Spatial and Temporal Variability of some Meteorological Parameters over Tropical Indian Ocean

The objective of the present study is to understand the spatial and temporal variability of sea surface temperature(SST), precipitable water, zonal and meridional components of wind stress over the tropical Indian Ocean to understand the different scales of variability of these features of Indian Ocean. Empirical Orthogonal Function (EOF) and wavelet analysis techniques are utilized to understand the standing oscillations and multi scale oscillations respectively. The study has been carried out over Indian Ocean and South Indian Ocean. For the present study, NCEP/NCAR(National Center for Environmental Prediction National Center for Atmospheric Research) reanalyzed daily fields of sea surface temperature, zonal and meridional surface wind components and precipitable water amount during 1960-1998 are used. The principle of EOF analysis and the methodology used for the analysis of spatial and temporal variance modes.

Stability of Random Sums and Extremes

This study is about the stability of random sums and extremes.The difficulty in finding exact sampling distributions resulted in considerable problems of computing probabilities concerning the sums that involve a large number of terms.Functions of sample observations that are natural interest other than the sum,are the extremes,that is , the minimum and the maximum of the observations.Extreme value distributions also arise in problems like the study of size effect on material strengths,the reliability of parallel and series systems made up of large number of components,record values and assessing the levels of air pollution.It may be noticed that the theories of sums and extremes are mutually connected.For instance,in the search for asymptotic normality of sums ,it is assumed that at least the variance of the population is finite.In such cases the contributions of the extremes to the sum of independent and identically distributed(i.i.d) r.vs is negligible.

Fabrication and Characterization of All-Fiber Components for Optical Access Networks

This Thesis deals with the fabrication and characterization of novel all-fiber components for access networks. All fiber components offer distinctive advantages due to low forward and backward losses, epoxy free optical path and high power handling. A novel fabrication method for monolithic 1x4 couplers, which are vital components in distributed passive optical networks, is realized. The fabrication method differs from conventional structures with a symmetric coupling profile and hence offers ultra wideband performance and easy process control. New structure for 1x4 couplers, by fusing five fibers is proposed to achieve high uniformity, which gives equivalent uniformity performance to 1x4 planar lightwave splitters, isolation in fused fiber WDM is improved with integration of long period gratings. Packaging techniques of fused couplers are analyzed for long term stability.

Characterization of Probability Distributions by Variance Bounds and its Applications

Department of Statistics, Cochin University of Science and Technology

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.

Vocational Higher Secondary Education in Kerala: A Status Study of Students, Pass Outs and Training Components

This study analyses the socio-economic backgrounds and entrepreneurial profiles of the students and pass outs of the Vocational Higher Secondary Education in Kerala and the academic achievements of the Vocational Higher Secondary students and pass outs in Kerala in terms of their performance in the examinations. The study also analyses the quality and availability of the various training and support facilities of the Vocational Higher Secondary Schools in Kerala, nature and rate of employment and higher studies among the pass outs of the Vocational Higher Secondary Education in Kerala and the awareness of students, pass outs, teachers and principals regarding the goals and objectives, mode of implementation, apprenticeship training and higher study and employment opportunities of the programme of the Vocational Higher Secondary Education in Kerala.

Study of the Oceanic Heat Budget Components over the Arabian Sea during the Formation and Evolution of Super Cyclone, Gonu

Oceans play a vital role in the global climate system. They absorb the incoming solar energy and redistribute the energy through horizontal and vertical transports. In this context it is important to investigate the variation of heat budget components during the formation of a low-pressure system. In 2007, the monsoon onset was on 28th May. A well- marked low-pressure area was formed in the eastern Arabian Sea after the onset and it further developed into a cyclone. We have analysed the heat budget components during different stages of the cyclone. The data used for the computation of heat budget components is Objectively Analyzed air-sea flux data obtained from WHOI (Woods Hole Oceanographic Institution) project. Its horizontal resolution is 1° × 1°. Over the low-pressure area, the latent heat flux was 180 Wm−2. It increased to a maximum value of 210 Wm−2 on 1st June 2007, on which the system was intensified into a cyclone (Gonu) with latent heat flux values ranging from 200 to 250 Wm−2. It sharply decreased after the passage of cyclone. The high value of latent heat flux is attributed to the latent heat release due to the cyclone by the formation of clouds. Long wave radiation flux is decreased sharply from 100 Wm−2 to 30 Wm−2 when the low-pressure system intensified into a cyclone. The decrease in long wave radiation flux is due to the presence of clouds. Net heat flux also decreases sharply to −200 Wm−2 on 1st June 2007. After the passage, the flux value increased to normal value (150 Wm−2) within one day. A sharp increase in the sensible heat flux value (20 Wm−2) is observed on 1st June 2007 and it decreased there- after. Short wave radiation flux decreased from 300 Wm−2 to 90 Wm−2 during the intensification on 1st June 2007. Over this region, short wave radiation flux sharply increased to higher value soon after the passage of the cyclone.

Behaviour of mrigal (cirrihinus mrigala) meat components during the washing process in the preparation of surimi

To elucidate the effect of washing, on flesh components, mrigal flesh was washed through one, two and three washing cycles. Washing resulted in absorption of water (1-3%) and loss of fat (49%). 35% loss of soluble protein (SP) was noticed in the first washing itself and the loss is almost equally shared by the sarcoplasmic (18% of SP) and the myofibrillar proteins (17% of SP). The subsequent washings removed small portions of water-soluble sarcoplasmic proteins resulting in the concentration of myofibrillar proteins. 73% of the soluble protein was retained in the flesh after three washing cycles. The protein had undergone marginal conformational changes as reflected by the decrease in the actomyosin Ca super(2+) ATPase activity The rheological properties of the washed flesh were,however, significantly better than that of the unwashed mince

Artificial neural network modeling for surface roughness prediction in cylindrical grinding of Al‐SiCp metal matrix composites and ANOVA analysis

Metal matrix composites (MMC) having aluminium (Al) in the matrix phase and silicon carbide particles (SiCp) in reinforcement phase, ie Al‐SiCp type MMC, have gained popularity in the re‐cent past. In this competitive age, manufacturing industries strive to produce superior quality products at reasonable price. This is possible by achieving higher productivity while performing machining at optimum combinations of process variables. The low weight and high strength MMC are found suitable for variety of components