applied to the films. As the outcome of the work, photopolymer films with more than 70% efficiency, a permanent recording material which required no fixing process, a reusable recording material etc. were fabricated.

PSWT Based Linear Predictive Coding and Development of a Parallel Multiple Subsequence Structure for DWT Computation

During 1990's the Wavelet Transform emerged as an important signal processing tool with potential applications in time-frequency analysis and non-stationary signal processing.Wavelets have gained popularity in broad range of disciplines like signal/image compression, medical diagnostics, boundary value problems, geophysical signal processing, statistical signal processing,pattern recognition,underwater acoustics etc.In 1993, G. Evangelista introduced the Pitch- synchronous Wavelet Transform, which is particularly suited for pseudo-periodic signal processing.The work presented in this thesis mainly concentrates on two interrelated topics in signal processing,viz. the Wavelet Transform based signal compression and the computation of Discrete Wavelet Transform. A new compression scheme is described in which the Pitch-Synchronous Wavelet Transform technique is combined with the popular linear Predictive Coding method for pseudo-periodic signal processing. Subsequently,A novel Parallel Multiple Subsequence structure is presented for the efficient computation of Wavelet Transform. Case studies also presented to highlight the potential applications.

Modeling and Analysis of Some Heavy Tailed Time Series

The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.

Hydrogeology,Stratigraphy and evolution of the Palaeo-Lagoon (kole land basin ) in the central Kerala coast, India

The present investigation on " Hydrology, stratigraphy, and evolution of the palaeo-lagoon (Koleland basin)in the Central Kerala coast, India" is an integrated approach based on hydrogeological,geophysical,hydrochemical and stratigraphic aspects.A strong scientific data base of the study area is generated using interpretation of well observation and water quality analysis. The salient findings of the present study are given to provide a holistic picture on the hydrogeology (including groundwater resource and its quality),stratigraphy and evolution of the palaeo-lagoon

Fractal based techniques for classification of mammograms and identification of microcalcifications

After skin cancer, breast cancer accounts for the second greatest number of cancer diagnoses in women. Currently the etiologies of breast cancer are unknown, and there is no generally accepted therapy for preventing it. Therefore, the best way to improve the prognosis for breast cancer is early detection and treatment. Computer aided detection systems (CAD) for detecting masses or micro-calcifications in mammograms have already been used and proven to be a potentially powerful tool , so the radiologists are attracted by the effectiveness of clinical application of CAD systems. Fractal geometry is well suited for describing the complex physiological structures that defy the traditional Euclidean geometry, which is based on smooth shapes. The major contribution of this research include the development of • A new fractal feature to accurately classify mammograms into normal and normal (i)With masses (benign or malignant) (ii) with microcalcifications (benign or malignant) • A novel fast fractal modeling method to identify the presence of microcalcifications by fractal modeling of mammograms and then subtracting the modeled image from the original mammogram. The performances of these methods were evaluated using different standard statistical analysis methods. The results obtained indicate that the developed methods are highly beneficial for assisting radiologists in making diagnostic decisions. The mammograms for the study were obtained from the two online databases namely, MIAS (Mammographic Image Analysis Society) and DDSM (Digital Database for Screening Mammography.

A study of the information seeking bebavior of science and technology teachers and researchers of Cocbin University of Science and Technology and University of Kerala in the cbanged library environment

Information communication technology (IC T) has invariably brought about fundamental changes in the way in which libraries gather. preserve and disseminate information. The study was carried out with an aim to estimate and compare the information seeking behaviour (ISB) of the academics of two prominent universities of Kerala in the context of advancements achieved through ICT. The study was motivated by the fast changing scenario of libraries with the proliferation of many high tech products and services. The main purpose of the study was to identify the chief source of information of the academics, and also to examine academics preference upon the form and format of information source. The study also tries to estimate the adequacy of the resources and services currently provided by the libraries.The questionnaire was the central instrument for data collection. An almost census method was adopted for data collection engaging various methods and tools for eliciting data.The total population of the study was 957, out of which questionnaire was distributed to 859 academics. 646 academics responded to the survey, of which 564 of them were sound responses. Data was coded and analysed using Statistical Package for Social Sciences (SPSS) software and also with the help of Microsofl Excel package. Various statistical techniques were engaged to analyse data. A paradigm shift is evident by the fact that academies push themselves towards information in internet i.e. they prefer electronic source to traditional source and the very shift is coupled itself with e-seeking of information. The study reveals that ISB of the academics is influenced priman'ly by personal factors and comparative analysis shows that the ISB ofthc academics is similar in both universities. The productivity of the academics was tested to dig up any relation with respect to their ISB, and it is found that productivity of the academics is extensively related with their ISB. Study also reveals that the users ofthe library are satisfied with the services provided but not with the sources and in conjunction, study also recommends ways and means to improve the existing library system.

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.

Studies on the universal parameters and onset of chaos in dissipative systems

It has become clear over the last few years that many deterministic dynamical systems described by simple but nonlinear equations with only a few variables can behave in an irregular or random fashion. This phenomenon, commonly called deterministic chaos, is essentially due to the fact that we cannot deal with infinitely precise numbers. In these systems trajectories emerging from nearby initial conditions diverge exponentially as time evolves)and therefore)any small error in the initial measurement spreads with time considerably, leading to unpredictable and chaotic behaviour The thesis work is mainly centered on the asymptotic behaviour of nonlinear and nonintegrable dissipative dynamical systems. It is found that completely deterministic nonlinear differential equations describing such systems can exhibit random or chaotic behaviour. Theoretical studies on this chaotic behaviour can enhance our understanding of various phenomena such as turbulence, nonlinear electronic circuits, erratic behaviour of heart and brain, fundamental molecular reactions involving DNA, meteorological phenomena, fluctuations in the cost of materials and so on. Chaos is studied mainly under two different approaches - the nature of the onset of chaos and the statistical description of the chaotic state.

The Systematics, Distribution and Bionomics of Deep sea fishes beyond depth 200m along the South west coast of India

Reducing fishing pressure in coastal waters is the need of the day in the Indian marine fisheries sector of the country which is fast changing from a mere vocational activity to a capital intensive industry. It requires continuous monitoring of the resource exploitation through a scientifically acceptable methodology, data on production of each species stock, the number and characteristics of the fishing gears of the fleet, various biological characteristics of each stock, the impact of fishing on the environment and the role of fishery—independent on availability and abundance. Besides this, there are issues relating to capabilities in stock assessment, taxonomy research, biodiversity, conservation and fisheries management. Generation of reliable data base over a fixed time frame, their analysis and interpretation are necessary before drawing conclusions on the stock size, maximum sustainable yield, maximum economic yield and to further implement various fishing regulatory measures. India being a signatory to several treaties and conventions, is obliged to carry out assessments of the exploited stocks and manage them at sustainable levels. Besides, the nation is bound by its obligation of protein food security to people and livelihood security to those engaged in marine fishing related activities. Also, there are regional variabilities in fishing technology and fishery resources. All these make it mandatory for India to continue and strengthen its marine capture fisheries research in general and deep sea fisheries in particular. Against this background, an attempt is made to strengthen the deep sea fish biodiversity and also to generate data on the distribution, abundance, catch per unit effort of fishery resources available beyond 200 m in the EEZ of southwest coast ofIndia and also unravel some of the aspects of life history traits of potentially important non conventional fish species inhabiting in the depth beyond 200 m. This study was carried out as part of the Project on Stock Assessment and Biology of Deep Sea Fishes of Indian EEZ (MoES, Govt. of India).

FEATURE SELECTION AND COMPARISON OF TWO NAÏVE BAYES CLASSIFICATION METHODS IN THE CONTEXT OF SPAM FILTERING

Treating e-mail filtering as a binary text classification problem, researchers have applied several statistical learning algorithms to email corpora with promising results. This paper examines the performance of a Naive Bayes classifier using different approaches to feature selection and tokenization on different email corpora

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

Design, Development and Realization of Quadratic Volterra Filters for Selected Applications

The basic concepts of digital signal processing are taught to the students in engineering and science. The focus of the course is on linear, time invariant systems. The question as to what happens when the system is governed by a quadratic or cubic equation remains unanswered in the vast majority of literature on signal processing. Light has been shed on this problem when John V Mathews and Giovanni L Sicuranza published the book Polynomial Signal Processing. This book opened up an unseen vista of polynomial systems for signal and image processing. The book presented the theory and implementations of both adaptive and non-adaptive FIR and IIR quadratic systems which offer improved performance than conventional linear systems. The theory of quadratic systems presents a pristine and virgin area of research that offers computationally intensive work. Once the area of research is selected, the next issue is the choice of the software tool to carry out the work. Conventional languages like C and C++ are easily eliminated as they are not interpreted and lack good quality plotting libraries. MATLAB is proved to be very slow and so do SCILAB and Octave. The search for a language for scientific computing that was as fast as C, but with a good quality plotting library, ended up in Python, a distant relative of LISP. It proved to be ideal for scientific computing. An account of the use of Python, its scientific computing package scipy and the plotting library pylab is given in the appendix Initially, work is focused on designing predictors that exploit the polynomial nonlinearities inherent in speech generation mechanisms. Soon, the work got diverted into medical image processing which offered more potential to exploit by the use of quadratic methods. The major focus in this area is on quadratic edge detection methods for retinal images and fingerprints as well as de-noising raw MRI signals